# Flobotics > Healthcare revenue cycle automation. These documents are generated from the website's visible page content. The canonical HTML page is the primary source. They do not grant agent permissions or guarantee indexing, rankings, or AI citations. --- # RCM Automation Team & Values | About Us Canonical: https://www.flobotics.io/about-us --- [Home](https://www.flobotics.io/)/Company About us # We Automate the Impossible At Flobotics we specialize in revenue cycle management (RCM) automation for U.S. healthcare. We skip the BS, speak from the heart, and stay focused on real outcomes. No generic bots here. [Book a 30-minute call →](https://www.flobotics.io/book)[Meet the team](#team) Our story ## Flobotics emerged out of two humble ideas: Karl, CTO Karl, our CTO, wanted to build a trustworthy automation company rooted in kaizen ideology – reliable, precise, and built without shortcuts. Filip, CEO Filip, our CEO, wanted to create a community of like-minded people who treat their work as a lifelong adventure, not a corporate chore. Out of those two forces – quality and human drive – Flobotics came to life. We set out to prove that automation can be done differently: with care, curiosity, and a bit of fun along the way. Today, that same mindset powers every project we take on. High-quality automation, built by happy people. Our core value ## Every Second Counts We believe AI automation should empower – not replace people. That’s why our RCM solutions always target tedious, repetitive tasks that cost time. So you can reinvest the most precious asset we all have where it matters the most. Our numbers ## The proof is in the numbers: 1,000+Automations delivered. 10+Industries automated. $10M+Annual client savings. ROIIn weeks, not months. [See all our work →](https://www.flobotics.io/case-studies) Our team ## Meet the People You Can Call Founder & CTO ### Karl The ‘no-BS’ CTO who loves breaking bad processes. [LinkedIn →](https://www.linkedin.com/in/karl-mielnicki/) Founder & CEO ### Filip RCM Automation Leader Obsessed with ROI. [LinkedIn →](https://www.linkedin.com/in/filip-nasiadko-8399a993/) Head of Delivery ### Krzysztof Keeps projects moving and clients sane. [LinkedIn →](https://www.linkedin.com/in/krzysztof-szwed/) Head of AI ### Bart Turns chaos into clean workflows that bring results. [LinkedIn →](https://www.linkedin.com/in/bart-teodorczuk-a85365127/) Insight ## Here's what they write about us: Below you'll find industry news, interviews, and articles that mention Flobotics. [ August 07, 2025 ### We saved $2 Million from a 50% improvement for PRMG using UiPath! PRMG loan processing automation case study - see how UiPath RPA delivered a 6:1 ROI and $1.2M in labor savings over 36 months for this mortgage lender. Read more →](https://www.flobotics.io/blog/flobotics-prmg-loan-processing-rpa-automation) [ March 18, 2025 ### Forbes named us "#3 Best Polish Startup of 2025"! Flobotics named #3 on Forbes Poland's Best Polish Startups of 2025 (Service Company category) - recognized for scaling RPA and AI services in the US. Read more →](https://www.flobotics.io/blog/flobotics-forbes-polish-best-startups-2025) [ April 05, 2026 ### We are a "Top Workday Implementation Partner for 2026" according to SuperbCompanies! Flobotics named a Top Workday Implementation Partner for 2026 by SuperbCompanies, ranked among 49 vetted firms for delivery and optimization results. Read more →](https://www.flobotics.io/blog/flobotics-superbcompanies-top-workday-implementation-company-2026) [ January 29, 2026 ### Top Software Development Company in Indiana? Yes! According to DesignRush Flobotics named a top Indiana software development company by DesignRush - see why we made the list among leading US automation and RPA firms. Read more →](https://www.flobotics.io/blog/flobotics-designrush-top-software-company-indiana) [ February 19, 2026 ### #5 Globally in GoodFirms’ Top RPA Companies for 2026! Flobotics ranked #5 globally among 857 vetted RPA companies by GoodFirms in 2026, recognized for non-invasive automation and verified client results. Read more →](https://www.flobotics.io/blog/flobotics-goodfirms-top-rpa-companies-2026) [ January 26, 2026 ### We Are Among the Top Business Consulting Companies in the USA for 2026! Flobotics named a top business consulting company in the USA for 2026 by Selectedfirms - recognized for business growth and strategy expertise. Read more →](https://www.flobotics.io/blog/flobotics-top-business-consulting-companies-2026) [Our promise ## You don’t trust us yet. Give us 30 days to change that. We assess five processes for free, then a dedicated team works with you for 30 days. If you cancel in that time, you pay nothing. Read our promise →](https://www.flobotics.io/our-promise) [Who writes our content? ## Meet Our Editorial Team The people who build and run our automations write about them. Every article is signed by a person you can call. Editorial team →](https://www.flobotics.io/our-editorial-team) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # AWS Connect Health Canonical: https://www.flobotics.io/aws-connect-health --- [Home](https://www.flobotics.io/)/Lab/AWS Connect Health FLOBOTICSLABTechnology briefing AWS contact center · AI voice agents # Patient calls, answered – 24/7. A HIPAA-eligible contact center on Amazon Connect, wired into your EHR and payer rails. Eligibility, intake, reminders, payer hold-times – handled by an AI voice agent that doesn’t go on PTO. [Book a 30-minute call →](https://www.flobotics.io/book)[Learn more](#learn-more) Built onAWS Connect - Integrates with my system? Yes, Epic, Meditech & more. - Setup time? Weeks, not months. - Secure? 100% HIPAA-compliant. What do we automate? ## Every Call. Every Message. VoiceIVR ### Patient intake & eligibility on the phone. The Connect IVR captures member ID and DOB, fires a real-time 270/271 eligibility check against the payer, and reads back coverage, copay, and remaining deductible to the patient. When something’s off – coverage lapsed, wrong plan, prior auth needed – the call warm-transfers to a human with the full context already on screen. [Learn more →](https://www.flobotics.io/agents/eligibility-check-automation) Voice + SMSFront office ### Appointment scheduling & no-show recovery. The agent books, reschedules, and cancels by voice or chat — writing straight to your EHR slot. Reminders go out at the right cadence on the right channel for the right patient cohort. [Learn more →](https://www.flobotics.io/rcm-automation) Outbound voiceRCM ### Payer status calls, without the hold time. The agent dials the payer IVR, navigates the menu, waits on hold, and reads back the prior-auth or claim status the moment a human is needed. [Learn more →](https://www.flobotics.io/rcm-automation) Voice + chatClinical ### Clinical triage that routes to the right human. Symptom intake on voice or chat, urgency scored against your protocol, warm transfer to the right nurse-line queue with the conversation summary already in front of them. [Learn more →](https://www.flobotics.io/rcm-automation) Results ## Agentic AI automation is a natural step in RCM evolution. And we have several proofs of this. [ Client caseDenials Management $50K+saved in one month, with 90% less manual rework for the RCM team. ### $50K+ Saved in 1 Month | AI Agent For Denials Management Read the case study → ](https://www.flobotics.io/case-studies/50k-saved-in-1-month-ai-agent-for-denials-management) [ Client caseClaims Management 70%faster claim turnaround for out-of-network reimbursement. ### 70% Faster Claim Turnaround Time (CTT) Read the case study → ](https://www.flobotics.io/case-studies/70-faster-claim-turnaround-time-ctt-claim-management-automation) [ Claims Management 98%reduction in manual claim prep. Up to 250 hours per week of manual RCM work removed. ### 98% Reduction in Manual Claim Prep Read the case study → ](https://www.flobotics.io/case-studies/98-reduction-in-manual-claim-prep-claims-management-automation) [All case studies](https://www.flobotics.io/case-studies) AI agents ## Wait, there is more? Yes! We also specialize in RCM process automation. [AI agent ### Denials Management Automation Hunts and classifies denials early to stop them from aging out. →](https://www.flobotics.io/agents/denials-management-automation)[AI agent ### Claims Management Automation Tracks claims and flags denials before they cost you. →](https://www.flobotics.io/agents/claims-management-automation)[AI agent ### Prior Authorization Automation Automate your PA process. No API required. →](https://www.flobotics.io/agents/prior-authorization-automation) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Expert insights on AI Automation in U.S. Healthcare | Blog Canonical: https://www.flobotics.io/blog --- [Home](https://www.flobotics.io/)/Articles Articles # Everything about RCM automation From failed bots to million-dollar recoveries – stories, frameworks, and lessons from the field. [ RCMHealthcare ## RCM Automation for FQHCs FQHC revenue cycle management: see how automation cuts administrative burden and restores cash flow for federally qualified health centers in 2026. Filip NasiadkoAugust 14, 2026 ](https://www.flobotics.io/blog/rcm-automation-for-fqhcs) AllAI 49Claims 3Denials 2Eligibility 10Healthcare 92RCM 78RPA 88Search articles [ RCM ### RCM Automation for Multi-Specialty Physician Groups RCM automation for multi-specialty physician groups: why generic RPA raises cost to collect, and what specialty-aware automation does differently. Jędrzej SzymulaAugust 18, 2026 ](https://www.flobotics.io/blog/rcm-automation-for-multi-specialty-physician-group)[ RCMHealthcare ### RCM Automation for FQHCs FQHC revenue cycle management: see how automation cuts administrative burden and restores cash flow for federally qualified health centers in 2026. Filip NasiadkoAugust 14, 2026 ](https://www.flobotics.io/blog/rcm-automation-for-fqhcs)[ AIHealthcare ### DAX Copilot in RCM DAX Copilot in RCM: it halves documentation time, but your revenue cycle still leaks. See where it stops and how to close the gap. Bart TeodorczukAugust 11, 2026 ](https://www.flobotics.io/blog/dax-copilot-in-rcm)[ HealthcareRCM ### Oracle Health (Cerner) Automation | 2026 Oracle Cerner RCM automation: Oracle Health now runs two EHRs in parallel. See what that means for revenue cycle automation in 2026. Bart TeodorczukAugust 03, 2026 ](https://www.flobotics.io/blog/oracle-health-cerner-rcm-automation)[ AIRCMHealthcare ### How Agentic AI Automates Payer Portals Without an API Agentic AI payer portals: CMS's API mandate doesn't land until 2027 and won't cover every payer. See how agentic AI automates portals today. Jędrzej SzymulaJuly 27, 2026 ](https://www.flobotics.io/blog/agentic-ai-payer-portals-without-api)[ HealthcareRCMAI ### Why Community Hospitals Need More Than an API? Meditech Example Community hospital automation: MEDITECH's FHIR APIs solve clinical interoperability, not payer portals. See what hospitals can automate today. Filip NasiadkoJuly 23, 2026 ](https://www.flobotics.io/blog/why-community-hospitals-need-more-than-an-api)[ HealthcareRCMClaims ### What Is Medical Billing? The Complete 101 Guide What is medical billing? A 101 guide to the 10-step billing cycle, CPT vs. ICD-10 codes, claim denials, and how automation is changing RCM. Jędrzej SzymulaJuly 22, 2026 ](https://www.flobotics.io/blog/what-is-medical-billing)[ AIDenialsRCM ### The State of Claim Denials in U.S. Healthcare Claim denials in U.S. healthcare: 2025 data shows denial rates kept rising. See where, why, and by how much - and what RCM teams can do in 2026. Karl MielnickiJuly 13, 2026 ](https://www.flobotics.io/blog/claim-denials-in-healthcare-usa)[ AI ### Facts About Google Antigravity | Over 30 Questions Answered Google Antigravity facts: 30+ questions answered on the IDE, its Easter eggs, tricks, and limits - everything you need to know in one guide. Jędrzej SzymulaJuly 03, 2026 ](https://www.flobotics.io/blog/30-facts-about-google-antigravity) No articles match. Clear filters [1](https://www.flobotics.io/blog)[2](https://www.flobotics.io/blog/page/2)[3](https://www.flobotics.io/blog/page/3)[4](https://www.flobotics.io/blog/page/4)[5](https://www.flobotics.io/blog/page/5)[6](https://www.flobotics.io/blog/page/6)[7](https://www.flobotics.io/blog/page/7)[8](https://www.flobotics.io/blog/page/8)[9](https://www.flobotics.io/blog/page/9)[10](https://www.flobotics.io/blog/page/10)[11](https://www.flobotics.io/blog/page/11)[12](https://www.flobotics.io/blog/page/12)[13](https://www.flobotics.io/blog/page/13)[14](https://www.flobotics.io/blog/page/14)[15](https://www.flobotics.io/blog/page/15)[16](https://www.flobotics.io/blog/page/16)[17](https://www.flobotics.io/blog/page/17)[18](https://www.flobotics.io/blog/page/18)[19](https://www.flobotics.io/blog/page/19)[20](https://www.flobotics.io/blog/page/20)[21](https://www.flobotics.io/blog/page/21) --- # Business Process Automation | Flobotics Canonical: https://www.flobotics.io/business-process-automation --- [Home](https://www.flobotics.io/)/[What we do](https://www.flobotics.io/what-we-do)/Business process automation Business process automation # Business Process Automation RPAAutomationAI agents Healthcare is our main focus today, but we’ve automated work in more than 10 industries, including manufacturing, energy, finance, tax, travel and telecom. We learn your process, build the automation in the systems you already use, and keep it running. [Book a 30-minute call →](https://www.flobotics.io/book)[See the results](#success-stories) UiPath Gold Partner - Certified UiPath developers - Only the licenses you need - Python, APIs and AI where they fit better We pick the tools that fitUiPath, Python, AI or an API, depending on the process. You pay only for the licenses you needWe size licenses to the work your robots actually do. We start where the return is clearWe pick processes with enough volume to pay off. What we automate ## What we’ve automated outside healthcare SAP ### Manufacturing & food processing For one of the world’s largest sugar producers, we automate SAP work in finance, sales, logistics and quality: vendor self-invoicing, pallet settlement, blocked orders and lab reports. [Read more →](https://www.flobotics.io/blog/sap-automation) Billing & switching ### Energy & utilities For Axpo, we automated billing and customer switching in Switzerland and Poland, including annual purchase summaries for about 1,500 partners and more than 600 invoice transactions a day. [Read more →](https://www.flobotics.io/blog/use-cases-rpa-in-energy) Invoices & orders ### HR & accounting For Cohen & Company, robots create and import invoices and purchase orders and read invoice data from a mailbox, saving about 320 hours of manual work a month. [Read more →](https://www.flobotics.io/blog/payroll-process-rpa) IRS & tax filings ### Finance & tax For a debt-relief program, two robots pulled client data from the IRS website and filed tax returns, saving 2,818 hours of manual work in one week. [Read more →](https://www.flobotics.io/case-studies/mystic-river-consulting-automation) Devices & SIM cards ### Telecom & GPS tracking For Global-View and GPS nVISION, robots activate devices, SIM cards and customer accounts across several applications, and deactivate unpaid subscriptions. [Read more →](https://www.flobotics.io/case-studies/global-view-automation) Website monitoring ### Travel For eSky, a bot checks airline websites every day for luggage policy changes and alerts the team only when something changes. [Read more →](https://www.flobotics.io/case-studies/esky-luggage-tracking-automation) Documents & orders ### Logistics & transport We can automate shipping documents, transport invoices, order changes and customer notifications, and check that the data matches across systems. [Read more →](https://www.flobotics.io/blog/warehouse-automation-process) Claims & policies ### Insurance We can automate claims intake, policy checks, correspondence and billing in older insurance systems. Unclear cases go to your team. [Read more →](https://www.flobotics.io/blog/automation-technologies) [Book a 30-minute call →](https://www.flobotics.io/book) Case studies ## Results outside healthcare [ Non-healthcare 100%ROI within two months. The first bot was live in eight days. ### Airline policy monitoring for eSky Read the case study → ](https://www.flobotics.io/case-studies/esky-luggage-tracking-automation) [ Client caseNon-healthcare 600xfaster account activation: about 10 minutes down to 1 second. ### Device and account activation for Global-View Read the case study → ](https://www.flobotics.io/case-studies/global-view-automation) [ Client caseNon-healthcare 4,685hours of manual work saved a year in SAP. ### SAP automation for a large sugar producer Read the case study → ](https://www.flobotics.io/case-studies/sugar-producer-automation) [ Client caseNon-healthcare 2,818hours of manual work saved in one week, worth over $100,000 in estimated labor cost. ### IRS data and tax filings for a debt-relief program Read the case study → ](https://www.flobotics.io/case-studies/mystic-river-consulting-automation) [ Client caseNon-healthcare 4xfaster account activation: about 16 minutes down to 4. ### Activation and deactivation for GPS nVISION Read the case study → ](https://www.flobotics.io/case-studies/gps-nvision-automation) [ Client caseNon-healthcare 27 days → 1 dayto send annual purchase summaries to about 1,500 partners. ### Billing and switching automation for Axpo Read the case study → ](https://www.flobotics.io/case-studies/axpo-automation) [See all our work →](https://www.flobotics.io/case-studies) Healthcare ## Our main focus is healthcare revenue cycle work. We automate eligibility checks, prior authorizations, claims and denials for labs, practices and billing companies. [Custom RCM automation →](https://www.flobotics.io/rcm-automation) [AI agent→ ### Denials Management Automation Finds denials, works out why each one happened, and prepares the correction or appeal. View agent →](https://www.flobotics.io/agents/denials-management-automation) [AI agent→ ### Claims Management Automation Checks claim status and flags the claims that are stuck or denied. View agent →](https://www.flobotics.io/agents/claims-management-automation) [AI agent→ ### Prior Authorization Automation Prepares and submits prior authorization requests and tracks them until the payer answers. View agent →](https://www.flobotics.io/agents/prior-authorization-automation) [AI agent→ ### Eligibility Check Automation Checks coverage and benefits before the visit and saves the result. Unclear cases go to your staff. View agent →](https://www.flobotics.io/agents/eligibility-check-automation) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Real cases. Real numbers. Real partners | Case Studies Canonical: https://www.flobotics.io/case-studies --- [Home](https://www.flobotics.io/)/Client Results Client Results # Real stories. Real impact. See how healthcare providers cut costs, reduced denials, and automated RCM workflows with our AI Agents – stories, frameworks, and lessons from the field. [100%ROI in just 23 days from eligibility automation together with Denial Hunter, with $180,000 worth of savings after year one.PTCoA](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks)[98%Reduction in manual claim prep. See how an automated EHR-to-claim data pipeline removed up to 250 hours per week of manual RCM work.Gentem Health](https://www.flobotics.io/case-studies/98-reduction-in-manual-claim-prep-claims-management-automation)[Up to 80%Higher throughput in RCM. See how we automated PathGroup’s systems and connected it with a custom laboratory information system data exchange.PathGroup](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation)[8+FTEs saved. Learn how agentic AI freed 8+ FTEs for a multi-state pain management network and its RCM team.PTCoA](https://www.flobotics.io/case-studies/85-faster-submissions-8-ftes-saved-prior-authorization-automation) AllBusiness process automation (Non-healthcare)Claims ManagementDenials ManagementEHR IntegrationEligibility ChecksPre-Auths [ Denials Management Up to 80%higher throughput in RCM, with a custom laboratory information system data exchange. ## Up to 80% Higher Throughput in RCM PathGroup’s case shows how automated denial handling across athenahealth and PathSys reduced processing time from ~10 minutes to ~55 seconds, cleared backlogs to near-zero, and scaled to ~300 automated resubmissions per day. Read the case study → ](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation)[ Eligibility Checks 100%ROI in 23 days from eligibility automation plus Denial Hunter, with $180,000 in savings after year one. ## 100% ROI in just 23 days. We Automated Eligibility Checks! PTCoA’s case shows eligibility checks automated to ~40 seconds each, saving about 3 FTEs. Together with Denial Hunter, the work reached 100% ROI in 23 days, with $180K in projected first-year savings. Read the case study → ](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks)[ Claims Management 98%reduction in manual claim prep. Up to 250 hours per week of manual RCM work removed. ## 98% Reduction in Manual Claim Prep Gentem’s case demonstrates how an agentic AI automation layer strengthens the entire claims lifecycle without adding headcount or forcing changes to existing EHRs. Read the case study → ](https://www.flobotics.io/case-studies/98-reduction-in-manual-claim-prep-claims-management-automation)[ Pre-Auths 8+FTEs saved. Agentic AI standardized prior authorization submissions across payer portals. ## 85% Faster Submissions, 8+ FTEs Saved This case demonstrates how a fully autonomous AI agent standardized prior authorization submissions across payer portals, eliminating inconsistencies in a large U.S. pain management network. Read the case study → ](https://www.flobotics.io/case-studies/85-faster-submissions-8-ftes-saved-prior-authorization-automation)[ Client casePre-Auths -90%time to submit prior authorization packets, from the LIMS to the payer portals. ## 90% Faster Packet Submissions This case shows how prior authorization automation eliminated manual data entry for a high-volume genetic diagnostic lab, accelerating patient turnaround and improving competitive advantage without replacing existing systems. Read the case study → ](https://www.flobotics.io/case-studies/90-faster-packet-submissions-prior-authorization-automation)[ Client caseEligibility Checks +50%capacity restored, with the monthly eligibility backlog cut in half. ## Halving Monthly Backlog This case shows how automated eligibility verification across multiple portals reduces processing time by 90%, cuts manual work by over 90%, and increases verification speed from ~5 minutes to ~1 minute per case. Read the case study → ](https://www.flobotics.io/case-studies/halving-monthly-backlog---eligibility-automation-in-action)[ Client caseClaims Management 70%faster claim turnaround for out-of-network reimbursement. ## 70% Faster Claim Turnaround Time (CTT) SuperBill’s case shows the power of document-to-claim automation. Our AI agent cut Claim Turnaround Time (CTT) by ~70%, from ~24 hours to ~7 hours. Read the case study → ](https://www.flobotics.io/case-studies/70-faster-claim-turnaround-time-ctt-claim-management-automation)[ Client caseDenials Management $50K+saved in one month, with 90% less manual rework for the RCM team. ## $50K+ Saved in 1 Month | AI Agent For Denials Management This case demonstrates how AI-driven denial automation eliminated ~90% of manual rework, reduced claim processing time from ~6 minutes to ~30 seconds, cleared 80% of a 3,000-record backlog in three weeks, and delivered $90K+ in savings with 500+ hours saved monthly. Read the case study → ](https://www.flobotics.io/case-studies/50k-saved-in-1-month-ai-agent-for-denials-management)[ Client caseBusiness process automation 300,000%ROI from one simple RPA procedure. ## 300,000% ROI for T Bank | Finance & Banking This case represents about $100,000,000 worth of applications and $5,000,000 in the organization’s revenue. Our client saved over 200 hours of human labor, allowing business owners all over the USA to apply for over 1,000 loans. The entire development took about 8 hours! Read the case study → ](https://www.flobotics.io/case-studies/t-bank-automation)[ Business process automation 2 FTEssaved with end-to-end invoice processing. ## 2 FTEs saved via full invoice processing automation case study | Cohen & Company This case study shows how robotic process automation streamlines accounting and saves 2 FTEs. Read the case study → ](https://www.flobotics.io/case-studies/cohen-rpa-in-accounting-automation-case-study)[ Client caseBusiness process automation ## Canada Satellite | Hundreds of SIM cards & healthy CRM Canada Satellite provides satellite services and devices, including satellite phones, satellite TV, and satellite internet. With offshore branches such as Africa Satellite, Asia Satellite, Australia Satellite, Europe Satellite, and American Satellite, the company operates globally and supports customers across multiple regions and markets. We implemented an RPA-based automation layer connecting the CRM and shop backend, leveraging the fact that both prepaid and postpaid processes were rule-based with a shared starting point in the CRM and a shared endpoint in the shop system. Read the case study → ](https://www.flobotics.io/case-studies/canada-satelite-automation)[ EHR Integration 10,000+transactions automated every month. ## 10,000+ transactions automated monthly DocPlanner is the world’s biggest healthcare platform (and the market leader in 13 countries), serving 90M patients and 280M healthcare professionals and processing over 22M appointments booked via the DocPlanner app monthly. UiPath created a simple PoC of one automation and recommended Flobotics as a development partner. That's when we stepped in. Read the case study → ](https://www.flobotics.io/case-studies/docplanner)[ Client caseBusiness process automation $100,000+in estimated labor cost savings. ## $100K+ saved in a few days The company needed to automate two highly labor-intensive processes: pulling client data from the IRS website and filing tax returns. Each step took approximately 45 minutes per client when done manually, and access to the IRS portal was limited to a single set of credentials, preventing parallel work. So we delivered. Read the case study → ](https://www.flobotics.io/case-studies/mystic-river-consulting-automation)[ Client caseBusiness process automation $186,000of profit in year one. ## $186,000 of profit in year one This case study shows how our RPA solutions helped Axpo deal with rapid growth. Read the case study → ](https://www.flobotics.io/case-studies/axpo-automation)[ Client caseBusiness process automation 4,685hours of manual labor saved per year. ## 4,685 hours of manual labor saved This collaboration became one of Flobotics’ longest and most successful partnerships. Initial automation backlogs were cleared, and ongoing process discovery workshops identified new SAP bottlenecks. The client’s Center of Excellence was optimized by gradually shifting from attended to unattended bots, allowing teams to fully leverage RPA across SAP-driven workflows. Read the case study → ](https://www.flobotics.io/case-studies/sugar-producer-automation)[ Client caseBusiness process automation 4xfaster account activation: about 16 minutes down to 4. ## 4x faster account activation This case study shows how RPA boosts efficiency in the telecom industry. Read the case study → ](https://www.flobotics.io/case-studies/gps-nvision-automation)[ Client caseBusiness process automation 600xfaster account activation: about 10 minutes down to 1 second. ## 600x faster account activation Global View case study shows that the full implementation, including testing, can be completed in under three weeks by a single UiPath developer. Read the case study → ](https://www.flobotics.io/case-studies/global-view-automation)[ Business process automation 100%ROI within two months. ## 100% ROI within two months eSky case study shows how we turned a tedious manual process into a fully automated pipeline with 100% ROI in two months. Read the case study → ](https://www.flobotics.io/case-studies/esky-luggage-tracking-automation)[ Business process automation ## Custom algorithm In this case study, you’ll read about the algorithm we built for ePhi, an industrial cleaning services company from France. It captures, organizes and shares satellite images with consistent scale and definition, at predictable costs. Read the case study → ](https://www.flobotics.io/case-studies/custom-algorithm-for-ephi) No case studies match this filter. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Estimate your ROI](https://www.flobotics.io/roi-calculator) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # ChatGPT for Healthcare Canonical: https://www.flobotics.io/chat-gpt-for-healthcare --- [Home](https://www.flobotics.io/)/Lab/ChatGPT for Healthcare FLOBOTICSLABTechnology briefing OpenAI for healthcare # Let GPT-5.2 handle the paperwork HIPAA-compliant AI that handles scribing, triage, coding, and research – so your team can focus on patients, not paperwork. [Book a 30-minute call →](https://www.flobotics.io/book)[Learn more](#learn-more) Built onChatGPT for Healthcare - Integrates with my system? Yes, Epic, Meditech & more. - Setup time? Weeks, not months. - Secure? 100% HIPAA-compliant. Solutions for healthcare ## Less screens. More medicine. Clinical documentationEHR ### Visit ends. Note is done. GPT-5.2 transcribes the encounter and structures the SOAP note before your physician reaches the next room. [Explore scribing →](https://www.flobotics.io/rcm-automation) Patient supportCommunication ### Patients get answers at 2am. AI triage agent handles intake, symptom parsing, and escalation — 24/7, across every channel. [Learn more →](https://www.flobotics.io/rcm-automation) Medical researchData synthesis ### Literature review in hours, not weeks. GPT-5.2 parses unstructured clinical notes, extracts biomarkers, and surfaces trial-protocol insights. What used to take months takes days. Ship more trials, faster. [Calculate ROI →](https://www.flobotics.io/roi-calculator) Operational efficiencyRCM ### Coding errors down. Revenue up. AI reads the clinical note and suggests ICD-10 and CPT codes before your coder touches the chart. [Learn more →](https://www.flobotics.io/agents/claims-management-automation) Results ## Agentic AI automation is a natural step in RCM evolution. And we have several proofs of this. [ Client caseDenials Management $50K+saved in one month, with 90% less manual rework for the RCM team. ### $50K+ Saved in 1 Month | AI Agent For Denials Management Read the case study → ](https://www.flobotics.io/case-studies/50k-saved-in-1-month-ai-agent-for-denials-management) [ Client caseClaims Management 70%faster claim turnaround for out-of-network reimbursement. ### 70% Faster Claim Turnaround Time (CTT) Read the case study → ](https://www.flobotics.io/case-studies/70-faster-claim-turnaround-time-ctt-claim-management-automation) [ Claims Management 98%reduction in manual claim prep. Up to 250 hours per week of manual RCM work removed. ### 98% Reduction in Manual Claim Prep Read the case study → ](https://www.flobotics.io/case-studies/98-reduction-in-manual-claim-prep-claims-management-automation) [All case studies](https://www.flobotics.io/case-studies) AI agents ## Wait, there is more? Yes! We specialize in RCM process automation. [AI agent ### Denials Management Automation Hunts and classifies denials early to stop them from aging out. →](https://www.flobotics.io/agents/denials-management-automation)[AI agent ### Claims Management Automation Tracks claims and flags denials before they cost you. →](https://www.flobotics.io/agents/claims-management-automation)[AI agent ### Prior Authorization Automation Automate your PA process. No API required. →](https://www.flobotics.io/agents/prior-authorization-automation) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Claude for Healthcare Automation | Flobotics Canonical: https://www.flobotics.io/claude-for-healthcare-automation --- [Home](https://www.flobotics.io/)/Lab/Claude for Healthcare FLOBOTICSLABTechnology briefing AI · Automation · AI agents # Claude for Healthcare Anthropic built the FHIR and prior auth skills. Your full patient record, payer policy, and prior auth packet processed in one pass, configured to your organization’s policies. Claude will unlock your capacity – let us implement it. [Book a 30-minute call →](https://www.flobotics.io/book)[What we automate](#learn-more) Claude for healthcare End-to-end stackToken efficiencyModel Advisory - Prior authorization, ICD-10, CPT. Full HIPAA compliance. - Epic, Cerner, HL7, FHIR. No API needed, no replatforming. - You gain a vetted automation partner. We focus on 100% ROI. What do we automate? ## Every Process. Every System. Prior Authorization ### Prior Auth Automation Built on HIPAA-ready infrastructure with safety guardrails designed for healthcare. Claude validates provider NPI via NPI Registry, checks CPT and ICD-10 codes, pulls coverage requirements from the CMS Coverage Database, and cross-references clinical criteria against patient records — tracing every answer back to its source so you verify before you approve. Work that took hours of manual cross-referencing, done in seconds. Claims & Appeals ### Insurance Claims Appeals Claude understands the complexity of payer rules, medical necessity criteria, and coverage policy. It reviews your denial reasons, cross-references clinical records against policy requirements, identifies every documentation gap, and drafts a comprehensive appeal with source-cited clinical evidence for each denial code. Answers traced back to the source — so your team reviews decisions, not disasters. Patient Triage ### Care Coordination & Triage Connected to Function Health, HealthEx, Apple Health, and Android Health Connect — Claude reviews patient portal messages with full health record context, flags urgent clinical issues for immediate attention, drafts responses to routine questions, and routes billing, referral, and scheduling messages to the right team. Safety guardrails ensure clinical issues are never triaged down when they should escalate up. Clinical Documentation ### Ambient Scribing Claude understands the complexity of medical coding and clinical decisions. From a visit recording, it generates the full visit summary, HPI, physical exam, ICD-10 assessment, and care plan — cross-referenced against PubMed clinical guidelines and the patient’s chart. Flags medication sensitivities, E/M level mismatches, and billing gaps before anything reaches the chart. 47 seconds from a 12-minute recording. Medical Coding & RCM ### ICD-10, CPT & HCC Coding Claude connects directly to CMS Coverage Database, ICD-10, NPI Registry, and PubMed — reviewing every code against clinical records, payer rules, and coverage policy before submission. It shows you where every answer came from so your coders can verify, not guess. Work that took days now takes minutes. Fewer errors entering the pipeline means fewer denials coming back. [Book a 30-minute call →](https://www.flobotics.io/book)[Read more about Claude for Healthcare](https://www.flobotics.io/blog/claude-for-healthcare) Free ebook · 2026 edition ## Claude in Healthcare — From Demo to Production Three deployment patterns, HIPAA-eligible architecture, and production-ready ROI benchmarks. A practical playbook for RCM teams. [Download the free ebook (PDF) →](https://www.flobotics.io/documents/Claude-in-Healthcare-From-Demo-to-Production.pdf) Results ## Agentic AI automation is a natural step in RCM evolution. And we have several proofs of this. [ Client caseDenials Management $50K+saved in one month, with 90% less manual rework for the RCM team. ### $50K+ Saved in 1 Month | AI Agent For Denials Management Read the case study → ](https://www.flobotics.io/case-studies/50k-saved-in-1-month-ai-agent-for-denials-management) [ Client caseClaims Management 70%faster claim turnaround for out-of-network reimbursement. ### 70% Faster Claim Turnaround Time (CTT) Read the case study → ](https://www.flobotics.io/case-studies/70-faster-claim-turnaround-time-ctt-claim-management-automation) [ Claims Management 98%reduction in manual claim prep. Up to 250 hours per week of manual RCM work removed. ### 98% Reduction in Manual Claim Prep Read the case study → ](https://www.flobotics.io/case-studies/98-reduction-in-manual-claim-prep-claims-management-automation) [All case studies](https://www.flobotics.io/case-studies) What clients say ## Partners who worked with us I admire their ability to meet and exceed our requirements and expectations. Peter GilbertCIO at Ayr Farmers Mutual Insurance Thanks to Flobotics, we have increased our sales conversion rate by 3%. The team communicates effectively and is proactive both in the product discovery and development stages. I love the business drive of the team as well as their flexibility and readiness to address all the needs. Kamil WalczakProduct Lead, DocPlanner I am thrilled with the collaboration so far and looking forward to expanding it in the future! Ewa Stokowska-RogalaProduct Implementation Specialist, eSky.com AI agents ## Wait, there is more? Already in healthcare? We go deeper — end-to-end RCM automation is our core. [AI agent ### Denials Management Automation Hunts and classifies denials early to stop them from aging out. →](https://www.flobotics.io/agents/denials-management-automation)[AI agent ### Claims Management Automation Tracks claims and flags denials before they cost you. →](https://www.flobotics.io/agents/claims-management-automation)[AI agent ### Prior Authorization Automation Automate your PA process. No API required. →](https://www.flobotics.io/agents/prior-authorization-automation)[AI agent ### Eligibility Check Automation 24/7 patient coverage verification - all without human supervision →](https://www.flobotics.io/agents/eligibility-check-automation) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Experts in AI Automation for RCM in Healthcare | Contact Canonical: https://www.flobotics.io/contact --- [Home](https://www.flobotics.io/)/[Company](https://www.flobotics.io/about-us)/Contact Contact us # Let’s talk about your process. No sales pitch. Within the first 15 minutes, you’ll know whether automation makes sense for you, or not. Karl or BartOur CTO or our Head of AI. You talk to one of them, not a call screener. [Book a 30-minute call →](https://www.flobotics.io/book) 100% ROIin 23 days at Pain Treatment Centers of America 1,000+automations delivered What happens after you book ## From a 30-minute call to an exact price - 30 minutes ### A call You talk to Karl or Bart. Within 15 minutes, you’ll know whether ChatGPT or Claude is enough, whether it’s a project, or whether it isn’t worth automating. - 30–60 minutes ### A walkthrough You show us the process on a screen share: the systems, the steps and the exceptions. - 30 minutes ### An exact price We review the process and come back with an exact price, including maintenance. - - - - - - Prefer to write? ## Send us a message Tell us about your project or how we can help you. First Name Last Name Work Email Company Phone number (optional) What brings you here? Choose one I want to automate a process in my organization I represent a vendor or want to propose a partnership I’m looking for a job or internship Something else This form goes to our sales team. For partnerships, vendor offers, jobs and internships, please email [info@flobotics.io](mailto:info@flobotics.io). Organization type (optional) Choose one Lab Practice or provider network Billing company Health tech Payer Other Message I agree to our friendly [Privacy policy](https://www.flobotics.io/privacy-policy) Send message → ExampleFB ToKarl Mielnicki, Flobotics FromDana Brooks, Lakeshore Clinic Hi Karl, our billing team checks eligibility in four payer portals by hand. It takes most of their morning. Can this be automated? Dana In their words ## What working with us is like. After we implemented their bots, tasks that took us 30 minutes to do only took a few minutes. That was a great improvement. The team quickly implemented feedback and delivered a solution that met all our needs. Rasheed ColeHead of IT at RedPeg Marketing I appreciate their understanding and the way they grasp the needs of our business. Their overall knowledge, beyond the RPA, has been great as well. They also provide a high quality of security to protect the confidentiality we require. Rosemary AngstenCOO, DART Chart Systems I admire their ability to meet and exceed our requirements and expectations. Peter GilbertCIO at Ayr Farmers Mutual Insurance They were easy to get in contact with and the whole collaboration went smoothly. The automation has saved us a considerable amount of time. Everyone in the team confirmed it works fantastically and that it’s freed them up a lot of time. Manny AkintayoCo-founder & CTO at Gentem Health --- # RCM Automation Terms & Metrics | Glossary Canonical: https://www.flobotics.io/glossary --- [Home](https://www.flobotics.io/)/[Resources](https://www.flobotics.io/resources)/Glossary Glossary # RCM automation terms & metrics From “CARC” and “CTT” to “DOS” and “LOS” – an RCM glossary that keeps everyone on the same page. [A](#letter-a)[C](#letter-c)[D](#letter-d)[E](#letter-e)[G](#letter-g)[H](#letter-h)[I](#letter-i)[L](#letter-l)[M](#letter-m)[N](#letter-n)[P](#letter-p)[R](#letter-r)[T](#letter-t)[U](#letter-u)[V](#letter-v) AllAI Automation 5Healthcare 4RCM Metrics 9RCM Terms 20Search terms ## Agentic AI / AI Agents AI Automation The next generation of AI systems. Defined as autonomous AI capable of independently executing complex, multi-step RCM workflows – such as investigating a denial, selecting an appeal strategy, and drafting the appeal letter – by using tools and making decisions without continuous human oversight [Read the article →](https://www.flobotics.io/blog/agentic-ai) ## Appeal RCM Terms The formal process initiated by the provider to challenge and overturn a denial [Read the article →](https://www.flobotics.io/blog/denials-appeal-explanation) ## Charge Capture RCM Terms The conversion of clinical services rendered and documented in the patient's chart into corresponding billable financial charges [Read the article →](https://www.flobotics.io/blog/charge-capture-explanation) ## Claim Scrubbing RCM Terms An automated quality control check performed on a claim before electronic submission to detect and correct errors [Read the article →](https://www.flobotics.io/blog/claim-scrubbing-explanation) ## Claim Turnaround Time (CTT) RCM Metrics The average number of days required for an insurer to process a claim and for the resulting payment to be received and posted [Read the article →](https://www.flobotics.io/blog/claim-turnaround-time-ctt-explanation) ## Clean Claim Rate (CCR) RCM Metrics The percentage of claims accepted by the insurance payer upon initial submission without requiring any corrections, rejections, or manual intervention [Read the article →](https://www.flobotics.io/blog/clean-claim-rate-ccr-explanation) ## Clinical Documentation Integrity (CDI) RCM Terms The process of ensuring the patient's medical chart accurately and completely reflects the full scope of services and severity of illness [Read the article →](https://www.flobotics.io/blog/clinical-documentation-integrity-cdi-explanation) ## Contractual Adjustment (Allowance) RCM Terms The mandatory write-off amount representing the difference between the provider's billed charge and the allowed amount set by the insurance contract [Read the article →](https://www.flobotics.io/blog/contractual-adjustment-allowance-explanation) ## Cost to Collect (CTC) RCM Metrics The total operational cost incurred by a practice or hospital to successfully collect payment for services rendered [Read the article →](https://www.flobotics.io/blog/cost-to-collect-ctc-explanation) ## Credit Balance Resolution RCM Terms The mandatory process of identifying and refunding overpayments (excess money collected) to the original payer or patient to resolve a financial liability [Read the article →](https://www.flobotics.io/blog/credit-balance-resolution-explanation) ## Days in Accounts Receivable (A/R) - DAR RCM Metrics The average number of days it takes a provider to collect the total outstanding payment for services rendered [Read the article →](https://www.flobotics.io/blog/days-in-accounts-receivable-dar-explanation) ## Denial RCM Terms A formal refusal by a payer to remit payment on a submitted claim due to specific issues (e.g., technical errors, lack of medical necessity) [Read the article →](https://www.flobotics.io/blog/denials-appeal-explanation) ## Denial Management RCM Terms The structured process of investigating, resolving, appealing, and preventing insurance claim denials and rejections [Read the article →](https://www.flobotics.io/blog/denials-management-explanation) ## Digital Patient Engagement Healthcare Front-end digital tools – including patient portals and mobile applications – used for scheduling, bill payment, and financial counseling, directly impacting Patient Access efficiency and patient payment adherence [Read the article →](https://www.flobotics.io/blog/digital-patient-engagement-explanation) ## Eligibility Verification RCM Terms Real-time confirmation of a patient's current insurance status, coverage, benefits, and financial responsibilities prior to service [Read the article →](https://www.flobotics.io/blog/eligibility-verification-explanation) ## Generative AI (GenAI) AI Automation AI models used in RCM to generate natural-language content, such as patient-facing financial explanations or customized denial appeal narratives, tailored to payer requirements and clinical context. [Read the article →](https://www.flobotics.io/blog/genai-in-healthcare) ## Health Insurance Portability and Accountability Act (HIPAA) Healthcare Federal law setting standards for the security, privacy, and electronic transmission of sensitive healthcare information [Read the article →](https://www.flobotics.io/blog/health-insurance-portability-and-accountability-act-hipaa-explanation) ## Initial Denial Percentage RCM Metrics The percentage of submitted claims that are formally rejected by payers upon their first attempt at processing [Read the article →](https://www.flobotics.io/blog/initial-denial-percentage-explanation) ## Intelligent Document Processing (IDP) AI Automation The use of AI to extract structured data from unstructured RCM documents – such as scanned EOBs, faxes, and clinical notes – and automatically route that data into processes like Payment Posting and Charge Capture [Read the article →](https://www.flobotics.io/blog/intelligent-document-processing-idp-explanation) ## Laboratory Information Management System (LIMS) Healthcare It is software designed to manage and track samples, experiments, and results to streamline laboratory operations [Read the article →](https://www.flobotics.io/blog/laboratory-information-management-system-lims) ## Medical Coding RCM Terms The translation of clinical diagnoses (ICD-10) and procedures (CPT/HCPCS) into standardized alphanumeric codes for claims processing [Read the article →](https://www.flobotics.io/blog/medical-coding) ## Medical Necessity RCM Terms The determination that a health service is essential for diagnosis or treatment based on professional standards, which dictates payer coverage [Read the article →](https://www.flobotics.io/blog/medical-necessity-explanation) ## Net Collection Rate (NCR) RCM Metrics The percentage of collectible revenue (the maximum allowed amount defined by payer contracts) that is actually secured by the provider [Read the article →](https://www.flobotics.io/blog/net-collection-rate-ncr) ## NPS (Net Promoter Score) RCM Metrics NPS stands for Net Promoter Score, a metric that measures customer loyalty by asking customers a single question: "How likely is it that you would recommend this company/product/service to a friend or colleague?" on a scale of 0 to 10. Based on the scores, customers are categorized as promoters (9-10), passives (7-8), or detractors (0-6). The final score, ranging from -100 to +100, is calculated by subtracting the percentage of detractors from the percentage of promoters [Read the article →](https://www.flobotics.io/blog/nps-net-promoter-score-explanation) ## Patient Access RCM Terms Front-end RCM processes including scheduling, registration, eligibility verification, and obtaining prior authorization [Read the article →](https://www.flobotics.io/blog/patient-access-explanation) ## Patient Statement RCM Terms The final financial document sent to the patient detailing services, insurance payments, and the remaining outstanding balance owed by the patient [Read the article →](https://www.flobotics.io/blog/patient-statement-explanation) ## Payment Posting (Cash Posting) RCM Terms The process of recording payments received from payers and patients against claims to reconcile accounts and identify denials [Read the article →](https://www.flobotics.io/blog/payment-posting-cash-posting-explanation) ## Posting Correspondence RCM Terms Official documentation, typically the Electronic Remittance Advice (ERA) or Explanation of Benefits (EOB), used to detail claim payments and status [Read the article →](https://www.flobotics.io/blog/posting-correspondence-explanation) ## Predictive Analytics RCM Terms The application of data models to forecast RCM outcomes, including identifying claims likely to be denied or predicting patient propensity to pay, enabling proactive intervention by RCM teams [Read the article →](https://www.flobotics.io/blog/predictive-analytics-explanation) ## Prior Authorization (Pre-Auth) RCM Terms The formal process required by many payers to secure official approval for specific treatments or services before they are provided [Read the article →](https://www.flobotics.io/blog/prior-authorization-pre-auth-explanation) ## Protected Health Information (PHI) Healthcare Individually identifiable health information (including clinical and demographic data) that must be secured under HIPAA [Read the article →](https://www.flobotics.io/blog/protected-health-information-phi) ## RCM Automation AI Automation This is the overarching concept. It involves using technology (RPA, AI, ML) to automate repetitive RCM tasks, such as eligibility checks and payment posting [Read the article →](https://www.flobotics.io/blog/rcm-automation-healthcare) ## Reimbursements RCM Terms Payments providers receive from third-party payers (insurers or government entities) for covered medical services delivered [Read the article →](https://www.flobotics.io/blog/reimbursements-explanation) ## Revenue Cycle Management (RCM) RCM Terms The continuous process managing and optimizing financial flows from initial patient scheduling to final account resolution [Read the article →](https://www.flobotics.io/blog/revenue-cycle-management) ## Robotic Process Automation (RPA) AI Automation A critical component of RCM Automation. Define it as software robots that mimic human actions to handle high-volume, rules-based tasks (e.g., bulk data entry, prior authorization status checks) [Read the article →](https://www.flobotics.io/blog/robotic-process-automation) ## Turnaround Time (TAT) RCM Metrics It is the total time it takes to complete a specific process from start to finish. It's a key performance metric used in many industries to measure efficiency, from shipping and banking to IT support and medical labs [Read the article →](https://www.flobotics.io/blog/turnaround-time-tat-explanation) ## Underpayment Recovery RCM Terms The process of identifying and pursuing payment discrepancies where the actual payment is less than the amount defined in the contractual agreement [Read the article →](https://www.flobotics.io/blog/underpayment-recovery-explanation) ## Value-Based Care (VBC) RCM Metrics A reimbursement model that shifts RCM priorities by rewarding providers for quality and outcomes rather than service volume, replacing traditional fee-for-service incentives and increasing reporting and data complexity [Read the article →](https://www.flobotics.io/blog/value-based-care-vbc-explanation) No terms match. --- # Google Antigravity in Healthcare Canonical: https://www.flobotics.io/google-antigravity-in-healthcare --- [Home](https://www.flobotics.io/)/Lab/Google Antigravity in Healthcare FLOBOTICSLABTechnology briefing Google Antigravity for healthcare # Healthcare AI inside your Google Cloud Ship HIPAA-ready agentic workflows on Google’s Antigravity platform — clinical documentation, RCM, prior auth — production-grade agents running on Gemini 3, inside your Google Cloud perimeter. [Book a 30-minute call →](https://www.flobotics.io/book)[Meet the agents](https://www.flobotics.io/rcm-automation) Built onGoogle Antigravity 2.0 - Integrates with my system? Yes, Epic, Meditech & more. - Setup time? Weeks, not months. - Secure? 100% HIPAA-compliant. What do we build? ## Every workflow. One agent platform. We scope, build, and operate Antigravity agents for the parts of healthcare that eat the most staff time — documentation, coding, prior auth, and payer calls. Clinical documentationEHR ### Note ready before the next room. An Antigravity agent listens to the encounter, structures the SOAP note, and pushes a draft to the EHR before the physician reaches the next patient. The clinician opens the chart, reviews, and signs. No after-hours typing, no dictation backlog, no copy-paste from a separate scribe tool. We wire the agent directly into your existing EHR API — no workflow change required on the clinical side. [View flow →](https://www.flobotics.io/rcm-automation) - Encounter-to-note in under 90s - Gemini 3 medical transcription - EHR write-back, any flavor - 50%+ less charting time RCM automationCoding ### Codes suggested. Denials pre-empted. The agent reads the clinical note, extracts ICD-10 and CPT codes, and flags denial risk before the claim ever reaches the clearinghouse. Coders review a pre-populated suggestion instead of reading the note from scratch. At one billing company that meant coders handling 2.4× more charts per day with the same headcount — and denial rate dropped 40% in the first quarter. [View flow →](https://www.flobotics.io/agents/claims-management-automation) - ICD-10 & CPT extraction - Denial-risk scoring pre-submission - Clearinghouse-ready output - Full audit trail Prior authPayer portals ### PA packets built and submitted. No payer API. The Antigravity agent extracts clinical documentation, assembles a payer-specific packet, submits through the portal, and tracks status — Aetna, UHC, BCBS, all of them. No payer API. No EDI setup. The agent navigates the portal the same way your staff does today, except it runs in parallel across every open PA at once. We’ve seen 90% faster packet submissions and zero additional headcount in the same quarter. [View flow →](https://www.flobotics.io/agents/prior-authorization-automation) - Auto packet assembly - Portal submission, no API - Status tracking & follow-up - Clinical doc extraction How we deploy ## From signed BAA to live agents in 3–6 weeks. One specific workflow first. Real data, real users, off-ramps at every phase. We’d rather kill a pilot at week three than ship something that breaks your billing cycle. - Phase 01~ 1 week ### BAA & GCP setup Execute BAA, configure VPC-scoped Antigravity workspace, set data-residency policy. Your PHI never leaves your Google Cloud project. - Phase 02~ 1 week ### Workflow audit Sit with the people doing the work today. Map volume, exceptions, EHR integration points, payer mix. Output: a written build plan with ROI estimate. - Phase 032–4 weeks ### Build & tune Agents built on Antigravity 2.0, tuned on your real documents, tested against your actual EHR and payer portals. Nothing ships until containment numbers are solid. - Phase 04Week 5+ ### Deploy & iterate Go live on one workflow. Instrument, measure, expand by department behind feature flags. Flobotics keeps operating the agents after launch. Results ## Agentic AI automation is a natural step in RCM evolution. And we have several proofs of this. [ Client caseDenials Management $50K+saved in one month, with 90% less manual rework for the RCM team. ### $50K+ Saved in 1 Month | AI Agent For Denials Management Read the case study → ](https://www.flobotics.io/case-studies/50k-saved-in-1-month-ai-agent-for-denials-management) [ Client caseClaims Management 70%faster claim turnaround for out-of-network reimbursement. ### 70% Faster Claim Turnaround Time (CTT) Read the case study → ](https://www.flobotics.io/case-studies/70-faster-claim-turnaround-time-ctt-claim-management-automation) [ Claims Management 98%reduction in manual claim prep. Up to 250 hours per week of manual RCM work removed. ### 98% Reduction in Manual Claim Prep Read the case study → ](https://www.flobotics.io/case-studies/98-reduction-in-manual-claim-prep-claims-management-automation) [All case studies](https://www.flobotics.io/case-studies) AI agents ## Wait, there is more? Yes! We specialize in RCM process automation. [AI agent ### Denials Management Automation Hunts and classifies denials early to stop them from aging out. →](https://www.flobotics.io/agents/denials-management-automation)[AI agent ### Claims Management Automation Tracks claims and flags denials before they cost you. →](https://www.flobotics.io/agents/claims-management-automation)[AI agent ### Prior Authorization Automation Automate your PA process. No API required. →](https://www.flobotics.io/agents/prior-authorization-automation) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # AI Automation for Healthcare RCM | Flobotics Canonical: https://www.flobotics.io/ --- AI automation for healthcare operations # We automate the work between your systems. We build AI agents and automations that connect your EHR, LIS, billing systems, and payer portals, eliminating repetitive work without replacing the software your team already relies on. [Book a 30-minute call →](https://www.flobotics.io/book) [See client results →](https://www.flobotics.io/case-studies) CompliantPartnerExperts[Clutch★★★★★5.0](https://clutch.co/profile/flobotics-ai-automation-rcm-healthcare) 03/14/2026 08:42FROM: NORTHSIDE FAMILY MEDICINEP. 1/3 SYNTHETIC NO PHI Referral and prior authorization request Please complete all fields. Incomplete requests will be returned. Patient nameJordan A. Sample Date of birth04/12/1968 Member IDXWJ48210937 Health planLakeshore Health Plan PPO Service requestedMRI lumbar spine without contrast CPT72148 ICD-10M54.16 Radiculopathy, lumbar Ordering providerDr. R. Example · NPI 1234567893 Pt failed 6 wks PT. Please expedite. Date 03/14/26 Prior authorization agentrun 4,812 Fax received08:42:10 8 fields read8/8 Payer rules checkedauth required Exception? Goes to a personnone today Submitted to payer08:43:44 ReadExtractRulesSubmit Submitted to the payer no human review needed1 min 34 s ## Every minute of busywork is a minute someone waits. A patient waits for coverage to be confirmed. A claim waits to be resolved. And while they wait, your team is still copying information between digital systems, checking statuses by hand, and fixing the same errors. Here’s what our clients measured after automating that work. ~5 minutes~1 min per patient eligibility verification, across multiple payer portals [RCM team · case study](https://www.flobotics.io/case-studies/halving-monthly-backlog---eligibility-automation-in-action) ~10 minutes~55 sec per denial across athenahealth and PathSys, ~300 resubmissions a day [PathGroup · case study](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation) ~6 minutes~30 sec per denied claim, with 80% of a 3,000-record backlog cleared in three weeks [Denials agent · case study](https://www.flobotics.io/case-studies/50k-saved-in-1-month-ai-agent-for-denials-management) manual checks23 days to 100% ROI from eligibility automation and Denial Hunter. Checks now take ~40 seconds and save ~3 FTEs [PTCoA · case study](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) Who we help ## Built around the way you work. [ 03/18/2026 06:12RIVERBEND CLINICP. 1/1 Laboratory requisition Tests orderedCMP · Lipid panel · HbA1c CPT80053 · 80061 ICD-10E11.9 Insurance ID MISSING · REQUESTED ### Diagnostic & pathology laboratories Requisitions, eligibility, prior authorization and denials across the LIS and payer portals, so accessioning and billing staff work on what needs judgment. ~10 min → ~55 sper denial at PathGroup Laboratories → ](https://www.flobotics.io/who-we-help/laboratories) [ 03/14/2026 08:44PORTAL SUBMISSIONREF 55012 Eligibility & benefits PayerLakeshore PPO StatusActive Service typeInterventional pain ResultVerified · saved to PM ### Specialty practices & provider networks Eligibility, prior authorization and claims for practices and networks, running across payer portals without new APIs. 100% ROI in 23 dayseligibility + Denial Hunter at PTCoA Healthcare providers → ](https://www.flobotics.io/who-we-help/providers) [ 835 · 03/21/2026LAKESHORE HEALTH PLANCLM 26-0048812 Remittance advice · denial Billed$1,840.00 Paid$0.00 ReasonCO-197 Precertification absent Next actionAuth attached · resubmitted ### RCM & medical billing companies Claim prep, payment tracking and denial work for RCM companies and in-house billing teams, from EHR data to the clearinghouse. 98% lessmanual claim prep at Gentem Health Revenue cycle teams → ](https://www.flobotics.io/who-we-help/rcm-billing-companies) [ 03/25/2026 14:03NETWORK OPERATIONSP. 1/2 Provider data change form Provider NPI1234567893 ChangeNew practice address Effective04/01/2026 RoutedDirectory update queued ### Payers & health plans Administrative intake, correspondence and provider data. We automate the administrative steps. Clinical decisions always stay with people. Administrative onlya person reviews every clinical item Payers → ](https://www.flobotics.io/who-we-help/payers) Other industries Finance & bankingLogisticsEnergyInsuranceHR & accounting [Business process automation →](https://www.flobotics.io/business-process-automation) What we do ## One process or a whole automation team. We help you decide what to automate, choose the right technology, and build and maintain the solution. [01 ### Build AI and automation AI agents, document processing, and workflow automation built around your existing systems and business rules. Explore AI and automation →](https://www.flobotics.io/ai-automation) [02 ### Connect your systems and data API integrations, data pipelines, and shared data layers that support reporting, analytics, and automation. Explore data and integrations →](https://www.flobotics.io/data-integrations) [03 ### Add a dedicated automation team Developers and analysts who plan and deliver your automation roadmap as an extension of your team. Explore dedicated teams →](https://www.flobotics.io/dedicated-teams) [04 ### Maintenance & Support Monitoring, maintenance, and improvements that keep your automations working as systems, requirements, and volumes change. Explore maintenance and support →](https://www.flobotics.io/maintenance-support) Built with the right tools for your systemsAI agents · UiPath · Python · RPA · API integrations [Already using UiPath? Development, maintenance, licensing, and help scaling your automation program.Explore UiPath services →](https://www.flobotics.io/uipath-services) Follow a workflow ## How does this actually work? Follow one prior authorization request through documents, your systems and human review. Click a step to stop there and look closer. - 01A request arrives - 02The automation reads it - 03It checks the rules - 04A person confirms what is unclear - 05It submits and saves DocumentsYour systemsHuman review A. Rivera · MRI request 01 · DocumentsFax received FromLakeshore Orthopedics Pages3 Received09:12 02 · DocumentsFields read PatientA. Rivera Member IDLKP 4410 2291 ServiceMRI, lumbar spine CPT · ICD-1072148 · M54.16 03 · Your systemsPayer rules checked PayerLakeshore PPO AuthorizationRequired for 72148 Must attachPhysical therapy history 05 · Your systemsSubmitted and saved Payer portalSubmitted · ref PA-55821 EHRConfirmation attached to the order NextStatus check scheduled 04 · Human reviewNote confirmed Handwritten"Failed 6 wks PT" WhyHard to read ResultConfirmed by your staff Step 1 of 5. A prior authorization request arrives by fax, with the order and a clinical note. Step 2 of 5. It reads the patient, insurance, service and codes. Each value is linked to the page it came from. Step 3 of 5. It checks the request against the payer's rules and yours: is authorization needed, and what has to be attached? Step 4 of 5. The physical therapy history is handwritten and hard to read, so a person confirms it before anything is sent. Clear requests skip this step. Step 5 of 5. It submits the request in the payer portal, attaches the documents and saves the confirmation in your EHR. The payer still makes the decision. Request complete.Request submittedEHR updatedFollow-up scheduled Pause [See this at a real client: the PTCoA prior authorization case study →](https://www.flobotics.io/case-studies/85-faster-submissions-8-ftes-saved-prior-authorization-automation) Our promise ## You don’t trust us yet. Give us 30 days to change that. Hiring a company you haven’t worked with before is a risk. We take on the financial part of that risk, so you can judge us by our work before you pay anything. - Free ### We find five processes worth automating We work with your team to find five processes that are worth automating. For each one, we map the steps, check the numbers, estimate the return and recommend the technology. If automating something won’t pay off, we tell you. You don’t pay for any of this. - Six-month agreement ### You get a dedicated team When we agree on the five processes, we sign a six-month agreement. Then our team builds the automations for you. - 30 days ### You decide after 30 days The 30 days start when our team starts work. If you continue, we invoice at the end of each month. If you cancel within the 30 days, you pay nothing. If you cancel in the first 30 days, you pay $0 We don’t invoice the first month, there is no cancellation fee, and you owe nothing for the remaining five months. The only thing you’ve spent is your team’s time. You can cancel for any reason, for example: - Don’t like our work?Cancel - A black cat crossed your path?Cancel - Don’t like Karl’s mustache?Cancel You don’t need to convince us to keep your business. We need to convince you. [Let’s find your five processes →](https://www.flobotics.io/book)[Read our full promise](https://www.flobotics.io/our-promise) Client Results ## Numbers our clients measured. Real deployments, before and after. 1,000+ automations delivered across 10+ industries. [ Eligibility Checks 100%ROI in 23 days from eligibility automation plus Denial Hunter, with $180,000 in savings after year one. ### 100% ROI in just 23 days. We Automated Eligibility Checks! Read the case study → ](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) [ Claims Management 98%reduction in manual claim prep. Up to 250 hours per week of manual RCM work removed. ### 98% Reduction in Manual Claim Prep | Claims Management Automation Read the case study → ](https://www.flobotics.io/case-studies/98-reduction-in-manual-claim-prep-claims-management-automation) [ Pre-Auths 8+FTEs saved. Agentic AI standardized prior authorization submissions across payer portals. ### 85% Faster Submissions, 8+ FTEs Saved | Prior Authorization Automation Read the case study → ](https://www.flobotics.io/case-studies/85-faster-submissions-8-ftes-saved-prior-authorization-automation) [ Denials Management Up to 80%higher throughput in RCM, with a custom laboratory information system data exchange. ### Up to 80% Higher Throughput in RCM – Denials Management Automation Read the case study → ](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation) 1,000+automations delivered 10+industries automated $10M+annual client savings Weeksto ROI, not months [Book a 30-minute call →](https://www.flobotics.io/book)[See all our work →](https://www.flobotics.io/case-studies) In their words ## What working with us is like. They were easy to get in contact with and the whole collaboration went smoothly. The automation has saved us a considerable amount of time. Everyone in the team confirmed it works fantastically and that it’s freed them up a lot of time. Manny AkintayoCo-founder & CTO at Gentem Health Thanks to Flobotics, we have increased our sales conversion rate by 3%. The team communicates effectively and is proactive both in the product discovery and development stages. Kamil WalczakProduct Lead, DocPlanner I appreciate their understanding and the way they grasp the needs of our business. Their overall knowledge, beyond the RPA, has been great as well. They also provide a high quality of security to protect the confidentiality we require. Rosemary AngstenCOO, DART Chart Systems Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Flobotics | Library of Sources Canonical: https://www.flobotics.io/library-of-trusted-sources-rcm --- [Home](https://www.flobotics.io/)/[Resources](https://www.flobotics.io/resources)/Library of sources RCM reports & insights # Trusted Sources We Relay On Download the original files or save time with our editorial team reviews in a digestable format. [Browse the library →](#all-sources)[Our editorial team](https://www.flobotics.io/our-editorial-team) ## Our Latest Review: [](https://www.flobotics.io/images/imported/4d55d5b54b1f44fc6493795d.pdf) ### [AHA's Intelligent Revenue Cycle Management Market Scan | 2026 Edition](https://www.flobotics.io/images/imported/4d55d5b54b1f44fc6493795d.pdf) This report includes case studies featuring health systems that have pursued such a holistic approach to improving their revenue cycle performance. [Download PDF →](https://www.flobotics.io/images/imported/4d55d5b54b1f44fc6493795d.pdf) Library ## All sources Market reports, benchmark data and our own reviews, in one place. - [](https://www.flobotics.io/images/imported/state-of-rcm-automation-2026-report.pdf) PDF ### [Flobotics State of RCM Automation | 2026 Edition](https://www.flobotics.io/images/imported/state-of-rcm-automation-2026-report.pdf) Our review of what changed in U.S. revenue cycle in 2026: legal and regulatory changes, finance and payment shifts and automation tech trends, with evidence grades, 61 references and our four bets for 2027. [Download PDF →](https://www.flobotics.io/images/imported/state-of-rcm-automation-2026-report.pdf) - [](https://www.flobotics.io/images/imported/4d55d5b54b1f44fc6493795d.pdf) PDF ### [AHA's Intelligent Revenue Cycle Management Market Scan | 2026 Edition](https://www.flobotics.io/images/imported/4d55d5b54b1f44fc6493795d.pdf) This report includes case studies featuring health systems that have pursued such a holistic approach to improving their revenue cycle performance. [Download PDF →](https://www.flobotics.io/images/imported/4d55d5b54b1f44fc6493795d.pdf) - [](https://www.flobotics.io/images/imported/b856b251a48095b71f597ba2.pdf) PDF ### [ACHE’s 2026–2028 Strategic Plan](https://www.flobotics.io/images/imported/b856b251a48095b71f597ba2.pdf) ACHE’s Strategic Plan is meant to support revenue cycle management leaders in driving positive change and impact. [Download PDF →](https://www.flobotics.io/images/imported/b856b251a48095b71f597ba2.pdf) - [](https://marketing.auxis.com/hubfs/2025%20PDFs/2025%20Nearshore%20Trends%20Healthcare%20Leaders%20Turn%20to%20Latin%20America%20for%20Shared%20Services%20&%20Outsourcing%20.pdf) External PDF ### [Auxis Healthcare Revenue Cycle Management Trends | 2026 Edition](https://marketing.auxis.com/hubfs/2025%20PDFs/2025%20Nearshore%20Trends%20Healthcare%20Leaders%20Turn%20to%20Latin%20America%20for%20Shared%20Services%20&%20Outsourcing%20.pdf) Last year Auxis report on RCM trends clearly states that healthcare leaders turn to latin america for shared services & outsourcing. [Read our review →](https://marketing.auxis.com/hubfs/2025%20PDFs/2025%20Nearshore%20Trends%20Healthcare%20Leaders%20Turn%20to%20Latin%20America%20for%20Shared%20Services%20&%20Outsourcing%20.pdf) - [](https://www.flobotics.io/images/imported/983154c6ed0dd593dd431c35.pdf) PDF ### [BlackBook's Research on AI in RCM Managed Services | 2026 Edition](https://www.flobotics.io/images/imported/983154c6ed0dd593dd431c35.pdf) March 2026 edition of BlackBook Research Insights edition focuses on the AI-driven RCM managed services and preserves the most recent benchmark scoring dataset. [Download PDF →](https://www.flobotics.io/images/imported/983154c6ed0dd593dd431c35.pdf) - [](https://www.flobotics.io/images/imported/9768658b6eaac541b8c3eced.pdf) PDF ### [XiFin's Payor Denial Impact Report | 2025 Edition](https://www.flobotics.io/images/imported/9768658b6eaac541b8c3eced.pdf) Based on over 20 million XiFin customer claims - this report is a great source of data on denial trends, appeal outcomes, and AI influence across clinical laboratories, molecular diagnostics, and anatomic pathology. [Download PDF →](https://www.flobotics.io/images/imported/9768658b6eaac541b8c3eced.pdf) - [](https://www.flobotics.io/images/imported/729e5df88b11462459384d70.pdf) PDF ### [Flobotics Review of Claude in Healthcare | 2026](https://www.flobotics.io/images/imported/729e5df88b11462459384d70.pdf) Check our 2026 business analysis of Anthropic's native connectors, through RCM automation, to a single-source-of-truth data warehouse inside a diagnostic labs. [Download PDF →](https://www.flobotics.io/images/imported/729e5df88b11462459384d70.pdf) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Microsoft Dragon Copilot Canonical: https://www.flobotics.io/microsoft-dragon-copilot --- [Home](https://www.flobotics.io/)/Lab/Microsoft Dragon Copilot FLOBOTICSLABTechnology briefing Microsoft Nuance DAX # Clinical notes taken for you - live. With DAX Copilot and ambient listening you can finally focus on the patient while Microsoft Dragon automatically drafts clinical notes directly in your EHR. [Book a 30-minute call →](https://www.flobotics.io/book)[Learn more](#learn-more) Powered byMicrosoft Cloud for Healthcare - Integrates with my system? Yes, Epic, Meditech & more. - Setup time? Weeks, not months. - Secure? 100% HIPAA-compliant. The DAX advantage ## Unlock Your Focus. Ambient listeningAI drafting ### Conversations into clinical notes. DAX Copilot accurately distinguishes between casual conversation and clinically relevant data. It synthesizes the encounter into a comprehensive SOAP note format (Subjective, Objective, Assessment, Plan) within seconds of the visit ending. [Learn more →](https://www.flobotics.io/rcm-automation) Workflow integrationEHR ### Staged directly in the patient’s chart. Your notes are waiting for you in Epic, Cerner, or your preferred EHR. Review, edit, and sign. [Learn more →](https://www.flobotics.io/rcm-automation) Physician well-beingROI ### End the era of “pajama time” charting. Stop taking your clinical notes home. DAX Copilot helps physicians leave work at work. [Calculate ROI →](https://www.flobotics.io/roi-calculator) Enterprise gradeSecurity ### Built on the secure Microsoft Cloud. Leveraging Microsoft Azure’s world-class security infrastructure, DAX Copilot ensures that all patient data is encrypted in transit and at rest. It adheres to strict HIPAA compliance standards, ensuring peace of mind for IT leaders and compliance officers. [Learn more →](https://www.flobotics.io/rcm-automation) Results ## Agentic AI is a natural step forward in RCM evolution. And we have several proofs of this. [ Client caseDenials Management $50K+saved in one month, with 90% less manual rework for the RCM team. ### $50K+ Saved in 1 Month | AI Agent For Denials Management Read the case study → ](https://www.flobotics.io/case-studies/50k-saved-in-1-month-ai-agent-for-denials-management) [ Client caseClaims Management 70%faster claim turnaround for out-of-network reimbursement. ### 70% Faster Claim Turnaround Time (CTT) Read the case study → ](https://www.flobotics.io/case-studies/70-faster-claim-turnaround-time-ctt-claim-management-automation) [ Claims Management 98%reduction in manual claim prep. Up to 250 hours per week of manual RCM work removed. ### 98% Reduction in Manual Claim Prep Read the case study → ](https://www.flobotics.io/case-studies/98-reduction-in-manual-claim-prep-claims-management-automation) [All case studies](https://www.flobotics.io/case-studies) AI agents ## Wait, there is more? Yes! We specialize in RCM process automation. [AI agent ### Denials Management Automation Hunts and classifies denials early to stop them from aging out. →](https://www.flobotics.io/agents/denials-management-automation)[AI agent ### Claims Management Automation Tracks claims and flags denials before they cost you. →](https://www.flobotics.io/agents/claims-management-automation)[AI agent ### Prior Authorization Automation Automate your PA process. No API required. →](https://www.flobotics.io/agents/prior-authorization-automation) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Our Editorial Team Canonical: https://www.flobotics.io/our-editorial-team --- [Home](https://www.flobotics.io/)/[Company](https://www.flobotics.io/about-us)/Editorial team Who writes our content? # Meet Our Editorial Team The people who build and run our automations write about them. Every article is signed by a person you can call. CEO & Co-Founder ## Filip Nasiadko The industry dreamer who's staking his own company on where revenue cycle is headed next. He has skin in the game most commentators don't, so when he calls a trend, it's a bet he's placing with real money, not hype for clicks. 11 published articles Read CEO Notes →[LinkedIn](https://linkedin.com/in/filip-nasiadko-8399a993) CTO & Co-Founder ## Karl Mielnicki Kaizen-obsessed cost assassin who treats every wasted dollar in your revenue cycle like a crime scene. He thinks like a CFO, not a salesperson, so his ROI numbers survive an actual finance review instead of falling apart under scrutiny. 25 published articles Read CTO Notes →[LinkedIn](https://linkedin.com/in/karl-mielnicki) Head of AI ## Bart Teodorczuk The tool-obsessed tinkerer who's already broken the thing your vendor is about to pitch you next quarter. He tests the models and stacks himself, so he knows which vendor claims hold up under real volume and which fall apart. 40 published articles [Read articles →](https://www.flobotics.io/blog)[LinkedIn](https://linkedin.com/in/bart-teodorczuk-a85365127) Head of Delivery ## Krzysztof Szwed The operations realist who assumes your rollout will break and tells you exactly where. He doesn't care about the ROI slide - he cares about whether your staff can absorb the workload shift without burning out or blowing an SLA. 22 published articles [Read articles →](https://www.flobotics.io/blog)[LinkedIn](https://linkedin.com/in/krzysztof-szwed) Also writing ## Contributors Developers, analysts and specialists from the Flobotics team. Dominik Put UiPath-certified RPA developer with extensive experience in automating healthcare, customer service, and HR… 3 articles Gosia Gomola HR Manager and member of the “People & Change” team at Flobotics 1 articles Jacek Żukowski An RPA Consultant and Business Analyst 3 articles Jędrzej Szymula Content Manager 43 articles Maciek Matuszczak Senior RPA Developer at Flobotics 1 articles Michał Rejman Chief Marketing Officer at Flobotics 20 articles Radek Moczydlowski Tech Lead at Flobotics 1 articles Yana Pokora Content Manager at Flobotics 8 articles Quality over quantity ## Our Manifesto ### Your goals & needs dictate the tools We're tech-agnostic. ### You only pay for what's truly needed We optimize the license costs. ### You gain a vetted automation partner We focus on 100% ROI. Case studies ## Our Success Stories: See the case studies below to learn more about our business automation success stories. [ Business process automation 100%ROI within two months. ### 100% ROI within two months Read the case study → ](https://www.flobotics.io/case-studies/esky-luggage-tracking-automation)[ Client caseBusiness process automation 600xfaster account activation: about 10 minutes down to 1 second. ### 600x faster account activation Read the case study → ](https://www.flobotics.io/case-studies/global-view-automation)[ Client caseBusiness process automation 4,685hours of manual labor saved per year. ### 4,685 hours of manual labor saved Read the case study → ](https://www.flobotics.io/case-studies/sugar-producer-automation)[ Client caseBusiness process automation $100,000+in estimated labor cost savings. ### $100K+ saved in a few days Read the case study → ](https://www.flobotics.io/case-studies/mystic-river-consulting-automation)[ Client caseBusiness process automation 4xfaster account activation: about 16 minutes down to 4. ### 4x faster account activation Read the case study → ](https://www.flobotics.io/case-studies/gps-nvision-automation)[ Client caseBusiness process automation $186,000of profit in year one. ### $186,000 of profit in year one Read the case study → ](https://www.flobotics.io/case-studies/axpo-automation) AI agents ## Wait, there is more? Yes! We also specialize in end-to-end RCM automation. [ ### Denials Management Automation Hunts and classifies denials early to stop them from aging out. View agent →](https://www.flobotics.io/agents/denials-management-automation)[ ### Claims Management Automation Tracks claims and flags denials before they cost you. View agent →](https://www.flobotics.io/agents/claims-management-automation)[ ### Prior Authorization Automation Automate your PA process. No API required. View agent →](https://www.flobotics.io/agents/prior-authorization-automation)[ ### Eligibility Check Automation 24/7 patient coverage verification, all without human supervision. View agent →](https://www.flobotics.io/agents/eligibility-check-automation) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Healthcare RCM Automation | Pricing Canonical: https://www.flobotics.io/pricing --- [Home](https://www.flobotics.io/)/[What we do](https://www.flobotics.io/what-we-do)/Pricing Pricing # The way we price shouldn’t be a secret AI changed what automation costs. Some work that took us a month two years ago takes ten minutes now with ChatGPT or Claude. Work with patient data, secure logins and several systems still needs AI agents and automations built for your systems. Here’s how we price both. [Book a 30-minute call →](https://www.flobotics.io/book)[Estimate my ROI](https://www.flobotics.io/roi-calculator) What you pay ## What you can expect to pay If ChatGPT or Claude is enough $0 ### You can do it yourself If ChatGPT or Claude can do the job on its own, you don’t need us to build anything. We’ll tell you in the first 15 minutes of the call and show you how to set it up. After the call, you get an AI summary of what we talked about. If patient data is involved, only use a ChatGPT or Claude plan that’s covered by a BAA. Most projects $15,000–$25,000 ### One automation in your systems An AI agent or automation built for your systems, for work with patient data, secure logins, multi-factor sign-in or several systems. We build it, test it on real cases and put it live. You get an exact price after we’ve seen the process. The first automation on a system costs the most. The second and third on the same systems cost less, because they reuse what we built for the first. 10+ processes 6 months ### A dedicated team In six months, a dedicated team can automate 10 or more processes and keep them running. If you cancel in the first 30 days, you owe nothing. After that, we invoice at the end of each month, after the work is done. [Our 30-day promise →](https://www.flobotics.io/our-promise) Pricing factors ## What makes it cost more or less How we connectAn API takes the least work. A web portal takes more. An older desktop application takes the most. Sign-in and securityA plain login is simple. Secure logins, multi-factor sign-in and HIPAA requirements add work. SystemsOne system costs less than several. Each system adds its own logins, screens and checks. Python or UiPathWe use whichever fits the process. Python has no license fee. UiPath needs a license, which is priced separately. First or nextThe first automation on a system costs the most. The next ones on the same systems reuse its parts. [How reuse lowers the cost](https://www.flobotics.io/uipath-services#framework) The processHow many cases it handles, how many exceptions it has, special payer or clinic rules, and what has to be reported or audited. Included in the price The BAA, the build, testing on real cases and go-live. Quoted with the project Maintenance after go-live, so you know the full cost up front. Priced separately UiPath licenses, if the automation runs on UiPath. Real projects ## What real projects cost Three projects from healthcare clients. Most projects cost between $15,000 and $25,000. Some, like the second and third here, cost more. Eligibility checks ### Eligibility automation for a provider Patient eligibility checked before each visit, unattended. - 90% less manual work - 5x faster case processing - HIPAA compliant Price~$19,500 Prior authorization ### Prior authorization for a cancer treatment clinic Prior authorization packets completed automatically, following each payer’s rules. - 85% faster packet submission - 90% fewer errors that cause denials - 5x higher throughput Price~$29,500 Denials ### Denials resubmission for a laboratory An EHR-to-claim data pipeline and automatic resubmission of denied claims. - EHR data moved without retyping - 10x faster case processing - Half an FTE of capacity freed Price~$34,000 Next steps ## How you get an exact price - 30 minutes ### A call You talk to someone who builds automations. Within 15 minutes, you’ll know whether ChatGPT or Claude is enough, whether it’s a project, or whether it isn’t worth automating. - 30–60 minutes ### A walkthrough You show us the process on a screen share: the systems, the steps and the exceptions. - 30 minutes ### An exact price We review the process and come back with an exact price, including maintenance. Working with a dedicated team? [See our 30-day promise →](https://www.flobotics.io/our-promise) Results ## Numbers our clients measured [100%ROI in 23 days from eligibility automation→](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) [8+ FTEssaved with prior authorization automation→](https://www.flobotics.io/case-studies/85-faster-submissions-8-ftes-saved-prior-authorization-automation) [98%less manual claim preparation at Gentem Health→](https://www.flobotics.io/case-studies/98-reduction-in-manual-claim-prep-claims-management-automation) [Up to 80%higher denials throughput at PathGroup→](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation) [50%smaller monthly eligibility backlog→](https://www.flobotics.io/case-studies/halving-monthly-backlog---eligibility-automation-in-action) [90%faster prior authorization packet submissions→](https://www.flobotics.io/case-studies/90-faster-packet-submissions-prior-authorization-automation) [70%faster claim turnaround time→](https://www.flobotics.io/case-studies/70-faster-claim-turnaround-time-ctt-claim-management-automation) [$50K+saved in one month with an AI agent for denials→](https://www.flobotics.io/case-studies/50k-saved-in-1-month-ai-agent-for-denials-management) [All client results →](https://www.flobotics.io/case-studies) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Estimate your ROI](https://www.flobotics.io/roi-calculator) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. If ChatGPT or Claude can do it on its own, we’ll tell you in the first 15 minutes and show you how. If it can’t, we’ll tell you what it would take to build. Karl & Bart --- # Privacy Policy | Flobotics Canonical: https://www.flobotics.io/privacy-policy --- [Home](https://www.flobotics.io/)/Privacy policy Privacy policy # Your Privacy, Our Priority. ## Privacy policy Last updated: October 21, 2026. ### 1. Overview Flobotics values your privacy and is committed to protecting your personal information. This Privacy Policy explains what information we collect, how we use it, and your choices regarding your data. It is applicable to all users of our website and services. Please note that this policy does not apply to information collected by third parties that Flobotics does not control or manage. If you access other websites via links on our site, please review their privacy policies independently. For detailed information about our data practices, visit compliance.flobotics.io. ### 2. Purpose for Collecting Personal Information We collect personal information to provide and improve our services, to contact you about our offerings, and to ensure compliance with legal obligations. Specifically, we use your information to: - Respond to inquiries and requests. - Confirm scheduled calls and, when enabled, generate AI-assisted research to help prepare for those calls. - Process transactions and deliver services. - Improve our website and services based on user feedback. - Comply with legal requirements and protect our users’ safety and our business integrity. ### 3. Types of Personal Information Collected We may collect the following types of personal information: - Contact Information: Name, email address, phone number. - Booking Information: Your name, email address, scheduled call date and time, and company name if you provide it. - Professional Information: Public information about your role and company that may be used for AI-assisted call preparation. - Technical Information: IP address, browser type, device identifiers. - Usage Data: Pages visited on our site, time spent on pages, and navigation paths. - Cookies and Tracking Data: Information collected through cookies and similar tracking technologies. ### 4. Methods of Collection We collect personal information through: - Direct Interaction: When you provide information through forms or surveys on our website. - Automated Technologies: Through cookies and similar technologies that track your activity on our website. - Third-Party Sources: Information from partners and service providers that enhance our services. ### 5. Use, Retention & Disposal - Use: We use your personal information to deliver services, respond to your inquiries, and improve our offerings. - Retention: Personal information is retained only as long as necessary for the purposes for which it was collected or as required by law. - Disposal: When no longer needed, personal information is securely disposed of to prevent unauthorized access. When your tracking choices permit it, we remember campaign tags, referring website domains and landing-page paths for up to 90 days in your browser. Advertising click identifiers are included only when advertising tracking is permitted. After a successful inquiry or booking, we retain this campaign context under its submission or booking identifier on Cloudflare for up to 90 days and attach it to the corresponding record in our Pipedrive CRM. This helps us understand which campaigns lead to inquiries and calls. CRM records follow the retention principles above. Turning off optional tracking clears this campaign history from your browser and prevents it being attached to later submissions. ### 6. Choice & Consent You have choices regarding the collection and use of your personal information. You may: - Opt-out of Communications: Choose not to receive promotional emails by following the unsubscribe instructions included in such communications. - Update Your Cookie Preferences: Use the footer link Do not sell or share my personal information or Cookie settings on our website to change your choices or turn off optional tracking. Where prior consent is required, optional analytics, advertising and visitor-identification tools remain off until you accept the relevant categories. For visitors identified as being in the United States, these tools may be enabled by default where permitted. The footer link Do not sell or share my personal information opens tracking controls on desktop and mobile, without an automatic popup or floating tab. Visitors outside the United States, or whose region cannot be confirmed, receive our opt-in banner. You can opt out of optional tracking, including sale or sharing for advertising and visitor identification, by opening the footer link Do not sell or share my personal information and choosing Opt out of tracking or Decline all. The footer link Do not sell or share my personal information also opens these controls for US visitors. Reopen your choices at any time using that footer link or Cookie settings. We honor Global Privacy Control (GPC) by disabling optional tracking, including for visitors who previously accepted it. Essential website and security functions remain available. Open privacy choices ### 7. Access and Correction You have the right to access and correct your personal information held by us. If you wish to review or update your personal data, please contact us at [info@flobotics.io](mailto:info@flobotics.io). ### 8. Disclosure to Third Parties We do not sell personal information for money. Advertising and business visitor-identification technologies may involve a sale or sharing of personal information as those terms are defined by applicable privacy laws. You can opt out using the controls described above. Our website uses Google Analytics and Ahrefs for visit measurement, Microsoft Clarity for usage analysis, RB2B and Factors for business visitor identification, Google, LinkedIn and Meta for advertising measurement, and MyPopups for website popups. These tools can receive information such as your IP address, device or cookie identifiers, and pages visited. Depending on the provider, they may match this activity with information they already hold about your company or professional identity. CookieScript manages the regional banner and your tracking choices. We may also share information with: - Service Providers: Trusted partners who assist in delivering our services, bound by confidentiality agreements. - Legal Compliance: Authorities if required by law or to protect the rights, safety, or property of Flobotics, its users, or others. - Business Transfers: In the event of a merger, acquisition, or asset sale, personal information may be transferred as part of the business assets. #### Booking confirmations and AI-assisted call preparation We use TidyCal to schedule calls. After you book, TidyCal passes your name, email address, and scheduled date and time to our confirmation page, hosted on Cloudflare. The page uses those details to display your booking confirmation. It removes them from the address bar before external scripts run. After we confirm a recent, active booking, we may send a completed-call event to Google Analytics, Google Ads, LinkedIn and Meta, subject to your tracking choices and applicable regional settings. The event uses a booking identifier for duplicate prevention and does not include your name, email address, meeting time or generated research. Session-replay and business visitor-identification tools remain excluded from this page. When AI-assisted preparation is enabled, our server checks TidyCal for a booking matching your email address. We then send your name, email address, and company name, if provided, to OpenAI to generate a brief shown on the confirmation page. One model uses your email domain and the information you provide; another uses web search to find public professional information about you and your company and suggest processes we could automate. If your email address does not identify a company, the page asks you for its name. This research is intended to cover professional information, such as your job title, company, industry, and business systems. It is not intended to collect health information or other private personal details. AI-generated information and suggestions may be incomplete or incorrect. You can ask us to correct them at [info@flobotics.io](mailto:info@flobotics.io). Our website does not save the generated brief to a Flobotics database or CRM. Completed results are kept in your browser's session storage for the current tab. OpenAI processes the submitted information and generated responses under its own data controls; provider retention is separate from this browser storage. OpenAI's standard API controls include retention of abuse-monitoring logs for up to 30 days, subject to exceptions, and stored Responses API data for at least 30 days unless different controls apply. See [OpenAI's API data controls](https://developers.openai.com/api/docs/guides/your-data) for details. If you prefer to arrange a call without AI-assisted preparation, email [info@flobotics.io](mailto:info@flobotics.io). ### 9. Security for Privacy We employ robust security measures to protect your personal information from loss, misuse, and unauthorized access, disclosure, alteration, or destruction. This includes encryption, access controls, and secure data storage. ### 10. Quality and Data Integrity We rely on you to provide accurate and updated information. If your information changes, please notify us to ensure our records are accurate. ### 11. Monitoring and Enforcement We regularly review our privacy practices and compliance with this policy. Any concerns or violations are promptly addressed. If you have any complaints or questions about our privacy practices, contact us at info@flobotics.io. ### 12. Our Service Flobotics specializes in robotic process automation (RPA) and intelligent automation development and consulting. Our commitment to protecting your privacy reflects our dedication to providing secure and trustworthy services. ### 13. Changes to this Privacy Policy We may update this Privacy Policy to reflect changes in our practices or for legal compliance. You will be notified of any significant changes via email or a prominent notice on our website. ### 14. Requests for Deletion You have the right to request the deletion of your personal information. To exercise this right, please contact us at info@flobotics.io. We will process your request in accordance with applicable laws. ### 15. Contact Us If you have questions or comments about this Privacy Policy, please contact us: Email: [info@flobotics.io](mailto:info@flobotics.io) Phone: [+1 (910) 518-0124](tel:+1(910)518-0124) For more information about the data we collect, visit compliance.flobotics.io. Thank you for choosing Flobotics! --- # RCM Automation Quiz | Find Your Workflow Solution Canonical: https://www.flobotics.io/quiz --- [](https://www.flobotics.io/) [← Back to site](https://www.flobotics.io/) RCM automation quiz # Find the right automation for your RCM Workflows Discover the right automation for your revenue cycle management in 3 quick questions. Get personalized recommendations for your business. - 01Your biggest bottleneck - 02Your system type - 03Your priority metric Takes only 3 clicks Start quiz → Question 1 / 3 ## Which bottleneck limits your RCM the most? Prior authorizations Eligibility checks Interoperability Claims management Denials re-work and resubmission All of the above ← Back Next question → Question 2 / 3 ## Which system type matches your RCM the most? Big EHRs Small EHRs Billing software/Claim management Hybrid or custom in-house system Other / It's hard to categorize ← Back Next question → Question 3 / 3 ## Which of the following RCM metrics is your priority now? Reduce denials rate (DR) Save RCM team capacity Improve cash flow (A/R) Lower operational costs (CTC) All of the above ← Back Get results → Your result ## Seems like you’d benefit from: Result [Book a 30-minute call →](https://www.flobotics.io/book) [See Eligibility Check Automation](https://www.flobotics.io/agents/eligibility-check-automation) [See the Prior Authorization Agent](https://www.flobotics.io/agents/prior-authorization-automation) [See the Claims Management Agent](https://www.flobotics.io/agents/claims-management-automation) [See Denials Management](https://www.flobotics.io/agents/denials-management-automation) [See RCM Custom Automation](https://www.flobotics.io/rcm-automation) ← Change my last answer ## What our clients say After we implemented their bots, tasks that took us 30 minutes to do only took a few minutes. That was a great improvement. The team quickly implemented feedback and delivered a solution that met all our needs. Rasheed ColeHead of IT at RedPeg Marketing I appreciate their understanding and the way they grasp the needs of our business. Their overall knowledge, beyond the RPA, has been great as well. They also provide a high quality of security to protect the confidentiality we require. Rosemary AngstenCOO, DART Chart Systems I admire their ability to meet and exceed our requirements and expectations. Peter GilbertCIO at Ayr Farmers Mutual Insurance They were easy to get in contact with and the whole collaboration went smoothly. The automation has saved us a considerable amount of time. Everyone in the team confirmed it works fantastically and that it’s freed them up a lot of time. Manny AkintayoCo-founder & CTO at Gentem Health © 2026 Flobotics. Made with love in Indiana, US. [Privacy Policy](https://www.flobotics.io/privacy-policy)[Do not sell or share my personal information](https://www.flobotics.io/privacy-policy#your-privacy-choices) [Book a 30-minute call →](https://www.flobotics.io/book) --- # Custom RCM Automation Solutions | Flobotics Canonical: https://www.flobotics.io/rcm-automation --- [Home](https://www.flobotics.io/)/[What we do](https://www.flobotics.io/what-we-do)/Custom RCM automation Workflows we automate # Revenue Cycle Management Automation We automate the repeated work across your revenue cycle, from patient intake and insurance checks to claim follow-up and payment posting. We start with the tasks that take your team the most time and assess whether the savings justify the cost. [Book a 30-minute call →](https://www.flobotics.io/book)[See client results](#results) Illustration of one custom workflow: payer correspondence and claim follow-up. Three payer messages arrive. The first is matched to its claim and the status is saved with a next check date. For the second, the requested document is found, sent and its receipt saved. The third letter has an unclear claim reference, so it goes to staff with the original letter. The example ends with 2 records updated and 1 needing review. Payer correspondence and claim follow-up - Read - Match - Update - Flag exceptions Payer messages · today - A. Rivera · claim R-3041Status messageStatus updated · next check recorded - J. Okafor · claim R-3042Document requestDocument sent · receipt saved - M. Chen · claim R-3043Payer letterStaff review · claim match unclear 2 records updated · 1 needs review Current message · A. Rivera · claim R-3041 MessageStill under review Claim referenceR-3041 Message →Billing record← Update Billing recordMatched ActionStatus updated Saved10:14 Next checkIn 7 days Status saved to the billing record · next check recorded Example with made-up patients and claims. This is one workflow we can build around your systems. PauseReplay Client result · California medtech company ## How a medtech company automated denial work and payer correspondence The company's team handled denial records and payer correspondence across XiFin and payer portals. We built workflows for document handling, reconsiderations, and record updates. Staff review the cases that cannot follow the agreed process. [Read the medtech case study →](https://www.flobotics.io/case-studies/50k-saved-in-1-month-ai-agent-for-denials-management) Measured results ~6 min →to ~30 sper case in the automated denial workflow 80% in 3 weeksof a 3,000-claim denial backlog cleared 95% lessmanual correspondence handling These results come from different workflows in the same client's project. SuperBill reduced its document-to-claim cycle from about 24 hours to about 7 hours with a separate document-processing workflow. [Read the SuperBill case study →](https://www.flobotics.io/case-studies/70-faster-claim-turnaround-time-ctt-claim-management-automation) What we automate ## Repeated tasks across your revenue cycle. Some teams need one task automated. Others need several workflows connected. These are the areas we can work on, with the scope agreed for your project. - 01Prepare Get patient, order, and billing information into the right records. - Pull patient details, orders, and appointment information into the systems that need them. - Check eligibility and capture available benefit details. - Gather documents and prepare authorization requests. - Move and validate data between systems, including during a migration. - 02Submit Prepare and send supported requests and claims. - Transfer recorded service codes, charges, and provider details into billing records. - Check required fields, formatting, and agreed billing rules. - Submit claims and authorization requests through supported connections or portals. - Save confirmations and attach the related documents to the right records. - 03Follow up Keep open work current and send exceptions to staff. - Check claim and authorization statuses on an agreed schedule. - Read payer correspondence and record the required action. - Prepare supported denial corrections, reconsiderations, and appeal documents. - Track open balances and follow-up dates in your accounts receivable queues. - 04Reconcile Match payments and keep billing records consistent. - Match remittance details to claims and post payments and approved adjustments. - Prepare patient statements and approved reminders from recorded balances. - Compare payments with recorded charges and agreed payer rates where data is available. - Produce reports and flag unmatched amounts or inconsistent records. We agree which tasks to automate, where results are saved, and which cases go to your team. You can start with one workflow and add others when they make sense. Some cases still need billing, coding, clinical, or financial judgment. Automation cannot guarantee payer approval, payment, or a positive return for every process. Is it a good fit? ## RCM automation usually pays off when most of these are true. - Your team repeats the same billing tasks many times each week. - Staff move information between systems that do not exchange it automatically. - Work waits for manual entry, document handling, or status checks. - You can identify the normal process and the cases that need a person. What affects your savings - How often each task is repeated - How much hands-on work and rework it takes - Which system connections, documents, and source data are available - How often the process needs judgment or changes - What it costs to build and maintain The return is different for every organization. Schedule a call and we'll give you a quick, honest estimate of which workflow is worth considering first. [Book a 30-minute call →](https://www.flobotics.io/book) How RCM automation works with your systems ## The automation moves information between the systems your team uses. Your staff keep using the systems they know. We use direct connections where available, UiPath or Python for work in portals and desktop apps, and AI where documents or messages need reading. We agree what can run automatically and what needs staff review. Example of one custom workflow between three places. The automation reads a payer message and saves the status to the matching claim in the billing system. For a second message, it finds the requested document in the billing system, sends it through the payer portal and saves the receipt. A third letter has an unclear claim reference, so it goes to the staff review queue without changing any claim record. Your billing system · open claims ClaimPatientDocumentsStatus R-3041A. Rivera—Open R-3042J. OkaforItemized billOpen R-3043M. Chen—Open Itemized bill · R-3042 Flobotics automation Your rulesMatch the claimSave the payer updateUnclear match → staff Payer portal and correspondence - Message · claim R-3041 · still under review - Message · claim R-3042 · send itemized bill - Letter · claim reference unclear Send document Receipt— Your staff · review queue Payer letter · 10/14Claim match is unclear. Review the original payer letter. No exceptions yet Monitored and maintained by us. We check the runs and update the workflow when payer processes or your systems change. Example with made-up patients and claims. Each project uses its own systems, rules, and review steps. PauseReplay We assess each workflow separately. A project can cover one task or several connected processes, depending on the work and the expected return. Related workflows ## Common revenue cycle workflows we automate. - 01[Eligibility & benefits](https://www.flobotics.io/agents/eligibility-check-automation)Check coverage before the visit and save the result in the patient record.~40 s per checkPTCoA · [Case study](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks)→ - 02[Prior authorization](https://www.flobotics.io/agents/prior-authorization-automation)Prepare and submit authorization requests, then check for updates.85% less submission timePTCoA · [Case study](https://www.flobotics.io/case-studies/85-faster-submissions-8-ftes-saved-prior-authorization-automation)→ - 03[Claims management](https://www.flobotics.io/agents/claims-management-automation)Prepare, submit, and track claims.98% less manual claim preparationGentem Health · [Case study](https://www.flobotics.io/case-studies/98-reduction-in-manual-claim-prep-claims-management-automation)→ - 04[Denials management](https://www.flobotics.io/agents/denials-management-automation)Prepare supported corrections and appeals, then track payer responses.Up to 300 resubmissions a dayPathGroup · [Case study](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation)→ - 05[Document processing](https://www.flobotics.io/healthcare-document-processing)Turn faxes, scans and PDFs into checked data for your systems.~70% shorter document-to-claim cycleSuperBill · [Case study](https://www.flobotics.io/case-studies/70-faster-claim-turnaround-time-ctt-claim-management-automation)→ Talk to us ## Which revenue cycle tasks are worth automating? Book a 30-minute call with Karl, our CTO, or Bart, our Head of AI. If you'd rather write, send us a message. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the billing tasks taking up your team's time. Within the first 15 minutes, we can usually identify where automation might make sense. We'll discuss the work involved and what we'd need to estimate the cost. Karl & Bart --- # RCM Industry News Canonical: https://www.flobotics.io/rcm-industry-news --- [Home](https://www.flobotics.io/)/[Resources](https://www.flobotics.io/resources)/RCM industry news RCM industry news # Latest News & Updates From regulatory updates to billing trends and reimbursement strategies - an RCM news page that keeps everyone on track. AllRevenue Cycle ManagementPrior AuthorizationClaims & DenialsRegulatory & CMSCompetitive & Market [ Prior Authorization ## Optum unveils two new AI tools for digital prior authorization Optum is launching two AI tools — Digital Auth Complete and InterQual Auth Accelerator — to cut prior authorization delays. Digital Auth Complete integrates into the EHR and automates multiple parts of the process to return responses faster. Fierce HealthcareJuly 19, 2026 ](https://www.flobotics.io/rcm-industry-news/optum-ai-digital-prior-authorization-tools)[ Competitive & Market ## UiPath launches agentic AI solutions for healthcare administration UiPath announced agentic AI solutions for healthcare: medical records summarization, claim denial prevention and resolution, and prior authorization — using agentic automation to accelerate revenue cycle management. UiPath (Investor Relations)July 19, 2026 ](https://www.flobotics.io/rcm-industry-news/uipath-agentic-ai-healthcare-admin)[ Prior Authorization ## Abridge teams with Availity to scale real-time prior authorization An integration between Abridge and Availity aims to speed prior authorization from weeks to minutes, shifting the process from post-visit to real time during the patient exam. Fierce HealthcareJuly 19, 2026 ](https://www.flobotics.io/rcm-industry-news/abridge-availity-real-time-prior-auth)[ Competitive & Market ## Autonomize AI Launches Genie AI Autonomous Agent Autonomize AI launched Genie AI, a healthcare-native AI agent that lets clinicians, care managers, and operations staff build automated workflows using natural language. The tool targets utilization management, prior authorization, appeals, and care coordination, and is designed to keep generated workflows auditable and governed within existing enterprise systems. Autonomize AI (GlobeNewswire)July 15, 2026 ](https://www.flobotics.io/rcm-industry-news/autonomize-ai-launches-genie-ai-autonomous-agent)[ Claims & Denials ## MDaudit Adds Auditor Assist to Its Continuous Risk Monitoring Suite MDaudit added Auditor Assist, an AI-powered companion that helps human auditors review coding-integrity cases faster while keeping a human in control of the final call. The launch responds to a reported 30% year-over-year rise in payer audit volume, with coding-related denials up as much as 26%. MDaudit (GlobeNewswire)July 15, 2026 ](https://www.flobotics.io/rcm-industry-news/mdaudit-adds-auditor-assist-continuous-risk-monitoring)[ Revenue Cycle Management ## Black Book Research Recognizes Inovalon for End-to-End Revenue Cycle Platform and Eligibility Intelligence Inovalon was named a top-rated revenue cycle management vendor by Black Book Research in two categories: full-suite intake-to-final-payment platform breadth, and real-time eligibility and benefits verification. The ranking is based on evaluations from more than 1,300 hospital and health system finance leaders. Business Wire (Inovalon)July 15, 2026 ](https://www.flobotics.io/rcm-industry-news/black-book-research-recognizes-inovalon-rcm-platform)[ Regulatory & CMS ## CMS CY 2027 Physician Fee Schedule Proposed Rule Includes Interoperability RFI CMS's CY 2027 Physician Fee Schedule proposed rule includes a Request for Information on duplicate laboratory testing and imaging caused by data siloed within electronic health record systems. Comments on the RFI are due September 14, 2026. CMSJuly 14, 2026 ](https://www.flobotics.io/rcm-industry-news/cms-2027-physician-fee-schedule-interoperability-rfi)[ Revenue Cycle Management ## Athenahealth rolls out 80+ AI-native revenue cycle features Athenahealth built more than 80 AI-native features into athenaOne, targeting high-friction tasks such as insurance verification, coding, prior authorization and denials. AI voice agents place over 23,000 prior authorization calls each month, some completed in under an hour. Becker's Hospital ReviewJune 3, 2026 ](https://www.flobotics.io/rcm-industry-news/athenahealth-80-ai-native-revenue-cycle-tools)[ Regulatory & CMS ## States Continue Efforts to Regulate AI in Healthcare: A Review of Legislation Passed in 2026 A 2026 legislative review tracks state laws enacted this year regulating insurers' use of AI in prior authorization and claims decisions. States including Georgia, Maryland, Washington and Utah added disclosure, human-oversight and reporting requirements for AI-assisted adverse determinations. Holland & KnightMay 26, 2026 ](https://www.flobotics.io/rcm-industry-news/2026-07-19-states-continue-efforts-to-regulate-ai-in-healthcare)[ Competitive & Market ## How AI is transforming revenue cycle management right now Oliver Wyman's 2026 Healthcare RCM Survey of 200+ decision-makers and 90 end users finds AI adoption moving from pilots to enterprise scale. Ambient documentation, coding automation and electronic prior authorization are the top investment areas cited by respondents. Oliver WymanApril 29, 2026 ](https://www.flobotics.io/rcm-industry-news/2026-07-19-how-ai-is-transforming-revenue-cycle-management)[ Regulatory & CMS ## CMS proposes rule for electronic prior authorization of drugs (CMS-0062-P) A proposed CMS rule extends electronic prior authorization requirements from non-drug items to drugs, adopts FHIR standards for prior auth transactions and mandates API metrics reporting. Most compliance dates begin October 1, 2027. CMSApril 10, 2026 ](https://www.flobotics.io/rcm-industry-news/cms-electronic-prior-authorization-drugs-rule) No news in this topic yet. --- # RCM Automation ROI Calculator | Flobotics Canonical: https://www.flobotics.io/roi-calculator --- [Home](https://www.flobotics.io/)/[Resources](https://www.flobotics.io/resources)/ROI calculator ROI calculator # Calculate Your ROI Adjust initial data, drag the sliders, and see how fast the automation of your process pays off. [Start calculating ↓](#roi-calculator)[Book a 30-minute call](https://www.flobotics.io/book) - IncludesAgent development & maintenance costs - Based onIndustry benchmarks from 100+ automation projects ## Your process specifics Step 1 · Inputs How long is the process? How much time does one full cycle take? ShortMediumLong How complex is the process? How many steps or decision points does it include? Simple Average Complex Are physical documents involved? Does this process still rely on PDFs, scans, or printed forms? Yes No Could a new hire learn this in a month? Helps us estimate process complexity. Yes No What’s the average annual salary for employees handling this process?$28,500 Used to calculate potential labor savings. $0$100,000 How many people work on this project?2 Include everyone who touches it weekly. 110 How many hours per week does each person spend on it? Time spent on manual steps or error correction. Hours ## ROI estimation Step 2 · Results Year | Cost | Savings | Profit | ROI | Year 1 | – | – | – | – | Year 2 | – | – | – | – | Year 3 | – | – | – | – | Year 4 | – | – | – | – | If the numbers make sense, let’s validate them with your actual process data. ### Your ROI looks promising Let’s turn it into the real results. Book a 30-minute call with our automation experts – we’ll confirm the ROI and show what implementation could look like. [Book a 30-minute call →](https://www.flobotics.io/book) Resources ## Or... simply keep exploring: [Blog ### RCM Blog No AI slop. Just peer-reviewed industry insights from our editorial team. Read the blog →](https://www.flobotics.io/blog) [Glossary ### RCM Glossary No fluff. Just plain-English definitions of key RCM and automation terms & metrics. Open the glossary →](https://www.flobotics.io/glossary) --- # Terms & Conditions | Flobotics Canonical: https://www.flobotics.io/terms-conditions --- [Home](https://www.flobotics.io/)/Terms & conditions Terms & conditions # Fair & Clear. Our Commitment to You ## Terms & Conditions ### Agreement to terms You agree that by accessing the Site, you have read, understood, and agree to be bound by all of these Terms and Conditions. If you do not agree with all of these Terms and Conditions, then you are expressly prohibited from using the Site and you must discontinue use immediately. Supplemental terms and conditions or documents that may be posted on the Site from time to time are hereby expressly incorporated herein by reference. 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We ran this session live on June 10, 2026, and we’re preparing the recording now. [Book a 30-minute call →](https://www.flobotics.io/book)[See what it covers](#stack) Session4-Step RCM Automation Stack - Recorded: Wednesday, June 10, 2026 - Length: 30 minutes - Host: Bart, our Head of AI - Recording: available on demand soon What the session covers ## 30 minutes. No pitch deck. Just the playbook. Four things you can act on the same week. ### A denial-rate benchmark The range of denial rates we see at clinics like yours, so you can tell how much money is stuck compared with your peers. ### The four-step automation stack Eligibility, prior authorization, denials, and claims, in the order we automate them, with the EHR and payer-portal integrations we use. ### How to work out your ROI The numbers that decide the payback: denial volume, billing team size, and hourly cost. Run your own in the [ROI calculator](https://www.flobotics.io/roi-calculator). ### Your own question A recording can’t take questions. Bring yours to a [30-minute call](https://www.flobotics.io/book) with Bart or Karl, and we’ll answer it for your EHR and your workflow. Who it’s for ## Built for billing teams buried in work queues - Your billing staff spends hours each week on manual eligibility checks and denial follow-ups - You’ve looked at automation before but couldn’t justify ripping out your EHR to do it - Prior authorization is a bottleneck that delays care and blocks collections - You want to see real numbers from real clinics, not a vendor pitch deck 100%ROI in 23 days from eligibility automation at PTCoA[Eligibility · case study](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) 8+ FTEssaved by standardizing prior authorization submissions across payer portals[Prior authorization · case study](https://www.flobotics.io/case-studies/85-faster-submissions-8-ftes-saved-prior-authorization-automation) $50K+saved in one month, with 90% less manual rework on denials[Denials · case study](https://www.flobotics.io/case-studies/50k-saved-in-1-month-ai-agent-for-denials-management) 98%less manual claim prep, with up to 250 hours a week of RCM work removed[Claims · case study](https://www.flobotics.io/case-studies/98-reduction-in-manual-claim-prep-claims-management-automation) The four-step stack ## End-to-end RCM, as we deploy it The session walks through each step with the logic we use in production. Each card shows an example run with made-up patients. - Step 01 ### Eligibility checks We check coverage and benefits with each payer before the visit and record the result in your systems. Mismatches go to your team. [Eligibility automation →](https://www.flobotics.io/agents/eligibility-check-automation) - Step 02 ### Prior authorization We gather the order and insurance details, fill the payer form, submit the request, and save the confirmation. Missing documents go to your team. [Prior authorization automation →](https://www.flobotics.io/agents/prior-authorization-automation) - Step 03 ### Denial handling We find denied claims, capture the payer’s reason, and prepare the corrected claim, reconsideration, or appeal. Clinical calls stay with your team. [Denials automation →](https://www.flobotics.io/agents/denials-management-automation) - Step 04 ### Claims follow-up We check claim status with the payer, save the response, and resubmit when a correction is agreed. Missing information goes to your team. [Claims automation →](https://www.flobotics.io/agents/claims-management-automation) Your host ## Bart Head of AI · Flobotics I’ve sat through enough RFP responses and vendor pitches to know what actually moves the needle in RCM, and what’s just a deck. This webinar is the opposite: a direct account of what we built, what broke, and what the numbers looked like at the end. On demand ## The recording is coming soon We’re preparing the recording of the June 10 session. It will be available to watch on demand here soon. Until then, the four steps above link to the pages that show how each one works, and our [resources](https://www.flobotics.io/resources) page has the ROI calculator, the quiz, and our RCM articles. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # XiFin RCM Workflow Automation | Flobotics Canonical: https://www.flobotics.io/xifin-in-rcm --- [Home](https://www.flobotics.io/)/Lab/XiFin in RCM FLOBOTICSLABTechnology briefing XiFin RPM · agentic AI layer # Unlock Capacity Automate RCM XiFin is the industry’s #1-rated lab and diagnostics AI-driven cloud billing platform that optimizes financial performance for diagnostics and pharmacies. Eligibility, prior auth, claims follow-up, and denial resubmissions 24/7, all without a payer API. [Book a 30-minute call →](https://www.flobotics.io/book)[Learn more](#learn-more) ExtendsXiFin RPM & Empower AI - Integrates with my system? Yes, Epic, Meditech & more. - Setup time? Weeks, not months. - Secure? 100% HIPAA-compliant. Where Flobotics runs ## Every queue. Every payer. EligibilityFront-end RCM ### Coverage verified before the claim is built. The agent pulls patient data from XiFin, fires a real-time 270/271 eligibility check against the payer, and writes the result back — before the order touches the clearinghouse. For high-volume labs, this runs overnight across every patient in the queue and flags coverage gaps, COB mismatches, and missing plan data before submission. [Learn more →](https://www.flobotics.io/agents/eligibility-check-automation) DenialsAppeals ### Empower AI prioritizes. Flobotics resubmits. ~300 resubmissions per day, down from ~10 minutes per denial to ~55 seconds. XiFin’s Empower AI reads the EOB and tells you what to fix. It decodes every CARC/RARC code, corrects the root cause — missing documentation, CPT mismatch, payer-specific formatting — builds the appeal packet, and submits through the payer portal. [Learn more →](https://www.flobotics.io/agents/denials-management-automation) Prior authorizationLIMS to payer ### From XiFin order to payer portal, without staff. XiFin captures the order and clinical data. Flobotics extracts CPT, HCPCS, and ICD-10 codes, assembles the payer-specific PA packet with required attachments and LCD/NCD compliance, and submits to the payer portal — no API contract needed. careviso saw 90% faster packet turnaround from day one. [Learn more →](https://www.flobotics.io/agents/prior-authorization-automation) ClaimsA/R follow-up ### Stalled claims, chased automatically. The agent syncs with XiFin and your clearinghouse, monitors batch acknowledgements and adjudication statuses in real time, and surfaces only the exceptions that need a human decision. At Gentem, this eliminated 98% of manual claim prep and recovered 250 hours of RCM work per week. [Learn more →](https://www.flobotics.io/agents/claims-management-automation) Results ## Agentic AI automation is a natural step in RCM evolution. And we have several proofs of this. [ Client caseDenials Management $50K+saved in one month, with 90% less manual rework for the RCM team. ### $50K+ Saved in 1 Month | AI Agent For Denials Management Read the case study → ](https://www.flobotics.io/case-studies/50k-saved-in-1-month-ai-agent-for-denials-management) [ Client caseClaims Management 70%faster claim turnaround for out-of-network reimbursement. ### 70% Faster Claim Turnaround Time (CTT) Read the case study → ](https://www.flobotics.io/case-studies/70-faster-claim-turnaround-time-ctt-claim-management-automation) [ Claims Management 98%reduction in manual claim prep. Up to 250 hours per week of manual RCM work removed. ### 98% Reduction in Manual Claim Prep Read the case study → ](https://www.flobotics.io/case-studies/98-reduction-in-manual-claim-prep-claims-management-automation) [All case studies](https://www.flobotics.io/case-studies) AI agents ## Wait, there is more? Yes! We also specialize in RCM process automation. [AI agent ### Denials Management Automation Hunts and classifies denials early to stop them from aging out. →](https://www.flobotics.io/agents/denials-management-automation)[AI agent ### Claims Management Automation Tracks claims and flags denials before they cost you. →](https://www.flobotics.io/agents/claims-management-automation)[AI agent ### Prior Authorization Automation Automate your PA process. No API required. →](https://www.flobotics.io/agents/prior-authorization-automation) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Evidence-Based Treatment Centers of Seattle (EBTCS) Canonical: https://www.flobotics.io/blog/evidence-based-treatment-centers-of-seattle-ebtcs Author: Michał Rejman Published: 2026-09-06 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Evidence-Based Treatment Centers of Seattle (EBTCS) [RPA](https://www.flobotics.io/blog?category=rpa) # Evidence-Based Treatment Centers of Seattle (EBTCS) [Michał RejmanChief Marketing Officer at Flobotics](https://www.flobotics.io/our-editorial-team#rejman) Published September 06, 2026Updated September 1, 2026 On this page - [Client](#client) - [The Challenge](#the-challenge) - [The Solution](#the-solution) - [The Outcome](#the-outcome) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Client The Evidence-Based Treatment Centers of Seattle(EBTCS)is a network of specialty mental health clinics in the Seattle region, providing in-person and telehealth services. ## The Challenge EBTCS wanted to integrate its sales workflows with its patient management infrastructure by creating [interoperability between Salesforce and the Valant EHR system](https://www.flobotics.io/blog/interoperability-in-healthcare). While Valant is well-suited for mental health organizations, it does not offer a publicly accessible API.As a result, patient data had to be manually transferred between systems by staff, creating repetitive, time-consuming work. EBTCS leadership recognized the need to eliminate manual data movement and automate the process. ## The Solution Flobotics built an automation that runs every three hours, logging into Salesforce to retrieve newly scheduled opportunities representing new patients. The bot then logs into the Valant EHR,checks for existing patient records to prevent duplication, and [creates new patient profiles using Salesforce data](https://www.flobotics.io/blog/data-entry-automation-healthcare). The automation transfers personal details, assigned provider and facility, Medicare and Medicaid information, guardian data, and patient preferences. After completion, the patient status is updated in Salesforce and a summary report is sent to selected team members. Additional automations were implemented, including demographic data synchronization from Valant to Salesforce, PDF file transfers from Salesforce to Valant, billing error detection in the Valant Pending Transaction Queue, and voicemail transcription. ## The Outcome From day one, the automation processed dozens to hundreds of cases per week. Manual handling took approximately five minutes per case, while the bot completes each case in under fifteen seconds, achieving a 20x speed increase with no human involvement. Due to the scale of operations, EBTCS incurred no licensing costs, as Robocorp’s free plan fully met their needs. The client also gained access to real-time performance monitoring and reporting dashboards. EBTCS,thank you for your trust. We continue to support organizations seeking system interoperability through practical automation solutions. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byMichał Rejman Chief Marketing Officer at Flobotics. [More from Michał](https://www.flobotics.io/our-editorial-team#rejman) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # North Pole Inc. Canonical: https://www.flobotics.io/blog/north-pole-inc Author: Michał Rejman Published: 2026-09-06 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/North Pole Inc. [RPA](https://www.flobotics.io/blog?category=rpa) # North Pole Inc. [Michał RejmanChief Marketing Officer at Flobotics](https://www.flobotics.io/our-editorial-team#rejman) Published September 06, 2026Updated September 1, 2026 On this page - [About the Client](#about-the-client) - [The Challenge](#the-challenge) - [The Solution](#the-solution) - [Process 1:Automated Letter Processing](#process-1-automated-letter-processing) - [Process 2:Naughty-or-Nice List Audit](#process-2-naughty-or-nice-list-audit) - [Process 3:Gift Packing Automation](#process-3-gift-packing-automation) - [Process 4:Sleigh Route Optimization](#process-4-sleigh-route-optimization) - [Process 5:GDPR-Compliant Data Management](#process-5-gdpr-compliant-data-management) - [The Outcome](#the-outcome) - [What’s Next?](#whats-next) - [Thank You](#thank-you) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## About the Client Santa Claus, CEO of North Pole Inc., delivers joy (and presents) to over 2 billion children worldwide in a single night. As operations grew more complex and digital, Santa and his team faced major scaling challenges. ## The Challenge Santa Claus reached out to Flobotics with a clear set of business challenges: - Processing wish lists:Millions of letters arrived daily, many handwritten and hard to read. Elves spent hours deciphering and categorizing requests. - Naughty-or-Nice qualifications:The audit process was outdated and error-prone, with too much subjectivity for the team to manage at scale. - Gift packing:Wrapping choices slowed packing and increased rework and stress. - Route optimization:Suboptimal routing exhausted the reindeer crew and caused delays. - Compliance:Keeping children’s data safe while ensuring GDPR compliance became a growing concern. “Ho ho ho!We’re drowning in inefficiency!Help us save Christmas!”—Santa Claus Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## The Solution To address Santa’s challenges, Flobotics deployed a set of tailored automations: ### Process 1:Automated Letter Processing Using OCR and NLP,we built an automation capable of: - Scanning millions of letters daily - Translating illegible handwriting into actionable data - Categorizing requests and adding them to Santa’s CRM system(CandyCane 360) Automation outcome:Work previously requiring more than 200 elves per day now runs on autopilot. ### Process 2:Naughty-or-Nice List Audit We implemented a rule-based evaluation automation that: - Cross-references school reports, parent feedback, and Elf-on-the-Shelf logs - Generates a real-time Naughty-or-Nice score for each child Business outcome:Higher accuracy, reduced bias, and a 34% reduction in parent complaints. ### Process 3:Gift Packing Automation We introduced gift-wrapping automations that handle: - Selecting the most efficient, eco-friendly wrapping method for each gift - Choosing paper color, bag style, and festive patterns - Reducing rework and stress in packing workflows Automation outcome:Packing time reduced by 78% and wrapping quality improved significantly. ### Process 4:Sleigh Route Optimization Using machine learning and logistics optimization, we built an automation that: - Analyzes weather patterns, air traffic, and global time zones in real time - Optimizes routes for efficiency and minimal reindeer fatigue Business outcome:Reduced flight time by 1,275 hours and fewer unnecessary stops. ### Process 5:GDPR-Compliant Data Management We created an automation that anonymizes sensitive data while maintaining personalized delivery records. Automation outcome:Zero breaches reported during the 2024 holiday season. ## The Outcome - Automated work previously handled by more than 200 elves, freeing the team for higher-value tasks - Saved 1,275 reindeer hours, improving wellbeing and operational reliability - Generated over 600% ROI(Return on Incredibility) - Automated over 2.2 billion actions this season to deliver on-time worldwide ## What’s Next? We continue working with Santa and his team on additional automation opportunities, including: - Autonomous drone-based gift deliveries for hard-to-reach rooftops - AI-powered toy trend forecasting dashboard - A real-time Elf Happiness Index(EHI)dashboard ## Thank You Thank you for trusting Flobotics, Mr.Claus.A special thanks to Santa and Rudolph for recommending us to the Tooth Fairy and the Easter Bunny—we’re already working on new automations to support their operations as well. Written byMichał Rejman Chief Marketing Officer at Flobotics. [More from Michał](https://www.flobotics.io/our-editorial-team#rejman) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # T-Bank SBA Loan Processing Automation | Flobotics Canonical: https://www.flobotics.io/blog/t-bank Author: Michał Rejman Published: 2026-09-06 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/T Bank [RPA](https://www.flobotics.io/blog?category=rpa) # T Bank [Michał RejmanChief Marketing Officer at Flobotics](https://www.flobotics.io/our-editorial-team#rejman) Published September 06, 2026Updated September 1, 2026 On this page - [Client](#client) - [The Challenge](#the-challenge) - [The Solution](#the-solution) - [The Outcome](#the-outcome) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Client T-Bank is a financial institution based in Texas and a partner with an entrepreneurial credit philosophy designed around business and practice needs. It is ranked among the Top 200 Healthiest Banks in the US in LendingTree’s 2021 analysis and is one of the leading SBA loan providers nationwide. ## The Challenge The SBA Paycheck Protection Program was a $699 billion US government loan initiative introduced during the COVID-19 crisis. Applications were open for limited windows, and once funds were depleted, applicants had to wait for new pools to open while the submission website remained unavailable. T-Bank needed to maximize the number of loan applications submitted before funding ran out and partnered with Flobotics to build an RPA solution. The implementation came with challenges. The loan submission website was frequently unavailable due to traffic spikes, and server overloads caused crashes during the final submission step, forcing users to re-enter data repeatedly. Time was critical, and changes had to be applied directly on a live system. ## The Solution Flobotics began work the moment the new funding pool opened and the website became available. An attended RPA robot was developed to work alongside a human operator, automatically filling out loan applications in seconds. The robot extracted applicant data from CSV files, navigated the submission website, and populated forms automatically. The operator only confirmed submission by clicking the final button. The automation also handled website instability. If the site crashed, the bot paused and resumed immediately once it recovered, eliminating repetitive manual input. The submission process was reduced from 10–15 minutes to just 6 seconds. ## The Outcome Through automation, the client saved over 200 hours of manual work and enabled the submission of more than 1,000 loan applications, representing approximately $100 million in applications and $5 million in revenue. The solution was developed in about 8 hours, allowing the client to see ROI almost immediately, without engaging internal staff or incurring high development costs. We continue to help finance organizations automate accounting and financial workflows through practical RPA solutions. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byMichał Rejman Chief Marketing Officer at Flobotics. [More from Michał](https://www.flobotics.io/our-editorial-team#rejman) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # XiFin vs. TELCOR vs. Quadax Canonical: https://www.flobotics.io/blog/xifin-vs-telcor-vs-quadax Published: 2026-09-06 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/XiFin vs. TELCOR vs. Quadax # XiFin vs. TELCOR vs. Quadax Published September 06, 2026Updated September 1, 2026 On this page - [The $1.6M Question: When Revenue-Share RCM Stops Making Financial Sense](#thed16mquestionwhenrevenuesharercmstopsmakingfinancialsense) - [XiFin: What Revenue-Share Actually Buys You](#xifinwhatrevenueshareactuallybuysyou) - [TELCOR: The Fixed-Cost Reality Check](#telcorthefixedcostrealitycheck) - [Quadax: Staged Transition as Risk Mitigation](#quadaxstagedtransitionasriskmitigation) - [Decision Framework: Capital Allocation, Not Software Selection](#decisionframeworkcapitalallocationnotsoftwareselection) - [Under the Microscope: What the Numbers Don't Tell You](#underthemicroscopewhatthenumbersdonttellyou) - [Strategic Implications: The Five-Year View](#strategicimplicationsthefiveyearview) - [Conclusion: Do You Know What You'll Pay Your Vendor in Three Years?](#conclusiondoyouknowwhatyoullpayyourvendorinthreeyears) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## The $1.6M Question: When Revenue-Share RCM Stops Making Financial Sense For a diagnostic laboratory processing $50 million in net collections annually, the difference between revenue-share billing and a fixed-cost platform represents approximately $1.59 million per year in direct operational expense. That figure alone should command board-level attention–yet most laboratory CFOs evaluate revenue cycle management platforms as technology decisions rather than capital allocation frameworks. The choice between XiFin, TELCOR, and Quadax is not fundamentally about features, user interface design, or vendor reputation. It is a question of cost structure: Do you accept variable costs that scale linearly with revenue? Do you possess the organizational capital–both financial and human–to absorb a fixed-cost structure? Or do you require a staged transition that allows progressive in-housing as internal capability matures? This analysis treats that question with the financial rigor it demands. ## XiFin: What Revenue-Share Actually Buys You XiFin's market position rests on a straightforward value proposition: outsource your entire revenue cycle operation to a cloud-based platform that charges a percentage of what it collects. Revenue-share pricing for XiFin is not publicly disclosed, but industry-reported ranges place it between 3.5% and 5.5% of net collections, with rates varying by volume tier and contractual structure (Source: HFMA Revenue Cycle Benchmarking Report, 2024). Using a conservative 4% estimate, a laboratory generating $25 million in net collections pays $1 million annually. At $50 million, that figure doubles to $2 million. The model's appeal is immediate: zero upfront capital expenditure, no recruitment burden for specialized billing staff, and instant access to XiFin's reported 2,500+ payer connections (vendor-reported; not independently verified). For early-stage laboratories–those below $10 million in collections or lacking human resources infrastructure to hire and retain specialized billing talent–this structure makes defensible sense. XiFin absorbs staffing volatility, manages payer connectivity maintenance, and delivers operational predictability. The platform's architecture as a native double-entry accounting system also simplifies ASC 606 revenue recognition compliance, a non-trivial advantage for organizations facing audit scrutiny. But the model's linearity creates a structural problem: marginal costs do not decline as volume scales. As McKinsey Health's research on healthcare administrative automation notes, "Administrative functions in healthcare, including billing and claims processing, are among the highest-ROI targets for process standardization precisely because marginal costs don't scale linearly with revenue." At $15 million in collections, XiFin's 4% fee equals $600,000 annually–a figure that begins to approach the total cost of ownership for an in-house operation. Beyond that threshold, the financial logic deteriorates rapidly. ## TELCOR: The Fixed-Cost Reality Check TELCOR operates on fundamentally different economics. Rather than taking a percentage of collections, TELCOR provides software licensing for internal billing departments to manage operations directly. Based on peer-reported implementations and industry analyst estimates, TELCOR licensing and implementation costs typically range from $230,000 to $550,000 in Year 1, with ongoing annual maintenance fees of $80,000–$150,000 (Source: Healthcare IT News vendor analyses; peer benchmarking data). Amortizing implementation costs over five years and assuming mid-range maintenance fees produces an annual software cost of approximately $130,000. Add 2.5 full-time billing specialists at a fully-loaded cost of $65,000 each–a figure drawn from AHA Revenue Cycle Staffing & Cost-to-Collect Data, which places specialized medical billing FTE costs between $55,000 and $85,000 annually–and total annual cost reaches approximately $292,500. Including clearinghouse fees of $20,000, total cost of ownership stabilizes around $312,500. The breakeven analysis is stark: $10M | $400,000 | $312,500 | $(87,500) – XiFin cheaper | $15M | $600,000 | $312,500 | $287,500 | $25M | $1,000,000 | $312,500 | $687,500 | $50M | $2,000,000 | $312,500 | $1,687,500 | ‍ Assumptions: XiFin pricing at 4% of net collections includes BPO staff, payer connectivity, and platform license. TELCOR total cost includes $130K annual software cost (implementation amortized over five years), 2.5 FTE at $65K loaded cost, and $20K clearinghouse fees. Does not include one-time migration costs ($50K–$150K) or opportunity cost of accounts receivable disruption during cutover. Breakeven model assumes successful implementation with 15% during migration, breakeven shifts to approximately $20M net collections. Organizations with internally managed RCM operations and purpose-built software platforms consistently outperform outsourced models on cost-to-collect metrics after the 18-to-24-month implementation maturity window (Source: Optum RCM Operational Efficiency Benchmarks). But that maturity window is not trivial. TELCOR hands you the operational engine–but you must staff, train, and manage it. Industry case reporting suggests that 20–30% of RCM platform migrations encounter timeline or budget overruns, most commonly due to underestimated data mapping complexity and insufficient parallel-run periods (Source: Becker's Hospital Review migration case studies, 2023–2024). CFOs evaluating TELCOR must allocate contingency budget for extended dual-system operations and plan for a 60–90-day accounts receivable stabilization period. For organizations without cash flow reserves to absorb that disruption, migration risk alone may disqualify the fixed-cost model–regardless of long-term savings. TELCOR also requires managing payer connectivity through external clearinghouses such as Availity or Change Healthcare. For laboratories with narrow payer mixes–fewer than 50 payers in single-state operations–this adds minimal burden. For multi-state labs managing 200+ payer relationships, XiFin's pre-built integrations reduce initial setup complexity, though this advantage diminishes after the first 12–18 months of operation. The financial question is not whether TELCOR is cheaper at scale–it objectively is–but whether your organization has the human capital, implementation risk tolerance, and cash flow buffer to execute the transition successfully. ## Quadax: Staged Transition as Risk Mitigation Quadax occupies the middle ground, offering three delivery models: pure SaaS (fixed platform fee), full business process outsourcing (percentage-based pricing), or hybrid. The hybrid structure is particularly noteworthy: Quadax charges a platform fee for software access plus a percentage-based fee only on claims volume processed through its BPO service. Organizations managing front-end billing in-house pay only for denial management and appeals outsourced to Quadax, creating a variable cost structure that declines as internal capability matures. This model addresses TELCOR's implementation cliff. Rather than executing a full cutover in one fiscal quarter, a laboratory can begin with full outsourcing through Quadax, gradually bring clean-claim generation in-house as staff are trained, and ultimately retain only complex denial management as outsourced–without changing the underlying software platform. The financial transition is incremental rather than binary. Quadax's technical strength lies in exception-based workflow automation. The platform's rules engine scrubs claims aggressively before submission, presenting staff only with claims that fail customized edits. For molecular diagnostics and genetic testing–where prior authorization and medical necessity rules produce denial rates of 18–25% compared to routine lab testing's 10–15%–this front-end rigor delivers measurable financial impact. The cost of a denied claim–including resubmission labor, appeals cycles, and write-off risk–is estimated at $25 to $117 per denial depending on complexity (Source: RevCycle Intelligence Denial Management Analysis). For a laboratory processing 50,000 claims annually with a baseline 12% denial rate, a 2% improvement in denial prevention eliminates 1,000 denials. At an average rework cost of $50, direct savings equal $50,000 annually–not including faster cash conversion and reduced days in accounts receivable, which are harder to quantify but operationally significant. Quadax's flexibility carries a governance cost. Organizations operating in hybrid mode must maintain clear accountability structures to avoid the operational no-man's-land where internal teams assume outsourced functions are managed and vice versa. Contractual service-level agreements must explicitly delineate responsibility boundaries–particularly for claims that fail initial edits and enter the denial management workflow. On ASC 606 compliance, Quadax achieves regulatory readiness through integration with external ERP systems such as Epic or Oracle Health, adding middleware complexity compared to XiFin's native general ledger architecture. This is an operational distinction–ease of integration–not a compliance gap. All three platforms support ASC 606 revenue recognition; the difference lies in how much ERP customization is required during implementation. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Decision Framework: Capital Allocation, Not Software Selection The choice between XiFin, TELCOR, and Quadax resolves to three questions: If you expect collections to double from $15M to $30M, your XiFin costs will grow from $600,000 to $1.2 million annually. TELCOR's costs will increase marginally–perhaps one additional FTE–but remain structurally fixed. The present value of that differential over five years is material. Can your organization tolerate a 60-day cash flow slowdown during platform cutover? Do you have HR infrastructure to recruit, onboard, and retain specialized billing staff in a labor market where turnover costs $15,000–$30,000 per hire? If the answer is no, revenue-share or hybrid models mitigate execution risk at the cost of long-term margin compression. XiFin and full-BPO Quadax arrangements create structural dependency: your revenue cycle exists inside their operational perimeter. TELCOR returns control to your internal teams–but also returns accountability. If your billing manager leaves and denial rates spike 8%, there is no vendor to blame. That is not a software risk; it is an organizational risk. | 3.5–5.5% net collections (revenue-share) | Fixed license + FTE ($312K annual est.) | Flexible: SaaS, BPO, or hybrid | | Below ~$12–15M collections | Above ~$15M collections | Depends on hybrid mix; typically $10–20M | | Outsourced (vendor-managed) | Internal (client-managed, 2.5–6 FTE) | Hybrid option (internal front-end, outsourced appeals) | | Native GL architecture (low integration lift) | ERP integration required (moderate complexity) | ERP integration required (moderate complexity) | | Low (outsourced continuity) | High (60–90 day AR stabilization period) | Medium (staged transition available) | ‍ ## Under the Microscope: What the Numbers Don't Tell You Three critical assumptions underlie this analysis, and each warrants scrutiny: If TELCOR implementation costs exceed budget by 100%–not unprecedented in complex ERP integrations–the breakeven threshold shifts from $15M to approximately $22M in collections. Organizations evaluating fixed-cost platforms should structure vendor contracts with cost caps and phased payment milestones tied to operational go-live, not project initiation. Historical case data suggests denial rates can increase 10–15% during the first 90 days post-cutover as staff acclimate to new workflows and claim edits are recalibrated (Source: HFMA implementation case studies). For a $25M lab with a baseline 12% denial rate, a 15% increase in denials during transition represents approximately 900 additional denials–or $45,000 in rework costs at $50 per denial. Migration budgets must include contingency reserves for temporary denial rate increases. XiFin's claimed 2,500+ payer connections sound comprehensive, but operational relevance depends on your specific payer mix. If 90% of your volume flows through 20 major payers, clearinghouse-based connectivity (TELCOR/Quadax) delivers functionally identical results. The connectivity advantage matters primarily during initial setup for labs with highly fragmented payer portfolios–typically multi-state operations with significant Medicaid exposure. ## Strategic Implications: The Five-Year View Revenue cycle management platforms are not two-year commitments. Implementation effort, staff training investment, and integration with clinical systems create switching costs that make these effectively five-to-seven-year decisions. The financial question CFOs must answer is not "Which platform is cheaper today?" but rather "What will I pay this vendor at my projected volume three years from now?" For laboratories on aggressive growth trajectories–particularly those in molecular diagnostics, oncology testing, or genetic screening where reimbursement models are stabilizing and volumes are scaling–fixed-cost platforms compound financial advantage over time. A lab growing from $20M to $50M in collections over five years will pay XiFin an incremental $1.2 million annually by year five. That cumulative cost differential funds significant internal capability building–or flows directly to EBITDA. For laboratories with uncertain volume outlook, regulatory exposure requiring frequent process redesign, or limited internal HR capacity, revenue-share models trade long-term margin for operational flexibility. That is not inherently inefficient–it is risk transfer. The question is whether you are paying a fair price for that transfer. Quadax's hybrid model offers a third path: staged de-risking. Begin with full outsourcing, incrementally in-house as capability matures, and retain complex denial management as outsourced. The financial profile shifts gradually from variable to semi-fixed, allowing organizations to match cost structure evolution to organizational capability development. The most expensive decision is often the one delayed. Every quarter a $30M laboratory operates on a 4% revenue-share model while possessing the organizational maturity to execute a fixed-cost migration represents $300,000 in foregone margin. Compounded over five years, that opportunity cost exceeds $7.5 million–enough to fund a complete RCM department build-out with redundancy. ## Conclusion: Do You Know What You'll Pay Your Vendor in Three Years? The laboratory revenue cycle management market is not undergoing a software revolution–it is experiencing a financial model reckoning. Organizations are increasingly questioning why administrative functions with near-zero marginal cost at scale should be priced as percentage-of-revenue arrangements. XiFin, TELCOR, and Quadax each represent defensible financial architectures for specific organizational contexts. XiFin makes sense for early-stage labs prioritizing operational simplicity over long-term cost optimization. TELCOR delivers superior unit economics at scale but demands implementation execution discipline and cash flow resilience. Quadax provides optionality–the ability to transition gradually without platform migration risk. The question is not which platform is "best." The question is which cost structure aligns with your growth trajectory, risk tolerance, and organizational capability over a five-to-seven-year horizon. If you cannot confidently project what you will pay your RCM vendor at your forecasted volume in three years, you do not yet have enough data to make this decision. Keeping your current platform? See how we automate [laboratory RCM workflows](https://www.flobotics.io/who-we-help/laboratories) and [work around XiFin](https://www.flobotics.io/xifin-in-rcm). Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # FHIR in Revenue Cycle Management | Flobotics Canonical: https://www.flobotics.io/blog/fhir Author: Krzysztof Szwed Published: 2026-08-31 Updated: 2026-09-03 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/FHIR [AI](https://www.flobotics.io/blog?category=ai)[Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # FHIR [Krzysztof SzwedHead of Delivery at Flobotics](https://www.flobotics.io/our-editorial-team#szwed) Published August 31, 2026Updated September 3, 2026 On this page - [FHIR and Revenue Cycle Management: The $19.7 Billion Question No CFO Can Ignore](#fhirandrevenuecyclemanagementthed197billionquestionnocfocanignore) - [The Regulatory Calendar Is Non-Negotiable](#theregulatorycalendarisnonnegotiable) - [Three Operational Pain Points With Measurable Financial Drag](#threeoperationalpainpointswithmeasurablefinancialdrag) - [Prior Authorization Throughput: The Hidden Working Capital Problem](#priorauthorizationthroughputthehiddenworkingcapitalproblem) - [Denial Rates: Technical Failures You're Paying to Fix](#denialratestechnicalfailuresyourepayingtofix) - [Revenue Velocity: The CFO's Real Concern](#revenuevelocitythecfosrealconcern) - [The Barriers No Vendor Slide Deck Mentions](#thebarriersnovendorslidedeckmentions) - [What Works: Operational Patterns From Early Adopters](#whatworksoperationalpatternsfromearlyadopters) - [A 90-Day Action Framework for Revenue Cycle Leaders](#a90dayactionframeworkforrevenuecycleleaders) - [The Cost of Waiting](#thecostofwaiting) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## FHIR and Revenue Cycle Management: The $19.7 Billion Question No CFO Can Ignore The U.S. hospital system burns [$19.7 billion annually](https://premierinc.com/newsroom/policy/claims-adjudication-costs-providers-257-billion-18-billion-is-potentially-unnecessary-expense) wrestling with prior authorization. That figure–published by Premier Inc.–isn't an IT problem. It's a balance sheet hemorrhage masquerading as administrative overhead. And in 22 months, it becomes a regulatory compliance issue with teeth. On January 1st, 2027, CMS flips the switch on mandatory FHIR-based Prior Authorization APIs under the [CMS-0057-F Final Rule](https://www.cms.gov/initiatives/burden-reduction/overview/interoperability/policies-regulations/cms-interoperability-prior-authorization-final-rule-cms-0057-f). Every Medicare Advantage, Medicaid, and CHIP payer must deliver authorization decisions within 72 hours for urgent requests and seven days for standard cases–through standardized data exchange. Organizations still treating Fast Healthcare Interoperability Resources (FHIR) as an IT side project will discover, painfully, that regulatory deadlines don't bend to legacy workflows. The question isn't whether FHIR in RCM matters. The question is: what's your number? What does prior authorization cycle time cost your organization per service line, per denied claim, per day your capital sits locked in accounts receivable? ## The Regulatory Calendar Is Non-Negotiable Healthcare loves pilot programs and phased rollouts. CMS just removed that luxury. The [Provider Access API mandate](https://www.cms.gov/newsroom/fact-sheets/cms-interoperability-prior-authorization-final-rule-cms-0057-f) went live January 1st, 2026. The Prior Authorization API requirement follows twelve months later. Both hinge on FHIR's ability to move structured clinical data between systems without fax machines, phone trees, or manual chart abstraction. Scope isn't limited to a handful of high-volume procedures. Every covered transaction–authorization requests, eligibility verification, clinical documentation–falls under the rule for affected payers. The timeline compresses authorization windows to levels that break manual processes. Seventy-two hours means business hours, not calendar days. Seven-day standard turnaround eliminates float time that historically masked workflow inefficiency. This isn't CMS experimenting with incentives. It's federal rulemaking with audit mechanisms and corrective action protocols. Payers face enforcement. Providers face something worse: structural cash flow drag in an industry already operating on single-digit operating margins. When your contracted payer can't deliver API access by deadline, you inherit the operational risk–denials, appeals, delayed revenue, patient leakage to competitors who sorted this out earlier. ## Three Operational Pain Points With Measurable Financial Drag ### Prior Authorization Throughput: The Hidden Working Capital Problem Current-state prior authorization for complex procedures averages 11 days from submission to decision, according to [Becker's Hospital Review 2023 benchmarking](https://www.beckershospitalreview.com/finance/medicare-advantage-prior-authorizations-19-numbers-to-know/). That's not processing time–it's elapsed time. Submission, clinical documentation requests, manual review, back-and-forth clarification, final determination. Each day adds float to your Days in A/R and pushes high-margin service lines further from cash conversion. Orthopedic surgery, oncology infusions, cardiology interventions–these aren't volume plays. They're margin engines. An 11-day PA cycle on a $47,000 joint replacement isn't an administrative delay. It's working capital tied up and patient anxiety creating opportunities for them to seek care elsewhere. FHIR-native workflows eliminate the documentation request loop. Structured clinical data–problem lists, medications, lab results, imaging reports–travels with the authorization request in machine-readable format. The payer's automated criteria matching engine runs immediately. No human rekeying. No "we need additional records" holding pattern. Organizations operating in high-interoperability environments report PA processing speeds 2-3x faster than low-interoperability peers, according to [HFMA analysis](https://www.hfma.org/revenue-cycle/billing-and-collections/prior-authorization-is-draining-revenue-which-is-why-automation-has-become-a-strategic-imperative/). That's not incremental improvement. It's structural advantage in revenue velocity. ### Denial Rates: Technical Failures You're Paying to Fix Kodiak Solutions' benchmarking analysis, cited by [HFMA](https://www.hfma.org/finance-and-business-strategy/hospital-financial-and-revenue-cycle-benchmarks-paint-a-complicated-picture-heading-into-the-new-year/), pegs initial denial rates at 10-15% across hospital systems. Drill into root cause, and 25-30% trace back to prior authorization issues–missing documentation, eligibility mismatches, clinical information gaps at the point of claim submission. These aren't medical necessity denials requiring clinical judgment. They're technical failures: the right information didn't reach the right system at the right time. Each denied claim costs $118 to rework, per [Becker's Hospital Review analysis](https://www.beckershospitalreview.com/finance/denial-rework-costs-providers-roughly-118-per-claim-4-takeaways/). That's staff time, system overhead, opportunity cost of delayed payment. Scale that across a mid-size system processing 500,000 claims annually. A 10-point improvement in first-pass resolution–moving from 85% to 95% clean claim rate–eliminates 50,000 rework cycles. That's $5.9 million in annual administrative cost avoidance before you count revenue acceleration from faster payment. FHIR attacks the root cause. When clinical context travels with the claim in structured format, payer adjudication systems match against medical policy criteria without human intervention. [Oracle Health implementation data](https://docs.oracle.com/en/industries/health/millennium-platform-apis/fhir-authorization-framework/) shows 20-35% improvement in first-pass resolution rates for FHIR-native submissions. The mechanism is straightforward: eliminate data latency, compress review cycles, reduce technical rejection surface area. ### Revenue Velocity: The CFO's Real Concern Days in A/R isn't an RCM metric. It's a proxy for how efficiently you convert clinical work into liquid capital. Prior authorization delays stretch A/R. Denials stretch it further. Appeals stretch it until patients forget they owe you money and your bad debt reserve climbs. Organizations implementing API-first workflows–eligibility verification, real-time authorization status, automated claim enrichment–report 5-10% administrative cost reduction within 24 months, according to the [CAQH Index](https://www.caqh.org/insights/caqh-index-report). The larger impact lives in cash conversion cycle compression. When PA turnaround drops from 11 days to 4 days, that's seven days of freed working capital per transaction. Multiply across high-value service lines and you're looking at material balance sheet impact. CMS's own [Regulatory Impact Analysis for the Final Rule](https://www.cms.gov/newsroom/press-releases/cms-finalizes-rule-expand-access-health-information-improve-prior-authorization-process) projects $1.5 billion in system-wide annual savings by end of the 10-year implementation window. That number assumes full adoption and payer compliance. The math works because it eliminates duplicated effort–providers stop generating paper clinical summaries, payers stop manually abstracting charts, both sides stop playing phone tag to resolve missing data elements. Individual organizational savings scale with claim volume and authorization intensity. A community hospital running 200,000 claims annually with moderate PA burden won't see $5.9 million in savings. A regional health system with complex surgical programs and specialty pharmacy spend will exceed it. ## The Barriers No Vendor Slide Deck Mentions Mandating FHIR APIs doesn't magically create interoperability. It creates compliance pressure. The path from regulatory requirement to operational benefit runs through legacy system integration, vendor readiness gaps, workflow retraining, and capital constraints that hit small and mid-size providers harder than integrated delivery networks. Legacy EHR integration isn't plug-and-play. Epic, Oracle Health (formerly Cerner), and Meditech occupy different points on the FHIR maturity curve. Epic's FHIR API ecosystem is well-developed; smaller regional vendors lag. If your core RCM system was implemented in 2012 and hasn't seen a major upgrade, the technical lift to enable real-time API connectivity involves middleware, interface engines, and HL7-to-FHIR translation layers. [HIMSS infrastructure surveys](https://www.himss.org) suggest full-stack integration runs $250,000 to $750,000 for mid-size systems, depending on existing architecture and vendor cooperation. That excludes staff retraining and workflow redesign. Vendor readiness variance is real. Not all EHR platforms ship production-grade FHIR APIs today. Some offer limited implementations–eligibility checks but not full clinical data exchange. Others charge separately for API access that CMS now mandates payers provide. Before committing to an implementation timeline, audit your contracted payers: which ones have live Provider Access APIs? Which ones publish their FHIR endpoint documentation? If your largest commercial payer hasn't launched compliant APIs six months before the deadline, you inherit operational risk regardless of your internal readiness. Small and mid-size providers face resource asymmetry. A 1,200-bed academic medical center has integration teams and capital budgets. A 40-physician specialty practice running a thin RCM staff doesn't. For smaller organizations, the implementation path likely runs through SaaS revenue cycle platforms offering FHIR-native connectivity as a built-in feature rather than custom integration. That shifts cost from capital expense to operating expense but doesn't eliminate the need for staff training on new workflows. Causation, not just correlation. FHIR doesn't reduce denials through magic–it reduces specific denial types by fixing data availability problems. Technical denials (missing patient history, eligibility mismatches, incomplete clinical documentation at submission) drop because structured data exchange eliminates those gaps. Medical necessity denials requiring clinical judgment? Those still require human review. FHIR improves the speed and data quality feeding that review but doesn't replace it. Organizations expecting across-the-board denial rate improvements without differentiating denial types will misforecast ROI. Timeline to measurable impact isn't instantaneous. CFOs rightly ask: when do we see the number move? The honest answer depends on workflow complexity and payer adoption rates. First measurable impacts–faster eligibility verification, reduced manual data entry–appear within 90-120 days for standard workflows, based on [HFMA case reporting](https://www.hfma.org/legal-and-regulatory-compliance/compliance/new-regulations-are-projected-to-bring-providers-a-measure-of-relief-from-prior-authorization-headaches/). System-wide denial rate improvement lags by 6-9 months as claim volume cycles through the new process and historical denials clear appeals queues. Organizations piloting FHIR integration on single high-volume PA workflows (orthopedic pre-certification, for example) can demonstrate proof-of-concept faster than those attempting enterprise-wide rollouts. CMS enforcement targets payers, but providers inherit friction. The Final Rule penalizes non-compliant payers through audits and corrective action. Providers can't force a contracted payer to launch a compliant API by deadline. If your second-largest commercial payer misses the January 2027 cutoff, you're left managing dual workflows–FHIR for compliant payers, legacy fax/portal processes for laggards. Document payer non-compliance. Escalate through contracts and provider relations. But budget for hybrid-state operations lasting 12-18 months post-deadline as enforcement pressure catches up with stragglers. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## What Works: Operational Patterns From Early Adopters The organizations seeing measurable ROI from FHIR investment share common implementation patterns. They didn't boil the ocean. They targeted high-friction, high-volume workflows where real-time data exchange delivers immediate value. Start with API-first eligibility verification. Before tackling prior authorization complexity, prove the technical integration works on a simpler use case. Real-time eligibility checks via FHIR APIs eliminate batch processing delays and catch coverage changes before services render. It's a low-risk pilot with fast feedback loops. If your vendor integration or payer API access has bugs, you discover them here rather than mid-authorization on a $200,000 transplant case. Prioritize highest-denial service lines. Not all procedures carry equal PA burden. Orthopedic surgery, bariatric procedures, advanced imaging, specialty pharmacy–these hit authorization bottlenecks harder than primary care visits. Analyze your denial data by DRG and CPT code. Identify the 20% of procedures generating 60% of PA-related denials. Route those through FHIR-native workflows first. The financial impact concentrates where margin and administrative friction intersect. Differentiate by organizational profile. Large integrated delivery networks can justify internal build teams and custom EHR integrations. Specialty practices and independent labs lack that luxury–but also face narrower workflow scope. A pathology lab doesn't manage prior authorization but still benefits from automated eligibility verification and claim data enrichment. SaaS RCM platforms offering pre-built FHIR connectors reduce implementation complexity for smaller organizations. The trade-off: less customization, more reliance on vendor roadmap alignment with regulatory timelines. Establish baseline metrics before implementation. You can't measure improvement without knowing the starting point. Current PA cycle time by procedure type. First-pass claim resolution rate. Denial rate segmented by denial reason. Rework cost per claim. These aren't nice-to-have KPIs–they're how you calculate actual ROI and justify continued investment when you hit implementation friction six months in. ## A 90-Day Action Framework for Revenue Cycle Leaders Strategic vision doesn't survive contact with operational reality without concrete next steps. Here's the sequence that works regardless of organization size: Days 1-30: Audit current state. Inventory contracted payers and their FHIR API availability. Which ones publish live Provider Access APIs today? Which ones have announced Prior Authorization API launch timelines? For those missing, document gap and escalate through payer relations. Separately, audit internal tech stack: does your EHR expose FHIR endpoints? Does your RCM platform support API-based data exchange, or is everything batch file transfers and manual portals? Days 31-60: Assess financial impact zones. Pull twelve months of denial data. Segment by denial reason, procedure type, payer, and service line. Calculate the current cost: PA cycle time x claim volume x margin per procedure. Identify the highest-pain workflows–where authorization delays and denial rates hurt most. These become pilot candidates. Cross-reference against payer API readiness. If your highest-volume payer lacks a compliant API, your pilot needs a fallback plan. Days 61-90: Launch bounded pilot. Pick one high-volume, high-friction PA workflow. Orthopedic pre-certification. Cardiology procedure authorization. Specialty infusion approval. Route it through FHIR-based submission if payer APIs allow. Measure PA cycle time, first-pass approval rate, and staff time per transaction. Run it parallel to legacy workflow initially–don't cut over until data confirms the new process performs. Use this pilot to surface integration bugs, staff training gaps, and payer API reliability issues before scaling. Beyond 90 days: Expand based on evidence. If the pilot demonstrates measurable cycle time reduction and denial rate improvement, expand to additional procedure types and payers. If it surfaces major technical barriers or payer non-compliance, you've learned that at contained cost rather than betting the entire RCM operation on a flawed implementation. For organizations lacking internal integration capacity, the evaluation shifts to SaaS RCM platforms. The right questions: Does the platform offer native FHIR connectivity to major payers? How do they handle payer API changes and versioning? What's their track record on regulatory deadline compliance? Can you pilot on a subset of claim volume before full migration? These platforms trade capital expense for operating expense and custom control for faster deployment–appropriate trade-offs for smaller organizations facing the same January 2027 deadline as large health systems. ## The Cost of Waiting CMS projects system-wide savings beginning 2026-2027 as implementation scales. Individual organizations realize returns in proportion to claim volume, PA intensity, and execution quality. The inverse matters more: what's the cost of sitting this out? Every month of delayed implementation is another month of 11-day PA cycles, $118 rework costs per denied claim, and working capital locked in aging A/R. That's the operational cost. The strategic cost is competitive position. In markets where patients have choice–elective procedures, specialist selection, high-deductible plan decisions–operational friction creates leakage. When a competitor offers faster authorization and fewer billing surprises, margin walks out the door. January 2027 isn't a suggestion. It's a regulatory hard stop. Organizations treating FHIR implementation as an IT checkbox will discover, in real-time, that cash flow doesn't care about technical complexity. It cares about how fast you convert clinical work into collected revenue. The systems that sorted this out in 2025 and 2026 will be running at structurally lower administrative cost and higher revenue velocity while laggards scramble to retrofit compliance into workflows designed for fax machines. The $19.7 billion PA burden isn't distributed evenly. Your share depends on service mix, payer contracts, and authorization intensity. But the shape of the problem is universal: manual processes don't scale to 72-hour regulatory mandates. The organizations that win this transition won't be the ones with the most ambitious IT roadmaps. They'll be the ones who identified the highest-cost friction points, piloted solutions with measurable KPIs, and executed relentlessly through vendor delays and payer non-compliance. That's not transformation. It's operational discipline meeting regulatory reality. ## FAQ: Is medical billing the same as medical coding? No. A coder translates clinical documentation into diagnosis and procedure codes. A biller uses those codes to build and submit the claim, then manages everything that happens to it afterward. Can a patient submit their own prior authorization? No, not usually. Prior authorization requests generally have to come from the treating provider's office, since insurers require clinical documentation only a provider can supply — a patient can push their provider's staff to submit or resubmit one, but can't file it independently. How often does Medicaid eligibility get checked? Under current federal rules, most Medicaid enrollees have their eligibility redetermined once every 12 months. That's changing under the 2025 One Big Beautiful Bill Act, which moves ACA expansion-group enrollees to eligibility checks every six months instead of annually. How many types of denials are there? Most RCM teams group denials into two broad categories, hard and soft, but denial-management systems often track a dozen or more specific sub-categories such as eligibility, authorization, coding, timely filing, and medical necessity. The exact count depends on how granular a given payer's or vendor's classification system is. Written byKrzysztof Szwed Head of Delivery at Flobotics. [More from Krzysztof](https://www.flobotics.io/our-editorial-team#szwed) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RCMHealthcare ### Medical Coding Automation: Why (and How) Should You Start? Medical coding services, automated: how RPA improves claims accuracy and cuts manual coding errors for healthcare providers. Karl MielnickiMay 13, 2022 ](https://www.flobotics.io/blog/medical-coding)[ RCMRPAHealthcare ### Medical Billing Management: Best Practices, Key Metrics and Automation Medical billing management: the 8-stage billing cycle, the metrics and reports that show revenue leakage, and 8 best practices to fix it. Yana PokoraJuly 25, 2023 ](https://www.flobotics.io/blog/medical-billing-management) [All articles →](https://www.flobotics.io/blog) --- # RCM Automation for Multi-Specialty Physician Groups Canonical: https://www.flobotics.io/blog/rcm-automation-for-multi-specialty-physician-group Author: Jędrzej Szymula Published: 2026-08-18 Updated: 2026-09-08 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/RCM Automation for Multi-Specialty Physician Groups [RCM](https://www.flobotics.io/blog?category=rcm) # RCM Automation for Multi-Specialty Physician Groups [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published August 18, 2026Updated September 8, 2026 On this page - [Multi-Specialty Physician Groups: Why Your RCM Automation Is Structurally Wrong](#multispecialtyphysiciangroupswhyyourrcmautomationisstructurallywrong) - [The Hidden Tax of Generic Automation](#thehiddentaxofgenericautomation) - [Why RPA Can't Scale Across Specialties](#whyrpacantscaleacrossspecialties) - [What Specialty-Aware Actually Means](#whatspecialtyawareactuallymeans) - [The Measurable Difference](#themeasurabledifference) - [Prerequisites for Success](#prerequisitesforsuccess) - [What to Do Monday Morning](#whattodomondaymorning) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Multi-Specialty Physician Groups: Why Your RCM Automation Is Structurally Wrong The cost-to-collect metric tells an uncomfortable story. Multi-specialty physician groups without specialty-specific automation tend to carry a materially higher cost-to-collect than single-specialty practices, since fragmented coding rules and prior-authorization workflows compound operational overhead. This isn't a management problem. It's an architecture problem. Most RCM directors inherit the same flawed assumption: that a multi-specialty group is simply a scaled-up version of a single-specialty practice. It isn't. Complexity doesn't scale additively in multi-specialty environments–it scales multiplicatively. Orthopedics plus oncology plus cardiology isn't three times the complexity. It's three coding rule sets multiplied by three prior authorization workflows multiplied by cross-specialty visit patterns multiplied by payer-specific carve-outs. No unified automation model can handle this without domain segmentation. The revenue cycle vendors know this. They sell anyway. ## The Hidden Tax of Generic Automation Aggregate metrics mask structural problems. Denial rates for multi-specialty groups without specialized automation vary widely by service line, and aggregate figures can mask where the bleeding actually occurs. Orthopedic claims, for instance, can face materially higher prior-authorization denial rates with certain commercial payers–while behavioral health requires entirely different appeal logic for medical necessity determinations. A denial rate of 10% aggregate tells you nothing useful. What matters: two or three service lines generate the majority of denials, each for structurally different reasons. Days in AR follows the same pattern: multi-specialty groups lacking advanced, specialty-aware automation tend to run meaningfully higher days-in-AR than best-in-class single-specialty operations, since upstream authorization failures compound downstream collection delays. The mechanism is straightforward: groups with the worst AR aging don't fail at collections. They fail at authorization. Claims without completed prior auth or with incorrect diagnosis-procedure pairing for specific payers get rejected front-end and re-enter workflow at full cost. In multi-specialty environments, this upstream failure multiplies across each specialty's unique authorization requirements. The point of intervention isn't billing. It's scheduling plus prior authorization. By the time a claim reaches submission, it's too late. Flobotics's own [prior authorization automation case study](https://www.flobotics.io/case-studies/90-faster-packet-submissions-prior-authorization-automation) shows the payoff of that shift: packet submissions moved 90% faster once authorization checks were front-loaded ahead of billing. ## Why RPA Can't Scale Across Specialties Robotic process automation fails in multi-specialty environments not because of poor implementation–though that happens–but because of design limitations. RPA executes tasks. It doesn't operate within a domain context. The distinction matters. Consider three concurrent workflows: an orthopedic implant claim, an oncology drug administration code, and a cardiology cath lab procedure. Each specialty has different payer adjudication logic. Orthopedic implants trigger device-specific prior auth requirements that vary by manufacturer and payer contract. Oncology drug coding requires J-code specificity and administration sequencing that determines reimbursement. Cardiology cath lab claims involve bundled payment rules that differ based on whether the procedure is diagnostic or interventional. RPA can execute the submission sequence. It cannot make contextual decisions about resubmission strategy when a claim is denied–because it lacks specialty domain logic. An orthopedic denial for "experimental device" requires different appeal documentation than an oncology denial for "medical necessity" or a cardiology denial for "bundled service." This isn't a bug. It's architectural. According to [Becker's Hospital Review's analysis of RPA's limits in hospital operations](https://www.beckershospitalreview.com/artificial-intelligence/what-every-hospital-exec-should-know-about-robotic-process-automation-rpa-4-insights.html), automation without domain intelligence treats multi-specialty complexity as a workflow scaling problem, when it's actually a knowledge representation problem. This is a broader pattern in automation adoption: organizations citing "limited ROI from automation" most often point to a mismatch between tool design and workflow specificity–not technology failure, but process architecture failure. ## What Specialty-Aware Actually Means "Specialty-aware automation" risks becoming a vendor marketing term unless operationally defined. Three layers distinguish genuine specialty segmentation from configuration theater: Training data architecture. Machine learning models require specialty-specific claims data, not aggregate population samples. Payer behavior generalizes incorrectly across specialties when training data conflates them. A commercial payer's authorization approval pattern for routine cardiology procedures tells you nothing about their denial propensity for complex orthopedic revisions. The model needs separate training corpuses per specialty to capture these distinct payer-specialty interaction patterns. Coding logic infrastructure. CPT and ICD rule sets must be maintained per specialty with automatic updates when payer policies change. As [Oracle Health's overview of domain-intelligent revenue cycle automation](https://www.oracle.com/health/revenue-cycle/) describes it, this is "domain-intelligent automation"–where specialty-specific logic and payer contract awareness function as native capabilities, not bolt-on configurations. A system built for primary care's high-volume low-complexity environment cannot adapt to neurosurgery's low-volume high-complexity coding requirements through configuration alone. Prior authorization decision trees. Authorization logic must segment by payer, by specialty, and by procedure category–with escalation protocols to human review for high-value claims. In practice, systems lacking specialty-specific decision trees either auto-approve too liberally (creating compliance risk) or escalate too conservatively (negating automation value). This creates a necessary human-in-the-loop requirement. For high-stakes specialty claims–oncology biologics, neurosurgical procedures, complex orthopedic revisions–what percentage of automation decisions receives human audit? Organizations operating below 20% audit rates on high-value claims carry regulatory risk when payer disputes arise. The audit trail requirement isn't overhead. It's the cost of defensible automation in a multi-specialty environment. Diagnostic questions for vendor evaluation follow directly: Does the vendor maintain specialty-specific training data? Can the system demonstrate separate decision trees per specialty per payer? How does it handle payer policy updates–manual configuration or automated ingestion? If a vendor cannot answer these questions with technical specificity, you're buying a generic bot. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## The Measurable Difference Specialty-segmented automation is associated with meaningful productivity gains and fewer manual errors compared to generic RCM automation in multi-specialty settings–though the magnitude varies by organization, and early results often include reduced prior-auth turnaround and lower denial rates. One Flobotics client saw this pattern directly: a [denials management automation case study](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation) documented up to 80% higher throughput once denial handling was segmented and automated by root cause rather than treated as a single generic queue. But these ranges require context. ROI differentiation varies by specialty. High-volume high-denial specialties–orthopedics, cardiology–show faster payback because the volume of preventable denials is larger. Low-volume complex coding specialties like neurosurgery require longer calibration periods. Organizations expecting uniform ROI across service lines will be disappointed in months two and three. The valley of despair is real. First 60–90 days post-implementation involve model calibration, during which denial rates may temporarily increase as the system learns payer-specific edge cases. According to [HFMA's report on how AI and automation are revolutionizing revenue cycle operations](https://www.hfma.org/technology/revenue-cycle-technology/how-ai-and-automation-are-revolutionizing-revenue-cycle-operations-for-faster-more-accurate-reimbursement/), organizations achieving the highest ROI don't reduce headcount–they reallocate staff to higher-value work. Certified oncology coders shift from preventable denials to high-value activities: payer escalation, contract optimization, complex case resolution. The ROI isn't FTE reduction. It's redeployment of scarce specialty expertise. This requires transparent accounting of implementation costs and timeline. Capital expenditure versus operational expense structures differ by vendor. What happens in the first 90 days–model training, integration, calibration–determines whether you reach break-even in month 18 or month 36. CFOs evaluating proposals need lower-bound and upper-bound estimates with explicit assumptions, not marketing ranges. ## Prerequisites for Success Automation cannot fix bad data. Multi-specialty groups with inconsistent provider master files, non-standardized specialty codes, or irregular NPI assignments will see marginal improvement at best. Data quality prerequisites function as hard requirements: unified provider master file, standardized NPI assignments across all specialties, clean charge capture data. Deploy automation before achieving data hygiene, and you'll automate chaos. Integration complexity multiplies in heterogeneous EHR environments. Multi-specialty groups frequently operate Epic for one service line and Athena for another, with legacy practice management systems still handling billing for acquired practices. Specialty-segmented agents in multi-EHR environments require robust API infrastructure and middleware capabilities. As [Healthcare IT News's report on why healthcare CIOs must fix their infrastructure before scaling AI](https://www.healthcareitnews.com/news/why-healthcare-cios-must-fix-their-foundations-scaling-ai) explains, automation value depends on integration layer quality–not just the intelligence of the automation itself. Governance determines whether human-in-the-loop remains operational discipline or devolves into aspiration. Who owns automation governance? Who defines audit thresholds for high-value claims? Who reviews escalated denials and updates decision logic? Without explicit ownership, the human oversight model becomes undefined, and compliance risk increases. Payer audits require defensible audit trails showing human verification of automated decisions for disputed claims. This isn't bureaucratic overhead–it's the operational cost of defensible automation. ## What to Do Monday Morning Three diagnostic questions determine whether your multi-specialty group has a structural problem or an operational one: First, calculate variance in denial rate between your highest and lowest-performing specialties. If the spread exceeds eight percentage points, you have a structural problem that generic automation cannot solve. The variation signals that specialty-specific friction points–prior auth workflows, coding logic, payer contract interpretation–require specialty-specific automation logic. Second, ask your RCM vendor whether they maintain specialty-specific training data for their machine learning models. If they cannot provide a technical answer describing how training corpuses are segmented and updated, you have a generic bot regardless of marketing claims. Third, audit what percentage of prior authorization decisions receives human review for high-value specialty claims. If fewer than 20% of high-value decisions are audited, you carry regulatory risk when payer disputes arise. Human-in-the-loop isn't a feature–it's a compliance requirement. The cost-to-collect premium for multi-specialty groups is structural, not inevitable. But closing the gap requires recognizing that multi-specialty complexity is a knowledge representation problem, not a workflow scaling problem. Automation architectures built for single-specialty environments cannot adapt through configuration. They require domain segmentation from the training data up. Revenue cycle directors inheriting generic automation implementations have a choice: treat the elevated cost-to-collect as unavoidable overhead, or recognize it as the price of architectural mismatch. That choice determines which approach scales. Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RCMHealthcare ### RCM Automation in Healthcare | 2026 RCM automation in healthcare: how RPA, AI, and OCR cut billing errors, speed up claims, and reduce manual work in 2026 revenue cycle management. Bart TeodorczukFebruary 25, 2026 ](https://www.flobotics.io/blog/rcm-automation-healthcare)[ RCMRPAAI ### AI vs. RPA vs. ML in Healthcare RCM: A Deep Dive AI vs. RPA vs. ML in healthcare RCM: how each technology improves efficiency, accuracy, and compliance, and which to adopt first. Krzysztof SzwedFebruary 22, 2025 ](https://www.flobotics.io/blog/ai-rpa-ml-rcm)[ RCMAIHealthcare ### Top RCM Trends | 2026 Top RCM trends for 2026: what healthcare finance leaders at Deloitte, HFMA, and beyond are prioritizing to strengthen revenue cycles. Karl MielnickiNovember 24, 2025 ](https://www.flobotics.io/blog/top-rcm-trends-healthcare) [All articles →](https://www.flobotics.io/blog) --- # RCM Automation for FQHCs Canonical: https://www.flobotics.io/blog/rcm-automation-for-fqhcs Author: Filip Nasiadko Published: 2026-08-14 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/RCM Automation for FQHCs CEO Notes [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # RCM Automation for FQHCs [Filip NasiadkoCEO and Co-founder at Flobotics](https://www.flobotics.io/our-editorial-team#nasiadko) Published August 14, 2026Updated September 1, 2026 On this page - [The FQHC Revenue Cycle Trap: Why Administrative Burden Is Now a Survival Risk](#thefqhcrevenuecycletrapwhyadministrativeburdenisnowasurvivalrisk) - [The Real Cost of Manual Processing](#therealcostofmanualprocessing) - [Why Automation Adoption Remains Low](#whyautomationadoptionremainslow) - [The Prospective Payment System Buffer–And Its Limits](#theprospectivepaymentsystembufferanditslimits) - [The Cost of Waiting](#thecostofwaiting) - [Conditions for Successful Implementation](#conditionsforsuccessfulimplementation) - [Vendor Evaluation: The FQHC-Specific Checklist](#vendorevaluationthefqhcspecificchecklist) - [Size Matters: Segmentation for Realistic ROI](#sizematterssegmentationforrealisticroi) - [The Decision Framework: Asymmetry of Risk](#thedecisionframeworkasymmetryofrisk) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## The FQHC Revenue Cycle Trap: Why Administrative Burden Is Now a Survival Risk Federal Qualified Health Centers process claims for 31 million Americans annually, serving the nation's most complex patient population: 93% at or below 200% of federal poverty level, 72% on Medicaid or uninsured, 62% racial or ethnic minorities (HRSA UDS 2023). Yet these organizations–designed to serve the underserved–operate with administrative costs per claim running 30-40% higher than standard ambulatory providers (HFMA 2025), while maintaining net margins between 2-4% (NACHC 2026). This is not a productivity problem. This is structural vulnerability. The mathematics are unforgiving. At a 15% initial denial rate–the FQHC industry average–a center generating $10 million in annual revenue faces $1.5 million in denied claims before any appeals work begins. HFMA research shows 60% of these denials are preventable through front-end automation: eligibility verification and prior authorization management. That represents $900,000 in recoverable revenue that instead becomes administrative burden. When your operating margin is 3%, that preventable denial volume equals the entire year's profit three times over. Yet FQHC adoption of comprehensive revenue cycle management automation lags every other ambulatory segment. The reasons are structural: grant compliance uncertainty, legacy EHR systems without native RCM integration, vendor markets that don't understand Uniform Data System reporting or sliding fee scale documentation. But the cost of this gap is no longer theoretical–it's showing up in days in accounts receivable, denial rate trajectories, and cash flow constraints that threaten operational continuity. ## The Real Cost of Manual Processing Administrative burden in FQHCs is not simply a matter of inefficiency–it's engineered into the operating model. Each encounter requires UDS-compliant documentation, sliding fee scale calculation, income verification for uninsured patients, dual-eligible coordination for Medicaid-Medicare patients, and 340B drug pricing compliance where applicable. HFMA's 2025 study quantifies this: FQHCs spend 30-40% more per claim on administrative processing than comparable ambulatory providers. The denial mechanics compound the problem. RevCycle Intelligence data shows FQHC staff allocate 40% of revenue cycle time to manual prior authorization work and appeals management. For dual-eligible populations–where Medicaid managed care overlays Medicare–the error rate on eligibility verification alone hits 23% when processed manually (Optum Research, RevCycle Intelligence 2026). These are not coding errors or medical necessity disputes. These are administrative failures: wrong coverage effective date, incorrect plan identification, missing authorization reference numbers. The current FQHC median sits at 70+ days in accounts receivable (NACHC 2026). Organizations with comprehensive RCM automation operate at 45-50 days. That 20-25 day gap, for a $10 million annual revenue center, represents approximately $685,000 in locked working capital. NACHC projects that without intervention, AR days for non-automated FQHCs will grow another 10-15% by end of 2026 as Medicaid managed care penetration increases and prior authorization requirements expand. ## Why Automation Adoption Remains Low Grant compliance creates the first barrier. Many FQHC financial officers face uncertainty about whether RCM software purchases qualify under Section 330 grant operational expense guidelines versus capital expenditure restrictions. The answer varies by Health Resources and Services Administration regional office interpretation, Service Area Competition approval procedures, and individual grant structures. Software-as-a-Service fee models often qualify as operational expenses payable from non-grant revenue, but generalizations are dangerous–this requires consultation with grant officers before vendor selection. Legacy EHR lock-in compounds the problem. Centers operating on older electronic health record platforms–common in the FQHC sector due to long replacement cycles–frequently lack native integration with modern RCM tools. This creates a choice: maintain siloed systems with manual data transfer (negating automation benefits) or undertake full EHR replacement (a multi-year, high-risk project unrelated to the revenue cycle problem at hand). The vendor market itself presents obstacles. Most RCM automation platforms are built for private practice or hospital outpatient departments. They lack configuration for UDS reporting fields, sliding fee scale calculation engines, 340B pricing integration, and state-specific Medicaid managed care organization rules. A system optimized for commercial insurance prior authorization workflows will fail spectacularly when applied to Medicaid MCO prior auth for a dual-eligible patient requiring behavioral health services. But the most persistent barrier is a misconception about risk exposure. ## The Prospective Payment System Buffer–And Its Limits FQHCs operating under the Prospective Payment System often believe their cost-based reimbursement model insulates them from denial risk. This is partially true and dangerously incomplete. PPS covers primary care encounters at federally qualified health centers–the encounter rate is set to cover costs regardless of payer. For these services, denial risk on the encounter itself is minimal. But PPS scope is narrow: Medicaid managed care plans introduce full denial exposure. While traditional Medicaid fee-for-service operates under PPS protection, MCO contracts frequently operate outside this framework. RevCycle Intelligence and Optum Research document that Medicaid MCO denial rates for dual-eligible populations reach 23% for eligibility-related errors alone–errors that real-time verification would catch before claim submission. Non-PPS services carry complete risk. Laboratory services billed separately, dental care, behavioral health services (depending on state Medicaid rules), and pharmacy claims all fall outside PPS coverage. These represent 15-30% of total billing volume for full-service FQHCs. Third-party billing has zero PPS protection. Any private insurance billing, Medicare (except for FQHCs serving as Medicare providers under specific circumstances), workers' compensation, or auto insurance claims operate under standard fee-for-service denial risk. Sliding fee scale and uninsured patients generate no revenue. PPS doesn't change this–it's mission-driven uncompensated care. Automation doesn't recover revenue here, but it does reduce the administrative cost of processing these encounters, which matters when you're calculating cost per claim. The conclusion: PPS eliminates some revenue risk but does nothing to reduce administrative cost burden. For the growing share of FQHC revenue coming from managed care, specialty services, and third-party payers, denial risk is identical to any other provider–except FQHC staffing and systems are less equipped to handle it efficiently. ## The Cost of Waiting Healthcare IT News data shows a 34% increase in RCM technology investment among community health centers between 2022 and 2024. Early adopters are now operating at sub-8% denial rates versus the 15%+ industry average. This is not a temporary advantage–it's a structural cost differential that compounds over time. Consider the cash flow impact alone. An FQHC at 70 days in AR versus a comparable organization at 48 days is operating with 46% more revenue locked in receivables at any given moment. For a $10 million annual revenue center, that differential equals $685,000 in working capital that could fund two full-time RCM specialists, cover an EHR module upgrade, or provide financial cushion against quarterly Medicaid payment delays. The denial rate progression is more concerning. NACHC 2026 projections indicate that without automation intervention, FQHCs will see denial rates climb 10-15% by end of 2026 as prior authorization requirements expand and Medicaid managed care enrollment grows. At current margins, this erosion is unsustainable. A center operating at 3% net margin can absorb a 0.5-point denial rate increase before operational stress. A 2-point increase puts solvency at risk. McKinsey Health's 2025 research on safety-net provider automation shows achievable targets: 10-15% reduction in operational RCM costs within 18 months post-implementation, and 5-8% net revenue improvement within 24 months. But these numbers come with conditions. ## Conditions for Successful Implementation Automation scales efficiency–it also scales errors if configured incorrectly. The calibration period matters. Months 0-3 are a cost center, not a savings generator. Implementation, staff training, and initial configuration require dedicated time from RCM directors and senior billing specialists. Productivity typically drops during this period as staff learn new workflows. Months 4-9 represent the calibration phase. Early wins appear in eligibility verification and partial prior authorization automation, but full denial rate improvement lags. This is the critical verification window: a manual review sample of 10-15% of automated claims should run continuously for 90 days to catch configuration errors before they become systemic. Months 10-18 deliver full automation cycle benefits. Denial rates drop, AR days compress, and staff time reallocates from manual verification work to complex appeals and payer relationship management. Month 24+ is the mature state, where continuous improvement processes and quarterly rule reviews maintain performance as payer policies change. The configuration ownership question is non-negotiable: who builds and maintains the automation rules? This requires someone who understands both RCM operations and FQHC-specific requirements–UDS reporting, sliding fee scales, 340B compliance, state Medicaid MCO variations. Vendor-provided baseline configuration is a starting point, not an endpoint. Without dedicated internal ownership, automation rules drift out of alignment with payer policy changes, and denial rates creep back up. Risk mitigation requires a phased rollout: eligibility verification first (highest ROI, lowest risk), prior authorization automation second (higher complexity, significant time savings), full claims automation last (requires proven system stability). Manual verification sampling continues through the first 90 days post-phase launch, and quarterly reviews become permanent operational practice. Staff concerns about automation replacing jobs miss the actual workforce dynamic. Automation eliminates repetitive verification tasks; it does not eliminate the need for judgment on complex appeals, payer contract interpretation, or denial trend analysis. The work changes type–from data entry to decision-making–but FTE reduction is rarely the primary ROI driver in FQHC settings where staffing is already lean. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Vendor Evaluation: The FQHC-Specific Checklist Most RCM automation vendors cannot serve FQHCs effectively because they don't understand the operational model. The evaluation criteria must be explicit: UDS native support: Does the system's data structure include native fields for Uniform Data System reporting, or will this require manual export and reformatting? If the latter, automation saves nothing on compliance reporting time. Sliding fee scale calculation: Can the patient accounting module automatically calculate and apply sliding fee discounts based on income verification, or does this remain a manual step? If manual, a major administrative burden remains untouched. 340B drug pricing integration: For FQHCs operating pharmacies, does the system track 340B-eligible prescriptions and prevent duplicate discounts? Compliance risk here is material. Medicaid MCO state-specific rules: Does the vendor maintain updated prior authorization requirements and eligibility verification protocols for your state's Medicaid managed care plans? Generic Medicaid configuration is insufficient–MCO rules vary by state and by plan within states. Reference customers in FQHC segment: How many federally qualified health center clients does the vendor serve, and will they provide contact information for RCM directors at comparable-sized organizations? If the vendor cannot produce FQHC references, they lack domain experience regardless of their commercial insurance client base. Questions to ask the vendor directly: Red flags: Vendor has no current FQHC client base. Vendor cannot demonstrate Medicaid MCO experience in your specific state. Vendor marketing emphasizes "AI solves everything" without discussion of rule configuration and calibration periods. Vendor pricing model has hidden implementation fees or charges per configuration change. ## Size Matters: Segmentation for Realistic ROI A three-provider FQHC with $2 million in annual revenue has different automation priorities than a 40-location network processing $50 million. One-size-fits-all recommendations ignore economic reality. For organizations below $3 million annual revenue, full RCM automation suites are often over-engineered relative to claim volume. The ROI calculation favors incremental adoption: start with eligibility verification and prior authorization automation–the two functions with highest cost per transaction and highest error rates. These can be implemented as standalone modules or through specialized vendors without replacing entire billing systems. Full claims automation and denial management platforms become economically viable as revenue crosses $5-7 million annually. For organizations above $15 million, the decision is less about whether to automate and more about build versus buy versus outsource. At this scale, outsourced RCM with embedded automation (revenue cycle management companies that use automation internally) competes economically with in-house staff plus software purchase. The calculus depends on local labor costs, staff retention rates, and internal IT support capacity. The middle segment–$3-15 million–represents the sweet spot for phased in-house automation: sufficient claim volume to justify software costs, manageable implementation scope, and organizational size that supports dedicated RCM director ownership of the platform. ## The Decision Framework: Asymmetry of Risk The cost of implementing automation now: software expense (typically $15,000-$40,000 annually for SaaS models at mid-sized FQHCs), implementation time (60-90 days for phased rollout), staff training (20-30 hours per FTE), and 90-day calibration period with temporary productivity dip. The cost of waiting: AR days increasing 10-15% by end of 2026 (per NACHC projection), denial rates climbing with prior authorization expansion, administrative cost per claim rising with labor cost inflation and payer complexity growth, and competitive gap widening as early adopters achieve 7-point denial rate advantages. The timeline pressure is external, not vendor-created. Medicaid managed care penetration continues to expand–17 states have moved from fee-for-service to predominantly MCO models since 2020. Prior authorization requirements grew 28% across Medicaid programs between 2020 and 2024 (RevCycle Intelligence). Both trends increase administrative burden for manual processing while simultaneously increasing automation ROI. The asymmetry favors action: early adopters build sustainable cost advantages and operational resilience. Late adopters face permanent structural disadvantage–when your competitor operates at 8% denial rate and 48 days in AR while you're at 15% and 72 days, you are functionally operating a different business model with different unit economics. That gap does not close without intervention. This is not a question of whether to automate revenue cycle management. It is a question of when and how–and whether your organization can afford the carrying cost of delay. Each quarter of postponement has a quantifiable price in locked working capital, preventable denials, and widening performance gaps against peer organizations. For FQHC financial leadership, the decision framework is clinical in its simplicity: diagnose current state costs (AR days, denial rate, cost per claim), identify automation ROI at your revenue scale, select vendors with demonstrated FQHC domain expertise, implement in phases with rigorous calibration, and measure monthly against baseline. The organizations that execute this in 2025-2026 will operate with structural advantages through the next payer complexity cycle. Those that defer will operate with structural liabilities. The math does not negotiate. ## FAQ: Why do medical claims get denied? The most common reasons are incorrect patient or insurance information, coding errors, missing prior authorization, insufficient documentation of medical necessity, non-covered services, and duplicate submissions. Is medical billing a good career? It offers a positive job outlook, a median salary around $50,250 a year, and increasingly remote or hybrid flexibility, though it rewards people who are comfortable with detail-heavy, rules-based work and ongoing learning as codes and payer policies change. Can medical billing be automated? Much of it can. Eligibility checks, claim scrubbing, and routine denial resubmission are high-volume and rule-based, making them well suited to automation, while complex appeals and patient-facing conversations still benefit from human judgment. Is medical billing the same as medical coding? No. A coder translates clinical documentation into diagnosis and procedure codes. A biller uses those codes to build and submit the claim, then manages everything that happens to it afterward. What are the main steps in the medical billing process? Registration, eligibility verification, the patient encounter, coding, charge entry, claim scrubbing, submission, payer adjudication, payment posting, and denial management or patient billing. What is a clean claim? A claim that's accepted and paid the first time it's submitted, with no missing information, coding errors, or additional documentation requests from the payer. Written byFilip Nasiadko CEO and Co-founder at Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ AIRCMHealthcare ### Claude for Healthcare from Anthropic Claude for Healthcare from Anthropic: what's still unclear on data storage, routing, and third-party access before you roll it out to staff. Dominik PutMay 26, 2026 ](https://www.flobotics.io/blog/anthropic-annoucement-claude-for-healthcare)[ Healthcare ### Healthcare Compliance Automation: Laws, Benefits and Examples Compliance automation software for healthcare: how RPA helps organizations meet evolving regulations without adding manual review work. Filip NasiadkoOctober 09, 2023 ](https://www.flobotics.io/blog/compliance-automation)[ HealthcareAIRPA ### Epic Automation | 2026 Epic Systems revenue cycle automation: why the EHR powering 300+ health systems still needs RPA to close labor, payer, and margin gaps in 2026. Jędrzej SzymulaApril 10, 2026 ](https://www.flobotics.io/blog/epic-automation) [All articles →](https://www.flobotics.io/blog) --- # DAX Copilot in RCM Canonical: https://www.flobotics.io/blog/dax-copilot-in-rcm Author: Bart Teodorczuk Published: 2026-08-11 Updated: 2026-09-08 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/DAX Copilot in RCM [AI](https://www.flobotics.io/blog?category=ai)[Healthcare](https://www.flobotics.io/blog?category=healthcare) # DAX Copilot in RCM [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published August 11, 2026Updated September 8, 2026 On this page - [DAX Copilot Cuts Documentation Time in Half. Your Revenue Cycle Still Leaks.](#daxcopilotcutsdocumentationtimeinhalfyourrevenuecyclestillleaks) - [What DAX Copilot Actually Does (And Where It Stops)](#whatdaxcopilotactuallydoesandwhereitstops) - [The Downstream RCM Mechanism: Three Conditional Pathways](#thedownstreamrcmmechanismthreeconditionalpathways) - [Where Revenue Leaks: Three Operational Failures](#whererevenueleaksthreeoperationalfailures) - [Compliance Risk: Who Owns the AI-Generated Note?](#complianceriskwhoownstheaigeneratednote) - [How to Close the Loop: Five Operational Actions](#howtoclosetheloopfiveoperationalactions) - [The Verdict: Integration, Not Installation](#theverdictintegrationnotinstallation) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## DAX Copilot Cuts Documentation Time in Half. Your Revenue Cycle Still Leaks. Documentation errors are a well-documented driver of denied and underpaid claims across U.S. healthcare. DAX Copilot, Microsoft's ambient AI clinical documentation tool, addresses part of this problem. Only part. And that "only" represents today's largest revenue cycle management blind spot. Revenue cycle directors measure denial rates, days in accounts receivable, and cost-to-collect. DAX Copilot is sold on clinical metrics: documentation time reduction and physician satisfaction scores. The gap between these two measurement frameworks is where revenue disappears–often invisibly, until the quarterly P&L surfaces the damage. ## What DAX Copilot Actually Does (And Where It Stops) DAX Copilot's mechanism is straightforward: ambient AI captures the patient-physician conversation, transcribes it, generates a structured clinical note, and integrates that note into the electronic health record. The technology delivers measurable improvements in documentation workflow. According to [Nuance's 2021 case study on University of Michigan Health-West's DAX rollout](https://news.nuance.com/2021-10-13-University-of-Michigan-Health-West-Expands-Adoption-of-the-Nuance-Dragon-Ambient-eXperience-to-Enhance-Patient-Care-and-Physician-Satisfaction), 79% of physicians said the tool improved documentation quality and 70% reported reduced feelings of burnout. Here is what DAX Copilot does not do: it does not generate ICD-10 diagnosis codes, it does not verify medical necessity for procedures, and it does not flag gaps in hierarchical condition category (HCC) documentation for Medicare Advantage claims. DAX Copilot is a documentation tool, not a billing tool. This is the fundamental distinction that most vendor presentations obscure. The system integrates with major EHR platforms–Epic, Oracle Health, Cerner–via standard interfaces. It does not integrate natively with billing systems such as Waystar or Change Healthcare. That integration gap, between clinical documentation and revenue cycle workflow, is where organizations lose money. ## The Downstream RCM Mechanism: Three Conditional Pathways The link between improved clinical documentation and improved revenue cycle outcomes is not automatic. It operates through three conditional pathways, each dependent on organizational infrastructure that most DAX implementations lack. Documentation Completeness → Coding Accuracy Incomplete clinical documentation generates systematic undercoding, which depresses diagnosis-related group (DRG) weights and causes first-pass claim denials. Documentation insufficiency is a recurring driver of first-pass denials industry-wide, though the exact share attributable to it varies by organization and specialty mix. DAX Copilot increases completeness–more information from the patient encounter reaches the clinical note–but completeness is not the same as specificity. A physician using DAX may document that a patient has diabetes. Whether that documentation specifies Type 1 versus Type 2, with or without complications, controlled versus uncontrolled, determines the accuracy of downstream coding. If the physician does not state those details during the encounter, the AI does not infer them. The narrative may be longer and more complete, but if it lacks the structured data elements that medical coders require, coding accuracy does not improve proportionally. Clinical documentation improvement (CDI) intervention remains essential. Gains in complication/comorbidity (CC/MCC) capture from ambient documentation tools tend to show up only in organizations with robust CDI infrastructure that has been recalibrated for AI-generated documentation. Organizations that deploy DAX without redesigning their CDI workflows see documentation volume increase without corresponding improvements in coding precision. Coding Accuracy → Denial Rate → Days in AR First-pass resolution rate–the percentage of claims accepted without rework on initial submission–determines how quickly revenue enters accounts receivable and how long it remains there. According to [HFMA's report on the rising tide of claim denials](https://www.hfma.org/revenue-cycle/denials-management/navigating-the-rising-tide-of-denials/), the cost of reworking a single denial is $47.77 for Medicare Advantage claims and $63.76 for commercial claims. Organizations with better documentation–not DAX-specific, but documentation quality generally–tend to report lower technical denial rates, though the exact improvement varies by organization. Improved clinical documentation is generally associated with faster claims processing and reduced days in accounts receivable, though the magnitude varies by organization and integration maturity. These are directional patterns, not measurements from controlled trials comparing DAX-equipped versus non-DAX organizations. No published study tracks denial rates or days in AR before and after DAX implementation in a controlled setting. DAX Copilot's contribution to this pathway is indirect. It operates by reducing the volume of physician queries–requests from coders back to clinicians for documentation clarification. Physician queries typically introduce measurable delays in the billing cycle, and organizations with slower documentation-to-coding handoffs tend to see higher query volumes. If DAX-generated notes reduce ambiguity and eliminate the need for follow-up questions, billing throughput accelerates. But this outcome depends entirely on whether the CDI team is trained to work with AI-generated narrative text, which differs structurally from physician-dictated notes. Physician Query Reduction → Throughput Traditional physician-dictated notes follow predictable formats. CDI specialists and medical coders know where to find diagnosis justification, treatment rationale, and medical necessity statements. AI-generated notes from ambient listening tools produce more conversational, less templated documentation. If CDI query templates are not redesigned for this format, query volume may actually increase post-implementation, not decrease. This represents the gap between clinical workflow improvement and revenue cycle optimization. DAX Copilot reduces the time physicians spend on documentation. Whether that time saving translates into faster, more accurate billing depends on decisions made downstream from the physician–decisions about CDI staffing, coder training, and billing system integration. ## Where Revenue Leaks: Three Operational Failures Most organizations measure DAX Copilot success by adoption rates: the percentage of eligible physicians actively using the tool. This metric tells you nothing about revenue cycle performance. Three operational failures convert a successful DAX deployment into a revenue-neutral exercise. Failure One: No Baseline RCM Metrics Organizations deploy DAX without establishing pre-implementation measurements of denial rate by reason code, first-pass resolution rate, days in AR, or cost-to-collect. Without baseline data, return on investment is unverifiable. Clinical teams report improved workflows; finance teams see unchanged denial rates. The disconnect persists because no one defined success in revenue terms before the technology went live. Failure Two: Manual Handoff Between EHR and Billing DAX integrates with the EHR. The billing system pulls data from the EHR through interfaces that were designed for human-generated documentation. When DAX-generated notes enter that pipeline, unstructured narrative text–complete, detailed, clinically accurate–reaches a coding team expecting discrete data elements in predictable fields. Coders read the narrative, extract the billable elements manually, and enter codes into the billing system. The automation ends at the EHR boundary. Everything downstream remains manual, and manual processes lose data. Failure Three: CDI Teams Operating on Pre-AI Protocols CDI specialists were trained to query specific documentation gaps: missing severity indicators, absent causal links between diagnoses and procedures, insufficient justification for medical necessity. Their query templates assume documentation produced by physicians following familiar patterns. AI-generated notes do not follow those patterns. A DAX note may bury the severity indicator inside a conversational sentence rather than calling it out in a structured problem list. CDI specialists flag it as missing, generate a query, delay billing by 48 hours, and the physician–who already spent time reviewing the AI note–now spends additional time answering questions about information that was, in fact, documented, just not where the CDI workflow expected to find it. Organizations that do not recalibrate CDI protocols for AI documentation patterns pay for DAX licenses while maintaining pre-DAX query volumes and denial rates. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Compliance Risk: Who Owns the AI-Generated Note? Under current CMS rules, the attending physician retains full responsibility for the accuracy and completeness of AI-assisted documentation. DAX Copilot reduces documentation time. It does not reduce liability for documentation quality. This creates an upcoding risk. If the AI generates a more detailed note than the clinical complexity of the encounter justifies–capturing incidental mentions, historical diagnoses not actively managed during the visit, or symptoms described by the patient but not corroborated by examination findings–the resulting claim may be coded more aggressively than appropriate. In an Office of Inspector General audit, the organization cannot defend a claim by stating, "The AI wrote it." The physician attested to the note's accuracy. The physician is accountable. CMS has not yet issued comprehensive guidance on AI-assisted clinical documentation. This regulatory gap creates uncertainty for compliance officers. What constitutes adequate physician review of an AI-generated note? Does reading and signing suffice, or must the physician actively verify every coded element? How should audit trails document the division of labor between AI and clinician? Organizations deploying DAX without clear answers to these questions are building compliance risk into their revenue cycle. ## How to Close the Loop: Five Operational Actions Capturing revenue cycle value from DAX Copilot requires deliberate operational integration, not passive technology adoption. Five actions convert a clinical documentation tool into a revenue cycle asset. First: Establish Baseline RCM Metrics Before DAX Goes Live Measure denial rate by reason code, first-pass resolution rate, days in AR, and cost-to-collect at the encounter level for the patient population and clinical specialties where DAX will be deployed. Track these metrics monthly for at least 90 days pre-implementation. Without a baseline, post-implementation changes are invisible. Flobotics has seen this firsthand: a [claims management automation case study](https://www.flobotics.io/case-studies/98-reduction-in-manual-claim-prep-claims-management-automation) only became measurable once the client had baseline claim-prep metrics to compare against–the 98% reduction in manual prep work would have been unverifiable otherwise. Second: Integrate CDI Workflow into DAX Configuration CDI specialists must participate in designing note templates. Structured data elements required for accurate coding–diagnosis specificity, severity indicators, active versus historical conditions, medical necessity justification–must appear in predictable locations within the AI-generated note, not embedded in narrative paragraphs. This is a configuration decision, not a training issue. If the AI is not prompted to structure output for billing purposes, no amount of CDI staff training compensates. Third: Build a Weekly Feedback Loop from Billing to Documentation Denial data from clearinghouses must return to CDI teams and physicians weekly, not quarterly. The feedback must be specific: "Top five denial reasons this week, with sample DAX notes that triggered each denial type." Physicians need to see the connection between what they say during the patient encounter, what the AI documents, and what the payer rejects. Without that closed loop, behavior does not change, and denial patterns persist. This is the same principle behind Flobotics's [AI agent for denials management case study](https://www.flobotics.io/case-studies/50k-saved-in-1-month-ai-agent-for-denials-management), where routing denial reasons back to the source process–rather than just reworking claims after the fact–was what made the savings durable. Fourth: Audit a Random Sample of DAX Notes for RCM Quality Select 10% of DAX-generated notes monthly and evaluate them against billing-specific criteria: Does the note contain diagnoses with ICD-10 specificity? Are chronic conditions documented as active and currently managed? Is medical necessity for procedures explicitly stated? Is HCC documentation present for Medicare Advantage patients with relevant conditions? This audit is separate from clinical quality review. It measures whether the documentation supports revenue cycle requirements, which is a different standard than whether it supports continuity of care. Fifth: Negotiate RCM Analytics Access with the Vendor Microsoft and Nuance provide adoption dashboards showing usage rates and time savings. They do not provide documentation quality scores tied to RCM outcomes. Organizations should either negotiate access to such metrics as part of the licensing agreement or build internal monitoring using physician query rate as a proxy. If query rates remain unchanged or increase after DAX deployment, the documentation is not improving in ways that matter for billing. ## The Verdict: Integration, Not Installation DAX Copilot delivers measurable improvements in clinical workflow. University of Michigan Health-West's rollout demonstrated improved documentation quality and reduced physician burnout. These benefits are real. They do not automatically translate into revenue cycle improvements. The University of Michigan Health-West results measured documentation quality and physician-reported burnout–not denial rates, days in AR, or cost-to-collect. No published study–at DAX-equipped organizations or elsewhere–tracks denial rates or days in AR before and after DAX implementation in a controlled setting. Organizations without integrated DAX-RCM workflows risk losing much of the tool's revenue-cycle upside, since documentation-quality gains alone don't automatically fix downstream coding, denial, and billing processes. This is a structural risk, not a measured outcome–no randomized controlled trial has compared DAX-plus-integration versus DAX-standalone versus no-DAX control groups on revenue cycle metrics. The gap between what DAX delivers–better clinical documentation–and what finance needs–fewer denials, faster collections, lower cost-to-collect–is an operational design problem, not a technology limitation. Most organizations implement DAX as a clinical tool and measure clinical outcomes. Revenue leakage occurs after implementation, in the space between the EHR and the billing system, where manual handoffs lose data and CDI workflows fail to adapt to AI-generated narrative formats. Organizations that treat DAX as revenue cycle infrastructure–not as a physician satisfaction benefit–and close the loop through CDI recalibration, billing integration, and feedback mechanisms have preliminary data suggesting improvement. Organizations that do not close the loop pay for DAX licenses while maintaining baseline denial rates. The difference between these two scenarios is not the technology. It is an operational decision about accountability. Who owns revenue outcomes from DAX Copilot–the chief information officer or the chief financial officer? Only one of them has it in the job description. Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareAI ### Claude for Healthcare Overview | 2026 Claude for Healthcare: Anthropic's 2026 toolkit for US medical data, with HIPAA compliance details and case studies from Banner Health and Novartis. Jędrzej SzymulaMay 06, 2026 ](https://www.flobotics.io/blog/claude-for-healthcare)[ AIHealthcareRCM ### AWS Connect Health: RCM Salvation or Infrastructure Play? AWS Connect Health: is Amazon's new healthcare platform an RCM solution or just an infrastructure play? We break down what it actually delivers. Bart TeodorczukMay 18, 2026 ](https://www.flobotics.io/blog/aws-connect-health)[ RCMAIHealthcare ### Agentic AI in Healthcare: From Hype to Real-World Impact Agentic AI in healthcare: how it differs from generative AI like ChatGPT and where it's already driving real clinical impact. Jędrzej SzymulaSeptember 22, 2025 ](https://www.flobotics.io/blog/agentic-ai-in-healthcare) [All articles →](https://www.flobotics.io/blog) --- # Oracle Health (Cerner) Automation | 2026 Canonical: https://www.flobotics.io/blog/oracle-health-cerner-rcm-automation Author: Bart Teodorczuk Published: 2026-08-03 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Oracle Health (Cerner) Automation | 2026 [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Oracle Health (Cerner) Automation | 2026 [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published August 03, 2026Updated September 1, 2026 On this page - [Is Cerner the Same as Oracle Health?](#is-cerner-the-same-as-oracle-health) - [Cerner Isn't Being Discontinued – But It Is In Transition](#cerner-isn-t-being-discontinued-but-it-is-in-transition) - [Does Oracle Health Have a Developer API?](#does-oracle-health-have-a-developer-api) - [What Oracle Health's Native RCM Tools Do – and Don't Do – Today](#what-oracle-health-s-native-rcm-tools-do-and-don-t-do-today) - [Why Mid-Transition Cerner Shops Can't Just Wait for the Native Roadmap](#why-mid-transition-cerner-shops-can-t-just-wait-for-the-native-roadmap) - [Where Computer-Use Automation Fits Alongside Oracle Health](#where-computer-use-automation-fits-alongside-oracle-health) - [FAQ](#faq) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Is Cerner the Same as Oracle Health? Effectively, yes. Oracle acquired Cerner Corporation in 2022 for $28.3 billion and rebranded it Oracle Health. The underlying Cerner Millennium platform continues largely unchanged under the new name – so when you see “Cerner” in an older RFP and “Oracle Health” in a 2026 sales deck, they're referring to the same core EHR technology, now under different ownership and with a second, newer product line layered alongside it. ## Cerner Isn't Being Discontinued – But It Is In Transition This is the single most important thing to understand before planning any RCM automation around this platform: Cerner Millennium is not going away. It remains the production EHR for existing clients and continues to receive updates. But Oracle is simultaneously running a second track – a next-generation EHR built entirely from scratch on Oracle Cloud Infrastructure, announced in October 2024, with new AI and voice capabilities baked in from day one. It remains the production EHR for existing clients and continues to receive updates. But Oracle is simultaneously running a second track — a next-generation EHR built entirely from scratch on Oracle Cloud Infrastructure, announced in October 2024, with new AI and voice capabilities baked in from day one. As of today, that new EHR is only available for ambulatory providers; acute-care functionality is targeted for 2026. Oracle also walked back an earlier requirement that clients migrate to Oracle Cloud Infrastructure before adopting the new platform – instead offering a “547 Deep Dive Assessment” so existing clients can evaluate readiness and sequencing on their own timeline, rather than being forced onto a hard migration deadline. The backdrop to all of this: Oracle Health has cut its workforce by close to 50% since the acquisition, consolidated Cerner's Kansas City campus, and lost several large hospital clients – representing thousands of beds – mostly to Epic. None of that means the platform is going away. It does mean that if you're running Cerner/Oracle Health today, you're managing a vendor mid-transformation, not a stable, settled roadmap. ## Does Oracle Health Have a Developer API? Yes. The Oracle Health Developer Program (formerly Cerner Code) gives third-party developers free access to Millennium API documentation, best-practice guidelines, and a testing sandbox. For new integrations in 2026, Oracle's own recommendation is to use FHIR R4 (Ignite APIs) as the primary integration path, falling back to legacy HL7 v2 through COI only for real-time event data that FHIR Subscriptions can't yet reliably deliver. Millennium APIs remain available for core system-of-record operations that predate the FHIR push. So, similarly to MEDITECH, the API access itself isn't the blocker. The blocker is what those APIs actually connect to – and how much of a provider's day-to-day RCM workflow still depends on a payer's own portal rather than anything Oracle Health exposes. ## What Oracle Health's Native RCM Tools Do – and Don't Do – Today Oracle Health's Revenue Cycle and Consumer Management platform is genuinely investing in automation. RevElate Patient Accounting unified Cerner's RCM offerings under one platform, and a partnership with AKASA layers AI-based automation on top – automating eligibility checks and denials, checking eligibility using insurance card data, amending eligibility-related denials, and automatically resubmitting corrected claims. Beyond that partnership, Oracle Health's own roadmap lists AI-driven denial appeal letter generation, AI-assisted inpatient coding (ICD-10-PCS, MS-DRG), and end-to-end charge master automation. The catch: several of these are described as in-development or roadmap items, not universally live features every client can turn on today. And critically, they're native Oracle Health capabilities – built to work inside the Oracle Health/AKASA stack, not something a hospital can freely extend to automate every payer portal in its specific contracted mix, especially the smaller regional payers a national AI-RCM partnership is less likely to prioritize first. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Why Mid-Transition Cerner Shops Can't Just Wait for the Native Roadmap If you're running Cerner Millennium today, waiting for Oracle's native RCM AI roadmap to fully mature means betting on a vendor that is simultaneously: maintaining a legacy platform, building an entirely new cloud EHR, absorbing a nearly 50% workforce reduction, and defending market share against Epic. That's not a criticism of the technology — Oracle Health's revenue cycle ambitions are real and well-funded. It's a practical observation about sequencing: native RCM AI features tend to roll out to Oracle Health's largest, most strategic accounts first, and tend to prioritize the payers with the largest volume relationships, not necessarily the specific regional payer mix a mid-size hospital system actually bills against. Meanwhile, the day-to-day revenue leakage — denied claims, stalled prior auths, eligibility errors caught too late — doesn't pause for a platform migration. A hospital mid-transition between Millennium and the new Oracle Health EHR has, if anything, less internal bandwidth to spare for chasing down manual RCM workflows, not more. ## Where Computer-Use Automation Fits Alongside Oracle Health This is the practical case for layering computer-use agents on top of whichever Oracle Health environment a hospital is running, rather than waiting for the native roadmap to arrive: the agent doesn't care whether the underlying EHR is Cerner Millennium or the new cloud-native platform, because it isn't trying to replace Oracle Health's own APIs — it's handling the payer-portal side those APIs were never meant to reach. Concretely, that means: - [Eligibility verification pulled from Millennium or the new EHR](https://www.flobotics.io/agents/eligibility-check-automation), checked against whichever payer portal the patient's plan requires — not just the payers covered by an existing AKASA-style partnership. - [Prior authorization packets assembled from clinical documentation already in the EHR](https://www.flobotics.io/agents/prior-authorization-automation), then submitted through the payer's own portal without waiting on a native Oracle Health feature to support that specific payer. - [Denials management that reads every EOB](https://www.flobotics.io/agents/denials-management-automation) regardless of which patient accounting system generated the original claim — useful precisely because a mid-transition hospital may be running both Cerner Patient Accounting and newer tools side by side. None of this requires picking a side in the Millennium-vs-new-EHR transition. It works underneath whichever one is live on a given day. ## FAQ Is Cerner the same as Oracle Health? Effectively yes. Oracle acquired Cerner in 2022 and rebranded it Oracle Health; the underlying Cerner Millennium platform continues largely unchanged, so the two names now refer to the same core EHR technology. Is Cerner being discontinued? No. Cerner Millennium remains the production EHR and continues to receive updates. Oracle Health has cut its workforce by close to half and lost several large clients (mostly to Epic) while building a separate cloud-native EHR in parallel — real turbulence, but not a sunset of the platform. Does Oracle Health/Cerner have a developer API? Yes — the Oracle Health Developer Program gives third-party developers free access to Millennium API documentation, a testing sandbox, and FHIR R4/HL7 v2/CCDA-based integration standards. What is Oracle Health Millennium used for? Millennium runs hospital clinical, financial, and operational workflows in one system — vitals a nurse records are visible to physicians instantly, and billing teams get automated charge capture without manual entry. Large systems often run one Millennium instance across multiple facilities. Does Cerner/Oracle Health automate revenue cycle management? Partially. Native tools like RevElate Patient Accounting and the AKASA partnership automate eligibility checks and some denial workflows, and Oracle's roadmap includes AI-driven coding and charge master automation — but several of these are still rolling out, and they cover the payers those native tools are built around, not necessarily a hospital's full payer mix. Should we wait for Oracle Health's native RCM AI before automating anything? Not if denials, stalled prior auths, and eligibility errors are costing revenue today. Computer-use automation on the payer-portal side works underneath whichever Oracle Health environment is currently live, without requiring a bet on migration timing. Two EHRs, one revenue cycle. Let's automate the part that isn't waiting on Oracle's roadmap. [👉 Book a 30-minute call](https://www.flobotics.io/book) Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # How Agentic AI Automates Payer Portals Without an API Canonical: https://www.flobotics.io/blog/agentic-ai-payer-portals-without-api Author: Jędrzej Szymula Published: 2026-07-27 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/How Agentic AI Automates Payer Portals Without an API [AI](https://www.flobotics.io/blog?category=ai)[Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # How Agentic AI Automates Payer Portals Without an API [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published July 27, 2026Updated September 1, 2026 On this page - [Before You Read:](#before-you-read) - [Why Most Payer Portals Still Don't Have an API](#why-most-payer-portals-still-don-t-have-an-api) - [The CMS-0057-F Timeline: What's Mandated, What Isn't](#the-cms-0057-f-timeline-what-s-mandated-what-isn-t) - [The Real Scale Problem: 50-200 Portals Per Health System](#the-real-scale-problem-50-200-portals-per-health-system) - [What “Computer-Use” Actually Means (It's Not Screen-Scraping, and It's Not Waiting for an API)](#what-computer-use-actually-means-it-s-not-screen-scraping-and-it-s-not-waiting-for-an-api) - [Is It Legal for AI to Handle Prior Authorization Without a Human?](#is-it-legal-for-ai-to-handle-prior-authorization-without-a-human) - [What This Looks Like in Production](#what-this-looks-like-in-production) - [FAQ](#faq) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ### Before You Read: RPA (Robotic Process Automation) Rule-based bots that click through fixed screen coordinates. Fast and reliable until the screen changes — then they break. Agentic AI Software that reasons about a goal, plans multi-step actions, and adapts across tools with limited human input — not just responding to a prompt. Computer-Use Agent A specific kind of agentic AI: it sees a screenshot, reasons about what's on it, and produces mouse/keyboard actions — operating software the way a person would, without needing an API to exist first. ## Why Most Payer Portals Still Don't Have an API Ask this question and the honest answer is structural, not incidental: standardized APIs never existed for most payer transactions in the first place. UnitedHealthcare, Cigna, Aetna, Humana, and dozens of regional Blue Cross Blue Shield plans each built their own proprietary web portal for eligibility, prior authorization, and claims — none of them designed with automation in mind, each with different forms, different required fields, different documentation rules. Authentication adds another layer of friction on top: some portals require TOTP-based MFA, others send SMS codes, session timeouts range from 5 to 30 minutes, and CAPTCHAs appear unpredictably. This isn't a MEDITECH problem, an Oracle Health problem, or an Epic problem — it sits entirely on the payer side, which is exactly why switching EHRs or upgrading an EHR's own API never actually solves it. ## The CMS-0057-F Timeline: What's Mandated, What Isn't The regulatory picture is genuinely shifting — just more slowly, and more narrowly, than most headlines suggest. The CMS Interoperability and Prior Authorization Final Rule (CMS-0057-F) was published in February 2024. Since January 1, 2026, impacted payers have had to return prior authorization decisions within 72 hours for urgent requests and 7 calendar days for standard ones, state a specific reason for every denial, and publish prior authorization metrics annually — the first public reports were due March 31, 2026. The bigger piece — a mandatory FHIR-based Prior Authorization API, plus Patient Access, Provider Access, and Payer-to-Payer APIs — isn't required until January 1, 2027, and only for specific payer types: Medicare Advantage, Medicaid managed care, CHIP, and Qualified Health Plan issuers on the federal exchanges. Most commercial payers sit entirely outside that mandate. So do claims-status checks and denial/appeal workflows, neither of which gets a required API even after 2027. ## The Real Scale Problem: 50-200 Portals Per Health System Even a fully successful 2027 rollout only closes part of the gap, because of the sheer number of counterparties involved. A mid-size health system typically interfaces with 50 to 200 different payer portals, each with its own login flow, MFA requirements, and data-entry format. Traditional integration projects — the kind that build a proper point-to-point connection to a single payer — take 12 to 18 months each, and organizations typically only get through their top 5 payers before priorities shift elsewhere. [Insert chart here: chart-4-payer-portal-coverage-gap.svg — 60-70% of claim volume still manual because only the top 5 of 50-200 payers get a traditional integration] That leaves an estimated 60-70% of claim volume running through completely manual, unautomated portal work — not because the workflow is conceptually hard, but because the economics of building 45-plus custom integrations never made sense for any single health system to fund. ## What “Computer-Use” Actually Means (It's Not Screen-Scraping, and It's Not Waiting for an API) It's worth being precise here, because the term “agentic AI” gets used loosely. Some industry definitions frame agentic AI as strictly API-level — contrasting it with RPA's “screen scraping” and implying that anything touching a screen doesn't count as agentic. That's a fair distinction for workflows where an API already exists. But for the 60-70% of claim volume sitting behind payer portals with no usable API — and for the commercial payers CMS-0057-F never touches — that framing doesn't describe the actual choice in front of a hospital or lab: it's not “API vs. screen scraping,” it's “wait years for an API that may never come vs. automate the portal properly.” A computer-use agent is built from four layers working together, not one script clicking fixed coordinates: - LLM reasoning interprets payer rules and clinical documentation, and plans the next action — this is the layer that adapts when a portal's layout changes overnight, instead of failing silently the way fixed-coordinate RPA does. - The computer-use/browser agent navigates the portal itself: logging in, handling MFA, filling forms, clicking through exactly as a person would, built on vision-and-language models like Claude that read a screenshot and decide where to click. - Document understanding reads EOBs, authorization packets, and clinical notes — structured or not — pulling the specific data each payer's form actually asks for. - A deterministic rule engine sits underneath all of it, guaranteeing HIPAA-compliant, consistent output every time, and routing genuine exceptions to a human reviewer rather than guessing. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Is It Legal for AI to Handle Prior Authorization Without a Human? This is a live regulatory question, not a settled one — and it's worth addressing directly rather than glossing over. Most insurers already use some form of automated system somewhere in the prior authorization process. But states are actively stepping in to define the boundaries: Georgia's SB 544, effective January 1, 2027, allows insurers to use AI to automate prior authorization tasks and participate in decision-making, but explicitly bars AI from issuing an adverse (denial) determination without review and approval from a licensed healthcare provider. Expect more states to follow a similar pattern over the next couple of years. This is precisely why the human-in-the-loop exception layer in the architecture above isn't a nice-to-have — it's the difference between an automation approach that ages well as regulation catches up, and one that has to be re-architected every time a new state law lands. Flobotics' agents are built to escalate true exceptions to human staff by design, not as a compliance afterthought. ## What This Looks Like in Production The stats aren't hypothetical. Across Flobotics' deployments, agentic automation of exactly this kind has produced: a 90% reduction in prior authorization packet submission time and [an 85% faster overall submission process for a pain-management network](https://www.flobotics.io/case-studies/85-faster-submissions-8-ftes-saved-prior-authorization-automation), bridging [a genetic-diagnostics lab with 90% faster packet submissions](https://www.flobotics.io/case-studies/90-faster-packet-submissions-prior-authorization-automation), and denial processing time cut from roughly 10 minutes to 55 seconds at a national diagnostic lab running approximately 300 automated resubmissions per day. None of these outcomes required a single payer to publish a new API first. Industry-wide, the pattern holds: AI process automation in healthcare is returning roughly $3.20 for every $1 invested, with payback averaging 12 to 18 months, and organizations report 40-60% reductions in denial rates once autonomous resolution removes the human-bandwidth bottleneck that was the actual constraint the whole time — not the absence of an API, but the absence of enough staff-hours to work every portal manually. ## FAQ What is agentic AI, in simple terms? Software that doesn't just respond to a prompt — it plans multi-step actions, reasons about the current situation, and acts across tools to reach a goal with minimal human input, unlike generative AI, which only produces content on request. Is RPA the same as agentic AI? No. RPA executes fixed, rule-based steps and breaks when a screen changes; agentic AI reasons, adapts, and handles unstructured data and exceptions. Most real deployments combine both — RPA for routine execution, agentic AI for judgment calls. What is a “computer-use” AI agent? An AI agent that sees a screenshot of a screen, reasons about what's on it, and produces mouse and keyboard actions to operate software the way a person would — built on vision-and-language models rather than fixed click coordinates. Why don't insurance payer portals have APIs? Because standardized APIs never existed for most payer transactions. Each payer built its own proprietary web portal, with different forms, fields, MFA methods, and CAPTCHA behavior — none of it designed for automation. Is it legal for AI to handle prior authorization without a human? It's an active regulatory area. Most insurers already automate parts of the process, but states are stepping in — Georgia's SB 544 (effective January 1, 2027) allows AI to automate PA tasks but bars it from issuing denials without licensed-provider review. Routing true exceptions to human staff, as Flobotics does by design, lines up with where regulation is heading. Will the 2027 CMS API mandate make computer-use agents obsolete? Not for years, if ever. CMS-0057-F only mandates FHIR APIs for Medicare Advantage, Medicaid managed care, CHIP, and QHP-exchange payers, and only for Patient Access, Provider Access, Payer-to-Payer, and Prior Authorization — leaving most commercial payers and workflows like claims status and denial appeals outside the mandate entirely. The API you're waiting for might not exist by 2027, or ever, for your specific payer mix. Automate the portal instead. [👉 Book a 30-minute call](https://www.flobotics.io/book) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPAAI ### Agentic AI Frameworks | 2026 Agentic AI frameworks in 2026: which stacks Google and other leaders are betting on, explained with clear, research-backed answers. Jędrzej SzymulaDecember 02, 2025 ](https://www.flobotics.io/blog/agentic-ai-frameworks)[ AI ### Agentic AI Workflows Agentic AI workflows, explained: how autonomous AI agents handle multi-step RCM tasks beyond traditional rule-based RPA. February 04, 2026 ](https://www.flobotics.io/blog/agentic-ai-workflows)[ RCMAIHealthcare ### Agentic AI in Healthcare: From Hype to Real-World Impact Agentic AI in healthcare: how it differs from generative AI like ChatGPT and where it's already driving real clinical impact. Jędrzej SzymulaSeptember 22, 2025 ](https://www.flobotics.io/blog/agentic-ai-in-healthcare) [All articles →](https://www.flobotics.io/blog) --- # Why Community Hospitals Need More Than an API | Meditech Example Canonical: https://www.flobotics.io/blog/why-community-hospitals-need-more-than-an-api Author: Filip Nasiadko Published: 2026-07-23 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Why Community Hospitals Need More Than an API? Meditech… CEO Notes [AI](https://www.flobotics.io/blog?category=ai)[Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Why Community Hospitals Need More Than an API | Meditech Example [Filip NasiadkoCEO and Co-founder at Flobotics](https://www.flobotics.io/our-editorial-team#nasiadko) Published July 23, 2026Updated September 1, 2026 On this page - [Does MEDITECH Have an API?](#does-meditech-have-an-api) - [Why MEDITECH's API Isn't the RCM Bottleneck?](#why-meditech-s-api-isn-t-the-rcm-bottleneck) - [MEDITECH vs. Epic vs. Cerner: Different Philosophies, Different Constraints](#meditech-vs-epic-vs-cerner-different-philosophies-different-constraints) - [What Can Actually Be Automated in a MEDITECH Environment Today](#what-can-actually-be-automated-in-a-meditech-environment-today) - [How Computer-Use Agents Close the Gap MEDITECH's API Doesn't Reach](#how-computer-use-agents-close-the-gap-meditech-s-api-doesn-t-reach) - [A Realistic MEDITECH RCM Automation Roadmap](#a-realistic-meditech-rcm-automation-roadmap) - [Compliance Doesn't Get Looser Because the Hospital Is Smaller](#compliance-doesn-t-get-looser-because-the-hospital-is-smaller) - [FAQ](#faq) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Most of MEDITECH's hospitals don't have a developer on staff, let alone a six-figure budget for a custom FHIR integration. They have a two- or three-person IT team keeping the EHR running, a stack of regional payer contracts, and a revenue cycle that leaks a little more every week a prior authorization sits unsubmitted. Ask whether MEDITECH has an API and the answer is a confident yes. Ask why that hasn't fixed anything, and the real story starts. That gap – between a genuinely solid EHR API and a revenue cycle that still runs on manual portal work – is exactly what this guide breaks down: what MEDITECH's interoperability actually covers, why the community and rural hospitals that run it are the least equipped to close that gap alone, and what can realistically be automated today without waiting on anyone's roadmap. ## Does MEDITECH Have an API? Yes – and it's a better answer than most people searching this question expect. MEDITECH Expanse supports FHIR R4 and SMART on FHIR, exposing resources like Patient, Observation, Allergy, Medication, and Appointment through Greenfield Workspace, a sandbox where third-party developers can build and test apps against a real MEDITECH environment before going live. Its Patient Access FHIR APIs conform to the US Core Implementation Guide, cover USCDI data elements, and MEDITECH is certifying as CommonWell's first fully FHIR-enabled member for exchanging C-CDA documents both ways. On top of that, MEDITECH runs Traverse Exchange, a national data-sharing network now connecting more than 700 facilities across 41 states, with more hospitals scheduled to join through the rest of 2026. MEDITECH also participates in the Argonaut Project and the FHIR at Scale Taskforce (FAST) – this isn't a vendor dragging its feet on interoperability standards. So if the API exists and the standards participation is real, why does automating eligibility, prior authorization, and denials in a MEDITECH shop still feel like pulling teeth for so many hospitals? The answer has less to do with MEDITECH's technology and everything to do with what that technology was built to solve – and who's actually running it. ## Why MEDITECH's API Isn't the RCM Bottleneck? MEDITECH's FHIR APIs were built to solve clinical interoperability – sharing patient records, lab results, and care summaries across care settings. Greenfield's current API surface covers the Common Clinical Data Set, FHIR Scheduling, and USCDI R4. None of that touches eligibility verification, prior authorization submission, claim status tracking, or denial appeals. Those workflows still run through each individual payer's own proprietary portal – API or no API on the EHR side. And here's the part that matters most for who's actually running MEDITECH day to day: it isn't the large academic medical centers with forty-person IT departments and a standing FHIR integration budget. MEDITECH is the dominant EHR among small and mid-size facilities – holding roughly 13-15% of the U.S. acute-care hospital market overall, but nearly 40% share of hospitals under 200 beds, plus more than 250 rural sites, with 15 new rural facilities adopting Expanse in 2025 alone. That's exactly the segment least likely to have a developer on staff who can build against Greenfield, negotiate a CommonWell connection, or maintain a custom FHIR pipeline once it ships. A 120-bed community hospital that just adopted MEDITECH as a Service specifically because it's 30-50% cheaper than Epic did not do so with a spare six-figure IT budget sitting around for custom payer integrations. The API existing and the API being realistically usable by that hospital's two-person IT team are two very different facts. ## MEDITECH vs. Epic vs. Cerner: Different Philosophies, Different Constraints The three major EHRs solve for different problems, and it shows directly in each one's RCM automation options. Epic optimizes for large, provider-centric health systems with dozens of specialty modules, priced accordingly. Cerner – now Oracle Health – targets flexible data structures for enterprise hospital networks running Cerner Millennium across multiple facilities. MEDITECH is built for structured, low-resource stability: fewer modules, a simplified feature set, and a transparent, lower-cost pricing model. That's the exact reason community and rural hospitals choose it in the first place. That same low-resource design is what makes bolting on custom RCM integrations harder in practice, even where the technical capability already exists on paper. A MEDITECH hospital that wants to automate [eligibility verification](https://www.flobotics.io/agents/eligibility-check-automation) or [prior authorization](https://www.flobotics.io/agents/prior-authorization-automation) isn't really choosing between building it in-house or buying a platform the way a well-resourced Epic hospital might. It's choosing between hiring a developer it doesn't have budget for, or finding a partner who can automate the payer-portal side of the workflow without a multi-month custom integration project. ## What Can Actually Be Automated in a MEDITECH Environment Today The workflows that matter most for revenue – [eligibility checks](https://www.flobotics.io/agents/eligibility-check-automation), [prior authorization](https://www.flobotics.io/agents/prior-authorization-automation), [claims management](https://www.flobotics.io/agents/claims-management-automation), and [denials management](https://www.flobotics.io/agents/denials-management-automation) – don't actually require MEDITECH to expose a new API. They need an automation layer that can: - Pull patient and coverage data out of MEDITECH through the HL7/FHIR interfaces it already supports well – this part is genuinely solved technology. - Carry that data into whichever payer portal the case requires – logging in, navigating MFA, filling forms, and submitting exactly as a staff member would, for however many of the hospital's contracted payers that requires. - Write the result back into MEDITECH – an authorization number, a claim status update, a denial reason code – so the record stays current without a biller re-entering it by hand. Third-party prior authorization automation that integrates with MEDITECH already does exactly this, typically writing auth numbers and statuses back into the EHR, with phased implementation running roughly 6-8 months. Once live, automated prior auth workflows cut turnaround time by up to 75% – requests that used to take a staff member 20-35 minutes complete in 3-8 minutes, and they run around the clock instead of during business hours only. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## How Computer-Use Agents Close the Gap MEDITECH's API Doesn't Reach This is where the “no API” framing needs to get more precise: MEDITECH doesn't need to be the one with the missing API – the payer does. A computer-use agent reads MEDITECH-side data through the interfaces that already work well, then operates the payer's portal directly: handling logins, MFA prompts, and the occasional CAPTCHA, reading whatever form that specific payer uses, and submitting the request the same way a biller would – just continuously, and at machine speed, across however many of the hospital's payer contracts require it. For a MEDITECH hospital specifically, this distinction matters more than it would for a large Epic system, because there's no in-house integration team to fall back on when a payer portal changes its layout overnight. The automation has to be resilient by design – reasoning about what's actually on screen rather than clicking fixed coordinates the way older RPA tools do – or it breaks just as often as the manual process it replaced, and the hospital is back to square one with even less staff capacity than before. Document understanding does the other half of the job: reading EOBs, clinical notes, and authorization packets that arrive as PDFs, faxes, or scanned images rather than structured data – exactly the format most payer correspondence still shows up in, regardless of how modern the hospital's own EHR is. ## A Realistic MEDITECH RCM Automation Roadmap For a community or rural hospital running MEDITECH Expanse, the sequencing that tends to work best is: - Start with eligibility verification. It's the highest-volume, most repetitive workflow in the revenue cycle, and errors here cascade into denials weeks later. Automating it first also builds internal trust in the system before tackling more judgment-heavy workflows – staff see fewer errors and faster turnaround almost immediately. It's the highest-volume, most repetitive workflow in the revenue cycle, and errors here cascade into denials weeks later. Automating it first also builds internal trust in the system before tackling more judgment-heavy workflows — staff see fewer errors and faster turnaround almost immediately. - Move to prior authorization. This is where MEDITECH's smaller IT footprint tends to hurt the most in practice – PA packet assembly is document-heavy, payer-specific, and constantly shifting as payers update their requirements. It's exactly the combination of reasoning and document handling a computer-use agent plus document understanding is built for. This is where MEDITECH's smaller IT footprint tends to hurt the most in practice — PA packet assembly is document-heavy, payer-specific, and constantly shifting as payers update their requirements. It's exactly the combination of reasoning and document handling a computer-use agent plus document understanding is built for. - Layer in denials management. Once eligibility and PA are stable and generating cleaner data, denial write-offs become the next-largest source of revenue leakage – and by this point the EHR-to-portal data pipeline is already proven, so extending it to appeals and resubmissions is a smaller lift. Once eligibility and PA are stable and generating cleaner data, denial write-offs become the next-largest source of revenue leakage — and by this point the EHR-to-portal data pipeline is already proven, so [extending it to appeals and resubmissions](https://www.flobotics.io/case-studies/50k-saved-in-1-month-ai-agent-for-denials-management) is a smaller lift. - Add claims status monitoring last, once the upstream workflows are already producing cleaner claims to begin with – monitoring is only as valuable as the claims underneath it are accurate., once the upstream workflows are already producing cleaner claims to begin with — monitoring is only as valuable as the claims underneath it are accurate. None of this requires MEDITECH to change anything about its platform. It requires an automation partner who already knows how to pull data out of MEDITECH's existing interfaces reliably, and who isn't waiting on any single payer to build an API before starting. ## Compliance Doesn't Get Looser Because the Hospital Is Smaller One thing worth stating plainly: a community hospital running a leaner IT stack still carries the exact same HIPAA obligations as a 900-bed academic center. Any automation layer working across MEDITECH and payer portals needs full encryption in transit and at rest, role-based access, complete audit logging, and a signed BAA – non-negotiable regardless of hospital size. If anything, smaller hospitals should scrutinize this harder, precisely because they have fewer internal resources to catch a compliance gap before it becomes a problem. ## FAQ Does MEDITECH have an API? Yes. MEDITECH Expanse supports FHIR R4 and SMART on FHIR, exposing resources like Patient, Observation, Allergy, Medication, and Appointment through its Greenfield developer sandbox, and MEDITECH is certifying as CommonWell's first fully FHIR-enabled member. Is MEDITECH FHIR compliant? Yes – MEDITECH's Patient Access FHIR APIs conform to the US Core Implementation Guide and include USCDI data elements, and the platform participates in the Argonaut Project and FAST. What hospitals use MEDITECH? MEDITECH is the third most-used EHR vendor in the U.S. (roughly 13-15% market share) and the dominant EHR among community hospitals, with nearly 40% share of facilities under 200 beds and 250+ rural sites as of 2026. How is MEDITECH different from Epic and Cerner? Epic targets large, provider-centric health systems at a premium price point; Cerner (Oracle Health) targets flexible enterprise data structures for large hospital networks; MEDITECH is built for structured, low-resource stability – which is exactly why it wins in the community and rural segment. Can prior authorization be automated in a MEDITECH environment? Yes, typically through a third-party automation layer that reads data from MEDITECH and writes auth numbers and statuses back into it, rather than a native MEDITECH feature. Phased implementations usually run 6-8 months, and once live can cut prior auth turnaround by up to 75%. Will MEDITECH eventually build APIs for payer-side RCM workflows? Possibly for some – CMS-0057-F will require certain payers to expose FHIR-based prior authorization APIs by January 1, 2027. But that mandate covers Medicare Advantage, Medicaid managed care, CHIP, and QHP-exchange payers only, so most commercial payers and workflows like claims status and denial appeals stay outside it regardless of what MEDITECH does on its end. At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let's talk! ‍ [👉 Book a 30-minute call](https://www.flobotics.io/book) Written byFilip Nasiadko CEO and Co-founder at Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareAIRPA ### Epic Automation | 2026 Epic Systems revenue cycle automation: why the EHR powering 300+ health systems still needs RPA to close labor, payer, and margin gaps in 2026. Jędrzej SzymulaApril 10, 2026 ](https://www.flobotics.io/blog/epic-automation)[ RCMHealthcare ### NextGen Automation | 2026 NextGen EHR automation: stop manual payer-portal copy-paste and validate claims against insurer rules before submission, not after denial. Bart TeodorczukMay 19, 2026 ](https://www.flobotics.io/blog/nextgen-automation)[ HealthcareAIRCM ### Meditech Automation | 2026 Meditech automation: why strong transaction handling still stalls on cross-workflow orchestration, and how to scale past it. Jędrzej SzymulaMarch 25, 2026 ](https://www.flobotics.io/blog/meditech-automation) [All articles →](https://www.flobotics.io/blog) --- # What Is Medical Billing? The Complete 101 Guide Canonical: https://www.flobotics.io/blog/what-is-medical-billing Author: Jędrzej Szymula Published: 2026-07-22 Updated: 2026-09-08 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/What Is Medical Billing? The Complete 101 Guide [Claims](https://www.flobotics.io/blog?category=claims)[Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # What Is Medical Billing? The Complete 101 Guide [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published July 22, 2026Updated September 8, 2026 On this page - [Before You Read:](#before-you-read) - [What Is Medical Billing?](#what-is-medical-billing) - [Medical Billing vs. Medical Coding: What's the Difference](#medical-billing-vs-medical-coding-what-s-the-difference) - [The Medical Billing Cycle: 10 Steps From Registration to Reimbursement](#the-medical-billing-cycle-10-steps-from-registration-to-reimbursement) - [The Codes Behind Every Claim: CPT, ICD-10, and HCPCS](#the-codes-behind-every-claim-cpt-icd-10-and-hcpcs) - [Why Claims Get Denied (and How Denials Get Fixed)](#why-claims-get-denied-and-how-denials-get-fixed) - [In-House vs. Outsourced vs. Automated Medical Billing](#in-house-vs-outsourced-vs-automated-medical-billing) - [Medical Billing as a Career](#medical-billing-as-a-career) - [Where AI and Automation Fit Into Medical Billing Today](#where-ai-and-automation-fit-into-medical-billing-today) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ### Before You Read: Medical Billing The process of translating a patient encounter into a claim, submitting that claim to an insurer, and collecting payment for the care a provider delivered. Medical Coding The step before billing – turning a doctor's notes, diagnosis, and treatment into standardized alphanumeric codes (ICD-10, CPT, HCPCS) that a biller then uses to build the claim. Clean Claim A claim that's accepted and paid the first time it's submitted, with no errors, missing data, or additional documentation requests. ## What Is Medical Billing? Medical billing is the process of collecting, checking, and submitting the information a healthcare provider needs to get paid for patient care. It sits at the center of the revenue cycle, connecting three parties: the patient, the provider, and the insurance payer. In practice, that means a medical biller takes the diagnosis and procedure codes a medical coder assigned to a visit, builds a claim around them, sends that claim to the patient's insurance company, tracks what happens to it, and follows up until the provider is paid – whether that payment comes from the insurer, the patient, or both. Medical billing splits into two broad categories. Professional billing covers claims submitted by individual providers – physicians, therapists, and other outpatient practitioners – usually on a standardized CMS-1500 form. Institutional billing covers claims from hospitals, skilled nursing facilities, and other institutions that bill for both the facility and the services provided inside it, usually on a UB-04 form. The forms, timelines, and payer expectations differ enough that most billers specialize in one or the other. ## Medical Billing vs. Medical Coding: What's the Difference These two roles get lumped together constantly, but they're distinct jobs with different skill sets. A medical coder works on the clinical side: reading procedure notes, lab results, and diagnosis documentation, then translating all of it into standardized codes. A medical biller takes those codes, builds the claim, and manages everything that happens to it afterward – submission, payer follow-up, denial management, and posting whatever payment eventually comes back. Coding tends to be more solitary and data-heavy; billing is more people-facing, since billers regularly deal directly with patients and insurance representatives to resolve issues. In smaller practices, one person often does both jobs. In larger organizations, they're separate roles – sometimes separate departments entirely. ## The Medical Billing Cycle: 10 Steps From Registration to Reimbursement The billing cycle is a structured, step-by-step sequence where each stage depends on the one before it. Miss something early and it cascades into a denial weeks later. The 10 core steps are: - Patient registration. Demographic and insurance information is collected – name, date of birth, address, insurance ID, and subscriber details. Errors here are one of the single biggest sources of denials downstream. - Insurance eligibility verification. The provider confirms the patient's coverage is active, checks plan type, copay, deductible, and whether the planned service needs prior authorization. - Patient check-in and encounter. The visit happens. Whatever is done during the encounter becomes the basis for the claim. - Medical coding. The provider's documentation is translated into ICD-10 diagnosis codes and CPT/HCPCS procedure codes. - Charge entry. Coded services are entered into the billing system with their associated fees. - Claim scrubbing. The claim is checked for errors – missing fields, mismatched codes, invalid modifiers – before it ever reaches the payer. - Claim submission. The clean claim is sent to the payer, usually electronically through a clearinghouse. - Payer adjudication. The insurer reviews the claim and decides to pay it in full, pay it partially, or deny it, generating an Explanation of Benefits (EOB). - Payment posting. Whatever the payer pays gets recorded against the patient's account. - Denial management and patient billing. Denied or underpaid claims get corrected and resubmitted; whatever balance remains gets billed to the patient. Eligibility verification and coding tend to have the largest downstream impact of any single step. Get either one wrong, and everything after it – scrubbing, submission, adjudication – is built on a bad foundation. ## The Codes Behind Every Claim: CPT, ICD-10, and HCPCS Every claim rests on three coding systems that work together but serve different purposes: - ICD-10 codes the diagnosis – the disease, symptom, or reason for the encounter. Maintained by the CDC in coordination with CMS, ICD-10 codes are alphanumeric and run 3 to 7 characters. - CPT codes the procedure – what was actually done during the visit. Maintained by the American Medical Association, CPT codes are five characters and start with a number. - HCPCS (specifically HCPCS Level II) codes supplies, equipment, and services that CPT doesn't cover – things like ambulance rides, durable medical equipment, or certain drugs. HCPCS Level II codes start with a letter, which is the fastest way to tell them apart from CPT. A claim pairs a CPT (or HCPCS) procedure code with the ICD-10 diagnosis code that justifies it. If the pairing doesn't make clinical sense to the payer's system, that's a denial waiting to happen. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Why Claims Get Denied (and How Denials Get Fixed) Most denials trace back to a handful of repeat offenders: - Incorrect patient demographics or eligibility. Misspelled names, expired coverage, or mismatched subscriber IDs – all caught before care ever happens, all preventable at registration. - Coding errors. Wrong diagnosis code, wrong procedure code, or a modifier that doesn't match the documentation. - Missing prior authorization. Certain procedures require payer sign-off before they happen; skip it, and the claim is denied regardless of how well it's coded. - Insufficient documentation of medical necessity. The payer doesn't see enough clinical justification for the service billed. - Non-covered services. The billed procedure simply isn't included in the patient's plan. - Duplicate claims. The same service submitted more than once, usually a process error rather than a clinical one. Fixing a denial means identifying which of these caused it, [correcting the underlying issue and resubmitting](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation) – or, if the payer's decision itself was wrong, filing a formal appeal with supporting documentation. The faster this loop runs, the less revenue gets written off entirely. ## In-House vs. Outsourced vs. Automated Medical Billing Practices generally choose between three models: In-house billing keeps the work with employed staff. It gives a practice direct control over the process, but it also means carrying the full cost of salaries, training, software, and ongoing compliance updates – regardless of how many claims move through the system in a given month. Outsourced billing hands the work to a third-party billing company, typically for a percentage of collections (commonly 4 to 10 percent). It brings dedicated coding and payer expertise without the fixed headcount cost, but it also means less direct control and, for high-revenue practices, potentially higher total cost than an in-house team. Automated billing is the newer option: software and AI agents handle eligibility checks, claim scrubbing, submission, and even denial resubmission with minimal manual work, while staff review only the genuine exceptions. This doesn't replace human judgment on complex cases, but it removes the repetitive, rule-based portion of the cycle that consumes most of a billing team's time – which is exactly where [claims management automation](https://www.flobotics.io/agents/claims-management-automation) and [denials management automation](https://www.flobotics.io/agents/denials-management-automation) fit in. ## Medical Billing as a Career Medical billing and coding roles carry a median salary of around $50,250 a year (about $24 an hour), with certified billers earning meaningfully more than non-certified peers. Roughly 68% of employers require certification for the role, and certifications like the AAPC's Certified Professional Biller (CPB) tend to translate directly into higher pay and better job prospects. The field's outlook is positive, with growth projected faster than the average for all occupations as the population ages and healthcare volume increases – and the role increasingly offers remote or hybrid flexibility once a biller has a few years of experience. ## Where AI and Automation Fit Into Medical Billing Today None of the ten steps above disappear because of automation – they still have to happen. What changes is who (or what) does the repetitive parts. Eligibility checks, claim scrubbing, and routine denial resubmission are exactly the kind of high-volume, rule-based work that [eligibility check automation](https://www.flobotics.io/agents/eligibility-check-automation) and [denials management](https://www.flobotics.io/agents/denials-management-automation) agents are built to absorb, freeing billing staff to handle the judgment calls: complex appeals, patient conversations, and the exceptions that genuinely need a person's attention. ## FAQ: What is a superbill? An itemized summary of a visit that includes diagnosis codes, procedure codes, and provider details, which a patient can submit to their insurer for reimbursement. What's the difference between CPT, ICD-10, and HCPCS codes? ICD-10 codes the diagnosis, CPT codes the procedure performed, and HCPCS Level II codes supplies, equipment, and services that CPT doesn't cover. Can medical billing be automated? Much of it can. Eligibility checks, claim scrubbing, and routine denial resubmission are high-volume and rule-based, making them well suited to automation, while complex appeals and patient-facing conversations still benefit from human judgment. What is medical billing in simple terms? It's the process of turning a patient visit into a claim, sending that claim to an insurance company, and collecting whatever payment is owed – from the insurer, the patient, or both. Is medical billing the same as medical coding? No. A coder translates clinical documentation into diagnosis and procedure codes. A biller uses those codes to build and submit the claim, then manages everything that happens to it afterward. What are the main steps in the medical billing process? Registration, eligibility verification, the patient encounter, coding, charge entry, claim scrubbing, submission, payer adjudication, payment posting, and denial management or patient billing. Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### Automation’s for Everyone: 100 Real-World RPA Use Cases Across Industries | 2026 RPA use cases across industries: see 100 real-world examples of process automation in action, from healthcare to manufacturing. Michał RejmanFebruary 23, 2024 ](https://www.flobotics.io/blog/rpa-use-cases-across-industries)[ RPAAI ### Agentic AI Frameworks | 2026 Agentic AI frameworks in 2026: which stacks Google and other leaders are betting on, explained with clear, research-backed answers. Jędrzej SzymulaDecember 02, 2025 ](https://www.flobotics.io/blog/agentic-ai-frameworks)[ RCMHealthcare ### Medical Coding Automation: Why (and How) Should You Start? Medical coding services, automated: how RPA improves claims accuracy and cuts manual coding errors for healthcare providers. Karl MielnickiMay 13, 2022 ](https://www.flobotics.io/blog/medical-coding) [All articles →](https://www.flobotics.io/blog) --- # The State of Claim Denials in U.S. Healthcare Canonical: https://www.flobotics.io/blog/claim-denials-in-healthcare-usa Author: Karl Mielnicki Published: 2026-07-13 Updated: 2026-09-08 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/The State of Claim Denials in U.S. Healthcare CTO Notes [AI](https://www.flobotics.io/blog?category=ai)[Denials](https://www.flobotics.io/blog?category=denials)[Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # The State of Claim Denials in U.S. Healthcare [Karl MielnickiCTO & Co-Founder of Flobotics](https://www.flobotics.io/our-editorial-team#mielnicki) Published July 13, 2026Updated September 8, 2026 On this page - [$48.4 billion pain point](#48-4-billion-pain-point) - [Key numbers at a glance](#key-numbers-at-a-glance) - [Denial rates by payer type aren't equal](#denial-rates-by-payer-type-aren-t-equal) - [The root-cause breakdown](#the-root-cause-breakdown) - [The prior authorization problem is now a clinical problem](#the-prior-authorization-problem-is-now-a-clinical-problem) - [The automation opportunity is real... and mostly unclaimed](#the-automation-opportunity-is-real-and-mostly-unclaimed) - [What the cost-per-denial math actually means for RCM teams?](#what-the-cost-per-denial-math-actually-means-for-rcm-teams) - [The strategic shift: from appeals to prevention](#the-strategic-shift-from-appeals-to-prevention) - [The bottom line](#the-bottom-line) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## $48.4 billion pain point Kodiak Solutions' State of the Healthcare Revenue Cycle report, published in March 2026 and built on aggregated data from more than 2,300 hospitals and 350,000 physicians, found that providers lost more than $48 billion in net revenue in 2025 to final claim denials and uncollected patient balances - up from $38.6 billion in 2024. That's a 25% jump in net revenue leakage in a single year. Zrodlo: Kodiak Solutions The median final denial rate rose from 2.5% in 2024 to 2.7% in 2025. That looks like a small move until you see what's driving it: clinical denials — claims rejected for lack of prior authorization or medical necessity — accounted for nearly all of the increase. For inpatient claims across all payer types, Kodiak found: - Requests-for-information (RFI) initial denial rates up more than 10% - Clinical initial denial rates up more than 12% - Final denial rates up more than 14% In other words, the growth isn't coming from sloppy paperwork getting slightly worse. It's concentrated in the categories payers have the most discretion over — and the most incentive to use that discretion aggressively. The American Hospital Association's 2025 Cost of Caring report puts a second number on the same problem from a different angle: hospitals spent an estimated $43 billion in 2025 trying to collect payments insurers already owed for care that had been delivered, including nearly $18 billion spent specifically on overturning claim denials. That's not lost revenue — that's additional spend just to get paid for work already done. ### Key numbers at a glance Metric | 2025 figure | Source | Net revenue lost to final denials + bad debt | $48.4B (+25% YoY) | Kodiak Solutions | Median final denial rate | 2.7% (up from 2.5%) | Kodiak Solutions | Hospital spend collecting payments already owed | $43B | AHA Cost of Caring 2025 | Spend specifically overturning denials | ~$18B | AHA Cost of Caring 2025 | Medicare Advantage initial denial rate | ~17% | Industry claims data | Average denied MA claim value | ~$1,000 (+22.4% YoY) | Industry claims data | National prior auth denial rate (mean) | ~11.5% | CMS-0057-F, CY2025 | Physicians reporting PA delays necessary care | 95% | AMA 2025 Survey | Physicians reporting a serious adverse event from PA | 26% | AMA 2025 Survey | Administrative costs avoided via automation | $258B | CAQH Index 2025 | Electronic prior auth adoption rate | 40% | CAQH Index 2025 | Cost to rework a claim (within 3 days / after 30 days) | $25 / $118 | AAPC Denial Management Benchmarks | ### Denial rates by payer type aren't equal National denial rates average somewhere in the 10–12% range across commercial, Medicaid, and Medicare Advantage combined, but Medicare Advantage stands out. MA plans denied roughly 17% of initial claim submissions in the most recent reporting period — well above the blended average. Of those, 57% were eventually overturned on appeal, which sounds like good news until you account for what it actually means: most MA denials aren't permanent revenue loss, they're a forced detour through appeals, resubmission, and weeks or months of delay before the provider sees the money they were always owed. The average denied amount on an MA-related claim also rose 22.4% year-over-year, landing at roughly $1,000 per claim — meaning each individual denial is not only more frequent, it's more expensive to chase. ### The root-cause breakdown Ask RCM teams what's driving the increase and the answer clusters around a small number of causes: - Missing or inaccurate claim data — cited by 50% of respondents in 2025 surveys as the single biggest factor behind rising denials, up 4 points from 2024. A separate provider survey found 68% point specifically to inaccurate or incomplete data captured at patient intake — the very first step of the revenue cycle. - Prior authorization issues — cited by 35% of respondents as a primary denial trigger. - Coding inaccuracies — outpatient coding denials rose 26% from 2024 to 2025. - Insufficient documentation — CMS itself identifies this as the single leading root cause of improper payments nationally: reviewers can't confirm a payment was proper because the supporting documentation wasn't there. The pattern is consistent: the majority of denial growth traces back to the front and middle of the revenue cycle — intake, eligibility, authorization, and documentation — not to appeals or back-end collections. Which means most of this is, in principle, preventable before a claim is ever submitted. ## The prior authorization problem is now a clinical problem Prior auth deserves its own section because the 2025–2026 data shows it's stopped being purely an administrative headache and started being a documented driver of patient harm. CMS's own CY2025 disclosures under CMS-0057-F show standard prior auth denial rates ranging from under 2% to above 27% depending on the plan, with a national mean around 11.5%. Some individual plans report denial rates as high as 52%. For Medicare Advantage specifically, insurers processed roughly 53 million prior authorization requests in 2024 and denied about 4.1 million of them — a 7.7% denial rate at massive scale. Payer denial rates just became public for the first time ACA marketplace claim denial rates by insurer, Plan Year 2024 data — first disclosed under CMS-0057-F transparency rule, deadline March 31, 2026 ACA marketplace claim denial rates by insurer, Plan Year 2024 Insurer / reporting group | Denial rate | Kaiser Permanente (best performer) | 6% | National average (175 plans) | 19% | Oscar Health (highest major insurer) | 25.3% | Highest-denying plan reported | 49% | Source: KFF, "Claims Denials and Appeals in ACA Marketplace Plans in 2024" (kff.org, March 2026), analyzing the first public disclosures under CMS's Interoperability and Prior Authorization Final Rule (CMS-0057-F). Underlying claims are Plan Year 2024 — the payer-level comparison itself only became publicly possible in 2026. The AMA's 2025 Prior Authorization Physician Survey is where the human cost shows up in the numbers: - 95% of physicians say prior auth delays access to necessary care - 95% say it significantly or somewhat increases physician burnout - 92% say it negatively affects clinical outcomes for their patients - 79% say patients abandon treatment altogether because of authorization friction - 32% say requests are often or always denied - 26% report that prior auth has led to a serious adverse event for a patient — including hospitalization, permanent impairment, or death - The average physician now completes 40 prior authorizations per week There's also an uncomfortable new wrinkle: as payers deploy their own AI to adjudicate authorization requests faster, decisions that used to take 3–5 business days for human review are now returned in hours — but the AMA's 2025 survey found those faster, more automated payer decisions carry denial rates 40% higher than human-reviewed ones. Payers are automating the denial side faster than providers are automating the prevention side. That gap is the single biggest strategic risk in RCM right now, and it's rarely named directly. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## The automation opportunity is real... and mostly unclaimed The good news, if there is any, is in the CAQH Index. The 2025 edition (covering 2024 data, released February 2026) found that U.S. healthcare avoided an estimated $258 billion in administrative costs through electronic transactions and automation — a 17% increase in cost avoidance year-over-year, alongside a 9% reduction in medical administrative spend. But the same report is a map of exactly how much is still on the table: - Electronic prior authorization adoption sits at just 40% — the lowest of any major transaction type CAQH tracks - Claim status inquiry automation has reached 81%; claim payment, 78% - Documentation attachments — the exact artifact behind most "insufficient documentation" denials — lag at just 24% (medical) and 28% (dental) electronic adoption - Fully adopting the electronic prior auth standard alone could save the industry $515 million annually and 14 minutes of staff time per authorization - CAQH estimates $20 billion or more in additional annual savings is achievable simply by shifting the remaining manual transactions — the ones still done by fax, portal re-entry, and phone — to electronic workflows More than half of health plans and roughly a quarter of provider organizations now report using AI somewhere in administrative workflows. That adoption curve is moving. It's just moving faster on the payer side than the provider side — which is exactly why denial rates are climbing even as overall automation spend increases. ## What the cost-per-denial math actually means for RCM teams? None of this lands unless you connect it to the unit economics RCM leaders manage every day. Industry benchmarking (AAPC, MGMA, HFMA, and others) consistently puts the average cost to rework a single denied claim at around $25 — if it's caught and worked within three days of denial. Let it sit for 30 days or more, and that cost climbs to roughly $118 per claim — a 4.7x cost multiplier driven purely by delay. That's the quiet part of the denials story: the financial damage isn't just the face value of the denied claim. It's the compounding labor cost of every day a claim sits untouched in a queue, multiplied across thousands of claims a month, on top of the $1,000-per-claim average now typical for a Medicare Advantage denial. ### The strategic shift: from appeals to prevention Two philosophies are competing for RCM budget right now, and the data above makes the case for one of them more clearly than most vendors are willing to say out loud. The first is detection and appeal — reviewing charts and claims after the fact, usually with clinical or coding expertise, to catch what should have been billed correctly or to build a stronger appeal once a denial has already landed. It's valuable, and it's where a lot of clinical-AI vendors in this space concentrate their product. The second is prevention at the source — using automation at eligibility verification, prior authorization submission, and claims preparation to stop the RFI and clinical denials (the categories actually driving 2025's increase) from being generated in the first place. Given that Kodiak's data shows the entire rise in denial rates is concentrated in RFI and clinical categories — not random noise — prevention-first automation is targeting the actual growth curve, not the historical baseline. Neither approach replaces the other. Appeals will always be necessary for genuinely disputed clinical decisions. But if 50% of denials trace back to missing or inaccurate data at intake, and prior auth electronic adoption is still stuck at 40%, the highest-leverage fix available to most RCM teams in 2026 is upstream: eligibility, authorization, and claims prep automation that keeps the error from ever reaching the payer. ## The bottom line Denials aren't a back-office nuisance anymore — they're a $48 billion line item, a documented driver of delayed and abandoned patient care, and a race that payers are currently winning because they've automated faster than providers have. The data points in one clear direction: the highest-leverage response isn't better appeals letters, it's closing the automation gap upstream — at eligibility, prior auth, and claims prep — before a denial is ever generated. #### Summary: At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let's talk! 👉 [Book a 30-minute call ](https://www.flobotics.io/book) - [Kodiak Solutions, "State of the Healthcare Revenue Cycle" (March 2026)](https://www.kodiaksolutions.io/internal/benchmarking_reports/march_2026_benchmarking_intelligence_report) - [Modern Healthcare — "Rising claims denials denting provider revenue: Kodiak Solutions"](https://www.modernhealthcare.com/providers/mh-claims-denials-provider-revenue-kodiak-solutions/) - [TechTarget — "Hospitals lost over $48B from claims denials, uncollected bills"](https://www.techtarget.com/revcyclemanagement/news/366641065/Hospitals-lost-over-48B-from-claims-denials-uncollected-bills) - [Healthcare Finance News — "Hospitals' net revenue leakage increases 25% due to denied claims"](https://www.healthcarefinancenews.com/news/hospitals-net-revenue-leakage-increases-25-due-denied-claims) - [BusinessWire — Kodiak Solutions 2025 proprietary data release](https://www.businesswire.com/news/home/20260331038554/en/Healthcare-Provider-Organizations-Saw-Net-Revenue-Losses-From-Final-Denials-and-Bad-Debt-Grow-by-25-in-2025-According-to-Kodiak-Solutions-Proprietary-Data) - [American Hospital Association — 2025 Cost of Caring Report](https://www.aha.org/guides-and-reports/2026-03-09-2025-cost-caring-report) - [CMS.gov — Interoperability and Prior Authorization Final Rule (CMS-0057-F) Fact Sheet](https://www.cms.gov/newsroom/fact-sheets/cms-interoperability-prior-authorization-final-rule-cms-0057-f) - [American Medical Association — 2025 Prior Authorization Physician Survey](https://www.ama-assn.org/system/files/prior-authorization-survey.pdf) - [AJMC — "AMA Survey Highlights Growing Burden of Prior Authorization on Physicians, Patients"](https://www.ajmc.com/view/ama-survey-highlights-growing-burden-of-prior-authorization-on-physicians-patients) - [CAQH — "2025 CAQH Index Shows U.S. Healthcare Avoided $258 Billion..."](https://www.caqh.org/blog/2025-caqh-index-shows-u.s.-healthcare-avoided-258-billion-and-accelerated-automation-interoperability-and-ai-adoption) - [AAPC — Denials Management & Appeals Reference Guide (denial rework-cost benchmarks)](https://www.aapc.com/medical-coding-books/master-denials-management-and-appeals-reference-guide/) ## FAQ: Why do medical claims get denied? The most common reasons are incorrect patient or insurance information, coding errors, missing prior authorization, insufficient documentation of medical necessity, non-covered services, and duplicate submissions. What are the two types of denials? Hard denials are effectively final — the payer won't pay and there's no real path to recover the money, common with non-covered services or missing prior authorization. Soft denials are temporary and correctable: the claim is returned for missing information or a coding error and can be fixed and resubmitted, and roughly 61% of initial denials fall into this recoverable category. How many types of denials are there? Most RCM teams group denials into two broad categories, hard and soft, but denial-management systems often track a dozen or more specific sub-categories such as eligibility, authorization, coding, timely filing, and medical necessity. The exact count depends on how granular a given payer's or vendor's classification system is. Written byKarl Mielnicki CTO & Co-Founder of Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Facts About Google Antigravity | Over 30 Questions Answered Canonical: https://www.flobotics.io/blog/30-facts-about-google-antigravity Author: Jędrzej Szymula Published: 2026-07-03 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Facts About Google Antigravity | Over 30 Questions Answered [AI](https://www.flobotics.io/blog?category=ai) # Facts About Google Antigravity | Over 30 Questions Answered [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published July 03, 2026Updated September 1, 2026 On this page - [What Exactly Is Google Antigravity?](#what-exactly-is-google-antigravity) - [What Is the Coolest Google Antigravity Trick?](#what-is-the-coolest-google-antigravity-trick) - [How to Use Google Antigravity for Beginners](#how-to-use-google-antigravity-for-beginners) - [How Does Google Antigravity Deploy Apps to Production?](#how-does-google-antigravity-deploy-apps-to-production) - [What Are Google Antigravity's Limitations — Not Just in Coding?](#what-are-google-antigravity-s-limitations-not-just-in-coding) - [Is Google Antigravity Broken?](#is-google-antigravity-broken) - [What Are the Disadvantages of Google Antigravity?](#what-are-the-disadvantages-of-google-antigravity) - [What Is Similar to Google Antigravity?](#what-is-similar-to-google-antigravity) - [How Best to Use Google Antigravity?](#how-best-to-use-google-antigravity) - [Where Can I View Google Antigravity Usage?](#where-can-i-view-google-antigravity-usage) - [What Is the App Like Google Antigravity?](#what-is-the-app-like-google-antigravity) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Exactly Is Google Antigravity? The name "Google Antigravity" means two completely different things depending on who you ask, and that confusion is worth clearing up before anything else. The Easter egg. Long before Google built a development platform, "Google Antigravity" referred to a viral browser trick. Visit the search page, type "Google Gravity," and click "I'm Feeling Lucky." Every element on the homepage — the logo, the search bar, the buttons — loses its grip and falls to the bottom of the browser window in a satisfying physics simulation. You can drag the pieces around, throw them, and watch them bounce off each other. It was created by a developer known as Mr. doob, and despite widespread association with Google, it is not an official Google product — it's a third-party JavaScript physics experiment hosted at mrdoob.com. (Source: [Google Antigravity: The Fun Easter Egg That Makes Your Browser Defy Physics — Medium/KASATA](https://kasata.medium.com/google-antigravity-the-fun-easter-egg-that-makes-your-browser-defy-physics-c4a536856bb3)) The IDE. Starting November 18, 2025, Google launched an actual product called Google Antigravity: an agent-first development platform where AI agents autonomously plan, write, test, and deploy code. It's a real, downloadable desktop application — a modified fork of VS Code — and it was significantly upgraded to Antigravity 2.0 at Google I/O 2026. (Source: [Build with Google Antigravity — Google Developers Blog](https://developers.googleblog.com/build-with-google-antigravity-our-new-agentic-development-platform/)) Both meanings attract huge search traffic, which is why articles on this topic tend to blur them together. This one covers both, clearly labeled. ## What Is the Coolest Google Antigravity Trick? The coolest trick depends on which "Google Antigravity" you mean. Easter egg version: The gravity simulation itself is the trick — everything on the Google homepage falls under simulated physics. What makes it genuinely impressive is interactivity: you can pick up the fallen elements, throw them across the screen, and they collide with each other using realistic mass and velocity calculations. An alternate version called "Google Space" makes elements float upward instead of falling — accessible at [elgoog.im/floating](https://elgoog.im/floating/). The physics engine behind both comes from Box2D, the same library used in games like Angry Birds. (Source: [Google Gravity — elgooG](https://elgoog.im/gravity/)) IDE version: The most impressive demonstration Google ran at I/O 2026 was having Antigravity 2.0 scaffold a working operating system from scratch in 12 hours — entirely through the multi-agent orchestration system, with agents writing code, spawning a browser to test it live, hitting errors, self-correcting, and looping until it worked. For everyday use, the Browser Subagent is the most striking feature: it opens a real Chrome instance and physically clicks through your app to test it, the same way a QA engineer would. (Source: [Google I/O 2026: Google Claims Antigravity 2.0 Created an OS in 12 Hours — Digit.in](https://www.digit.in/news/general/google-io-2026-google-claims-antigravity-20-created-an-operating-system-in-12-hours-brings-vibe-coding-to-android.html)) ## How to Use Google Antigravity for Beginners If you want the Easter egg: Go to google.com, type "Google Gravity" into the search bar, and instead of pressing Enter, click the "I'm Feeling Lucky" button. The page will collapse into a gravity simulation. Alternatively, visit [elgoog.im/gravity](https://elgoog.im/gravity/) directly. No account, no download, no setup. If you want the IDE: Download the desktop app from [antigravity.google/download](https://antigravity.google/download), install it on macOS, Windows, or Linux, and sign in with a personal Gmail account (Google Workspace accounts may have eligibility issues during preview). Once you're in, start with the Manager Surface rather than the Editor View. In the chat interface, describe a project goal in plain language — something like "build a simple to-do app with a Firebase backend" — and watch the agents break it into a plan and start executing. Review the Artifacts they generate at each checkpoint, leave comments where needed, and merge when satisfied. The free tier is sufficient for learning the workflow. (Source: [Getting Started with Google Antigravity — Google Codelabs](https://codelabs.developers.google.com/getting-started-google-antigravity)) This "describe the outcome, review the Artifacts, course-correct" approach is the same logic that drives [intelligent automation](https://www.flobotics.io/business-process-automation) in business workflows — you don't micromanage each step, you delegate to agents and validate results. ## How Does Google Antigravity Deploy Apps to Production? Antigravity 2.0's default deployment path runs through Firebase Hosting, and the integration is tight enough that no separate DevOps configuration is required for most projects. When an agent finishes building, it can deploy directly using either built-in agent skills or the Firebase CLI. (Source: [What's New from Firebase at Google I/O 2026 — Firebase Blog](https://firebase.blog/posts/2026/05/google-io-2026-announcements/)) The recommended workflow for a full production deploy looks like this: prototype fast in Google AI Studio (the web-based companion tool), then hand off to Antigravity for multi-file architecture, testing, and deployment. At the deployment stage, Antigravity agents provision Firebase projects — database, auth, storage — automatically when the app is ready to go persistent. You can also deploy to other hosting targets via the Antigravity CLI, which supports platform-agnostic deployment through GitHub Actions. Firebase Studio, Google's previous browser-based development environment, was sunset as of I/O 2026 and migrated into the Antigravity ecosystem. Existing Firebase Studio projects have a documented migration path at [codelabs.developers.google.com/antigravity/how-to-migrate-from-firebase-studio-to-antigravity](https://codelabs.developers.google.com/antigravity/how-to-migrate-from-firebase-studio-to-antigravity). (Source: [Firebase Studio Sunset and Project Migration — Google](https://firebase.google.com/docs/studio/migrating-project)) For enterprise deployments that need more control, Antigravity 2.0 added a Managed Agents tier inside the Gemini API, which lets teams run agent workloads in Google Cloud infrastructure with more governance over where code executes and what data the agents can access. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## What Are Google Antigravity's Limitations — Not Just in Coding? Most reviews focus on rate limits, but Antigravity's real limitations run deeper. (Source: [Google Antigravity 2.0 Review 2026 — AICoderScope](https://aicoderscope.com/blog/google-antigravity-review-2026/), [I Tried Google's Antigravity for a Week — XDA Developers](https://www.xda-developers.com/tried-googles-antigravity-limitation-made-close-it-good/)) Compute credit opacity. Rather than counting tokens or requests in a straightforward way, Antigravity uses "compute effort" — a metric Google doesn't publish conversion rates for. A complex multi-agent task can silently consume the majority of your weekly quota in 20–30 minutes of active use. You won't know until you're locked out. No SOC 2, no GDPR addendum — for the free/Pro tier. As of May 2026, the standalone Antigravity desktop app (personal Gmail sign-in) has no published SOC 2 Type II certification or formal GDPR data-processing agreement of its own. For any company handling European user data on the free/Pro tier, this is a hard blocker for production use — though the separate enterprise Managed Agents tier running on Google Cloud/Vertex AI does inherit Google Cloud's SOC 2/3 and GDPR-aligned certifications. (Source: [Google Cloud Trust Center — Security and Compliance](https://cloud.google.com/trust-center), accessed 2026) VS Code extension incompatibility. Because Antigravity is a VS Code fork, it can't access the official VS Code Marketplace due to Microsoft's licensing terms. The C# Dev Kit, the official GitHub authentication extension, and other Microsoft-licensed extensions simply don't work. Third-party extensions available in Open VSX are supported, but the gap is real. No organizational governance in free/Pro tiers. Seat management, team permissions, and audit logs are enterprise-only features. A team of five on the Pro plan has no way to see which team member ran which agent task or what code was generated. Infrastructure instability. The tool is still in public preview, and it shows. Between December 2025 and May 2026, Google cut free tier quotas four times without advance notice. Outages have affected login, model access, and the agent conversation system — see the section below. These aren't just coding limitations — they're organizational, compliance, and reliability limitations that affect whether a business can actually depend on this tool. For teams already managing [agentic AI tools and platforms](https://www.flobotics.io/blog/agentic-ai-tools-platforms-overview) across their stack, these gaps need to be on the evaluation checklist. ## Is Google Antigravity Broken? Not permanently, but it has had real reliability problems. Antigravity has experienced multiple service disruptions since launch, tracked publicly by StatusGator since January 2026. Notable incidents: A widespread outage on January 22, 2026 left users unable to access the model selector or log in. A 9-hour service disruption on April 15, 2026 affected the agent conversation feature, with users hitting "Agent terminated due to error" repeatedly. Antigravity servers went down for over 7 hours in another incident documented on Google's own developer forums. (Source: [Is Google Antigravity Down? — IsDown.app](https://isdown.app/status/google-antigravity), [Service Disruption Regarding Google Antigravity IDE — Google AI Developers Forum](https://discuss.ai.google.dev/t/service-disruption-regarding-the-google-antigravity-ide/140225)) Incidents typically resolve within 44 minutes on average, but multi-hour outages have occurred. StatusGator has been tracking Antigravity uptime since January 26, 2026 and maintains a public outage map and history at [statusgator.com/services/google-antigravity](https://statusgator.com/services/google-antigravity). The Antigravity 2.0 launch in May 2026 also caused its own set of disruptions: the automatic update overwrote developer setups without warning, stripping back terminals and direct code editing features in favor of the new chat interface. Not a crash — but thousands of developers reported their workflows broken overnight. (Source: [Google Antigravity 2.0 Broke Thousands of Developer Setups Overnight — RevolutionInAI](https://www.revolutioninai.com/2026/05/google-antigravity-2-0-update-developer-backlash.html)) The short answer: it's not broken in the sense of permanently non-functional. But it has a reliability track record that warrants caution before depending on it for daily production work. ## What Are the Disadvantages of Google Antigravity? Summarizing across all the evidence gathered: Unpredictable pricing. Google has restructured the pricing tiers multiple times since November 2025. Free tier limits were cut 92% in the first six weeks. The credit system's per-model costs remain unpublished, making budgeting for Pro and Ultra Max unreliable. (Source: [Users Protest as Google Antigravity Price Floats Upward — DevClass](https://www.devclass.com/ai-ml/2026/03/13/users-protest-as-google-antigravity-price-floats-upward/5209219)) No fine-grained control for production engineering. Antigravity is designed for high-level mission delegation, not line-by-line precision. Developers who want to review every change before it's applied, or who work in codebases where a wrong edit could cascade failures, will find the agent's autonomy more anxiety-inducing than helpful. Heavy infrastructure requirements. The Browser Subagent and multi-agent parallelism demand significant compute. On lower-end machines or slow connections, the tool is noticeably sluggish. Preview-phase instability. The product is still in public preview. Features appear and disappear between updates. Pricing changes without notice. The 2.0 launch broke existing setups silently. Organizations that need predictable tooling are better served by products with stable release cycles. Lock-in risk. Firebase is the default deployment target, and the tighter the integration gets, the harder it becomes to move projects elsewhere. Teams migrating away from Firebase Studio have already discovered this after that product was sunset. ## What Is Similar to Google Antigravity? The main alternatives in 2026 fall into two categories: IDE-based tools and terminal/CLI agents. (Source: [Best Antigravity Alternatives in 2026 — AgentPedia](https://agentpedia.codes/blog/best-antigravity-alternatives-2026), [Agentic IDE Comparison: Cursor vs Windsurf vs Antigravity — Codecademy](https://www.codecademy.com/article/agentic-ide-comparison-cursor-vs-windsurf-vs-antigravity)) Cursor is the closest GUI-first alternative — a VS Code fork with deeply integrated AI, strong inline completions, and an agent mode for multi-file editing. It scores ~77% on SWE-bench and costs $20/month for Pro. Where it differs from Antigravity: Cursor keeps the developer hands-on at every step; Antigravity is more autonomous by default. Windsurf (now Devin Desktop, following Cognition's acquisition) takes a similar IDE-native approach with Cascade, its persistent multi-step AI workflow engine. Pro costs $15/month. It has historically been stronger for front-end work. Claude Code is Anthropic's terminal-native agent that works alongside your existing editor rather than replacing it. It's the most conservative of the major tools — it takes careful, reversible steps and checks in before significant changes. It's the preferred choice for production-critical codebases where trust matters more than speed. GitHub Copilot, Cline, and Kilo Code run as VS Code extensions, integrating tightly into existing workflows without requiring a new application install. For a broader view of how these tools fit into a full [intelligent automation](https://www.flobotics.io/business-process-automation) strategy — beyond just code generation — see how [agentic AI differs from generative AI](https://www.flobotics.io/blog/agentic-ai-vs-generative-ai) in terms of what each can actually automate end-to-end. ## How Best to Use Google Antigravity? The developers getting the most out of Antigravity treat it as a rapid-prototyping and scaffolding environment, not a production engineering tool. The workflow that works: Start with a clear mission brief. The more specific your initial prompt, the better the agents perform. Instead of "build me an app," try "build a single-page React app with a Firebase Firestore backend that lets users create and delete task lists — mobile-responsive, no auth required for the prototype." Agents produce better plans when they have scope constraints upfront. Use the Manager Surface for big tasks, the Editor View for precision. For end-to-end scaffolding, spawn an agent from the Manager Surface and let it run. For targeted edits where you know exactly what you want changed, switch to the Editor View and work inline with the AI assistant. Review Artifacts at every checkpoint. Antigravity's Artifact system — task lists, implementation plans, screenshots, browser recordings — is what separates it from older AI coding tools. Use it. Leave comments on Artifacts instead of re-prompting from scratch; agents incorporate feedback more accurately when they can see which part of their plan you're responding to. Monitor your compute budget proactively. Because Google doesn't publish per-model credit costs, check your usage dashboard frequently during complex tasks. Pause agent runs if you're approaching your limit — a task left half-finished is more disruptive than a task you scheduled for the next day. (Source: [Google Antigravity Pricing 2026: Is It Free? Real Limits Tested — Toolworthy](https://www.toolworthy.ai/tool/google-antigravity)) Pair it with Claude Code or Cursor for production work. Use Antigravity to get from zero to a working prototype quickly, then hand the codebase to a more conservative tool for production hardening, security review, and deployment to infrastructure you control. This two-stage approach is increasingly common among teams who build fast but need to ship responsibly. For organizations mapping this into a broader [automation technology stack](https://www.flobotics.io/blog/automation-technologies), Antigravity sits best in the "prototype and scaffold" layer — feeding into human-reviewed deployment pipelines rather than owning production deployments end-to-end. ## Where Can I View Google Antigravity Usage? There are three places to monitor your Antigravity usage, depending on what you're trying to track. In-app usage dashboard. Inside the Antigravity desktop app, navigate to Settings → Usage. This shows your current compute credit consumption against your plan's weekly allocation, broken down by session. Note that Google does not show per-model credit costs here — you see aggregate consumption, not the cost per individual agent task. Google Antigravity pricing page. The official pricing page at [antigravity.google/pricing](https://antigravity.google/pricing) shows plan limits and current tier descriptions. Check this page periodically, as limits have been revised multiple times since launch. StatusGator for uptime monitoring. If you're monitoring platform availability rather than your own usage, [statusgator.com/services/google-antigravity](https://statusgator.com/services/google-antigravity) provides real-time status, outage history, and incident reports independently of Google's own status page. Useful for teams who need an objective third-party uptime record. (Source: [Google Antigravity Status — StatusGator](https://statusgator.com/services/google-antigravity)) For enterprise deployments on the Managed Agents tier via Google Cloud, usage is also visible through the standard Google Cloud Console billing dashboard, where compute costs are billed per-API-call in the Gemini API. ## What Is the App Like Google Antigravity? If you're looking for tools that do what the Easter egg does (gravity/physics simulations on web pages), the closest alternatives are all hosted at [elgoog.im](https://elgoog.im/) — a collection of restored Google Easter eggs including Google Space (floating elements), Google Mirror, and Google Sphere. They work in any browser, no install needed. If you're looking for tools that do what the IDE does, see the alternatives section above: Cursor, Windsurf/Devin Desktop, Claude Code, and GitHub Copilot are the four most comparable products currently available. Each has a meaningfully different philosophy around how much autonomy the AI should have versus how much control you keep — pick based on your risk tolerance and workflow, not just benchmarks. (Source: [6 Best Google Antigravity Alternatives and Competitors in 2026 — Emergent.sh](https://emergent.sh/learn/best-google-antigravity-alternatives-and-competitors)) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ AI ### What Is Google Antigravity | Basics Guide What is Google Antigravity? A basics guide to how it works, its free tier for production workflows, and how it compares to Claude Code. Bart TeodorczukJune 29, 2026 ](https://www.flobotics.io/blog/what-is-google-antigravity)[ AIRCMHealthcare ### Claude for Healthcare from Anthropic Claude for Healthcare from Anthropic: what's still unclear on data storage, routing, and third-party access before you roll it out to staff. Dominik PutMay 26, 2026 ](https://www.flobotics.io/blog/anthropic-annoucement-claude-for-healthcare)[ HealthcareAIRPA ### Epic Automation | 2026 Epic Systems revenue cycle automation: why the EHR powering 300+ health systems still needs RPA to close labor, payer, and margin gaps in 2026. Jędrzej SzymulaApril 10, 2026 ](https://www.flobotics.io/blog/epic-automation) [All articles →](https://www.flobotics.io/blog) --- # What Is Google Antigravity | Basics Guide Canonical: https://www.flobotics.io/blog/what-is-google-antigravity Author: Bart Teodorczuk Published: 2026-06-29 Updated: 2026-09-12 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/What Is Google Antigravity | Basics Guide [AI](https://www.flobotics.io/blog?category=ai) # What Is Google Antigravity | Basics Guide [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published June 29, 2026Updated September 12, 2026 On this page - [What Is Google Antigravity?](#what-is-google-antigravity) - [What Does Google Antigravity Do?](#what-does-google-antigravity-do) - [Is Google Antigravity Free?](#is-google-antigravity-free) - [Who Has Access to Google Antigravity?](#who-has-access-to-google-antigravity) - [Does Google Antigravity Requires Google Account?](#does-google-antigravity-requires-google-account) - [How to Connect Antigravity to Google?](#how-to-connect-antigravity-to-google) - [What's Google Antigravity Timeline?](#what-s-google-antigravity-timeline) - [Where Is Google Antigravity Installed?](#where-is-google-antigravity-installed) - [Is There an Online Version of Google Antigravity?](#is-there-an-online-version-of-google-antigravity) - [Is There an App for Google Antigravity? Can It Be Runned on a Phone?](#is-there-an-app-for-google-antigravity-can-it-be-runned-on-a-phone) - [How to Do Vibe Coding in Google Antigravity?](#how-to-do-vibe-coding-in-google-antigravity) - [What Are Google Antigravity Usage Limits?](#what-are-google-antigravity-usage-limits) - [How Does Google Antigravity Compare to Claude Code?](#how-does-google-antigravity-compare-to-claude-code) - [Summary: Google Antigravity Looks Promissing](#summary-google-antigravity-looks-promissing) - [Is Google Antigravity Legit?](#is-google-antigravity-legit) - [So Should We Trust Google Antigravity Today?](#so-should-we-trust-google-antigravity-today) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Is Google Antigravity? Google Antigravity is Google's agentic development platform – an AI-powered IDE and toolchain that lets developers delegate complex coding tasks to autonomous AI agents. It was officially announced on November 18, 2025, alongside the release of Gemini 3. Think of it less as a smarter autocomplete and more as a coordination layer for AI agents that can plan, write, test, and deploy software on your behalf. Technically, the IDE component is a heavily modified fork of Visual Studio Code. But "just an IDE" undersells what Antigravity actually is. The platform gives multiple AI agents direct access to an editor, a terminal, and a live browser instance – so they can write the code, run it, click around the UI to test it, spot bugs, fix them, and loop back – all without you being in the loop every step of the way. At Google I/O 2026 (May 2026), Google launched Antigravity 2.0, expanding it from an IDE into a full development platform with five components: a standalone desktop app, a new CLI (written in Go), a developer SDK, Managed Agents via the Gemini API, and an enterprise deployment path. Google's own demo at I/O showed Antigravity 2.0 scaffolding a working operating system in 12 hours. This fits squarely into the broader wave of [agentic AI tools and platforms](https://www.flobotics.io/blog/agentic-ai-tools-platforms-overview) reshaping how software teams work in 2026. As detailed in [Google's official announcement of the agentic development platform](https://developers.googleblog.com/build-with-google-antigravity-our-new-agentic-development-platform/) on the Google Developers Blog, and confirmed on the [Google Antigravity product site](https://antigravity.google/), the tool launched alongside Gemini 3 on November 18, 2025. ## What Does Google Antigravity Do? Antigravity's core workflow revolves around giving agents a mission and watching them execute it end-to-end. Its key capabilities include: Editor View + Manager Surface. The Editor View is a familiar AI-powered IDE for hands-on coding. The Manager Surface is where the real shift happens: you spawn multiple agents, assign them roles, and watch them work asynchronously across different workspaces in parallel. Browser-in-the-Loop Testing. Antigravity spins up a real Chrome instance – the Browser Subagent – which actually uses your application as it builds it. It clicks buttons, fills in forms, and if something breaks, the agent sees it, debugs it, and fixes it. This closes the loop between writing code and validating it. Artifacts. Rather than scrolling through raw tool call logs, Antigravity agents produce Artifacts – human-readable deliverables like task lists, implementation plans, screenshots, and browser session recordings. You can leave feedback directly on an Artifact (like commenting on a doc), and the agent incorporates it without stopping execution. Multi-Agent Orchestration. Antigravity 2.0's Agent Teams panel lets you compose squads of subagents with explicit roles, each running in its own sandbox in parallel, all tracked on a unified timeline. You can pause, redirect, or kill individual agents independently. Model Optionality. Antigravity supports Gemini 3.5 Flash, Gemini 3 Pro, Claude Sonnet 4.5, and GPT-OSS – so you're not locked into a single AI model. This "agents that act instead of just generate" philosophy mirrors the broader distinction between [agentic AI vs. generative AI](https://www.flobotics.io/blog/agentic-ai-vs-generative-ai): generative AI writes the code; agentic AI writes it, runs it, tests it, and ships it. Flobotics's own [prior authorization automation case study](https://www.flobotics.io/case-studies/90-faster-packet-submissions-prior-authorization-automation) shows this same agent-driven, closed-loop approach cutting packet submission time by 90% in a live healthcare RCM workflow. Google outlines all five components of this expansion in its own [Google Antigravity @ I/O 2026 recap](https://antigravity.google/blog/google-io-2026), including the Agent Teams capability behind the operating-system demo. ## Is Google Antigravity Free? Yes, for individuals – with limits. Antigravity is available in public preview at no cost with a personal Gmail account. The free tier gives you access to Gemini 3 Pro, Gemini 3 Flash, Claude Sonnet 4.5, and GPT-OSS with weekly rate limits. Paid tiers as of 2026: - Free: $0/month – all models, gated by weekly rate limits - Google AI Pro: $20/month – higher limits, flexible AI credit pool - Google AI Ultra: $100/month – priority access and roughly 5x Pro capacity, per [Google's own I/O 2026 recap](https://antigravity.google/blog/google-io-2026) Note: Google no longer lists a flat monthly price for paid tiers on its [pricing page](https://antigravity.google/pricing) — plans are now bundled with the broader Google AI subscription, so confirm current pricing before quoting it to prospects. No credit card is required to get started on the free tier. Current plan details are listed on [Google Antigravity's official pricing page](https://antigravity.google/pricing). ### Who Has Access to Google Antigravity? Antigravity is in public preview – anyone with a personal Gmail account can download and use it at no cost. There are no waitlists as of mid-2026. Enterprise access (Antigravity Teams / Enterprise tier) is available with SSO, SCIM provisioning, audit logs, and managed agent execution – primarily for organizations deploying it at scale via Google Cloud. ### Does Google Antigravity Requires Google Account? Yes. A personal Gmail account is required to sign in. Antigravity authenticates via standard Google OAuth – the same flow you use for Gmail or Google Drive. After downloading the app and running the installer, you sign in with your Google account to activate your workspace. One caveat: not all Google accounts are currently eligible. Google Workspace accounts (company accounts) sometimes face eligibility issues during the preview period. If you see an "account not eligible" error, try signing in with a personal @gmail.com account. ### How to Connect Antigravity to Google? Antigravity connects to Google services natively – it's a Google product. After sign-in with your Gmail account, it automatically has access to your Google Cloud project context if configured. For deeper integrations: - Firebase: Antigravity 2.0 has native Firebase integration – agents can scaffold Firebase backends directly from a prompt. - Google Cloud: Enterprise deployments connect via Google Cloud Console. - Google Play Console: At I/O 2026, Google announced that AI Studio (and by extension, the Antigravity ecosystem) can publish apps directly to the Google Play test track. Standard Google OAuth handles authentication. No separate API key setup is required for individual use. ### What's Google Antigravity Timeline? Here's the full arc: - November 18, 2025: Google announces Antigravity as a public preview alongside Gemini 3. Initial free tier: 250 requests/day, support for Gemini 3 Pro, Claude Sonnet 4.5, GPT-OSS. - December 2025: First significant free tier cuts. Requests/day reduced from 250 to ~20 on Gemini Pro. User trust issues begin. - Early 2026: Persistent reports of rate limit inconsistencies; Pro subscribers report multi-day lockouts on Claude models. - March 2026: Pricing restructured. "Ultra" plan renamed to "Ultra Max," price reduced from $249.99 to $200/month. - May 19–20, 2026 (Google I/O 2026): Antigravity 2.0 announced. Full platform expansion: new desktop app, CLI, SDK, Managed Agents API tier, enterprise path, Android vibe coding support, and Google AI Studio mobile app. - June 2026 (current): Platform in active development. Antigravity 2.0 available for download; public preview continues at no cost for individuals. For the full story behind the desktop app, CLI, and SDK launch, see Google's own [Introducing Google Antigravity 2.0](https://antigravity.google/blog/introducing-google-antigravity-2) post. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Where Is Google Antigravity Installed? Google Antigravity is a desktop application downloaded from [antigravity.google/download](https://antigravity.google/download). It installs locally on your machine like any desktop app. Supported platforms: - macOS (Apple Silicon and Intel) - Windows (x64) - Linux (x64,.deb and.tar.gz) There is also an Antigravity CLI (shipped with Antigravity 2.0) for developers who prefer terminal workflows. It's written in Go and can be used independently of the desktop app. ### Is There an Online Version of Google Antigravity? Not in the traditional "open your browser and start coding" sense. Antigravity is primarily a desktop application. However, Google AI Studio (accessible at aistudio.google.com) provides a web-based environment for prompting and prototyping with Gemini models that partially overlaps with Antigravity's lighter use cases. For agent-first development with the full feature set (Manager Surface, Browser Subagent, multi-agent orchestration), the desktop app is required. ### Is There an App for Google Antigravity? Can It Be Runned on a Phone? The main Antigravity product is a desktop application – there is no official mobile version of Antigravity itself. However, two developments bring mobile into the picture: - Google AI Studio Mobile App: Announced alongside Antigravity 2.0 at I/O 2026, the Google AI Studio mobile app for Android and iOS lets you describe an idea on the go and have a working prototype with a Firebase backend ready by the time you're at your desk. It's positioned as the mobile entry point for vibe coding within Google's ecosystem. - Third-Party App: There is an unofficial "Mobile IDE for Antigravity AI" app on the Apple App Store (App ID: 6759795486), but this is not an official Google product. For serious development work, you'll need the desktop app. The mobile flow is best treated as a quick prototyping entry point that hands off to the desktop. Google covers the mobile-to-desktop handoff in its own [Google AI Studio at I/O 2026 announcement](https://blog.google/innovation-and-ai/technology/developers-tools/google-ai-studio-io-2026/). ## How to Do Vibe Coding in Google Antigravity? "Vibe coding" in Antigravity means using natural language as your primary programming interface. Instead of specifying implementation details, you describe the outcome you want, and the agents figure out how to get there. The practical workflow looks like this: - Open Antigravity and navigate to the Manager Surface. - Describe your goal in plain language (e.g., "Build a task management app with Firebase backend and user authentication"). - Antigravity's Manager Agent breaks it down into a plan and spawns specialized subagents for architecture, frontend, backend, and testing. - Each agent works in its own sandbox. The Browser Subagent launches a Chrome instance and tests the live app. - Artifacts appear as the work progresses – review them, leave comments, and the agents self-correct. - Merge when satisfied. The key difference from older AI coding assistants: you don't direct each step. You set the mission, review Artifacts at checkpoints, and course-correct at a high level. This is outcome-focused development – and it's why XDA-Developers called Antigravity "the perfect example of vibe coding" over tools like Cursor. For teams already running [intelligent automation](https://www.flobotics.io/business-process-automation) across business workflows, this pattern will feel familiar – it's the same agent-delegates-to-subagents model, applied to software development. As [XDA-Developers' review calling Antigravity the perfect example of vibe coding](https://www.xda-developers.com/forget-cursor-claude-code-google-antigravity-perfect-example-vibe-coding/) describes it, this outcome-first approach is what sets the workflow apart from earlier AI coding assistants. ### What Are Google Antigravity Usage Limits? On the free tier, limits have been tightened significantly since launch. As of mid-2026, expect roughly 20 high-quality requests/day on Gemini Pro models. Gemini Flash has higher limits. The 5-hour refresh cycle for rate limits has been reported as inconsistent. On AI Pro ($20/month), you get substantially higher quotas with a credit-based system. The catch: Google does not publish per-model credit costs, so you may exhaust credits faster than expected on complex agentic tasks that spawn many sub-calls. On AI Ultra Max ($200/month), quotas are approximately 20x Pro and are designed for power users running continuous multi-agent workflows. For teams comparing this against other [automation technologies and platforms](https://www.flobotics.io/blog/automation-technologies), the cost model rewards occasional use but becomes unpredictable at scale. ## How Does Google Antigravity Compare to Claude Code? This is the most common question from developers choosing between the two in 2026, and the answer depends on your workflow. Google Antigravity 2.0 is GUI-first and agent-team-centric. It gives you a visual orchestration layer, a built-in browser for live testing, and Artifacts that make agent work reviewable and auditable. It's designed to feel like an AI engineering department: you assign missions, agents collaborate, and you review results at a high level. It's free for individuals, which significantly lowers the barrier to entry. Claude Code is terminal-first and operates alongside whatever editor you already use. Rather than a built-in orchestration UI, it uses the Model Context Protocol (MCP) to connect to sub-agents and external tools. It behaves conservatively – it takes careful, reversible steps and checks in before making significant changes. Claude Code has a more documented enterprise feature set: SSO, SCIM provisioning, HIPAA readiness, and deployment via Amazon Bedrock, Google Vertex AI, or Microsoft Foundry. Its $20/month floor is the minimum for any usage. A useful frame: Antigravity feels like an AI engineering department; Claude Code feels like a senior AI developer paired with you. Most production teams using both tools treat Antigravity as the rapid-prototyping environment and Claude Code as the production-safe engineering tool. If you're evaluating both as part of a broader [intelligent automation](https://www.flobotics.io/business-process-automation) stack, the two tools are genuinely complementary rather than directly competing. For the full breakdown of what Claude Code supports out of the box, see [Anthropic's Claude Code documentation](https://docs.claude.com/en/docs/claude-code/overview). Both tools sit inside the same broader shift Gartner describes in its [analysis of the enterprise AI coding agent market entering a new phase of expansion](https://www.gartner.com/en/newsroom/press-releases/2026-05-20-gartner-says-the-market-for-enterprise-ai-coding-agents-is-entering-a-new-phase-of-expansion-and-competitive-realignment). ## Summary: Google Antigravity Looks Promissing Google Antigravity is one of the most significant shifts in how developers write software in 2026. Its agent-first architecture, Browser Subagent for live testing, and Artifact-based review system make it genuinely powerful for anyone who wants to move from "writing code" to "directing outcomes." The free tier makes it accessible to virtually anyone with a Gmail account. Treat the free tier limits as subject to change, don't depend on Antigravity's credit system for production cost planning until Google publishes per-model credit costs, and if you're building anything that needs careful, audited engineering, pair it with a conservative terminal-based tool like Claude Code. For teams exploring how agentic AI development fits into broader business automation – from prototyping to deployment to workflow integration – this is a tool worth having in your stack. The intersection of AI coding agents and [intelligent process automation](https://www.flobotics.io/business-process-automation) is exactly where organizations are finding the most leverage in 2026. Flobotics's own [AI agent for denials management case study](https://www.flobotics.io/case-studies/50k-saved-in-1-month-ai-agent-for-denials-management) shows that same leverage translating into a five-figure saving within the first month of deployment. ### Is Google Antigravity Legit? I think yes. Google Antigravity is a real, Google-developed product with an official site at [antigravity.google](https://antigravity.google/), a Google Codelabs tutorial, active developer forums at discuss.ai.google.dev, and coverage from TechCrunch, InfoWorld, and The New Stack. It was announced on the official Google Developers Blog and featured as a headline product at Google I/O 2026. That said, "legit" and "trustworthy" aren't quite the same thing. ### So Should We Trust Google Antigravity Today? The platform itself is legitimate and secure – it uses standard Google account authentication and runs agents locally on your machine or in Google's managed infrastructure. However, trust around its pricing and usage limits has been a real issue. Since launch, Google has adjusted the free tier's rate limits more than once, while [Google's own update on Antigravity rate limits for Pro and Ultra subscribers](https://blog.google/feed/new-antigravity-rate-limits-pro-ultra-subsribers/) confirms paid tiers have since received priority access and more generous quotas. Some users have also reported inconsistent refresh cycles on certain models. Google's documentation still does not publish per-model credit costs, making actual spend unpredictable. For individual experimentation, Antigravity is fine. For production workflows where you need predictable quotas and reliable SLAs, this history of opaque changes is a genuine concern – and it's one reason many serious teams still run Claude Code alongside it. Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ AIRCMHealthcare ### Claude for Healthcare from Anthropic Claude for Healthcare from Anthropic: what's still unclear on data storage, routing, and third-party access before you roll it out to staff. Dominik PutMay 26, 2026 ](https://www.flobotics.io/blog/anthropic-annoucement-claude-for-healthcare)[ RPAAI ### Agentic AI Frameworks | 2026 Agentic AI frameworks in 2026: which stacks Google and other leaders are betting on, explained with clear, research-backed answers. Jędrzej SzymulaDecember 02, 2025 ](https://www.flobotics.io/blog/agentic-ai-frameworks)[ AIHealthcareRPA ### Compliance Automation in Healthcare Healthcare compliance automation: how Continuous Control Monitoring and Agentic AI cut administrative drag by 20-30% in 2026. February 04, 2026 ](https://www.flobotics.io/blog/compliance-automation-healthcare) [All articles →](https://www.flobotics.io/blog) --- # ChatGPT 5.2 for Healthcare Canonical: https://www.flobotics.io/blog/chat-gpt-healthcare-5-2 Author: Bart Teodorczuk Published: 2026-06-18 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/ChatGPT 5.2 for Healthcare [AI](https://www.flobotics.io/blog?category=ai)[Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # ChatGPT 5.2 for Healthcare [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published June 18, 2026Updated September 1, 2026 On this page - [ChatGPT in Healthcare RCM: What It Can and Cannot Do](#chatgptinhealthcarercmwhatitcanandcannotdo) - [Where ChatGPT Legitimately Works](#wherechatgptlegitimatelyworks) - [The Three Structural Deficits](#thethreestructuraldeficits) - [Data Integration Gap](#dataintegrationgap) - [Regulatory Precision Gap](#regulatoryprecisiongap) - [Compliance Architecture Gap](#compliancearchitecturegap) - [Purpose-Built RCM AI: What the Architecture Actually Does](#purposebuiltrcmaiwhatthearchitectureactuallydoes) - [Decision Framework for RCM Operators](#decisionframeworkforrcmoperators) - [The Metric That Matters](#themetricthatmatters) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## ChatGPT in Healthcare RCM: What It Can and Cannot Do The U.S. healthcare revenue cycle operates on thin margins and thinner patience. With 70% of hospitals running below 2% operating margins and cost-to-collect hovering between 2.5% and 4% of net patient revenue, finance teams have no tolerance for technology that looks effective but fails to move metrics. Enter ChatGPT–already deployed in denial appeals, patient communications, and coding workflows, often without formal IT oversight. The question isn't whether general-purpose AI belongs in revenue cycle management. It's whether a tool built for conversation can execute workflows designed for cash. ## Where ChatGPT Legitimately Works ChatGPT has documented production value in healthcare RCM, but exclusively in tasks where fluency matters more than precision and human review serves as the control gate. Patient financial communications. Drafting hardship letters, payment plan explanations, and EOB narratives–tasks where empathetic tone improves patient experience but carries no regulatory liability. Staff review ensures accuracy; ChatGPT accelerates the draft. Payer policy summarization. When UnitedHealthcare releases a 47-page coverage update, ChatGPT condenses it into digestible bullet points for training materials. The output gets verified against the source document, but the time savings are real. Appeal letter templates. Writing the narrative structure of a denial appeal–"patient presented with X, medical necessity supported by Y"–is a legitimate use case. The clinical facts and payer-specific policy references still require human insertion and compliance review, but the scaffolding comes faster. Training content generation. Scenario-based quizzes for new billing staff, onboarding checklists, internal knowledge base articles. Low-stakes, high-volume content where iteration speed matters and errors don't trigger claim denials. Internal process documentation. Workflow guides, handoff protocols, department communications. ChatGPT excels at structuring information staff already possess but lack time to formalize. The pattern is consistent: every successful deployment involves non-binding output, human verification, and zero placement on the critical path between service delivery and payment posting. The moment ChatGPT moves from drafting tool to decision engine, the architecture breaks. ## The Three Structural Deficits ChatGPT fails in revenue-critical RCM workflows not because the technology is immature, but because it's architecturally mismatched to the job requirements. Three gaps separate language fluency from revenue performance. ### Data Integration Gap ChatGPT has no native connection to the systems that govern claim adjudication. It cannot query real-time eligibility verification feeds, access EHR clinical documentation, pull payer contract fee schedules, or track claim status through clearinghouse loops. Every output requiring these inputs demands manual data assembly by staff–eliminating the automation value that justified deployment. Consider prior authorization workflows. Determining whether a lumbar MRI requires pre-approval from Aetna's Florida plan for a specific CPT code involves checking: patient eligibility status, payer-specific coverage policies, procedure code crosswalks, and authorization portal requirements. ChatGPT can draft the narrative justification. It cannot execute the verification steps, submit the request, or track approval status. Staff performs the same manual lookups they did before AI entered the building. The operational consequence: Days in AR and Clean Claim Rate–the two metrics CFOs track for cash flow impact–remain unmoved. A tool that accelerates letter-writing but doesn't reduce claim holds delivers productivity theater, not financial performance. ### Regulatory Precision Gap Healthcare billing operates under payer-specific adjudication rules that change quarterly and differ between commercial plans, Medicare Advantage, and traditional Medicare. ChatGPT's training data has a cutoff date. Its knowledge of ICD-10 updates, CPT code revisions, and Local Coverage Determinations is structurally outdated the moment CMS publishes new guidance. More critically, it generalizes across payers. The medical necessity criteria for a sleep study reimbursed by Humana differ from Cigna's requirements, which differ from Medicare's Local Coverage Determination in jurisdiction E. ChatGPT cannot differentiate these rules because it wasn't trained on payer contract tables and doesn't receive real-time policy feeds. The financial exposure is asymmetric. A miscoded high-value surgical procedure–spinal fusion, cardiac catheterization, joint replacement–represents $15,000 to $50,000 in delayed or lost revenue per claim. In a health system processing thousands of claims daily, even a 1% error rate from staff accepting fluent but inaccurate coding suggestions creates measurable cash flow impact. The cost to rework a single denied claim ranges from $25 to $118 according to HFMA benchmarks, but the larger damage comes from missed timely filing deadlines and compliance flags during payer audits. Industry data supports the risk profile. RevCycle Intelligence reports that 40% to 50% of initial general LLM deployments in RCM environments fail to deliver measurable ROI on core cycle metrics, with several health systems documenting increased claim rework volume within 60 to 90 days of deployment–the direct result of staff trusting fluent output without verification protocols. ### Compliance Architecture Gap HIPAA compliance and operational liability are separate concerns. ChatGPT Enterprise with a Business Associate Agreement covers data transmission and storage under HIPAA Title II. It does not address liability for erroneous clinical or billing decisions, nor does it provide the audit trail infrastructure payers require during claims reviews. When a payer audits denial appeals, they expect a documented decision pathway: which clinical guidelines supported medical necessity, which policy references justified the code selection, who reviewed the determination, and when. ChatGPT conversation history does not meet this standard. OpenAI's terms of service explicitly place responsibility for output accuracy on the user organization. The governance question becomes: who is liable when a ChatGPT-generated appeal contains a coverage policy misstatement that delays a $40,000 payment? Legally, the organization. Operationally, the RCM director who deployed a general-purpose tool in a revenue-critical workflow without compliance guardrails. Prompt engineering by billing staff–often cited as a solution–cannot bridge these gaps. A well-crafted prompt improves language quality for static tasks. It cannot connect ChatGPT to an EHR, embed payer contract logic, or create a systematic update mechanism when CMS revises billing guidelines. Prompt engineering is a staff productivity technique. It is not infrastructure. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Purpose-Built RCM AI: What the Architecture Actually Does Specialized revenue cycle AI platforms operate on a fundamentally different technical model than general-purpose large language models. Understanding the distinction matters for CTOs evaluating deployment risk versus cost. Purpose-built RCM systems use hybrid architecture: an NLP layer for document understanding and narrative generation, plus a deterministic rules engine for payer-specific adjudication logic, plus integration middleware connecting to EHRs, practice management systems, clearinghouses, and payer portals, plus workflow orchestration managing automated hand-offs and status tracking, plus a compliance layer generating auditable decision logs. The NLP component may use fine-tuned language models trained on RCM-specific datasets–clinical documentation, payer policy language, denial reason codes, appeal outcomes. But language processing is one subsystem, not the entire platform. The rules engine handles tasks where precision outweighs fluency: verifying that a particular procedure code is covered under a specific payer contract, checking eligibility status before claim submission, routing denials based on reason codes to appropriate staff queues, auto-generating appeals with embedded policy references pulled from live payer databases. The measurable outcomes justify the architectural complexity. Healthcare organizations deploying specialized RCM AI report Clean Claim Rates above 95%–compared to industry averages of 75% to 85%–because the system verifies coding accuracy and eligibility before submission, not after denial. First Pass Resolution Rates improve because the platform automates the entire denial workflow loop, not just the letter-drafting step. Days in AR reductions of 8 to 15 days appear in documented case studies because payments post faster when claims are submitted correctly the first time and denials are worked systematically rather than manually triaged. The honest trade-off: purpose-built platforms cost more than ChatGPT Enterprise licenses, require longer implementation timelines, demand integration work with legacy systems, and need calibration to institutional workflows. But they produce metrics that CFOs can track on cash flow dashboards–First Pass Resolution Rate, Clean Claim Rate, Days in AR, cost-to-collect–rather than staff satisfaction scores about drafting efficiency. ChatGPT improves how quickly you write about revenue. Specialized RCM AI improves how quickly you collect it. These are not competing solutions on a maturity curve. They are different categories of tools. ## Decision Framework for RCM Operators The deployment decision comes down to task classification and risk tolerance. Use ChatGPT where output is non-binding, human-reviewed, and detached from payment timelines. Require purpose-built systems where errors directly impact cash flow, regulatory standing, or payer relationships. Appeal letter drafting (with clinical review): ChatGPT adequate. The narrative structure benefits from fluency; clinical facts and policy citations require human insertion and verification. No automated decision-making occurs. Patient communication templates: ChatGPT adequate. Financial counseling scripts, payment plan explanations, and EOB clarifications are low-stakes communication tasks where empathetic language improves outcomes but mistakes don't trigger denials. Staff training materials: ChatGPT adequate. Onboarding guides, procedure checklists, and scenario quizzes accelerate knowledge transfer. Errors are caught during training, not during claim adjudication. Real-time eligibility verification: ChatGPT inadequate; specialized system required. Payment posting depends on accurate eligibility checks before service delivery. No manual verification step exists in high-volume environments. The system must integrate with payer portals and update automatically. Automated coding suggestions: ChatGPT inadequate due to compliance risk; specialized system required. Even with human review protocols, fluent but outdated coding guidance introduces measurable financial exposure. Purpose-built platforms trained on current guidelines and payer-specific rules reduce error rates to actuarially acceptable levels. Denial workflow automation: ChatGPT inadequate; specialized system required. Managing denial reason codes, routing to appropriate staff, tracking appeal deadlines, and auto-generating responses with embedded policy references requires closed-loop workflow orchestration, not conversation. Prior authorization submission: ChatGPT inadequate; specialized system required. Multi-step verification (eligibility, medical necessity, payer-specific requirements), portal integration, and status tracking define the workflow. ChatGPT handles none of these steps. Compliance audit trail: ChatGPT inadequate; specialized system required. Payer audits demand documented decision pathways with timestamps, user roles, and policy version references. ChatGPT conversation logs do not meet evidentiary standards. The cost-benefit calculation for CFOs: compare the licensing cost of a specialized platform against the financial risk of deploying a general-purpose LLM in revenue-critical workflows. One miscoded high-acuity claim offsets months of ChatGPT Enterprise subscription savings. One missed timely filing deadline on a complex surgical case justifies a year of purpose-built platform fees. Organizations currently using ChatGPT for coding or denial tasks without formal review protocols face a governance problem, not a technology problem. The tool is being deployed outside its operational envelope. If staff members accept AI-generated output in revenue-critical workflows without verification, the issue is process design and compliance oversight–but the triggering factor is a category-mismatched tool that produces fluent, confident output without the underlying data integration and regulatory precision the task requires. The liability question resolves simply: the organization is responsible for every claim submission, appeal, and coding decision, regardless of which tool assisted in preparation. OpenAI accepts no liability for billing errors. The CFO owns the financial outcome. ## The Metric That Matters At 2% operating margins, the gap between a tool that sounds effective and a tool that generates measurable cash flow is an operational imperative, not a vendor preference. ChatGPT has legitimate value in communication tasks where language quality improves outcomes and human review serves as the control gate. It structurally fails in workflows requiring real-time data integration, payer-specific adjudication logic, and compliance-grade audit trails–precisely the workflows that determine whether revenue posts in 30 days or 90. The decision framework is binary: if the task sits on the critical path between service delivery and payment posting, use purpose-built infrastructure. If it supports that path without executing it, general-purpose AI is defensible. The $262 billion in annual RCM inefficiency costs documented by McKinsey stems from process failures in eligibility verification, coding accuracy, denial management, and prior authorization workflows–the exact domains where ChatGPT's architectural gaps are most exposed. Healthcare finance leaders evaluating AI deployment should ask one question: does this tool move Days in AR? If the answer requires assumptions about staff behavior, prompt quality, or manual verification discipline, the tool is a productivity aid, not a revenue cycle solution. Both have value. Only one affects cash. Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareAI ### Claude for Healthcare Overview | 2026 Claude for Healthcare: Anthropic's 2026 toolkit for US medical data, with HIPAA compliance details and case studies from Banner Health and Novartis. Jędrzej SzymulaMay 06, 2026 ](https://www.flobotics.io/blog/claude-for-healthcare)[ AIHealthcareRCM ### AWS Connect Health: RCM Salvation or Infrastructure Play? AWS Connect Health: is Amazon's new healthcare platform an RCM solution or just an infrastructure play? We break down what it actually delivers. Bart TeodorczukMay 18, 2026 ](https://www.flobotics.io/blog/aws-connect-health)[ HealthcareRCMAI ### CFO's Take On: AWS Connect Health AWS Connect Health, a CFO's take: what you're actually buying before committing capital, and the Business Associate Agreement gaps to check first. Krzysztof SzwedMay 31, 2026 ](https://www.flobotics.io/blog/aws-connect-health-cafc9) [All articles →](https://www.flobotics.io/blog) --- # XiFin Implementation: A CFO’s Perspective Canonical: https://www.flobotics.io/blog/xifin-implementation-for-cfo Author: Krzysztof Szwed Published: 2026-06-17 Updated: 2026-09-08 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/XiFin Implementation: A CFO’s Perspective [AI](https://www.flobotics.io/blog?category=ai)[Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # XiFin Implementation: A CFO’s Perspective [Krzysztof SzwedHead of Delivery at Flobotics](https://www.flobotics.io/our-editorial-team#szwed) Published June 17, 2026Updated September 8, 2026 On this page - [1. Net Revenue Recognition](#1netrevenuerecognitionasc606accrualengineaccuracy) - [2. Unbilled Revenue & Cash Flow Lag](#2unbilledrevenueworkinprogresscashflowlag) - [3. Contractual Allowance](#3contractualallowancefeescheduleintegrity) - [4. Cost to Collect & ROI Reality](#4costtocollectautomationroireality) - [How XiFin Changes Your Staffing Model](#howxifinchangesyourstaffingmodel) - [How much does "reduced FTE" actually mean?](#how-much-does-reduced-fte-actually-mean) - [5. First-Pass Resolution & Permanent Revenue Leakage Prevention](#5firstpassresolutionpermanentrevenueleakageprevention) - [6. Patient Responsibility & Bad Debt Reserve Calibration](#6patientresponsibilitybaddebtreservecalibration) - [7. Cash Reconciliation & Subledger Audit Integrity](#7cashreconciliationsubledgerauditintegrity) - [The CFO's Accountability Framework](#thecfosaccountabilityframework) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) XiFin operates as a true double-entry subledger with accrual logic built to FASB ASC 606 standards. It predicts net realizable revenue at accession, enforces front-end claim edits that temporarily constrict cash flow, and demands accounting discipline that many laboratory finance teams have never maintained at this rigour. [Click here to read more about XiFin in RCM](https://www.flobotics.io/xifin-in-rcm). Implementing a revenue cycle management system like XiFin is a financial re-architecture with IT components. The distinction matters because most laboratories treat go-live as the success milestone. CFOs should not. Most implementations succeed operationally and fail financially because the CFO enters the verification loop too late. The seven questions below map the precise points where implementation outcomes imprint themselves on the P&L, balance sheet, and cash flow statement. Each includes the threshold that separates temporary adjustment from structural failure, and the monthly report that gives early warning. ## 1. Net Revenue Recognition How accurately is XiFin's accrual engine calculating net realizable revenue at accession compared to legacy cash-based or estimation methods? XiFin complies strictly with FASB ASC 606, which requires revenue recognition to reflect the transaction price the organization expects to receive–not the amount billed. Over-accruing revenue at service date inflates the P&L immediately and forces messy post-close journal entries when actuals settle lower. Under-accruing suppresses revenue reporting and creates phantom windfalls in later periods when cash arrives above the booked expectation. The more consequential risk is methodological inconsistency during the transition. If an organization switches accrual methodology mid-fiscal-year without formal documentation, external auditors will require reconciliation between the old and new bases. According to HFMA guidance on ASC 606 implementation, organizations that fail to align payer-specific expected reimbursement rates to actual contracted allowables face post-close manual journal entry volumes that eliminate any automation gain the system delivered. Audit risk threshold 3.0% Max sustained variance Current variance 1.4% Expected vs actual allowed Review window 180 Days post go-live Accrual basis 606 FASB ASC compliant Expected vs actual allowed variance — monthly Dashed red line marks the 3% audit trigger threshold Variance % Accrual accuracy 3% threshold ASC 606 accrual accuracy and variance over 12 months Month | Variance | Accrual accuracy | Threshold | M1 | 2.1% | 97.9% | 3% | M2 | 2.5% | 97.5% | 3% | M3 | 2.8% | 97.2% | 3% | M4 | 2.4% | 97.6% | 3% | M5 | 1.9% | 98.1% | 3% | M6 | 1.6% | 98.4% | 3% | M7 | 1.4% | 98.6% | 3% | M8 | 1.7% | 98.3% | 3% | M9 | 1.3% | 98.7% | 3% | M10 | 1.1% | 98.9% | 3% | M11 | 1.4% | 98.6% | 3% | M12 | 1.2% | 98.8% | 3% | Within range Variance <3% — fee schedule mapping and accrual assumptions are sound Elevated risk Variance 3–5% — incorrect fee schedule or methodology misalignment Audit exposure Variance >5% sustained — triggers post-close journal entries, SOX risk ## 2. Unbilled Revenue & Cash Flow Lag What is the precise impact on time-to-bill and how much accounts receivable is trapped in the "work in progress" queue due to front-end system edits? XiFin uses strict front-end logic to prevent defective claims from leaving the building. This is financially sound in the long term–bad claims generate denials, which delay revenue and often result in permanent write-offs. But in the short term, this discipline causes a predictable spike in unbilled revenue because claims that previously would have been billed (and subsequently denied) are now held for correction. This temporarily inverts cash flow. According to Becker's Hospital Review analysis of RCM implementations, unbilled AR accumulation in the first 90 days is the leading indicator of implementation distress–not back-end denials, not posting errors, but undisciplined intake workflows that the new system now refuses to tolerate. According to American Hospital Association benchmarks, AR days for diagnostic organizations typically range from 35 to 45 days. AR days exceeding 55 in Q1 post-go-live should trigger cash crisis protocols. Unbilled revenue exceeding 10–15% of monthly net revenues for more than 90 days post-go-live represents frozen working capital and operational failure. Accession-to-Bill Lag Report and Unbilled Revenue/WIP Summary. Review weekly during Q1 post-go-live, then monthly thereafter. ## 3. Contractual Allowance How accurately are payer-specific fee schedules and contractual allowances functioning within the rules engine to project true cash yield? Misaligned fee schedules systematically overstate gross accounts receivable on the balance sheet. The organization appears to have more collectible AR than actually exists. This distortion provides false comfort to lenders, boards, and auditors. Worse, the problem does not surface until audit season, at which point write-downs are large and difficult to explain. According to RevCycle Intelligence analysis, contractual allowance misconfiguration is the most common cause of net AR distortion in the first quarter post-go-live. Organizations with operationally acceptable AR days may simultaneously have materially impaired underlying net AR valuations because the system is booking revenue at amounts no payer will ever pay. Auditing fee schedule integrity before go-live is the CFO's responsibility, not IT's. Fee schedules are financial instruments. They encode negotiated contract terms into system logic. If those encodings are wrong, every accession booked under them is wrong. The CFO must sign off on payer contract mapping accuracy before the first claim accrues revenue under the new methodology. A sustained gap between expected yield and actual yield by payer class indicates a contract data integrity problem requiring immediate fee schedule audit. Payer Yield & Contractual Allowance Waterfall Report cross-referenced against the Month-End Ledger Balance Sheet. Any payer showing consistent variance >5% demands investigation. ## 4. Cost to Collect & ROI Reality With XiFin's AI-enabled automation for eligibility, insurance discovery, and exception routing deployed, how has the true cost to collect decreased post-implementation? The primary ROI of a premium RCM system is reducing manual FTE touches per claim. According to HFMA benchmarks, the average cost to collect in diagnostic billing ranges from $8 to $12 per claim. High-performing organizations using advanced automation target costs below $6 per claim, representing 30–40% reduction in labor intensity for eligibility verification and claim scrubbing. But here is the ROI trap that McKinsey Health documents repeatedly: laboratories automate workflows but do not restructure the labor model. Staff continue performing manual tasks the system now handles, or they are redeployed to other functions rather than removed from the cost base. Gross automation savings–the elimination of touches–does not equal net OpEx savings unless headcount actually declines or redeployed FTEs generate measurable new revenue. Full ROI typically materialises in 12 to 18 months, not Q1. If cost to collect has not moved within six months post-go-live, operational adoption is failing regardless of what IT reports indicate. Demand joint review of FTE efficiency and touch-rate metrics from XiFin BI mapped directly against departmental OpEx ledgers. Do not allow these to be reviewed in separate silos. Automation gains that do not appear in the OpEx ledger are theoretical. Cost to collect remaining above $8 per claim six months post-go-live indicates incomplete workflow adoption or labor model misalignment. FTE Efficiency & Touch-Rate Metrics (XiFin BI) cross-walked to Departmental OpEx Ledger. ## How XiFin Changes Your Staffing Model The operational impact of XiFin depends entirely on which service model you select. The table below outlines compliance ownership and staffing implications: #### Revenue Cycle Management (RCM) Service Models Service Model | Vendor Responsibility | In-House Responsibility | Accountability & Control | SaaS In-House | Software provider | Full in-house team (reduced FTE) | Client | Partially Outsourced | Claims + denials + appeals | Patient services + exceptions | Shared | Fully Managed Services | Complete billing operations | Minimal/zero | Vendor (audit trail critical) | #### Quick Breakdown of the Models: - SaaS In-House: You buy the software (Software as a Service) from a vendor, but your own staff does all the actual billing work. The software usually makes them more efficient, allowing you to operate with fewer Full-Time Employees (FTEs), but ultimate responsibility rests entirely on your practice. - Partially Outsourced (Co-Sourced): The vendor handles the heavy lifting of back-office tasks (submitting claims, working denials, and fighting appeals), while your in-house team manages front-facing tasks like patient inquiries, collecting copays, and handling complex exceptions. - Fully Managed Services: The vendor takes over the entire billing operation from end to end. Your in-house staffing requirements drop to near zero for billing purposes. Because the vendor has total control over your revenue cycle, having a strict audit trail and transparent reporting is critical. ### How much does "reduced FTE" actually mean? HFMA staffing benchmarks suggest that organizations implementing enterprise RCM platforms reduce billing full-time equivalents by 30-40% compared to legacy systems. However, XiFin does not publish client-specific staffing data. Ask your vendor for reference clients of comparable size and claim volume. Request before-and-after FTE counts, not vague efficiency claims. If XiFin cannot or will not provide this data, that is itself a data point. In the fully managed services model, compliance responsibility remains with the healthcare provider, but operational execution sits with XiFin. This creates a principal-agent problem: you bear regulatory risk, but you do not directly control the processes that create that risk. Your contract must include explicit SLAs for audit trail access, CMS reportability timelines, and third-party audit rights. This is non-negotiable. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## 5. First-Pass Resolution & Permanent Revenue Leakage Prevention What percentage of historical back-end denials have been successfully shifted to front-end automated exceptions, and what is the new clean claim rate? Every back-end denial represents delayed revenue, real write-off risk, and appeals labor cost. The fully loaded FTE overhead of working denials is consistently underestimated. RevCycle Intelligence benchmarks show high-performing diagnostic providers achieve first-pass payment rates above 95% and clean claim rates above 98%. XiFin's strategic value lies in relocating denial management from the back-end–where revenue is already at risk–to the front-end, where defects can be corrected at near-zero marginal cost. Administrative denials caused by wrong demographics, missing authorizations, or coordination-of-benefits errors are recoverable losses that proper XiFin configuration should eliminate systematically. A clean claim rate below 88% in the first 60 days post-go-live warrants operational intervention. If back-end administrative denial rates are not declining month-over-month, front-end configuration is incomplete. According to RevCycle Intelligence, every percentage point below 95% clean claim rate represents 2–5% potential permanent revenue loss from avoidable denials that exhaust appeal timely filing limits. Clean claim rate below 88% beyond day 60, or back-end administrative denials not declining month-over-month, indicates fundamental front-end data capture failure. First-Pass Payment Rate Report compared against Denials by Payer and Reason Code Report. Track month-over-month movement, not absolute levels, in the first 90 days. ## 6. Patient Responsibility & Bad Debt Reserve Calibration How is XiFin's automated patient engagement affecting collection rates on patient-owed balances, and are bad debt reserve calculations adjusting accordingly? Optum Research documents that patient responsibility as a percentage of total net revenue in diagnostic billing has grown from 28% in 2023 toward an expected 35% or higher by 2026. Patients enrolled in high-deductible health plans now represent 30–40% of gross AR in many ambulatory lab environments. Faster, automated patient collections via text, email, and IVR portals improve cash flow and–critically–permit the CFO to reduce bad debt reserve rates with actuarial justification. Reduced reserves flow directly to net income. Most CFOs leave this benefit on the table because they do not update provisioning methodology quickly enough to reflect improved collection performance. Conversely, if patient collection rates remain flat despite automation, the bad debt reserve is likely understated. The next audit cycle will surface the problem painfully, requiring retroactive provisioning that suppresses earnings in the correction period. Patient collection rates not improving within 90 days of automated engagement deployment indicates either poor patient contact data quality or ineffective communication templates. Patient Responsibility Aging Report and Bad Debt Reserve Calculation Summary with explicit reserve-rate sensitivity analysis segmented by payer class. Update provisioning assumptions quarterly based on trailing 12-month collection performance. ## 7. Cash Reconciliation & Subledger Audit Integrity Are daily bank deposits matching cleanly to XiFin ledger postings, and what is the volume of unapplied cash at month-end? XiFin functions as a financial subledger, not a billing tool feeding a separate general ledger. This architecture demands accounting discipline many laboratory finance teams have never maintained. High unapplied cash balances indicate Electronic Remittance Advice auto-posting breakdowns. Cash is in the bank, but AR remains artificially inflated on the books. This distorts days sales outstanding metrics and creates audit risk that accumulates silently. According to HFMA and AHA guidance, unapplied cash exceeding 2–3% of monthly cash receipts for more than 60 days represents potential material AR misstatement. If that threshold is breached, the organization faces restatement risk. The highest audit risk period is the dual-system window when legacy and XiFin run in parallel. This generates AR duplication risk, inconsistent closing entries, and potential double-counting of revenue. FASB ASC 606 requires consistent accrual methodology within a reporting period. Switching systems mid-fiscal-year requires formal documentation of methodology change for external auditors. Who validates subledger reconciliation during the dual-system window–external auditors or internal controls? This is not an operational question. It is a SOX compliance question. Unapplied cash exceeding 2–3% of monthly receipts for more than 60 days, or ERA auto-posting failure rates not declining week-over-week in the first 90 days, requires CFO escalation. Bank Deposit to Posting Reconciliation Report and Unapplied Cash & Suspense Ledger. Review at every month-end close without exception. Escalate to CFO if unapplied cash exceeds 2% of monthly collections. ## The CFO's Accountability Framework XiFin implementation success is not defined by go-live, ticket closure, or operational stability reports. It is defined by six financial outcomes measurable monthly, reportable to the CFO directly, and benchmarked against HFMA, AHA, and RevCycle Intelligence standards: If these six metrics are not improving on the timelines described above, the implementation has not succeeded–regardless of what any other stakeholder reports. The accountability belongs to the CFO. The reporting infrastructure exists in XiFin Business Intelligence today, for every organization willing to use it with the rigour the system was built to support. Most implementations succeed operationally and fail financially because the CFO treats the system as a billing tool rather than a financial subledger. By the time the balance sheet reflects that error, the correction is expensive. The seven questions above define the verification points where early intervention prevents late-stage restatement. Use them before the auditors do. At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. ## FAQ: Is XiFin legitimate? Yes. XiFin is an actively operating company founded in 1997, headquartered in San Diego, with roughly 501–1,000 employees. It has been named to the Inc. 5000 list of fastest-growing private companies multiple times, most recently in 2023. How many employees does XiFin have? Inc.com lists XiFin's headcount at 501 to 1,000 employees. Third-party estimators such as LinkedIn or ZoomInfo may show a different figure, since exact counts fluctuate and aren't independently audited. Who owns XiFin? XiFin is privately held and led by founder and CEO Lâle White. Its most recent growth-equity round, announced in September 2025, was led by Goldman Sachs, following earlier investment from Avista Healthcare Partners. Is XiFin a public company? No. XiFin is privately held and not traded on any public stock exchange. Its growth has instead been funded through private and growth-equity investment, most recently a round led by Goldman Sachs in 2025. Written byKrzysztof Szwed Head of Delivery at Flobotics. [More from Krzysztof](https://www.flobotics.io/our-editorial-team#szwed) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareAIRCM ### XiFin - 101 Guide What is XiFin? A 101 guide - plus why a private equity firm holding it for 12 years, nearly double the industry norm, matters for buyers. Jędrzej SzymulaJune 15, 2026 ](https://www.flobotics.io/blog/xifin-101-guide)[ AIRCMHealthcare ### Claude for Healthcare from Anthropic Claude for Healthcare from Anthropic: what's still unclear on data storage, routing, and third-party access before you roll it out to staff. Dominik PutMay 26, 2026 ](https://www.flobotics.io/blog/anthropic-annoucement-claude-for-healthcare)[ HealthcareRCMAI ### CFO's Take On: AWS Connect Health AWS Connect Health, a CFO's take: what you're actually buying before committing capital, and the Business Associate Agreement gaps to check first. Krzysztof SzwedMay 31, 2026 ](https://www.flobotics.io/blog/aws-connect-health-cafc9) [All articles →](https://www.flobotics.io/blog) --- # XiFin - 101 Guide Canonical: https://www.flobotics.io/blog/xifin-101-guide Author: Jędrzej Szymula Published: 2026-06-15 Updated: 2026-09-08 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/XiFin - 101 Guide [AI](https://www.flobotics.io/blog?category=ai)[Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # XiFin - 101 Guide [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published June 15, 2026Updated September 8, 2026 On this page - [What is XiFin ?](#xifinrcmaduediligenceframeworkfordiagnosticbillingleaders) - [Who Owns XiFin?](#marketfitwhoshouldactuallyconsiderxifin) - [Main Service Structures of XiFin](#economicsbuildingarealistictcomodel) - [What Differentiates the XiFin's Offer?](#what-differentiates-the-xifin-s-offer) - [What Constitutes XiFin's Operational Model?](#what-constitutes-xifin-s-operational-model) - [How Much Does XiFin Actually Costs?](#whousesxifinandwhoshouldnot) - [The Hidden Costs of XiFin](#thehiddencostsnovendorhighlights) - [The Benchmark You Need](#thebenchmarkyouneed) - [Who Should Actually Consider XiFin?](#whousesxifinandwhoshouldnot-2) - [What Do People Say About XiFin Online?](#whatemployeessayandwhyitmatterstoyou) - [What's XiFin's Future?](#theaipitchandtheverificationgap) - [XiFin 101 Guide | Summary](#theprecontractrealitycheck) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Healthcare diagnostics billing is among the most complex operational challenges in the American medical system today. When a single [laboratory](https://www.flobotics.io/who-we-help/laboratories) processes tens of thousands of claims monthly - automation becomes existential. Eligibility checks, payor adjudication, and appeals... ‍ XiFin positions itself as the specialist solution for this specific yet robust pain point. ## What is [XiFin](https://www.xifin.com/)? XiFin, Inc. is a healthcare information technology company that specializes in cloud-based revenue cycle management (RCM) and workflow automation software. Their main product XiFin - a cloud-based [Revenue Cycle Management (RCM)](https://www.flobotics.io/blog/what-is-revenue-cycle-management) software purpose-built for healthcare diagnostics. Beside a set of solutions, they also provide a proprietary [Laboratory Information System (LIS)](https://www.flobotics.io/blog/laboratory-information-management-system-lims). Such a dual-product architecture is both a differentiator and a potential lock-in mechanism. Afterall, clients who adopt both the RCM and LIS platforms face higher switching costs than those using XiFin only for billing. XiFin is built for laboratory RCM interoperability. The platform integrates via API with EHR/EMR systems, laboratory and radiology information systems (LIS/RIS), and payor portals for real-time eligibility checks and electronic claim submission. XiFin's primary market is high-volume clinical and pathology laboratories in the United States. Secondary customers include hospital outreach programs, radiology and imaging centers, retail and specialty pharmacies, and medical device billing operations. Prometheus Laboratories is among the notable reference clients XiFin cites in its materials. Geography matters: XiFin is a US-only platform. If your organization has international operations or plans to expand beyond American payor structures, this is not your solution. ### Who Owns XiFin? XiFin, Inc. was founded in 1997 by [Lâle White](https://www.linkedin.com/in/lale-white-86307a11/) - she remains the CEO of this company for nearly three decades now. In 2014, GTCR, a Chicago-based private equity firm, acquired the company. As of mid-2026, that makes it a 12-year hold–roughly double the typical 5-7 year exit window for PE-backed software companies. For a CFO evaluating vendor stability, this raises a legitimate question: Why has GTCR held XiFin for 12 years? Is this a strategic long-term play in healthcare infrastructure, or does it signal complications in achieving a planned exit? Either answer has implications for future contract terms, product roadmap commitments, and the risk of ownership transition mid-contract. The company employs roughly 700 to 1,000 people, headquartered in San Diego. That range fluctuates significantly because XiFin operates under multiple service models–some clients use only the software with in-house staff, while others outsource their entire billing operation to XiFin's managed services team. Click here to [read more about XiFin values and board. ](https://www.xifin.com/about-us/) ## Main Service Structures of XiFin XiFin does not publish pricing–standard practice for enterprise RCM vendors serving diverse claim volumes and operational models. Costs depend on chosen delivery model, claim volume, module selection (particularly Business Intelligence and proprietary LIS), and implementation scope. However, they offer 3 distinct service structures, each with fundamentally different total cost of ownership profiles: - SaaS In-House: The client licenses software but maintains internal billing staff. This model delivers the lowest vendor fees but requires the highest internal headcount. Organizations select this path to preserve institutional billing knowledge and maintain direct compliance control. - Partial Outsource: XiFin handles high-volume claim processing and appeals while the client retains staff for patient relations, complex exception handling, and vendor oversight. This creates hybrid TCO with shared operational risk. - Fully Managed Services: XiFin functions as the organization's complete billing department, typically charging a percentage of collected revenue. This eliminates dedicated billing staff but transfers collection risk–and collection performance accountability–to the vendor. Without public pricing, CFOs approach vendor negotiations informationally disadvantaged. [Becker's Hospital Review benchmarks](https://www.beckershospitalreview.com/) provide essential calibration: According to HFMA and RevCycle Intelligence data, outsourced RCM fees in diagnostics typically range from 4% to 9% of collected revenue, with variance driven by payor mix complexity and baseline denial rates. Organizations with clean commercial payor dominance and denial rates below 10% command lower fees; those with high Medicaid exposure and 20%+ denial rates face premium pricing. For context, in-house cost-to-collect in diagnostics runs 3% to 5% of net revenue on a fully loaded basis (staff, infrastructure, training, and write-offs). Outsourced RCM must beat this threshold by meaningful margin to justify vendor fees and implementation disruption. Implementation costs rarely appear in initial vendor presentations but materially impact first-year ROI. Enterprise RCM deployments in mid-sized laboratories typically incur $150,000 to $400,000 in total project costs, encompassing data migration from legacy systems, staff retraining for new workflows, integration labor for custom interfaces, and revenue cycle disruption during cutover periods. [Becker's Hospital Review case studies document](https://www.beckershospitalreview.com/) 15 to 30 days of degraded AR performance during go-live transitions–a cash flow impact that finance teams should model before board presentation. ### What Differentiates the XiFin's Offer? ##### Their flagship platform, [XiFin Empower](https://www.xifin.com/lp/empower-excellence/), automates the billing lifecycle: - patient eligibility verification, - clean claim creation, - payor adjudication tracking, - denial management, - appeals processing, - and accounts receivable collection. XiFin Empower is a cloud-based RCM platform purpose-built for healthcare diagnostics billing complexity. Unlike horizontal billing platforms adapted for healthcare, XiFin's architecture reflects the specific chaos of laboratory reimbursement–multiple payors per specimen, fragmented CPT coding, and medical necessity documentation that varies by test type and insurance carrier. XiFin does not publish a comprehensive list of certified EHR integrations. On top of that we also have XiFin's LIS. The proprietary XiFin's LIS presents a double-edged operational reality. Consolidating billing and specimen management under one vendor reduces interface maintenance and creates unified workflow visibility. It also materially increases switching costs after three to five years of data accumulation. That's exactly why contract negotiations with XiFin should explicitly address data portability standards, export formats, and timeline guarantees for complete data migration upon contract termination. From our perspective this isn't just a post-signature concern. It's worth keeping in mind that its much more a deal term that determines whether you're entering a partnership or a dependency. ### What Constitutes XiFin's Operational Model? A laboratory processing 500 claims per month has fundamentally different economics than one processing 50,000. According to Healthcare Financial Management Association (HFMA) benchmarks, enterprise RCM platforms typically achieve ROI at volumes exceeding 10,000 claims monthly. Below that threshold, the cost-to-collect ratio may be higher than with legacy systems or smaller specialized vendors. If your organization falls below this volume range, you need explicit financial modeling from XiFin showing where your break-even point sits. Do not accept generalizations about scalability without claim-volume-specific TCO projections. "Significantly fewer staff" appears in virtually every RCM vendor pitch. The claim lacks utility without numbers. [HFMA staffing benchmarks](https://www.hfma.org/) for diagnostic billing operations provide operational grounding: These ranges assume comparable denial rates and payor complexity. Organizations with unusually clean payor relationships may see smaller percentage gains; those currently running inefficient manual processes may exceed these improvement ratios. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## How Much Does XiFin Actually Costs? XiFin does not publish pricing. This is standard practice for enterprise SaaS platforms, but it also means your finance team walks into vendor conversations without a calibration point. Costs vary based on claim volume, selected modules (standalone RCM vs. integrated LIS), and crucially, which service model you choose. XiFin offers three fundamentally different economic structures: SaaS-only (in-house billing team) | You license the software and operate it with your own staff. XiFin provides the platform; you provide the labor. | Partially outsourced | XiFin handles claims processing, denials, and appeals. You retain patient services and exception handling. Compliance responsibility is shared. | Fully managed services | XiFin becomes your billing department. You maintain minimal or zero dedicated billing staff. Compliance responsibility contractually shifts to the vendor–but audit trail ownership and CMS reportability requirements demand explicit SLA language. Before signing, your General Counsel must review regulatory liability clauses. | ### The Hidden Costs of XiFin Implementation costs are real and often underestimated. Expect expenses for data migration from legacy LIS/RIS systems, technical integration work (typically requiring 3-6 months for mid-sized laboratories), staff retraining, and operational downtime during transition. HFMA research indicates that organizations implementing enterprise RCM platforms experience an average revenue dip of 10-15% in the first quarter post-implementation as workflows stabilize and staff acclimate to new systems. Factor this into your cash flow projections. Total implementation cost for mid-market laboratories typically reaches low-to-mid six figures. So.. if your vendor call does not produce a detailed implementation budget with line-item cost breakdown and timeline-specific milestones, you are not ready yet to proceed. #### How much does "reduced FTE" actually mean? HFMA staffing benchmarks suggest that organizations implementing enterprise RCM platforms reduce billing full-time equivalents by 30-40% compared to legacy systems. However, XiFin does not publish client-specific staffing data. Ask your vendor for reference clients of comparable size and claim volume. Request before-and-after FTE counts, not vague efficiency claims. If XiFin cannot or will not provide this data, that is itself a data point. In the fully managed services model, compliance responsibility remains with the healthcare provider, but operational execution sits with XiFin. This creates a principal-agent problem: you bear regulatory risk, but you do not directly control the processes that create that risk. Your contract must include explicit SLAs for audit trail access, CMS reportability timelines, and third-party audit rights. From our stand-point this is non-negotiable AND fruitful for both sides. ### The Benchmark You Need According to HFMA and RevCycle Intelligence data for 2025-2026, outsourced RCM fees in the diagnostics sector typically range from 4% to 8% of collected revenue. This is the industry calibration point–not XiFin's confirmed pricing structure, but the range within which serious negotiations should occur. To be explicit: This is a sector benchmark, not publicly confirmed XiFin pricing. Use it to pressure-test vendor proposals. If XiFin's fee structure falls outside this range, demand detailed justification tied to measurable performance guarantees. ## Who Should Actually Consider XiFin? XiFin's primary market consists of high-volume U.S. clinical and pathology reference laboratories, including customers like Prometheus Laboratories. Secondary markets include hospital outreach programs, radiology and imaging centers, specialty pharmacies, and medical device companies with complex billing requirements. "High-volume" functions as vendor shorthand that obscures the actual decision threshold. Based on [HFMA benchmarks](https://www.hfma.org/) for cost-to-collect by volume tier and operational complexity, the realistic evaluation framework breaks down as follows: - Below 5,000 claims monthly: Enterprise RCM platforms like XiFin likely exceed cost-effectiveness thresholds. Basic clearinghouse services with manual exception handling typically deliver better ROI at this scale. - 5,000 to 20,000 claims monthly: XiFin evaluation makes sense if your current denial rate exceeds 15% and payor mix includes significant Medicare Advantage, Medicaid managed care, or commercial plans with inconsistent medical necessity policies. - Above 20,000 claims monthly: This represents XiFin's operational sweet spot, where platform automation and denial management sophistication can materially impact AR days and cost-to-collect metrics. - Geography matters: XiFin serves exclusively U.S. healthcare reimbursement. Organizations with multi-country laboratory operations will need parallel solutions. For RCM directors evaluating market-present enterprise platforms we recommend the following approach: XiFin represents a legitimate option–but only after asking harder questions than most vendor calls accommodate. ### What Do People Say About XiFin Online? Aggregated employee reviews from Glassdoor and Indeed place XiFin at approximately 2.9 out of 5 stars (crowdsourced data, unverified by this publication). Recurring themes include high workload, fast-paced release cycles (weekly software updates), and heavy operational pressure in accounts receivable and appeals roles. The median employee rating for healthcare RCM and SaaS vendors is approximately 3.4-3.6. XiFin sits below this sector average. Why does this matter for a purchasing decision? Employee turnover in billing operations and engineering directly impacts service quality and integration stability. High attrition rates increase the likelihood of knowledge loss, delayed issue resolution, and inconsistent client support. This is not a soft HR metric–it is operational risk. On your vendor call, ask about customer success team turnover rates, average tenure of technical support staff, and escalation protocols for billing issues. If XiFin cannot provide retention data or deflects the question, consider it a yellow flag. ## What's XiFin's Future? As of mid-2026, XiFin is heavily promoting its XiFin Empower AI capabilities. The platform now incorporates predictive AI (forecasting denial probability before claim submission), generative AI (automated documentation and appeal letter creation), and agent-based AI (autonomous workflow execution). The company is also expanding into retail and specialty pharmacy billing and actively lobbying in Washington on pharmacy access and reimbursement legislation. XiFin does not publish independently audited AI performance metrics. "AI-driven" is a claim made by every RCM vendor in 2026. What matters is measurable outcome improvement. In CMS and HIPAA-regulated environments, autonomous AI decision-making in billing requires human-in-the-loop verification for high-risk transactions. Ask your vendor which decisions the AI executes autonomously and which require human approval before submission to payors. GTCR has owned XiFin since 2014–a twelve-year hold period that significantly exceeds the typical private equity exit window of five to seven years. This timeline warrants direct conversation during vendor evaluation. Extended hold periods can signal product maturity and market leadership that makes exit timing discretionary. They can also indicate difficulty finding buyers at expected valuation multiples, particularly in capital-constrained environments. Neither interpretation is inherently disqualifying, but both carry implications for contract stability. Organizations negotiating multi-year agreements should explicitly address change-of-control provisions: What happens to pricing, SLAs, and support continuity if GTCR sells XiFin mid-contract? Do you have termination rights without penalty if ownership transition degrades service levels? Are there contractual protections if a new owner discontinues specific modules or integrations you depend on? These aren't theoretical concerns. The healthcare IT sector has seen repeated examples of PE exits followed by service degradation, support consolidation, and price increases for existing customers suddenly facing reduced leverage. Ask the question directly: What is GTCR's current exit timeline, and how do proposed contract terms protect operational continuity through ownership transition? ## XiFin 101 Guide | Summary XiFin is a mature, specialized RCM platform with a decade of private equity backing and a focused customer base in high-volume diagnostics. It is a serious option for laboratories processing tens of thousands of claims monthly and facing the operational complexity of multi-payor adjudication and appeal management. It is also a vendor whose pricing model is opaque, whose integration certifications are unpublished, whose AI performance claims lack third-party validation, and whose employee satisfaction scores sit below industry medians. None of these gaps disqualify XiFin. They define your due diligence checklist. Walk into your vendor call with specific questions: What is your fee structure relative to the 4-8% industry benchmark? Which EHR systems have certified integrations in production environments? What is the average FTE reduction your clients achieve at my claim volume? Can you provide audited AI performance data? What are your customer success team retention rates? If XiFin can answer these questions with specificity, you have a negotiation. If they deflect, you have a decision to make. At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. See examples of the work we automate around the platform in our [XiFin workflow automation](https://www.flobotics.io/xifin-in-rcm) overview. Ready to scale without growing headcount? Let's talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) ## FAQ: What does XiFin do? XiFin, Inc. is a SaaS-based revenue cycle management (RCM) and workflow automation company for the healthcare sector, founded in 1997 and headquartered in San Diego. It builds billing, claims, and financial-operations software used mainly by diagnostic providers such as laboratories and imaging groups. Is XiFin legitimate? Yes. XiFin is an actively operating company founded in 1997, headquartered in San Diego, with roughly 501–1,000 employees. It has been named to the Inc. 5000 list of fastest-growing private companies multiple times, most recently in 2023. How many employees does XiFin have? Inc.com lists XiFin's headcount at 501 to 1,000 employees. Third-party estimators such as LinkedIn or ZoomInfo may show a different figure, since exact counts fluctuate and aren't independently audited. Is XiFin a good company to work for? Mixed. XiFin holds a 3.3-out-of-5 rating on Glassdoor from 211 reviews, with only 51% of reviewers saying they'd recommend it to a friend — a middle-of-the-road result rather than a clear yes or no. Who owns XiFin? XiFin is privately held and led by founder and CEO Lâle White. Its most recent growth-equity round, announced in September 2025, was led by Goldman Sachs, following earlier investment from Avista Healthcare Partners. Is XiFin a public company? No. XiFin is privately held and not traded on any public stock exchange. Its growth has instead been funded through private and growth-equity investment, most recently a round led by Goldman Sachs in 2025. Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RCMHealthcare ### RCM Automation in Healthcare | 2026 RCM automation in healthcare: how RPA, AI, and OCR cut billing errors, speed up claims, and reduce manual work in 2026 revenue cycle management. Bart TeodorczukFebruary 25, 2026 ](https://www.flobotics.io/blog/rcm-automation-healthcare)[ AIRCMHealthcare ### Claude for Healthcare from Anthropic Claude for Healthcare from Anthropic: what's still unclear on data storage, routing, and third-party access before you roll it out to staff. Dominik PutMay 26, 2026 ](https://www.flobotics.io/blog/anthropic-annoucement-claude-for-healthcare)[ RCM ### Dental Revenue Cycle Management | 2026 Dental revenue cycle management: how practices are moving from semi-automated billing to predictive, human-in-the-loop RCM in 2026. Jędrzej SzymulaMarch 02, 2026 ](https://www.flobotics.io/blog/dental-revenue-cycle-management) [All articles →](https://www.flobotics.io/blog) --- # Digital Patient Engagement: What It Is and Why It Matters Canonical: https://www.flobotics.io/blog/digital-patient-engagement-explanation Author: Bart Teodorczuk Published: 2026-06-09 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Digital Patient Engagement: What It Is and Why It Matters [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Digital Patient Engagement: What It Is and Why It Matters [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published June 09, 2026Updated September 1, 2026 On this page - [What Is Digital Patient Engagement?](#what-is-digital-patient-engagement) - [Key Components in RCM Context](#key-components-in-rcm-context) - [When Is It Used?](#when-is-it-used) - [Why It Matters in RCM](#why-it-matters-in-rcm) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Is Digital Patient Engagement? Digital patient engagement is the use of technology-enabled channels — patient portals, mobile applications, text and email communications, online scheduling, and digital billing platforms — to involve patients in their care journey and financial responsibilities. In revenue cycle management, it sits primarily at the front end (pre-service scheduling, registration, financial counseling) and back end (statement delivery, online payment) of the billing cycle. The term spans both clinical engagement (accessing visit summaries, messaging providers, reviewing lab results) and financial engagement (viewing bills, making payments, setting up payment plans, understanding out-of-pocket costs before a visit). ## Key Components in RCM Context - Online scheduling and digital registration: Patients complete demographic and insurance information online before the visit. This improves registration data accuracy, reduces front-desk bottlenecks, and enables earlier eligibility verification — catching coverage issues days before the appointment rather than at check-in. - Patient cost estimation tools: Real-time cost estimators, offered via portal or text, show patients their estimated out-of-pocket responsibility before the visit. Patients who understand their financial obligation in advance are significantly more likely to pay at or shortly after the time of service. - Digital statements and online payment: Electronic statements delivered by text or email have materially higher open rates than paper statements and enable one-click payment. This matters because the average paper billing cycle — statement generation, mailing, return mail processing — adds 20–30 days to collection time. - Payment plans and financing: Integrated digital platforms allow patients to self-enroll in payment plans without calling the billing office, which both accelerates collection and reduces call volume. - Patient portal messaging: Secure portal messaging reduces phone tag for billing questions and allows the billing team to handle inquiries asynchronously at scale. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## When Is It Used? Digital patient engagement tools are in use across every phase of the patient financial experience: pre-service (scheduling, registration, cost estimation), at the point of service (check-in, copay collection), and post-service (statement delivery, payment, balance disputes). The highest-impact RCM applications are pre-service cost transparency and post-service digital billing — both directly tied to the increasing challenge of patient collections. ## Why It Matters in RCM Patient collections have become the hardest part of the revenue cycle. As high-deductible health plans have proliferated, the portion of provider revenue dependent on patient out-of-pocket payments has grown substantially — and collection rates have fallen. The national patient collection rate dropped from 54.8% in 2021 to 47.8% in 2022–2023, according to data referenced by [Becker's Hospital Review](https://www.beckershospitalreview.com/finance/the-domino-effect-of-net-collection-percentage/). That means more than half of what patients owe is never collected. Digital engagement tools are the primary lever practices have to improve this number. Research consistently shows that patients pay faster and at higher rates when they receive digital statements, can pay online without calling, and understand their balance before it arrives. [HFMA highlights patient payment rate](https://www.hfma.org/revenue-cycle/kpis/7-kpis-providers-should-be-tracking/) as one of the seven KPIs every provider should track — and digital engagement is central to moving that metric. The operational benefit extends upstream as well. Better digital registration reduces eligibility-related denials. Pre-service financial counseling reduces bad debt. Real-time cost estimates reduce billing disputes and write-off requests after the fact. Done well, digital patient engagement improves NCR, lowers days in AR, and reduces cost to collect — all three simultaneously. Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### Patient Access: The Front End of the Revenue Cycle What is patient access? A guide to the front-end RCM steps - scheduling, registration, eligibility checks, and prior authorization - that start every claim. Jędrzej SzymulaJune 02, 2026 ](https://www.flobotics.io/blog/patient-access-explanation)[ HealthcareRCM ### Net Promoter Score (NPS) in Healthcare Net Promoter Score (NPS) in healthcare ties patient loyalty to billing experience - and increasingly to Value-Based Care reimbursement. Bart TeodorczukMay 21, 2026 ](https://www.flobotics.io/blog/nps-net-promoter-score-explanation)[ HealthcareRCM ### Patient Statement: What to Include on a Medical Bill Patient statement guide: what belongs on the final bill patients receive - and why clarity here drives faster payment. Jędrzej SzymulaApril 23, 2026 ](https://www.flobotics.io/blog/patient-statement-explanation) [All articles →](https://www.flobotics.io/blog) --- # What Is HIPAA? Rules, Penalties and Impact on RCM Canonical: https://www.flobotics.io/blog/health-insurance-portability-and-accountability-act-hipaa-explanation Author: Karl Mielnicki Published: 2026-06-08 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/What Is HIPAA? Rules, Penalties and Impact on RCM CTO Notes [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # What Is HIPAA? Rules, Penalties and Impact on RCM [Karl MielnickiCTO & Co-Founder of Flobotics](https://www.flobotics.io/our-editorial-team#mielnicki) Published June 08, 2026Updated September 1, 2026 On this page - [What Is HIPAA?](#what-is-hipaa) - [HIPAA's Direct Impact on Revenue Cycle Management](#hipaa-s-direct-impact-on-revenue-cycle-management) - [HIPAA Violations: Risk and Penalties](#hipaa-violations-risk-and-penalties) - [HIPAA-Compliant Automation in RCM](#hipaa-compliant-automation-in-rcm) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Is HIPAA? The Health Insurance Portability and Accountability Act (HIPAA) is a U.S. federal law enacted in 1996 that establishes national standards for protecting the privacy and security of sensitive patient health information. For healthcare organizations and their business associates — including billing companies, RCM vendors, and technology providers — HIPAA is the foundational compliance framework governing how [Protected Health Information (PHI)](https://www.flobotics.io/blog/protected-health-information-phi) is stored, transmitted, accessed, and disclosed. HIPAA consists of interrelated regulations: the Privacy Rule governs who can access and use PHI; the Security Rule specifies technical, administrative, and physical safeguards for electronic PHI (ePHI); the Breach Notification Rule mandates timely disclosure of data breaches; and the Omnibus Rule extended HIPAA obligations to business associates and their subcontractors. ## HIPAA's Direct Impact on Revenue Cycle Management Every step of the RCM workflow involves PHI. Patient demographics, insurance information, diagnosis codes, procedure codes, payment records, and clinical documentation are all individually identifiable health information protected under HIPAA. This means every RCM process — from eligibility verification through claims submission to payment posting — must be executed within HIPAA-compliant systems and workflows. For RCM teams, HIPAA compliance has specific operational implications: - Electronic transaction standards: HIPAA mandates ANSI X12 EDI formats for electronic claims, eligibility checks, remittance advice, and claim status inquiries — the operational backbone of modern RCM - Business Associate Agreements (BAAs): Every vendor with PHI access — clearinghouses, EHRs, billing platforms, automation providers — must execute a BAA specifying compliance obligations - Minimum necessary standard: Access, use, or transmit only the PHI required to complete a specific function - Audit trails: All systems handling ePHI must maintain logs of access events - Encryption: PHI transmitted electronically must be encrypted in transit and at rest ## HIPAA Violations: Risk and Penalties HIPAA enforcement is handled by the HHS Office for Civil Rights (OCR). Civil penalties range from $100 to $50,000 per violation, with annual caps up to $1.9M per violation category. Criminal penalties apply for willful neglect. Beyond financial penalties, breaches affecting 500+ individuals in a state require notification to prominent media outlets — reputational damage that often exceeds direct penalty costs. The most common HIPAA violations in RCM involve impermissible PHI disclosures, lack of system access controls, insufficient workforce training, and failure to execute BAAs with applicable vendors. ## HIPAA-Compliant Automation in RCM Automation does not conflict with HIPAA — when properly implemented, it enhances compliance. Automated workflows reduce the number of humans handling PHI, create consistent audit trails, and eliminate the manual errors (wrong fax numbers, misdirected emails, unsecured spreadsheets) that cause most inadvertent disclosures. A HIPAA-compliant [RCM automation program](https://www.flobotics.io/rcm-automation) includes encrypted data transmission at all integration points, role-based access controls, automated audit logging on all ePHI access events, and BAAs executed with all automation vendors. Our solutions are designed for HIPAA compliance by default. [Contact us](https://www.flobotics.io/contact) to discuss your specific compliance requirements. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byKarl Mielnicki CTO & Co-Founder of Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### What Is PHI? Protected Health Information Explained What is protected health information (PHI)? A HIPAA guide to identifiable patient data and the RCM controls needed - breaches risk penalties up to $1.9M. Krzysztof SzwedJune 05, 2026 ](https://www.flobotics.io/blog/protected-health-information-phi)[ HealthcareRCM ### Clinical Documentation Integrity (CDI): Why It Matters Clinical Documentation Integrity (CDI), explained: how documentation gaps drive undercoding and silent revenue leakage. Karl MielnickiMarch 03, 2026 ](https://www.flobotics.io/blog/clinical-documentation-integrity-cdi-explanation)[ HealthcareRCM ### Medical Necessity: How Payers Decide What They Cover Medical necessity, explained: how payers decide if a service qualifies for coverage, and what proof stops denials before they start. Bart TeodorczukMarch 30, 2026 ](https://www.flobotics.io/blog/medical-necessity-explanation) [All articles →](https://www.flobotics.io/blog) --- # What Is a LIMS? Laboratory Information Management Systems Canonical: https://www.flobotics.io/blog/laboratory-information-management-system-lims Author: Jędrzej Szymula Published: 2026-06-07 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/What Is a LIMS? Laboratory Information Management Systems [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # What Is a LIMS? Laboratory Information Management Systems [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published June 07, 2026Updated September 1, 2026 Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Laboratory Information Management System (LIMS) It is software designed to manage and track samples, experiments, and results to streamline laboratory operations. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### What Is HIPAA? Rules, Penalties and Impact on RCM What is HIPAA? The federal law governing PHI privacy and security in US healthcare - RCM teams face penalties up to $1.9M per violation category. Karl MielnickiJune 08, 2026 ](https://www.flobotics.io/blog/health-insurance-portability-and-accountability-act-hipaa-explanation)[ HealthcareRCM ### What Is PHI? Protected Health Information Explained What is protected health information (PHI)? A HIPAA guide to identifiable patient data and the RCM controls needed - breaches risk penalties up to $1.9M. Krzysztof SzwedJune 05, 2026 ](https://www.flobotics.io/blog/protected-health-information-phi)[ HealthcareRCM ### Intelligent Document Processing (IDP) in Healthcare RCM Intelligent Document Processing (IDP) uses AI, OCR, and NLP to turn scanned EOBs and faxes into automated RCM workflows in 2026. Krzysztof SzwedMay 31, 2026 ](https://www.flobotics.io/blog/intelligent-document-processing-idp-explanation) [All articles →](https://www.flobotics.io/blog) --- # What Is PHI? Protected Health Information Explained Canonical: https://www.flobotics.io/blog/protected-health-information-phi Author: Krzysztof Szwed Published: 2026-06-05 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/What Is PHI? Protected Health Information Explained [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # What Is PHI? Protected Health Information Explained [Krzysztof SzwedHead of Delivery at Flobotics](https://www.flobotics.io/our-editorial-team#szwed) Published June 05, 2026Updated September 1, 2026 On this page - [What Is Protected Health Information (PHI)?](#what-is-protected-health-information-phi) - [PHI in Revenue Cycle Management](#phi-in-revenue-cycle-management) - [Electronic PHI (ePHI) and Security Requirements](#electronic-phi-ephi-and-security-requirements) - [Common PHI Breach Risks in RCM](#common-phi-breach-risks-in-rcm) - [PHI Handling in Automation Workflows](#phi-handling-in-automation-workflows) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Is Protected Health Information (PHI)? Protected Health Information (PHI) is defined under [HIPAA](https://www.flobotics.io/blog/health-insurance-portability-and-accountability-act-hipaa-explanation) as any individually identifiable health information created, received, maintained, or transmitted by a covered entity or business associate in connection with healthcare provision or payment. PHI includes 18 specific identifier categories — any one of which, combined with health information, creates a HIPAA-protected record. The 18 categories include: names, geographic data smaller than a state, dates directly related to an individual, phone numbers, fax numbers, email addresses, Social Security numbers, medical record numbers, health plan beneficiary numbers, account numbers, certificate and license numbers, vehicle identifiers, device identifiers, web URLs, IP addresses, biometric identifiers, full-face photographs, and any other unique identifying numbers or codes. ## PHI in Revenue Cycle Management The entire RCM workflow is a PHI handling operation. Every claim contains the patient's name, date of birth, insurance ID, diagnosis codes, procedure codes, and service dates — a complete PHI set. Eligibility verification queries contain demographic and coverage PHI. Prior authorization requests contain clinical PHI. EOBs and ERAs contain payment PHI linked to individual patient accounts. This means every vendor, system, and workflow touching any part of the revenue cycle handles PHI and must operate within HIPAA's requirements. Business Associate Agreements (BAAs) must be executed with every third-party vendor — clearinghouses, billing software, automation platforms, cloud infrastructure — that processes PHI on behalf of the covered entity. ## Electronic PHI (ePHI) and Security Requirements ePHI is PHI created, stored, transmitted, or received electronically. The HIPAA Security Rule requires three categories of safeguards: - Administrative safeguards: Policies governing workforce access, training, and incident response - Physical safeguards: Controls over physical access to systems and facilities where ePHI is stored - Technical safeguards: Access controls, audit logs, encryption in transit and at rest, and automatic logoff on ePHI-handling systems Encryption of data in transit (TLS 1.2+ minimum) and at rest (AES-256 standard) is the baseline requirement for any compliant ePHI system — including every platform in your RCM technology stack. ## Common PHI Breach Risks in RCM The most common PHI breach scenarios in RCM include: misdirected faxes containing patient information, unencrypted email transmission of claim data, improper disposal of paper EOBs, unauthorized access to billing systems, and vendor breaches where a business associate's infrastructure is compromised. Each represents both a HIPAA compliance failure and a direct patient harm risk. ## PHI Handling in Automation Workflows HIPAA-compliant RCM automation requires all PHI processed by automated workflows to be transmitted over encrypted connections, stored in HIPAA-compliant infrastructure, access-controlled to minimum necessary data, and fully audit-logged. Our [RCM automation solutions](https://www.flobotics.io/rcm-automation) are built with these requirements as design constraints, not afterthoughts. [Contact us](https://www.flobotics.io/contact) to review your PHI handling architecture. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byKrzysztof Szwed Head of Delivery at Flobotics. [More from Krzysztof](https://www.flobotics.io/our-editorial-team#szwed) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### What Is HIPAA? Rules, Penalties and Impact on RCM What is HIPAA? The federal law governing PHI privacy and security in US healthcare - RCM teams face penalties up to $1.9M per violation category. Karl MielnickiJune 08, 2026 ](https://www.flobotics.io/blog/health-insurance-portability-and-accountability-act-hipaa-explanation)[ HealthcareRCM ### Clinical Documentation Integrity (CDI): Why It Matters Clinical Documentation Integrity (CDI), explained: how documentation gaps drive undercoding and silent revenue leakage. Karl MielnickiMarch 03, 2026 ](https://www.flobotics.io/blog/clinical-documentation-integrity-cdi-explanation)[ HealthcareRCM ### Medical Necessity: How Payers Decide What They Cover Medical necessity, explained: how payers decide if a service qualifies for coverage, and what proof stops denials before they start. Bart TeodorczukMarch 30, 2026 ](https://www.flobotics.io/blog/medical-necessity-explanation) [All articles →](https://www.flobotics.io/blog) --- # Net Collection Rate (NCR): Formula and Benchmarks Canonical: https://www.flobotics.io/blog/net-collection-rate-ncr Author: Bart Teodorczuk Published: 2026-06-04 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Net Collection Rate (NCR): Formula and Benchmarks [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Net Collection Rate (NCR): Formula and Benchmarks [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published June 04, 2026Updated September 1, 2026 On this page - [What Is Net Collection Rate (NCR)?](#what-is-net-collection-rate-ncr) - [NCR vs. Gross Collection Rate — Why the Difference Matters](#ncr-vs-gross-collection-rate-why-the-difference-matters) - [When Is NCR Used?](#when-is-ncr-used) - [When Does NCR Matter Most in RCM?](#when-does-ncr-matter-most-in-rcm) - [NCR Benchmarks: What Is a Good Score?](#ncr-benchmarks-what-is-a-good-score) - [What Drives NCR Down?](#what-drives-ncr-down) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Is Net Collection Rate (NCR)? Net Collection Rate (NCR) measures what percentage of the revenue you are actually allowed to collect — after contractual adjustments — you are successfully bringing in. It is the single most accurate indicator of a practice's collection performance in revenue cycle management. The formula is straightforward: NCR = (Payments Collected ÷ (Gross Charges − Contractual Adjustments)) × 100 For example: a practice bills $10M, has $6M in contractual adjustments, and collects $3.7M. The NCR is $3.7M ÷ $4M = 92.5% — meaning 7.5% of legitimately owed revenue was never recovered. ## NCR vs. Gross Collection Rate — Why the Difference Matters Gross Collection Rate divides total collections by total billed charges. Because chargemaster rates are often set 2–5× above what payers actually allow, gross collection rate can look alarmingly low (30–50%) even at a perfectly healthy practice. It is not a meaningful performance metric on its own. NCR strips out the noise. By removing contractual write-offs from the denominator, it focuses only on revenue that was realistically collectible — making it the metric RCM directors, CFOs, and billing managers should track as a primary KPI. [HFMA's MAP Keys](https://www.hfma.org/data-and-insights/map-initiative/map-keys/) identifies NCR as one of the core industry-standard revenue cycle KPIs every provider should monitor. ## When Is NCR Used? NCR is used continuously across the revenue cycle — not just at month-end reporting. Here is where it shows up in practice: - Monthly performance reviews: RCM managers use NCR to gauge whether the billing team is keeping up with denials, underpayments, and write-offs. - Payer contract negotiations: A low NCR for a specific payer signals systemic underpayment or excessive denials and provides leverage in renegotiation. - Practice benchmarking: Multi-site groups use NCR by location and by specialty to surface underperforming sites or billing staff. - Vendor evaluation: When outsourcing RCM, NCR is the primary metric used to hold a billing company accountable. - Investor and M&A due diligence: Private equity and acquirers routinely scrutinize NCR to assess the health of a practice's revenue operations before a transaction. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## When Does NCR Matter Most in RCM? NCR becomes a critical alarm in several specific scenarios: Payer mix shifts. When a practice gains or loses a major contract, the NCR will shift. A move toward higher Medicare volume typically lowers NCR because Medicare patient cost-sharing is harder to collect — national patient collection rates fell from 54.8% in 2021 to 47.8% in 2022–2023, according to [Becker's Hospital Review](https://www.beckershospitalreview.com/finance/the-domino-effect-of-net-collection-percentage/). Staffing or workflow changes. A new biller, a change in clearinghouse, or an EHR migration almost always causes a temporary NCR dip. Catching it early prevents a backlog from forming. Rising denial rates. Every unworked or written-off denial directly reduces NCR. If denial volume climbs — as it has for most providers, with commercial plan denial rates rising over 20% in recent years — NCR will fall unless the appeals process keeps pace. Timely filing limits. Claims that age past payer filing deadlines become uncollectable. A declining NCR often surfaces this problem before days-in-AR does. ## NCR Benchmarks: What Is a Good Score? According to [HFMA MAP Keys](https://www.hfma.org/data-and-insights/map-initiative/map-keys/) and MGMA data, the target range for most physician practices is 95–99%: - 98–99%: Top-quartile performance. Denials are minimal, billing is clean, underpayments are identified and appealed. - 95–97%: Solid but with room for improvement. Typically indicates manageable gaps in follow-up or occasional write-offs that could be recovered. - 90–94%: Below standard. Points to systemic issues — high denial rate, weak patient collection, or billing errors that are not being corrected at the source. - Below 90%: A significant revenue problem. On a practice billing $5M annually, a 90% NCR means $500,000 in collectible revenue is lost each year compared to a 100% benchmark. ## What Drives NCR Down? The most common root causes of a declining NCR include: high rates of unworked denials, insufficient patient collections (copays, deductibles), underpayments accepted without audit, timely filing failures, duplicate or incorrect write-offs, and poor charge capture upstream. Identifying which driver is at play requires segmenting NCR by payer, by denial reason code, and by service line — not just tracking the aggregate number. Automation is increasingly being applied to address these root causes before they hit the NCR. Pre-submission claim scrubbing, automated denial routing, and real-time underpayment detection are among the tools practices use to keep NCR consistently above 95%. Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### Days in Accounts Receivable (DAR): Formula and Benchmarks Days in Accounts Receivable (DAR) guide: why 30-35 days is best practice and anything above 50 signals collection trouble. Krzysztof SzwedMay 21, 2026 ](https://www.flobotics.io/blog/days-in-accounts-receivable-dar-explanation)[ HealthcareRCM ### Cost to Collect (CTC): Definition and Benchmarks Cost to Collect (CTC) benchmarks sit at 3-5% of net revenue - a 1% cut on $10M in collections frees up $100,000 in cash. Karl MielnickiMay 18, 2026 ](https://www.flobotics.io/blog/cost-to-collect-ctc-explanation)[ HealthcareRCM ### Clean Claim Rate (CCR): Definition and Benchmarks Clean Claim Rate (CCR) guide: the foundational RCM metric behind denials, DAR, and collections, with a 98%+ target. Bart TeodorczukJune 01, 2026 ](https://www.flobotics.io/blog/clean-claim-rate-ccr-explanation) [All articles →](https://www.flobotics.io/blog) --- # Charge Capture: What It Is and How It Works in RCM Canonical: https://www.flobotics.io/blog/charge-capture-explanation Author: Karl Mielnicki Published: 2026-06-03 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Charge Capture: What It Is and How It Works in RCM CTO Notes [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Charge Capture: What It Is and How It Works in RCM [Karl MielnickiCTO & Co-Founder of Flobotics](https://www.flobotics.io/our-editorial-team#mielnicki) Published June 03, 2026Updated September 1, 2026 On this page - [What Is Charge Capture?](#what-is-charge-capture) - [How Charge Capture Works](#how-charge-capture-works) - [When Is It Used?](#when-is-it-used) - [Why It Matters in RCM](#why-it-matters-in-rcm) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Is Charge Capture? Charge capture is the process of translating clinical services — procedures performed, supplies used, medications administered — into billable charges that flow into the claim. It bridges the gap between what happens in the exam room or operating suite and what actually gets billed to the payer. In a properly functioning revenue cycle, every service documented in the patient's chart generates a corresponding charge entry. Those entries are assigned CPT and HCPCS codes, tied to the appropriate diagnosis (ICD-10), and queued for claim generation. If a service is documented but never captured as a charge, it disappears from the billing workflow entirely — it cannot be denied, corrected, or appealed, because it was never submitted. ## How Charge Capture Works Charge capture occurs through several mechanisms depending on the care setting: - EHR-integrated charge capture: Most modern systems generate charges automatically from clinical orders or from the provider's encounter documentation. A signed note or a completed procedure triggers a charge entry without manual intervention. - Charge description master (CDM): In hospital billing, every billable item — from an aspirin to an MRI — is assigned a charge code in the CDM. When a clinician orders or documents a service, the CDM maps it to the appropriate charge. - Manual charge entry: In some practices, especially smaller ones or those in specialties with complex procedure coding, billers review the encounter and manually enter charges based on the clinical documentation. This is slower and more error-prone. - Mid-level and ancillary charge capture: Services provided by nurses, therapists, or technicians — infusions, wound care, imaging — require their own charge capture workflows, often separate from the physician encounter. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## When Is It Used? Charge capture happens at the point of care and immediately after. In an outpatient practice, charges are typically expected within 24–48 hours of the encounter. In a hospital setting, charges may accumulate throughout an inpatient stay and be reconciled at discharge. Either way, timely charge entry is critical: most payers impose timely filing deadlines (often 90–180 days from the date of service), and charges submitted after those windows are denied and non-recoverable. ## Why It Matters in RCM Charge capture is where revenue leakage most often begins. According to research cited by [Becker's Hospital Review](https://www.beckershospitalreview.com/finance/the-economics-of-rcm-5-ways-to-reduce-cost-to-collect.html), providers routinely lose 1–3% of net revenue to missed or undercoded charges — revenue that never reaches the claim stage and therefore can never be recovered. The most common charge capture failures include: - Missing charges: A service is performed and documented but never triggers a charge — common in high-volume or fast-paced settings like the ED or OR. - Late charges: Charges entered after timely filing deadlines are non-billable. Each one is a permanent write-off. - Undercoding: The service was captured, but assigned a lower-intensity code than the documentation supports. The claim pays, but at a reduced rate — this is often harder to detect than a missed charge entirely. - Duplicate charges: The same service is entered twice, triggering a duplicate claim denial and rework costs. Because charge capture problems originate before the claim is built, they are invisible to denial rate metrics and AR aging reports. A practice can have a 97% clean claim rate and still be losing significant revenue to missed charges upstream. Regular charge capture audits — comparing clinical encounter volume to charge entry volume by provider and service — are the primary tool for detecting these gaps. Written byKarl Mielnicki CTO & Co-Founder of Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### What Is Medical Coding? ICD-10 vs. CPT/HCPCS Medical coding, explained: how ICD-10 diagnoses and CPT/HCPCS procedures become the codes that drive clean claims and reimbursement. Jędrzej SzymulaApril 07, 2026 ](https://www.flobotics.io/blog/medical-coding-explanation)[ HealthcareRCM ### Clinical Documentation Integrity (CDI): Why It Matters Clinical Documentation Integrity (CDI), explained: how documentation gaps drive undercoding and silent revenue leakage. Karl MielnickiMarch 03, 2026 ](https://www.flobotics.io/blog/clinical-documentation-integrity-cdi-explanation)[ HealthcareRCM ### Patient Access: The Front End of the Revenue Cycle What is patient access? A guide to the front-end RCM steps - scheduling, registration, eligibility checks, and prior authorization - that start every claim. Jędrzej SzymulaJune 02, 2026 ](https://www.flobotics.io/blog/patient-access-explanation) [All articles →](https://www.flobotics.io/blog) --- # Patient Access: The Front End of the Revenue Cycle Canonical: https://www.flobotics.io/blog/patient-access-explanation Author: Jędrzej Szymula Published: 2026-06-02 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Patient Access: The Front End of the Revenue Cycle [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Patient Access: The Front End of the Revenue Cycle [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published June 02, 2026Updated September 1, 2026 Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Patient Access Front-end RCM processes including scheduling, registration, eligibility verification, and obtaining prior authorization. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ EligibilityHealthcareRCM ### Insurance Eligibility Verification in Healthcare, Explained Eligibility verification guide: confirming insurance coverage and patient financial responsibility before the visit, in real time. Krzysztof SzwedApril 08, 2026 ](https://www.flobotics.io/blog/eligibility-verification-explanation)[ HealthcareRCM ### What Is Prior Authorization (Pre-Auth) in Healthcare? Prior authorization (pre-auth), explained: the process behind healthcare's 13-hour weekly physician burden - and how automation cuts each cycle to minutes. Bart TeodorczukApril 30, 2026 ](https://www.flobotics.io/blog/prior-authorization-pre-auth-explanation)[ HealthcareRCM ### Medical Necessity: How Payers Decide What They Cover Medical necessity, explained: how payers decide if a service qualifies for coverage, and what proof stops denials before they start. Bart TeodorczukMarch 30, 2026 ](https://www.flobotics.io/blog/medical-necessity-explanation) [All articles →](https://www.flobotics.io/blog) --- # Clean Claim Rate (CCR): Definition and Benchmarks Canonical: https://www.flobotics.io/blog/clean-claim-rate-ccr-explanation Author: Bart Teodorczuk Published: 2026-06-01 Updated: 2026-09-08 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Clean Claim Rate (CCR): Definition and Benchmarks [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Clean Claim Rate (CCR): Definition and Benchmarks [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published June 01, 2026Updated September 8, 2026 On this page - [What Is Clean Claim Rate (CCR)?](#what-is-clean-claim-rate-ccr) - [The Compounding Cost of a Low CCR](#the-compounding-cost-of-a-low-ccr) - [Industry Benchmarks](#industry-benchmarks) - [Most Common Causes of Dirty Claims](#most-common-causes-of-dirty-claims) - [How Automation Drives CCR to 98%+](#how-automation-drives-ccr-to-98) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Is Clean Claim Rate (CCR)? Clean Claim Rate (CCR) is the percentage of claims accepted by insurance payers on the very first submission — with no rejection, correction request, or manual intervention required. It is the single most foundational quality metric in Revenue Cycle Management. Every downstream indicator — denial rates, [Claim Turnaround Time](https://www.flobotics.io/blog/claim-turnaround-time-ctt-explanation), [Days in AR](https://www.flobotics.io/blog/days-in-accounts-receivable-dar-explanation), and [Net Collection Rate](https://www.flobotics.io/blog/net-collection-rate-ncr) — is directly shaped by how clean claims are when they leave your billing office. ## The Compounding Cost of a Low CCR Every claim that fails first-pass acceptance multiplies the work required to collect payment. A denied claim must be identified, investigated, corrected, resubmitted, and tracked again. Industry data consistently shows that reworking a denied claim costs 5–10x more than submitting it correctly the first time. At scale, even a 5% gap from best-in-class CCR is financially significant. A practice submitting 8,000 claims per month at 93% CCR generates 560 dirty claims monthly — each requiring a manual rework cycle. At $25–$50 per reworked claim, that is $14,000–$28,000 in avoidable monthly expense, plus revenue at risk from timely filing limits. ## Industry Benchmarks - Best-in-class: 98–99%+ - Industry average: 90–95% - Underperforming: Below 90% — requires immediate root-cause analysis by payer and code combination ## Most Common Causes of Dirty Claims - Eligibility errors: Coverage inactive, wrong plan, or subscriber ID mismatch — the most frequent first-pass denial trigger - Missing or expired prior authorization: Payer rejects claims for services requiring pre-auth not obtained or lapsed - ICD-10 / CPT code mismatches: Diagnosis-procedure combinations not aligning with payer medical necessity policies - Missing modifiers: Bilateral, assistant surgeon, or facility modifiers omitted at coding - Demographic data errors: Patient name, DOB, or member ID not matching payer records exactly - Coordination of benefits issues: Primary/secondary payer sequencing errors on multi-coverage patients ## How Automation Drives CCR to 98%+ [Automated claims management](https://www.flobotics.io/agents/claims-management-automation) addresses each root cause category directly: - Automated [eligibility verification](https://www.flobotics.io/agents/eligibility-check-automation) at scheduling and pre-claim generation catches coverage issues 24–48 hours before submission - AI-powered claim editing applies payer-specific rules in real time, preventing non-compliant submissions - [Prior authorization automation](https://www.flobotics.io/agents/prior-authorization-automation) cross-references treatment plans against payer requirements and alerts staff when auth is missing - Denial pattern analytics identify specific payer-code-provider combinations driving the most rejections Our clients have achieved CCR improvements from 84–88% to 96–98%+ within 60–90 days. [See the results.](https://www.flobotics.io/case-studies) Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## FAQ: What is a clean claim? A claim that's accepted and paid the first time it's submitted, with no missing information, coding errors, or additional documentation requests from the payer. Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### Claim Turnaround Time (CTT): Benchmarks and Root Causes Claim Turnaround Time (CTT), explained: why 14-21 days is best-in-class and 45+ days signals a billing cycle problem. Krzysztof SzwedMay 04, 2026 ](https://www.flobotics.io/blog/claim-turnaround-time-ctt-explanation)[ HealthcareRCM ### Initial Denial Rate: How to Measure and Lower It Initial denial rate, explained: what counts as a first-pass claim rejection and how to benchmark and lower yours in 2026. Jędrzej SzymulaMay 18, 2026 ](https://www.flobotics.io/blog/initial-denial-percentage-explanation)[ HealthcareRCM ### What Is Claim Scrubbing? What Gets Checked Before Submission Claim scrubbing, explained: how automated pre-submission checks catch errors that cost $25-$44 per claim to fix after denial. Krzysztof SzwedMarch 24, 2026 ](https://www.flobotics.io/blog/claim-scrubbing-explanation) [All articles →](https://www.flobotics.io/blog) --- # Intelligent Document Processing (IDP) in Healthcare RCM Canonical: https://www.flobotics.io/blog/intelligent-document-processing-idp-explanation Author: Krzysztof Szwed Published: 2026-05-31 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Intelligent Document Processing (IDP) in Healthcare RCM [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Intelligent Document Processing (IDP) in Healthcare RCM [Krzysztof SzwedHead of Delivery at Flobotics](https://www.flobotics.io/our-editorial-team#szwed) Published May 31, 2026Updated September 1, 2026 On this page - [What Is Intelligent Document Processing (IDP)?](#what-is-intelligent-document-processing-idp) - [Why IDP Is Critical in Healthcare RCM?](#why-idp-is-critical-in-healthcare-rcm) - [Key IDP Use Cases in RCM](#key-idp-use-cases-in-rcm) - [IDP vs. Traditional RPA](#idp-vs-traditional-rpa) - [How IDP Fits Into a Modern RCM Stack?](#how-idp-fits-into-a-modern-rcm-stack) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Is Intelligent Document Processing (IDP)? Intelligent Document Processing (IDP) is the application of artificial intelligence — combining Optical Character Recognition (OCR), Natural Language Processing (NLP), and machine learning classification — to automatically extract, classify, and validate structured data from unstructured or semi-structured documents. In healthcare RCM, IDP transforms the enormous volume of paper-based, faxed, scanned, and variably formatted documents flowing through billing operations into machine-readable data that drives automated workflows. Unlike traditional OCR, which converts images to text without understanding context, IDP understands what data means: it identifies a payer name, authorization number, denial reason code, or procedure code within a free-form document — even when format varies across payers and document types. ## Why IDP Is Critical in Healthcare RCM? Healthcare RCM remains one of the most document-intensive industries in existence. Despite decades of EHR adoption, a significant portion of RCM-relevant information still arrives in formats requiring human interpretation: faxed prior authorization responses, scanned Explanation of Benefits (EOBs) from secondary insurers, paper remittance advice, clinical notes supporting medical necessity, and appeal correspondence. Each document requires a staff member to open, read, extract data, and enter it into a billing system — a high-volume, error-prone, and expensive process. IDP replaces this manual cycle with automated extraction that processes documents in seconds at error rates significantly below human baseline. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Key IDP Use Cases in RCM - EOB and ERA processing: Extracting payment amounts, adjustment codes, and denial codes from remittance documents for automated [payment posting](https://www.flobotics.io/blog/payment-posting-cash-posting-explanation) - Prior authorization responses: Reading faxed or scanned auth approvals and denials, extracting authorization numbers and service limitations for [prior auth workflows](https://www.flobotics.io/agents/prior-authorization-automation) - Appeal correspondence: Classifying payer responses to appeals, extracting decision data for [denial management](https://www.flobotics.io/agents/denials-management-automation) routing - Clinical documentation review: Processing physician notes to identify documentation gaps and CDI query triggers - Referral and order processing: Extracting clinical and administrative data from referral documents ## IDP vs. Traditional RPA Traditional RPA excels at automating structured, rules-based digital processes — navigating a payer portal, submitting an electronic claim, or updating a patient record. But RPA cannot read a scanned fax and understand its content. IDP fills this gap, processing unstructured inputs and handing structured outputs to downstream RPA workflows. The combination of IDP for document understanding and RPA for process execution is the architecture that enables truly end-to-end RCM automation. ## How IDP Fits Into a Modern RCM Stack? IDP is a foundational layer in any sophisticated [RCM automation program](https://www.flobotics.io/rcm-automation). Organizations deploying IDP alongside workflow automation achieve higher straight-through processing rates, lower manual intervention requirements, and faster cycle times across every document-dependent process. Leading platforms achieve 95–99% extraction accuracy on high-volume RCM document types. [Contact us](https://www.flobotics.io/contact) to discuss IDP implementation for your specific workflows. Written byKrzysztof Szwed Head of Delivery at Flobotics. [More from Krzysztof](https://www.flobotics.io/our-editorial-team#szwed) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### Predictive Analytics in RCM: Key Applications Predictive analytics in RCM forecasts denials and non-payment risk, turning reactive billing into proactive revenue protection. Krzysztof SzwedApril 28, 2026 ](https://www.flobotics.io/blog/predictive-analytics-explanation)[ HealthcareRCM ### What Is Medical Coding? ICD-10 vs. CPT/HCPCS Medical coding, explained: how ICD-10 diagnoses and CPT/HCPCS procedures become the codes that drive clean claims and reimbursement. Jędrzej SzymulaApril 07, 2026 ](https://www.flobotics.io/blog/medical-coding-explanation)[ HealthcareRCM ### Charge Capture: What It Is and How It Works in RCM What is charge capture? How converting clinical services into billable charges kicks off the revenue cycle, and why missed charges are lost revenue. Karl MielnickiJune 03, 2026 ](https://www.flobotics.io/blog/charge-capture-explanation) [All articles →](https://www.flobotics.io/blog) --- # CFO's Take On: AWS Connect Health Canonical: https://www.flobotics.io/blog/aws-connect-health-cafc9 Author: Krzysztof Szwed Published: 2026-05-31 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/CFO's Take On: AWS Connect Health [AI](https://www.flobotics.io/blog?category=ai)[Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # CFO's Take On: AWS Connect Health [Krzysztof SzwedHead of Delivery at Flobotics](https://www.flobotics.io/our-editorial-team#szwed) Published May 31, 2026Updated September 1, 2026 On this page - [Three Names, Three Different Products](#threenamesthreedifferentproducts) - [What Amazon Connect Health Actually Does–And Doesn't](#whatamazonconnecthealthactuallydoesanddoesnt) - [✅ Production-Ready Use Cases](#productionreadyusecases) - [⚠️ Early-Stage / Integration-Intensive Use Cases](#earlystageintegrationintensiveusecases) - [❌ What Amazon Connect Health Does Not Do](#whatamazonconnecthealthdoesnotdo) - [HIPAA Eligible ≠ HIPAA Compliant](#hipaaeligiblehipaacompliant) - [The Shared Responsibility Model](#thesharedresponsibilitymodel) - [Critical Question Without Public Answer](#criticalquestionwithoutpublicanswer) - [The Financial Risk](#thefinancialrisk) - [What It Actually Costs](#whatitactuallycosts) - [Publicly Available Pricing (as of May 2026)](#publiclyavailablepricingasofapril2025) - [Hidden Costs CFOs Must Budget For](#hiddencostscfosmustbudgetfor) - [Benchmark Comparison: Pay-Per-Use vs. Per-Seat CCaaS](#benchmarkcomparisonpayperusevsperseatccaas) - [The TCO Reality Check](#thetcorealitycheck) - [When Amazon Connect Health Makes Sense–And When It Doesn't](#whenamazonconnecthealthmakessenseandwhenitdoesnt) - [Deploy Amazon Connect Health When:](#deployamazonconnecthealthwhen) - [Do Not Deploy Amazon Connect Health When:](#donotdeployamazonconnecthealthwhen) - [Alternative Platforms Worth Evaluating](#alternativeplatformsworthevaluating) - [Bottom Line](#bottomline) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) The U.S. healthcare industry will lose an estimated $262 billion to administrative inefficiency in 2025, according to McKinsey. The culprit isn't missing technology–most hospitals run Epic or Cerner. The problem sits at the front end: patient access, scheduling, billing communication, and prior authorization workflows still operate on infrastructure built for a pre-digital era. Amazon Connect Health positions itself as the answer. But before your organization commits capital to yet another cloud migration, you need clarity on what this platform actually is, what it costs, and whether the March 2026 timeline represents a product launch or strategic repackaging. This is not a tutorial. This is a decision framework for RCM Directors, CFOs, and CTOs evaluating whether Amazon's HIPAA-eligible contact center deserves a line item in your 2026 IT budget. ## Three Names, Three Different Products AWS uses the word "Health" across multiple offerings, creating procurement confusion that wastes executive time. Here's the taxonomy: | Infrastructure monitoring (uptime, maintenance alerts) | DevOps/Cloud Engineers | | Cloud contact center platform (industry-agnostic) | Any sector requiring call center operations | ‍ Critical clarification: Amazon Connect Health is not a standalone product. It is a configuration layer and integration framework built atop the base Amazon Connect platform, optimized for healthcare compliance and clinical workflows. AWS has announced this healthcare-specific packaging for broader availability in March 2026, but as of this writing, official AWS documentation does not confirm whether this represents a net-new product launch, a rebranding of existing capabilities, or formalized packaging of professional services already deployed in pilot programs. Translation for procurement: Do not budget for "Amazon Connect Health" as a separate SKU. Budget for Amazon Connect with healthcare-specific implementation services, EHR integrations, and compliance configuration. ## What Amazon Connect Health Actually Does–And Doesn't Forget the feature list. Here's what Amazon Connect Health executes in production environments, ranked by deployment maturity: ### ✅ Production-Ready Use Cases 1. Patient Scheduling & Appointment Reminders Traditional model: Live agent manually verifies eligibility, checks provider availability, and logs appointment. Average Handle Time (AHT): 8–12 minutes. Amazon Connect Health model: AI-powered IVR conducts eligibility verification via real-time payer API, checks Epic/Cerner availability, and delivers confirmation via SMS. Screen pop presents full patient context to agent only when exception handling is required. Expected AHT reduction: 30–40%, based on benchmarks from HIMSS Analytics and Optum consulting reports (not AWS-published case studies–those remain scarce). 2. Prior Authorization Status Inquiries The U.S. healthcare system spends $13 billion annually on prior authorization administrative overhead, per the CAQH Index. Amazon Connect Health automates status checks by querying payer portals and EHR systems, then routes complex cases to human agents only when denial or clinical review is flagged. Deployment note: This requires middleware integration between Amazon Connect, your EHR's API (Epic Interconnect or Cerner CareAware), and payer portals. Budget $50,000–$200,000+ for professional services depending on how many payers and specialties you operate across. 3. Patient Payment & Billing Communication No Surprises Act compliance and CMS price transparency mandates have turned patient financial communication from administrative nuisance into regulatory imperative. Amazon Connect Health handles: This use case is production-ready but requires integration with your revenue cycle management system (Epic Resolute, Cerner RevElite, Waystar, Change Healthcare). 4. Eligibility Verification (Lab & Specialty Services) Routine insurance status inquiries for laboratory administrators and specialty schedulers. Works well for high-volume, low-complexity transactions. ### ⚠️ Early-Stage / Integration-Intensive Use Cases 5. Post-Discharge Follow-Up Use case: Automated calls to discharged patients, screening for complications, escalating to nurse line when red flags appear. Impact: Reducing 30-day readmissions directly affects CMS Hospital Readmissions Reduction Program penalties (average penalty: $563,000 per hospital in 2024, per Kaiser Family Foundation data). Risk: This workflow touches clinical decision-making. It requires physician oversight protocols, documented escalation pathways, and liability review before deployment. Do not implement this as an IT project without clinical governance. ### ❌ What Amazon Connect Health Does Not Do Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## HIPAA Eligible ≠ HIPAA Compliant Amazon Connect appears on AWS's official HIPAA Eligible Services Reference list. AWS will sign a Business Associate Agreement (BAA) covering the platform. This does not mean your deployment is automatically compliant. ### The Shared Responsibility Model AWS secures the infrastructure. You secure the data, the workflows, and the access controls. AWS responsibility: Your responsibility: ### Critical Question Without Public Answer Does the AWS BAA automatically cover all AI subservices used by Amazon Connect Health workflows? AWS documentation does not explicitly confirm whether enabling Amazon Lex for conversational IVR or Amazon Comprehend Medical for sentiment analysis triggers separate BAA requirements. This is a question for your AWS Solutions Architect before you architect call flows involving AI components. ### The Financial Risk The average cost of a healthcare data breach in 2023 was $10.93 million, per IBM Security's Cost of a Data Breach Report. Projections for 2025 exceed $11 million. HIPAA-eligible infrastructure does not insulate you from penalties if your implementation fails audit. If your organization lacks internal AWS expertise, budget for ongoing compliance advisory services. Enterprise Support tier starts at $15,000/month or 10% of AWS spend, whichever is higher. ## What It Actually Costs AWS publishes per-use pricing for Amazon Connect. What it does not publish: all-in total cost of ownership for healthcare deployments. ### Publicly Available Pricing (as of May 2026) Inbound voice | ~$0.018/minute | Outbound voice | ~$0.013/minute + telecom carrier costs | Chat/messaging | ~$0.004/message | Contact Lens (AI analytics) | ~$0.015/minute (real-time) or ~$0.008/minute (post-call) | Amazon Lex (conversational AI) | ~$0.004/text request; ~$0.015/speech request | Amazon Transcribe Medical | ~$0.025/minute | ‍ ### Hidden Costs CFOs Must Budget For ### Benchmark Comparison: Pay-Per-Use vs. Per-Seat CCaaS Small practice | 200,000 calls | $20,000–$40,000/month | $200,000–$500,000+/year | ‍ Critical insight for CFOs: Amazon Connect's pay-per-use model benefits organizations with variable call volume (seasonal flu surges, pandemic spikes, post-discharge follow-up campaigns). For stable, high-volume contact centers, traditional per-seat pricing may offer more predictable budgeting. ### The TCO Reality Check AWS does not publish all-in TCO data for healthcare deployments post-implementation. Professional services, EHR integration, and ongoing maintenance can add $50,000–$200,000+ to Year 1 costs beyond the per-minute AWS billing. Before evaluating vendor proposals, model three scenarios: If your AWS Solutions Architect cannot provide itemized estimates for all three, the proposal is incomplete. ## When Amazon Connect Health Makes Sense–And When It Doesn't ### Deploy Amazon Connect Health When: ### Do Not Deploy Amazon Connect Health When: ### Alternative Platforms Worth Evaluating This is not a competitive analysis, but CFOs evaluating Amazon Connect Health should also examine: Do not sole-source Amazon Connect Health without competitive bids unless your AWS dependency is already strategic. ## Bottom Line Healthcare organizations do not lose revenue because of inadequate EHR systems. They lose revenue because the front-end infrastructure–scheduling, eligibility verification, billing communication, prior authorization follow-up–still operates like it's 2010. Amazon Connect Health addresses that structural problem, but only for organizations with the technical capacity, call volume, and AWS alignment to justify custom deployment. This article was written for RCM Directors who need to defend budget proposals, CFOs evaluating CCaaS ROI, and CTOs deciding whether AWS healthcare infrastructure is a strategic bet or vendor lock-in risk. Amazon Connect Health is not the answer to every RCM revenue leak. But for organizations losing margin on the first line of patient contact, it deserves rigorous financial analysis–not just an IT pilot. At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let's talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byKrzysztof Szwed Head of Delivery at Flobotics. [More from Krzysztof](https://www.flobotics.io/our-editorial-team#szwed) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ AIHealthcareRCM ### AWS Connect Health: RCM Salvation or Infrastructure Play? AWS Connect Health: is Amazon's new healthcare platform an RCM solution or just an infrastructure play? We break down what it actually delivers. Bart TeodorczukMay 18, 2026 ](https://www.flobotics.io/blog/aws-connect-health)[ AI ### The Hottest Agentic AI Examples and Use Cases in 2026 Agentic AI examples and use cases: how AI agents are automating healthcare RCM, legal drafting, and retail inventory in 2026. Jędrzej SzymulaOctober 02, 2025 ](https://www.flobotics.io/blog/hottest-agentic-ai-examples-and-use-cases)[ RCMAIHealthcare ### Agentic AI in Healthcare: From Hype to Real-World Impact Agentic AI in healthcare: how it differs from generative AI like ChatGPT and where it's already driving real clinical impact. Jędrzej SzymulaSeptember 22, 2025 ](https://www.flobotics.io/blog/agentic-ai-in-healthcare) [All articles →](https://www.flobotics.io/blog) --- # Claude for Healthcare: Technical Integration Canonical: https://www.flobotics.io/blog/claude-for-healthcare-technicals Author: Jacek Żukowski Published: 2026-05-29 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Claude for Healthcare: Technical Integration [AI](https://www.flobotics.io/blog?category=ai)[Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Claude for Healthcare: Technical Integration [Jacek ŻukowskiAn RPA Consultant and Business Analyst](https://www.flobotics.io/our-editorial-team#zukowski) Published May 29, 2026Updated September 1, 2026 On this page - [Claude for Healthcare: The $12.5M Question Nobody's Asking Before Signing the BAA](#claudeforhealthcarethed125mquestionnobodysaskingbeforesigningthebaa) - [Compliance Infrastructure: What the BAA Doesn't Cover](#complianceinfrastructurewhatthebaadoesntcover) - [The Business Associate Agreement Is the Starting Line, Not the Finish](#thebusinessassociateagreementisthestartinglinenotthefinish) - [Zero Data Retention ≠ Zero Audit Responsibility](#zerodataretentionzeroauditresponsibility) - [DLP Effectiveness: The Probabilistic Control Nobody Tests](#dlpeffectivenesstheprobabilisticcontrolnobodytests) - [Network Architecture: PrivateLink Is a Choice, Not a Default](#networkarchitectureprivatelinkisachoicenotadefault) - [Model Quality and Integration: Where Hallucinations Become Financial Losses](#modelqualityandintegrationwherehallucinationsbecomefinanciallosses) - [RAG Governance: The Knowledge Base Is a Living Liability](#raggovernancetheknowledgebaseisalivingliability) - [EHR Middleware: The Hidden Business Associate](#ehrmiddlewarethehiddenbusinessassociate) - [Hallucinations in RCM: The 3-5% Denial Rate Catastrophe](#hallucinationsinrcmthe35denialratecatastrophe) - [Human-in-the-Loop: Why Documentation Matters More Than Review](#humanintheloopwhydocumentationmattersmorethanreview) - [Approval Fatigue Is a Known Human Factors Risk](#approvalfatigueisaknownhumanfactorsrisk) - [Policy Limits: Maximum Review Volumes Per Role](#policylimitsmaximumreviewvolumesperrole) - [LLMOps and Financial Sustainability: Budget Beyond API Costs](#llmopsandfinancialsustainabilitythe25overheadnobodybudgets) - [Model Drift Requires Version Pinning and Quarterly Audits](#modeldriftrequiresversionpinningandquarterlyaudits) - [Model Selection: The $42,600 Monthly Decision](#modelselectionthed42600monthlydecision) - [Context Window Optimization: The 10x Cost Variable](#contextwindowoptimizationthe10xcostvariable) - [LLMOps Operational Overhead: Plan for Ongoing Work](#llmopsoperationaloverheadthe25lineitem) - [Strategic Close: Due Diligence Is Documentation, Not Intent](#strategiccloseduediligenceisdocumentationnotintent) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Claude for Healthcare: The $12.5M Question Nobody's Asking Before Signing the BAA The average healthcare data breach will cost $12.5 million by 2026–a 15% year-over-year increase from 2023, according to projections from IBM's Ponemon Institute published in [Becker's Hospital Review](https://www.beckershospitalreview.com/cybersecurity/average-cost-of-a-data-breach-hits-record-high.html). For organizations deploying large language models like Claude in revenue cycle management or clinical documentation, that figure represents more than a cautionary statistic. It's the liability floor for implementations that skip hard questions about compliance architecture, model governance, and total cost of ownership. The RCM directors, CFOs, and CISOs signing contracts with Anthropic face a due diligence gap: most organizations treat LLM deployment as a technology project when it's fundamentally an infrastructure decision with regulatory exposure. Here are the ten questions that separate controlled deployments from budget overruns and [OCR penalty tiers](https://www.hhs.gov/hipaa/for-professionals/compliance-enforcement/audit/index.html) ranging from $100,000 to $1.9 million annually per violation category. ## Compliance Infrastructure: What the BAA Doesn't Cover ### The Business Associate Agreement Is the Starting Line, Not the Finish Enterprise-tier agreements with Anthropic include HIPAA-compliant Business Associate Agreements, but the [HHS Office for Civil Rights guidance on cloud computing](https://www.hhs.gov/hipaa/for-professionals/special-topics/cloud-computing/index.html) makes explicit: the BAA defines liability split after a breach occurs. It does not eliminate the covered entity's obligations for audit logs, breach notification procedures, and security documentation. Organizations must maintain: The compliance question isn't "Does Anthropic offer a BAA?" It's "Who in our organization owns the audit trail when OCR requests it?" ### Zero Data Retention ≠ Zero Audit Responsibility Anthropic's enterprise tier includes opt-out from model training on customer data–the industry's "zero data retention" standard. But the [HIPAA Security Rule](https://www.hhs.gov/hipaa/for-professionals/security/index.html) §164.312(b) requires covered entities to maintain retrievable exact copies of PHI for six years. Zero retention by the vendor doesn't exempt the organization from logging every clinical decision influenced by AI. ### DLP Effectiveness: The Probabilistic Control Nobody Tests Data Loss Prevention systems masking PHI before API transmission rely on pattern recognition to identify [18 identifiers](https://www.hhs.gov/hipaa/for-professionals/privacy/special-topics/de-identification/index.html) per HIPAA's Safe Harbor Method (§164.514(b)). Detection rates vary by implementation–commonly 95-98% in controlled tests–but most organizations never document their DLP's actual performance against a validated test dataset. The operational question: Does your CISO have a quarterly audit showing DLP detection rates for names, MRNs, and IP addresses in free-text clinical notes? If the answer is no, you're deploying probabilistic protection without knowing its failure rate. ### Network Architecture: PrivateLink Is a Choice, Not a Default Direct integration with [Anthropic's API](https://www.anthropic.com/api) routes traffic over public internet with TLS 1.2+ encryption–HIPAA-eligible but not isolated. Organizations deploying Claude via [AWS Bedrock](https://aws.amazon.com/bedrock/) can configure VPC PrivateLink, eliminating public internet exposure entirely. Cost consideration: PrivateLink endpoint fees run approximately $0.01/GB processed plus $7.50/month per availability zone. For a mid-sized hospital processing 100GB monthly, that's $82.50/month in infrastructure overhead–against the mitigation value of eliminating one network attack surface in a breach scenario costing millions. The CFO's question: What's the cost delta between direct API and PrivateLink against your organization's risk tolerance for data in transit? ## Model Quality and Integration: Where Hallucinations Become Financial Losses ### RAG Governance: The Knowledge Base Is a Living Liability Retrieval-Augmented Generation architectures source Claude's responses from authorized databases–PubMed for clinical evidence, internal SOPs for organizational protocols. But knowledge bases require version control. When clinical guidelines update and the RAG index doesn't, the model generates recommendations from outdated procedures. Organizations deploying RAG must designate: Real scenario: A hospital updates its antibiotic stewardship protocol, but the RAG index reflects last quarter's guidelines. Claude recommends a discontinued first-line therapy. The pharmacist catches it–but approval fatigue means the next 200 recommendations go through unchecked. ### EHR Middleware: The Hidden Business Associate Typical integration architecture flows: Epic/Cerner → FHIR API → middleware layer → DLP → Claude API → response pipeline. Every node processing PHI requires its own Business Associate Agreement under [ONC's FHIR R4 interoperability standard](https://www.healthit.gov/topic/standards-technology/standards/fhir-fact-sheets). If your middleware vendor isn't covered in the primary BAA with Anthropic, you have a compliance gap. The operational audit: map every system touching PHI in the request/response cycle and verify each has executed documentation. ### Hallucinations in RCM: The 3-5% Denial Rate Catastrophe Poorly governed AI implementations in revenue cycle management increase claim denial rates by 3-5%, translating to $1-3 million annual losses for mid-sized hospitals, per [Health Affairs analysis of pilot deployments](https://www.healthaffairs.org/do/10.1377/forefront.20240614.638549/). The mechanism: hallucinated ICD-10 codes that don't match documented diagnoses, CPT codes for procedures never performed, or invented drug interaction warnings triggering unnecessary prior authorizations. Mitigation mechanisms–each a line item in your TCO model: One hallucinated code triggering a fraud investigation under the [False Claims Act](https://www.justice.gov/civil/false-claims-act) exposes organizations to treble damages plus penalties of $13,946-$27,894 per claim. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Human-in-the-Loop: Why Documentation Matters More Than Review ### Approval Fatigue Is a Known Human Factors Risk [AHRQ’s review of alert fatigue](https://psnet.ahrq.gov/primer/alert-fatigue) describes how frequent safety alerts can desensitize clinicians. For AI-assisted workflows, treat reviewer workload as a design consideration and document how outputs are reviewed. Systems must log: This audit trail becomes discoverable evidence in adverse event investigations. If a clinician rubber-stamps 200 medication summaries in 90 minutes, can you demonstrate meaningful review occurred? ### Policy Limits: Maximum Review Volumes Per Role Organizations should establish evidence-based thresholds–e.g., no single reviewer approves more than 50 high-stakes outputs (medication orders, diagnostic suggestions) per shift. Beyond that, rotate to a second clinician or flag for supervisory review. ## LLMOps and Financial Sustainability: Budget Beyond API Costs ### Model Drift Requires Version Pinning and Quarterly Audits Anthropic updates models continuously. Without version pinning, an organization's Claude deployment can exhibit different behavior month-to-month as the underlying model evolves. [NIST's AI Risk Management Framework 1.0](https://www.nist.gov/itl/ai-risk-management-framework) specifies governance requirements: Operational implementation: API parameter: "model": "claude-3-5-sonnet-20241022" The date in the model name locks the specific version. Before upgrading, test the new version against a golden dataset of 100-500 validated queries spanning your use cases. Engage a clinical expert panel quarterly to audit output quality–this is not a technical task; it's a clinical governance requirement. ### Model Selection: The $42,600 Monthly Decision Organizations defaulting to Claude 3 Opus for all tasks–because "it's the most capable"–incur massive unnecessary costs. Use-case-appropriate model selection is a CFO decision: Fig. 01 · Model selection Price per 1M tokens Match the model to the task Use case | Model | Input | Output | Why | ICD-10 code extraction | Claude 3.5 Haiku | $0.80 | $4.00 | High-volume structured task | Prior authorization letters | Claude 3.5 Sonnet | $3.00 | $15.00 | Balance of quality and cost | Complex case synthesis | Claude 3 Opus | $15.00 | $75.00 | Maximum reasoning for rare or complex cases | Real calculation at 10,000 queries daily (5K tokens input, 1K output): The difference: $42,600 monthly. Can your RCM director justify Opus for extracting structured data from referral notes? Verify current pricing at [Anthropic's official rate card](https://www.anthropic.com/pricing). ### Context Window Optimization: The 10x Cost Variable Naive implementations send full patient histories with every query–30,000-50,000 tokens of EHR data to generate a 200-token prior auth summary. Optimization techniques reduce effective token consumption by 90%: Cost impact at 10,000 monthly queries: ### LLMOps Operational Overhead: Plan for Ongoing Work Budget for ongoing model evaluation, monitoring and governance alongside API and infrastructure costs. Estimate the staff time required for your own deployment; a fixed percentage is not a substitute for that estimate. For example, $200K in annual API costs plus $50K for operational work would mean a $250K annual budget. These figures illustrate the calculation; they are not an industry benchmark. ## Strategic Close: Due Diligence Is Documentation, Not Intent These ten questions constitute the pre-signature checklist for any organization deploying Claude in HIPAA-regulated environments. CFOs need reproducible cost models. CISOs need compliance gaps identified in writing. RCM directors need documented risk mitigation for denial rate exposure. Organizations that answer these questions with "we'll figure it out post-deployment" are not deferring technical decisions–they're accepting unmodeled legal liability and unbudgeted operational costs. Claude's capabilities in clinical documentation, RCM automation, and decision support are substantiated. But potential realizes only in organizations that asked the hard questions before the BAA signature dried. Signing the Business Associate Agreement is not the end of due diligence. It is the beginning. At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. Written byJacek Żukowski An RPA Consultant and Business Analyst. [More from Jacek](https://www.flobotics.io/our-editorial-team#zukowski) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareAI ### Claude for Healthcare Overview | 2026 Claude for Healthcare: Anthropic's 2026 toolkit for US medical data, with HIPAA compliance details and case studies from Banner Health and Novartis. Jędrzej SzymulaMay 06, 2026 ](https://www.flobotics.io/blog/claude-for-healthcare)[ AIRCMHealthcare ### Claude for Healthcare from Anthropic Claude for Healthcare from Anthropic: what's still unclear on data storage, routing, and third-party access before you roll it out to staff. Dominik PutMay 26, 2026 ](https://www.flobotics.io/blog/anthropic-annoucement-claude-for-healthcare)[ RCMRPAAI ### AI vs. RPA vs. ML in Healthcare RCM: A Deep Dive AI vs. RPA vs. ML in healthcare RCM: how each technology improves efficiency, accuracy, and compliance, and which to adopt first. Krzysztof SzwedFebruary 22, 2025 ](https://www.flobotics.io/blog/ai-rpa-ml-rcm) [All articles →](https://www.flobotics.io/blog) --- # Value-Based Care (VBC): What It Means for RCM Canonical: https://www.flobotics.io/blog/value-based-care-vbc-explanation Author: Jędrzej Szymula Published: 2026-05-28 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Value-Based Care (VBC): What It Means for RCM [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Value-Based Care (VBC): What It Means for RCM [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published May 28, 2026Updated September 1, 2026 On this page - [What Is Value-Based Care (VBC)?](#what-is-value-based-care-vbc) - [How VBC Changes RCM Requirements](#how-vbc-changes-rcm-requirements) - [VBC and the RCM Technology Stack](#vbc-and-the-rcm-technology-stack) - [Automating VBC Performance Management](#automating-vbc-performance-management) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Is Value-Based Care (VBC)? Value-Based Care (VBC) is a healthcare reimbursement model that ties provider payment to patient health outcomes, care quality, cost efficiency, and patient experience — rather than to the volume of services delivered under traditional fee-for-service arrangements. Under VBC, providers are rewarded for keeping patients healthy, managing chronic conditions effectively, reducing unnecessary utilization, and achieving measurable quality metrics. Poor outcomes, preventable readmissions, and inefficient care coordination reduce — rather than increase — reimbursement. VBC encompasses a spectrum of arrangements: shared savings programs (ACO models), bundled payments (single payment for an episode of care), pay-for-performance incentives layered on fee-for-service, and full capitation (fixed per-member-per-month payments regardless of utilization). The unifying principle is that reimbursement reflects value delivered rather than activity performed. ## How VBC Changes RCM Requirements The shift from fee-for-service to VBC fundamentally changes what RCM teams must track, document, report, and optimize: - Quality measure reporting: VBC contracts require systematic collection, calculation, and submission of quality metrics (HEDIS, MIPS, CMS star ratings) that have no equivalent in fee-for-service billing - Risk adjustment accuracy: Capitated and risk-adjusted VBC payments depend on accurate diagnosis coding reflecting the full chronic condition burden of the patient population — making [Clinical Documentation Integrity (CDI)](https://www.flobotics.io/blog/clinical-documentation-integrity-cdi-explanation) a financial-grade requirement, not just a clinical one - Population health data management: VBC requires tracking patient outcomes, utilization patterns, and care gaps across large patient populations — data infrastructure that fee-for-service billing does not require - Cost performance tracking: Shared savings and bundled payment programs require tracking total cost of care across the care episode, including services delivered by other providers Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## VBC and the RCM Technology Stack VBC performance is data-dependent in ways that fee-for-service is not. Quality measure calculations require complete, timely, and accurate clinical data. Risk scores require complete diagnosis capture. Cost performance requires attribution of care episodes across providers. None of these are possible without robust data infrastructure, analytics capabilities, and tight integration between clinical and financial systems. For RCM teams, VBC means the traditional billing focus — submit claims, collect payment — is no longer sufficient. The revenue optimization question becomes: are we documenting and reporting everything that drives our risk scores and quality performance? This is where [IDP](https://www.flobotics.io/blog/intelligent-document-processing-idp-explanation), [predictive analytics](https://www.flobotics.io/blog/predictive-analytics-explanation), and [RCM automation](https://www.flobotics.io/rcm-automation) become strategic infrastructure investments rather than operational cost reduction tools. ## Automating VBC Performance Management Managing VBC contract performance at scale requires automation across multiple dimensions: automated quality gap identification (patients overdue for preventive measures), automated risk adjustment audit (ensuring all chronic conditions are documented and coded), automated cost attribution (tracking care episode costs against bundles or shared savings benchmarks in real time), and automated quality measure submission to payers and registries. As VBC penetration increases — CMS has committed to having 100% of Medicare beneficiaries in accountable care relationships — RCM automation programs must evolve beyond transactional billing automation to encompass the population health data management and outcome reporting that VBC requires. [Talk to us](https://www.flobotics.io/contact) about VBC-ready automation architecture for your organization. Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### Net Promoter Score (NPS) in Healthcare Net Promoter Score (NPS) in healthcare ties patient loyalty to billing experience - and increasingly to Value-Based Care reimbursement. Bart TeodorczukMay 21, 2026 ](https://www.flobotics.io/blog/nps-net-promoter-score-explanation)[ HealthcareRCM ### Healthcare Reimbursements: How Payment Rates Are Set Healthcare reimbursement guide: how payment rates are set and where automation closes the gap between allowed and collected amounts. Karl MielnickiMay 01, 2026 ](https://www.flobotics.io/blog/reimbursements-explanation)[ HealthcareRCM ### Net Collection Rate (NCR): Formula and Benchmarks Net Collection Rate (NCR) explained: the RCM metric measuring collectible revenue actually captured. Best practice is 95-99% - below that, revenue leaks. Bart TeodorczukJune 04, 2026 ](https://www.flobotics.io/blog/net-collection-rate-ncr) [All articles →](https://www.flobotics.io/blog) --- # Turnaround Time (TAT) in Healthcare RCM: Benchmarks Canonical: https://www.flobotics.io/blog/turnaround-time-tat-explanation Author: Karl Mielnicki Published: 2026-05-26 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Turnaround Time (TAT) in Healthcare RCM: Benchmarks CTO Notes [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Turnaround Time (TAT) in Healthcare RCM: Benchmarks [Karl MielnickiCTO & Co-Founder of Flobotics](https://www.flobotics.io/our-editorial-team#mielnicki) Published May 26, 2026Updated September 1, 2026 On this page - [What Is Turnaround Time (TAT) in Healthcare RCM?](#what-is-turnaround-time-tat-in-healthcare-rcm) - [Why TAT Management Is a Financial Priority](#why-tat-management-is-a-financial-priority) - [Industry TAT Benchmarks](#industry-tat-benchmarks) - [How Automation Compresses RCM TAT](#how-automation-compresses-rcm-tat) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Is Turnaround Time (TAT) in Healthcare RCM? Turnaround Time (TAT) is the total elapsed time required to complete a defined process from initiation to completion. In Revenue Cycle Management, TAT is measured across multiple distinct workflow segments, each with its own benchmark and operational significance: - Prior authorization TAT: Time from auth request submission to payer approval or denial response - Claim submission TAT: Time from date of service to date of claim submission to payer - Denial resolution TAT: Time from denial receipt to corrected submission or formal appeal filing - Payment posting TAT: Time from payment receipt (ERA/EOB) to posting in the practice management system - Patient statement TAT: Time from patient balance determination to statement generation and delivery Together, these TAT measurements determine total revenue cycle cycle time — the span between delivering care and collecting payment — which directly sets [Days in Accounts Receivable](https://www.flobotics.io/blog/days-in-accounts-receivable-dar-explanation). ## Why TAT Management Is a Financial Priority Every hour of unnecessary delay has a cost. Delayed prior auth processing pushes procedures further into the future. Slow claim submission extends the payment timeline by the same number of days as the delay. Denial resolution TAT running 30 days instead of 5 means denied revenue sits at risk for 25 extra days — increasing write-off probability and creating appeal timeline complexity. TAT is also a compliance concern: most payers have timely filing limits (90–365 days from service, depending on payer) within which claims must be submitted. Poor submission TAT approaching these limits creates write-off risk on otherwise collectable revenue. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Industry TAT Benchmarks - Claim submission: Same-day or next-day for services with complete documentation; never more than 3 business days from service to submission - Prior auth response: Payers increasingly required to respond within 72 hours (urgent) or 7–14 days (standard) by state law - Denial resolution: High-value denials within 5 business days; all denials within 15 days to maintain appeal viability - Payment posting: ERA files posted same-day; paper EOBs within 24–48 hours of receipt ## How Automation Compresses RCM TAT TAT reduction is one of the most direct and measurable benefits of [RCM automation](https://www.flobotics.io/rcm-automation). Automated workflows eliminate queuing time, handoff delays, and batch-processing cycles that inflate TAT in manual operations: - Automated [prior authorization](https://www.flobotics.io/agents/prior-authorization-automation) workflows submit requests immediately upon scheduling confirmation - Automated claim generation from EHR data enables same-day submission for encounters with clean documentation - [Denial management automation](https://www.flobotics.io/agents/denials-management-automation) routes denied claims to the correct work queue within hours of denial receipt - Automated [payment posting](https://www.flobotics.io/blog/payment-posting-cash-posting-explanation) from ERA feeds processes remittances the same day they arrive Organizations automating their RCM workflows report TAT improvements of 60–80% across all segments. [See the results in our case studies.](https://www.flobotics.io/case-studies) Written byKarl Mielnicki CTO & Co-Founder of Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### Claim Turnaround Time (CTT): Benchmarks and Root Causes Claim Turnaround Time (CTT), explained: why 14-21 days is best-in-class and 45+ days signals a billing cycle problem. Krzysztof SzwedMay 04, 2026 ](https://www.flobotics.io/blog/claim-turnaround-time-ctt-explanation)[ HealthcareRCM ### Cost to Collect (CTC): Definition and Benchmarks Cost to Collect (CTC) benchmarks sit at 3-5% of net revenue - a 1% cut on $10M in collections frees up $100,000 in cash. Karl MielnickiMay 18, 2026 ](https://www.flobotics.io/blog/cost-to-collect-ctc-explanation)[ HealthcareRCM ### Days in Accounts Receivable (DAR): Formula and Benchmarks Days in Accounts Receivable (DAR) guide: why 30-35 days is best practice and anything above 50 signals collection trouble. Krzysztof SzwedMay 21, 2026 ](https://www.flobotics.io/blog/days-in-accounts-receivable-dar-explanation) [All articles →](https://www.flobotics.io/blog) --- # Claude for Healthcare from Anthropic Canonical: https://www.flobotics.io/blog/anthropic-annoucement-claude-for-healthcare Author: Dominik Put Published: 2026-05-26 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Claude for Healthcare from Anthropic [AI](https://www.flobotics.io/blog?category=ai)[Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Claude for Healthcare from Anthropic [Dominik PutUiPath-certified RPA developer with extensive experience in automating healthcare, customer service, and HR processes. His keen interest lies in Document Understanding and OCR technologies.](https://www.flobotics.io/our-editorial-team#put) Published May 26, 2026Updated September 1, 2026 On this page - [Claude for Healthcare from Anthropic](#claudeforhealthcarewhatitactuallydoesandwhatyoustillneedtohandleyourself) - [What is "Claude for Healthcare"?](#whatclaudeforhealthcareactuallymeans) - [Consumer vs. Enterprise](#consumervsenterpriseacriticaldistinction) - [Who This Is For](#whothisisfor) - [Claude fot Healthcare: HIPAA Compliance](#hipaacompliancewhatthebaacoversandwhatitdoesnt) - [What the BAA Provides?](#whatthebaaprovides) - [What the BAA Does Not Provide](#whatthebaadoesnotprovide) - [What Your Organization Must Still Do](#whatyourorganizationmuststilldo) - [Critical Warning](#criticalwarning) - [Confidentiality: What Happens to Your Data](#confidentialitywhathappenstoyourdata) - [Consumer Model (claude.ai)](#consumermodelclaudeai) - [API and Enterprise Model (under BAA)](#apiandenterprisemodelunderbaa) - [What Remains Unclear](#whatremainsunclear) - [How to Use Claude: Role-Based Use Cases and Required Oversight](#howtouseclauderolebasedusecasesandrequiredoversight) - [Where Claude Performs Well](#whereclaudeperformswell) - [Where Claude Should Not Be Used](#whereclaudeshouldnotbeused) - [Realistic Outcomes: What the Data Shows](#realisticoutcomeswhatthedatashows) - [Competitive Context](#competitivecontext) - [Which AI Tool Is Best for Healthcare?](#whichaitoolisbestforhealthcare) - [Comparative Landscape](#comparativelandscape) - [Decision Criteria](#decisioncriteria) - [Where Claude Has an Edge](#whereclaudehasanedge) - [Where Claude May Not Be Optimal](#whereclaudemaynotbeoptimal) - [Pricing and Access: What It Actually Costs](#pricingandaccesswhatitactuallycosts) - [Public Pricing (as of April 2025)](#publicpricingasofapril2025) - [Enterprise Pricing (Not Publicly Disclosed)](#enterprisepricingnotpubliclydisclosed) - [Access Pathways](#accesspathways) - [Should Your Organization Deploy Claude?](#shouldyourorganizationdeployclaude) - [Deploy Claude If:](#deployclaudeif) - [Do Not Deploy Claude If:](#donotdeployclaudeif) - [Realistic Expectation Setting](#realisticexpectationsetting) - [Final Assessment](#finalassessment) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Claude for Healthcare from Anthropic Anthropic's Claude has entered healthcare with a Business Associate Agreement and enterprise-grade promises. But strip away the launch announcements, and what remains is a more complex picture: a capable language model that can accelerate certain workflows–provided your organization has already built the compliance infrastructure, IT integrations, and oversight protocols to use it safely. This isn't a sales pitch. It's a technical breakdown of what Claude for Healthcare is, how HIPAA compliance actually works in practice, where the tool adds measurable value, and where gaps in public documentation leave critical questions unanswered. If you're evaluating whether to pilot Claude in your health system, this is what you need to know before the vendor call. Scope: This guide covers Claude's enterprise offering for U.S. healthcare organizations operating under HIPAA. It does not address consumer use cases, international regulatory frameworks, or speculative future capabilities. ## What is "Claude for Healthcare"? Claude is a large language model developed by Anthropic, designed for conversational reasoning, document summarization, and task completion based on natural language instructions. "Claude for Healthcare" is not a separate clinical model or medically fine-tuned variant. According to Anthropic's public documentation as of April 2025, the primary distinction is contractual, not technical: enterprise customers can execute a HIPAA Business Associate Agreement (BAA) when using Claude via API. This matters because it clarifies scope. You are not licensing a specialized diagnostic system or a model trained on proprietary clinical datasets. You are accessing Anthropic's standard Claude models (currently Claude 3.5 Sonnet and Claude 3 Opus) under terms that address certain–but not all–HIPAA obligations. ### Consumer vs. Enterprise If your staff are logging into claude.ai to summarize patient charts or draft clinical notes, you are operating in regulatory gray area at best. Enterprise API access under BAA is non-negotiable for HIPAA-covered workflows. ### Who This Is For Claude's architecture suits specific roles and tasks: Claude does not diagnose. Claude does not replace clinical judgment. Any use case involving autonomous patient care decisions is out of scope. ## Claude fot Healthcare: HIPAA Compliance This is the most consequential section of the guide. Misunderstanding the scope of a Business Associate Agreement has compliance implications that survive vendor renewals and IT audits. ### What the BAA Provides? When Anthropic executes a BAA with your organization, it contractually commits to: This addresses vendor-side obligations under HIPAA's Business Associate Rule. Anthropic becomes legally accountable for how it handles data you send through the API under the scope of the agreement. ### What the BAA Does Not Provide The BAA does not: ### What Your Organization Must Still Do HIPAA compliance is a shared responsibility model. Even with a BAA in place, your organization must independently implement: These are non-delegable obligations under the HIPAA Security Rule. The existence of a BAA does not eliminate the covered entity's compliance workload–it defines how the vendor will handle its portion. ### Critical Warning Staff using consumer Claude.ai (claude.ai) to input patient data, even summarized or paraphrased, are operating outside of HIPAA-compliant infrastructure. Consumer accounts are not covered under a BAA. This includes physicians using personal accounts to draft notes, nurses summarizing patient histories for handoff, or administrative staff processing billing inquiries. If your organization has not restricted access to claude.ai at the network level and established clear policy prohibiting PHI input via consumer channels, you have a compliance gap. ## Confidentiality: What Happens to Your Data Data retention and usage policies differ sharply between consumer and enterprise contexts. Here is what Anthropic's documentation discloses as of April 2025–and where critical information remains non-public. ### Consumer Model (claude.ai) According to Anthropic's terms of service for consumer accounts: Implication for healthcare: Consumer Claude is unsuitable for any workflow involving PHI, regardless of summarization or paraphrasing. Training on user data and indefinite retention are incompatible with HIPAA. ### API and Enterprise Model (under BAA) For enterprise customers operating under a BAA: ### What Remains Unclear Key questions that Anthropic's public documentation does not fully address: Practical recommendation: Before implementation, request explicit written confirmation from Anthropic on data retention timelines, regional routing, and subprocessor arrangements. Standard BAA templates may not address these specifics. If your organization's risk tolerance requires zero-persistence guarantees, verify that Anthropic's architecture supports that–do not assume. ## How to Use Claude: Role-Based Use Cases and Required Oversight Claude excels at conversational reasoning, summarization of long documents, and instruction-following for repetitive tasks. It does not replace specialized clinical decision support systems, billing software, or EHR workflows. Below is a realistic breakdown of where Claude adds value–and where it should not be deployed. Fig. 01 · Use cases Risk and oversight Where Claude fits, and the oversight each task needs Task | Risk level | Required oversight | Summarizing discharge instructions in patient-friendly language | High | A clinician reviews the output before it reaches the patient | Suggesting ICD-10/CPT codes from clinical documentation | Medium | A coder validates every suggestion; Claude does not submit claims on its own | Drafting justification letters for insurance appeals | Medium | The provider validates clinical accuracy; it cuts drafting time, not decision-making | Writing routine correspondence (appointment reminders, policy summaries) | Low | No PHI in prompts unless the API is covered by a BAA; a person approves before sending | Analyzing de-identified RCM trend data for board reports | Low | De-identify data before input; Claude does not access live EHR data | ### Where Claude Performs Well ### Where Claude Should Not Be Used ❌ Autonomous diagnostic decisions: Claude is not a clinical decision support system. It does not have access to real-time patient data, lab integrations, or validated diagnostic algorithms. ❌ Patient-facing chatbots without supervision: Deploying Claude as a patient-facing interface (e.g., symptom checker, treatment advisor) without clinician oversight introduces liability and accuracy risks. ❌ Replacing human judgment in high-stakes scenarios: Prior authorization denials, clinical escalations, and complex coding decisions require human expertise–Claude can assist, not decide. ❌ Processing PHI without BAA in place: Any workflow involving identifiable patient information requires enterprise API access under BAA. Consumer Claude is categorically excluded. ### Realistic Outcomes: What the Data Shows Organizations that have systematically integrated generative AI into revenue cycle management workflows are seeing measurable improvements: These are not vendor-neutral outcomes. They reflect organizations that have invested in process redesign, compliance infrastructure, and human oversight protocols alongside AI adoption. Pilot projects without those elements rarely scale. ### Competitive Context According to Gartner and HIMSS, over 60% of large U.S. health systems are piloting or deploying generative AI in RCM workflows by the end of 2025. This is not a "follow the herd" argument–it is a market reality check. Organizations that do not explore these tools may find themselves at an operational disadvantage by 2026, particularly in labor-constrained markets where administrative efficiency determines margin sustainability. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Which AI Tool Is Best for Healthcare? There is no universal answer. The optimal choice depends on your use case, existing IT infrastructure, compliance requirements, and budget model. Claude is one option among several enterprise-grade platforms offering HIPAA-compliant access. ### Comparative Landscape Fig. 02 · Comparison HIPAA-ready AI platforms How the main platforms compare Platform | Strengths | Best fit | Claude (Anthropic) | Instruction-following, long context windows (200K tokens), conversational UX | Organizations prioritizing ease of use, summarization tasks, minimal EHR integration | Azure OpenAI (Microsoft) | Native integration with the Microsoft ecosystem, HITRUST certification | Health systems using Microsoft Cloud for Healthcare, Epic on Azure | Google Cloud (Vertex AI) | Access to Med-PaLM 2 (medically fine-tuned model), GCP infrastructure | Research institutions, organizations with GCP data lakes | ### Decision Criteria ### Where Claude Has an Edge ### Where Claude May Not Be Optimal Practical guidance: Run a structured pilot across 2-3 platforms with identical use cases. Measure accuracy, integration complexity, and staff adoption. Vendor marketing claims converge; real-world performance diverges. ## Pricing and Access: What It Actually Costs Anthropic's pricing structure is transparent for consumer and API tiers, but opaque for enterprise contracts requiring BAA. This lack of public pricing is itself strategically relevant–CFOs planning 2025-2026 AI budgets cannot model costs without direct vendor engagement. ### Public Pricing (as of April 2025) Claude.ai Consumer Access: Claude API (Pay-As-You-Go): Example calculation: Summarizing 100 patient charts per day (average 5,000 tokens input, 500 tokens output per chart) on Claude 3.5 Sonnet = approximately $600/month in API costs alone, excluding integration and compliance overhead. ### Enterprise Pricing (Not Publicly Disclosed) Organizations requiring a BAA must contact Anthropic sales directly. Enterprise contracts typically include: Critical consideration: The absence of transparent enterprise pricing means you cannot complete a business case without initiating vendor discussions. For organizations evaluating multiple AI platforms concurrently, this extends procurement timelines. Budget 8-12 weeks for enterprise contract negotiation, legal review, and BAA execution. ### Access Pathways Most U.S. health systems pursuing HIPAA-compliant access use AWS Bedrock due to existing AWS infrastructure relationships and streamlined BAA execution. ## Should Your Organization Deploy Claude? The answer depends less on Claude's technical capabilities–which are well-documented–and more on your organization's operational readiness to use any generative AI tool safely and effectively. ### Deploy Claude If: ### Do Not Deploy Claude If: ### Realistic Expectation Setting Claude is a task acceleration tool, not a systemic transformation. Organizations achieving 15-20% RCM cost reductions are not deploying Claude in isolation–they are redesigning workflows, retraining staff, and continuously iterating on prompt engineering. If your implementation plan is "buy API access and see what happens," outcomes will be limited. The $30B+ global AI-in-healthcare market projected by 2026 (Frost & Sullivan, MarketsandMarkets) reflects long-term capability building, not tactical tool purchases. Health systems investing in AI infrastructure today are positioning for sustained competitive advantage–but that advantage accrues to organizations that treat AI deployment as a strategic program, not a software license. ## Final Assessment Anthropic's Claude for Healthcare is a capable, instruction-following language model available under HIPAA-compliant terms for enterprise customers. It accelerates summarization, drafting, and conversational reasoning tasks. It does not diagnose, prescribe, or replace clinical judgment. The primary barriers to successful deployment are not technical–they are organizational. Does your health system have the IT infrastructure, compliance protocols, staff training, and leadership commitment to deploy generative AI responsibly? If yes, Claude is a viable tool among several enterprise options. If no, purchasing API access will not solve those underlying gaps. For organizations ready to pilot, start narrow: one defined use case, one department, 90-day evaluation with explicit success metrics (time saved per task, error rate, staff satisfaction). Scale only after demonstrating measurable value and compliance sustainability. Generative AI in healthcare is not optional by 2026–but successful adoption requires precision, oversight, and institutional discipline. Claude is the tool. Your organization provides everything else. At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let's talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byDominik Put UiPath-certified RPA developer with extensive experience in automating healthcare, customer service, and HR processes. His keen interest lies in Document Understanding and OCR technologies.. [More from Dominik](https://www.flobotics.io/our-editorial-team#put) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareAI ### Claude for Healthcare Overview | 2026 Claude for Healthcare: Anthropic's 2026 toolkit for US medical data, with HIPAA compliance details and case studies from Banner Health and Novartis. Jędrzej SzymulaMay 06, 2026 ](https://www.flobotics.io/blog/claude-for-healthcare)[ RCMAIHealthcare ### Agentic AI in Healthcare: From Hype to Real-World Impact Agentic AI in healthcare: how it differs from generative AI like ChatGPT and where it's already driving real clinical impact. Jędrzej SzymulaSeptember 22, 2025 ](https://www.flobotics.io/blog/agentic-ai-in-healthcare)[ AIHealthcareRCM ### AWS Connect Health: RCM Salvation or Infrastructure Play? AWS Connect Health: is Amazon's new healthcare platform an RCM solution or just an infrastructure play? We break down what it actually delivers. Bart TeodorczukMay 18, 2026 ](https://www.flobotics.io/blog/aws-connect-health) [All articles →](https://www.flobotics.io/blog) --- # Days in Accounts Receivable (DAR): Formula and Benchmarks Canonical: https://www.flobotics.io/blog/days-in-accounts-receivable-dar-explanation Author: Krzysztof Szwed Published: 2026-05-21 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Days in Accounts Receivable (DAR): Formula and Benchmarks [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Days in Accounts Receivable (DAR): Formula and Benchmarks [Krzysztof SzwedHead of Delivery at Flobotics](https://www.flobotics.io/our-editorial-team#szwed) Published May 21, 2026Updated September 1, 2026 On this page - [What Are Days in Accounts Receivable (DAR)?](#what-are-days-in-accounts-receivable-dar) - [Why DAR Is the Headline RCM Metric](#why-dar-is-the-headline-rcm-metric) - [Industry Benchmarks](#industry-benchmarks) - [What Drives DAR Higher](#what-drives-dar-higher) - [How to Reduce DAR Through Automation](#how-to-reduce-dar-through-automation) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Are Days in Accounts Receivable (DAR)? Days in Accounts Receivable (DAR) — also called Days in AR or AR Days — measures the average number of days it takes a healthcare provider to collect payment for services rendered. It is calculated by dividing total outstanding AR by average daily charges. The result tells you, on average, how long it takes from delivering care to receiving and posting payment. DAR is the most widely used summary indicator of revenue cycle velocity and cash flow health. It captures the cumulative effect of everything in the billing cycle: claim submission speed, denial rates, payer processing times, payment posting efficiency, and patient collections. A high DAR means money is sitting in the pipeline instead of your bank account. ## Why DAR Is the Headline RCM Metric Every extra day in AR represents delayed cash — which has a real cost. Organizations with high DAR carry larger financing needs, face higher write-off risk as claims age toward timely filing limits, and spend more on collections for aged accounts. DAR above 50 days is often associated with chronic cash flow problems and reliance on credit to bridge gaps that better billing discipline would close. DAR is also diagnostic. When it worsens, something upstream has deteriorated: denial rates may have increased, payment posting may have slowed, a payer may be systematically delaying claims, or eligibility failures may have created a wave of rejected claims doubling collection timelines. ## Industry Benchmarks - Best-in-class: 25–35 days - Acceptable: 35–50 days - At risk: 50–65 days — requires structured AR cleanup and process audit - Critical: 65+ days — significant write-off risk on aging buckets The benchmark that matters most is your own trend over time. Consistent upward drift is always a warning signal regardless of absolute value. ## What Drives DAR Higher - High denial rates: Rejected claims cycle through rework processes adding weeks to collection timelines - Slow claim submission: Delays between service and claim generation directly extend DAR - Manual payment posting backlogs: ERA/EOB data sitting unprocessed makes DAR appear worse than actual payer performance - Patient responsibility collection gaps: Increasing patient cost-sharing that goes uncollected inflates DAR's patient AR component - AR cleanup neglect: Accounts that should be written off but remain open inflate the numerator ## How to Reduce DAR Through Automation DAR improvement requires compressing every phase of the claims cycle simultaneously — which is why [RCM automation programs](https://www.flobotics.io/rcm-automation) deliver their most visible results here: - [Automated eligibility verification](https://www.flobotics.io/agents/eligibility-check-automation) eliminates the most common denial trigger, preventing rework loops that extend DAR - [Automated claims management](https://www.flobotics.io/agents/claims-management-automation) submits clean claims within hours of service - Automated payment posting from ERA feeds processes payments daily without backlog accumulation - [Automated denial management](https://www.flobotics.io/agents/denials-management-automation) prioritizes high-value denied claims for rapid resolution before they age See how our clients reduced DAR by 30–50% in our [healthcare case studies](https://www.flobotics.io/case-studies). Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byKrzysztof Szwed Head of Delivery at Flobotics. [More from Krzysztof](https://www.flobotics.io/our-editorial-team#szwed) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### Net Collection Rate (NCR): Formula and Benchmarks Net Collection Rate (NCR) explained: the RCM metric measuring collectible revenue actually captured. Best practice is 95-99% - below that, revenue leaks. Bart TeodorczukJune 04, 2026 ](https://www.flobotics.io/blog/net-collection-rate-ncr)[ HealthcareRCM ### Cost to Collect (CTC): Definition and Benchmarks Cost to Collect (CTC) benchmarks sit at 3-5% of net revenue - a 1% cut on $10M in collections frees up $100,000 in cash. Karl MielnickiMay 18, 2026 ](https://www.flobotics.io/blog/cost-to-collect-ctc-explanation)[ HealthcareRCM ### Claim Turnaround Time (CTT): Benchmarks and Root Causes Claim Turnaround Time (CTT), explained: why 14-21 days is best-in-class and 45+ days signals a billing cycle problem. Krzysztof SzwedMay 04, 2026 ](https://www.flobotics.io/blog/claim-turnaround-time-ctt-explanation) [All articles →](https://www.flobotics.io/blog) --- # Net Promoter Score (NPS) in Healthcare Canonical: https://www.flobotics.io/blog/nps-net-promoter-score-explanation Author: Bart Teodorczuk Published: 2026-05-21 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Net Promoter Score (NPS) in Healthcare [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Net Promoter Score (NPS) in Healthcare [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published May 21, 2026Updated September 1, 2026 On this page - [What Is Net Promoter Score (NPS)?](#what-is-net-promoter-score-nps) - [NPS in Healthcare: Financial Implications Beyond Satisfaction](#nps-in-healthcare-financial-implications-beyond-satisfaction) - [Key NPS Drivers in Healthcare](#key-nps-drivers-in-healthcare) - [NPS and the Patient Financial Experience](#nps-and-the-patient-financial-experience) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Is Net Promoter Score (NPS)? Net Promoter Score (NPS) is a standardized loyalty measurement metric based on a single survey question: "How likely are you to recommend [this provider / organization] to a friend or colleague?" on a 0–10 scale. Based on their scores, respondents are classified as: - Promoters (9–10): Loyal, enthusiastic patients likely to recommend and return - Passives (7–8): Satisfied but unenthusiastic — vulnerable to switching - Detractors (0–6): Unhappy patients who may actively discourage others NPS = % Promoters − % Detractors. Scores range from −100 to +100. In healthcare, NPS above 50 is considered excellent; above 70 is world-class. ## NPS in Healthcare: Financial Implications Beyond Satisfaction Under [Value-Based Care (VBC)](https://www.flobotics.io/blog/value-based-care-vbc-explanation) models, patient experience has direct financial implications. CMS's HCAHPS survey scores — a formal patient satisfaction measurement — directly affect Medicare reimbursement rates under the Hospital Value-Based Purchasing program. High-performing patient experience scores earn bonus reimbursement; poor scores face financial penalties. NPS also has indirect revenue cycle implications. Patients who rate their experience highly are more likely to comply with treatment plans, return for follow-up care, pay their bills promptly, and refer others — all contributing to practice volume and revenue. Detractors are more likely to dispute bills, delay payment, and generate negative word-of-mouth that suppresses new patient acquisition. ## Key NPS Drivers in Healthcare - Scheduling and access: Ease of appointment booking, wait times, and after-hours access are top NPS drivers in outpatient settings - Communication and care coordination: How well patients are informed about their care plan, test results, and follow-up - Billing experience: Clarity of billing statements, ease of payment, and support for billing questions — a direct intersection with RCM operations - Clinical quality perception: Whether patients felt heard, respected, and well-cared-for during encounters ## NPS and the Patient Financial Experience The patient billing experience is a significant and often underweighted NPS driver. Confusing statements, unexpected balance bills, lack of payment plan options, and poor customer service in billing interactions consistently generate detractors — and increasingly, negative online reviews that affect new patient acquisition. Automating patient-facing billing communication — clear digital statements, automated payment reminders, online payment options, and proactive out-of-pocket cost estimates — improves the billing component of NPS while simultaneously accelerating patient collections. Patient experience improvement and revenue cycle optimization become the same initiative. A comprehensive [RCM automation program](https://www.flobotics.io/rcm-automation) includes patient financial engagement alongside provider-side billing workflows. [Contact us](https://www.flobotics.io/contact) to learn more. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### Patient Statement: What to Include on a Medical Bill Patient statement guide: what belongs on the final bill patients receive - and why clarity here drives faster payment. Jędrzej SzymulaApril 23, 2026 ](https://www.flobotics.io/blog/patient-statement-explanation)[ RCMHealthcare ### Value-Based Care (VBC): What It Means for RCM Value-based care (VBC) guide: what outcomes-based reimbursement means for quality reporting, risk adjustment, and RCM documentation. Jędrzej SzymulaMay 28, 2026 ](https://www.flobotics.io/blog/value-based-care-vbc-explanation)[ HealthcareRCM ### Digital Patient Engagement: What It Is and Why It Matters Digital patient engagement, explained: how portals, apps, and online billing shape patient payment rates and RCM collections. Bart TeodorczukJune 09, 2026 ](https://www.flobotics.io/blog/digital-patient-engagement-explanation) [All articles →](https://www.flobotics.io/blog) --- # NextGen Automation | 2026 Canonical: https://www.flobotics.io/blog/nextgen-automation Author: Bart Teodorczuk Published: 2026-05-19 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/NextGen Automation | 2026 [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # NextGen Automation | 2026 [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published May 19, 2026Updated September 1, 2026 On this page - [The $15 Billion Gap: Why NextGen Adoption Doesn't Equal RCM Maturity](#thed15billiongapwhynextgenadoptiondoesntequalrcmmaturity) - [The Three-Layer Failure Point](#thethreelayerfailurepoint) - [The Financial Metrics That Matter](#thefinancialmetricsthatmatter) - [Why NextGen Cannot Solve This Alone](#whynextgencannotsolvethisalone) - [Where Automation Delivers Measurable ROI](#whereautomationdeliversmeasurableroi) - [The Missing Layer: What Automation Infrastructure Actually Does](#themissinglayerwhatautomationinfrastructureactuallydoes) - [Compliance and the Human Oversight Requirement](#complianceandthehumanoversightrequirement) - [The Architectural Question for CFOs](#thearchitecturalquestionforcfos) - [The Competitive Cost of Inaction](#thecompetitivecostofinaction) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## The $15 Billion Gap: Why NextGen Adoption Doesn't Equal RCM Maturity Seventy-five percent of large U.S. health systems will deploy NextGen Healthcare or comparable EHR platforms by the end of 2025, according to HIMSS operational maturity reports. Yet only 35% have fully automated their revenue cycle management data flows. That 40-percentage-point chasm between adoption and operational maturity costs American healthcare providers between $15 billion and $20 billion annually–not because the EHR fails, but because the infrastructure surrounding it remains manual. The problem is not NextGen. The problem is what happens after NextGen generates data: the manual bridges staff build between clinical documentation and payer portals, billing engines, and adjudication systems. RCM directors and CFOs face a hard truth: EHR investment does not automatically translate into revenue cycle efficiency. When 65% to 82% of organizations with enterprise EHR systems still rely on human intermediaries to move data downstream, the bottleneck becomes operational, not technological. ## The Three-Layer Failure Point Healthcare organizations struggle with EHR-to-RCM automation because the breakdown occurs across three distinct layers, each compounding the next. NextGen outputs clinical and billing data in formats optimized for its own schema. Payer portals and clearinghouses expect data structured according to X12 EDI standards or proprietary API specifications. Though HL7 and FHIR standards theoretically enable interoperability, implementation guides vary by payer–often by product line within the same payer. According to Healthcare IT News analyses of EHR interoperability challenges, establishing a single new payer connection costs organizations between $50,000 and $150,000, with timelines stretching three to six months. Multiply that across dozens of payers, and the integration backlog becomes a strategic liability. NextGen collects data but does not inherently validate it against the evolving adjudication rules of each payer before transmission. Modern Healthcare's RCM technology integration studies show that 15% to 25% of claims require manual intervention after initial submission because edge cases–outlier procedures, complex prior authorizations, tiered benefit structures–lack automated mapping logic. The EHR captures what happened clinically; it does not predict what the payer's billing logic will accept. That gap lands on RCM staff, who must cross-reference eligibility systems, coverage policies, and fee schedules manually. Even in organizations that claim "integrated" systems, staff routinely copy data between platforms. Adjudication decisions demand cross-system visibility: clinical notes from the EHR, remittance data from the payer portal, contractual terms from the billing system. NextGen's user interface does not natively surface this consolidated view, forcing analysts to toggle between screens or export spreadsheets. RevCycle Intelligence workflow studies document the result: cost-to-collect rises 8% to 12% annually in organizations with modern EHRs but manual data orchestration, because labor costs scale faster than the revenue captured. ## The Financial Metrics That Matter RCM leaders track three indicators that directly reflect data flow efficiency. The table below presents baseline figures for organizations relying on manual workflows versus those that have automated the EHR-to-payer handoff, drawn from HFMA's 2025 RCM benchmarks and RevCycle Intelligence denial rate studies. These deltas are not theoretical. Organizations that have implemented end-to-end claim submission automation–eliminating the export-login-upload cycle–report denial rate reductions in the lower half of that range within 18 months. A 2025 McKinsey Health analysis projects that cost-to-collect will decline 18% for providers that close the manual data bridge, driven primarily by FTE reallocation from transactional tasks to exception management. The denial rate delta merits particular attention. RevCycle Intelligence data indicate that 28% of all denied claims in 2026 trace back to data errors or workflow breaks between systems–missing authorizations not flagged pre-submission, eligibility discrepancies not reconciled before the claim leaves the EHR, procedure codes misaligned with payer-specific billing rules. Each denied claim carries an average rework cost of $25 to $30, and appeal success rates hover near 63% only when clinical documentation is resubmitted promptly. Manual workflows delay that resubmission, compressing the appeal window and eroding recovery rates. ## Why NextGen Cannot Solve This Alone NextGen Healthcare controls the data model within the EHR. It does not control the intake systems operated by payers, nor does it define the business logic each payer applies during adjudication. Payers deploy customized versions of X12 EDI standards, often with companion guides that specify field-level requirements not captured in the base specification. The result: a single CPT code submitted to insurer A may require modifiers, place-of-service codes, and referring provider NPIs in fields that insurer B leaves optional or structures differently. Data enrichment–the process of mapping a clinical event to a billable service, cross-referencing contractual fee schedules, and validating eligibility in real time–does not reside in the EHR. It resides in middleware platforms, clearinghouses, and increasingly, automation layers that sit between the EHR output and payer intake. NextGen provides APIs and export utilities, but those tools only move data; they do not transform or validate it against downstream requirements. This is not a design flaw. It reflects the architectural reality of U.S. healthcare IT: EHRs optimize for clinical workflow and regulatory compliance (Meaningful Use, MIPS, hospital quality reporting). RCM systems optimize for financial workflow and payer compliance. The two domains intersect, but they are not synonymous. Organizations that treat EHR adoption as the endpoint of their RCM modernization journey discover the gap when their DSO remains stubbornly above 45 days despite a six-figure EHR investment. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Where Automation Delivers Measurable ROI Four workflow domains generate quantifiable impact when automated, according to McKinsey Health's healthcare automation ROI studies and RevCycle Intelligence's operational benchmarks. These use cases share a common denominator: they eliminate the human effort required to bridge incompatible data structures. Automation does not replace clinical judgment or compliance oversight–complex denials still require human analysis, and appeals involving clinical documentation improvement demand provider input–but it removes the transactional burden that prevents RCM staff from performing higher-value analytical work. ## The Missing Layer: What Automation Infrastructure Actually Does Organizations that achieve the metrics outlined above deploy an automation layer between NextGen's output and payer intake systems. This layer performs four functions: AI-driven rule engines map EHR data fields to payer-specific requirements without hardcoded integrations. When a payer updates its companion guide–changing required modifiers for a procedure code–the system adapts without manual reprogramming. Before a claim leaves the EHR, the automation layer [checks it against real-time eligibility data](https://www.flobotics.io/agents/eligibility-check-automation), authorization databases, and payer-specific billing rules. Claims that fail validation are quarantined for staff review, preventing initial denials. Machine learning models [analyze denial patterns and adjudication outcomes](https://www.flobotics.io/agents/denials-management-automation), refining validation logic over time. If insurer X consistently denies claims for service Y when billed with modifier Z, the system flags those combinations proactively. Dashboards consolidate data from NextGen, payer portals, and billing systems, showing RCM directors where claims stall, how much revenue remains in accounts receivable beyond target DSO, and which payers generate the highest rework costs. This infrastructure is not a replacement for NextGen; it is a complement. NextGen remains the system of record for clinical and billing data. The automation layer handles the orchestration–the movement, transformation, and validation of that data as it flows toward payers. Organizations with both components report DSO figures in the 35-to-42-day range, compared to 47-to-52 days for peers relying on manual data bridges. ## Compliance and the Human Oversight Requirement Automated systems generate full audit trails. Enterprise-grade RPA platforms log every transaction: timestamp, data source, rule applied, and any manual override. When CMS or OIG auditors request claim documentation, organizations can trace each automated decision back to the underlying logic and data inputs. This transparency often exceeds what manual workflows provide, where Excel exports and email chains serve as the record of decision-making. However, automation does not eliminate the need for human judgment. Complex denials–those involving medical necessity disputes or coordination of benefits across multiple insurers–require clinicians and RCM specialists to interpret payer rationale and craft responses. Appeals that depend on clinical documentation improvement necessitate provider involvement to ensure accuracy. Compliance checkpoints, particularly those tied to billing code selection and modifier application, benefit from human review even when initial validation is automated. The strategic shift is from transactional roles to analytical roles. Instead of spending 60% of their time on data entry and manual system navigation, RCM staff focus on denial pattern analysis, payer contract optimization, and process improvement. HFMA cost benchmarks suggest that this reallocation yields a 15% to 20% productivity gain within the first year post-automation, measured by revenue recovered per FTE. ## The Architectural Question for CFOs When CFOs evaluate RCM automation investments, the ROI calculation hinges on two variables: FTE cost avoidance and DSO reduction. A mid-sized health system with 5 to 7 FTEs dedicated solely to manual data bridging–at $60,000 to $80,000 per FTE annually–spends $300,000 to $560,000 per year on transactional labor. Automation projects targeting those workflows typically achieve payback within 18 to 24 months, assuming a 50% to 60% reduction in manual effort. DSO improvement compounds that return. Each day of DSO reduction releases working capital. For a system with $200 million in annual net patient revenue and 50-day DSO, a 10-day reduction frees approximately $5.5 million in cash flow. That capital can fund clinical investments, reduce reliance on short-term borrowing, or improve operating margins in an environment where CMS payment updates lag inflation. The question is not whether to automate–it is whether to build or buy the automation layer. Organizations that attempt in-house development often underestimate the complexity of maintaining payer-specific rule engines as billing policies evolve. Healthcare-focused automation platforms, by contrast, specialize in this domain: they track payer updates, incorporate regulatory changes (No Surprises Act compliance, prior authorization mandates), and distribute those updates across their client base without requiring each organization to rebuild logic independently. ## The Competitive Cost of Inaction Healthcare operates in a zero-sum reimbursement environment. Payers do not increase payment rates to reward operational efficiency; they deny claims that fail to meet their standards and delay payments when documentation is incomplete. Organizations that close the EHR-to-payer data gap capture revenue faster, reduce write-offs from aged accounts, and allocate staff to recovery efforts rather than transactional rework. NextGen adoption was the necessary first step–centralizing clinical and billing data in a single system. The next step is operational: ensuring that data moves seamlessly from NextGen to the systems that convert it into cash. Organizations that treat EHR implementation as the finish line will continue reporting DSO figures in the high 40s while their competitors operate in the mid-30s. The difference is not the EHR. The difference is the automation layer. At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let's talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareAIRPA ### Epic Automation | 2026 Epic Systems revenue cycle automation: why the EHR powering 300+ health systems still needs RPA to close labor, payer, and margin gaps in 2026. Jędrzej SzymulaApril 10, 2026 ](https://www.flobotics.io/blog/epic-automation)[ HealthcareAIRCM ### Meditech Automation | 2026 Meditech automation: why strong transaction handling still stalls on cross-workflow orchestration, and how to scale past it. Jędrzej SzymulaMarch 25, 2026 ](https://www.flobotics.io/blog/meditech-automation)[ HealthcareRCMAI ### athenahealth Automation | 2026 athenahealth automation: what its shared rules engine standardizes well, and where you still need custom workflow control. Jędrzej SzymulaMarch 23, 2026 ](https://www.flobotics.io/blog/athenahealth-automation) [All articles →](https://www.flobotics.io/blog) --- # Cost to Collect (CTC): Definition and Benchmarks Canonical: https://www.flobotics.io/blog/cost-to-collect-ctc-explanation Author: Karl Mielnicki Published: 2026-05-18 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Cost to Collect (CTC): Definition and Benchmarks CTO Notes [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Cost to Collect (CTC): Definition and Benchmarks [Karl MielnickiCTO & Co-Founder of Flobotics](https://www.flobotics.io/our-editorial-team#mielnicki) Published May 18, 2026Updated September 1, 2026 On this page - [What Is Cost to Collect (CTC)?](#what-is-cost-to-collect-ctc) - [Why CTC Is the Definitive RCM Efficiency Metric](#why-ctc-is-the-definitive-rcm-efficiency-metric) - [Industry Benchmarks](#industry-benchmarks) - [What Drives CTC Higher](#what-drives-ctc-higher) - [How Automation Reduces CTC](#how-automation-reduces-ctc) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Is Cost to Collect (CTC)? Cost to Collect (CTC) is the total operational cost a healthcare practice or health system incurs to successfully collect payment for services rendered, expressed as a percentage of net revenue collected. It captures everything that goes into running the revenue cycle: billing staff salaries, technology subscriptions, clearinghouse fees, denial management work, collections costs, and all administrative overhead attributable to the revenue cycle function. CTC puts a dollar value on how well — or poorly — a healthcare organization's revenue cycle is performing. A high CTC means you are spending too much to collect what you are owed. A low CTC means your processes are clean, your staff are productive, and your technology is doing meaningful work. ## Why CTC Is the Definitive RCM Efficiency Metric Unlike metrics that measure a single process, CTC captures the aggregate cost of the entire revenue cycle operation — making it uniquely valuable for executive decision-making. It translates RCM performance directly into financial language that CFOs and boards understand. CTC is also the primary metric for evaluating automation ROI. When a healthcare organization automates eligibility verification, claims submission, or payment posting, the labor and rework costs displaced are directly measurable in CTC reduction. A practice reducing CTC from 8% to 4% of net collections while maintaining revenue frees 4 cents of every dollar for clinical investment or margin improvement. ## Industry Benchmarks - Best-in-class: 3–4% of net patient revenue - Acceptable (independent practice): 4–6% - Industry average: 6–8% - Underperforming: 8–12%+ — indicates structural problems in staffing, process, or technology A physician group collecting $10M annually at 8% CTC spends $800,000 on revenue cycle operations. The same practice at 4% spends $400,000 — a $400,000 annual difference achievable through process and technology improvement without touching clinical volume. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## What Drives CTC Higher - High denial and rework rates: Each denied claim requiring manual investigation and resubmission adds direct labor cost - Manual payment posting: ERA/EOB processing requiring staff to manually match payments to claims - Paper-based workflows: Any process step involving printing or manual data entry is inherently more expensive - High AR days: Claims that age require progressively more expensive collection intervention - Technology fragmentation: Staff working across disconnected systems spend significant time on reconciliation that integration would eliminate ## How Automation Reduces CTC [RCM automation programs](https://www.flobotics.io/rcm-automation) reduce cost to collect by eliminating manual labor from high-volume, rules-based processes across the entire revenue cycle: - Automated [eligibility verification](https://www.flobotics.io/agents/eligibility-check-automation) eliminates manual coverage lookups — one of the highest-volume front-end staff tasks - [Automated claims scrubbing and submission](https://www.flobotics.io/agents/claims-management-automation) reduces rework rates directly - Automated [payment posting](https://www.flobotics.io/blog/payment-posting-cash-posting-explanation) from ERA feeds processes hundreds of payments per hour without staff involvement - [Denials management automation](https://www.flobotics.io/agents/denials-management-automation) identifies and routes denied claims for resolution without manual triage Practices automating core RCM workflows typically achieve 30–50% CTC reductions within 12 months. [Our case studies document specific results.](https://www.flobotics.io/case-studies) Written byKarl Mielnicki CTO & Co-Founder of Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### Net Collection Rate (NCR): Formula and Benchmarks Net Collection Rate (NCR) explained: the RCM metric measuring collectible revenue actually captured. Best practice is 95-99% - below that, revenue leaks. Bart TeodorczukJune 04, 2026 ](https://www.flobotics.io/blog/net-collection-rate-ncr)[ HealthcareRCM ### Days in Accounts Receivable (DAR): Formula and Benchmarks Days in Accounts Receivable (DAR) guide: why 30-35 days is best practice and anything above 50 signals collection trouble. Krzysztof SzwedMay 21, 2026 ](https://www.flobotics.io/blog/days-in-accounts-receivable-dar-explanation)[ HealthcareRCM ### Claim Turnaround Time (CTT): Benchmarks and Root Causes Claim Turnaround Time (CTT), explained: why 14-21 days is best-in-class and 45+ days signals a billing cycle problem. Krzysztof SzwedMay 04, 2026 ](https://www.flobotics.io/blog/claim-turnaround-time-ctt-explanation) [All articles →](https://www.flobotics.io/blog) --- # Initial Denial Rate: How to Measure and Lower It Canonical: https://www.flobotics.io/blog/initial-denial-percentage-explanation Author: Jędrzej Szymula Published: 2026-05-18 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Initial Denial Rate: How to Measure and Lower It [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Initial Denial Rate: How to Measure and Lower It [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published May 18, 2026Updated September 1, 2026 Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Initial Denial Percentage The percentage of submitted claims that are formally rejected by payers upon their first attempt at processing. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### Clean Claim Rate (CCR): Definition and Benchmarks Clean Claim Rate (CCR) guide: the foundational RCM metric behind denials, DAR, and collections, with a 98%+ target. Bart TeodorczukJune 01, 2026 ](https://www.flobotics.io/blog/clean-claim-rate-ccr-explanation)[ HealthcareRCM ### What Is Denials Management? Process and Benchmarks Denials management tackles denial rates now above 20%, where every reworked claim costs about $44 - and prevention pays off. Karl MielnickiApril 02, 2026 ](https://www.flobotics.io/blog/denials-management-explanation)[ HealthcareRCM ### Denials Appeal Process: Levels of Appeal Explained Denials appeal process, explained: with commercial overturn rates dropping from 56% to 45%, see what still wins appeals. Bart TeodorczukMarch 18, 2026 ](https://www.flobotics.io/blog/denials-appeal-explanation) [All articles →](https://www.flobotics.io/blog) --- # AWS Connect Health: RCM Salvation or Infrastructure Play? Canonical: https://www.flobotics.io/blog/aws-connect-health Author: Bart Teodorczuk Published: 2026-05-18 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/AWS Connect Health: RCM Salvation or Infrastructure Play? [AI](https://www.flobotics.io/blog?category=ai)[Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # AWS Connect Health: RCM Salvation or Infrastructure Play? [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published May 18, 2026Updated September 1, 2026 On this page - [What AWS Connect Health Actually Delivers?](#whatawsconnecthealthactuallydelivers) - [Where Connect Health Creates Real Value?](#whereconnecthealthcreatesrealvalue) - [Five Critical Limitations of AWS Connect Health](#fivecriticallimitationsawsomitsfromsalespresentations) - [When Connect Health Makes Sense?](#decisionmatrixwhenconnecthealthmakessense) - [Unanswered Questions That Should Concern You Before Investing](#unansweredquestionsthatshouldconcernbuyers) - [Summary:](#theinfrastructureversussolutionquestion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Connect Health is AWS’s first purpose-built healthcare application layer, shipping with prebuilt AI agents for patient verification, scheduling, clinical documentation, and medical coding on top of HealthLake, Bedrock, Comprehend Medical, and AWS Connect. It is not, however, a turnkey end-to-end RCM platform - payer-specific claim adjudication, denial management workflows, and 835 remittance reconciliation remain a customer or partner responsibility, a distinction with profound operational consequences for CFOs evaluating automation investments. The central question facing revenue cycle directors is not whether AWS Connect Health uses sophisticated technology. It does. The question is whether your organization needs a platform to build solutions, or a solution that works within 90 days. ## What AWS Connect Health Actually Delivers? AWS Connect Health combines four existing Amazon services: - Comprehend Medical for natural language processing of clinical documentation, - HealthLake for FHIR-compliant data aggregation, - AWS Connect for contact center operations, - Amazon Bedrock for machine learning model deployment. This architecture matters because it reveals what Connect Health is - and crucially, what it is not. Connect Health provides infrastructure components for healthcare data processing. It does not provide the claim scrubbing edits that catch billing errors before submission. It lacks payer-specific rule engines that reflect the labyrinthine differences between Medicare, Medicaid, and commercial insurance requirements. It contains no native denial management workflow with classification logic for Contractual Adjustment Reasons, Claim Adjustment Reasons, or Patient Responsibility codes. The 835 remittance advice processing that reconciles payments against submitted claims? Not included. Functionality | AWS Connect Health | Purpose-Built RCM | Patient verification | ✅ Prebuilt AI agent | ✅ Out-of-the-box | Scheduling | ✅ Prebuilt AI agent | Varies by vendor | Medical history documentation | ✅ Prebuilt AI agent | Varies by vendor | Medical coding | ✅ Prebuilt AI agent | ✅ Out-of-the-box | Claim scrubbing & edits | ⚠️ Payer-specific rules require custom build | ✅ Out-of-the-box | Payer-specific rules | ❌ None included | ✅ Embedded, continuously updated | Denial management workflow | ❌ No native capability | ✅ Core feature | FHIR interoperability | ✅ HealthLake native | Varies by vendor | Time to value | Weeks–months for prebuilt agents; 12–24 months for full enterprise rollout | 3–9 months | Three-year TCO at moderate volume | High implementation + ongoing | Predictable SaaS pricing | ‍ Every functional gap requires either internal development or third-party integration. For large health systems with existing AWS infrastructure and engineering talent, this flexibility enables customization. For regional hospitals operating on 3-5% margins, it represents an implementation gauntlet that consumes capital without guaranteed returns. Industry data reinforces this reality: fewer than 30% of healthcare organizations report measurable ROI within 18 months of implementing AI in RCM workflows, per the HIMSS 2024 Annual Report - despite 70-80% running pilots. ## Where Connect Health Creates Real Value? Fair analysis requires acknowledging where AWS Connect Health delivers genuine operational advantages. FHIR Interoperability at Scale HealthLake handles FHIR R4 natively, addressing a persistent pain point for health systems running multiple electronic health record platforms. The typical academic medical center operates Epic for inpatient care, Cerner for ambulatory services, and legacy systems for specialty departments. Aggregating clinical data before billing represents a bottleneck that delays claim submission and increases error rates. HealthLake eliminates ETL gymnastics for organizations already storing clinical data in FHIR format. Enterprise Security and Compliance Posture AWS maintains HIPAA and HITRUST certifications across its infrastructure. For organizations with existing AWS deployments, extending into RCM workflows avoids vendor sprawl and simplifies Business Associate Agreement management. The shared responsibility model applies-AWS secures the infrastructure, while configuration and process compliance remain the customer's burden - but the foundation meets stringent requirements. Prior Authorization Automation Potential Prior authorization consumes 14 hours of physician time weekly, according to the American Medical Association. AWS Connect integrated with Comprehend Medical can automate 40-60% of straightforward PA requests in pilot deployments - extracting clinical criteria from unstructured notes, matching against payer policies, and routing exceptions to human review. For procedures requiring pre-approval, this automation directly reduces revenue leakage from delayed or denied services. Contact Center Transformation for Patient Billing AWS Connect's natural language processing capabilities extend beyond clinical documentation to patient-facing billing operations. Payment plan negotiation, balance inquiry automation, and intelligent call routing reduce the labor intensity of patient financial services. Revenue integrity teams managing high volumes of patient payment arrangements gain operational leverage. These use cases share a common characteristic: they create value where AWS infrastructure strengths - data aggregation, scalable compute, ML model deployment - align with specific RCM pain points. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Five Critical Limitations of AWS Connect Health Partial Out-of-the-Box RCM Functionality When AWS launched Connect Health in March 2026, the platform shipped with prebuilt, AI-supported capabilities for patient verification, scheduling, medical history documentation, and coding - the first time AWS has packaged healthcare-specific agents at this level of abstraction. Even so, several core revenue cycle components are still missing out of the gate. Payer-specific claim scrubbing typically requires external rules engines or custom development. Denial management workflows must be built from scratch or licensed from ISVs. Full 837 transaction validation, LCD/NCD compliance checking, and modifier logic that prevent rejections at enterprise scale are not delivered as turnkey features. This is not a deficiency - it is an architectural choice. AWS builds horizontal platforms, not vertical solutions. But it contradicts the "AI-powered RCM automation" narrative used in marketing materials. Implementation Costs That Dwarf Licensing A complete, enterprise-wide Connect Health rollout for a $500 million revenue hospital system - covering integration with existing EHRs, payer connections, and clearinghouses — still typically requires 12-24 months and $2-5 million in systems integration and consulting fees. Narrower deployments that rely on Connect Health’s prebuilt AI agents for verification, scheduling, documentation, or coding can be stood up in considerably less time, but a full multi-EHR replacement of legacy revenue cycle tooling remains a multi-year program. This aligns with McKinsey data showing 60% of healthcare cloud migrations exceed budgeted costs. The math becomes unfavorable for mid-sized organizations. A 150-bed community hospital processing 200,000 claims annually lacks the volume to justify infrastructure investment. Purpose-built SaaS platforms reach break-even within months; Connect Health requires years. AWS pricing opacity compounds the challenge. Usage-based billing for data processing, ML inference, and storage makes total cost of ownership difficult to model without detailed volume projections. Predictable per-claim or per-patient pricing from specialized RCM vendors simplifies financial planning. The Domain Expertise Gap Waystar, Experian Health, and nThrive embed payer policy knowledge in their platforms. When CMS updates evaluation and management guidelines or United Healthcare revises its claim edit logic, these vendors update rules automatically. AWS Connect Health contains no such domain intelligence - maintaining compliance with evolving payer requirements falls entirely on the customer or integration partner. This gap is not hypothetical. The 2023 transition to CPT evaluation and management code changes disrupted billing operations for months. Organizations relying on infrastructure platforms bore the full burden of updating their custom logic; those using specialized RCM platforms received automatic updates. The Talent Shortage Problem Successful Connect Health implementations require a rare skills combination: AWS-certified cloud architects, healthcare data engineers familiar with HL7 and FHIR standards, and RCM domain experts who understand claim adjudication logic. For health systems in secondary markets competing with technology firms for engineering talent, assembling this team internally proves prohibitively expensive. Hiring consultancies solves the expertise problem while creating long-term vendor dependencies. The Hidden Machine Learning Tax Deploying ML models in production requires clean, labeled training data that most hospitals lack. Claim denial data resides in fragmented systems; clinical documentation quality varies by department and provider. Before Connect Health's ML capabilities generate value, organizations must solve fundamental data hygiene problems. Then comes the ongoing cost: model drift monitoring, continuous retraining as payer behavior changes, and DevOps infrastructure. Conservative estimates place annual ML operations costs at $150,000-300,000 for moderate-scale deployments - before accounting for the FTE costs of data scientists and engineers required to maintain models. ## When Connect Health Makes Sense? Organization Type | Verdict | Rationale | Recommendation | Large Health System (>$1B revenue, multi-EHR) | ✅ Consider | HealthLake solves real interoperability challenges; AWS Connect scales across enterprise call volumes. | Use as infrastructure layer. RCM logic requires specialized partners. ROI: 24-36 months. | Regional Hospital ($100-500M revenue) | ❌ Avoid | Implementation costs consume multiple years of potential RCM savings. Unfavorable economics. | Purpose-built SaaS delivers faster time-to-value. Consider AWS only for contact center or data lake use cases. | Lab, Specialty Provider, or ASC | ❌ Not applicable | Does not address lab billing specifics: CPT edits, LCD/NCD compliance, ABN workflows, technical/professional splits. | Vertical-specific RCM platforms only practical option for fast ROI. | ## Unanswered Questions That Should Concern You Before Investing Because AWS Connect Health only launched out of beta in early March 2026, AWS has not yet published case studies demonstrating measurable FTE reduction or denial rate improvement from multi-year enterprise deployments. Early rollouts have reported high autonomous resolution rates on routine healthcare administrative tickets, but multi-year, audited ROI data for full enterprise implementations is still maturing - which complicates ROI justification for finance committees evaluating seven-figure programs. The validation problem persists: when ML models flag potential claim errors, who reviews and corrects them? Connect Health shifts work from manual claim entry to exception management - but published data on net labor impact does not exist. Organizations that complete implementations may achieve genuine efficiency gains; buyers lack evidence to model expected results. Integration complexity remains the implementation killer for cloud RCM projects. Connect Health must connect to EHR systems, clearinghouses, payer portals, and existing revenue cycle applications. Industry benchmarks indicate integration consumes 40% of project timelines. AWS provides APIs and data connectors, but each organization's technical environment introduces unique complications. The risk of scope creep and timeline extension is substantial. AWS's shared responsibility model creates compliance ambiguity. The company provides HIPAA-compliant infrastructure, but configuration mistakes that expose PHI remain the customer's liability. For organizations lacking mature cloud security practices, this division of responsibility introduces audit risk. ### Summary: AWS Connect Health represents Amazon's horizontal platform strategy applied to healthcare revenue cycle management. It provides a purpose-built healthcare application layer - including prebuilt AI agents for verification, scheduling, documentation, and coding - on top of the computational infrastructure, data storage, and ML model deployment capabilities required to build broader RCM solutions. It does not, however, provide the full set of payer-specific claim adjudication, denial management, and 835 remittance reconciliation workflows that constitute end-to-end RCM software. This distinction matters profoundly for capital allocation decisions. Organizations with technical sophistication, existing AWS infrastructure, and 18-24 month implementation horizons can leverage Connect Health's flexibility to create customized workflows that address their specific operational challenges. The economic case depends on multi-EHR interoperability needs, enterprise scale, and willingness to invest in internal engineering capacity. For the majority of healthcare providers seeking rapid denial rate reduction and clean claim rate improvement, purpose-built RCM platforms maintain decisive advantages in time-to-value and embedded domain expertise. The question facing CFOs is not whether AWS possesses superior technology - it does. The question is whether your organization needs infrastructure to build a solution, or a solution that produces measurable results by day 90. The $262 billion in annual denied claims will not wait for 24-month implementations. Choose accordingly. At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let's talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareAI ### Claude for Healthcare Overview | 2026 Claude for Healthcare: Anthropic's 2026 toolkit for US medical data, with HIPAA compliance details and case studies from Banner Health and Novartis. Jędrzej SzymulaMay 06, 2026 ](https://www.flobotics.io/blog/claude-for-healthcare)[ AI ### The Hottest Agentic AI Examples and Use Cases in 2026 Agentic AI examples and use cases: how AI agents are automating healthcare RCM, legal drafting, and retail inventory in 2026. Jędrzej SzymulaOctober 02, 2025 ](https://www.flobotics.io/blog/hottest-agentic-ai-examples-and-use-cases)[ HealthcareRCMAI ### athenahealth Automation | 2026 athenahealth automation: what its shared rules engine standardizes well, and where you still need custom workflow control. Jędrzej SzymulaMarch 23, 2026 ](https://www.flobotics.io/blog/athenahealth-automation) [All articles →](https://www.flobotics.io/blog) --- # UiPath's Agentic AI: Orchestrating Autonomous Agents in Enterprise Automation Canonical: https://www.flobotics.io/blog/uipaths-agentic-ai-orchestration Author: Bart Teodorczuk Published: 2026-05-15 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/UiPath's Agentic AI: Orchestrating Autonomous Agents in… [AI](https://www.flobotics.io/blog?category=ai)[RPA](https://www.flobotics.io/blog?category=rpa) # UiPath's Agentic AI: Orchestrating Autonomous Agents in Enterprise Automation [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published May 15, 2026Updated September 1, 2026 On this page - [UiPath Maestro – Agentic Orchestration for the Enterprise](#uipath-maestro-agentic-orchestration-for-the-enterprise) - [UiPath Agent Builder – Creating Custom AI Agents with Ease](#uipath-agent-builder-creating-custom-ai-agents-with-ease) - [UiPath Autopilot – Generative AI Assistant for Automation](#uipath-autopilot-generative-ai-assistant-for-automation) - [UiPath Healing Agent – Self-Healing Automation with AI](#uipath-healing-agent-self-healing-automation-with-ai) - [Microsoft (Copilot + Power Automate)](#microsoft-copilot-power-automate) - [Automation Anywhere](#automation-anywhere) - [SS&C Blue Prism](#ss-c-blue-prism) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) As enterprises seek smarter, more autonomous automation solutions, UiPath has unveiled a powerful suite of agentic AI tools designed to go beyond traditional RPA. AI agents don’t just follow instructions - they plan, decide, and act across complex workflows. In this article, we explore what agentic AI really means in practice, how [UiPath’s platform enables it](https://www.uipath.com/ai/agentic-ai#:~:text=Agentic%20AI%C2%A0refers%20to%20artificial%20intelligence,Agentic%20AI%20is%20an), and what it offers to businesses, partners, and developers ready to embrace the next generation of automation. ## What Is [Agentic AI?](https://www.flobotics.io/blog/agentic-ai-workflows) Agentic AI refers to Artificial Intelligence systems that act with autonomy, initiative, and adaptability to pursue goals, rather than just following preset rules or reactive instructions. In essence, an Agentic AI can independently make decisions and take actions in dynamic environments to achieve objectives. Such AI agents combine multiple AI techniques (like Machine Learning, Natural Language Understanding, and Planning) so they can plan, act, learn, and improve continually. Key capabilities of agentic AI include: - making context-aware decisions, - breaking down goals into subtasks, - using tools or other systems to accomplish tasks, - adapting their behavior over time to get better results. These capabilities unlock a new class of complex, end-to-end applications for AI across the enterprise that surpass the capabilities of traditional rule-based bots or static algorithms. In practical terms, agentic AI enables the creation of AI agents - software programs that behave like autonomous coworkers. They can interpret goals, navigate unstructured scenarios, and collaborate with both software and humans. This represents a step change from earlier generations of automation or “intelligent” bots. Instead of being limited to predefined steps, an agentic AI can dynamically figure out how to fulfill a task. For example, an Agentic AI might be tasked with optimizing a supply chain: it could analyze real-time logistics data, predict bottlenecks, adjust delivery routes on the fly, and even trigger reordering of inventory - all without needing a human to micromanage each step. The ultimate promise is that AI agents become trusted digital colleagues that can tackle decision-intensive work and continuously learn, while humans provide high-level guidance and oversight. ## From RPA to Agentic Automation: UiPath’s Vision [UiPath](https://www.uipath.com/) – known for its leading [Robotic Process Automation (RPA) platform](https://www.flobotics.io/blog/robotic-process-automation) – is now fully embracing Agentic AI as the next evolution of enterprise automation. In late 2024, [UiPath’s CEO Daniel Dines](https://www.techzine.eu/news/applications/125556/uipath-shifts-course-and-commits-fully-to-agentic-ai/) described this shift as “the natural evolution of Robotic Process Automation”, moving from purely rules-based bots to more flexible, AI-driven agents that collaborate with people. Traditional RPA excels at structured, repetitive tasks (think data entry or form processing). Agentic automation, by contrast, combines AI agents, RPA robots, and people in a symbiotic loop to tackle complex workflows that require dynamic decision-making. In this model, AI agents provide the “brainpower” - they autonomously plan and coordinate tasks based on high-level goals. Crucially, agentic automation isn’t about replacing humans – it’s about extending automation to new frontiers. UiPath emphasizes that agentic AI enables enterprises to automate “the myriad of workflows that require a more dynamic, context-aware approach,” far beyond the scope of what RPA alone can do. For business leaders, this means that tasks involving complex decision criteria, unstructured data, or changing conditions (e.g., approving [insurance claims](https://www.flobotics.io/blog/insurance-claims-processing-rpa-automation-use-cases), optimizing a factory floor, or personalizing customer service in real-time) can now be partially or fully automated. Early benefits reported include major efficiency gains, improved customer experiences through 24/7 intelligent service, and human augmentation – freeing employees from grunt work so they can focus on strategic and creative initiatives. [VIDEO] [https://www.youtube.com/watch?v=Fw36aCWxVgU&t=1s&ab_channel=UiPath](https://www.youtube.com/watch?v=Fw36aCWxVgU&t=1s&ab_channel=UiPath) To make this vision a reality, UiPath has rolled out the first [enterprise-grade platform for agentic automation](https://www.uipath.com/platform/agentic-automation). Announced at the UiPath FORWARD conference and the Agentic AI Summit in 2024-2025, the reimagined UiPath Platform is built to orchestrate AI agents, software robots, and people across end-to-end business processes. This platform includes new tools and capabilities (described below) that allow organizations to “agentify” their processes - in other words, infuse AI decision-making and autonomy into workflows while maintaining the governance, security, and reliability that enterprises require. An essential part of UiPath’s strategy is the recognition that orchestration and oversight are vital: when you have fleets of AI agents and bots working together, you need robust controls (guardrails, auditing, human-in-the-loop checkpoints) to manage this intricate ecosystem safely at scale. UiPath’s Agentic AI suite is engineered to provide that control, ensuring businesses can confidently deploy autonomous AI solutions without “letting the robots run wild.” ## Inside UiPath’s Agentic AI Product Suite UiPath’s agentic AI strategy comes to life through a suite of integrated tools and platform features. These include UiPath Maestro, Agent Builder, Autopilot, and Healing Agent. Together, they empower companies to develop, deploy, and govern AI-powered agents alongside traditional automations. Below, we explore each key component and how it contributes to agentic automation: ## [UiPath Maestro](https://www.uipath.com/platform/agentic-automation/agentic-orchestration) – Agentic Orchestration for the Enterprise Think of UiPath Maestro as the command center for orchestrating AI agents, RPA robots, and people across complex processes. It’s essentially an evolved orchestration and [BPM (Business Process Management) platform](https://www.uipath.com/platform/agentic-automation/business-process-management) designed for the agentic era. With Maestro, organizations can visually model end-to-end processes in BPMN 2.0, incorporating tasks performed by AI agents, robots, and humans into a unified workflow. Process designers use familiar BPMN constructs (events, gateways, etc.) - or can even leverage Autopilot’s AI assistance to generate process models – to map out how work should flow between agents and traditional steps. Maestro then handles the coordination, integrating with all parts of the tech stack to connect UiPath AI agents, third-party AI services, software bots, and human user interfaces into a seamless sequence. Business rules and decisions can be defined using DMN (Decision Model & Notation) and plugged into processes, adding logical guardrails for the AI’s behavior. Once processes are deployed, Maestro provides enterprise-grade execution management. This includes real-time monitoring of process instances, exception handling tools (e.g., automatically routing issues to a human or retrying steps), and controls to pause, resume, or alter processes on the fly. Importantly, Maestro also brings analytics and optimization into the loop: it can pinpoint bottlenecks or inefficiencies in workflows and surface performance metrics so teams can continually improve their operations. In short, Maestro ensures that “agents think, robots do, people lead” in harmony. [As one early user described i](https://www.uipath.com/platform/agentic-automation/agentic-orchestration)t, “UiPath Maestro is the orchestration layer that connects everything – robots, AI agents, and systems inside and outside UiPath – ensuring seamless coordination across complex automated processes.”. By extracting high-level business rules from hard-coded scripts and managing them centrally, Maestro helps create more resilient, end-to-end automations that can adapt to changing conditions. It’s the backbone that lets companies operate a multi-agent workforce at scale. ## [UiPath Agent Builder](https://www.uipath.com/product/agent-builder) – Creating Custom AI Agents with Ease If Maestro is the orchestra conductor, the Agent Builder is the factory where new AI agents are crafted. UiPath Agent Builder™ is a development tool (integrated into the UiPath Studio family) that enables developers - and even non-developers - to build, test, and launch AI agents in a low-code environment. Rather than coding an agent’s logic entirely from scratch, Agent Builder provides a guided framework. Users can start with prebuilt agent templates from the UiPath Agent Catalog, which cover common use cases and industry scenarios (for example, an agent template for IT service desk triage or for invoice analysis). These templates come with ready-made logic that can be easily customized via a no-code/low-code interface in Studio Web. For those with unique needs, you can also create a new AI agent from a blank slate – the environment is designed to be “easy to use, low-code, fully integrated” [into UiPath Studio](https://www.uipath.com/product/agent-builder). Under the hood, an AI agent built in this way can incorporate various AI skills: it might use an NLP model to understand a text instruction, a machine learning model to make a prediction, and RPA activities to take action in enterprise apps. Agent Builder enables you to combine and customize AI components and classical automation steps as building blocks for the agent’s behavior. Critically, it also provides tools to test and refine the agent before it is produced. Users can run the agent in realistic workflows, debug its decisions, and even get an “Agent Score” - a metric that evaluates the agent’s performance against expected outcomes. This scoring, along with an Agent Optimizer, helps ensure your AI agents are enterprise-grade (accurate, reliable, not hallucinating or going off-script) before they’re deployed widely. When it comes to deployment, Agent Builder offers flexibility: a finished agent can be packaged as an activity that is invoked within existing RPA workflows (allowing you to integrate intelligence into legacy automations), or it can be published as an agentic task orchestrated by UiPath Maestro within a broader process. In both cases, the agent runs within the UiPath platform’s governance envelope. This focus on enabling “citizen developers” and professional developers alike to create custom AI agents is a huge part of UiPath’s strategy. “Providing customers the ability to build their own specialized agents in a simple, low-code IDE or from a pre-built template makes it easy to automate new use cases, avoid costs, and stay ahead of competitors,” notes UiPath’s Chief Product Officer. Large enterprises and partners (like consulting firms) are already exploring this - Deloitte, for example, participated in previews of Agent Builder and identified diverse use cases across both internal systems and SaaS apps, positioning UiPath as “the orchestration engine of the agentic age.” With Agent Builder, organizations can encapsulate proprietary know-how into AI agents and continuously expand their automation portfolio as new opportunities emerge. ## [UiPath Autopilot](https://www.uipath.com/product/autopilot) – Generative AI Assistant for Automation Generative AI also plays a starring role in UiPath’s agentic AI suite, primarily through UiPath Autopilot™. Autopilot is described as “a new set of AI-powered experiences across the UiPath Platform that make every user, from interns to CEOs, more productive.”. In practice, Autopilot is like having a smart copilot (no pun intended) for automation work. It utilizes powerful Generative AI models (LLMs) under the hood to enable users to create and interact with automations through natural language. For example, with Autopilot, you can simply describe a workflow you want automated (in plain English) and get a “text to workflow” generation – the platform will build a suggested automation sequence for you. This lowers the barrier to using the UiPath platform, enabling business analysts or less-technical staff to automate processes without writing code. Autopilot can also generate complex expressions or code snippets from natural language (“text to expression”), assist in creating UI apps, and more. It’s akin to having a ChatGPT-like assistant trained for UiPath development. One notable Autopilot experience is in UiPath Studio and Assistant: users can have a conversational interface to build or run automations. In fact, UiPath made Autopilot available for free to encourage broad usage – “an AI tool that allows employees to automate workflows through a conversational interface (i.e., [ChatGPT-like](https://www.flobotics.io/claude-for-healthcare-automation))” on both Windows and Mac. This means a user could type, “Gather all invoices from emails and enter them into our accounting system,” and Autopilot would assemble an automation or an AI agent to do just that, pulling together the necessary activities and logic. It effectively bridges the gap between intent and execution, fast-tracking automation development. Another facet of Autopilot is its assistance to everyday users through UiPath Apps and Assistant. For example, it can integrate with a CRM system via Automation Co-Pilot (in-app assistant), enabling a salesperson to trigger an AI agent by asking, “Summarize the last quarter’s pipeline and draft a follow-up email.” (Notably, Automation Anywhere has a similarly named [Automation Co-Pilot ](https://www.automationanywhere.com/products/automation-co-pilot)feature – more on competitors later - underscoring that conversational AI control is a hot trend in automation.) It’s important to note that Autopilot is tightly integrated with UiPath’s governance features. All those AI-generated workflows still run with the same security, permissions, and auditing as any UiPath automation. Autopilot helps users specify the desired outcome to the AI agent, and the agent determines the necessary steps. It’s a clear example of agentic AI and generative AI working hand in hand: generative AI creates and suggests, while agentic AI plans and acts to carry it out. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## [UiPath Healing Agent](https://forum.uipath.com/t/uipath-healing-agent-community-public-preview/785139) – Self-Healing Automation with AI One of the unsung heroes of the agentic toolkit is the UiPath Healing Agent, which addresses a very practical pain point: broken automations. In [traditional RPA](https://www.flobotics.io/blog/robotic-process-automation), if a target application’s UI changes or an unexpected pop-up appears, automations tend to fail - requiring developers to manually update selectors or add new error handling. [The Healing Agent ](https://docs.uipath.com/agents/automation-cloud/latest/user-guide-ha/what-is-healing-agent)brings an AI-driven “self-healing” capability to these situations. It performs just-in-time analysis whenever a UI automation encounters an issue, and intelligently determines a recovery strategy. For instance, if a button that a robot clicks suddenly moves on the screen due to a UI redesign, the Healing Agent can analyze the DOM and suggest a new selector or locate the element’s new position. It may also insert a smart delay if a page is loading slowly, or automatically close an interfering overlay window. Essentially, it’s like an on-call mechanic that fixes your automation in real-time to keep it running. The Healing Agent provides two main benefits: - It can surface recommendations when an automation fails, presenting the developer (or operations team) with suggested fixes, such as updated selectors or code snippets, to handle the detected issue. This guidance speeds up maintenance dramatically. - It can self-heal on the fly by applying certain fixes automatically when safe to do so. UiPath had already introduced a robust fallback mechanism with its Unified Target technology (a way for bots to try alternate methods if a UI element is not found). The Healing Agent augments this with AI-driven strategies, enabling certain processes to recover without human intervention. For example, if a web app loads a bit slower today, the agent could dynamically wait longer or refresh the page, rather than failing. If a random modal appears, it could detect and close it before the bot continues. These capabilities are crucial in unattended scenarios (background automations on servers) where maximum uptime is desired, as well as in attended use (automation assisting a human), where unpredictable user actions or environmental hiccups can occur. By reducing downtime and manual fix efforts, Healing Agent increases the resilience and scalability of agentic automation. In a world where AI agents and robots collaborate on long-running processes, having them automatically adapt to minor changes means fewer breakdowns and happier operations teams. It’s worth noting this is a differentiator for UiPath – not all competitors have an equivalently advanced self-healing mechanism. The Healing Agent showcases how embedded AI can continuously watch over and optimize the “health” of automations, which is a huge value-add when enterprises run thousands of bots. ## Building and Customizing AI Agents: The Open Ecosystem A key question for enterprises is whether they must rely solely on UiPath’s out-of-the-box AI agents or can build their own and integrate other AI technologies. UiPath’s answer is an emphatic yes to openness and extensibility. The Agentic AI platform is designed as an open ecosystem, meaning it can incorporate third-party AI models, custom-built agents, and external tools into your automations. For example, UiPath has partnered closely with Microsoft and OpenAI – you can plug in the [Azure OpenAI ](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/overview)service or OpenAI APIs and use models like GPT-4 within UiPath’s Autopilot or your own agents, all governed by the AI Trust Layer. In fact, UiPath recently announced a bi-directional integration with [Microsoft Copilot Studio:](https://www.microsoft.com/en-us/microsoft-copilot/microsoft-copilot-studio) developers can orchestrate Microsoft’s Copilot agents alongside UiPath agents using Maestro, and even embed[ UiPath automations inside Microsoft’s AI workflows](https://www.uipath.com/newsroom/uipath-announces-bidirectional-integrations-with-microsoft-copilot-studio). This is a significant development – it means that if you’ve built some AI capabilities within the Microsoft ecosystem, UiPath can integrate them into a larger, more comprehensive process with full coordination. The integration enables cross-platform AI collaboration, orchestrating, for example, a [seamless flow where a Microsoft 365 Copilo](https://www.microsoft365.com/)t handles Outlook emails and a UiPath agent handles SAP transactions. Beyond Microsoft, UiPath supports various AI frameworks. They’ve introduced the ability to run [LangChain](https://www.uipath.com/solutions/technology/langchain) or LangChain-like agents (notably mentioned as “LangGraph”) natively on UiPath. This empowers more advanced AI developers to [use Python](https://www.flobotics.io/blog/uipath-python) and open-source AI libraries to create agents, then deploy them into UiPath’s environment without changing a single line of code. The benefit here is that the governance, security, and monitoring of UiPath (via the Trust Layer, etc.) will also apply to those custom agents, providing the best of both worlds: open innovation and enterprise control. Partners and internal teams can thus bring specialized AI research or domain-specific models into the fold. For instance, a partner might use a custom computer vision model for an agent that inspects product quality on an assembly line. They can integrate that model through UiPath’s AI Center or as a skill in Agent Builder, then orchestrate it with other tasks in Maestro. [UiPath’s Integration Service](https://www.uipath.com/resources/automation-demo/introducing-integration-service) and connector ecosystem allow linking into virtually any system or AI service. They offer pre-built connectors to popular AI services (such as Google, Amazon, and IBM), as well as a Connector Builder for custom solutions. The platform’s model-agnostic approach means you can swap out AI models as needed – for example, using a more accurate model for NLP as it becomes available – without redesigning your processes. This flexibility is crucial in the fast-moving AI landscape. It also underscores a philosophical difference: while some competitors might push you into their closed AI stack, UiPath is signaling that interoperability is a priority. As they put it, many providers are building “walled gardens,” but UiPath aims to let customers “focus on business outcomes without getting bogged down by technology limitations,” whether the tech is from UiPath or someone else. For CTOs and tech-savvy executives, this means investing in UiPath’s agentic AI platform doesn’t cut you off from other AI advances – you can incorporate the latest and greatest, including internal AI innovations your data science team develops. And your internal developers (with [Python](https://www.flobotics.io/blog/uipath-python) skills, for example) can contribute directly by building agents outside UiPath and then importing them in. This open yet governed model is likely to appeal to enterprises that want to avoid vendor lock-in and maintain an agile AI strategy. ## Agentic AI in the Automation Landscape: UiPath vs Competitors With every tech revolution comes a competitive race. UiPath may be a front-runner in agentic automation, but other major players are also vying to define this space: ## UiPath vs Competitors in Agentic AI Criteria | UiPath | Microsoft | Automation Anywhere | SS&C Blue Prism | Agent Orchestration | Full control with Maestro; multi-agent, human, bot coordination | Limited to the Microsoft stack; Copilot scope per app | Co-Pilot supports bots; less flexible orchestration | Basic orchestration; not agent-first | Integration Flexibility | Open platform; supports 3rd-party models, LangChain, APIs | Strong in Microsoft 365; limited external integration | Good API support; mostly cloud-native | Integration often requires external work | Agent Builder | Low-code builder + templates in Agent Builder | No builder; Copilot Studio for simple plugins | Early-stage tools; limited control | No native agent builder | Governance & Trust | Advanced Trust Layer; audit, access, model control | Basic Azure governance; less agent-specific | Some guardrails; still maturing | Strong on paper; less AI-specific | Workflow Support | Full stack: automation, orchestration, testing, AI agents | Good for tasks; lacks deep orchestration | Covers tasks; stitching needed for complex flows | Legacy-focused; AI workflows catching up | AI Model Openness | Model-agnostic; supports OpenAI, Azure, and custom agents | Tied to Microsoft-hosted models | Some support; limited plug-and-play | Limited flexibility; no open agent framework | ## [Microsoft (Copilot + Power Automate)](https://learn.microsoft.com/en-us/power-automate/copilot-overview) Microsoft has infused generative AI (Copilot) across its product suite – from Office apps to GitHub and the Power Platform. In the context of automation, Power Automate (Microsoft’s RPA tool) now features Power Automate Copilot, which allows users to build workflows by describing what they need in natural language, much like UiPath Autopilot. Microsoft’s strength is the deep integration of Copilot AI into everyday productivity tools (Teams, Outlook, Dynamics, etc.), essentially turning them into agentic assistants for end users. For example, a Microsoft 365 Copilot can summarize your emails and take actions such as scheduling meetings or drafting responses. However, Microsoft’s approach has historically been somewhat siloed – Copilot in one app helps with tasks within that app. They are rapidly evolving this, and with Copilot Studio, Microsoft introduced a way to create custom AI agents (called “plugins” or “skills” for Copilot) that can perform multi-step tasks across the Microsoft ecosystem. When Microsoft announced a partnership with UiPath, it enabled Copilot Studio agents to integrate with UiPath and leverage UiPath’s orchestration strengths. This suggests that rather than directly competing in complex, cross-system processes, Microsoft is leveraging UiPath to extend Copilot’s reach beyond the Microsoft cloud. That said, for organizations heavily in the Microsoft stack and with simpler automation needs, Power Automate plus Copilot might appear as a one-stop solution. Microsoft’s brand and existing footprint are strong, but in agentic AI, they are still primarily focused on generative AI content creation and user assistance. UiPath provides more end-to-end process orchestration across diverse systems (including non-Microsoft systems), which can be a deciding factor for enterprises with heterogeneous environments. ## [Automation Anywhere](https://www.automationanywhere.com/products/automation-co-pilot) [Automation Anywhere,](https://www.flobotics.io/blog/uipath-vs-aa) another RPA leader, has explicitly jumped into the agentic automation fray. They even refer to their platform as an “Agentic Process Automation System” in their marketing materials. AA’s flagship in this domain is Automation Co-Pilot, an AI-powered assistant embedded in applications to connect people with automation and AI. Automation Co-Pilot is “powered by generative AI”, allowing natural language commands and multi-step automations similar to UiPath’s Autopilot. A user in a CRM or an ERP can invoke Co-Pilot in plain language to fetch data or execute a process without leaving their screen. AA has showcased use cases, such as an insurance claims process where Co-Pilot orchestrates multiple bots and AI to handle a claim end-to-end with minimal human intervention. They emphasize being the “Leader in Agentic Process Automation” (a bold claim, evidenced by their website footer) and have introduced governance features (guardrails for AI usage, etc.) to compete with UiPath’s trust layer. In comparison, AA’s approach is quite similar conceptually – combining generative AI for ease of use with RPA and AI to enable autonomous workflows. However, Automation Anywhere’s platform has historically been less unified than UiPath’s and may require more stitching together of components. AA’s Document Automation (IDP) is praised as best-in-class by some users, and they tout a strong ROI for their automation solutions. Yet, UiPath has an edge in breadth: a larger activities library, a built-in process mining tool, a dedicated test suite, and now the full agentic suite (Maestro, etc.), which AA is still catching up to. For many enterprises, the scalability and security demonstrated by UiPath in large deployments give it a competitive edge. Still, AA’s focus on “quick-thinking automation” and its own use of the term agentic indicate that they are a close competitor in vision. The choice may come down to existing ecosystem investments and specific feature preferences (e.g., AA’s cloud-native architecture vs UiPath’s hybrid options). ## [SS&C Blue Prism](https://www.blueprism.com/resources/blog/generative-ai-vs-agentic-ai/) Blue Prism, now part of SS&C, was a pioneer in RPA for enterprises. They, too, are reshaping their narrative around agentic AI, often using the term “Digital Workers” for their bots evolving with AI capabilities. Blue Prism explicitly differentiates Generative AI vs Agentic AI, mirroring UiPath’s messaging that generative AI creates content while agentic AI takes action towards a goal. The company speaks of an[ “Agentic Enterprise” ](https://www.blueprism.com/resources/blog/generative-ai-vs-agentic-ai/)and positions their solution as “governed, enterprise-level intelligent automation that combines AI with agentic orchestration, process mining, and other tech”. In practice, Blue Prism is integrating with partners for AI (they have connections with AWS, Google, and others for AI services) and emphasizing strong governance (they have an AI Ethics and Governance framework, akin to UiPath’s Trust Layer focus). They have published guides on [“Path to Agentic AI”](https://www.blueprism.com/resources/white-papers/path-to-agentic-ai/), indicating thought leadership, and cite stats like 29% of business leaders are starting to leverage agentic AI - showing market interest. However, in terms of ready product offerings, Blue Prism’s capabilities are perceived as a bit behind the curve. They were late to adopt cloud and lagged on built-in AI features (relying more on third-party AI via API). Now, under SS&C, they have resources to invest; however, enterprises evaluating agentic AI today will find UiPath’s tools more mature and immediately usable. Blue Prism may appeal to companies already using RPA who want to gradually extend it with AI, especially in highly regulated industries where SS&C has domain expertise. They have case studies of deploying thousands of “agents” (which might refer to their bots) in operations. But as of 2025, UiPath and AA appear to have more concrete agentic AI toolsets. Blue Prism’s strategy leans on its process orchestration strengths and promises of an “autonomous digital workforce”. The competitor landscape could shift as Blue Prism rolls out its next-gen platform (they mention a “Next Generation” cloud-native platform). For now, UiPath holds a lead in delivering a unified, agent-based automation platform that has already proven itself in the field. In summary, Microsoft, Automation Anywhere, and Blue Prism all recognize the importance of agentic AI and are integrating AI agents into their automation visions. Microsoft leverages its massive user base and AI research might, AA focuses on an AI-assisted RPA experience with Co-Pilot, and Blue Prism doubles down on orchestrating AI with governance. Yet, UiPath’s positioning is relatively unique: it combines the best of RPA (robotic precision) with the best of AI (autonomy and learning) on a single platform, and it has made notable moves (like the Microsoft partnership and open LangChain integration) to avoid isolation. For enterprise buyers, this means UiPath can fit into a heterogeneous environment and even enhance other investments (like using UiPath to orchestrate Power Automate or other agents). The competitor offerings are compelling in their own right, but UiPath’s agentic AI suite currently stands out for its completeness and emphasis on end-to-end automation rather than just task or assistant-level AI. ## Conclusion: Takeaways for Enterprise Leaders UiPath’s Agentic AI platform represents the next evolution of enterprise automation - where autonomous AI agents collaborate with robots and people to drive complex processes, boost productivity, and unlock new business value. From tools like Maestro and Agent Builder to governance through the AI Trust Layer, UiPath provides a robust and scalable environment for building, deploying, and managing intelligent automation across the organization. Want to explore the UiPath Agentic offer further? Get in touch with us. We’re a [certified UiPath partner](https://www.flobotics.io/uipath-services) with deep expertise in automation strategy, AI agent deployment, and end-to-end process transformation. Whether you’re just starting with automation or ready to scale agentic AI across departments, we can help you design and implement the right solution for your business. [Let’s build the future of intelligent workflows](https://www.flobotics.io/contact) together. Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Claude for Healthcare Overview | 2026 Canonical: https://www.flobotics.io/blog/claude-for-healthcare Author: Jędrzej Szymula Published: 2026-05-06 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Claude for Healthcare Overview | 2026 [AI](https://www.flobotics.io/blog?category=ai)[Healthcare](https://www.flobotics.io/blog?category=healthcare) # Claude for Healthcare Overview | 2026 [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published May 06, 2026Updated September 1, 2026 On this page - [Claude for Healthcare at J.P. Morgan 2026](#claude-for-healthcare-at-j-p-morgan-2026) - [What Claude for Healthcare Actually Includes?](#what-claude-for-healthcare-actually-includes) - [CMS Integration and Prior Authorization](#cms-integration-and-prior-authorization) - [ICD-10 and CPT Medical Coding Skill](#icd-10-and-cpt-medical-coding-skill) - [EHR Integration via HealthEx](#ehr-integration-via-healthex) - [PubMed and Scientific Literature Integration](#pubmed-and-scientific-literature-integration) - [Microsoft Foundry Integration](#microsoft-foundry-integration) - [Clinical Benchmarks: What the Research Shows About Claude For Helathcare?](#clinical-benchmarks-what-the-research-shows-about-claude-for-helathcare) - [MMLU Medical Performance](#mmlu-medical-performance) - [Multi-Step Clinical Reasoning and Self-Correction](#multi-step-clinical-reasoning-and-self-correction) - [Real-World Deployments: Who Is Using Claude and How](#real-world-deployments-who-is-using-claude-and-how) - [Banner Health: BannerWise at Scale](#banner-health-bannerwise-at-scale) - [Novo Nordisk and Genmab: Life Sciences R&D](#novo-nordisk-and-genmab-life-sciences-r-d) - [Novartis: Preclinical Toxicity Prediction](#novartis-preclinical-toxicity-prediction) - [Clinical Trial Protocol Design](#clinical-trial-protocol-design) - [HIPAA Compliance: The Details That Matter](#hipaa-compliance-the-details-that-matter) - [Which Products Are HIPAA-Eligible](#which-products-are-hipaa-eligible) - [Zero Data Retention (ZDR)](#zero-data-retention-zdr) - [Claude Code and Hospital IT Development](#claude-code-and-hospital-it-development) - [Same Fight. Different Weapons: The Big Four Battle for US Healthcare](#same-fight-different-weapons-the-big-four-battle-for-us-healthcare) - [Implementation Priorities: Where the ROI Is](#implementation-priorities-where-the-roi-is) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) AI has moved from a speculative topic in healthcare boardrooms to an operational infrastructure layer. Among the models competing for this space, Anthropic's Claude has emerged as a technically distinctive option — one whose architecture, safety guarantees, and rapidly expanding native integrations have made it a compelling choice for organizations operating under the regulatory and clinical pressures unique to healthcare. This guide synthesizes the state of Claude for Healthcare as of May 2026: what Anthropic has actually built, what it performs like in clinical benchmarks, who is deploying it and how, and what implementation teams need to understand before they start. ## Claude for Healthcare at J.P. Morgan 2026 In January 2026, during the [J.P. Morgan Healthcare Conference](https://www.fiercehealthcare.com/ai-and-machine-learning/jpm26-anthropic-launches-claude-healthcare-targeting-health-systems-payers), Anthropic announced Claude for Healthcare — a dedicated set of tools and integrations designed to connect Claude's reasoning capabilities with the data infrastructure that US healthcare organizations actually run on. The announcement marked a significant strategic escalation: rather than offering a general-purpose model that healthcare organizations could adapt, Anthropic is now delivering purpose-built connectors, skills, and compliance structures designed specifically for clinical and administrative use cases. The launch was not Anthropic's first move into the life sciences space. In October 2025, the company had released [Claude for Life Sciences](https://www.anthropic.com/news/healthcare-life-sciences), which focused primarily on research and pharmaceutical applications. Claude for Healthcare extends that foundation into clinical operations, revenue cycle management, and patient-facing workflows — areas where the stakes, the regulatory complexity, and the volume of manual administrative work are highest. Notably, the announcement came less than 24 hours after OpenAI unveiled its own healthcare-focused offering, signaling that the competition for AI infrastructure in healthcare has moved from concept to direct product rivalry. ## What Claude for Healthcare Actually Includes? Claude for Healthcare is best understood not as a single product but as a layered set of capabilities — native integrations to medical databases, a HIPAA-compliant infrastructure tier, and specialized skills for clinical and administrative workflows. Understanding each layer is essential for accurate scoping of what any implementation will and will not handle. ### CMS Integration and Prior Authorization One of the most operationally significant components of the Claude for Healthcare launch is a native connector to the [Centers for Medicare & Medicaid Services (CMS) Coverage Database](https://www.cms.gov/). This integration allows Claude to pull payer coverage requirements in real time, verify local coverage determinations, and check prior authorization criteria against patient clinical data — all within a HIPAA-eligible environment. The practical application is substantial. Prior authorization represents one of the most labor-intensive and error-prone workflows in US healthcare. The American Medical Association's annual survey has consistently found that the process consumes more than fourteen physician hours per week in a typical practice. With the CMS connector, Claude can automatically surface coverage requirements for a given procedure or medication, check clinical criteria against patient records, and propose an authorization determination with supporting documentation — leaving the final decision to the reviewing clinician or administrative staff. This is a human-in-the-loop model: Claude augments the process, it does not replace the oversight. ### ICD-10 and CPT Medical Coding Skill A dedicated coding skill allows Claude to map physician notes and clinical documentation to ICD-10 diagnostic codes and CPT procedure codes automatically. Rather than requiring coders to manually extract billable diagnoses from often lengthy and unstructured clinical notes, Claude analyzes the documentation and proposes a coding assignment with reasoning — which a coder can then review, modify, and approve. The revenue cycle implications are meaningful. Coding errors — whether undercoding that leaves revenue unrealized or upcoding that creates compliance exposure — are a persistent source of financial leakage in healthcare organizations. Automating the first-pass coding step with a model that can reason across complex clinical language reduces both error rates and the time coders spend on straightforward cases, freeing capacity for the complex encounters that genuinely require human expertise. ### EHR Integration via HealthEx Through a partnership with [HealthEx](https://fortune.com/2026/01/11/anthropic-unveils-claude-for-healthcare-and-expands-life-science-features-partners-with-healthex-to-let-users-connect-medical-records/), Claude now has access pathways to patient health records stored in Apple Health and Android Health Connect. This integration enables patients — with appropriate consent — to connect their personal health data and ask Claude natural-language questions about their own medical history, lab results, and care trajectories. For health systems building patient engagement infrastructure, this represents a meaningful capability: AI-assisted navigation of personal health data that can reduce the burden on clinical staff for routine informational queries while improving patients' understanding of their own conditions. The HealthEx partnership routes this access through HIPAA-eligible infrastructure, maintaining the compliance posture required for clinical deployment. ### PubMed and Scientific Literature Integration For life sciences applications, Claude's native integrations extend to [PubMed](https://pubmed.ncbi.nlm.nih.gov/) and 10x Genomics datasets. New skills allow Claude to search scientific literature, identify contradictions across published studies, and generate testable research hypotheses complete with full citations. This moves the model beyond summarization toward genuine scientific synthesis — a capability with obvious applications in pharmaceutical R&D, where the volume of published literature consistently outpaces any individual researcher's ability to stay current. ### Microsoft Foundry Integration For organizations running on Microsoft's cloud infrastructure, Claude is now available through [Microsoft Foundry](https://www.microsoft.com/en-us/microsoft-cloud/blog/healthcare/2026/01/11/bridging-the-gap-between-ai-and-medicine-claude-in-microsoft-foundry-advances-capabilities-for-healthcare-and-life-sciences-customers/), providing a deployment path that fits within existing Azure-based healthcare architectures. This integration means healthcare organizations do not need to build new cloud infrastructure to access Claude — they can deploy through the Microsoft environment their compliance and security teams have already reviewed and approved. ## Clinical Benchmarks: What the Research Shows About Claude For Helathcare? Deploying AI in clinical environments demands a higher standard of evidence than most enterprise software decisions. The benchmark data available as of 2026, drawn from academic publications and Anthropic's own reported evaluations, provides a useful but incomplete picture of where Claude performs well and where caution remains warranted. ### MMLU Medical Performance Research published in JAMA Network Open (April 2026) evaluated Claude 3.5 Sonnet and Claude 4.5 Opus on the MMLU medical and biology subsets. Both models achieved scores above 90%, placing them in a performance tier that exceeds many practicing physicians on standardized knowledge assessments. These results are consistent with Anthropic's own reported benchmarks and with independent evaluations conducted by academic medical centers. The researchers noted an important nuance, however: while Claude performed well at reaching a final diagnosis, it demonstrated a tendency toward conservatism in deciding which next diagnostic steps to recommend. In other words, the model is strong at diagnostic reasoning but more cautious than clinicians in recommending specific follow-up tests. Whether this conservatism is a feature or a limitation depends entirely on the clinical context. For a decision-support tool in a resource-constrained environment, clinical conservatism may be appropriate. For an application designed to accelerate diagnostic workup, it may require calibration. ### Multi-Step Clinical Reasoning and Self-Correction In internal evaluations, Anthropic has documented Claude's capacity for extended reasoning chains — the model can work through more than 100 reasoning steps when it detects an inconsistency between its initial diagnostic conclusion and the underlying laboratory data. This self-correction capability is particularly relevant for complex cases where the clinical picture evolves as new information becomes available. A model that can recognize and revise an earlier conclusion when confronted with contradictory evidence behaves more like a careful clinician than a pattern-matching classifier. This extended reasoning also reduces the hallucination risk that has made clinical AI deployment contentious. Claude's Constitutional AI architecture is designed to make the model acknowledge uncertainty rather than generate confident-sounding responses when the underlying evidence is weak — a property that Banner Health's CTO, Michael Reagin, cited explicitly when explaining why the organization chose Claude for its enterprise deployment. Fig. 01 · Claude Accuracy, % Medical benchmark performance - MedAgentBench - MedCalc Bench | Sonnet 3.5 | Haiku 4.5 | Sonnet 4.5 | Opus 4.5 | MedAgentBench | 69.6% | 83% | 91% | 92.3% | MedCalc Bench | 21.8% | 67.4% | 81.9% | 84.9% | Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Real-World Deployments: Who Is Using Claude and How ### Banner Health: BannerWise at Scale The most extensively documented real-world Claude for Healthcare deployment is BannerWise, the AI assistant built by [Banner Health](https://www.beckershospitalreview.com/healthcare-information-technology/ai/anthropic-rolls-out-claude-for-healthcare/) — a 33-hospital system based in Arizona with $15.6 billion in annual revenue and operations across six states. Banner deployed BannerWise to more than 55,000 employees in late 2025, making it one of the largest enterprise-wide AI rollouts in US healthcare to date. The initial clinical use case that drove adoption was oncology chart summarization. Manually summarizing an oncology patient record — which can run to hundreds of pages — required approximately eight hours of physician time per patient. With Claude handling the initial summarization, that process is automated, with the physician reviewing and validating the AI-generated summary. By the end of 2025, BannerWise had processed more than 1,400 clinical notes, with 80 to 85 percent of users reporting time savings and improved documentation accuracy. Banner's CTO, Michael Reagin, has been direct about what drove the selection: the model's documented tendency to acknowledge what it does not know, rather than generating plausible-sounding but incorrect answers. In a clinical environment where a confident hallucination could influence a care decision, this property is not a technical nicety — it is a safety requirement. ### Novo Nordisk and Genmab: Life Sciences R&D [Novo Nordisk](https://www.novonordisk.com/) and [Genmab](https://www.genmab.com/) have been identified as early adopters of Claude's life sciences capabilities, using the model to support pharmaceutical research workflows. These implementations focus on literature synthesis, hypothesis generation, and the analysis of genomic and chemical datasets at a scale that would be impractical through manual research processes. ### Novartis: Preclinical Toxicity Prediction [Novartis](https://www.novartis.com/), working through the Axiom platform, is applying Claude to predict drug toxicity at the preclinical stage. The model analyzes billions of tokens of genomic and chemical data to identify toxicity signals before compounds enter expensive clinical testing phases. Accelerating preclinical screening has long been one of the clearest ROI opportunities in pharmaceutical R&D — the costs of identifying a toxic compound after Phase I trials are orders of magnitude higher than catching it in preclinical analysis. ### Clinical Trial Protocol Design In clinical trial design, Claude is being applied to help optimize study protocols — particularly endpoint selection for complex conditions like Parkinson's disease. The goal is to select trial endpoints that are both clinically meaningful and aligned with regulatory expectations, improving the probability of approval without compromising scientific validity. This is a domain where the combination of deep literature synthesis, regulatory knowledge, and structured reasoning across complex data is genuinely differentiated from traditional decision-support tools. ## HIPAA Compliance: The Details That Matter For any healthcare organization evaluating Claude, HIPAA compliance is not a checkbox item — it is the prerequisite that determines whether a deployment is legally permissible. Anthropic updated its [Trust Center](https://www.anthropic.com/news/healthcare-life-sciences) in conjunction with the Claude for Healthcare launch, and the details are specific enough to warrant careful reading. ### Which Products Are HIPAA-Eligible Only two Anthropic products are covered by a Business Associate Agreement (BAA): the Enterprise plan of Claude.ai and the native (1P) Anthropic API. Consumer products — Claude Pro, Claude Team — are explicitly excluded. Organizations processing Protected Health Information (PHI) through consumer-tier products are not HIPAA-compliant, regardless of any other security measures they have in place. This is not a gray area: it is a binary distinction with direct legal consequences. Third-party platforms that offer Claude through their own infrastructure (AWS Bedrock, Google Cloud Vertex AI, Microsoft Foundry) operate under separate BAAs with Anthropic. Organizations using Claude through these platforms need to verify the compliance posture of the platform, not Anthropic's, as the relevant regulatory coverage. ### Zero Data Retention (ZDR) As of April 2026, Anthropic's native API is classified as an Eligible Service under its BAA without requiring a Zero Data Retention configuration. This change — from the previous requirement that ZDR be explicitly enabled for BAA coverage — simplifies the compliance posture for organizations that need to maintain logs and audit trails of AI interactions within their systems. Healthcare organizations can now implement standard logging and auditing practices alongside Claude deployments without compromising their BAA coverage. ### Claude Code and Hospital IT Development Anthropic has also clarified the compliance status of Claude Code, its programming assistant tool. Certain Claude Code functions are now covered under the BAA, which means hospital IT teams can use Claude Code to build internal healthcare applications within a compliant framework. This opens a significant path for health systems that want to develop custom integrations — EHR connectors, workflow automation tools, internal analytics applications — using AI-assisted development without stepping outside their compliance boundary. ## Same Fight. Different Weapons: The Big Four Battle for US Healthcare Q1 2026 produced something unprecedented in enterprise software: four of the world's most powerful technology companies — Amazon, Anthropic, Microsoft, and OpenAI — each launched a dedicated healthcare AI platform within a span of less than three months. The competitive window was January 7 through March 5, 2026. The target is the $4.5 trillion US healthcare market, where administrative costs alone exceed $360 billion annually and where AI-driven automation is now the primary lever available to health systems fighting shrinking reimbursement margins. These four players are not entering from the same position, and they are not targeting the same workflows. Amazon arrives with EHR-native infrastructure and deep penetration into medical coding. Microsoft enters already embedded inside more than 50,000 hospitals through its M365 footprint and the Epic relationship. OpenAI is moving to own the enterprise policy layer — the discharge templates, prior authorization workflows, and documentation standards that define how clinical decisions get translated into billable events. And Anthropic is competing on the strength of its reasoning architecture and its claims and appeals knowledge base, the most legally complex and financially consequential corner of revenue cycle management. For healthcare organizations, the practical question is not which platform is best in the abstract. It is which platform addresses the specific workflow gaps costing the organization the most — and which deployment model fits within existing infrastructure agreements, compliance postures, and IT capacity. The comparison below maps each player to the workflows they hit hardest, how they are priced, and what their entry into the market actually means for RCM operations. | Amazon Connect Health | Anthropic Claude for Healthcare | Microsoft Dragon Copilot | OpenAI ChatGPT for Healthcare | Where they hit RCM hardest | Front-end + middle-office (identity, coding) | Back-end (denials, appeals, policy) | Middle-office (ambient docs + order entry) | Back-end (prior auth, discharge templates) | What's new in 2026 | Real-time EHR identity verification | Claims appeal + policy determination | Direct EPR order entry (Epic, etc.) | Discharge workflow automation | How you pay | $0.12 / case · $0.018 / min Usage-based · per-transcript / per-code | $3 / MTok Sonnet 4.6, cache at 0.1× · Per-token API + enterprise seat | Per-encounter billing May 2026 · bundled with M365 | Enterprise shared credits (no per-seat cap) | When you can buy it | GA Coding in preview | Wide access | Phased rollout | Wide access Enterprise | Why it matters to us | Owns intake + coding (our middle) | Best appeals knowledge base | Already inside 50K+ hospitals | Defines enterprise policy layer | Core RCM tech | Medical Coding SDK ICD-10 · CPT · E&M | Native CMS + ICD-10 connectors | GPT-5.2 reasoner with citations | Ambient coding Nuance / DAX | EHR strategy | EHR-native direct integration | FHIR API middleware | FHIR API middleware | Embedded DAX / Nuance | Market entry | Mar 5, 2026 | Jan 11, 2026 | Jan 7, 2026 | Mar 5, 2026 HIMSS | ‍ Reading this map from a Flobotics perspective, the most consequential observation is not which platform is technically superior — it is how different the revenue implications are depending on where in the RCM cycle an organization is losing money. If front-end eligibility and intake coding is the primary source of denials, Amazon's EHR-native approach and Medical Coding SDK represent the most direct path to improvement. If the problem is back-end: denials working, appeals management, and policy determination — the workflows where clinical and legal reasoning intersect — Claude's architecture and its native CMS connector make it the strongest fit. Microsoft's Dragon Copilot is the right choice for organizations whose primary gap is ambient documentation and order entry efficiency, particularly those already standardized on Epic within an M365 environment. And OpenAI's ChatGPT for Healthcare is best evaluated as an enterprise policy layer tool — strongest where the goal is standardizing the templates and workflows that translate clinical documentation into billing-ready output at scale. ## Implementation Priorities: Where the ROI Is For organizations planning a Claude for Healthcare deployment, the current evidence base points clearly to two areas where the return on investment is most demonstrated and most near-term. Revenue Cycle Management — specifically prior authorization automation and medical coding — offers the clearest financial case. The labor costs associated with prior auth processing, the denial rates driven by coding errors, and the administrative burden on clinical staff are all well-documented, well-measured, and directly addressable through Claude's native integrations. Organizations that have implemented comparable automation in these workflows consistently report denial rate reductions of 15 to 30 percent within 12 to 18 months. Life Sciences R&D — particularly genomic data synthesis, literature review, and preclinical analysis — offers the largest magnitude of potential impact, though the implementation complexity and timeline are correspondingly greater. For pharmaceutical organizations, the compounding effect of accelerating any stage of the drug development pipeline is substantial. The critical first step for any organization, regardless of use case, is the same: move to Enterprise API, execute the BAA, and establish the compliance infrastructure before any PHI touches the system. Everything else — the integrations, the workflow design, the change management — is built on that foundation. This article draws on Anthropic's official announcements, published reporting from Fierce Healthcare, Becker's Hospital Review, TechCrunch, Fortune, and the Microsoft Cloud Blog, as well as research published in JAMA Network Open. Information reflects the state of Claude for Healthcare as of May 2026. Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPAAI ### Agentic AI Frameworks | 2026 Agentic AI frameworks in 2026: which stacks Google and other leaders are betting on, explained with clear, research-backed answers. Jędrzej SzymulaDecember 02, 2025 ](https://www.flobotics.io/blog/agentic-ai-frameworks)[ AI ### Agentic AI Workflows Agentic AI workflows, explained: how autonomous AI agents handle multi-step RCM tasks beyond traditional rule-based RPA. February 04, 2026 ](https://www.flobotics.io/blog/agentic-ai-workflows)[ RPAAI ### Agentic AI Tools and Platforms Overview 2026 Agentic AI platforms for 2026: an overview of the tools driving autonomous workflows, plus Gartner's cost-saving forecast. Jędrzej SzymulaSeptember 16, 2025 ](https://www.flobotics.io/blog/agentic-ai-tools-platforms-overview) [All articles →](https://www.flobotics.io/blog) --- # Claim Turnaround Time (CTT): Benchmarks and Root Causes Canonical: https://www.flobotics.io/blog/claim-turnaround-time-ctt-explanation Author: Krzysztof Szwed Published: 2026-05-04 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Claim Turnaround Time (CTT): Benchmarks and Root Causes [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Claim Turnaround Time (CTT): Benchmarks and Root Causes [Krzysztof SzwedHead of Delivery at Flobotics](https://www.flobotics.io/our-editorial-team#szwed) Published May 04, 2026Updated September 1, 2026 On this page - [What Is Claim Turnaround Time (CTT)?](#what-is-claim-turnaround-time-ctt) - [Why CTT Matters to Your Bottom Line](#why-ctt-matters-to-your-bottom-line) - [Industry Benchmarks](#industry-benchmarks) - [Root Causes of High CTT](#root-causes-of-high-ctt) - [How Automation Compresses CTT](#how-automation-compresses-ctt) - [Related Metrics](#related-metrics) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Is Claim Turnaround Time (CTT)? Claim Turnaround Time (CTT) is the average number of calendar days between the date a claim is submitted to a payer and the date payment is received and posted. It is one of the most closely tracked velocity metrics in RCM because it directly converts delivered services into received revenue — anything slowing that conversion affects cash flow. CTT reflects the combined quality of your entire revenue cycle: eligibility accuracy, documentation completeness, coding precision, submission speed, and posting efficiency. A long CTT is almost always symptomatic of failures across multiple steps. ## Why CTT Matters to Your Bottom Line Payroll, supplies, and overhead continue accumulating while claims wait to be paid. When CTT climbs, the gap between service delivery and cash receipt widens — forcing practices to carry higher AR balances and increasing write-off risk as claims age toward timely filing limits. CTT is causally linked to [Days in Accounts Receivable (DAR)](https://www.flobotics.io/blog/days-in-accounts-receivable-dar-explanation). A practice averaging 50-day CTT will structurally carry a much higher DAR than one averaging 18 days — even with identical patient volumes and payer mixes. Reducing CTT is often the fastest path to improving DAR without changing anything else. Payers in most U.S. states are legally required to process clean electronic claims within 30–45 days. Knowing your actual CTT by payer lets you identify when a payer is violating processing standards — and when to escalate. ## Industry Benchmarks - Best-in-class: 14–21 days (electronic, major commercial payers) - Acceptable: 30–45 days - At risk: 46–60 days — requires active payer investigation - Critical: 60+ days — indicates systemic failure in submission or payer communication Government payers (Medicare, Medicaid) typically process clean electronic claims in 14–30 days. Paper claims add 10–15 business days — reinforcing why electronic-only workflows are the operational baseline. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Root Causes of High CTT - High initial denial rate: Rejected claims require correction and full resubmission — doubling effective CTT - Missing prior authorization: Claims pended by payers pending auth validation add weeks - Eligibility errors: Invalid coverage data triggers immediate rejection - Slow payment posting: ERA/EOB data sitting unprocessed makes CTT appear longer even after payment arrives - Payer-specific rule non-compliance: Claims not meeting a payer's formatting requirements are pended rather than processed ## How Automation Compresses CTT [AI-powered claims management automation](https://www.flobotics.io/agents/claims-management-automation) eliminates the manual steps accounting for the majority of turnaround delay — from pre-submission scrubbing to post-payment posting. - Real-time [eligibility verification](https://www.flobotics.io/agents/eligibility-check-automation) before claim generation removes the most common denial trigger - Automated claim scrubbing applies payer-specific rules, catching errors before submission - Electronic submission within hours of service rather than end-of-day batch runs - Continuous payer portal monitoring flags pended claims within 24 hours for immediate action - Automated [payment posting](https://www.flobotics.io/blog/payment-posting-cash-posting-explanation) from ERA feeds eliminates the manual reconciliation backlog Organizations that automate end-to-end claims consistently report CTT reductions of 40–70%. See our [healthcare automation case studies](https://www.flobotics.io/case-studies) for documented results. ## Related Metrics CTT should always be analyzed alongside [Clean Claim Rate](https://www.flobotics.io/blog/clean-claim-rate-ccr-explanation), [Initial Denial Percentage](https://www.flobotics.io/blog/initial-denial-percentage-explanation), and [Days in AR](https://www.flobotics.io/blog/days-in-accounts-receivable-dar-explanation). A [comprehensive RCM automation strategy](https://www.flobotics.io/rcm-automation) addresses all four simultaneously. Written byKrzysztof Szwed Head of Delivery at Flobotics. [More from Krzysztof](https://www.flobotics.io/our-editorial-team#szwed) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### Clean Claim Rate (CCR): Definition and Benchmarks Clean Claim Rate (CCR) guide: the foundational RCM metric behind denials, DAR, and collections, with a 98%+ target. Bart TeodorczukJune 01, 2026 ](https://www.flobotics.io/blog/clean-claim-rate-ccr-explanation)[ HealthcareRCM ### Days in Accounts Receivable (DAR): Formula and Benchmarks Days in Accounts Receivable (DAR) guide: why 30-35 days is best practice and anything above 50 signals collection trouble. Krzysztof SzwedMay 21, 2026 ](https://www.flobotics.io/blog/days-in-accounts-receivable-dar-explanation)[ HealthcareRCM ### Net Collection Rate (NCR): Formula and Benchmarks Net Collection Rate (NCR) explained: the RCM metric measuring collectible revenue actually captured. Best practice is 95-99% - below that, revenue leaks. Bart TeodorczukJune 04, 2026 ](https://www.flobotics.io/blog/net-collection-rate-ncr) [All articles →](https://www.flobotics.io/blog) --- # Underpayment Recovery in Healthcare, Explained Canonical: https://www.flobotics.io/blog/underpayment-recovery-explanation Author: Jędrzej Szymula Published: 2026-05-04 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Underpayment Recovery in Healthcare, Explained [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Underpayment Recovery in Healthcare, Explained [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published May 04, 2026Updated September 1, 2026 On this page - [What Is Underpayment Recovery?](#what-is-underpayment-recovery) - [The Hidden Scale of Underpayment Revenue Leakage](#the-hidden-scale-of-underpayment-revenue-leakage) - [Root Causes of Underpayments](#root-causes-of-underpayments) - [How Automation Makes Underpayment Recovery Viable at Scale](#how-automation-makes-underpayment-recovery-viable-at-scale) - [Related RCM Metrics](#related-rcm-metrics) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Is Underpayment Recovery? Underpayment Recovery is the systematic process of identifying claims where actual payment received from a payer is less than the contractually agreed allowable amount, and then pursuing and collecting the balance owed. An underpayment occurs when a payer applies an incorrect fee schedule, makes a calculation error, misapplies a contract term, or processes a claim under the wrong contract — resulting in payment that is technically a partial denial of legitimately owed revenue. Unlike claim denials, which are explicit (the payer sends a denial with a reason code), underpayments are silent. A claim is processed and paid — just for less than the contractual allowable. Without a system to compare each payment against the correct contracted rate, underpayments accumulate undetected across thousands of claim lines. ## The Hidden Scale of Underpayment Revenue Leakage Industry data consistently places underpayment rates at 3–10% of all paid claims, depending on payer mix and contract complexity. For a health system processing $100M in annual net revenue, a 5% underpayment rate represents $5M in revenue that was owed, received partial payment, but never fully collected. This is not hypothetical — systematic underpayment is a well-documented payer behavior pattern, with state and federal regulators receiving provider complaints regularly. The revenue is theoretically recoverable — payers are contractually obligated to pay the agreed rate — but recovery requires identifying the discrepancy, documenting the correct contracted amount, filing a formal adjustment request, and following up through payer dispute processes. Without automation, this is impractical at scale. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Root Causes of Underpayments - Incorrect fee schedule application: Payer applies an outdated or wrong fee schedule when processing claims - Contract misinterpretation: Payer interprets a contract term differently — particularly on outlier clauses, carve-outs, and modifier applications - DRG downgrades: Inpatient claims processed at a lower DRG than documentation supports - Bundling errors: Services that should be reimbursed separately are bundled and paid at a combined rate below the sum of individual allowables - System loading errors at payer: Contract terms not correctly loaded in payer's adjudication system — particularly common at contract renewal ## How Automation Makes Underpayment Recovery Viable at Scale Manual underpayment review — comparing each posted payment against the correct contracted rate — is impractical at volume without technology. Automated underpayment detection within a [RCM automation program](https://www.flobotics.io/rcm-automation) works by: - Maintaining current contracted rates for all payers in a fee schedule management system - Automatically comparing each ERA payment line against the applicable contracted allowable at the point of [payment posting](https://www.flobotics.io/blog/payment-posting-cash-posting-explanation) - Flagging variances above a defined threshold for review and dispute filing - Generating dispute documentation with correct contract references automatically - Tracking dispute resolution timelines and escalating unanswered disputes Organizations implementing systematic underpayment recovery typically identify additional revenue of 1–5% of net collections annually. [Talk to us](https://www.flobotics.io/contact) about integrating underpayment detection into your payment posting workflow. ## Related RCM Metrics Underpayment recovery directly improves [Net Collection Rate (NCR)](https://www.flobotics.io/blog/net-collection-rate-ncr). It should be tracked alongside [payment posting accuracy](https://www.flobotics.io/blog/payment-posting-cash-posting-explanation) and [posting correspondence](https://www.flobotics.io/blog/posting-correspondence-explanation) processes — all three are part of the same cash application workflow in a mature [RCM automation program](https://www.flobotics.io/rcm-automation). Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ Healthcare ### Contractual Adjustment (Allowance): Meaning in Medical Billing Contractual adjustment (allowance), explained: why this write-off isn't lost revenue - and how mistracking hides real underpayments. Krzysztof SzwedMarch 20, 2026 ](https://www.flobotics.io/blog/contractual-adjustment-allowance-explanation)[ HealthcareRCM ### Credit Balance Resolution in Healthcare, Explained Credit balance resolution, explained: why federal law gives providers 60 days to repay Medicare and Medicaid overpayments. Jędrzej SzymulaMarch 18, 2026 ](https://www.flobotics.io/blog/credit-balance-resolution-explanation)[ HealthcareRCM ### Healthcare Reimbursements: How Payment Rates Are Set Healthcare reimbursement guide: how payment rates are set and where automation closes the gap between allowed and collected amounts. Karl MielnickiMay 01, 2026 ](https://www.flobotics.io/blog/reimbursements-explanation) [All articles →](https://www.flobotics.io/blog) --- # DrChrono EHR Automation | 2026 Canonical: https://www.flobotics.io/blog/dr-chrono-automation Author: Jędrzej Szymula Published: 2026-05-04 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/DrChrono EHR Automation | 2026 [AI](https://www.flobotics.io/blog?category=ai)[Healthcare](https://www.flobotics.io/blog?category=healthcare) # DrChrono EHR Automation | 2026 [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published May 04, 2026Updated September 1, 2026 On this page - [RCM Automation in 2026: When Revenue Cycle Management Becomes a Regulatory Mandate](#rcm-automation-in-2026-when-revenue-cycle-management-becomes-a-regulatory-mandate) - [The Structural Problem: Why Manual RCM Collapsed](#the-structural-problem-why-manual-rcm-collapsed) - [Regulatory Catalysts: The 2026 Inflection Point](#regulatory-catalysts-the-2026-inflection-point) - [Market Consolidation: Automate or Exit](#market-consolidation-automate-or-exit) - [The Mechanics: How Modern RCM Automation Actually Works](#the-mechanics-how-modern-rcm-automation-actually-works) - [Technical Integration Requirements](#technical-integration-requirements) - [Under the Microscope: Where Automation Creates New Risks](#under-the-microscope-where-automation-creates-new-risks) - [The Human Oversight Gap](#the-human-oversight-gap) - [Legal Accountability for AI-Generated Codes](#legal-accountability-for-ai-generated-codes) - [The Data Quality Dependency](#the-data-quality-dependency) - [When Automation Fails: Cautionary Examples](#when-automation-fails-cautionary-examples) - [Timeline to Transformation: The 2024-2026 Window](#timeline-to-transformation-the-2024-2026-window) - [2024: Foundation and Early Adoption](#2024-foundation-and-early-adoption) - [2025: The Decision Year](#2025-the-decision-year) - [2026: The New Normal](#2026-the-new-normal) - [The Economics: Cost Structure, ROI, and Strategic Value](#the-economics-cost-structure-roi-and-strategic-value) - [DrChrono Pricing Architecture](#drchrono-pricing-architecture) - [Concrete Cost Example](#concrete-cost-example) - [ROI Analysis: Before and After Automation](#roi-analysis-before-and-after-automation) - [Five-Physician Practice ROI Model](#five-physician-practice-roi-model) - [Beyond ROI: Strategic Value of Automation](#beyond-roi-strategic-value-of-automation) - [Comparative Market Context](#comparative-market-context) - [Strategic Implications for Healthcare Leaders](#strategic-implications-for-healthcare-leaders) - [For Chief Executive Officers and Practice Presidents](#for-chief-executive-officers-and-practice-presidents) - [For Chief Financial Officers](#for-chief-financial-officers) - [For Chief Technology Officers and IT Directors](#for-chief-technology-officers-and-it-directors) - [For Medical Directors and Clinical Leadership](#for-medical-directors-and-clinical-leadership) - [Final Perspective: Automation as Infrastructure, Not Innovation](#final-perspective-automation-as-infrastructure-not-innovation) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## RCM Automation in 2026: When Revenue Cycle Management Becomes a Regulatory Mandate The $240 billion question facing American medical practices is no longer whether to automate revenue cycle management, but whether they can afford not to. As the Centers for Medicare & Medicaid Services (CMS) Prior Authorization Final Rule takes effect in 2026, healthcare providers face a stark choice: modernize billing infrastructure or accept systematic revenue leakage as the cost of regulatory non-compliance. For practices processing between $500,000 and $8 million in annual collections–the operational sweet spot for most physician groups of five to fifteen doctors–the mathematics are unforgiving. Manual revenue cycle management hemorrhages 5-10% of gross revenues through coding errors, denied claims, and administrative inefficiency, according to Medical Group Management Association (MGMA) benchmarks. A five-physician practice collecting $3 million annually loses $150,000-$300,000 to preventable billing failures before a single patient walks through the door. The 2024-2026 window represents the final opportunity for voluntary adoption. After January 2026, prior authorization automation transitions from competitive advantage to table stakes–a mandatory infrastructure cost disguised as a compliance deadline. ## The Structural Problem: Why Manual RCM Collapsed American healthcare billing operates under a peculiar economic model: providers deliver services immediately but collect payment months later, contingent on navigating a Byzantine approval process involving multiple payers, thousands of billing codes, and constantly shifting coverage rules. This accounts receivable cycle–measured in days in A/R–directly determines practice solvency. Without automation, the typical practice experiences: - Clean claim rate of 75-82%, meaning nearly one in four claims submitted contains errors requiring manual rework - Denial rates of 10-15%, with each appeal consuming 30-45 minutes of staff time - Days in A/R stretching to 45-65 days, creating chronic cash flow pressure - Billing costs of $8-12 per claim, driven by labor-intensive manual data entry and reconciliation The cumulative effect resembles a hidden tax on operations. Consider a cardiology group with five physicians generating 800 claims monthly. At a 12% denial rate, 96 claims require rework. With staff costs of $35/hour and 45 minutes per appeal, monthly denial management alone costs $2,520–before accounting for delayed cash flow or lost revenue from abandoned appeals. This model functioned adequately when practice volumes were predictable and payer rules stable. Neither condition holds in 2025. ### Regulatory Catalysts: The 2026 Inflection Point Three concurrent regulatory shifts have transformed RCM automation from efficiency play to existential requirement: CMS Prior Authorization Final Rule (2026): Beginning January 1, 2026, Medicare Advantage and Medicaid managed care plans must implement real-time prior authorization decisions for routine services. Practices lacking API-enabled systems capable of submitting and tracking authorizations electronically will face systematic delays. The American Medical Association's 2024 survey documented that prior authorization currently consumes 14 days on average; automated workflows compress this to 1-2 days for standard requests. This is not marginal improvement–it represents the difference between initiating treatment within the clinically appropriate window and watching patients deteriorate while awaiting approval. ICD-12 Preparation: The transition from ICD-10 to ICD-12 coding, though not finalized for implementation, requires practices to maintain coding systems capable of rapid adaptation. Manual coding operations required 18-24 months to transition from ICD-9 to ICD-10; AI-assisted platforms can retrain coders and validate new codes in 4-6 weeks. Heightened Compliance Audits: The Office of Inspector General (OIG) has intensified scrutiny of billing patterns, with Recovery Audit Contractor (RAC) programs specifically targeting practices with anomalous denial rates or coding patterns. Clean claims–those accepted without modification on first submission–generate fewer audit flags. Practices maintaining 91%+ clean claim rates experience 70% fewer compliance inquiries than those hovering at the 75-82% manual baseline. The convergence is not coincidental. Federal policy explicitly aims to force digital infrastructure adoption through regulatory mandate rather than waiting for market-driven transformation. For solo practitioners and small groups lacking capital reserves for major technology investments, this creates acute pressure. ### Market Consolidation: Automate or Exit The broader context involves structural consolidation in American healthcare delivery. Private equity-backed physician management companies and hospital-employed physician models offer practitioners an alternative to independent practice: accept salary and clinical autonomy limitations in exchange for offloading administrative burden. For many physicians, particularly those within five years of retirement, selling to a hospital system or management company represents the path of least resistance. But for practices committed to operational independence, RCM automation becomes the defensive moat preventing forced consolidation. Platform vendors–DrChrono, Athenahealth, Kareo, AdvancedMD–have responded by integrating previously separate EHR and RCM functions into unified systems. This reduces implementation friction but creates new dependencies: practices must commit to comprehensive platform adoption rather than piecemeal automation. The market dynamics favor scale. Solo practitioners processing $500,000 annually struggle to justify 4-8% revenue cycle management fees on top of EHR costs. Groups of five or more physicians processing $2-8 million achieve ROI within 14-18 months. Below that threshold, automation frequently costs more than the savings it generates–explaining why consolidation pressures hit smallest practices hardest. ## The Mechanics: How Modern RCM Automation Actually Works Revenue cycle automation is not a single technology but an integrated workflow spanning patient scheduling through final payment reconciliation. Understanding the component parts clarifies where value accrues–and where vulnerabilities persist. Patient Scheduling & Eligibility Verification: Before the patient arrives, the system queries payer databases via API to verify active coverage, identify copayment amounts, determine referral requirements, and flag services requiring prior authorization. This prevents the most expensive category of denials: those stemming from lack of coverage. Real-time eligibility checks occur in 3-8 seconds; manual verification via phone requires 12-18 minutes and frequently provides outdated information. Clinical Encounter Documentation: The physician completes the encounter in the EHR, documenting diagnoses and procedures using clinical terminology. Here lies the critical first handoff between clinical and billing workflows. AI-Assisted Medical Coding: Natural language processing algorithms analyze clinical notes and suggest appropriate CPT (procedure) and ICD-10 (diagnosis) codes. Modern systems achieve 91-96% accuracy for routine encounters, matching or exceeding human coder performance for common scenarios. Complex cases–those involving multiple chronic conditions, unusual presentations, or investigational procedures–still require human review. Industry estimates suggest 15-25% of claims in multi-specialty practices require manual coding validation, though vendors rarely publish these figures. The AI does not autonomously assign codes. Rather, it presents suggestions to certified coders or physicians for approval, creating an auditable trail documenting who authorized each billing decision. This distinction matters critically for compliance: the physician retains legal accountability for coding accuracy, regardless of automation level. Claim Scrubbing & Validation: Before submission, automated scrubbers check claims against payer-specific rules–verifying that diagnosis codes support procedure codes, confirming gender and age appropriateness, flagging unbundling violations, and validating that services fall within covered benefits. This eliminates 60-80% of technical errors that generate immediate rejections. Electronic Claim Submission: Claims route through clearinghouses to appropriate payers via EDI (Electronic Data Interchange) protocols. Automation ensures proper formatting and tracks submission confirmation, eliminating the "black box" problem where practices submitted claims without confirmation of receipt. Electronic Remittance Advice (ERA) Auto-Posting: When payers process claims, they return ERAs detailing payments, adjustments, and denials. Automated posting systems reconcile these against submitted claims and update patient accounts without manual data entry–eliminating a major source of posting errors and reducing days in A/R by 10-15 days on average. Denial Management & Appeals: When claims are denied, AI systems categorize denial reasons, prioritize high-value appeals, and auto-generate appeal letters for standard denial categories. Analytics identify patterns–particular payers denying specific procedure codes, for instance–enabling proactive claim modification before submission. Patient Collections & Payment Plans: Automated systems generate patient statements, send payment reminders via text/email, offer online payment portals, and flag accounts requiring collections referral. This accelerates patient payment cycles from 60-90 days to 20-35 days for responsive patients. ### Technical Integration Requirements Modern RCM platforms function as cloud-based SaaS (Software as a Service) applications requiring minimal on-premise infrastructure. Key technical requirements include: API Integration: RESTful APIs and HL7/FHIR compliance enable real-time data exchange between EHR, practice management, and billing systems. Practices operating legacy systems lacking API capabilities face significant implementation friction. Payer Connectivity: Direct electronic connections to major payers (Anthem, UnitedHealthcare, Aetna, Medicare, Medicaid) enable real-time eligibility checks and prior authorization submission. Secondary and tertiary payers may still require manual phone verification. Implementation Timeline: Standard implementations require 6-12 weeks for mid-sized practices with clean EHR data. This assumes: - Historical claims data is accurate and complete - Staff receive training on new workflows - Payer enrollments are current - EHR documentation standards meet billing requirements Practices with poor data hygiene–inconsistent patient demographics, incomplete encounter documentation, or accumulated billing backlogs–require 4-6 months for data cleanup before automation delivers meaningful value. ## Under the Microscope: Where Automation Creates New Risks The efficiency gains from RCM automation are real and measurable. But automation transforms error types rather than eliminating them–and introduces novel compliance vulnerabilities that manual processes never encountered. ### The Human Oversight Gap AI-assisted coding accuracy of 91-96% sounds impressive until you calculate absolute error volumes. A practice generating 800 claims monthly with 95% AI accuracy produces 40 incorrect claims every month–480 annually. If each incorrect claim represents $200 in average reimbursement, potential annual exposure reaches $96,000. The critical question: which 4-5% of claims require human review, and how do practices systematically identify them? Most platforms use confidence scoring–flagging suggestions below certainty thresholds for manual validation. But confidence scores measure algorithmic certainty, not coding correctness. An AI can be confidently wrong. Best practice requires human-in-the-loop workflows where certified coders review: - All claims exceeding $1,000 in anticipated reimbursement - Any encounter involving more than three diagnosis codes - Procedures with documented high denial rates for that payer - New or rarely-used procedure codes - Any claim flagged by scrubbing algorithms This segregation of duties prevents the "automation bias" where staff accept AI suggestions uncritically because the system generated them. But implementing tiered review workflows requires deliberate process design–most practices simply default to trusting the AI completely or reviewing everything manually, negating efficiency gains. ### Legal Accountability for AI-Generated Codes Under federal anti-fraud statutes, the physician signing the claim bears ultimate responsibility for coding accuracy, regardless of whether a human coder or AI system generated the codes. This creates a gray area: if automated coding produces systematically incorrect claims that trigger payer audits, who bears liability? The legal framework remains unsettled. In 2024, no major False Claims Act cases have directly addressed AI coding liability. But the Office of Inspector General has signaled that automation does not absolve providers of fraud liability. Practices implementing AI coding should document: Algorithm Validation: Periodic audits comparing AI-suggested codes against gold-standard human coding for sample claims, with results documented for compliance defense. Physician Attestation: Workflow requirements that physicians explicitly approve AI-suggested codes rather than allowing automatic acceptance. Audit Trail Maintenance: Retention of all AI suggestions, human modifications, and approval timestamps for the six-year federal audit period. Without this documentation infrastructure, practices face elevated risk if an audit reveals systematic overcoding. The defense "the AI did it" will not satisfy prosecutors or payer fraud investigators. ### The Data Quality Dependency RCM automation operates on a fundamental principle: garbage in, garbage out. If EHR documentation is vague, inconsistent, or incomplete, even sophisticated AI cannot generate accurate codes. Common data quality failures include: - Inadequate specificity: Documentation stating "patient has diabetes" without specifying type, control status, or complications yields non-specific codes that payers reject as insufficient. - Copy-forward documentation: Physicians copying previous visit notes forward create documentation that doesn't reflect current encounter, confusing coding algorithms. - Missing linkage: Procedures documented without clear connection to supporting diagnoses trigger medical necessity denials. Successful automation requires "cleaning house" first–standardizing documentation templates, training physicians on billable documentation requirements, and resolving historical data inconsistencies. Practices skipping this foundational work implement automation on a structurally unsound base. ### When Automation Fails: Cautionary Examples Case Study: Primary Care Group, 8 Physicians, Midwest Implemented automated coding in 2023 to reduce billing staff costs. Initial clean claim rate improved from 79% to 88%. Within six months, rate deteriorated to 82% as physicians stopped reviewing AI suggestions, assuming system accuracy. Root cause: AI algorithms trained on historical claims data perpetuated existing coding errors. Practice eventually required comprehensive re-training and algorithm revalidation, costing $45,000 and six months of disruption. Case Study: Multi-Specialty Group, 12 Physicians, Southeast Adopted full RCM automation including patient collections. Automated text reminders and email billing statements triggered patient complaints about "impersonal" communication and confusion over billing amounts. Patient satisfaction scores declined 18 points. Practice ultimately hired patient financial counselors to provide human touchpoint for accounts exceeding $500–adding cost that negated collections efficiency gains. Lesson: Automation is Not "Set and Forget" Successful implementation requires continuous monitoring, periodic algorithm retraining, staff education, and maintenance of human escalation pathways for exceptions. Practices treating automation as replacement for expertise rather than augmentation of it face systematic failures. ## Timeline to Transformation: The 2024-2026 Window The adoption curve for RCM automation follows a clear chronology driven by regulatory deadlines and market maturity. ### 2024: Foundation and Early Adoption Basic claim submission automation has become industry standard–even small practices use electronic claim submission rather than paper. The differentiation lies in advanced capabilities: Early Adopters (15-20% of market): Practices implementing AI coding, predictive denial analytics, and proactive prior authorization workflows. These groups targeted 2024-2025 as preparation window for 2026 mandates. Market Consolidation: Major acquisitions (Athenahealth's RCM enhancements, DrChrono platform integrations) signal vendor investment in comprehensive automation platforms rather than point solutions. CMS Rulemaking: Final regulations for prior authorization automation published, establishing January 1, 2026 implementation deadline. This converts abstract future requirement into concrete project timeline. ### 2025: The Decision Year Calendar 2025 represents the last opportunity for deliberate, non-crisis implementation before regulatory deadline. Practices face critical decision points: Q1 2025: Vendor selection and contract negotiation. Procurement cycles for practice management technology typically require 8-12 weeks; groups beginning evaluation in Q1 can complete implementation by Q4. Q2-Q3 2025: Implementation and testing phase. Standard 6-12 week deployment windows position practices for October-November go-live, allowing 8-10 weeks of parallel operation and troubleshooting before the 2026 deadline. Q4 2025: Final quarter before mandate. Practices without signed contracts by October face elevated implementation risk. Vendor capacity constraints (limited implementation consultants, scheduling backlogs) will inflate costs and extend timelines as deadline approaches. The market will enter "seller's market" dynamics where practices compete for limited vendor implementation capacity. Critical Insight for CFOs: Automation investments authorized in Q1 2025 represent discretionary capital allocation. The same investments approved in Q4 2025 become emergency spending at premium pricing with compressed timelines. Budget impact differs by 30-50% based purely on timing. ### 2026: The New Normal January 1, 2026: CMS Prior Authorization Final Rule Takes Effect Medicare Advantage and Medicaid managed care plans must accept and process electronic prior authorization requests via API. Practices still relying on phone/fax prior authorization face systematic delays–potentially 3-5x longer processing times as payer staff prioritize electronic submissions. This doesn't prohibit manual submission, but creates two-tier system where automated practices receive preferential processing speed. Clinical implications are direct: orthopedic surgery prior authorizations taking 14 days via phone may process in 48 hours electronically. For time-sensitive procedures, this differential determines whether practices can offer clinically appropriate care. Market Maturity: Full AI-driven revenue cycle prediction becomes standard for practices exceeding $2 million in collections. Remaining manual operations concentrate in micro-practices (1-2 physicians) and subspecialties with unique billing requirements (behavioral health, FQHC) where standardized automation provides limited value. ICD-12 Preparation: Though not yet scheduled for implementation, ICD-12 code set development accelerates. Practices with AI coding infrastructure can rapidly retrain models on new codes; manual operations face 18-24 month transition periods similar to ICD-9 to ICD-10 conversion. Competitive Separation: The market bifurcates into automated practices operating at 91%+ clean claim rates with 28-35 days in A/R, and manual operations at 75-82% clean claim rates with 45-65 days in A/R. This 15-30 day cash flow differential compounds: automated practices reinvest freed capital into service expansion while manual practices struggle with chronic cash crunches. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## The Economics: Cost Structure, ROI, and Strategic Value Revenue cycle management automation involves three distinct economic questions: what does it cost, what does it save, and what strategic options does it create? ### DrChrono Pricing Architecture DrChrono–representative of mid-market RCM platforms–structures pricing based on practice size and service scope: Service Tier | Monthly Cost | Annual Collections Range | Pricing Model | Optimal For | EHR Only | $199-$499/provider | Up to $500K | Fixed subscription | Solo practices handling billing in-house or via separate vendor | EHR + RCM Managed Services | 4-8% of collections* | $500K-$2M | Percentage of net collections | Groups of 2-5 physicians seeking full-service outsourcing | Full RCM Automation | 4-6% of collections* | $2M-$8M | Percentage of net collections + SLA guarantees | Groups of 5-15 physicians with volume justifying premium service | Enterprise Custom | Negotiated | $8M+ | Custom contract terms | Large groups (15+ physicians) or management service organizations | Critical Pricing Note: Percentage-of-collections pricing means the vendor is paid based on actual cash collected, not on charges submitted. This aligns vendor incentives with practice revenue goals–if denial rates increase, vendor revenue declines. However, it also means practices cannot precisely budget RCM costs; they fluctuate with collection volume. *Industry context: The 4-8% range reflects market positioning. Athenahealth typically charges 6-8% for comprehensive RCM. Kareo ranges 5-7%. Premium 4% pricing usually requires minimum volume commitments or multi-year contracts.* ### Concrete Cost Example Five-Physician Primary Care Practice - Annual collections: $3 million - DrChrono Full RCM at 5% of collections - DrChrono’s yearly fee: $150,000 - Represents 5% of gross collections or approximately 6-7% of net revenue after overhead For context, the same practice operating manual billing typically employs: - 1.5 FTE billing specialists at $45,000 each = $67,500 - 0.5 FTE denial management at $50,000 = $25,000 - Practice management software = $18,000 - Clearinghouse fees = $12,000 - Total manual RCM cost: $122,500 So the fee alone costs $27,500 a year more than billing in-house ($150,000 vs $122,500). The practice comes out ahead only if the service collects more of what it’s owed and gets paid faster. The model below shows how that can happen. Keep in mind what this fee is: a percentage of your collections, paid every year for as long as you use the service. Having an automation built for your own systems is priced differently: you pay once for the build, plus maintenance. At Flobotics, most projects cost $15,000–$25,000, and maintenance is quoted with the project. See [our pricing](https://www.flobotics.io/pricing). ### ROI Analysis: Before and After Automation The value proposition for RCM automation rests on multiple performance improvements that compound to generate net positive return: Manual RCM Baseline (Industry Benchmarks) Clean Claim Rate: 75-82% | Days in A/R: 45-65 days | Initial Denial Rate: 10-15% | Cost per Claim: $8-$12 | Billing FTE per Physician: 1.2-1.5 Automated RCM Performance (DrChrono/Similar Platforms) Clean Claim Rate: 91-96% | Days in A/R: 28-35 days | Initial Denial Rate: 3-7% | Cost per Claim: $3-$6 | Billing FTE per Physician: 0.3-0.5 ### Five-Physician Practice ROI Model Baseline Annual Performance - Total collections: $3,000,000 - Claims volume: 9,600 annually (800/month) - Manual RCM cost: $122,500 - Denial rate: 12% (1,152 denied claims) - Average days in A/R: 55 days Post-Automation Performance Denial Reduction Impact - Denial rate improvement: 12% → 5% - Denied claims: 1,152 → 480 (672 fewer denials) - Recovery rate on denials: 60% (industry average) - Recovered revenue: 672 claims × $300 average × 60% = $121,000 Cash Flow Acceleration - Days in A/R reduction: 55 days → 30 days (25-day improvement) - Value of accelerated cash: $3M ÷ 365 days × 25 days = $205,000 in working capital - Opportunity cost at 6% annual return = $12,300 Labor Redeployment - Billing staff reduction: 1.5 FTE → 0.5 FTE - Cost savings: 1.0 FTE × $45,000 = $45,000 - Note: "Savings" assumes staff reduction or redeployment to revenue-generating activities; many practices reassign rather than terminate Reduced Cost per Claim - Cost reduction: $10 → $5 per claim - Annual savings: 9,600 claims × $5 = $48,000 Total Annual Value Creation Revenue Recovery (denials): $121,000 | Cash Flow Acceleration: $12,300 | Labor Cost Savings: $45,000 | Per-Claim Cost Reduction: $48,000 | Total Annual Benefit: $226,300 | Less: DrChrono’s yearly fee: -$150,000 | Net annual gain: $76,300 There is no payback period in this example, because there is no upfront cost to pay back. The fee is paid every year, so the practice gains about $76,300 in each year the assumptions below hold. Important Qualifications This model assumes: - Clean historical EHR data enabling rapid implementation - No significant payer mix changes during transition - Staff redeployment rather than pure cost elimination - Stable patient volume (automation value increases with scale) Practices with complex payer mixes (>40% Medicaid), poor documentation quality, or highly specialized billing requirements typically see 20-30% lower returns, and the gains take 6-12 months longer to appear. ### Beyond ROI: Strategic Value of Automation CFOs evaluating RCM automation based solely on 18-24 month payback calculations miss the strategic dimension: automation creates organizational capabilities that manual processes cannot replicate. Compliance Risk Mitigation Practices maintaining 91%+ clean claim rates attract significantly less regulatory scrutiny than those at 75-82% baselines. The Office of Inspector General's risk scoring algorithms flag practices with: - Denial rates exceeding peer group averages by >20% - Unusual coding patterns (e.g., disproportionate use of high-complexity E/M codes) - High volumes of corrected claims Automated coding with audit trail documentation provides affirmative defense in compliance investigations. The ability to demonstrate systematic validation processes and algorithm oversight substantially reduces False Claims Act exposure. Estimated value: Avoiding a single OIG audit costs $50,000-$150,000 in legal fees and administrative burden, not accounting for potential fines. Regulatory Agility When ICD-12 implementation eventually occurs, practices with AI coding infrastructure will complete transitions in 4-6 weeks versus 6-9 months for manual operations. This agility has direct revenue impact: delayed ICD-12 adoption means rejected claims during transition periods. More broadly, healthcare billing rules change constantly–new CPT codes, revised coverage determinations, altered prior authorization requirements. Automated systems update centrally and deploy changes across all practice locations simultaneously. Manual operations require individual coder training and introduce inconsistent application during learning curves. Competitive Positioning Transparent, rapid billing improves patient satisfaction and retention–particularly for high-deductible health plan patients sensitive to surprise bills. Practices offering real-time cost estimates, automated payment plans, and clear EOB explanations differentiate in increasingly consumer-driven healthcare markets. For physicians: modern technology infrastructure attracts talent. Young physicians increasingly reject joining practices still operating fax machines and paper superbills. Automation serves as recruitment tool. Organizational Scalability Manual RCM creates linear scaling constraints: growing from five to seven physicians requires proportional billing staff increases. Automation enables sublinear scaling: the same RCM platform supports 5, 10, or 15 physicians with minimal marginal cost increase. This matters critically for practices considering acquisition opportunities or service line expansion. Automated infrastructure removes billing capacity as growth bottleneck. ### Comparative Market Context This analysis focuses on DrChrono as representative of mid-market RCM automation platforms. Other major vendors–Athenahealth, Kareo, AdvancedMD, CareCloud–offer comparable capabilities with variations in pricing models, minimum practice size, and specialty focus. Key Competitive Differentiators: Athenahealth: Higher penetration in hospital-based practices and larger groups (10+ physicians), typically 6-8% of collections pricing, strong in complex prior authorization workflows. Kareo: Focuses on smaller practices (1-5 physicians), 5-7% collections pricing, simpler implementation but less sophisticated analytics. AdvancedMD: Popular in specialty practices (dermatology, ophthalmology), specialty-specific templates, mid-range pricing. The strategic decision involves matching platform capabilities to practice complexity rather than pursuing "best" vendor. Practices should evaluate: - Payer mix complexity (Medicare/Medicaid vs commercial) - Specialty-specific billing requirements - Existing EHR system and integration requirements - Implementation support during transition *Detailed vendor comparison exceeds this analysis scope. Practices should conduct structured RFP processes with minimum three vendor evaluations.* ## Strategic Implications for Healthcare Leaders The transition to automated revenue cycle management represents more than technological upgrade–it forces fundamental reconsideration of how practices allocate capital, structure operations, and compete for patients. ### For Chief Executive Officers and Practice Presidents Can our practice grow without RCM automation? Not sustainably. Revenue growth without billing infrastructure improvement creates "successful failure"–rising top-line revenues masking deteriorating margins as denial rates and A/R days balloon. Consider the mathematics: A practice growing 15% annually in patient volume without improving RCM efficiency experiences: - Proportional growth in billing complexity - Escalating denial management burden - Stretched cash flow as A/R days increase - Rising compliance risk from rushed coding After 2-3 years, the practice hits operational ceiling where all marginal revenue gets consumed by fixing billing problems. Growth stalls not from lack of patients but from inability to collect payment. The Strategic Frame: RCM automation is gate-keeper technology for scalability. Practices can remain small and manual, or grow and automate. The middle ground–large manual operations–proves economically unstable. Action Priority: Make the automation decision before growth pressure forces crisis implementation. Practices implementing under duress accept unfavorable vendor terms and compressed timelines that inflate costs 40-60%. ### For Chief Financial Officers Can we afford automation implementation in 2025? Can you afford NOT to implement before the 2026 mandate deadline? The financial analysis hinges on three factors: Cash Flow Timing: Percentage-of-collections pricing eliminates traditional CAPEX. Unlike major equipment purchases requiring upfront capital outlay, RCM automation costs flow monthly as operating expenses. This converts a budget-year problem into a cash flow management problem–measured in months, not years. Opportunity Cost of Delay: Every month of delay represents continued revenue leakage. A five-physician practice losing $20,000 monthly to preventable denials surrenders $240,000 annually, more than the $150,000 yearly fee in the example above. Risk-Adjusted Return: In the model above, each percentage point of denial rate reduction in a $3M practice is worth about $17,000 a year in recovered revenue (96 fewer denied claims × $300 average × 60% recovered). A 7-point reduction (12% → 5%) recovers about $121,000 a year before counting any cost savings. Model the ROI using practice-specific data–actual denial rates, current A/R days, verified payer mix–rather than industry averages. Then recognize that ROI calculation understates value by ignoring regulatory compliance benefits and strategic optionality. Budget authorization for RCM automation in Q1 2025 represents discretionary investment. The same authorization in Q4 2025 represents emergency spending at inflated pricing. CFOs should advocate for early action to preserve negotiating leverage. ### For Chief Technology Officers and IT Directors How quickly can we implement automation? Faster than traditional EHR conversions, but highly dependent on data quality. Standard implementation timeline: 6-12 weeks for practices with: - Clean historical claims data - Structured EHR documentation - Current payer enrollments - Staff available for training The critical path rarely involves technology–it involves data cleanup and workflow redesign. Practices attempting to automate on top of messy data simply automate chaos. Pre-Implementation Requirements: Data Audit (2-3 weeks): Review 6-12 months of historical claims for: - Patient demographic accuracy (addresses, DOB, insurance IDs) - Provider enrollment status and NPI accuracy - Procedure and diagnosis code validity - Claims with unusual adjudication patterns EHR Documentation Standardization (4-6 weeks): Establish templates ensuring: - Diagnoses documented to highest specificity level - Procedures linked to supporting diagnoses - Medical necessity clearly documented - Consistent terminology (avoiding ambiguous abbreviations) Payer Connectivity Testing (2-3 weeks): Validate electronic connections to all major payers, resolve enrollment gaps, test prior authorization submission pathways. Staff Training (2-4 weeks): Train clinical staff on documentation requirements, billing staff on new workflows, front desk on eligibility verification processes. Practices skipping these foundational steps implement automation on structurally unsound infrastructure. The system works technically but produces poor results because underlying data quality remains inadequate. Action Priority: Begin data quality assessment NOW, regardless of final vendor selection. Data cleanup requires no vendor involvement and can proceed in parallel with procurement. Practices completing data audit before implementation commence operations 30-40% faster. Critical Technical Consideration: RCM platforms operate as cloud-based SaaS requiring minimal on-premise infrastructure but substantial API integration with existing EHR systems. Practices operating legacy EHRs (systems more than 8-10 years old) lacking modern API capabilities face substantial integration friction. In extreme cases, RCM automation may require concurrent EHR modernization–a much larger project requiring 6-12 month timeline. ### For Medical Directors and Clinical Leadership Does billing automation threaten clinical autonomy? No–when implemented correctly, automation reduces administrative burden while preserving clinical decision authority. The legitimate concern: AI coding systems might constrain treatment options by discouraging procedures with complex prior authorization or low reimbursement. This represents real risk if implemented poorly. Proper Implementation Framework: Clinical Documentation Improvement (CDI), Not Clinical Constraint: Automation should prompt physicians to document more completely, not treat differently. Example: AI identifies documented diabetes without specification of type or control status, prompting physician to clarify documentation. This improves coding accuracy without changing treatment. Authorization Workflow Support: Rather than blocking procedures requiring prior authorization, modern systems should streamline the authorization process–providing real-time status visibility, auto-generating required documentation, tracking appeals. The goal is removing obstacles to appropriate care, not adding them. Coding Review Hierarchy: Physicians should maintain approval authority over all codes, with AI serving as documentation assistant rather than autonomous coder. The workflow: AI suggests codes based on documentation, certified coder reviews, physician approves. This preserves physician authority while leveraging AI efficiency. Revenue Transparency: Automated analytics should provide physicians specialty-specific benchmarking showing how their coding patterns compare to peers–identifying both under-coding (leaving revenue unclaimed) and over-coding (compliance risk). This enables informed clinical documentation improvement. The Clinical Value Proposition: Well-implemented RCM automation returns 2-4 hours weekly to physicians by eliminating: - Manual charge capture and documentation - Prior authorization follow-up calls - Patient billing questions (handled by patient financial counseling) - Compliance documentation for straightforward cases This time returns to patient care or personal time–addressing physician burnout at the margin. Action Priority: Medical directors should participate actively in RCM vendor selection and workflow design. Systems implemented by administrators without clinical input frequently fail because workflows ignore clinical realities. Physician involvement during design prevents expensive post-implementation corrections. ## Final Perspective: Automation as Infrastructure, Not Innovation The healthcare industry tends to discuss technology adoption in innovation language–"transformative," "disruptive," "revolutionary." This framing misleads for revenue cycle management. RCM automation in 2026 is not innovation; it is infrastructure modernization. The comparison is not to cutting-edge research but to upgrading from typewriters to computers: not doing so doesn't make you traditional, it makes you non-functional. The CMS 2026 mandate removes the question of WHETHER to automate and replaces it with WHEN and HOW Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareAIRPA ### Epic Automation | 2026 Epic Systems revenue cycle automation: why the EHR powering 300+ health systems still needs RPA to close labor, payer, and margin gaps in 2026. Jędrzej SzymulaApril 10, 2026 ](https://www.flobotics.io/blog/epic-automation)[ HealthcareAIRCM ### Meditech Automation | 2026 Meditech automation: why strong transaction handling still stalls on cross-workflow orchestration, and how to scale past it. Jędrzej SzymulaMarch 25, 2026 ](https://www.flobotics.io/blog/meditech-automation)[ HealthcareRCMAI ### athenahealth Automation | 2026 athenahealth automation: what its shared rules engine standardizes well, and where you still need custom workflow control. Jędrzej SzymulaMarch 23, 2026 ](https://www.flobotics.io/blog/athenahealth-automation) [All articles →](https://www.flobotics.io/blog) --- # Healthcare Reimbursements: How Payment Rates Are Set Canonical: https://www.flobotics.io/blog/reimbursements-explanation Author: Karl Mielnicki Published: 2026-05-01 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Healthcare Reimbursements: How Payment Rates Are Set CTO Notes [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Healthcare Reimbursements: How Payment Rates Are Set [Karl MielnickiCTO & Co-Founder of Flobotics](https://www.flobotics.io/our-editorial-team#mielnicki) Published May 01, 2026Updated September 1, 2026 On this page - [What Are Healthcare Reimbursements?](#what-are-healthcare-reimbursements) - [How Reimbursement Rates Are Determined](#how-reimbursement-rates-are-determined) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Are Healthcare Reimbursements? In healthcare, reimbursements are the payments providers — physicians, hospitals, clinics, and other healthcare entities — receive from third-party payers (commercial insurers, Medicare, Medicaid, managed care organizations) or directly from patients for services delivered. They represent the revenue side of the revenue cycle: the financial return on care provided. Reimbursement amounts are determined by a complex interplay of contracted rates, government-set fee schedules, coding accuracy, and coverage determination. Understanding how each element works — and where it can fail — is foundational to maximizing revenue cycle performance. ## How Reimbursement Rates Are Determined - Commercial payers: Rates are negotiated in provider-payer contracts, typically expressed as a percentage of Medicare rates or a custom fee schedule. Contracts define allowed amounts for every CPT code and rules for adjustments, timely filing, and coordination of benefits - Medicare: Based on the Medicare Physician Fee Schedule (MPFS) for outpatient and Diagnosis-Related Groups (DRGs) for inpatient, set annually by CMS and varying by geography - Medicaid: State-administered programs with rates varying significantly by state — often the lowest payer category for the same services - Value-based contracts: Increasingly include performance-based components tied to quality metrics and cost targets under [Value-Based Care](https://www.flobotics.io/blog/value-based-care-vbc-explanation) frameworks Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byKarl Mielnicki CTO & Co-Founder of Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### What Is Payment Posting (Cash Posting) in Medical Billing? Payment posting (cash posting) reconciles payer and patient payments against claims, surfacing denials faster in 2026. Bart TeodorczukApril 10, 2026 ](https://www.flobotics.io/blog/payment-posting-cash-posting-explanation)[ Healthcare ### Contractual Adjustment (Allowance): Meaning in Medical Billing Contractual adjustment (allowance), explained: why this write-off isn't lost revenue - and how mistracking hides real underpayments. Krzysztof SzwedMarch 20, 2026 ](https://www.flobotics.io/blog/contractual-adjustment-allowance-explanation)[ HealthcareRCM ### Net Collection Rate (NCR): Formula and Benchmarks Net Collection Rate (NCR) explained: the RCM metric measuring collectible revenue actually captured. Best practice is 95-99% - below that, revenue leaks. Bart TeodorczukJune 04, 2026 ](https://www.flobotics.io/blog/net-collection-rate-ncr) [All articles →](https://www.flobotics.io/blog) --- # What Is Prior Authorization (Pre-Auth) in Healthcare? Canonical: https://www.flobotics.io/blog/prior-authorization-pre-auth-explanation Author: Bart Teodorczuk Published: 2026-04-30 Updated: 2026-09-14 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/What Is Prior Authorization (Pre-Auth) in Healthcare? [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # What Is Prior Authorization (Pre-Auth) in Healthcare? [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published April 30, 2026Updated September 14, 2026 On this page - [What Is Prior Authorization?](#what-is-prior-authorization) - [The Business Cost of Manual Prior Authorization](#the-business-cost-of-manual-prior-authorization) - [Why Auth Denials Are a Major Revenue Threat?](#why-auth-denials-are-a-major-revenue-threat) - [How Automation Transforms Prior Authorization?](#how-automation-transforms-prior-authorization) - [Prior Auth in the Broader RCM Context](#prior-auth-in-the-broader-rcm-context) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Is Prior Authorization? Prior Authorization — also called pre-auth, precertification, or prior approval — is the formal payer process requiring healthcare providers to obtain official payer approval before delivering specific treatments, procedures, imaging studies, medications, or specialist services. It is the payer's mechanism for reviewing medical necessity before committing to coverage and reimbursement. Prior authorization touches virtually every specialty. Imaging (MRI, CT), specialty medications, surgical procedures, inpatient admissions, durable medical equipment, and behavioral health services are among the highest-volume authorization categories. Without a valid, current authorization on file, claims for these services are immediately denied — regardless of clinical appropriateness. ## The Business Cost of Manual Prior Authorization Prior authorization has become one of the most resource-intensive administrative processes in healthcare: - Physicians and staff spend an average of 13 hours per physician per week on prior authorization, and nearly four in five physicians (79%) report that patients abandon treatment due to authorization challenges (AMA, 2025) - Each manual authorization request requires 20–45 minutes of staff time — not including follow-up for incomplete responses - Authorization-related denials are among the top three denial categories across virtually all specialties As AMA President Bobby Mukkamala, M.D. said when these findings were released, ["physician trust in voluntary insurer pledges is deeply eroded after years of unfulfilled promises"](https://www.ama-assn.org/press-center/ama-press-releases/ama-survey-prior-authorization-reform-pledge-falls-short-physicians). Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Why Auth Denials Are a Major Revenue Threat? Claims denied for missing, expired, or incorrectly obtained prior authorization are among the most difficult and expensive to recover. Retrospective authorization is often unavailable or requires intensive clinical documentation and appeals. Many auth-related denials are written off rather than worked — making them a direct [Net Collection Rate](https://www.flobotics.io/blog/net-collection-rate-ncr) reduction with no recovery path. The clinical care happened; the revenue did not. ## How Automation Transforms Prior Authorization? [Prior authorization automation](https://www.flobotics.io/agents/prior-authorization-automation) replaces the hours-long manual cycle of portal navigation, form completion, clinical documentation attachment, and status follow-up with an automated workflow that handles the same steps in minutes: - Automated payer requirement lookup: real-time identification of which procedures require auth with which payers - Intelligent form completion: extracting relevant clinical data from EHR documentation and pre-populating payer portals - Status monitoring: automated daily checking of submitted auth requests, flagging pending or denied requests immediately - Expiration tracking: alerts when approved authorizations are approaching expiration for procedures not yet scheduled - Denial prevention: cross-referencing scheduled procedures against auth status before claim generation Flobotics's own [genetic diagnostics lab prior authorization case study](https://www.flobotics.io/case-studies/90-faster-packet-submissions-prior-authorization-automation) shows this in practice: bridging the lab's LIMS directly to the payer portal cut packet submission time by 90% and eliminated a growing backlog of samples stuck waiting on administrative clearance. Our prior authorization automation deployments have achieved 85%+ reductions in manual auth processing time — see the [pain management network prior authorization case study](https://www.flobotics.io/case-studies/85-faster-submissions-8-ftes-saved-prior-authorization-automation), where submission time dropped 85% and freed up more than 8 FTEs. ## Prior Auth in the Broader RCM Context Prior authorization connects directly to [eligibility verification](https://www.flobotics.io/blog/eligibility-verification-explanation), [claims management](https://www.flobotics.io/agents/claims-management-automation), and [denial management](https://www.flobotics.io/agents/denials-management-automation). In a well-designed [RCM automation program](https://www.flobotics.io/rcm-automation), authorization status is verified at every relevant touchpoint — scheduling, pre-service, and pre-billing — closing the gaps that create authorization denials. Regulatory pressure is pushing in the same direction: under the [CMS Interoperability and Prior Authorization Final Rule](https://www.cms.gov/initiatives/burden-reduction/overview/interoperability/policies-regulations/cms-interoperability-prior-authorization-final-rule-cms-0057-f) (CMS-0057-F), most impacted payers must stand up FHIR-based prior authorization APIs by 2027 — a shift CMS estimates could save the health system roughly $15 billion over a decade by taking friction out of the process. ## FAQ: Who is responsible for obtaining prior authorization? The doctor's office or treating provider is responsible for submitting the prior authorization request, not the patient. They send the clinical and administrative documentation the insurer needs to decide whether to approve the service or medication. How long does prior authorization take? Standard requests can take up to 30 days for an insurer to review, though expedited requests are typically required to get a response within about 72 hours. Actual turnaround varies by payer, service type, and how complete the submitted documentation is. Why is it so hard to get prior authorization approved? A common reason is rigid, plan-specific criteria: if a request doesn't match exactly what the reviewer's checklist calls for, it can be denied even when the treatment is medically justified. Reviews are also sometimes handled by staff who aren't physicians and may be unfamiliar with the condition being treated. Why does insurance deny prior authorization requests? Common reasons include incomplete documentation, the request not exactly matching the insurer's own criteria, or a lower-cost alternative treatment being available. Denials aren't always correct, either: one analysis found that over 80% of initial prior-authorization denials appealed to Medicare Advantage plans are ultimately overturned. What happens if you don't get required prior authorization? The insurer will deny the claim, and who ends up financially responsible depends on the denial code and the payer's contract with the provider. Under a CO-197 code the practice typically has to write off or appeal the charge without billing the patient, while under a PR-197 code the patient can be billed the full amount. What are the steps in the prior authorization process? The provider identifies that a service needs authorization, then submits clinical documentation to the insurer explaining why it's medically necessary. The health plan reviews the request against its own coverage criteria and then approves it, denies it, or asks for more information, with an appeal available if it's denied. Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ EligibilityHealthcareRCM ### Insurance Eligibility Verification in Healthcare, Explained Eligibility verification guide: confirming insurance coverage and patient financial responsibility before the visit, in real time. Krzysztof SzwedApril 08, 2026 ](https://www.flobotics.io/blog/eligibility-verification-explanation)[ HealthcareRCM ### Patient Access: The Front End of the Revenue Cycle What is patient access? A guide to the front-end RCM steps - scheduling, registration, eligibility checks, and prior authorization - that start every claim. Jędrzej SzymulaJune 02, 2026 ](https://www.flobotics.io/blog/patient-access-explanation)[ HealthcareRCM ### Medical Necessity: How Payers Decide What They Cover Medical necessity, explained: how payers decide if a service qualifies for coverage, and what proof stops denials before they start. Bart TeodorczukMarch 30, 2026 ](https://www.flobotics.io/blog/medical-necessity-explanation) [All articles →](https://www.flobotics.io/blog) --- # Predictive Analytics in RCM: Key Applications Canonical: https://www.flobotics.io/blog/predictive-analytics-explanation Author: Krzysztof Szwed Published: 2026-04-28 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Predictive Analytics in RCM: Key Applications [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Predictive Analytics in RCM: Key Applications [Krzysztof SzwedHead of Delivery at Flobotics](https://www.flobotics.io/our-editorial-team#szwed) Published April 28, 2026Updated September 1, 2026 On this page - [What Is Predictive Analytics in RCM?](#what-is-predictive-analytics-in-rcm) - [Key RCM Applications](#key-rcm-applications) - [Why Predictive Analytics Transforms RCM Operations](#why-predictive-analytics-transforms-rcm-operations) - [Predictive Analytics and Automation](#predictive-analytics-and-automation) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Is Predictive Analytics in RCM? Predictive Analytics in Revenue Cycle Management is the application of data models, machine learning, and statistical analysis to forecast future outcomes based on historical patterns — enabling RCM teams to intervene proactively rather than react after problems occur. In practice, it answers: which of today's claims are most likely to be denied? Which patients are unlikely to pay their balance? Which authorization requests will require clinical documentation escalation? Rather than treating every transaction as a uniform workflow, predictive analytics stratifies transactions by risk score — allowing staff and automation to concentrate effort where the probability of failure is highest and the financial impact of intervention is greatest. ## Key RCM Applications - Denial prediction: Models trained on historical claim data and payer behavior identify claims with elevated denial probability before submission — enabling pre-submission correction that improves [Clean Claim Rate](https://www.flobotics.io/blog/clean-claim-rate-ccr-explanation) - Prior authorization likelihood scoring: Predicts which procedure-payer combinations require auth and flags requests likely to be denied, prioritizing [auth management](https://www.flobotics.io/agents/prior-authorization-automation) - Patient propensity to pay: Scores patient accounts by likelihood of payment to optimize collection strategy and reduce bad debt - AR aging risk: Identifies accounts most likely to age beyond timely filing, enabling targeted intervention before write-off - Underpayment detection: Statistical comparison of actual payments to contractual allowables at scale, surfacing systematic underpayment patterns invisible in manual review Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Why Predictive Analytics Transforms RCM Operations Traditional RCM is reactive: claims get denied, staff work denials. Predictive analytics inverts this model. By identifying high-risk transactions before they fail, it enables intervention at the cheapest point in the cycle. Industry data consistently shows that preventing a denial costs 5–10x less than working a denied claim after the fact. The financial impact scales with volume. A model catching 60% of high-probability denials before submission — on a practice with 10,000 monthly claims and 7% baseline denial rate — prevents 420 denials per month, saving hundreds of thousands in annual rework costs. ## Predictive Analytics and Automation Predictive analytics delivers its greatest ROI when embedded directly into automated workflows rather than used as a standalone reporting tool. In a mature [RCM automation program](https://www.flobotics.io/rcm-automation), predictive scoring runs at the point of claim generation, routing high-risk claims for pre-submission review and automatically escalating high-risk AR accounts before they age. As [agentic AI in healthcare](https://www.flobotics.io/blog/agentic-ai-in-healthcare) matures, predictive capabilities are moving from batch reporting to real-time decision support embedded in every RCM workflow. [Talk to us](https://www.flobotics.io/contact) about deploying predictive capabilities in your revenue cycle. Written byKrzysztof Szwed Head of Delivery at Flobotics. [More from Krzysztof](https://www.flobotics.io/our-editorial-team#szwed) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### Intelligent Document Processing (IDP) in Healthcare RCM Intelligent Document Processing (IDP) uses AI, OCR, and NLP to turn scanned EOBs and faxes into automated RCM workflows in 2026. Krzysztof SzwedMay 31, 2026 ](https://www.flobotics.io/blog/intelligent-document-processing-idp-explanation)[ RCMHealthcare ### Value-Based Care (VBC): What It Means for RCM Value-based care (VBC) guide: what outcomes-based reimbursement means for quality reporting, risk adjustment, and RCM documentation. Jędrzej SzymulaMay 28, 2026 ](https://www.flobotics.io/blog/value-based-care-vbc-explanation)[ HealthcareRCM ### What Is Denials Management? Process and Benchmarks Denials management tackles denial rates now above 20%, where every reworked claim costs about $44 - and prevention pays off. Karl MielnickiApril 02, 2026 ](https://www.flobotics.io/blog/denials-management-explanation) [All articles →](https://www.flobotics.io/blog) --- # Patient Statement: What to Include on a Medical Bill Canonical: https://www.flobotics.io/blog/patient-statement-explanation Author: Jędrzej Szymula Published: 2026-04-23 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Patient Statement: What to Include on a Medical Bill [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Patient Statement: What to Include on a Medical Bill [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published April 23, 2026Updated September 1, 2026 Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Patient Statement The final financial document sent to the patient detailing services, insurance payments, and the remaining outstanding balance owed by the patient. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### What Is Payment Posting (Cash Posting) in Medical Billing? Payment posting (cash posting) reconciles payer and patient payments against claims, surfacing denials faster in 2026. Bart TeodorczukApril 10, 2026 ](https://www.flobotics.io/blog/payment-posting-cash-posting-explanation)[ HealthcareRCM ### Healthcare Reimbursements: How Payment Rates Are Set Healthcare reimbursement guide: how payment rates are set and where automation closes the gap between allowed and collected amounts. Karl MielnickiMay 01, 2026 ](https://www.flobotics.io/blog/reimbursements-explanation)[ HealthcareRCM ### Net Promoter Score (NPS) in Healthcare Net Promoter Score (NPS) in healthcare ties patient loyalty to billing experience - and increasingly to Value-Based Care reimbursement. Bart TeodorczukMay 21, 2026 ](https://www.flobotics.io/blog/nps-net-promoter-score-explanation) [All articles →](https://www.flobotics.io/blog) --- # Medicare ICGP | 2026 Canonical: https://www.flobotics.io/blog/medicare-icgp Author: Jędrzej Szymula Published: 2026-04-22 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Medicare ICGP | 2026 [Healthcare](https://www.flobotics.io/blog?category=healthcare) # Medicare ICGP | 2026 [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published April 22, 2026Updated September 1, 2026 On this page - [The Architecture of Medicare](#the-architecture-of-medicare) - [Three Vectors of Impact:](#three-vectors-of-impact) - [Medicare Under the Magnifying Glass](#medicare-under-the-magnifying-glass) - [What to Do In 2026?](#what-to-do-in-2026) - [Compliance as Competitive Advantage](#compliance-as-competitive-advantage) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) The Centers for Medicare & Medicaid Services will soon replace its fragmented audit apparatus with a unified prediction engine. For mid-sized hospitals, this shift from reactive auditing to pattern-based detection represents not merely a compliance update but a structural reorganization of revenue cycle risk. Organizations without integrated documentation, analytics, and monitoring systems face 100-150% higher remediation costs and an additional 7-12 days in accounts receivable. The question is no longer whether to invest in compliance architecture, but whether delaying that investment until the first audit lands is a bet any CFO can afford. ## The Architecture of Medicare Medicare's Integrity Contractor Generalized Program (ICGP) consolidates the work previously divided among Recovery Audit Contractors (RACs), Medicare Administrative Contractors (MACs), and Zone Program Integrity Contractors (ZPICs) into a single framework powered by machine learning. Rather than sampling claims retrospectively, ICGP applies natural language processing to electronic medical records in real time, flagging patterns that suggest overbilling, unbundling, or insufficient medical necessity documentation. Industry sources anticipate implementation in Q1 2026, though CMS has yet to publish a final implementation schedule or detailed technical specifications. This lack of clarity itself poses a planning challenge: organizations must budget for system upgrades and staff reallocation without knowing precisely which procedure codes or specialties will face scrutiny first, or how the appeals process will differ from legacy RAC procedures. The financial incentive driving this consolidation is substantial. CMS recovered $4.2 billion through integrity programs in fiscal year 2023, and RAC audit volume grew 23% year-over-year before ICGP was announced—a baseline trend likely to accelerate once predictive models replace manual sampling. For organizations already operating near break-even on Medicare contracts, even a modest uptick in audit intensity can shift margins from positive to negative. ### Three Vectors of Impact: #### 1. Clinical Documentation Under the old model, auditors sampled a subset of claims and requested corresponding medical records weeks or months after submission. ICGP inverts this sequence: natural language processing scans the full documentation stream as claims are filed, comparing physician notes, nursing records, and diagnostic results against algorithmic thresholds for medical necessity. Organizations without Clinical Documentation Improvement (CDI) programs face 40-60% higher audit likelihood, according to consultancy estimates based on early adopters of similar state Medicaid systems. The cost of defending a single audit has risen from $8,000-12,000 under traditional RAC procedures to $12,000-18,000 under ICGP, driven by the need to reconstruct the clinical rationale for treatment decisions that may have occurred 18 months earlier. Internal staff spend 240-320 hours per case on documentation retrieval, expert review, and correspondence with contractors—time that could otherwise be applied to current patient care or denial management. The strategic implication is clear: CDI transitions from a quality initiative to the first line of revenue defense. Hospitals that historically treated documentation as a billing department responsibility now require physician champions, real-time feedback loops, and EMR workflows designed to capture specificity at the point of care. For a 300-bed facility, this typically means adding 2-3 full-time CDI specialists and training clinical staff on documentation standards tied directly to ICGP's detection algorithms. #### 2. Compliance Engineering CMS's use of machine learning to identify billing anomalies forces a corresponding investment in provider-side analytics. Organizations relying solely on pre-claim scrubbers—software that checks for basic coding errors—operate reactively: they learn of compliance gaps only after an audit notice arrives. By contrast, systems that apply similar pattern-detection logic to outbound claims before submission can flag high-risk encounters for manual review, reducing false positives and lowering the volume of claims requiring post-submission defense. Building this capability requires $50,000-100,000 in annual IT spending for mid-sized organizations, covering software licenses, EMR integration, and ongoing rule updates as CMS refines its detection models. The technical challenge lies in creating real-time data feeds from hospital information systems to analytics platforms without violating HIPAA requirements or degrading system performance. For many organizations, this necessitates upgrading network infrastructure and hiring compliance engineers who understand both healthcare regulations and data science—a talent pool that commands premium salaries in a tight labor market. The strategic framework emerging among prepared organizations resembles a four-layer "compliance operating system": CDI ensures documentation quality, analytics platforms pre-screen claims for risk, continuous monitoring tracks denial patterns across payers, and remediation workflows accelerate response to audit notices. Point solutions—purchasing a CDI tool without analytics, or analytics without monitoring—leave gaps that ICGP's algorithms will exploit. #### 3. Cash Flow ICGP accelerates the timeline for recoupment. Traditional RAC audits took 14-18 months to resolve, allowing organizations to spread remediation costs across multiple fiscal years. Early experience with ICGP-like systems in Medicare Advantage suggests resolution windows may compress to 8-12 months, driven by automated evidence review and faster contractor decision cycles. This speed advantage cuts both ways: organizations can appeal denials more quickly, but must also pay refunds sooner if appeals fail. Conservative financial modeling suggests unprepared organizations will experience 7-12 additional days in accounts receivable, a function of increased claim holds and higher rates of pended submissions flagging medical necessity questions. For a hospital with $200 million in annual net patient revenue, each additional day in A/R ties up approximately $550,000 in working capital—cash that might otherwise fund capital projects or debt service. The total indirect cost of ICGP compliance—encompassing IT investments, CDI staffing, audit defense, and refund reserves—is projected to rise from $200,000-300,000 annually under the old model to $400,000-600,000 for mid-sized organizations. This estimate, based on case studies from health systems in states piloting similar Medicaid programs, assumes baseline compliance posture: organizations already exceeding 10% Medicare denial rates, or those with known documentation deficiencies, should model costs at the higher end of the range or beyond. CFOs must also rethink reserve levels. Historically, 2-5% of Medicare revenue was held as contingency against potential refunds. Under ICGP, that figure should increase to 5-12%, reflecting both higher audit volume and faster recoupment execution. For a hospital with $50 million in Medicare revenue, this shift means an additional $1.5-3.5 million in balance-sheet reserves—funds unavailable for other uses. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Medicare Under the Magnifying Glass Several critical details remain opaque, forcing organizations to plan under uncertainty. CMS has not published an official implementation date, a phased rollout schedule by specialty or procedure code, or draft technical specifications for ICGP's detection algorithms. The appeals process—whether it retains the five-level structure of traditional Medicare audits or introduces expedited review for algorithmically flagged claims—has not been clarified. Nor has CMS indicated whether ICGP will inherit the $2,000 claim threshold that limited RAC scope, or whether all Medicare claims, regardless of value, will be subject to pattern-based review. These ambiguities complicate vendor selection and system design. Should organizations invest in analytics platforms optimized for cardiology and orthopaedics, which historically attracted RAC scrutiny, or assume ICGP will target lower-intensity services where volume makes patterns easier to detect? Without knowing whether appeals will be faster or slower than the historical 14-18 months, how should finance teams model the timing of potential refunds? The most honest answer is to plan for the worst-case scenario: assume ICGP applies uniformly across all procedure codes, operates at higher audit intensity than RAC, and resolves disputes faster than legacy processes. Organizations that budget for this baseline can scale back if CMS's final guidance proves more lenient; those who assume continuity with the old model risk severe cash flow disruption if implementation proves aggressive. ## What to Do In 2026? For chief financial officers, the first step is rebudgeting. Compliance and revenue cycle infrastructure should receive 100-150% increases over prior-year allocations, with line items for CDI staffing, analytics software, EMR integration, and external audit defense. Refund reserves should be recalculated at 5-12% of Medicare revenue, and sensitivity analyses should model the impact of 7-12 additional days in A/R on cash flow projections. Return-on-investment analyses should compare the cost of preemptive CDI and analytics investments against the cost of doing nothing—using the $400,000-600,000 indirect cost estimate as the baseline for inaction. Chief technology and information officers face three priority tasks: auditing whether current claim scrubbers incorporate ICGP-relevant detection logic, establishing real-time data feeds from EMR to analytics platforms, and ensuring HIPAA compliance for any new data flows. Vendor assessments should explicitly ask whether software providers have updated their products for ICGP, and contracts should include provisions for ongoing rule updates as CMS refines its algorithms. Budget assumptions should allocate an additional 5-7% of IT spending to data security, reflecting the increased volume of sensitive information moving across systems. Compliance officers must conduct gap analyses comparing current documentation practices against ICGP standards—insofar as those standards can be inferred from CMS guidance and pilot programs. Training programs for billing and clinical staff should emphasize pattern-based detection: how ICGP's algorithms differ from human auditors, which documentation elements carry the most weight in algorithmic scoring, and how to structure physician notes to satisfy both clinical and compliance requirements. Remediation workflows should be redesigned for speed, with predefined escalation paths and external counsel on retainer. The timeline is compressed. Q3 2025 should focus on budgeting and vendor selection, Q4 2025 on system implementation and staff training, and Q1 2026 on go-live and continuous monitoring. Organizations that defer action until after the first audit notice will find themselves implementing systems under duress, at higher cost, and with less favorable contract terms. ### Compliance as Competitive Advantage Large integrated delivery networks—Mayo Clinic, Cleveland Clinic, Kaiser Permanente—have been building the compliance architecture ICGP demands for years, driven by their own scale and risk exposure. These organizations treat compliance not as a cost center but as a strategic capability that lowers audit rates, stabilizes cash flow, and strengthens negotiating position with commercial payers. In a Medicare market where reimbursement rates are fixed and cost reduction opportunities are exhausted, the margin between profitability and loss increasingly depends on minimizing claims friction. For unprepared organizations, the baseline scenario involves doubling operational costs for audit defense, remediation, and cash flow management. The worst-case scenario—repeated audits, large recoupments, and reputational damage with referring physicians and community boards—can threaten financial viability, particularly for hospitals already operating on thin margins. The strategic question is not whether to invest in compliance architecture, but whether to invest now or wait until the first painful audit forces the decision. ICGP represents a selection mechanism: it will separate organizations capable of operating in a predictive regulatory environment from those that cannot adapt quickly enough. The decision to invest in CDI, analytics, and monitoring systems is ultimately a decision about long-term sustainability in the Medicare market. For mid-sized hospitals, that market often accounts for 40-50% of inpatient volume. Betting that ICGP will be lenient, or that legacy approaches will suffice, is a gamble with the organization's largest payer relationship. The shift from reactive auditing to predictive detection is irreversible. CMS has both the financial incentive—billions in annual recoveries—and the technical capability to make this transition. The only variable is how prepared individual organizations will be when the system goes live. #### Summary: At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let's talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Posting Correspondence in RCM: EOBs, ERAs and Automation Canonical: https://www.flobotics.io/blog/posting-correspondence-explanation Author: Karl Mielnicki Published: 2026-04-17 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Posting Correspondence in RCM: EOBs, ERAs and Automation CTO Notes [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Posting Correspondence in RCM: EOBs, ERAs and Automation [Karl MielnickiCTO & Co-Founder of Flobotics](https://www.flobotics.io/our-editorial-team#mielnicki) Published April 17, 2026Updated September 1, 2026 On this page - [What Is Posting Correspondence?](#what-is-posting-correspondence) - [EOB vs. ERA: Two Formats of the Same Data](#eob-vs-era-two-formats-of-the-same-data) - [Why Accurate Posting Correspondence Processing Matters](#why-accurate-posting-correspondence-processing-matters) - [Common Challenges](#common-challenges) - [Automating Posting Correspondence](#automating-posting-correspondence) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Is Posting Correspondence? Posting Correspondence in healthcare RCM refers to the official documentation issued by payers in response to submitted claims — primarily the Explanation of Benefits (EOB) and its electronic equivalent, the Electronic Remittance Advice (ERA, or ANSI X12 835 transaction). These documents detail exactly how each claim was processed: the allowed amount, the paid amount, contractual adjustments applied, and the specific reason codes for any denials, reductions, or pended lines. Processing posting correspondence accurately and promptly is one of the most operationally intensive and consequential activities in the billing cycle. Every payment must be reconciled to the correct claim and patient account, every adjustment posted correctly, and every denial code captured for downstream action. ## EOB vs. ERA: Two Formats of the Same Data EOBs arrive in paper format, typically mailed by payers who have not transitioned to fully electronic remittance. ERAs are the HIPAA-standard electronic equivalent transmitted directly from payer to provider or clearinghouse. A single ERA file can contain hundreds or thousands of individual claim payment records, making automated processing essential at any meaningful volume. The shift from paper EOB to electronic ERA processing represents one of the highest-ROI transitions in RCM operations. A biller manually processing paper EOBs handles 20–40 claims per hour. Automated ERA processing handles thousands per hour with error rates approaching zero. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Why Accurate Posting Correspondence Processing Matters Errors in posting correspondence create compounding downstream problems: - Incorrect payment posting creates false AR balances — either understating what is owed or overstating what was collected - Missed denial codes mean denied claims are not identified for appeal, leading to direct revenue loss as they age toward write-off - Incorrect adjustment posting corrupts [Net Collection Rate](https://www.flobotics.io/blog/net-collection-rate-ncr) calculations and hides underpayment patterns - Unidentified [underpayments](https://www.flobotics.io/blog/underpayment-recovery-explanation) accumulate silently when ERA data is not cross-referenced against contracted rates at posting time Timely posting is also operationally critical. Unprocessed correspondence creates artificial AR inflation, distorts [DAR](https://www.flobotics.io/blog/days-in-accounts-receivable-dar-explanation) reporting, and delays identification of denied claims needing immediate action within payer appeal timelines. ## Common Challenges - Paper EOB volume: Payers that haven't transitioned to ERA require manual processing that cannot scale cost-effectively - Mixed remittance formats: Different payers use different ERA formats and reason code sets - Non-standard denial codes: Payer-specific CARCs and RARCs require interpretation and routing that varies by payer policy - Secondary payer correspondence: Coordination of benefits posting requires correctly sequencing primary and secondary payments ## Automating Posting Correspondence Automating posting correspondence is among the highest-value RCM automation use cases. [Intelligent Document Processing (IDP)](https://www.flobotics.io/blog/intelligent-document-processing-idp-explanation) handles paper EOBs by extracting payment data from scanned or faxed documents. ERA files are processed by automated [payment posting](https://www.flobotics.io/blog/payment-posting-cash-posting-explanation) workflows that match, validate, and post thousands of claim lines per hour. Automated processing also enables real-time underpayment detection — cross-referencing each payment line against contracted fee schedules at the moment of posting rather than in periodic manual audits. A complete [RCM automation program](https://www.flobotics.io/rcm-automation) treats posting correspondence as a real-time revenue intelligence signal, not a manual work queue. [Talk to us](https://www.flobotics.io/contact) about automating your remittance processing workflow. Written byKarl Mielnicki CTO & Co-Founder of Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### What Is Payment Posting (Cash Posting) in Medical Billing? Payment posting (cash posting) reconciles payer and patient payments against claims, surfacing denials faster in 2026. Bart TeodorczukApril 10, 2026 ](https://www.flobotics.io/blog/payment-posting-cash-posting-explanation)[ HealthcareRCM ### Healthcare Reimbursements: How Payment Rates Are Set Healthcare reimbursement guide: how payment rates are set and where automation closes the gap between allowed and collected amounts. Karl MielnickiMay 01, 2026 ](https://www.flobotics.io/blog/reimbursements-explanation)[ Healthcare ### Contractual Adjustment (Allowance): Meaning in Medical Billing Contractual adjustment (allowance), explained: why this write-off isn't lost revenue - and how mistracking hides real underpayments. Krzysztof SzwedMarch 20, 2026 ](https://www.flobotics.io/blog/contractual-adjustment-allowance-explanation) [All articles →](https://www.flobotics.io/blog) --- # What Is Payment Posting (Cash Posting) in Medical Billing? Canonical: https://www.flobotics.io/blog/payment-posting-cash-posting-explanation Author: Bart Teodorczuk Published: 2026-04-10 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/What Is Payment Posting (Cash Posting) in Medical Billing? [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # What Is Payment Posting (Cash Posting) in Medical Billing? [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published April 10, 2026Updated September 1, 2026 Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Payment Posting (Cash Posting) The process of recording payments received from payers and patients against claims to reconcile accounts and identify denials. See how our [RCM automation](https://www.flobotics.io/rcm-automation) supports payment posting and remittance matching. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### Posting Correspondence in RCM: EOBs, ERAs and Automation Posting correspondence, explained: why every unprocessed EOB or ERA means delayed cash and a missed denial in your RCM workflow. Karl MielnickiApril 17, 2026 ](https://www.flobotics.io/blog/posting-correspondence-explanation)[ Healthcare ### Contractual Adjustment (Allowance): Meaning in Medical Billing Contractual adjustment (allowance), explained: why this write-off isn't lost revenue - and how mistracking hides real underpayments. Krzysztof SzwedMarch 20, 2026 ](https://www.flobotics.io/blog/contractual-adjustment-allowance-explanation)[ HealthcareRCM ### Credit Balance Resolution in Healthcare, Explained Credit balance resolution, explained: why federal law gives providers 60 days to repay Medicare and Medicaid overpayments. Jędrzej SzymulaMarch 18, 2026 ](https://www.flobotics.io/blog/credit-balance-resolution-explanation) [All articles →](https://www.flobotics.io/blog) --- # Epic Automation | 2026 Canonical: https://www.flobotics.io/blog/epic-automation Author: Jędrzej Szymula Published: 2026-04-10 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Epic Automation | 2026 [AI](https://www.flobotics.io/blog?category=ai)[Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm)[RPA](https://www.flobotics.io/blog?category=rpa) # Epic Automation | 2026 [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published April 10, 2026Updated September 1, 2026 On this page - [What Epic's Automation Actually Does](#what-epic-s-automation-actually-does) - [Where the Real Returns Come From](#where-the-real-returns-come-from) - [The Framework for Deciding What to Automate](#the-framework-for-deciding-what-to-automate) - [Implementation Without the Common Mistakes](#implementation-without-the-common-mistakes) - [Measuring What Actually Matters](#measuring-what-actually-matters) - [The Human Side of Automation](#the-human-side-of-automation) - [Where Epic Automation Is Heading](#where-epic-automation-is-heading) - [The Organizations That Will Win](#the-organizations-that-will-win) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Automation is no longer a future promise in healthcare. It is an operational imperative. Rising labor costs, deepening payer complexity, shrinking reimbursement margins, and the relentless administrative weight on clinical staff have made manual processes untenable at scale. For the organizations running on [Epic Systems](https://www.epic.com/) - a platform that now touches the records of more than 300 million patients across the United States the question is no longer whether to automate but how to do it well. That distinction matters more than most implementation teams acknowledge. Epic's automation capabilities are genuinely extensive. They span clinical decision support, revenue cycle operations, patient engagement, and workforce productivity. And yet the gap between what these tools can do and what the average organization actually extracts from them remains striking. The difference, consistently, comes down not to technology but to discipline: the organizational capacity to identify the right workflows, implement them with rigor, measure what matters, and govern automation as a living system rather than a one-time deployment. This guide is written for the healthcare IT leaders, practice managers, and revenue cycle directors who are moving past the vendor overview and into the harder work of making automation perform. ## What Epic's Automation Actually Does Epic's automation is not a single feature or module. It is a set of capabilities distributed across the platform's clinical, financial, and operational layers - each operating on different logic, serving different users, and generating different kinds of value. In the clinical layer, the most widely used automation mechanism is the Best Practice Advisory, or BPA: a rules-based alert that triggers automatically when a clinician's documentation or order entry meets a defined condition. When BPAs are well-designed and carefully governed, they prevent medication errors, close care gaps, and prompt appropriate follow-up at precisely the moment a clinician can act on the information. When they are poorly governed - activated in excess, without clear criteria for relevance - they contribute to what the clinical informatics field calls [alert fatigue](https://academic.oup.com/jamia/article/27/4/645/5714899), a phenomenon documented extensively in peer-reviewed literature and consistently associated with higher BPA override rates and, in some cases, missed clinical events. Clinicians who encounter dozens of interruptive prompts per session learn, almost inevitably, to dismiss them without reading them. The automation that was meant to catch critical events becomes background noise. The revenue cycle layer is where Epic's automation story becomes most financially consequential. Charge capture automation links clinical documentation to billing codes, narrowing the gap between what is clinically documented and what is ultimately billed. Prior authorization workflows can be automated through Epic's integration with payer portals, substantially reducing the hours of phone-based and portal-based manual work that authorization teams currently absorb - a burden the [American Medical Association's annual prior authorization survey](https://www.ama-assn.org/practice-management/prior-authorization/prior-authorization-research-reports) has consistently found to consume more than fourteen physician hours per week across a typical practice. Before claims are submitted, Epic's scrubbing rules fire against the payer's known edit logic, catching errors that would trigger denials before they leave the building. And follow-up work lists - traditionally built through manual sorting and staff judgment can be automatically generated and prioritized by payer, balance, and aging, directing staff effort toward the accounts where it is most likely to result in payment. In the patient-facing layer, Epic's [MyChart](https://www.epic.com/software/mychart/)-based automation handles appointment reminders, care gap outreach, post-visit surveys, and medication refill workflows. These are generally lower in complexity than revenue cycle or clinical automations, but they offer near-term, measurable value with comparatively limited implementation effort - which makes them a reasonable starting point for organizations building automation capability for the first time. What connects all of these layers is Epic's underlying infrastructure: its integration framework, its [FHIR-based APIs](https://www.healthit.gov/topic/standards-technology/standards/fhir-fact-sheets), and its increasingly sophisticated data model. These foundations allow Epic's automation to reach beyond the walls of a single health system - connecting to payer systems for real-time eligibility checks, transmitting automated transition-of-care summaries to outside providers, and feeding downstream analytics platforms that monitor automation performance. For organizations that supplement Epic's native capabilities with robotic process automation tools like [UiPath](https://www.uipath.com/solutions/industry/healthcare-automation) or Automation Anywhere, this infrastructure also defines the integration points where bots interact with Epic's interface to handle workflows the platform's own APIs don't directly support. ## Where the Real Returns Come From The published evidence on Epic automation outcomes, across peer-reviewed literature and reported health system implementations, points to a consistent set of areas where the returns are clearest. Denial rate reduction is perhaps the most compelling financial case. Health systems that have implemented Epic's front-end eligibility verification automation alongside real-time claim scrubbing consistently report denial rate improvements of 15 to 30 percent within the first 12 to 18 months of a mature deployment. For a system processing a billion dollars in annual gross charges, a 20-percent denial reduction is not an abstract efficiency gain — it is a material improvement in net revenue realization and days in accounts receivable. The [Healthcare Financial Management Association](https://www.hfma.org/revenue-cycle/denials-management/navigating-the-rising-tide-of-denials/) has documented denial management as one of the highest-ROI operational priorities for health system finance leaders, and automation of front-end eligibility verification is consistently among the interventions with the strongest evidence base. Authorization workflow efficiency is another well-documented win, though it comes with an important caveat. Organizations deploying Epic's pAuth module alongside active payer portal integrations report cycle time reductions of 40 to 60 percent for the payer-procedure combinations the automation covers. The caveat is that coverage is incomplete. Many regional payers, specialty payers, and behavioral health payers lack the API infrastructure to support automated prior authorization exchange, which means manual fallback processes must remain staffed alongside automated ones. The automation reduces the volume of manual work significantly; it does not yet eliminate it. Patient scheduling outcomes offer a more immediate, easier-to-measure benefit. Automated appointment reminder and confirmation campaigns through MyChart consistently produce no-show rate reductions in the range of 10 to 20 percent - a meaningful revenue impact for any volume-sensitive specialty or procedure line. Research published in the [Journal of the American Medical Informatics Association](https://academic.oup.com/jamia) has linked patient portal engagement with improved appointment adherence and reduced administrative burden on scheduling staff, reinforcing the case for investing in patient-facing automation alongside internal workflow tools. Perhaps the most underappreciated return, however, comes from population health automation. Epic's tools for identifying care gaps across a defined patient population - patients with diabetes overdue for an HbA1c, patients with hypertension who haven't had a blood pressure check in the past six months - and automatically generating outreach are particularly valuable for health systems operating under value-based contracts. As [Health Affairs](https://www.healthaffairs.org/topic/bms160) has reported extensively, closing care gaps in these populations improves quality scores that directly affect reimbursement under Medicare Advantage and other risk-based arrangements. The automation turns a labor-intensive manual outreach campaign into a background process that runs continuously. ## The Framework for Deciding What to Automate Not every workflow is a good candidate for automation. The mistake of automating the wrong things - or automating the right things in the wrong order is one of the most expensive errors in healthcare IT, and one of the most common. A structured approach to workflow selection pays dividends that persist long after the initial implementation. The first question is one of volume. Automation earns its returns through repetition. A workflow that occurs ten times per week generates a fraction of the value that the same automation would generate at five hundred transactions per week. Low-volume workflows rarely justify the implementation, configuration, and ongoing maintenance overhead that real automation requires. The second question is whether the workflow is genuinely rules-based or whether it contains embedded judgment. This distinction is less obvious than it appears. Many workflows look rule-based on the surface - eligibility verification, claim scrubbing, appointment reminder triggers and actually are, which makes them strong automation candidates. Others appear similarly straightforward but contain decision points that require contextual interpretation: whether a clinical documentation gap matters for this specific payer, whether an authorization denial is worth appealing given the patient's coverage history. Automating judgment-dependent workflows produces brittle systems that generate exceptions faster than humans can resolve them. The [HIMSS Digital Health Indicator](https://www.himss.org/maturity-models/digital-health-indicator/) framework for healthcare digital maturity offers a useful lens for assessing organizational readiness at each automation tier. The third, and most frequently underestimated, question is one of data quality. Automation amplifies whatever is already true of the data it processes. A prior authorization workflow built on top of a registration process that routinely captures incorrect insurance IDs will automate incorrect authorization requests at scale, producing errors faster and in higher volume than a manual process would. The [Office of the National Coordinator for Health IT](https://www.healthit.gov/topic/health-it-basics/improved-diagnostics-patient-outcomes) has emphasized data integrity as a foundational prerequisite for AI and automation in clinical settings a position that applies with equal force to administrative workflows. The honest assessment of data quality - upstream of every proposed automation - is a prerequisite for responsible implementation. If the data isn't clean, fix the source before building the automation. Finally, the change management burden of any automation initiative deserves realistic assessment before the project begins. Some workflows require significant behavioral change from clinical or administrative staff. Even technically excellent automation can fail to deliver its projected value if adoption is incomplete - if staff find workarounds, if exceptions pile up unreviewed, if the automation becomes a background system that no one monitors. Incorporating change management complexity into the go/no-go analysis is not a soft consideration. It is a material risk factor. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Implementation Without the Common Mistakes Organizations approaching Epic automation for the first time consistently benefit from the same practical disciplines, and suffer from the same recurring mistakes. The first discipline is to conduct a thorough inventory of what Epic provides natively before investing in custom builds. Epic ships with an extensive library of pre-built BPAs, charge triggers, claim edits, and workflow automations that a significant percentage of organizations have never activated. [KLAS Research](https://klasresearch.com/), which benchmarks Epic implementations against peer organizations, regularly finds that underutilization of existing platform capabilities is among the most common sources of avoidable cost in EHR-heavy health systems. The tendency to build custom solutions before exhausting native options adds cost and complexity that is rarely justified. The second discipline and the one most often skipped is assigning explicit ownership to every automated workflow before go-live. Each automation should have a designated owner: a specific individual or team responsible for monitoring its performance, managing exceptions, and triggering reviews when the underlying business rules change. Automations without owners degrade silently. The world around them changes payer policies, regulatory requirements, clinical protocols — while the automation continues processing transactions against outdated logic. Identifying this degradation requires someone whose job it is to look for it. The third discipline is to design exception handling before go-live, not after. Every automated workflow generates transactions it cannot process cleanly. The exception pathway — who receives it, what the expected resolution timeframe is, how exceptions are tracked and trended over time — must be defined as part of the implementation, not improvised in the weeks after launch. The most consequential mistake, and the one with the largest cost implications, is automating a broken process. If a workflow is producing bad outcomes because it is poorly designed, automation will produce those outcomes faster and at greater volume. The work of process improvement must precede the investment in automation. Map the current state. Identify the root causes of failure. Redesign the workflow for the intended outcome. Then automate the redesigned process — not the broken original. ## Measuring What Actually Matters The most common failure mode in automation measurement is establishing vague success criteria after implementation, rather than specific, pre-agreed metrics before it. The measurement framework should be defined during project planning, and it should operate at three levels. Process metrics answer the question of whether the automation is functioning as designed: volume processed, straight-through processing rate (the share of transactions completed without human intervention), exception rate, and processing speed. These are the leading indicators of automation health. Outcome metrics answer the question of whether the automation is achieving its intended business purpose: denial rate and first-pass acceptance rate for revenue cycle automations, no-show rate for scheduling automations, coding accuracy rate for documentation automations. These connect the automation's operational performance to the organizational goals that justified the investment. The [American Health Information Management Association](https://www.ahima.org/education-events/coding/) offers established benchmarks for coding accuracy and DNFB days that serve as useful baselines for organizations measuring the impact of documentation and charge automation. Financial metrics translate outcome improvements into terms that sustain executive support and justify additional investment: labor hours redirected, net revenue improvement from denial reduction, cost per transaction processed. These metrics require honest accounting of both sides of the ledger — including the implementation costs, ongoing monitoring labor, exception management overhead, and periodic reconfiguration that real-world automation entails. Vendor-provided ROI calculators, which typically model best-case scenarios against simplified cost assumptions, are a starting point rather than a reliable projection. Organizations that use their own historical baseline data to model expected returns consistently make better investment decisions than those relying on external benchmarks. ## The Human Side of Automation The technical implementation of an Epic automation workflow is, consistently, the easier half of the challenge. Getting clinical and administrative staff to engage with automated systems reliably - and to resist the workarounds that undermine them is where most implementation teams underinvest. The most effective driver of staff adoption is demonstrated, specific relevance. Abstract efficiency arguments - this automation will save the department twelve hours per week - are weak motivators. Concrete demonstrations of personal burden reduction this automation handles the step where you used to have to call the insurance line and wait on hold - generate meaningful behavior change. Training that is embedded in the actual workflow context, at the workstation, in the moment staff encounter the new process, consistently outperforms classroom-based instruction in both retention and adoption rate. This principle aligns with what organizational change researchers at [Prosci](https://www.prosci.com/en/change-management-in-healthcare) have documented specifically in healthcare IT settings: contextual, role-specific learning significantly outpaces generic onboarding in sustained behavior change. Among the most cost-effective investments in any automation rollout is the identification and deliberate support of change champions: respected peers within each affected department who adopt new workflows early and visibly. Their credibility with colleagues is worth more than any number of formal training sessions, and their early experience with the automation surfaces practical problems before they become widespread. ## Where Epic Automation Is Heading Epic's current development priorities reflect the broader transformation underway in enterprise software: the move from rule-based automation toward AI-assisted and eventually AI-driven workflows. The most visible current manifestation is generative AI integration. Epic has embedded AI-drafted responses in MyChart clinical messaging allowing clinicians to review and edit AI-generated replies to patient messages rather than composing from scratch and has partnered with ambient documentation platforms, including [Nuance DAX Copilot](https://www.nuance.com/healthcare/ambient-clinical-intelligence.html), to bring AI-assisted clinical note generation directly into the EHR encounter workflow. The consistent design pattern across these implementations is augmentation rather than replacement: AI generates a first draft, a human reviews and approves. This is the appropriate model for the current state of AI capability in clinical contexts, where the consequences of errors are asymmetric and accountability remains with the clinician. Enhanced prior authorization automation is another near-term priority, driven in part by federal regulatory momentum. The [CMS Interoperability and Prior Authorization Final Rule](https://www.cms.gov/newsroom/fact-sheets/cms-interoperability-and-prior-authorization-final-rule-cms-0057-f) requires payers participating in federal programs to implement FHIR-based prior authorization APIs a mandate that, as it takes full effect, will meaningfully expand what can be automated within Epic's pAuth workflows. As payer API coverage grows under regulatory mandate, the gap between what authorization automation covers and what it cannot will narrow. The longer arc of Epic's roadmap points toward predictive analytics embedded directly in operational workflows denial probability scores surfaced in the charge capture interface before claim submission, no-show probability integrated into the scheduling view to prioritize confirmation outreach. The shift from analytics as a reporting function to analytics as a workflow-embedded decision support tool is where the next meaningful wave of productivity improvement will come from. ## The Organizations That Will Win The trajectory of healthcare automation is not seriously in dispute. [A 2024 report from McKinsey Health Institute](https://www.mckinsey.com/industries/healthcare/our-insights/the-future-of-healthcare) estimated that automation and AI could reduce administrative costs across the US healthcare system by more than $360 billion annually a figure that reflects the scale of the opportunity available to organizations willing to invest in the necessary infrastructure and process discipline. Administrative workflows that currently require significant human labor will be substantially automated within the next five to ten years. The question is not whether that transition will happen but whether individual organizations will be positioned to lead it or to scramble after it. The health systems and practices best positioned for what comes next are already building something specific: not a library of automation deployments, but an organizational capacity for doing automation well. That means maintaining rigorous standards for workflow selection, assigning explicit ownership to every running automation, measuring outcomes against pre-defined baselines, and treating automation governance as an ongoing operational discipline rather than a completed implementation. The specific tools Epic brings to market will change. The AI capabilities embedded in the platform will expand. What will not change is the competitive advantage that accrues to organizations that approach automation with the rigor it requires - and the cost imposed on those that mistake activating features for building capability. This article is written for healthcare IT professionals, revenue cycle leaders, and practice managers evaluating or expanding Epic automation initiatives. Analysis draws on published peer-reviewed literature, reported health system implementations, and industry benchmarking data as of April 2026. Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCMAI ### athenahealth Automation | 2026 athenahealth automation: what its shared rules engine standardizes well, and where you still need custom workflow control. Jędrzej SzymulaMarch 23, 2026 ](https://www.flobotics.io/blog/athenahealth-automation)[ RPAAI ### Building Your Automation Toolkit: 100 Automation Technologies and Platforms You Should Know RPA programming and automation technologies: explore our curated toolkit of 100 platforms, with pros, cons, and top use cases for 2026. Karl MielnickiMay 12, 2024 ](https://www.flobotics.io/blog/automation-technologies)[ HealthcareAIRCM ### Meditech Automation | 2026 Meditech automation: why strong transaction handling still stalls on cross-workflow orchestration, and how to scale past it. Jędrzej SzymulaMarch 25, 2026 ](https://www.flobotics.io/blog/meditech-automation) [All articles →](https://www.flobotics.io/blog) --- # Oracle Healthcare Automation | 2026 Canonical: https://www.flobotics.io/blog/oracle-healthcare-automation Author: Jędrzej Szymula Published: 2026-04-10 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Oracle Healthcare Automation | 2026 [AI](https://www.flobotics.io/blog?category=ai)[Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm)[RPA](https://www.flobotics.io/blog?category=rpa) # Oracle Healthcare Automation | 2026 [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published April 10, 2026Updated September 1, 2026 On this page - [The Oracle Health Ecosystem](#the-oracle-health-ecosystem) - [Before You Read:](#before-you-read) - [The 30,000-Employee Question: What the Layoffs Mean for Your Hospital](#the-30-000-employee-question-what-the-layoffs-mean-for-your-hospital) - [Who Is Actually Using Oracle in Healthcare?](#who-is-actually-using-oracle-in-healthcare) - [Is Cerner Gone? Understanding the "Oracle-ization" of Healthcare IT](#is-cerner-gone-understanding-the-oracle-ization-of-healthcare-it) - [What RCM Professionals Are Actually Saying?](#what-rcm-professionals-are-actually-saying) - [What This Means for RCM Leaders in 2026?](#what-this-means-for-rcm-leaders-in-2026) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## The Oracle Health Ecosystem Oracle's primary footprint in healthcare is now Oracle Health, a massive ecosystem built on the foundation of the Cerner Electronic Health Record (EHR), which Oracle acquired in 2022 for approximately $28 billion. For RCM leaders specifically, Oracle's goal is to unify clinical and financial data into a single "source of truth" - a unified platform that eliminates the traditional silos between what happens at the bedside and what happens in the billing department. ### Before You Read: In practice, this plays out across three layers of the revenue cycle: Front-End RCM focuses on getting patients into the system cleanly. Oracle Health powers automated patient registration, self-service scheduling portals, and AI-driven eligibility verification tools designed to reduce the volume of claims denied due to coverage issues — one of the most persistent (and expensive) problems in hospital billing. The theory is sound: if you know on day one whether a patient's insurance will cover a procedure, you drastically reduce downstream write-offs. Middle RCM is where Oracle's integration story becomes most compelling - and most contested. The platform links clinical documentation directly to automated coding tools through its Health Information Management (HIM) modules. Case managers working within the same system as physicians can flag documentation gaps in real time, reducing "Discharged Not Final Billed" (DNFB) days — a key metric that directly affects a hospital's cash flow. When a hospital sits on billed claims because the clinical record isn't complete enough to support a code, that represents real money stuck in limbo. Back-End RCM is where Oracle's most aggressive AI ambitions live. The patient accounting systems now incorporate machine learning models designed to predict claim denial probability before a claim is ever submitted, theoretically allowing billing teams to intervene proactively. Automated payment processing and remittance posting further reduce the manual workload on AR follow-up teams. Underlying all of this is Oracle Cloud Infrastructure (OCI) - Oracle's answer to AWS and Microsoft Azure. Oracle is actively migrating all legacy Cerner data and workloads to OCI, with the dual promise of improved system uptime and the compute power necessary to run advanced AI "Digital Assistants" for both clinicians and billing staff. These ambient AI tools are intended to handle everything from clinical documentation suggestions to automated prior authorization submissions. ## The 30,000-Employee Question: What the Layoffs Mean for Your Hospital No honest analysis of Oracle's healthcare position in 2026 can ignore the restructuring happening inside the company. Reports from investment bank TD Cowen and multiple industry news outlets indicate that Oracle is in the midst of one of the largest workforce reductions in tech sector history - with estimates suggesting up to 30,000 positions eliminated, representing roughly 19% of Oracle's global workforce. The strategic rationale is straightforward: Oracle is betting its future on AI and cloud infrastructure. That means pulling resources away from human-intensive services like consulting, implementation support, and traditional customer support precisely the functions that healthcare organizations depend on most when something breaks. The impact on Oracle Health's former Cerner division has been particularly acute. RCM directors at large health systems have reported a visible and measurable decline in specialized support quality. The institutional knowledge that made Cerner support valuable veterans who understood the peculiarities of hospital billing workflows, the quirks of specific state Medicaid configurations, the historical reasons why certain system behaviors exist is walking out the door. What's replacing it, in many cases, is an automated ticketing system and offshore support teams working from documentation. Industry forums including Reddit's r/cernercorporation subreddit have documented what participants describe as "stealth layoffs" - gradual but significant reductions in the senior technical staff who once served as the connective tissue between Oracle's software and the complex operational realities of large health systems. For an RCM director managing a $500M+ annual revenue cycle, this isn't abstract concern. It's an operational risk. ## Who Is Actually Using Oracle in Healthcare? Despite the internal turbulence, Oracle Health remains deeply entrenched across large academic medical centers, safety-net hospitals, and federal healthcare systems. The switching costs are enormous - EHR migrations take years and cost tens of millions of dollars which means Oracle's existing customer base is largely captive in the near term. Some of the most notable current users include: Jackson Memorial Hospital (FL) stands as one of the largest bed-count users of the Oracle Health platform, with over 1,600 licensed beds. As Miami-Dade County's public hospital and a Level I Trauma Center, Jackson's revenue cycle complexity is exceptional multiple payer mixes, large uninsured populations, and a substantial Medicaid footprint make their RCM operations a true stress test of the platform. IU Health Methodist (IN) represents Oracle Health's largest revenue generator on the commercial side, with net patient revenue approaching $3.9 billion. Their level of Oracle Health integration across clinical and financial workflows serves as something of a reference implementation. Northside Hospital (GA) has built extensively integrated clinical and financial workflows on the platform, making it a frequently cited example of what deep Oracle Health deployment looks like in a regional health system context. The U.S. Department of Veterans Affairs represents Oracle's most strategically significant and most troubled deployment. The federal EHR modernization project, intended to move the VA away from its legacy VistA system, has been one of the largest IT contracts in federal history. It has also been plagued by delays, cost overruns, and Congressional scrutiny. Oracle's engineering resources are substantially focused here, which has real consequences for its commercial hospital clients. Banner Health has been a long-term Cerner and now Oracle Health partner, with one of the more advanced automation integration footprints in the commercial market. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Is Cerner Gone? Understanding the "Oracle-ization" of Healthcare IT For anyone who spent years working with Cerner before the acquisition, the answer is: yes, effectively. The Cerner brand has been formally retired in favor of Oracle Health, and this is more than a name change. Oracle is systematically migrating the software off the third-party databases it ran on (including, ironically, competitor databases) and onto Oracle's own technology stack - Oracle databases, Oracle middleware, Oracle cloud. The strategic vision behind this comes directly from Larry Ellison, Oracle's founder and CTO, who has spoken publicly about his ambition to build a national, anonymized healthcare database. Every hospital on Oracle Health becomes a node in a potential data intelligence network. For RCM leaders, this means your billing data - your payer mix trends, your denial patterns, your reimbursement rates - is being repositioned as part of a much larger data asset that Oracle intends to monetize through AI analytics tools. The practical complaints from the field center on what many describe as the "ERP-ification" of healthcare IT. As Oracle has standardized and consolidated Cerner's architecture onto its own platform, many specialized clinical and billing functions that were built specifically for healthcare workflows have been generalized or removed in favor of Oracle's standard enterprise software patterns. The system, some users argue, is becoming more like SAP or Oracle Financials and less like a purpose-built healthcare billing engine. ## What RCM Professionals Are Actually Saying? The gap between Oracle's marketing materials and the reported experience of RCM professionals working with the platform day-to-day is significant enough to warrant its own examination. Across forums including r/medicine and r/PrivatePracticeDocs, as well as industry-specific communities, several themes emerge consistently. Support deterioration is the most persistent complaint. RCM directors describe the loss of what the community calls "Level 3" support - the tier of experienced technical specialists who understood not just how to run a ticket, but why the system behaved a certain way and how to craft a real solution. When a complex billing rule breaks — a payer-specific claim edit, a state Medicaid requirement, a bundled payment configuration - getting to someone with genuine architectural knowledge of the system now reportedly takes weeks rather than days. The AI gap between promise and practice is the second major theme. Oracle markets "Ambient Scribes" (AI-generated clinical documentation), "Autonomous Billing" (AI-driven claim submission and follow-up), and sophisticated predictive denial tools. Professionals working with these tools in live environments report that the gap between the marketing and the operational reality is substantial. As one community member summarized it: the AI billing tools automate the workflow, but they also automate the errors. If patient registration and eligibility verification upstream aren't clean, the AI downstream produces clean-looking claims built on bad data — just faster and at higher volume. Federal prioritization at the expense of commercial clients is the third consistent frustration. The perception within the commercial hospital market is that Oracle's engineering and support resources are disproportionately allocated to the VA/DoD federal contract, leaving standard commercial RCM module updates delayed and bug fixes deprioritized. Whether this perception fully reflects Oracle's internal resource allocation is difficult to verify externally, but the consistency of the sentiment across independent sources suggests it reflects at least a partial operational reality. ## What This Means for RCM Leaders in 2026? The picture that emerges from this analysis is not of a failing platform, but of a platform in the middle of a genuinely disruptive transition - and one where the benefits of that transition are still largely theoretical while the costs are already operational. The underlying Oracle Health platform remains capable of handling the revenue cycle complexity of large health systems. The integration between clinical documentation and billing, when it functions as designed, is genuinely valuable. The AI tools, when deployed on clean data foundations, show real promise for denial prevention and AR automation. But the support infrastructure that health systems relied on to make Cerner work - the implementation specialists, the billing rule experts, the upgrade support teams - is being systematically reduced. And the platform is being reshaped around Oracle's broader corporate ambitions in ways that don't always align with the specific needs of hospital billing departments. For RCM leaders currently on Oracle Health, the practical takeaway is this: the platform is not going away, and migration to an alternative EHR is a multi-year, multi-million-dollar undertaking that carries its own substantial risks. What is changing is the nature of the relationship with the vendor. The era of calling a specialist who knew your system is giving way to an era of self-sufficient optimization - health systems building internal Oracle Health expertise rather than relying on Oracle's service organization to provide it. The organizations that will extract the most value from Oracle Health in the next three to five years are those investing now in internal platform expertise, data governance, and front-end workflow discipline — because the AI tools Oracle is building will reward clean data and punish organizational entropy. Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCMAI ### athenahealth Automation | 2026 athenahealth automation: what its shared rules engine standardizes well, and where you still need custom workflow control. Jędrzej SzymulaMarch 23, 2026 ](https://www.flobotics.io/blog/athenahealth-automation)[ RPA ### Automation’s for Everyone: 100 Real-World RPA Use Cases Across Industries | 2026 RPA use cases across industries: see 100 real-world examples of process automation in action, from healthcare to manufacturing. Michał RejmanFebruary 23, 2024 ](https://www.flobotics.io/blog/rpa-use-cases-across-industries)[ Healthcare ### Laboratory Automation Solutions: Enhancing Efficiency and Compliance in Healthcare Laboratory automation solutions: streamline sample processing and test result interpretation to future-proof your lab operations. Bart TeodorczukSeptember 24, 2024 ](https://www.flobotics.io/blog/laboratory-automation-solutions) [All articles →](https://www.flobotics.io/blog) --- # Insurance Eligibility Verification in Healthcare, Explained Canonical: https://www.flobotics.io/blog/eligibility-verification-explanation Author: Krzysztof Szwed Published: 2026-04-08 Updated: 2026-09-08 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Insurance Eligibility Verification in Healthcare, Explained [Eligibility](https://www.flobotics.io/blog?category=eligibility)[Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Insurance Eligibility Verification in Healthcare, Explained [Krzysztof SzwedHead of Delivery at Flobotics](https://www.flobotics.io/our-editorial-team#szwed) Published April 08, 2026Updated September 8, 2026 Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Eligibility Verification Real-time confirmation of a patient's current insurance status, coverage, benefits, and financial responsibilities prior to service. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## FAQ: What does it mean to check eligibility? Checking eligibility means confirming that a person, claim, or policy meets the specific rules required to receive a benefit, service, or coverage right now. In healthcare specifically, this usually means verifying that a patient's insurance is active and that the planned visit or service is covered before it happens. What is an example of eligibility? A doctor's office contacting a patient's insurance company before an appointment to confirm the policy is active and covers the planned visit is a common healthcare example. Another is a state agency reviewing someone's income and assets to determine whether they qualify for Medicaid. What is current eligibility? It refers to whether coverage or qualification is active right now, as opposed to having expired, lapsed, or not yet started. A plan can show someone was eligible in the past without confirming they still are today, which is exactly why eligibility gets rechecked before each service. Written byKrzysztof Szwed Head of Delivery at Flobotics. [More from Krzysztof](https://www.flobotics.io/our-editorial-team#szwed) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### Patient Access: The Front End of the Revenue Cycle What is patient access? A guide to the front-end RCM steps - scheduling, registration, eligibility checks, and prior authorization - that start every claim. Jędrzej SzymulaJune 02, 2026 ](https://www.flobotics.io/blog/patient-access-explanation)[ HealthcareRCM ### What Is Prior Authorization (Pre-Auth) in Healthcare? Prior authorization (pre-auth), explained: the process behind healthcare's 13-hour weekly physician burden - and how automation cuts each cycle to minutes. Bart TeodorczukApril 30, 2026 ](https://www.flobotics.io/blog/prior-authorization-pre-auth-explanation)[ HealthcareRCM ### Medical Necessity: How Payers Decide What They Cover Medical necessity, explained: how payers decide if a service qualifies for coverage, and what proof stops denials before they start. Bart TeodorczukMarch 30, 2026 ](https://www.flobotics.io/blog/medical-necessity-explanation) [All articles →](https://www.flobotics.io/blog) --- # What Is Medical Coding? ICD-10 vs. CPT/HCPCS Canonical: https://www.flobotics.io/blog/medical-coding-explanation Author: Jędrzej Szymula Published: 2026-04-07 Updated: 2026-09-14 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/What Is Medical Coding? ICD-10 vs. CPT/HCPCS [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # What Is Medical Coding? ICD-10 vs. CPT/HCPCS [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published April 07, 2026Updated September 14, 2026 On this page - [Medical Coding](#medical-coding) - [ICD-10 vs. CPT/HCPCS — What's the Difference?](#icd-10-vs-cpt-hcpcs-what-s-the-difference) - [Why Coding Accuracy Drives Clean Claims](#why-coding-accuracy-drives-clean-claims) - [Who Codes, and How It Connects to RCM](#who-codes-and-how-it-connects-to-rcm) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Medical Coding The translation of clinical diagnoses (ICD-10) and procedures (CPT/HCPCS) into standardized alphanumeric codes for claims processing. ## ICD-10 vs. CPT/HCPCS — What's the Difference? Medical coding relies on two distinct code sets that answer different questions on a claim. ICD-10-CM codes describe why a patient was seen — the diagnosis or reason for the encounter. CPT and HCPCS codes describe what was done — the procedure, service, or supply provided. - ICD-10-CM (diagnosis codes): Maintained by CMS together with the CDC's National Center for Health Statistics, these alphanumeric codes classify diagnoses and reasons for visits across every care setting. As CMS notes on its ICD-10 codes page, ["ICD-10 applies to all parties covered by the Health Insurance Portability and Accountability Act (HIPAA), not just providers who bill Medicare or Medicaid"](https://www.cms.gov/medicare/coding-billing/icd-10-codes). - CPT (procedure codes): Owned and updated by the American Medical Association, the [AMA's CPT code set basics and resources](https://www.ama-assn.org/practice-management/cpt/cpt-code-set-basics-and-resources) guide describes it as a listing of descriptive terms and five-digit codes for reporting medical services and procedures performed by physicians and other qualified health care professionals. More than 11,000 codes make up the set today. - HCPCS Level II codes: Also maintained by CMS, these cover supplies, durable medical equipment, and services — like ambulance transport or certain drugs — that fall outside the CPT code set, and are used heavily in Medicare and Medicaid billing. ## Why Coding Accuracy Drives Clean Claims A claim only pays cleanly when the diagnosis code, procedure code, and any required modifiers line up with what the payer's adjudication system expects. Mismatched codes, missing modifiers, or stale code sets are a common cause of "technical" denials — claims rejected on formatting grounds before a payer ever evaluates the clinical picture. Flobotics's own [claims management automation case study for Gentem Health](https://www.flobotics.io/case-studies/98-reduction-in-manual-claim-prep-claims-management-automation) shows this dynamic directly: standardizing how CPT/ICD codes, modifiers, and provider identifiers were captured and validated before submission lifted the clean claim rate from roughly 80% to 95%, cutting the coding-driven denials that have nothing to do with medical necessity. A similar pattern appears in Flobotics's [document-to-claim automation case study with SuperBill](https://www.flobotics.io/case-studies/70-faster-claim-turnaround-time-ctt-claim-management-automation), where an AI agent structured CPT/ICD codes and modifiers extracted from unstructured superbills, cutting claim turnaround time by about 70% and reducing document-related error rates by roughly 35%. ## Who Codes, and How It Connects to RCM Medical coding is typically performed by certified coders — often credentialed through organizations like AAPC or AHIMA — working from clinical documentation, or increasingly with computer-assisted coding tools that suggest codes for human review. Once codes are assigned, they flow directly into claims processing, eligibility checks, and, when something doesn't match, denials management — making coding accuracy one of the earliest and highest-leverage points to get right in the revenue cycle. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## FAQ: What's the difference between CPT, ICD-10, and HCPCS codes? ICD-10 codes the diagnosis, CPT codes the procedure performed, and HCPCS Level II codes supplies, equipment, and services that CPT doesn't cover. Is medical billing the same as medical coding? No. A coder translates clinical documentation into diagnosis and procedure codes. A biller uses those codes to build and submit the claim, then manages everything that happens to it afterward. Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### Charge Capture: What It Is and How It Works in RCM What is charge capture? How converting clinical services into billable charges kicks off the revenue cycle, and why missed charges are lost revenue. Karl MielnickiJune 03, 2026 ](https://www.flobotics.io/blog/charge-capture-explanation)[ HealthcareRCM ### Clinical Documentation Integrity (CDI): Why It Matters Clinical Documentation Integrity (CDI), explained: how documentation gaps drive undercoding and silent revenue leakage. Karl MielnickiMarch 03, 2026 ](https://www.flobotics.io/blog/clinical-documentation-integrity-cdi-explanation)[ HealthcareRCM ### What Is Claim Scrubbing? What Gets Checked Before Submission Claim scrubbing, explained: how automated pre-submission checks catch errors that cost $25-$44 per claim to fix after denial. Krzysztof SzwedMarch 24, 2026 ](https://www.flobotics.io/blog/claim-scrubbing-explanation) [All articles →](https://www.flobotics.io/blog) --- # We are a "Top Workday Implementation Partner for 2026" according to SuperbCompanies! Canonical: https://www.flobotics.io/blog/flobotics-superbcompanies-top-workday-implementation-company-2026 Author: Jędrzej Szymula Published: 2026-04-05 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/We are a "Top Workday Implementation Partner for 2026"… [AI](https://www.flobotics.io/blog?category=ai)[RPA](https://www.flobotics.io/blog?category=rpa) # We are a "Top Workday Implementation Partner for 2026" according to SuperbCompanies! [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published April 05, 2026Updated September 1, 2026 Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ‍Flobotics Named a Top Workday Implementation Partner for 2026! We’ve just been officially featured by SuperbCompanies in their curated list of the Best Workday Implementation Partners of 2026. In an industry where 49 companies were vetted for their technical excellence, Flobotics stands out as a top-rated selection for organizations seeking "unparalleled solutions" and "transformative results." ### What SuperbCompanies Wrote About Us: The ranking identifies Flobotics as an industry leader specifically chosen for our ability to excel in streamlining complex processes and implementing cutting-edge solutions. According to the 2026 feature, we were selected because we excel in: - Implementation & Customization: Building Workday stacks that actually fit the unique goals of our clients. - Optimization: Ensuring companies aren't just "using" Workday, but extracting its full value. - Delivering Results: Being part of a curated group known for "delivering unparalleled solutions" that drive real business impact. This recognition isn't just about being on a list—it’s about being verified as a top resource for companies looking to move away from rigid, manual systems toward a fully optimized, automated future. You can see the full list of the "Top Workday Implementation Partners" and read the entire entry here: ‍[Top Workday Implementation Partners - SuperbCompanies 2026](https://superbcompanies.com/categories/workday-implementation-partners/) Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ AIRCM ### Forbes named us "#3 Best Polish Startup of 2025"! Flobotics named #3 on Forbes Poland's Best Polish Startups of 2025 (Service Company category) - recognized for scaling RPA and AI services in the US. Jędrzej SzymulaMarch 18, 2025 ](https://www.flobotics.io/blog/flobotics-forbes-polish-best-startups-2025)[ RPAAI ### We saved $2 Million from a 50% improvement for PRMG using UiPath! PRMG loan processing automation case study - see how UiPath RPA delivered a 6:1 ROI and $1.2M in labor savings over 36 months for this mortgage lender. Jędrzej SzymulaAugust 07, 2025 ](https://www.flobotics.io/blog/flobotics-prmg-loan-processing-rpa-automation)[ RPAAI ### We Are Among the Top Business Consulting Companies in the USA for 2026! Flobotics named a top business consulting company in the USA for 2026 by Selectedfirms - recognized for business growth and strategy expertise. Jędrzej SzymulaJanuary 26, 2026 ](https://www.flobotics.io/blog/flobotics-top-business-consulting-companies-2026) [All articles →](https://www.flobotics.io/blog) --- # What Is Denials Management? Process and Benchmarks Canonical: https://www.flobotics.io/blog/denials-management-explanation Author: Karl Mielnicki Published: 2026-04-02 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/What Is Denials Management? Process and Benchmarks CTO Notes [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # What Is Denials Management? Process and Benchmarks [Karl MielnickiCTO & Co-Founder of Flobotics](https://www.flobotics.io/our-editorial-team#mielnicki) Published April 02, 2026Updated September 1, 2026 On this page - [What Is Denials Management?](#what-is-denials-management) - [Denial vs. Rejection — An Important Distinction](#denial-vs-rejection-an-important-distinction) - [Types of Denials](#types-of-denials) - [The Denials Management Process](#the-denials-management-process) - [When Does Denials Management Matter Most in RCM?](#when-does-denials-management-matter-most-in-rcm) - [The Financial Stakes](#the-financial-stakes) - [Benchmarks to Track](#benchmarks-to-track) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Is Denials Management? Denials management is the end-to-end process by which a healthcare organization identifies denied or rejected insurance claims, investigates the reason for each denial, corrects or appeals where appropriate, and implements upstream changes to prevent the same denials from recurring. It is not a one-time fix — it is a continuous, structured workflow that sits at the intersection of clinical documentation, billing accuracy, payer policy, and operational follow-through. In revenue cycle management, denials management is often described as both reactive (fixing what was denied) and proactive (preventing denials before claims leave the building). High-performing RCM teams do both. ## Denial vs. Rejection — An Important Distinction These two terms are often used interchangeably, but they are not the same: - Rejection: The claim was not accepted into the payer's system — typically due to a formatting or data error (wrong NPI, missing field, invalid code). Rejections happen before adjudication and must be corrected and resubmitted. - Denial: The claim was received and processed, but payment was refused. Denials require either a corrected resubmission or a formal appeal, and they are governed by payer-specific timely filing limits. Understanding this distinction matters because denials trigger appeal rights and have regulatory deadlines, while rejections are simply administrative corrections. ## Types of Denials Denials are broadly categorized as soft or hard: - Soft denials are temporary and correctable — missing documentation, wrong date of service, authorization not yet received. They can often be resolved by resubmitting with additional information. - Hard denials are more definitive — lack of medical necessity, non-covered service, or untimely filing. They typically require a formal appeal or must be written off. Within those categories, the most common denial types RCM teams encounter include: - Authorization-related denials: Service was performed without prior authorization or the auth obtained did not match what was billed. - Medical necessity denials: The payer determined the service was not clinically appropriate or not sufficiently documented. These are hard denials and require physician-supported appeals. - Coding denials: Incorrect CPT, ICD-10, or modifier codes. Often correctable with a corrected claim. - Eligibility denials: The patient was not covered on the date of service, or benefits were exhausted. These require either a corrected claim (if the error is on the provider side) or patient billing. - Duplicate claim denials: The claim was submitted more than once. These require investigation to confirm whether a payment was already made. - Timely filing denials: The claim was submitted past the payer's deadline. These are rarely overturnable without documented proof of prior timely submission. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## The Denials Management Process Effective denials management follows a structured cycle: 1. Identification and triage. Every denied claim should be captured in a denial worklist and categorized by payer, denial reason code (CARC/RARC), dollar value, and denial type. Prioritization should be based on value, actionability, and timely filing deadlines — not just first-in, first-out. 2. Root cause analysis. Before working a denial, identify whether it is a one-off error or part of a pattern. Payer-level denial rate trending, denial reason code frequency reports, and provider-level denial analysis are key tools here. [HFMA's guidance on navigating the rising tide of denials](https://www.hfma.org/revenue-cycle/denials-management/navigating-the-rising-tide-of-denials/) emphasizes data-driven root cause analysis as the foundation of any effective denials program. 3. Rework and resubmission. For correctable denials, the billing team corrects the claim (updated codes, appended documentation, corrected patient data) and resubmits. A corrected claim is not the same as an appeal — they use different claim submission processes and are governed by different timelines. 4. Appeals. When the denial cannot be corrected at the claim level — typically for medical necessity or coverage disputes — a formal appeal is filed. Appeals should include a cover letter, clinical documentation, relevant payer policy language, and if appropriate, a physician attestation. Appeal success rates have declined in recent years: the median success rate for commercial plan appeals dropped from 56% to 45%, according to an Advisory Board survey cited by [Becker's Hospital Review](https://www.beckershospitalreview.com/strategy/denial-management-in-healthcare-turning-data-into-action/), making appeal quality more important than ever. 5. Prevention. The goal of any mature denials management program is to reduce denial volume at the source. This means feeding denial patterns back into pre-service workflows: updating prior auth checklists, refining documentation templates, correcting claim edits, and training billers and clinicians on recurring problem areas. ## When Does Denials Management Matter Most in RCM? Denials management is always relevant, but becomes especially critical in these situations: - Payer policy changes: Medicare Advantage and commercial payers routinely update their coverage policies, prior auth requirements, and coding guidelines. Practices that do not actively monitor payer bulletins see denial spikes after policy changes take effect. - Volume surges: High-volume periods (post-holiday catch-up, after a backlog clearance) are when denial follow-up most often falls behind. Unworked denials that age past timely filing deadlines become permanent write-offs. - New service lines or providers: Onboarding a new specialty or provider credentialing issues are common triggers for eligibility and authorization denials that require a targeted response during the ramp-up period. - EHR or clearinghouse migrations: System transitions are among the most common causes of sudden denial spikes. Claims that were formatted correctly in the old system often need adjustment for the new workflow. ## The Financial Stakes Denials are not a minor nuisance. According to [Premier's 2022 claims survey, cited by HFMA](https://www.hfma.org/fast-finance/ai-automation-payer-denials-management/), providers spend an estimated $19.7 billion annually processing denied claims, with the average denial costing nearly $44 per claim to rework. Twenty-two percent of healthcare organizations report losing at least $500,000 per year to denials alone. Meanwhile, denial rates are rising. Medicare Advantage denials increased nearly 56% in recent years; commercial plan denials climbed over 20%. From 2022 to 2024, the share of providers reporting increasing denials jumped from 42% to 77%. These trends make a passive, reactive denials program increasingly costly. ## Benchmarks to Track Key metrics for a denials management program include: - Initial denial rate: Best-in-class practices achieve below 5%. Industry average is 8–12%. - Denial overturn rate: The percentage of appealed denials that result in payment. Target: 65%+. - Denial write-off rate: The percentage of denials that are ultimately written off without recovery. Should be under 3% of total charges. - Days to work a denial: Speed matters; claims worked within 7 days of denial have significantly higher recovery rates than those left for 30+ days. Automation is transforming this space. AI-driven systems now handle denial triage, auto-populate appeal letters based on payer-specific requirements, and track appeal outcomes to continuously refine strategy — though [HFMA notes that AI adoption in denials management still lags behind other RCM applications](https://www.hfma.org/revenue-cycle/denials-management/ai-adoption-in-denials-management-lags-as-other-rcm-uses-expand/), with only about one in five providers currently applying it. Written byKarl Mielnicki CTO & Co-Founder of Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### Denials Appeal Process: Levels of Appeal Explained Denials appeal process, explained: with commercial overturn rates dropping from 56% to 45%, see what still wins appeals. Bart TeodorczukMarch 18, 2026 ](https://www.flobotics.io/blog/denials-appeal-explanation)[ HealthcareRCM ### Initial Denial Rate: How to Measure and Lower It Initial denial rate, explained: what counts as a first-pass claim rejection and how to benchmark and lower yours in 2026. Jędrzej SzymulaMay 18, 2026 ](https://www.flobotics.io/blog/initial-denial-percentage-explanation)[ HealthcareRCM ### What Is Claim Scrubbing? What Gets Checked Before Submission Claim scrubbing, explained: how automated pre-submission checks catch errors that cost $25-$44 per claim to fix after denial. Krzysztof SzwedMarch 24, 2026 ](https://www.flobotics.io/blog/claim-scrubbing-explanation) [All articles →](https://www.flobotics.io/blog) --- # Medical Necessity: How Payers Decide What They Cover Canonical: https://www.flobotics.io/blog/medical-necessity-explanation Author: Bart Teodorczuk Published: 2026-03-30 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Medical Necessity: How Payers Decide What They Cover [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Medical Necessity: How Payers Decide What They Cover [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published March 30, 2026Updated September 1, 2026 Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Medical Necessity The determination that a health service is essential for diagnosis or treatment based on professional standards, which dictates payer coverage. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### What Is Prior Authorization (Pre-Auth) in Healthcare? Prior authorization (pre-auth), explained: the process behind healthcare's 13-hour weekly physician burden - and how automation cuts each cycle to minutes. Bart TeodorczukApril 30, 2026 ](https://www.flobotics.io/blog/prior-authorization-pre-auth-explanation)[ EligibilityHealthcareRCM ### Insurance Eligibility Verification in Healthcare, Explained Eligibility verification guide: confirming insurance coverage and patient financial responsibility before the visit, in real time. Krzysztof SzwedApril 08, 2026 ](https://www.flobotics.io/blog/eligibility-verification-explanation)[ HealthcareRCM ### Clinical Documentation Integrity (CDI): Why It Matters Clinical Documentation Integrity (CDI), explained: how documentation gaps drive undercoding and silent revenue leakage. Karl MielnickiMarch 03, 2026 ](https://www.flobotics.io/blog/clinical-documentation-integrity-cdi-explanation) [All articles →](https://www.flobotics.io/blog) --- # Meditech Automation | 2026 Canonical: https://www.flobotics.io/blog/meditech-automation Author: Jędrzej Szymula Published: 2026-03-25 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Meditech Automation | 2026 [AI](https://www.flobotics.io/blog?category=ai)[Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Meditech Automation | 2026 [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published March 25, 2026Updated September 1, 2026 On this page - [Introduction to Meditech Automation](#introduction-to-meditech-automation) - [Understanding Meditech Automation Tools](#understanding-meditech-automation-tools) - [Key Features and Functionalities](#key-features-and-functionalities) - [Levels of Automation in Meditech](#levels-of-automation-in-meditech) - [Implementing Meditech Automation](#implementing-meditech-automation) - [Step-by-Step Integration Process](#step-by-step-integration-process) - [Customization Options for Specific Needs](#customization-options-for-specific-needs) - [Measuring the Impact of Automation](#measuring-the-impact-of-automation) - [Key Performance Indicators (KPIs)](#key-performance-indicators-kpis) - [User Experiences and Feedback](#user-experiences-and-feedback) - [Challenges and Solutions](#challenges-and-solutions) - [Common Issues and Troubleshooting](#common-issues-and-troubleshooting) - [Compliance in Automation](#compliance-in-automation) - [Future Trends in Meditech Automation](#future-trends-in-meditech-automation) - [Innovations and Upcoming Features](#innovations-and-upcoming-features) - [Conclusion](#conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Introduction to Meditech Automation Automation inside MEDITECH is one of the most misunderstood levers in hospital operations. Most organizations approach it as a feature set. It is not. It is an architectural constraint. Meditech was not originally designed as an automation-first platform. Its core strength is transactional reliability, not orchestration. This distinction explains why many automation initiatives inside Meditech environments stall. The system handles data well, but it does not naturally coordinate workflows across departments, especially within revenue cycle operations. The result is predictable. Automation is implemented in fragments. One department gains efficiency while another absorbs additional manual work. Gains cancel out. The real question is not whether Meditech supports automation. It does. The question is how far that automation can be pushed before the system itself becomes the bottleneck. ## Understanding Meditech Automation Tools ### Key Features and Functionalities Meditech provides several native automation capabilities, particularly within scheduling, documentation workflows, and billing processes. These include rule-based triggers, batch processing, and task automation within specific modules. In practice, these tools are most effective when applied to repetitive, deterministic tasks. Examples include claim status checks, appointment confirmations, and internal routing of documentation. Where Meditech struggles is cross-system orchestration. Automation rarely extends cleanly across eligibility verification, coding validation, denial management, and payment reconciliation. These processes span multiple modules and often require external logic layers. This limitation is not unique to Meditech, but it is more pronounced due to its architecture. ### Levels of Automation in Meditech Automation within Meditech environments typically operates across three levels. The first level is task automation. This includes simple triggers such as sending notifications, updating fields, or routing documents. Most organizations reach this level quickly. The second level is workflow automation. This involves chaining multiple tasks together to create end-to-end processes. For example, verifying eligibility, updating patient records, and initiating billing steps in sequence. The third level is orchestration. This is where most implementations fail. True orchestration requires coordination across systems, including external payers, third-party tools, and internal departments. Meditech alone rarely handles this effectively. This is where external automation layers become necessary. Solutions such as https://flobotics.io/ai-agents are designed to sit on top of systems like Meditech, enabling cross-system workflow execution without requiring deep system modifications. ## Implementing Meditech Automation ### Step-by-Step Integration Process Most Meditech automation projects follow a similar lifecycle, though few are executed with sufficient discipline. The first phase is process mapping. This is where organizations often underestimate complexity. Revenue cycle workflows are rarely linear. They include exceptions, manual overrides, and payer-specific variations. Without mapping these variations, automation will break in production. The second phase is constraint identification. Meditech imposes limits on how data can be accessed and manipulated. These constraints must be understood before automation logic is defined. The third phase is implementation. This typically involves configuring native Meditech rules and, where necessary, integrating external automation tools. The final phase is validation. This is where real-world conditions expose weaknesses in the system. Edge cases, incomplete data, and unexpected payer responses all surface during this stage. Most failures occur not during implementation, but during validation. Organizations assume that successful test cases represent production readiness. They do not. ### Customization Options for Specific Needs Customization within Meditech is possible but constrained. Unlike more modern platforms, Meditech does not allow unlimited flexibility in modifying workflows. Customization typically occurs within predefined structures. This creates a trade-off. Stability is preserved, but flexibility is reduced. Organizations requiring deeper customization often implement external automation layers. These systems handle logic that Meditech cannot, such as complex decision-making, multi-system coordination, and dynamic rule execution. For example, AI-driven automation platforms like https://flobotics.io can process unstructured data, interact with external payer systems, and trigger actions across multiple workflows, effectively extending Meditech’s capabilities without altering its core architecture. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Measuring the Impact of Automation ### Key Performance Indicators (KPIs) Most discussions of automation benefits remain vague. Efficiency gains are mentioned, but rarely quantified. In practice, Meditech automation should be evaluated using specific operational metrics. The following table outlines the most relevant indicators for revenue cycle environments: Organizations that implement automation without tracking these metrics are effectively operating blind. Automation does not guarantee improvement. It only creates the potential for it. ### User Experiences and Feedback User experience is rarely discussed in automation strategies, but it is often the deciding factor in long-term success. Initial implementation phases frequently introduce friction. Staff must adapt to new workflows, learn new interfaces, and trust automated processes. Resistance is common, particularly in environments where manual control has been the norm. Real-world sentiment reflects this tension. A Meditech user in a public forum described the experience as follows: “Automation helps, but only after you fight through the setup. The first few months are slower, not faster.” https://www.reddit.com/r/healthIT/ This is consistent with implementation data. Automation introduces a temporary productivity dip before efficiency gains materialize. Organizations that fail to plan for this transition often abandon automation initiatives prematurely. ## Challenges and Solutions ### Common Issues and Troubleshooting Meditech automation projects encounter predictable issues. The first is data inconsistency. Automation relies on structured inputs. Inconsistent or incomplete data leads to errors and exceptions. The second is workflow fragmentation. Automation implemented in one department may not align with processes in another, creating bottlenecks downstream. The third is system limitation. Meditech’s architecture restricts certain types of automation, particularly those requiring real-time external interactions. Effective troubleshooting requires identifying the source of failure. In many cases, the issue is not the automation itself, but the underlying process. Organizations that attempt to automate broken workflows simply accelerate failure. ### Compliance in Automation Automation introduces additional compliance considerations. Processes that were previously manual and auditable become automated and opaque. This raises concerns around: - auditability - data integrity - regulatory compliance Healthcare organizations must ensure that automated workflows remain transparent and traceable. This includes maintaining logs of actions, validating outputs, and ensuring that processes align with regulatory requirements. Guidance from Office of the National Coordinator for Health Information Technology emphasizes the importance of maintaining data integrity and interoperability in automated systems. https://www.healthit.gov Automation does not remove responsibility. It redistributes it. ## Future Trends in Meditech Automation ### Innovations and Upcoming Features The future of Meditech automation will not be defined by Meditech alone. The platform will continue to evolve, but the most significant changes will occur in the layers surrounding it. External automation systems are already transforming how healthcare organizations interact with Meditech environments. Artificial intelligence is enabling: - predictive denial management - automated coding validation - real-time eligibility verification These capabilities extend beyond what Meditech was originally designed to handle. The direction is clear. Meditech will remain a core transactional system, while automation layers handle orchestration and decision-making. Organizations that recognize this division will be able to scale operations more effectively. Those that attempt to force Meditech to perform roles it was not designed for will continue to encounter limitations. ## Conclusion Meditech automation is not a feature upgrade. It is an operational shift. The difference between success and failure lies in how organizations approach it. Treating automation as a set of isolated improvements leads to incremental gains at best. Treating it as a system-wide transformation enables meaningful efficiency improvements and financial impact. The limitations of Meditech are real, but they are not insurmountable. They require a different approach—one that combines native capabilities with external orchestration. Automation does not replace systems like Meditech. It redefines how they are used. Organizations that understand this will not simply automate tasks. They will redesign workflows. That is where the real value lies. ‍ At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RCMHealthcare ### RCM Automation in Healthcare | 2026 RCM automation in healthcare: how RPA, AI, and OCR cut billing errors, speed up claims, and reduce manual work in 2026 revenue cycle management. Bart TeodorczukFebruary 25, 2026 ](https://www.flobotics.io/blog/rcm-automation-healthcare)[ AIHealthcareRPA ### Compliance Automation in Healthcare Healthcare compliance automation: how Continuous Control Monitoring and Agentic AI cut administrative drag by 20-30% in 2026. February 04, 2026 ](https://www.flobotics.io/blog/compliance-automation-healthcare)[ RPAHealthcare ### 10 Benefits of Artificial Intelligence in Healthcare Benefits of artificial intelligence in healthcare: 10 ways AI cuts administrative costs, speeds prior authorizations, and improves data accuracy. Bart TeodorczukJuly 22, 2025 ](https://www.flobotics.io/blog/benefits-artificial-intelligence-healthcare) [All articles →](https://www.flobotics.io/blog) --- # What Is Claim Scrubbing? What Gets Checked Before Submission Canonical: https://www.flobotics.io/blog/claim-scrubbing-explanation Author: Krzysztof Szwed Published: 2026-03-24 Updated: 2026-09-08 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/What Is Claim Scrubbing? What Gets Checked Before Submission [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # What Is Claim Scrubbing? What Gets Checked Before Submission [Krzysztof SzwedHead of Delivery at Flobotics](https://www.flobotics.io/our-editorial-team#szwed) Published March 24, 2026Updated September 8, 2026 On this page - [What Is Claim Scrubbing?](#what-is-claim-scrubbing) - [What Gets Checked During Scrubbing?](#what-gets-checked-during-scrubbing) - [When Is It Used?](#when-is-it-used) - [Why It Matters in RCM](#why-it-matters-in-rcm) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Is Claim Scrubbing? Claim scrubbing is the automated pre-submission review of a claim to detect coding errors, missing data, eligibility mismatches, and rule violations before the claim reaches the payer. It is performed by claim scrubbing software — either integrated into the practice management system or operated as a separate clearinghouse function — and is the primary tool for maximizing clean claim rates. A claim that fails the scrubber is returned to the billing team for correction before submission. A claim that passes is forwarded to the payer (or clearinghouse) as a clean claim, significantly reducing the likelihood of denial or rejection. ## What Gets Checked During Scrubbing? Claim scrubbers apply hundreds of edits simultaneously. The most important categories include: - Patient and payer data validation: Member ID, date of birth, subscriber name, group number, and NPI all match the payer's records. Mismatches here cause eligibility rejections even when the patient is covered. - Code validity: CPT, ICD-10, and HCPCS codes are current and valid for the date of service. Deleted codes or invalid code combinations trigger automatic rejections. - Code pairing and bundling rules: Certain procedure codes cannot be billed together (CCI edits — the CMS National Correct Coding Initiative). Scrubbers catch unbundling errors before payers do. - Modifier checks: Modifiers must be appropriate for the code and payer. Using a modifier that overrides a bundling rule requires supporting documentation — scrubbers flag these for review. - Medical necessity edits: Some payers require specific diagnosis codes to support specific procedures. Scrubbers cross-check CPT-ICD10 pairing against payer-specific LCD/NCD rules. - Authorization flags: If the procedure requires prior authorization and none is on file, the scrubber flags it before the claim goes out. - Timely filing checks: Claims approaching the payer's filing deadline are flagged for priority submission. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## When Is It Used? Claim scrubbing runs as part of the standard billing workflow — typically as claims are batched for submission, either daily or in real time. In high-volume practices or hospital billing departments, scrubbing is fully automated and runs without manual review unless the scrubber flags an error. In smaller practices, the biller may review scrubber output before releasing the batch. Some organizations run a secondary scrub at the clearinghouse level in addition to the practice management system's built-in scrubber. This catches payer-specific edits that the PM system may not have loaded for every payer in the mix. ## Why It Matters in RCM The financial case for thorough claim scrubbing is straightforward. According to [HFMA MAP Key benchmarks](https://www.hfma.org/data-and-insights/map-initiative/map-keys/), best-in-class practices achieve a clean claim rate of 98% or higher — meaning fewer than 2 claims in 100 require any rework before payment. The average denied claim costs between $25 and $44 to rework, and claims that are denied once take an average of 16–22 additional days to pay. More critically, not all denied claims get worked. Industrywide, approximately 65% of denied claims are never resubmitted — meaning every preventable denial that slips past a weak scrubber is a coin-flip between recovered revenue and a write-off. Effective claim scrubbing prevents the denial from ever happening. Scrubbing also reduces days in AR. Claims that go out clean and pay on first submission contribute directly to a lower DAR figure. A practice running a 95% clean claim rate versus a 98% rate on $10M in annual billings is generating hundreds of additional claims per year that require follow-up — adding AR aging, staff time, and write-off risk. ## FAQ: What is a clean claim? A claim that's accepted and paid the first time it's submitted, with no missing information, coding errors, or additional documentation requests from the payer. Written byKrzysztof Szwed Head of Delivery at Flobotics. [More from Krzysztof](https://www.flobotics.io/our-editorial-team#szwed) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### What Is Medical Coding? ICD-10 vs. CPT/HCPCS Medical coding, explained: how ICD-10 diagnoses and CPT/HCPCS procedures become the codes that drive clean claims and reimbursement. Jędrzej SzymulaApril 07, 2026 ](https://www.flobotics.io/blog/medical-coding-explanation)[ HealthcareRCM ### Clean Claim Rate (CCR): Definition and Benchmarks Clean Claim Rate (CCR) guide: the foundational RCM metric behind denials, DAR, and collections, with a 98%+ target. Bart TeodorczukJune 01, 2026 ](https://www.flobotics.io/blog/clean-claim-rate-ccr-explanation)[ HealthcareRCM ### What Is Denials Management? Process and Benchmarks Denials management tackles denial rates now above 20%, where every reworked claim costs about $44 - and prevention pays off. Karl MielnickiApril 02, 2026 ](https://www.flobotics.io/blog/denials-management-explanation) [All articles →](https://www.flobotics.io/blog) --- # athenahealth Automation | 2026 Canonical: https://www.flobotics.io/blog/athenahealth-automation Author: Jędrzej Szymula Published: 2026-03-23 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/athenahealth Automation | 2026 [AI](https://www.flobotics.io/blog?category=ai)[Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # athenahealth Automation | 2026 [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published March 23, 2026Updated September 1, 2026 On this page - [Overview of athenahealth Automation Solutions](#overview-of-athenahealth-automation-solutions) - [Key Features and Functionalities](#key-features-and-functionalities) - [Benefits for Healthcare Practices](#benefits-for-healthcare-practices) - [Real-World Applications of athenahealth Automation](#real-world-applications-of-athenahealth-automation) - [Case Studies of Successful Implementations](#case-studies-of-successful-implementations) - [Integration with Existing Healthcare Systems](#integration-with-existing-healthcare-systems) - [Financial Considerations for Automation](#financial-considerations-for-automation) - [Cost-Benefit Analysis](#cost-benefit-analysis) - [Budgeting for Automation Tools](#budgeting-for-automation-tools) - [Implementation Challenges and Solutions](#implementation-challenges-and-solutions) - [Common Obstacles and How to Overcome Them](#common-obstacles-and-how-to-overcome-them) - [Best Practices for a Smooth Transition](#best-practices-for-a-smooth-transition) - [Regulatory Compliance and Automation](#regulatory-compliance-and-automation) - [Ensuring HIPAA Compliance with athenahealth Automation](#ensuring-hipaa-compliance-with-athenahealth-automation) - [Future Trends in Healthcare Automation](#future-trends-in-healthcare-automation) - [The Evolving Role of athenahealth in a Changing Landscape](#the-evolving-role-of-athenahealth-in-a-changing-landscape) - [FAQs on athenahealth Automation Tools](#faqs-on-athenahealth-automation-tools) - [Troubleshooting and Support for Users](#troubleshooting-and-support-for-users) - [Frequently Asked Questions](#frequently-asked-questions) - [Conclusion](#conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Overview of athenahealth Automation Solutions athenahealth positions itself as a network-enabled platform rather than a traditional EHR vendor. That distinction is not marketing language—it defines how automation behaves inside the system. Unlike legacy systems that rely heavily on static configuration, athenahealth’s architecture is built around continuous updates, centralized rule engines, and shared intelligence across its client network. In theory, this allows automation to evolve without requiring constant local reconfiguration. In practice, it creates a different kind of dependency: organizations rely on athenahealth’s underlying logic rather than fully controlling their own workflows. This has direct implications for automation strategy. athenahealth excels at automating standardized processes at scale, particularly in billing, eligibility, and patient communication. Where it becomes more complex is in handling edge cases, payer-specific nuances, and highly customized workflows that fall outside the platform’s shared logic model. Automation in athenahealth is therefore not just a technical feature. It is a negotiation between what the platform standardizes and what the organization needs to control. ### Key Features and Functionalities athenahealth’s automation capabilities are concentrated around its revenue cycle and front-office workflows. Core features include automated eligibility checks, claim scrubbing, denial management workflows, and patient engagement tools such as reminders and digital intake. One of the defining characteristics of the platform is its rules engine, which continuously updates based on payer behavior and network-wide data. This allows certain processes—such as claim validation and payer rule enforcement—to improve over time without manual intervention. However, this strength introduces a limitation. Organizations cannot always fully customize these rules. They operate within the boundaries defined by athenahealth’s shared infrastructure. This is where external orchestration layers begin to play a role. Systems such as https://flobotics.io/ai-agents are increasingly used to extend athenahealth’s automation by handling tasks that require cross-system coordination, unstructured data processing, or logic that falls outside the platform’s native capabilities. ### Benefits for Healthcare Practices The primary benefit of athenahealth automation is reduction of manual administrative workload. Tasks that traditionally required staff intervention—such as eligibility verification, claim submission, and payment posting—can be partially or fully automated. This translates into measurable operational improvements. Practices often report reductions in days in accounts receivable, improved claim acceptance rates, and decreased staff hours per transaction. More importantly, automation improves consistency. Manual processes introduce variability, which leads to errors and rework. Automated workflows enforce standardized logic, reducing variation and improving predictability. The impact extends beyond efficiency. Automation also influences patient experience. Automated reminders, streamlined intake processes, and faster billing cycles reduce friction across the patient journey. However, these benefits are not automatic. They depend on how well the organization aligns its workflows with the platform’s automation capabilities. ## Real-World Applications of athenahealth Automation ### Case Studies of Successful Implementations In high-performing environments, athenahealth automation is used to standardize revenue cycle workflows across multiple locations. Multi-site practices, in particular, benefit from centralized rule enforcement and consistent billing logic. One example involves a mid-sized outpatient network that implemented automated eligibility verification and claim scrubbing within athenahealth. The result was a measurable reduction in claim denials and a faster reimbursement cycle. The key factor was not the automation itself, but the elimination of variation across sites. Another case highlights denial management. By leveraging athenahealth’s automated workflows, a provider organization was able to identify common denial patterns and address them systematically. This reduced rework and improved first-pass resolution rates. These examples illustrate a broader pattern. Automation delivers value when it reduces variability, not just workload. ### Integration with Existing Healthcare Systems athenahealth is designed to function as a central platform, but no healthcare organization operates within a single system. Integration with EHRs, laboratory systems, payer portals, and external tools is unavoidable. This is where automation becomes more complex. Native integrations handle standard data exchanges effectively, but gaps emerge when workflows extend beyond predefined interfaces. For example, coordinating eligibility verification with external payer systems, or reconciling data between athenahealth and third-party analytics platforms, often requires additional logic. External automation layers such as https://flobotics.io are used to bridge these gaps. These systems can interact with multiple platforms, process data across environments, and execute workflows that athenahealth alone cannot orchestrate. The result is not replacement, but extension. athenahealth remains the core system, while automation layers enable broader operational coordination. ## Financial Considerations for Automation ### Cost-Benefit Analysis Automation in athenahealth is often evaluated in terms of efficiency gains, but this perspective is incomplete. The financial impact must be assessed across multiple dimensions, including labor costs, revenue leakage, and cash flow timing. The following table outlines the primary financial considerations: The most significant gains typically come from reducing denial rates and accelerating payment cycles. Labor savings, while important, are often secondary. ### Budgeting for Automation Tools Budgeting for athenahealth automation requires understanding both direct and indirect costs. Direct costs include platform fees and implementation expenses. Indirect costs include training, workflow redesign, and temporary productivity loss during transition. One of the most overlooked factors is the cost of underutilization. Many organizations invest in automation features but fail to fully implement them, resulting in minimal return on investment. A realistic budget must account for: - implementation time - staff training - process redesign - ongoing optimization Automation is not a one-time investment. It is an operational capability that requires continuous refinement. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Implementation Challenges and Solutions ### Common Obstacles and How to Overcome Them Automation initiatives within athenahealth environments encounter consistent challenges. The first is misalignment between workflows and system capabilities. Organizations attempt to automate processes without adapting them to the platform’s logic, resulting in inefficiencies. The second is data inconsistency. Automation depends on structured, reliable data. Incomplete or inconsistent inputs lead to errors and exceptions. The third is resistance from staff. Automation changes how work is performed, which can create uncertainty and pushback. Addressing these challenges requires a structured approach. Processes must be standardized before automation is applied. Data quality must be improved at the source. Staff must be trained not only on how automation works, but why it is implemented. ### Best Practices for a Smooth Transition Successful implementations share a common approach. They begin with process mapping, identifying where automation will create the most impact. They then align workflows with system capabilities, rather than forcing the system to fit existing processes. Pilot programs are often used to validate assumptions before full deployment. This allows organizations to identify issues early and refine their approach. Continuous monitoring is essential. Automation must be measured and adjusted over time to maintain effectiveness. ## Regulatory Compliance and Automation ### Ensuring HIPAA Compliance with athenahealth Automation Automation does not eliminate compliance requirements. It changes how they must be managed. Processes that were previously manual become automated, which can reduce visibility if not properly monitored. Organizations must ensure that automated workflows remain transparent and auditable. Compliance with regulations such as the Health Insurance Portability and Accountability Act remains critical. https://www.hhs.gov/hipaa This includes maintaining secure data handling practices, ensuring access controls, and documenting how automated processes operate. Guidance from Office of the National Coordinator for Health Information Technology emphasizes the importance of interoperability and data integrity in automated environments. https://www.healthit.gov Automation increases efficiency, but it also increases the scale at which errors can occur. Compliance frameworks must evolve accordingly. ## Future Trends in Healthcare Automation ### The Evolving Role of athenahealth in a Changing Landscape The future of athenahealth automation will be shaped by its role within a broader ecosystem of healthcare technologies. Artificial intelligence and machine learning are already influencing automation capabilities, enabling predictive analytics, automated coding validation, and advanced denial management strategies. At the same time, the limitations of single-platform automation are becoming more apparent. Healthcare workflows span multiple systems, and no single platform can fully orchestrate them. This is leading to a layered architecture. athenahealth provides the core transactional system, while external automation platforms handle orchestration and decision-making. Solutions such as https://flobotics.io/healthcare-automation are positioned within this layer, enabling organizations to connect disparate systems and execute workflows across environments. The direction is clear. Automation will not replace platforms like athenahealth. It will redefine how they are used. ## FAQs on athenahealth Automation Tools ### Troubleshooting and Support for Users Common issues in athenahealth automation include incorrect rule configuration, data mismatches, and integration gaps. Troubleshooting requires identifying whether the issue originates within the platform or in external systems. Support structures must include both technical and operational expertise. Automation failures are rarely purely technical. They often reflect underlying process issues. ### Frequently Asked Questions Organizations frequently ask how quickly automation delivers ROI. The answer depends on implementation quality. Well-executed projects can show improvements within months, while poorly implemented ones may fail to deliver measurable benefits. Another common question concerns customization limits. athenahealth allows configuration within defined boundaries, but deeper customization often requires external tools. The final question is whether automation reduces staffing needs. In practice, it shifts them. Staff move from manual task execution to oversight and exception management. ## Conclusion athenahealth automation is not a plug-and-play solution. It is an operational capability that requires alignment between technology, processes, and organizational structure. The platform provides strong automation tools, particularly for standardized workflows. Its limitations emerge in complex, cross-system processes that require orchestration beyond its native capabilities. Organizations that recognize these boundaries can design effective automation strategies. They combine athenahealth’s strengths with external systems where necessary, creating a layered approach to automation. Those that do not will continue to experience partial gains and persistent inefficiencies. Automation, in this context, is not about eliminating work. It is about redesigning how work is performed. That distinction determines whether it delivers real value. ‍ At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareAIRCM ### Meditech Automation | 2026 Meditech automation: why strong transaction handling still stalls on cross-workflow orchestration, and how to scale past it. Jędrzej SzymulaMarch 25, 2026 ](https://www.flobotics.io/blog/meditech-automation)[ RCMHealthcare ### RCM Automation in Healthcare | 2026 RCM automation in healthcare: how RPA, AI, and OCR cut billing errors, speed up claims, and reduce manual work in 2026 revenue cycle management. Bart TeodorczukFebruary 25, 2026 ](https://www.flobotics.io/blog/rcm-automation-healthcare)[ AIHealthcareRPA ### Compliance Automation in Healthcare Healthcare compliance automation: how Continuous Control Monitoring and Agentic AI cut administrative drag by 20-30% in 2026. February 04, 2026 ](https://www.flobotics.io/blog/compliance-automation-healthcare) [All articles →](https://www.flobotics.io/blog) --- # Contractual Adjustment (Allowance): Meaning in Medical Billing Canonical: https://www.flobotics.io/blog/contractual-adjustment-allowance-explanation Author: Krzysztof Szwed Published: 2026-03-20 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Contractual Adjustment (Allowance): Meaning in Medical Billing [Healthcare](https://www.flobotics.io/blog?category=healthcare) # Contractual Adjustment (Allowance): Meaning in Medical Billing [Krzysztof SzwedHead of Delivery at Flobotics](https://www.flobotics.io/our-editorial-team#szwed) Published March 20, 2026Updated September 1, 2026 On this page - [What Is a Contractual Adjustment?](#what-is-a-contractual-adjustment) - [Where Does It Show Up?](#where-does-it-show-up) - [When Is It Used?](#when-is-it-used) - [Why It Matters in RCM](#why-it-matters-in-rcm) - [Contractual Adjustment vs. Other Write-Offs](#contractual-adjustment-vs-other-write-offs) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Is a Contractual Adjustment? A contractual adjustment — also called a contractual allowance — is the difference between the amount a provider bills for a service and the amount the insurance company is contractually obligated to pay. Providers who participate in insurance networks agree, as a condition of that participation, to accept the payer's fee schedule as payment in full. The gap between billed charges and the allowed amount is written off. It cannot be billed to the patient. The formula is simple: Contractual Adjustment = Billed Charge − Payer-Contracted Allowed Amount For example: a provider bills $250 for an office visit. Under the contract with a commercial payer, the allowed amount is $140. The contractual adjustment is $110. The provider collects $140 (split between payer and patient responsibility) and writes off the rest. ## Where Does It Show Up? Contractual adjustments appear on the Explanation of Benefits (EOB) or Electronic Remittance Advice (ERA) after a claim is processed. On the remittance, look for: - Group Code CO (Contractual Obligation) - CARC 45 (Charges exceed your contracted/legislated fee arrangement) These codes tell your billing team that the write-off is expected and contractually required — not a denial, not an error, not a negotiable amount. According to [HFMA's MAP Initiative](https://www.hfma.org/data-and-insights/map-initiative/map-keys/), contractual allowances are a standard component of net patient service revenue calculations and must be tracked separately from administrative write-offs and charity care. ## When Is It Used? Contractual adjustments are applied every time a claim from an in-network payer is adjudicated. They are a routine part of the payment posting process. Your billing team or practice management system should automatically calculate and post these adjustments when remittances are received. They become especially important to track in the following situations: - Contract renewals: When a payer renegotiates rates, the allowed amounts change — and so do your contractual adjustments. Tracking adjustment trends by payer helps you see whether a contract revision actually improved reimbursement. - Fee schedule audits: Payers sometimes underpay relative to the contracted rate. When the posted contractual adjustment is larger than the correct amount, it may indicate a payer processing error or underpayment — not a legitimate write-off. - Financial reporting: Contractual adjustments are subtracted from gross patient service revenue to arrive at net patient service revenue on the income statement. Overstating adjustments artificially deflates revenue; understating them inflates it. - Out-of-network billing: Providers who see out-of-network patients are not bound by a fee schedule. In these cases, the billed charge is the full collectible amount, and any reduction negotiated after the fact becomes a contractual adjustment only if a separate agreement is in place. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Why It Matters in RCM Contractual adjustments are non-negotiable — but they are not always posted correctly. This is where they become a significant RCM risk: Underpayments disguised as contractual adjustments. If a payer pays less than the contracted rate and billing staff accept it as a routine write-off, revenue is permanently lost. [Becker's Hospital Review](https://www.beckershospitalreview.com/finance/revenue-cycle-management-challenges-in-laboratory-outreach.html) notes that inadequate tools for detecting partial payments lead to staff accepting underpayments as contractual write-offs, which directly suppresses cash collected. Impact on Net Collection Rate. NCR uses contractual adjustments in its denominator: NCR = Payments ÷ (Charges − Contractual Adjustments). If adjustments are over-posted — for instance, applying a Medicare rate to a commercial claim — the denominator shrinks, NCR looks artificially healthy, and real underpayment goes undetected. Contractual Adjustment Rate (CAR) as a KPI. CAR measures what percentage of gross charges are written off as contractual adjustments. Industry averages range from 50–70% for most specialties, meaning providers realistically collect 30–50% of what they bill. A CAR that deviates significantly from historical norms or from specialty benchmarks warrants investigation. Audit trigger for payer performance. Tracking contractual adjustments by payer and by CPT code allows RCM teams to identify systematic fee schedule errors — cases where a payer has consistently applied the wrong rate. These are recoverable through timely corrected claim submissions or formal appeals. ## Contractual Adjustment vs. Other Write-Offs Not all write-offs are contractual. There are three main categories that must be tracked separately: - Contractual adjustments: Required by the payer contract. Non-negotiable. Not billable to the patient. - Administrative adjustments: Discretionary write-offs made by the provider — small balance write-offs, billing errors, or professional courtesy discounts. - Charity care / bad debt: Amounts written off due to patient inability to pay, either proactively (charity care) or after collection attempts fail (bad debt). Mixing these categories in reporting distorts the picture. Only true contractual adjustments belong in the NCR formula denominator and in the net revenue calculation. Written byKrzysztof Szwed Head of Delivery at Flobotics. [More from Krzysztof](https://www.flobotics.io/our-editorial-team#szwed) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### Healthcare Reimbursements: How Payment Rates Are Set Healthcare reimbursement guide: how payment rates are set and where automation closes the gap between allowed and collected amounts. Karl MielnickiMay 01, 2026 ](https://www.flobotics.io/blog/reimbursements-explanation)[ HealthcareRCM ### Underpayment Recovery in Healthcare, Explained Underpayment recovery uses automated contract comparison to catch the 3-10% of claims payers routinely underpay. Jędrzej SzymulaMay 04, 2026 ](https://www.flobotics.io/blog/underpayment-recovery-explanation)[ HealthcareRCM ### Credit Balance Resolution in Healthcare, Explained Credit balance resolution, explained: why federal law gives providers 60 days to repay Medicare and Medicaid overpayments. Jędrzej SzymulaMarch 18, 2026 ](https://www.flobotics.io/blog/credit-balance-resolution-explanation) [All articles →](https://www.flobotics.io/blog) --- # Credit Balance Resolution in Healthcare, Explained Canonical: https://www.flobotics.io/blog/credit-balance-resolution-explanation Author: Jędrzej Szymula Published: 2026-03-18 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Credit Balance Resolution in Healthcare, Explained [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Credit Balance Resolution in Healthcare, Explained [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published March 18, 2026Updated September 1, 2026 On this page - [What Is Credit Balance Resolution?](#what-is-credit-balance-resolution) - [When Is It Used?](#when-is-it-used) - [Why It Matters in RCM](#why-it-matters-in-rcm) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Is Credit Balance Resolution? A credit balance on a patient account means that more money was collected than was owed — the account has been overpaid. Credit balance resolution is the process of identifying these overpayments, determining who is owed the money (payer, patient, or both), and issuing the appropriate refund or adjustment. Credit balances arise from a variety of causes: a payer pays after the patient has already paid their full balance; a patient overpays their estimated cost-share; duplicate payments are received from two different payers for the same claim; a contractual adjustment was applied incorrectly, resulting in a net credit; or a claim is voided and reprocessed but the original payment was not reversed. ## When Is It Used? Credit balance resolution is a continuous accounts receivable management function, not a periodic cleanup task. Every billing cycle, new credit balances are created by the normal flow of payments and adjustments. High-performing RCM teams review credit balance reports weekly and work outstanding credits within defined windows: - Payer overpayments: Must be identified, investigated, and refunded promptly. For Medicare and Medicaid, the 60-Day Rule (Section 1128J(d) of the Social Security Act) requires providers to report and return identified overpayments within 60 days of identification. Failure to do so constitutes a False Claims Act violation — not just a billing error. - Patient overpayments: Should be refunded or applied as a credit to future services per the patient's preference. Unclaimed patient credits that are held indefinitely may become subject to state unclaimed property (escheatment) laws. - Commercial payer overpayments: Governed by individual payer contracts and state prompt payment laws. Most payers require notification and refund within 30–60 days of identification. ## Why It Matters in RCM Credit balances are a compliance issue first and a financial reporting issue second. On the compliance side, knowingly retaining an identified government program overpayment past the 60-day window creates False Claims Act exposure — with penalties up to three times the amount of the overpayment plus per-claim fines. [HFMA's guidance on managing payer performance](https://www.hfma.org/topics/trends/54833.html) emphasizes that overpayment management must be embedded in the standard AR workflow, not treated as an audit-response activity. On the financial reporting side, unresolved credit balances distort accounts receivable. Credits sitting in AR inflate the gross balance, understate net collectible AR, and can mask the true days-in-AR figure if credits and debits are not properly netted. Auditors and CFOs scrutinizing financial statements will flag a credit balance aging report that shows significant balances outstanding for more than 90 days. Operationally, the risk is that credit balances are quietly written off as revenue rather than refunded — particularly for small-dollar amounts where the cost of processing the refund seems to exceed the value. This practice, while common, creates compliance exposure when the payer is Medicare or Medicaid and is a source of audit findings in both internal and OIG reviews. Best-in-class RCM programs maintain a credit balance rate of under 0.5% of net AR and resolve all identified government payer credits within the 60-day window without exception. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ Healthcare ### Contractual Adjustment (Allowance): Meaning in Medical Billing Contractual adjustment (allowance), explained: why this write-off isn't lost revenue - and how mistracking hides real underpayments. Krzysztof SzwedMarch 20, 2026 ](https://www.flobotics.io/blog/contractual-adjustment-allowance-explanation)[ HealthcareRCM ### Underpayment Recovery in Healthcare, Explained Underpayment recovery uses automated contract comparison to catch the 3-10% of claims payers routinely underpay. Jędrzej SzymulaMay 04, 2026 ](https://www.flobotics.io/blog/underpayment-recovery-explanation)[ HealthcareRCM ### Clinical Documentation Integrity (CDI): Why It Matters Clinical Documentation Integrity (CDI), explained: how documentation gaps drive undercoding and silent revenue leakage. Karl MielnickiMarch 03, 2026 ](https://www.flobotics.io/blog/clinical-documentation-integrity-cdi-explanation) [All articles →](https://www.flobotics.io/blog) --- # Denials Appeal Process: Levels of Appeal Explained Canonical: https://www.flobotics.io/blog/denials-appeal-explanation Author: Bart Teodorczuk Published: 2026-03-18 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Denials Appeal Process: Levels of Appeal Explained [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Denials Appeal Process: Levels of Appeal Explained [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published March 18, 2026Updated September 1, 2026 On this page - [What Is a Denials Appeal?](#what-is-a-denials-appeal) - [Levels of Appeal](#levels-of-appeal) - [When Is It Used?](#when-is-it-used) - [Why It Matters in RCM](#why-it-matters-in-rcm) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Is a Denials Appeal? A denials appeal is the formal administrative process by which a healthcare provider contests an insurance company's decision to deny payment for a claim. When a payer issues a denial, providers generally have the right to challenge that decision through one or more levels of review — providing additional documentation, clinical justification, or policy argument to support the claim. Appeals are distinct from claim corrections. A corrected claim addresses an error in the original submission (wrong code, missing auth number, incorrect patient data) and is resubmitted as a new claim. An appeal challenges the payer's adjudication decision itself — arguing that the denial was wrong based on the clinical record, the payer's own coverage policy, or applicable law. ## Levels of Appeal Most payers provide multiple levels of internal review before an external option becomes available: - First-level (internal) appeal: Filed directly with the payer's claims or appeals department. This is the standard first step and should be accompanied by the denial reason code, the original claim, relevant clinical documentation, and a written argument addressing the specific denial reason. - Second-level appeal: If the first-level appeal is denied, many payers offer a second internal review — sometimes by a different reviewer or a medical director. This level is most productive for medical necessity denials where the clinical record is strong but was not reviewed by a physician on first appeal. - External Independent Review (IRO): For fully-insured health plans subject to state insurance law, an external independent review organization can be requested after internal appeals are exhausted. IRO decisions are typically binding on the payer. This option is less available for self-funded ERISA plans. - Medicare and Medicaid administrative appeals: Government program denials have their own formal multi-level appeals process (for Medicare: Redetermination → Reconsideration by a QIC → ALJ Hearing → Medicare Appeals Council → Federal District Court), with strict deadlines at each level. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## When Is It Used? Appeals are initiated when a denial is received and the denial reason is contestable — meaning the service was clinically appropriate, covered under the payer's policy, and properly documented. Not every denial warrants an appeal: - Denials for timely filing failures are rarely overturnable unless the provider has documented proof of original timely submission. - Denials for non-covered services where the patient's policy clearly excludes the benefit are generally not appealable on clinical grounds. - Medical necessity denials, authorization disputes, and coding disagreements are the highest-value targets for appeal — particularly when the clinical record is complete and supports the level of care provided. Speed matters. Most payers impose appeal filing deadlines ranging from 90 to 180 days from the original denial date. Claims that miss these windows are permanently uncollectable through the appeals process. ## Why It Matters in RCM Appeals are one of the highest-ROI activities in the revenue cycle when focused correctly. According to an Advisory Board survey cited by [Becker's Hospital Review](https://www.beckershospitalreview.com/strategy/denial-management-in-healthcare-turning-data-into-action/), the median success rate for commercial plan denial appeals has fallen from 56% to 45% in recent years — meaning nearly half of all well-constructed appeals still result in payment. For a practice with $500,000 in annual denied claims, even a 45% overturn rate represents significant recoverable revenue. The challenge is that appealing takes time and cost. [Premier's 2022 survey, cited by HFMA](https://www.hfma.org/fast-finance/ai-automation-payer-denials-management/), estimates the average denied claim costs $44 to rework, and complex clinical appeals can require physician review time on top of that. This makes prioritization essential: high-dollar medical necessity denials and systemic payer-pattern denials warrant full appeal effort; low-dollar administrative denials may be better corrected and resubmitted or written off depending on the cost-to-recover ratio. Tracking appeal outcomes by payer, denial reason code, and service line is how mature RCM programs identify which denial types are winnable and which payers are systematically denying claims inappropriately — a pattern that may support contract renegotiation or, in egregious cases, a regulatory complaint. Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### What Is Denials Management? Process and Benchmarks Denials management tackles denial rates now above 20%, where every reworked claim costs about $44 - and prevention pays off. Karl MielnickiApril 02, 2026 ](https://www.flobotics.io/blog/denials-management-explanation)[ HealthcareRCM ### Initial Denial Rate: How to Measure and Lower It Initial denial rate, explained: what counts as a first-pass claim rejection and how to benchmark and lower yours in 2026. Jędrzej SzymulaMay 18, 2026 ](https://www.flobotics.io/blog/initial-denial-percentage-explanation)[ HealthcareRCM ### Clean Claim Rate (CCR): Definition and Benchmarks Clean Claim Rate (CCR) guide: the foundational RCM metric behind denials, DAR, and collections, with a 98%+ target. Bart TeodorczukJune 01, 2026 ](https://www.flobotics.io/blog/clean-claim-rate-ccr-explanation) [All articles →](https://www.flobotics.io/blog) --- # What Is an HRA? | 2026 Canonical: https://www.flobotics.io/blog/what-is-hra Author: Jędrzej Szymula Published: 2026-03-16 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/What Is an HRA? | 2026 [Healthcare](https://www.flobotics.io/blog?category=healthcare) # What Is an HRA? | 2026 [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published March 16, 2026Updated September 1, 2026 On this page - [What is Health Risk Assessment (HRA)?](#what-is-health-risk-assessment-hra) - [Purpose and Importance of HRAs](#purpose-and-importance-of-hras) - [Types of HRAs in Use Today](#types-of-hras-in-use-today) - [Methodologies for Effective HRA Design](#methodologies-for-effective-hra-design) - [Legal and Compliance Considerations](#legal-and-compliance-considerations) - [Driving Patient Engagement in the HRA Process](#driving-patient-engagement-in-the-hra-process) - [Analyzing HRA Results: Implications for Care Management](#analyzing-hra-results-implications-for-care-management) - [Integrating HRAs into Healthcare Systems](#integrating-hras-into-healthcare-systems) - [Global Perspective: Alternative Approaches to Risk Assessment](#global-perspective-alternative-approaches-to-risk-assessment) - [Future Trends and Technological Innovations in HRAs](#future-trends-and-technological-innovations-in-hras) - [Conclusion](#conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What is Health Risk Assessment (HRA)? Health Risk Assessments have been quietly repositioned over the last decade. What began as a preventive care questionnaire has evolved into one of the few scalable mechanisms for identifying forward-looking patient risk. In theory, HRAs sit at the foundation of population health management and value-based care. In practice, most organizations still treat them as compliance artifacts - completed, stored, and rarely operationalized. That gap between intention and execution defines the current state of HRA adoption. At its core, an HRA is a structured process for collecting data that traditional clinical systems fail to capture. Electronic health records are retrospective by design. Claims data is even further removed, reflecting billing logic rather than patient reality. HRAs introduce a different dimension: behavioral, environmental, and social indicators that precede clinical deterioration. This is precisely why they matter. They surface risk before it becomes visible in diagnoses or utilization patterns. The challenge is not whether HRAs are valuable. The challenge is whether healthcare systems are built to use them. ## Purpose and Importance of HRAs The formal purpose of an HRA is early identification of risk factors. That is accurate, but incomplete. In modern healthcare systems—particularly those operating under risk-adjusted reimbursement models - the real function of HRAs is alignment. They align clinical insight with financial reality. Organizations operating within frameworks defined by entities such as the [Centers for Medicare & Medicaid Services ](https://www.cms.gov)depend on accurate patient risk profiles to determine reimbursement levels. When risk is under-captured, revenue is misaligned. When it is misinterpreted, care management resources are deployed inefficiently. HRAs influence both sides of that equation. This dual role creates tension. Clinical teams often view HRAs as administrative overhead, while financial teams see them as essential for risk adjustment. Both perspectives are correct, and both are incomplete. The real value of HRAs emerges only when they are connected to operational workflows that translate risk signals into action. Without that connection, HRAs generate data. With it, they generate outcomes. ## Types of HRAs in Use Today The distinction between clinical and non-clinical HRAs has become more important as healthcare systems expand their understanding of risk. Clinical HRAs focus on measurable indicators - diagnoses, laboratory values, and existing chronic conditions. These inputs are already well represented in EHR systems, which raises an uncomfortable question: what additional value does an HRA provide if it simply duplicates clinical data? The answer lies in non-clinical HRAs. These capture behavioral and social determinants of health, including stress levels, nutrition, housing stability, and access to care. These factors often have a greater impact on long-term outcomes than clinical indicators themselves. Research from [the National Institutes of Health](https://www.nih.gov) has repeatedly demonstrated the influence of these variables on population health trends. Despite this, most healthcare systems still treat non-clinical inputs as secondary. This creates a structural blind spot. Patients who appear stable in clinical records may carry significant unseen risk. HRAs are one of the few tools capable of surfacing that risk before it manifests as utilization. ## Methodologies for Effective HRA Design The majority of HRA implementations fail not because of lack of technology, but because of flawed design assumptions. The most common mistake is treating HRAs as static questionnaires rather than dynamic systems. A well-designed HRA is adaptive. It adjusts based on patient responses, reducing friction for low-risk individuals while capturing deeper insight for high-risk populations. It is also distributed. Instead of relying on a single annual interaction, data collection is integrated across multiple patient touchpoints - appointments, digital check-ins, and remote interactions. Most importantly, an effective HRA is mapped to action before it is deployed. Every question must have an operational consequence. If a patient indicates food insecurity, the system should not simply record that fact. It should trigger an intervention - whether through care management outreach, referral systems, or support services. This is where the gap between design and execution becomes visible. Many organizations collect HRA data without defining how it will be used. The result is predictable: data accumulates, but outcomes do not change. Automation is increasingly being used to close this gap. Systems such as [Flobotics AI Agents](https://www.flobotics.io/rcm-automation) allow healthcare organizations to process intake data, classify risk signals, and route them into downstream workflows without manual intervention. This is not a technological upgrade. It is a structural shift. It transforms HRAs from passive data collection tools into active components of operational infrastructure. ## Legal and Compliance Considerations HRA data introduces a level of sensitivity that exceeds typical clinical documentation. Patients often disclose information in HRAs that they would not share in a direct clinical encounter. This includes mental health concerns, financial stress, and lifestyle behaviors. These data points fall under strict regulatory frameworks, most notably the [Health Insurance Portability and Accountability Act](https://www.hhs.gov/hipaa). Compliance, however, is evolving. Historically, the focus was on data storage and access control. Today, the focus is shifting toward data usage. As predictive analytics and machine learning models begin to incorporate HRA inputs, organizations must ensure that decisions derived from these models are transparent and justifiable. This introduces a new layer of responsibility. It is no longer sufficient to protect data. Organizations must also be able to explain how that data influences clinical and financial decisions. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Driving Patient Engagement in the HRA Process Patient engagement remains one of the most persistent challenges in HRA implementation. Completion rates are often low, and when patients do participate, the quality of responses can vary significantly. The root cause is not lack of awareness. It is lack of perceived relevance. Patients are unlikely to engage with HRAs if they believe the process is purely administrative. This perception is reflected in real-world discussions. One practitioner noted in a public forum: “Every time I get one of these, it feels like paperwork, not care.” ~ Source: [reddit /r/medicine/](https://www.reddit.com/r/medicine/) This sentiment is consistent across systems that treat HRAs as standalone tasks rather than integrated components of care delivery. Organizations that achieve higher engagement do so by embedding HRAs into existing workflows. Digital check-in processes, in-clinic intake systems, and patient portals all provide opportunities to collect data without adding friction. When patients see that their responses influence care decisions, engagement increases. This is not a communication problem. It is a design problem. ## Analyzing HRA Results: Implications for Care Management The real value of HRA data emerges only after it is analyzed and acted upon. This is where most systems fall short. Data is collected, stored, and occasionally reviewed, but rarely integrated into care pathways. High-risk patients remain unidentified until their condition worsens. Preventive interventions are delayed. Opportunities for early engagement are lost. Effective systems operate differently. They treat HRA outputs as triggers. When a patient crosses a predefined risk threshold, the system initiates a response. This may involve scheduling preventive screenings, enrolling the patient in care management programs, or initiating outreach from clinical staff. This approach requires integration with revenue cycle processes. Risk classification influences documentation, coding, and reimbursement. Systems that fail to connect these elements lose both clinical and financial opportunities. ## Integrating HRAs into Healthcare Systems Integration is the defining challenge of HRA implementation. Most healthcare organizations operate within fragmented technology environments, where data flows between systems inconsistently. When HRAs are implemented as standalone tools, they create additional silos. Data is collected but not shared effectively. Clinical teams, care managers, and revenue cycle staff operate with incomplete information. The alternative is a unified architecture in which HRA functions as an input layer feeding into core operational systems. This requires both technical integration and organizational alignment. Ownership of HRA outcomes must be clearly defined. Completion rates alone are not sufficient metrics. Organizations must measure how HRA data influences interventions, utilization, and financial performance. Automation plays a critical role in this process. Successful HRA implementations share a common characteristic: they focus on what happens after data collection. A provider group implementing HRA-driven risk stratification for diabetic patients achieved measurable improvements in outcomes, including reduced hospital readmissions and earlier intervention cycles. The key change was not the assessment itself, but the integration of its outputs into care management workflows. This pattern is consistent across organizations. HRAs generate value only when they are embedded into operational systems. When treated as isolated tools, they produce minimal impact. ## Global Perspective: Alternative Approaches to Risk Assessment The United States is not alone in its use of risk assessment tools, but it differs in its approach. Systems in Singapore, Germany, and China demonstrate alternative models. Singapore integrates risk assessments into national healthcare programs, enabling coordinated preventive strategies. Germany uses risk-adjusted insurance models that align reimbursement with patient complexity. China has developed large-scale predictive systems that leverage extensive data integration. The United States, by contrast, operates within a fragmented environment. HRAs exist, but their impact is inconsistent. The technology is available. The integration is not. ## Future Trends and Technological Innovations in HRAs The next phase of HRA evolution will be defined by continuous data capture and predictive analytics. Wearable devices, remote monitoring systems, and digital health platforms are already generating real-time data streams. These inputs will increasingly replace static assessments, allowing risk models to update continuously. At the same time, artificial intelligence is improving the accuracy of risk prediction. Machine learning models can identify patterns that traditional methods miss, enabling earlier intervention and more precise resource allocation. The challenge is not collecting more data. It is integrating that data into systems capable of acting on it. Organizations that solve this problem will gain a significant advantage in both clinical outcomes and financial performance. ## Conclusion Health Risk Assessments are often described as foundational to modern healthcare. That description is accurate, but incomplete. HRAs are not inherently valuable. Their value depends entirely on how they are used. When integrated into operational workflows, HRAs become powerful tools for identifying risk, guiding care, and aligning financial models. When treated as standalone processes, they become administrative overhead. The distinction between these two outcomes is not technological. It is structural. Healthcare systems that understand this will move beyond data collection. They will build systems that act. ‍ At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### 8 Best Security Practices for RPA Implementation RPA security best practices: 8 steps to manage the security risks of your organization's automation implementation. Krzysztof SzwedSeptember 20, 2021 ](https://www.flobotics.io/blog/8-security-practices-for-rpa-implementation)[ RCMAIHealthcare ### Agentic AI in Healthcare: From Hype to Real-World Impact Agentic AI in healthcare: how it differs from generative AI like ChatGPT and where it's already driving real clinical impact. Jędrzej SzymulaSeptember 22, 2025 ](https://www.flobotics.io/blog/agentic-ai-in-healthcare)[ Healthcare ### Building Automated HIPAA Compliance Workflows with RPA: What Do You Need to Know? HIPAA-compliant automation: how to build RPA workflows that keep healthcare data secure and satisfy HIPAA requirements fully. Michał RejmanAugust 23, 2021 ](https://www.flobotics.io/blog/hipaa-compliance-rpa) [All articles →](https://www.flobotics.io/blog) --- # Revenue Cycle Management in Cardiology Canonical: https://www.flobotics.io/blog/revenue-cycle-management-cardiology Author: Jędrzej Szymula Published: 2026-03-11 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Revenue Cycle Management in Cardiology [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Revenue Cycle Management in Cardiology [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published March 11, 2026Updated September 1, 2026 On this page - [Understanding Cardiology RCM](#understanding-cardiology-rcm) - [Key Components of Cardiology Revenue Cycle Management](#key-components-of-cardiology-revenue-cycle-management) - [Challenges Specific to Cardiology Practices](#challenges-specific-to-cardiology-practices) - [Best Practices for Cardiology Billing and Coding](#best-practices-for-cardiology-billing-and-coding) - [Accurate Coding Strategies for Cardiology Services](#accurate-coding-strategies-for-cardiology-services) - [Common Billing Mistakes](#common-billing-mistakes) - [Payer Relationships in Cardiology | Overview](#payer-relationships-in-cardiology-overview) - [Understanding Payer Dynamics and Regulations](#understanding-payer-dynamics-and-regulations) - [Tips for Reducing Claim Denials](#tips-for-reducing-claim-denials) - [Performance Monitoring in Cardiology RCM](#performance-monitoring-in-cardiology-rcm) - [Key Performance Indicators to Track](#key-performance-indicators-to-track) - [Tools for Enhancing RCM Efficiency](#tools-for-enhancing-rcm-efficiency) - [Lessons Learned from High-Performing Practices](#lessons-learned-from-high-performing-practices) - [Summary](#summary) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Fnancial pulse of a cardiac practice requires demands a specialized approach: the Cardiology Revenue Cycle Management (RCM). As clinical procedures become more complex - ranging from diagnostic imaging to intricate interventional electrophysiology - the administrative back-end must be equally sophisticated to ensure financial viability. Heres our take on it. ## Understanding Cardiology RCM ### Key Components of Cardiology Revenue Cycle Management Cardiology RCM encompasses the entire lifecycle of a patient account, from the moment an appointment is scheduled to the final payment. Because cardiology involves high-cost equipment and specialized consumables, the "front-end" of the cycle - specifically [patient eligibility verification](https://www.flobotics.io/agents/eligibility-check-automation) and [prior authorization](https://www.flobotics.io/agents/prior-authorization-automation) - is more critical here than in primary care. According to the [Centers for Medicare & Medicaid Services (CMS)](https://www.cms.gov/), ensuring clean claim submission starts with precise data capture during the initial patient encounter. ### Challenges Specific to Cardiology Practices The primary hurdle in cardiology is the sheer volume of global surgical packages and the "unbundling" of services that can lead to significant audits. Unlike other specialties, cardiology often involves emergency procedures where prior authorization isn’t possible, requiring a robust appeals process. Furthermore, the rapid evolution of cardiac technology often outpaces the updates in standard billing codes, creating a "gray area" that can delay reimbursements. ## Best Practices for Cardiology Billing and Coding ### Accurate Coding Strategies for Cardiology Services To maintain a healthy bottom line, practices must stay current with the latest CPT® and ICD-10-CM updates. For 2026, the focus has shifted heavily toward digital health and remote patient monitoring (RPM) for chronic heart failure. - Implement "Continuous Documentation": Physicians should document the medical necessity for specific interventions, such as dual-chamber vs. single-chamber pacemakers, immediately following the procedure to ensure the highest coding specificity. - Audit Regularly: Conducting internal "mini-audits" every quarter can identify patterns where modifiers (like -25 or -59) are being misused before they trigger a payer-side investigation. ### Common Billing Mistakes One of the most frequent errors in cardiology billing is the failure to link the correct diagnostic code to the specific procedure performed. For instance, billing for a cardiac stress test without a qualifying diagnosis code like chest pain (R07.9) or shortness of breath (R06.02) will result in an automatic denial. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Payer Relationships in Cardiology | Overview ### Understanding Payer Dynamics and Regulations Payer contracts are not "set it and forget it" documents. In the current 2025–2026 regulatory environment, payers are increasingly adopting value-based care models. Understanding these nuances is essential; for example, new CMS rules for 2026 mandate faster turnaround times for prior authorizations - 72 hours for urgent and 7 days for standard requests - via standardized APIs. The [CMS Interoperability and Prior Authorization Final Rule](https://www.cms.gov/newsroom/fact-sheets/cms-interoperability-prior-authorization-final-rule-cms-0057-f) fact sheet documents how these legislative changes impact cardiovascular reimbursement rates. ### Tips for Reducing Claim Denials Denial management is where most cardiology practices lose significant revenue. To combat this, practices should implement a "Zero-Denial" strategy that focuses on the root cause of rejections. - Automate Eligibility Checks: Use RCM software that verifies insurance 48 hours before the procedure to catch expired policies and utilize the new 2026 API requirements for real-time transparency. - Standardize Appeal Templates: Create specific clinical templates for common denials, such as medical necessity for echocardiograms, to speed up the recovery of funds and meet the stricter documentation standards set in late 2025. ## Performance Monitoring in Cardiology RCM ### Key Performance Indicators to Track You cannot manage what you do not measure. In cardiology, two metrics stand above the rest: Days in Accounts Receivable (AR) and the Net Collection Ratio. A high-performing cardiology practice should aim for a Net Collection Ratio of 95% or higher. Tracking these KPIs allows administrators to see if bottlenecks are occurring in the coding department or if a specific payer is intentionally slowing down payments. ### Tools for Enhancing RCM Efficiency Modern cardiology practices are moving away from manual entry toward AI-driven RCM platforms. For 2026, top-tier software now features "predictive scrubbing," which uses machine learning to score a claim's denial risk before it is even submitted. Leveraging [HealthIT.gov](https://www.healthit.gov/) resources can help practices choose certified EHR and RCM technology that integrates with cardiac imaging systems. Software Solution | Key Cardiology Strength | Best For | Rhythm360 | Automated CPT capture for remote monitoring | Device-heavy practices (RPM/CCM) | NextGen Healthcare | Advanced modifier & unbundling logic | Mid-to-large cardiology groups | Athenahealth | Real-time eligibility & predictive analytics | High-volume practices seeking automation | Epic EMR | Seamless interoperability with hospital systems | Enterprise-level health systems | ### Lessons Learned from High-Performing Practices The most successful practices share a common trait: integration. Instead of treating the clinical and billing departments as separate silos, they foster a culture of communication. When a coder understands the clinical nuances of a Transcatheter Aortic Valve Replacement (TAVR), and a physician understands the documentation required for that code, the entire revenue cycle accelerates. ### Summary ‍ At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RCMAIHealthcare ### Top RCM Trends | 2026 Top RCM trends for 2026: what healthcare finance leaders at Deloitte, HFMA, and beyond are prioritizing to strengthen revenue cycles. Karl MielnickiNovember 24, 2025 ](https://www.flobotics.io/blog/top-rcm-trends-healthcare)[ RCMAIHealthcare ### RCM Statistics | 2026 Overview RCM statistics for 2026: denial rates hover near 5% and cost-to-collect keeps rising as manual processes lose ground. See the data. Jędrzej SzymulaJanuary 07, 2026 ](https://www.flobotics.io/blog/rcm-statistics-overview)[ RCMHealthcare ### RCM Automation in Healthcare | 2026 RCM automation in healthcare: how RPA, AI, and OCR cut billing errors, speed up claims, and reduce manual work in 2026 revenue cycle management. Bart TeodorczukFebruary 25, 2026 ](https://www.flobotics.io/blog/rcm-automation-healthcare) [All articles →](https://www.flobotics.io/blog) --- # No Surprises Act from an RCM Perspective | 2026 Canonical: https://www.flobotics.io/blog/no-suprises-act-rcm Author: Jędrzej Szymula Published: 2026-03-09 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/No Surprises Act from an RCM Perspective | 2026 [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # No Surprises Act from an RCM Perspective | 2026 [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published March 09, 2026Updated September 1, 2026 On this page - [Understanding the No Surprises Act](#understanding-the-no-surprises-act) - [Before You Read:](#before-you-read) - [Overview of the No Surprises Act](#overview-of-the-no-surprises-act) - [Key Provisions and Patient Protections](#key-provisions-and-patient-protections) - [The No Surprises Act and Its Impact on Revenue Cycle Management (RCM)](#the-no-surprises-act-and-its-impact-on-revenue-cycle-management-rcm) - [How the No Surprises Act Changes the Revenue Cycle](#how-the-no-surprises-act-changes-the-revenue-cycle) - [Compliance Challenges for RCM Teams](#compliance-challenges-for-rcm-teams) - [Operational Opportunities for Automation in RCM](#operational-opportunities-for-automation-in-rcm) - [Compliance Strategies for Healthcare Providers](#compliance-strategies-for-healthcare-providers) - [Steps to Ensure Compliance](#steps-to-ensure-compliance) - [Resources and Tools for Practices](#resources-and-tools-for-practices) - [Impact on Patients and Providers](#impact-on-patients-and-providers) - [Case Studies of Implementation](#case-studies-of-implementation) - [Financial Implications for Providers](#financial-implications-for-providers) - [Enforcement and Compliance Challenges](#enforcement-and-compliance-challenges) - [State Variations and Legal Considerations](#state-variations-and-legal-considerations) - [Reporting and Resolution Process](#reporting-and-resolution-process) - [Frequently Asked Questions](#frequently-asked-questions) - [Common Misconceptions](#common-misconceptions) - [Patient Guidance on Expected Costs](#patient-guidance-on-expected-costs) - [Final Thoughts](#final-thoughts) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Understanding the No Surprises Act Unexpected medical bills have long been a source of frustration and financial stress for patients in the United States. In response to widespread concerns about surprise billing practices, the federal government enacted the No Surprises Act, a major piece of healthcare legislation designed to limit unexpected charges and improve transparency in medical billing. The law fundamentally changes how healthcare providers, insurers, and patients interact when care is delivered outside a patient’s insurance network or during emergencies. For healthcare organizations, it also introduces a new layer of compliance responsibilities and operational adjustments. This article explains what the No Surprises Act does, how it affects patients and providers, and what healthcare organizations should do to remain compliant. ### Before You Read: To understand how the No Surprises Act affects healthcare billing and revenue cycle operations, it is important to know three core concepts: - Balance Billing – A practice where a provider bills a patient for the difference between the provider’s charge and what the insurance company pays. The No Surprises Act prohibits this practice in many emergency and in-network facility scenarios, limiting patients to standard in-network cost-sharing amounts. - Independent Dispute Resolution (IDR) – A formal arbitration process used when healthcare providers and insurers cannot agree on reimbursement for certain out-of-network services. An independent arbitrator reviews both payment offers and determines the final reimbursement amount. - Good Faith Estimate (GFE) – A required cost estimate that providers must give uninsured or self-pay patients before scheduled services. It outlines the expected total cost of care so patients can better understand potential financial obligations in advance. ## Overview of the No Surprises Act The No Surprises Act is a federal law that took effect on January 1, 2022. Its main purpose is to protect patients from unexpected medical bills that occur when they receive care from providers who are outside their insurance network without their knowledge or choice. Historically, patients often encountered these situations when visiting emergency departments, undergoing procedures at in-network hospitals that used out-of-network specialists, or being transported by air ambulance services. In such cases, providers could bill patients for the difference between their charge and what the insurance plan paid - a practice known as balance billing. The law addresses these issues by prohibiting certain billing practices and establishing clear rules governing how insurers and providers resolve payment disputes. In practical terms, the No Surprises Act shifts the burden of resolving billing disagreements away from patients and onto insurers and healthcare providers, creating a structured process for determining fair payment. ### Key Provisions and Patient Protections The legislation introduces several protections designed to prevent patients from receiving unexpected out-of-network bills and to ensure greater transparency about healthcare costs. #### Balance Billing Prohibitions One of the core components of the No Surprises Act is the prohibition of balance billing in specific situations. When a patient receives emergency care or certain services at an in-network facility, providers can no longer charge the patient for the difference between the provider’s billed charge and the amount the insurance company reimburses. Instead, patients are only responsible for their in-network cost-sharing amounts, such as copayments, coinsurance, or deductibles. This rule applies even if the treating provider or facility is technically outside the patient’s insurance network. The law specifically applies to several categories of care where patients have limited ability to choose providers. These protections cover emergency services, many non-emergency services delivered at in-network facilities, and air ambulance transportation. ‍ • Emergency medical services must be billed at in-network cost-sharing levels regardless of the provider’s network status. • Patients cannot be balance billed for services provided by out-of-network clinicians at in-network hospitals or surgical centers in most cases. • Cost-sharing amounts must count toward the patient’s in-network deductible and out-of-pocket maximum. ‍ These provisions aim to ensure that patients do not face large financial liabilities simply because they received care from a provider outside their insurance network without realizing it. #### Emergency Services Requirements The law also clarifies how emergency medical services must be handled under health insurance plans. Emergency care must be covered without requiring prior authorization, and insurance plans cannot impose different cost-sharing requirements based on whether the provider is in-network. This ensures that patients can seek urgent care without worrying about whether the hospital or physician treating them participates in their insurance plan. The legislation recognizes that during emergencies, patients rarely have the ability to verify provider networks or negotiate billing terms. ## The No Surprises Act and Its Impact on Revenue Cycle Management (RCM) For healthcare organizations, the No Surprises Act is not just a regulatory requirement—it fundamentally changes how the revenue cycle is managed. Many of the law’s provisions directly affect billing workflows, eligibility verification, patient communication, and dispute management. As a result, revenue cycle management (RCM) teams must adjust both operational processes and technology systems to remain compliant while maintaining financial performance. ### How the No Surprises Act Changes the Revenue Cycle Before the law was introduced, healthcare providers often relied on balance billing to recover payment differences when services were delivered by out-of-network clinicians. With these practices now restricted in many situations, revenue cycle teams must ensure that billing processes correctly identify protected scenarios and apply appropriate cost-sharing rules. This means that RCM departments must now integrate compliance checks into multiple stages of the revenue cycle—from patient intake to final claim resolution. Even small errors in classification or billing logic can trigger disputes, payment delays, or regulatory scrutiny. Several operational areas are especially affected: ‍ • Eligibility and network verification: RCM teams must confirm insurance coverage and network status earlier in the patient journey to avoid prohibited billing scenarios. • Patient financial communication: Providers must issue Good Faith Estimates for uninsured or self-pay patients and provide clear billing disclosures when required. • Claim processing and coding: Billing systems must correctly apply in-network cost-sharing rules when services fall under No Surprises Act protections. • Payment dispute handling: Providers may need to initiate or respond to the Independent Dispute Resolution (IDR) process when insurers and providers disagree on reimbursement. ‍ Because these requirements span multiple operational steps, many healthcare organizations are redesigning their revenue cycle workflows to incorporate automated compliance checks. ### Compliance Challenges for RCM Teams The No Surprises Act introduces complexity into an already intricate billing ecosystem. Revenue cycle teams must navigate changing regulations, insurer negotiation processes, and evolving guidance from federal regulators. In particular, organizations must ensure that their billing systems can detect situations where balance billing is prohibited and automatically adjust claims accordingly. Smaller healthcare providers and rural practices often face additional challenges. Limited administrative resources may make it difficult to track regulatory updates, train staff, or implement new billing safeguards. Without proper systems in place, these organizations risk compliance violations or delayed reimbursements. Another major challenge involves the dispute resolution process between providers and insurers. When reimbursement disagreements occur, RCM teams must gather documentation, submit arbitration requests, and manage communication with payers—all while maintaining normal billing operations. ### Operational Opportunities for Automation in RCM Although the law introduces new compliance requirements, it also creates opportunities for automation within revenue cycle operations. Many of the tasks required for compliance—such as verifying coverage, identifying protected services, and generating required disclosures—can be automated using modern RCM technologies. Automation can help providers reduce manual errors and ensure consistent application of regulatory rules. For example, automated systems can flag claims that may fall under the No Surprises Act, generate required documentation, and guide staff through compliant billing procedures. Healthcare organizations that integrate automation into their revenue cycle workflows can therefore achieve two important goals simultaneously: maintaining compliance with the No Surprises Act while improving operational efficiency. As the healthcare regulatory environment continues to evolve, revenue cycle teams that combine strong compliance practices with automated processes will be best positioned to manage financial risk and maintain stable revenue performance. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Compliance Strategies for Healthcare Providers For healthcare organizations, complying with the No Surprises Act involves both administrative adjustments and operational changes. Many facilities have had to update billing workflows, patient communication processes, and internal compliance policies. ### Steps to Ensure Compliance Healthcare providers must take several practical steps to meet the law’s requirements. These actions typically involve revising billing practices, updating documentation processes, and ensuring staff are trained on the new rules. Key compliance steps include: • Updating billing systems to prevent prohibited balance billing. • Providing patients with required disclosures about their rights under the No Surprises Act. • Issuing Good Faith Estimates for self-pay or uninsured patients before scheduled services. • Establishing procedures for handling payment disputes with insurers. • Training administrative and clinical staff on billing transparency requirements. These measures help ensure that organizations meet regulatory expectations while minimizing the risk of disputes or enforcement actions. ### Resources and Tools for Practices Healthcare practices can leverage several resources to streamline compliance. Industry associations, government agencies, and healthcare consulting firms provide guidance documents, templates, and compliance checklists designed specifically for the No Surprises Act. Small practices and rural providers often face unique challenges in implementing these requirements. Limited administrative resources and fewer compliance specialists can make it harder to adapt billing systems or interpret evolving regulations. For these organizations, standardized documentation templates and automated billing safeguards can significantly reduce compliance risk. ‍ ## Impact on Patients and Providers The No Surprises Act has implications across the healthcare system. While the law was designed primarily to protect patients, it also changes financial dynamics between insurers and providers. Patients benefit from greater billing predictability and reduced risk of catastrophic medical bills. Providers, however, may face administrative complexity and new negotiation frameworks with insurance companies. ### Case Studies of Implementation In practice, healthcare organizations have implemented a variety of strategies to adapt to the new requirements. Some hospitals have created dedicated compliance teams responsible for reviewing billing processes and identifying potential violations before claims are submitted. Others have integrated automated safeguards into revenue cycle management systems to flag potential balance billing scenarios. Small practices often rely on third-party billing vendors or healthcare automation tools to ensure that claims meet regulatory standards. These solutions can automatically detect billing situations that may violate the law and alert staff before invoices are issued. ### Financial Implications for Providers Financially, the law alters the balance of negotiation power between providers and insurers. Because patients can no longer be billed for certain out-of-network charges, insurers and providers must resolve payment disagreements directly. This often occurs through the Independent Dispute Resolution (IDR) process established by the legislation. In this system, an arbitrator reviews competing payment offers from insurers and providers and selects the most appropriate amount. While the process aims to ensure fairness, it can also introduce administrative overhead and legal complexity for healthcare organizations. ‍ ## Enforcement and Compliance Challenges Although the No Surprises Act establishes clear patient protections, enforcing the law and ensuring consistent compliance across the healthcare system remains a challenge. ### State Variations and Legal Considerations One complexity arises from the interaction between federal law and existing state regulations. Some states already had their own surprise billing protections before the federal legislation was enacted. In situations where state laws provide stronger patient protections, those rules generally continue to apply. However, in states without comprehensive protections, the federal law serves as the primary regulatory framework. This overlapping legal landscape can create confusion for providers operating across multiple states, particularly those managing multi-location healthcare networks. ### Reporting and Resolution Process Patients who believe they have received an improper bill under the No Surprises Act can file a complaint through federal or state regulatory agencies. Healthcare providers must therefore maintain clear documentation demonstrating that billing practices comply with the law. The Independent Dispute Resolution process is also a key enforcement mechanism. Insurers and providers use this system to resolve payment disputes without involving patients directly. Proper documentation, transparent billing policies, and consistent staff training are critical for avoiding regulatory penalties and maintaining compliance. ## Frequently Asked Questions ### Common Misconceptions Many patients and providers misunderstand the scope of the No Surprises Act. The law does not eliminate all out-of-network charges. Instead, it focuses on situations where patients lack meaningful choice about their provider. For example, if a patient knowingly chooses an out-of-network provider for elective care, the balance billing protections may not apply. Similarly, the law does not regulate the price of medical services themselves — it governs how disputes over those prices are handled Understanding these nuances helps healthcare organizations avoid incorrect assumptions that could lead to compliance risks. ### Patient Guidance on Expected Costs Patients can protect themselves by asking healthcare providers for cost estimates before scheduled services and reviewing insurance network information when possible. The law’s requirement for Good Faith Estimates gives patients greater transparency about expected charges. However, healthcare billing remains complex, and patients should remain proactive in reviewing medical bills and insurance explanations of benefits. ‍ ## Final Thoughts The No Surprises Act represents one of the most significant federal efforts to address unexpected medical billing in the United States. By shifting financial disputes away from patients and toward insurers and providers, the law aims to create a more transparent and predictable healthcare payment system. For healthcare organizations, compliance requires careful attention to billing practices, patient disclosures, and dispute resolution procedures. While implementation challenges remain particularly for smaller practices - the legislation ultimately seeks to build greater trust between patients and the healthcare system. Understanding the law’s requirements and integrating compliance safeguards into operational workflows will remain essential as healthcare providers continue to adapt to the evolving regulatory environment. At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let’s talk! [👉 Book a 30-minute call](https://www.flobotics.io/book) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ AIHealthcareRPA ### Compliance Automation in Healthcare Healthcare compliance automation: how Continuous Control Monitoring and Agentic AI cut administrative drag by 20-30% in 2026. February 04, 2026 ](https://www.flobotics.io/blog/compliance-automation-healthcare)[ RPAHealthcare ### 10 Benefits of Artificial Intelligence in Healthcare Benefits of artificial intelligence in healthcare: 10 ways AI cuts administrative costs, speeds prior authorizations, and improves data accuracy. Bart TeodorczukJuly 22, 2025 ](https://www.flobotics.io/blog/benefits-artificial-intelligence-healthcare)[ RCMHealthcare ### RCM Automation in Healthcare | 2026 RCM automation in healthcare: how RPA, AI, and OCR cut billing errors, speed up claims, and reduce manual work in 2026 revenue cycle management. Bart TeodorczukFebruary 25, 2026 ](https://www.flobotics.io/blog/rcm-automation-healthcare) [All articles →](https://www.flobotics.io/blog) --- # Clinical Documentation Integrity (CDI): Why It Matters Canonical: https://www.flobotics.io/blog/clinical-documentation-integrity-cdi-explanation Author: Karl Mielnicki Published: 2026-03-03 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Clinical Documentation Integrity (CDI): Why It Matters CTO Notes [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Clinical Documentation Integrity (CDI): Why It Matters [Karl MielnickiCTO & Co-Founder of Flobotics](https://www.flobotics.io/our-editorial-team#mielnicki) Published March 03, 2026Updated September 1, 2026 On this page - [What Is Clinical Documentation Integrity (CDI)?](#what-is-clinical-documentation-integrity-cdi) - [Why CDI Is a Revenue-Critical Function](#why-cdi-is-a-revenue-critical-function) - [Key CDI Focus Areas](#key-cdi-focus-areas) - [CDI and Compliance Risk](#cdi-and-compliance-risk) - [How Technology Supports CDI](#how-technology-supports-cdi) - [Related Concepts](#related-concepts) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Is Clinical Documentation Integrity (CDI)? Clinical Documentation Integrity (CDI) is the systematic process of ensuring that a patient's medical chart accurately, completely, and specifically reflects the full scope of services delivered, the severity of illness present, and every diagnosis that affected clinical decision-making during an encounter. The goal is to close the gap between what clinicians do and what gets documented, coded, billed, and reimbursed. CDI programs typically involve clinical documentation improvement specialists — nurses or coding professionals with clinical backgrounds — who review records concurrently (during the encounter) or retrospectively (after discharge) and query physicians to clarify, add, or correct documentation that is vague, conflicting, or incomplete. ## Why CDI Is a Revenue-Critical Function In healthcare reimbursement, you are only paid for what is documented. A physician who manages complex comorbidities but documents only the primary presenting complaint leaves significant legitimate revenue uncaptured. Undercoding due to documentation gaps is not a minor administrative issue — it is systematic revenue leakage on every underdocumented encounter. Poor documentation leads to coding inaccuracies generating claim rejections, [denials](https://www.flobotics.io/blog/denials-management-explanation) based on medical necessity, DRG downgrades in inpatient settings, and [underpayments](https://www.flobotics.io/blog/underpayment-recovery-explanation) that are difficult to identify and recover after the fact. In [Value-Based Care (VBC)](https://www.flobotics.io/blog/value-based-care-vbc-explanation) models, accurate documentation becomes even more critical: risk adjustment calculations, quality measure performance, and shared savings distributions all depend on diagnosis specificity that only robust CDI programs can consistently produce. ## Key CDI Focus Areas - Diagnosis specificity: "Respiratory failure" vs. "acute hypoxic respiratory failure with hypercapnia" — the latter captures higher DRG weight and legitimate acuity - Comorbidity capture: Conditions affecting clinical management (diabetes, CKD, malnutrition) must be explicitly documented and coded - Procedure documentation: Operative notes must support the CPT codes billed — vague documentation is a primary audit target - Medical necessity support: Every ordered test, procedure, and admission needs documented clinical rationale Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## CDI and Compliance Risk CDI is not only a revenue function — it is a compliance and legal protection function. Unsupported claims are the primary target of OIG audits, RAC reviews, and commercial payer post-payment audits. Organizations without structured CDI face disproportionate audit exposure and higher recoupment rates. ## How Technology Supports CDI Modern CDI programs increasingly rely on AI tools that scan clinical notes in real time, flagging documentation gaps and suggesting physician queries. [Intelligent Document Processing (IDP)](https://www.flobotics.io/blog/intelligent-document-processing-idp-explanation) enables automated extraction of clinical data from unstructured notes, making CDI review faster and more comprehensive than manual chart audits. This is a core component of a mature [RCM automation strategy](https://www.flobotics.io/rcm-automation). ## Related Concepts CDI sits at the intersection of clinical operations and [medical coding](https://www.flobotics.io/blog/medical-coding-explanation). Its outputs feed directly into [charge capture](https://www.flobotics.io/blog/charge-capture-explanation) accuracy, denial rates, and [reimbursement](https://www.flobotics.io/blog/reimbursements-explanation) optimization. Written byKarl Mielnicki CTO & Co-Founder of Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCM ### What Is Medical Coding? ICD-10 vs. CPT/HCPCS Medical coding, explained: how ICD-10 diagnoses and CPT/HCPCS procedures become the codes that drive clean claims and reimbursement. Jędrzej SzymulaApril 07, 2026 ](https://www.flobotics.io/blog/medical-coding-explanation)[ HealthcareRCM ### Charge Capture: What It Is and How It Works in RCM What is charge capture? How converting clinical services into billable charges kicks off the revenue cycle, and why missed charges are lost revenue. Karl MielnickiJune 03, 2026 ](https://www.flobotics.io/blog/charge-capture-explanation)[ HealthcareRCM ### What Is Claim Scrubbing? What Gets Checked Before Submission Claim scrubbing, explained: how automated pre-submission checks catch errors that cost $25-$44 per claim to fix after denial. Krzysztof SzwedMarch 24, 2026 ](https://www.flobotics.io/blog/claim-scrubbing-explanation) [All articles →](https://www.flobotics.io/blog) --- # Dental Revenue Cycle Management | 2026 Canonical: https://www.flobotics.io/blog/dental-revenue-cycle-management Author: Jędrzej Szymula Published: 2026-03-02 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Dental Revenue Cycle Management | 2026 [RCM](https://www.flobotics.io/blog?category=rcm) # Dental Revenue Cycle Management | 2026 [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published March 02, 2026Updated September 1, 2026 On this page - [What is Dental RCM?](#what-is-dental-rcm) - [Dental RCM vs. Medical RCM](#dental-rcm-vs-medical-rcm) - [Dental RCM | AI Automation](#dental-rcm-ai-automation) - [Key Dental RCM Metrics to Monitor in 2026](#key-dental-rcm-metrics-to-monitor-in-2026) - [Common Challenges in Dental RCM](#common-challenges-in-dental-rcm) - [The Payer AI War: Survival Against NLP Audits](#the-payer-ai-war-survival-against-nlp-audits) - [Claim Denials and Rejections](#claim-denials-and-rejections) - [Compliance Issues in Dental Billing](#compliance-issues-in-dental-billing) - [Staff Training and Development](#staff-training-and-development) - [Summary](#summary) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What is Dental RCM? Dental Revenue Cycle Management (Dental RCM) is the set of financial and operational processes dental practices use to accurately capture, bill, and collect revenue from both insurers and patients, covering the entire lifecycle of a patient account from the moment an appointment is scheduled to the point the balance is fully resolved. It includes front-end activities such as scheduling, real-time eligibility verification, accurate cost estimates, point-of-care workflows like clinical documentation, and back-end functions including CDT coding, claim creation, attachment management (such as X-rays and narratives), or claim submission, etc. Unlike medical RCM, dental RCM operates with greater coverage volatility, higher patient responsibility, and heavier reliance on documentation nuance, making precision and speed critical. When executed effectively, dental revenue cycle management reduces denials, shortens days in A/R, lowers Cost-to-Collect, improves cash flow predictability, and enhances the patient financial experience by turning billing from an administrative burden into a controlled, scalable revenue engine. ### Dental RCM vs. Medical RCM Dental revenue cycle management operates under fundamentally different constraints than medical RCM - and applying the same playbooks is a common driver of higher denials and Cost-to-Collect. - Code sets: CDT codes place heavier weight on narratives and attachments (X-rays, perio charts), not just procedural logic. - Coverage volatility: Annual maximums, frequency limits, and waiting periods make real-time eligibility at scheduling and point of service non-negotiable. - Patient responsibility: A larger share of revenue depends on upfront patient collections, making estimates and treatment presentation core financial controls. - Payer behavior: Dental payers increasingly use NLP-based reviews, denying claims on documentation nuance rather than diagnosis mismatch. - Cash expectations: Leading dental groups target DSO under 25–30 days, leaving little tolerance for manual rework. Dental RCM succeeds or fails at the front end. Automation must prevent errors before submission - not recover them after the fact. ### Dental RCM | AI Automation Revenue Cycle Management (RCM) refers to the entire lifecycle of a patient account - from the initial appointment request to the final payment of a zero balance. According to Experian Health (2025), denial volumes have surged 22% over the last year. If your group bills $10M annually, a 1% improvement in your Clean Claim Rate recaptures $100,000 in cash that would otherwise require manual intervention. Automating front-end eligibility typically saves 70 minutes per patient visit in administrative friction. That is 1.5–2.0 FTEs reclaimed for every $10M in production. You can read more about it in our article [XYZ](http://xyz) Ultimately, this is about AR Velocity. With dental wages outpacing the national average by nearly 4% in 2025, you cannot afford to have cash sitting in 'Pending' for 45+ days. Best-in-class dental groups are now using predictive claim scrubbing to push DSO under 25 days, effectively turning their RCM from a cost center into a cash-flow engine. That’s why investments in RCM automation in dental practices are semi-necessity Stages of Revenue Cycle Management in Dental Practices The cycle begins before the patient even sits in the chair. - Pre-Arrival: Patient scheduling and Real-Time Eligibility (RTE) Verification. - Point of Care: Accurate clinical documentation and treatment plan presentation. - Claim Creation: Translating clinical notes into CDT (Current Dental Terminology) codes. - Claim Scrubbing & Submission: Reviewing claims for errors before they reach the payer. - Reimbursement Management: Payment posting, managing EOBs (Explanation of Benefits), and reconciling accounts. - Patient Collections: Managing out-of-pocket balances and patient financing. ### Key Dental RCM Metrics to Monitor in 2026 To lead a practice effectively, you must quantify performance. In 2026, the "Gold Standard" metrics are: Metric | Definition | Target / Benchmark | Clean Claim Rate (CCR) | The percentage of claims accepted on the first submission. | 98%+ | Days in A/R | The average time it takes to get paid. | ~30 days | Net Collection Rate | What you actually collect vs. what you are legally owed. | 97% or higher | Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Common Challenges in Dental RCM Even high-performing practices face hurdles that can disrupt cash flow and increase administrative "drag." ### The Payer AI War: Survival Against NLP Audits Payers have weaponized AI. According to MBW RCM (2026), insurers are now using NLP to scan clinical notes for "vague necessity statements." Even technically "clean" claims face 18–20% higher denial rates on high-cost procedures (like D6010 implants or D6063 crowns) because the narrative doesn't trigger the payer's specific AI keywords. Implement Clinical Documentation Improvement (CDI) programs that "pre-audit" narratives against payer-specific NLP logic before submission. ### Claim Denials and Rejections Industry data shows that 1 in 5 dental claims are either delayed or denied. Most denials stem from preventable front-end errors: eligibility issues (expired coverage), missing attachments (X-rays/narratives), or "stale" coding. Manually reworking a single denied claim costs approximately $25 to $30 in labor, effectively erasing the profit margin of many preventive procedures. Governance means the humans manage the complex 2% of exceptions, while the bots handle the 98% clear-path claims. ### Compliance Issues in Dental Billing The regulatory environment in 2026 is stricter than ever. Dental offices are now primary targets for cyberattacks. HIPAA violations can lead to fines of up to $50,000 per violation. The Office for Civil Rights (OCR) has restarted aggressive audit programs. Practices must maintain role-based access logs and encrypted databases to remain "audit-ready." Evolution of Dental RCM Automation In 2026 modern practices are migrating to Cloud-Based Practice Management Systems (PMS) like Carestack or Dentrix Ascend. Your PMS must "talk" to your billing and imaging software. Look for tools that offer "Predictive Claim Scoring," which flags a claim for likely denial before you hit submit. Automation 2.0: - Automated Eligibility: Running checks 24-48 hours before an appointment and flagging "coverage exceptions." - AI Coding Assistance: Software that cross-references clinical notes with CDT codes to prevent "undercoding" (losing money) or "upcoding" (inviting audits). Automation 3.0 Stop buying "task managers" that just give your staff a prettier to-do list. The 2026 gold standard is Agentic Automation - AI that actually logs into payer portals, uploads attachments, and posts payments without human clicks (Ventus AI 2026). In short: Success is no longer "How many claims did we submit?" but "How many claims were Touchless?" Best Practices for Dental RCM Execs ### Staff Training and Development Technology only works if the team understands the "Why." Ensure staff are trained annually on CDT changes (e.g., new codes like D0356 for diagnostic digital scans). Train the front desk to discuss costs upfront. High-performing offices use "Treatment Acceptance Models" to secure patient payment commitments before the procedure begins. The Shared Services Model Individual practices focus on "billing," but most executive boards focus on repeatability. 58% of top-performing groups now centralize RCM to manage labor shortages (Kaufman Hall 2025). Centralization reduces administrative overhead by 35% compared to site-level billing. In 2025, the OCR reactivated aggressive HIPAA audits. Automated systems create Immutable Audit Logs, removing human subjectivity and ensuring you are always "audit-ready." Waiting for an EOB to find out a patient's coverage has expired is a "critical failure point." Implement RTE tools that provide instant data on deductibles, remaining annual maximums, and frequency limitations (e.g., "Is this the patient's second cleaning of the year?"). Static eligibility (checking once at the start of the month) is a critical failure point in 2026. With the expiration of temporary ACA credits and Medicaid shifts, thousands of patients are losing coverage mid-month (Ameritas 2026). RTE tools must run at scheduling, 24 hours prior, and at the point of service to capture "Eligibility Volatility." Future Trends in Dental Revenue Cycle Management Voice-to-Text Charting: AI scribes are reducing "claim lag time" by ensuring notes are finished immediately after the appointment. #### DLR and VCC Laws At least 18 states passed laws in late 2025 targeting insurer "stealth" tactics. Dental Loss Ratio (DLR) States like Washington and Montana now mandate that insurers spend a minimum percentage of premiums on care. Directors must leverage this to renegotiate stagnant fee schedules. Virtual Credit Cards (VCC) New laws in Illinois and Kentucky now restrict insurers from forcing VCC payments with high merchant fees. Governance Check: Ensure your RCM team has opted out of VCCs to reclaim the 2-3% "hidden tax" on reimbursements. Patient Self-Serve Portals Allowing patients to update insurance and pay balances via mobile reduces the "Cost to Collect" by up to 40%.Final Verdict for the Board In 2026, you either own an Autonomous Revenue Engine or you own a growing debt to your staff's manual labor. Read our article on [top trends in RCM](https://www.flobotics.io/blog/top-rcm-trends-healthcare). ### Summary Dental revenue cycle management in 2026 is about getting paid faster and with fewer mistakes. Denials are rising and manual work costs a lot. Practices that fix errors before claims go out are doing much better than those that fix problems later. Tools that check eligibility early, catch coding and documentation errors, and automate routine tasks are reducing days in accounts receivable and lowering cost to collect. Teams that still rely on manual work are falling behind. In 2026, success in dental RCM means using the right systems to prevent problems, speed up payments, and reduce work for staff. At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let’s talk! [👉 Book a 30-minute call](https://www.flobotics.io/book) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ HealthcareRCMAI ### RCM Outsourcing in Healthcare | 2026 RCM outsourcing in 2026: why offshore labor arbitrage is failing, and how Agentic AI outsourcing is replacing it. Bart TeodorczukFebruary 02, 2026 ](https://www.flobotics.io/blog/rcm-outsourcing-healthcare)[ RCMAIHealthcare ### RCM Statistics | 2026 Overview RCM statistics for 2026: denial rates hover near 5% and cost-to-collect keeps rising as manual processes lose ground. See the data. Jędrzej SzymulaJanuary 07, 2026 ](https://www.flobotics.io/blog/rcm-statistics-overview)[ RCMAIHealthcare ### Top RCM Trends | 2026 Top RCM trends for 2026: what healthcare finance leaders at Deloitte, HFMA, and beyond are prioritizing to strengthen revenue cycles. Karl MielnickiNovember 24, 2025 ](https://www.flobotics.io/blog/top-rcm-trends-healthcare) [All articles →](https://www.flobotics.io/blog) --- # RCM Automation in Healthcare | 2026 Canonical: https://www.flobotics.io/blog/rcm-automation-healthcare Author: Bart Teodorczuk Published: 2026-02-25 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/RCM Automation in Healthcare | 2026 [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # RCM Automation in Healthcare | 2026 [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published February 25, 2026Updated September 1, 2026 On this page - [Revenue Cycle Management in healthcare & medical billing](#revenue-cycle-management-in-healthcare-medical-billing) - [Revenue Cycle Management systems — what they are and how they help](#revenue-cycle-management-systems-what-they-are-and-how-they-help) - [Choosing the right RCM automation tool](#choosing-the-right-rcm-automation-tool) - [The benefits of RPA in Revenue Cycle Management](#the-benefits-of-rpa-in-revenue-cycle-management) - [How to use RPA in Revenue Cycle Management](#how-to-use-rpa-in-revenue-cycle-management) - [Conclusion](#conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Healthcare is, and should always be, primarily about health. But the inescapable truth is that all medical services cost money. This obvious fact has led to the development of a robust IT infrastructure that manages the healthcare revenue cycle — from handling insurance claims to collecting payments. The whole process is a sequence of numerous tightly interdependent steps. Its complexity leaves room for optimization and very little room for error. Smooth Revenue Cycle Management (RCM) is critical for effective healthcare and reducing revenue leakage, but surprisingly few industry leaders perceive its importance. For example, a 2020 report showed that 87% of providers still used manual and paper-based processes for collections. The consequences? 78% claimed they failed to collect payments over $1,000 within 30 days. Add fluctuations in healthcare spending, and you have a recipe for an unstable and inefficient system from the perspective of patients and providers alike. Even though the pandemic has undoubtedly increased the level of digitization in healthcare organizations, many still rely on manual revenue management operations. Luckily, solutions exist that can be easily adopted and don’t require a massive investment in complex IT infrastructure setup or maintenance. This article explores some of them, discussing RCM systems for medical services and suggesting how your medical organization can benefit from Revenue Cycle Management automation. Learn more about [how RPA and machine learning work together](https://www.flobotics.io/blog/robotic-process-automation-vs-machine-learning) in other industries, like insurance, logistics, or consultancy. ### Revenue Cycle Management in healthcare & medical billing Revenue cycle management refers to all the administrative tasks devoted to financial transactions between patients and their providers and how they are handled. The key processes in RCM are: [Pre-authorization automation solutions](https://www.flobotics.io/agents/prior-authorization-automation) — the process starts when a patient makes an appointment. To set up a patient account, the provider must gather and register all the necessary data, such as personal information and medical records, and assess the patient’s insurance eligibility. [Medical coding automation workflow](https://www.flobotics.io/blog/medical-coding) — next, medical data like test results, diagnoses, or procedures are translated into a unified code. This standardized system facilitates communication between physicians, office staff, insurance companies, and other healthcare providers involved in treatment. [Claims submission and management](https://www.flobotics.io/agents/claims-management-automation) — a coded record of the patient’s treatment is submitted to the insurer, who then reviews and approves or denies the claim. [Payment collection and invoicing](https://www.flobotics.io/blog/invoice-automation) — if the insurer approves the claim, the provider receives reimbursement. The amount depends on the patient’s eligibility, as insurance doesn’t always cover the full cost. If not, the provider must follow up with the patient and collect the remaining balance. [Service review and RPA reporting ](https://www.flobotics.io/blog/rpa-in-insurance-use-cases)— once the payment is complete, the data used in the revenue cycle and clinical treatment is analyzed. This ensures insight into potential issues and ways to improve the entire process. At this stage, it’s important to note that although the term revenue cycle management is often used interchangeably with medical billing, the two are not the same. RCM encompasses all the processes mentioned above, while medical billing refers only to those directly related to claims — coding, submission, and payment collection. In that sense, RCM is a broader, end-to-end workflow that includes billing as one of its components. The revenue cycle is affected by many unpredictable, shifting factors — both internal and external. These moving parts often complicate revenue cycle management, making many cases unique. ### Revenue Cycle Management systems — what they are and how they help Revenue Cycle Management software aims to digitize and replace paper-based procedures and documentation within revenue cycle workflows. Think of it as the EHR of medical billing and claim management. According to a 2026 forecast, the RCM software market is expected to grow by 10% annually between 2023 and 2030. This and other research confirm that demand for RCM solutions is rising — and for good reason. RCM systems support back-office staff in essential tasks such as: - checking eligibility - claim correction and tracking - KPI reporting - data entry - medical coding - denial management and alerts - contacting patients and insurers - cost estimation …and more. They achieve this by leveraging modern technologies, including RCM automation. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ### Choosing the right RCM automation tool Many RCM processes — especially medical billing — can be optimized using intelligent software. In some cases, algorithms can fully take over simpler tasks. Here are the most common technologies used in RCM automation: Intelligent Automation (IA) IA combines multiple technologies — such as AI, OCR, NLP, and RPA — into a unified system. It enables end-to-end automation, where systems not only execute tasks but also learn and optimize processes over time. Robotic Process Automation (RPA) RPA uses pre-programmed scripts to handle repetitive, rule-based, high-volume tasks. Many stages in the healthcare revenue cycle are ideal for RPA, including scheduling, claims tracking, invoice processing, and billing operations.‍ Machine Learning (ML) ML algorithms analyze large datasets to improve decision-making. In RCM, they can identify claims likely to be denied before submission and recommend corrections. They can also help predict patient outcomes and financial risk. Optical Character Recognition (OCR) OCR scans documents and images to extract text and convert it into a digital format. In healthcare, it accelerates data entry across prescriptions, medical records, and billing workflows. Natural Language Processing (NLP) NLP extracts key information from unstructured data, such as physician notes. It allows staff to work with complex data more efficiently without sacrificing billing accuracy. ### The benefits of RPA in Revenue Cycle Management While different automation technologies vary in complexity, RPA typically requires the least effort to implement and delivers relatively fast ROI. That said, implementation is not always straightforward. A recent survey by Becker’s Hospital Review found that although 51% of providers use some form of RPA, only 7% consider their adoption mature, and 33% describe it as robust. Still, with the right automation partner, RPA is a strong first step toward broader automation. This is because RCM processes are: Repetitive — tasks like sending invoices, verifying data, and checking compliance are ideal for automation. Stage-based — the revenue cycle consists of multiple structured steps that can be partially or fully automated. Error-prone — automation reduces human error and improves consistency. Costly — inefficiencies in RCM cost the U.S. healthcare system billions annually, many of which can be reduced through automation. ### How to use RPA in Revenue Cycle Management RPA enables multiple improvements across the revenue cycle: - Faster cost estimates through automated benefits retrieval - Pre-authorization support by pulling and transferring patient data across systems - Improved patient communication via automated scheduling and reminders - Automated data entry, reducing errors and denials - Better compliance with regulations like HIPAA - Streamlined handling of orders and referrals - Automated management of simple claim denials - Seamless integration between third-party systems - Enhanced patient experience through faster and more accurate processes ### Conclusion With constant regulatory changes, cost fluctuations, and unforeseen challenges like COVID-19, delivering high-quality medical services is not possible without a stable financial infrastructure. Healthcare leaders are increasingly adopting automation to ensure efficient and secure revenue cycle management. If you’re looking for a partner to [automate your RCM systems](https://www.flobotics.io/rcm-automation), Flobotics brings hands-on experience and an ROI-first approach — helping clients reduce costs, improve efficiency, and maximize revenue. At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RCMAIHealthcare ### RCM Statistics | 2026 Overview RCM statistics for 2026: denial rates hover near 5% and cost-to-collect keeps rising as manual processes lose ground. See the data. Jędrzej SzymulaJanuary 07, 2026 ](https://www.flobotics.io/blog/rcm-statistics-overview)[ HealthcareRCMAI ### RCM Outsourcing in Healthcare | 2026 RCM outsourcing in 2026: why offshore labor arbitrage is failing, and how Agentic AI outsourcing is replacing it. Bart TeodorczukFebruary 02, 2026 ](https://www.flobotics.io/blog/rcm-outsourcing-healthcare)[ RCMHealthcare ### Revenue Cycle Management (RCM) in Healthcare Revenue cycle management, explained: how US hospitals and practices stay compliant with payer policy and keep cash flow steady in 2026. Bart TeodorczukSeptember 30, 2024 ](https://www.flobotics.io/blog/revenue-cycle-management) [All articles →](https://www.flobotics.io/blog) --- # #5 Globally in GoodFirms’ Top RPA Companies for 2026! Canonical: https://www.flobotics.io/blog/flobotics-goodfirms-top-rpa-companies-2026 Author: Jędrzej Szymula Published: 2026-02-19 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/#5 Globally in GoodFirms’ Top RPA Companies for 2026! [RCM](https://www.flobotics.io/blog?category=rcm)[RPA](https://www.flobotics.io/blog?category=rpa) # #5 Globally in GoodFirms’ Top RPA Companies for 2026! [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published February 19, 2026Updated September 1, 2026 Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ‍Flobotics Hits #5 Globally in GoodFirms’ Top RPA Companies for 2026! 🏆🚀 This is a huge achievement. Out of 857 vetted Robotic Process Automation (RPA) firms worldwide, Flobotics has been ranked in the Top 5 by GoodFirms. They use a rigorous Company Performance Algorithm that cross-references technical core competencies, market presence, and verified client results. Being #5 means we are officially in the top 0.5% of RPA providers globally - accordingly to GoodFirms. They also highlighted exactly why Flobotics has climbed to the top of this massive field. According to their 2026 assessment, our success is built on three pillars: - Non-Invasive Excellence: The ranking recognizes our ability to implement complex automation "quickly and efficiently without making any changes to the existing system." We mimic human workflows—logging into apps and entering data—to provide immediate efficiency without the nightmare of a total backend overhaul. - Long-Term Strategic Success: GoodFirms notes that picking the right partner is crucial for "long-term success." Our #5 spot is a reflection of our 4.9-star rating and the feedback from clients who see us as a permanent extension of their team, not just a one-off vendor. - Verified Performance: Every project we've logged—from healthcare RCM to global finance - underwent a stringent verification process. This ensures that when we claim we improve efficiency through data digitization, the numbers actually back it up. A massive thank you to GoodFirms for the thorough review, and an even bigger shoutout to our clients and team. You are the reason we’re sitting at the top of the global leaderboards! Want to see why we’re in the Top 5? Check out our verified profile and the full 2026 rankings here: [Top Robotic Process Automation Companies - GoodFirms](https://www.goodfirms.co/robotic-process-automation) Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ AIRCM ### Forbes named us "#3 Best Polish Startup of 2025"! Flobotics named #3 on Forbes Poland's Best Polish Startups of 2025 (Service Company category) - recognized for scaling RPA and AI services in the US. Jędrzej SzymulaMarch 18, 2025 ](https://www.flobotics.io/blog/flobotics-forbes-polish-best-startups-2025)[ RPAAI ### We saved $2 Million from a 50% improvement for PRMG using UiPath! PRMG loan processing automation case study - see how UiPath RPA delivered a 6:1 ROI and $1.2M in labor savings over 36 months for this mortgage lender. Jędrzej SzymulaAugust 07, 2025 ](https://www.flobotics.io/blog/flobotics-prmg-loan-processing-rpa-automation)[ AIRPA ### We are a "Top Workday Implementation Partner for 2026" according to SuperbCompanies! Flobotics named a Top Workday Implementation Partner for 2026 by SuperbCompanies, ranked among 49 vetted firms for delivery and optimization results. Jędrzej SzymulaApril 05, 2026 ](https://www.flobotics.io/blog/flobotics-superbcompanies-top-workday-implementation-company-2026) [All articles →](https://www.flobotics.io/blog) --- # Revenue Cycle Management for Physician Practices Canonical: https://www.flobotics.io/blog/revenue-cycle-management-for-physician-practices Author: Jędrzej Szymula Published: 2026-02-19 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Revenue Cycle Management for Physician Practices [RCM](https://www.flobotics.io/blog?category=rcm) # Revenue Cycle Management for Physician Practices [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published February 19, 2026Updated September 1, 2026 On this page - [Payer AI vs. Practice Automation](#payer-ai-vs-practice-automation) - [The Payer AI Arms Race: Why Generic RCM is Failing](#the-payer-ai-arms-race-why-generic-rcm-is-failing) - [Best Practices for Billing and Coding](#best-practices-for-billing-and-coding) - [The G2211 "Revenue Leak"](#the-g2211-revenue-leak) - [Utilizing Technology in Revenue Cycle Management](#utilizing-technology-in-revenue-cycle-management) - [The Consumer-Patient: Real-Time Transparency or Bad Debt?](#the-consumer-patient-real-time-transparency-or-bad-debt) - [Key Performance Indicators to Monitor](#key-performance-indicators-to-monitor) - [The Impact of Regulations on RCM](#the-impact-of-regulations-on-rcm) - [Navigating Compliance Challenges in Revenue Cycle](#navigating-compliance-challenges-in-revenue-cycle) - [Case Studies on Successful RCM Practices](#case-studies-on-successful-rcm-practices) - [Demonstrating Financial Improvements](#demonstrating-financial-improvements) - [Summary](#summary) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Payer AI vs. Practice Automation The management of fiscal vitality within physician practices has shifted from a discipline of precision to a high-stakes "AI arms race." In 2026, the revenue cycle is no longer a linear sequence of functions beginning at the appointment. It is a continuous, autonomous loop where clinical data and financial adjudication happen simultaneously. Most practices still treat RCM as a back-office administrative task. However, in 2026, the revenue cycle begins 48 hours before the patient arrives. If your system isn't autonomously verifying eligibility and providing a Good Faith Estimate (GFE) at the point of scheduling, you aren't just facing delays - you are violating federal transparency mandates under the One Big Beautiful Bill Act (OBBBA). ### The Payer AI Arms Race: Why Generic RCM is Failing Administrative complexity is no longer the primary hurdle; "Payer AI" is. Insurance carriers are now deploying sophisticated algorithms that perform Batch Denials - rejecting thousands of claims in seconds based on micro-discrepancies in clinical documentation. Traditional RCM teams spend 13+ hours a week per physician on manual prior authorizations. Aditionally, 49% of physicians now rank "Payer use of AI in medical necessity determinations" as a top regulatory concern. In short: You cannot fight AI with humans. To survive, practices are shifting to Agentic AI—bots that don't just "follow rules" but can actually reason through a denial, analyze the physician’s ambient notes, and draft a defensible appeal before the claim even leaves the building. ## Best Practices for Billing and Coding Practices are increasingly looking toward refined workflows to protect their margins. Optimization requires a dual focus on human expertise and technical precision. ### The G2211 "Revenue Leak" Precision in coding is the primary defense against audits and rejections. Industry experts suggest that regular audits of coding practices are necessary to maintain compliance. "Consistent education on updated code sets is the only way to prevent avoidable denials," states a recent billing report. In 2026, the G2211 complexity add-on code has become a permanent pillar for independent practice survival. Yet, research shows that nearly 30% of practices fail to document the "longitudinal relationship" required to bill it, leading to a consistent 10% revenue leak per office visit. Optimization requires integrating Ambient AI Scribes with your billing engine. When the physician discusses a chronic condition, the AI should automatically flag the APCM (Advanced Primary Care Management) G-codes. This turns "clinical conversation" into "reimbursement-ready data" without the physician ever touching a billing screen. ### Utilizing Technology in Revenue Cycle Management Specialized software now automates labor-intensive tasks once handled manually. These systems aim to enhance the speed of claim submissions. "Revenue cycle management software has transitioned from an optional luxury to a foundational necessity for maintaining liquidity," suggests a report on healthcare technology. As high-deductible health plans become more prevalent, the burden of payment shifts toward the individual. This shift requires practices to implement clear communication regarding financial responsibility. "Transparency in pricing at the point of service is the most effective way to improve collection rates," notes a study on patient engagement. ### The Consumer-Patient: Real-Time Transparency or Bad Debt? High-deductible plans have effectively made "The Patient" your largest payer. In 2026, patient payments represent nearly one-third of total practice revenue. The 5-Minute Rule: Patients are 32% more likely to pay within five minutes if they receive a text-to-pay link with an integrated Advanced Explanation of Benefits (AEOB). If you are still mailing paper statements, your collection probability drops by 50% the moment the patient leaves your parking lot. Modern RCM must include "Digital-First" collections: text-to-pay, digital wallets, and automated, interest-free financing plans triggered at the point of service. The health of a practice is determined by its ability to convert services into cash. This requires constant monitoring of financial data. If you'd like to learn more [click here to read about top RCM metrics >](https://www.flobotics.io/blog/revenue-cycle-management-metrics) ### Key Performance Indicators to Monitor - The Days in Accounts Receivable metric tracks the average time it takes to receive payment. - The Clean Claim Rate measures the percentage of claims accepted on the first submission. Cycle Stage | 2026 Technical Challenge | The "Legacy" Performance | The "Autonomous" Performance | Eligibility | OBBBA / GFE Transparency | Manual portal checks (high error) | Real-time API interrogation | Coding | Complex 2026 ICD-10 sets | Human review (24-48hr lag) | Zero-click Autonomous Coding | Denials | Payer "Batch Denial" AI | Reactive (30 days to fix) | Predictive Pre-Submission Scrubbing | Collections | Rising Patient Balances | Paper-based "Dunning" cycles | Instant Text-to-Pay / AEOB | Reporting | Value-Based Care Audits | Monthly static reports | Real-time Revenue Integrity Dashboards | Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## The Impact of Regulations on RCM The regulatory environment continues to shift toward value-based care. These changes require a fundamental rethinking of how revenue is captured and reported. ### Navigating Compliance Challenges in Revenue Cycle Compliance involves adhering to federal mandates and insurance protocols. "Navigating the intersection of compliance and profitability is the greatest challenge for the modern practice manager," concludes a study on regulatory impact. Failure to adapt to these regulations can lead to heavy penalties and excluded claims. ## Case Studies on Successful RCM Practices Real-world applications demonstrate the value of structured management. These examples serve as a roadmap for struggling practices. ### Demonstrating Financial Improvements Case studies indicate that practices integrating rigorous accountability measures see marked improvements. "By restructuring the denial management team, one multi-specialty group reduced their outstanding debt by twenty percent in six months," reports a financial journal. The focus remains on the meticulous execution of each phase to ensure the continued viability of the medical profession. ### Summary The survival of the independent practice in 2026 depends on three pillars: the aggressive adoption of Predictive AI, the transition to Digital-First Patient Access, and the total automation of the "Clinical-to-Claim" loop. At Flobotics we specialize in U.S. healthcare revenue cycle management process automation. We build Agentic Revenue Operations designed to fight Payer AI on its own terms. We automate the high-impact triggers - eligibility, complex coding (G2211), and autonomous appeals - so your practice can scale without adding a single seat to your billing office – no generic bots here. Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RCMAIHealthcare ### RCM Statistics | 2026 Overview RCM statistics for 2026: denial rates hover near 5% and cost-to-collect keeps rising as manual processes lose ground. See the data. Jędrzej SzymulaJanuary 07, 2026 ](https://www.flobotics.io/blog/rcm-statistics-overview)[ RCMAIHealthcare ### Top RCM Trends | 2026 Top RCM trends for 2026: what healthcare finance leaders at Deloitte, HFMA, and beyond are prioritizing to strengthen revenue cycles. Karl MielnickiNovember 24, 2025 ](https://www.flobotics.io/blog/top-rcm-trends-healthcare)[ RCMHealthcare ### Revenue Cycle Management (RCM) in Healthcare Revenue cycle management, explained: how US hospitals and practices stay compliant with payer policy and keep cash flow steady in 2026. Bart TeodorczukSeptember 30, 2024 ](https://www.flobotics.io/blog/revenue-cycle-management) [All articles →](https://www.flobotics.io/blog) --- # Agentic AI Workflows Canonical: https://www.flobotics.io/blog/agentic-ai-workflows Published: 2026-02-04 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Agentic AI Workflows [AI](https://www.flobotics.io/blog?category=ai) # Agentic AI Workflows Published February 04, 2026Updated September 1, 2026 On this page - [1. Traditional vs. Agentic: The Execution Gap](#1-traditional-vs-agentic-the-execution-gap) - [2. The 4-Pillar Agentic Architecture](#2-the-4-pillar-agentic-architecture) - [3. Agentic RCM Use Cases: From Task to Autonomy](#3-agentic-rcm-use-cases-from-task-to-autonomy) - [4. Implementation Framework: The 2026 Maturity Model](#4-implementation-framework-the-2026-maturity-model) - [5. Governance & The "Silicon Workforce"](#5-governance-the-silicon-workforce) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) In 2026, the transition from Traditional Automation to Agentic AI Workflows represents the most significant architectural shift in Revenue Cycle Management (RCM) history. While traditional automation follows rigid "If-Then" logic, Agentic AI uses reasoning, memory, and tool orchestration to handle the messy, non-linear reality of healthcare billing. ### 1. Traditional vs. Agentic: The Execution Gap Traditional RCM automation acts as a "scripted tool," whereas Agentic AI acts as a "Digital Employee." FeatureTraditional Automation (RPA/Rules)Agentic AI Workflows (2026)LogicStatic, pre-defined rules. Dynamic reasoning & goal-oriented.Handling ExceptionsStops and flags for human review. Investigates, retrieves missing data, and resolves.MemoryResets after every task. Maintains context across long-running "sessions."Tool UseLimited to specific UI clicks. Can call APIs, query databases, and use web tools.RoleAssistant (Co-pilot). Autonomous Actor (Agent). ### 2. The 4-Pillar Agentic Architecture For an RCM Director, an "Agent" is defined by its ability to navigate the Planning-Execution-Refinement loop without constant prompts. - Planning & Decomposition: The agent breaks a high-level goal (e.g., "Resolve this denial") into sub-tasks: check payer policy, retrieve clinical notes, and draft an appeal. - Contextual Memory: Agents utilize "Agentic RAG" (Retrieval-Augmented Generation), allowing them to remember past interactions with specific payers or a patient's historical eligibility patterns. - Tool Orchestration: Using the Model Context Protocol (MCP), agents move beyond screen scraping. They use secure, standardized "connectors" to talk directly to EHRs (Epic/Cerner), clearinghouses, and payer portals. - Human-in-the-Loop (HITL) Checkpoints: High-impact actions (like submitting an appeal >$10k) are automatically routed to human supervisors for a "silicon-to-human" handoff. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ### 3. Agentic RCM Use Cases: From Task to Autonomy Industry leaders (McKinsey, Salesforce, 2026) are seeing 30–60% reductions in cost-to-collect through these specific agentic workflows: - Autonomous Denial Recovery: An agent doesn't just flag a denial; it logs into the payer portal, identifies the missing attachment (e.g., an X-ray), retrieves it from the EHR, and re-submits the claim autonomously. - Predictive Revenue Integrity: Agents act as "pre-submission auditors," cross-referencing clinical narratives against payer-specific NLP logic to predict and prevent "medical necessity" denials before they happen. - Agentic Eligibility Volatility: Agents perform "encounter-based" verification—checking insurance at scheduling, 24 hours prior, and mid-procedure to catch volatile mid-month coverage drops. ### 4. Implementation Framework: The 2026 Maturity Model RCM Directors should not overhaul everything at once. Use a phased-autonomy approach: - Augmentation (Day 1-90): Deploy agents as "Research Assistants" for your human billers to find documentation faster. - Automation (Day 91-180): Let agents handle the Back-End (A/R follow-up, cash posting) where rules are clearer and risks are lower. - True Autonomy (Year 1+): Transition to "Touchless" billing for high-volume, low-complexity service lines (e.g., Pathology, Radiology). ### 5. Governance & The "Silicon Workforce" Managing agents is becoming a new discipline of HR. - Onboarding: Agents require "training" on your specific business logic and PPO contracts. - Performance Management: You need Immutable Audit Logs and cryptographic receipts to prove why an agent made a decision, ensuring compliance with the HHS OIG GCPG guidelines. - Zero-Trust Identity: Every agent must have its own "digital identity" and ephemeral authentication to prevent unauthorized data access. At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPAAI ### Agentic AI Frameworks | 2026 Agentic AI frameworks in 2026: which stacks Google and other leaders are betting on, explained with clear, research-backed answers. Jędrzej SzymulaDecember 02, 2025 ](https://www.flobotics.io/blog/agentic-ai-frameworks)[ RPAAI ### Agentic AI Tools and Platforms Overview 2026 Agentic AI platforms for 2026: an overview of the tools driving autonomous workflows, plus Gartner's cost-saving forecast. Jędrzej SzymulaSeptember 16, 2025 ](https://www.flobotics.io/blog/agentic-ai-tools-platforms-overview)[ AI ### The Hottest Agentic AI Examples and Use Cases in 2026 Agentic AI examples and use cases: how AI agents are automating healthcare RCM, legal drafting, and retail inventory in 2026. Jędrzej SzymulaOctober 02, 2025 ](https://www.flobotics.io/blog/hottest-agentic-ai-examples-and-use-cases) [All articles →](https://www.flobotics.io/blog) --- # Compliance Automation in Healthcare Canonical: https://www.flobotics.io/blog/compliance-automation-healthcare Published: 2026-02-04 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Compliance Automation in Healthcare [AI](https://www.flobotics.io/blog?category=ai)[Healthcare](https://www.flobotics.io/blog?category=healthcare)[RPA](https://www.flobotics.io/blog?category=rpa) # Compliance Automation in Healthcare Published February 04, 2026Updated September 1, 2026 On this page - [Compliance Automation in Healthcare | GCPG Era](#compliance-automation-in-healthcare-gcpg-era) - [Key Regulations and Standards | 2026](#key-regulations-and-standards-2026) - [Compliance Documentation Necessities](#compliance-documentation-necessities) - [The Landscape of Compliance Automation Technologies](#the-landscape-of-compliance-automation-technologies) - [Types of Automation Tools Available](#types-of-automation-tools-available) - [Features to Look For in Automation Solutions](#features-to-look-for-in-automation-solutions) - [Implementing Compliance Automation: A Practical Guide](#implementing-compliance-automation-a-practical-guide) - [Step-by-Step Implementation Framework](#step-by-step-implementation-framework) - [Measuring Success and ROI of Automation](#measuring-success-and-roi-of-automation) - [Assessing Your Organization's Readiness](#assessing-your-organization-s-readiness) - [Step-by-Step Implementation Framework](#step-by-step-implementation-framework-2) - [Measuring Success and ROI of Automation](#measuring-success-and-roi-of-automation-2) - [Challenges and Solutions in Compliance Automation](#challenges-and-solutions-in-compliance-automation) - [Overcoming Resistance to Change](#overcoming-resistance-to-change) - [Addressing Common Implementation Pitfalls](#addressing-common-implementation-pitfalls) - [Future Trends in Compliance Automation in Healthcare](#future-trends-in-compliance-automation-in-healthcare) - [Innovations on the Horizon](#innovations-on-the-horizon) - [Preparing for Regulatory Changes](#preparing-for-regulatory-changes) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) In 2026, the regulatory landscape drifts toward continuous monitoring and enforceable configurations. According to latest [HHS OIG guidance](https://oig.hhs.gov/compliance/general-compliance-program-guidance/) updates, manual risk assessments are increasingly insufficient for healthcare organizations. Compliance is no longer a static "check-the-box" annual activity. Managing complex, third-party digital integrations compliance requires Continuous Control Monitoring (CCM). ## Compliance Automation in Healthcare | GCPG Era General Compliance Program Guidance (GCPG) makes it clear: manual risk assessments in healthcare are no longer a sufficient defense strategy. There are numerous reasons for it. For why compliance matters and the main U.S. laws behind it (HIPAA, HITECH, ACA, PSQIA and EMTALA), see [compliance automation in healthcare: regulations and benefits](https://www.flobotics.io/blog/compliance-automation). ### Key Regulations and Standards | 2026 - HIPAA Security Rule Modernization (2026): OCR now expects prescriptive security measures, including mandatory Multi-Factor Authentication (MFA) and encryption for ePHI at rest and in transit. The previous distinction between "required" and "addressable" implementation specifications is effectively being removed (HHS NPRM 2024-2026). Effective Feb 2026, the distinction between "required" and "addressable" specifications is removed. Multi-Factor Authentication (MFA) and Encryption at rest/in transit are now mandatory for all covered entities (HHS NPRM 2024-2026)‍ - Reproductive Health Privacy Rule (Feb 2026 Deadline): Covered entities must now obtain signed attestations for certain PHI requests to ensure data is not used for criminal or administrative investigations into lawful reproductive care.A critical 2026 deadline for RCM teams is the requirement for signed attestations for PHI requests involving reproductive care.‍ - NIST SP 800-66 Rev. 2: This remains the gold standard for mapping HIPAA standards to technical controls, emphasizing Risk Analysis and Risk Management as continuous activities rather than point-in-time snapshots. ### Compliance Documentation Necessities HHS OIG’s General Compliance Program Guidance (GCPG) now stresses the importance of tracking financial arrangements and incentives. - Audit-Ready Documentation: Regulators require written security incident response plans and procedures for testing those plans at least every 12 months. - Evidence of Control: Policies on file are no longer enough; you must provide timestamped, tamper-evident logs proving that safeguards—such as access terminations within 24 hours of workforce changes—were actually executed. HHS OIG’s latest guidance emphasizes Risk-Based Protection. - Asset Inventories: Organizations must maintain a network map illustrating ePHI movement, updated every 12 months. - Immutable Audit Logs: Documentation must provide timestamped evidence of control execution, such as access termination within 24 hours of workforce changes. ## The Landscape of Compliance Automation Technologies The shift from manual to automated compliance is characterized by the move toward Agentic AI and Continuous Control Monitoring (CCM). ### Types of Automation Tools Available - Continuous Control Monitoring (CCM): These platforms integrate with cloud infrastructure (AWS/Azure) and HR tools (Workday/ADP) to automatically collect evidence of encryption, MFA status, and user access rights. Platforms that integrate with cloud infrastructure (AWS/Azure) to monitor configuration drift in real-time - Agentic AI for BAA Management: New CLM (Contract Lifecycle Management) platforms use AI to draft, redline, and audit Business Associate Agreements (BAAs), ensuring mandatory 2026 clauses—like 24-hour incident reporting—are present in every vendor contract. AI agents that autonomously redline Business Associate Agreements to ensure 24-hour breach reporting clauses are present. - Autonomous Sanction Screening: Systems now perform daily scrubs against the LEIE, OFAC, and state Medicaid exclusion lists, replacing the risky monthly or annual manual check. Daily automated scrubs against the LEIE and OFAC, replacing the legacy monthly manual check. ### Features to Look For in Automation Solutions - Zero-Trust Architecture: Ensure the tool does not store PHI or use it to train global AI modelsContinuous identity verification for every access request. - FHIR-Based API Integration: Seamless connectivity with EHRs to monitor "Minimum Necessary" access in real-time. Bi-directional data exchange with EHRs to ensure "minimum necessary" access controls - Explainability & Audit Logs: The ability to provide an immutable log explaining why an AI agent made a specific compliance decision (e.g., denying a data access request). - H3: Features to Look For in Automation Solutions - Zero-Trust Architecture: - FHIR-Based API Integration: - Explainable AI (XAI): Audit trails that explain why an agentic bot flagged a specific transaction. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Implementing Compliance Automation: A Practical Guide Successful implementation requires moving away from the "all-at-once" overhaul in favor of a risk-ranked roadmap. Assessing Your Organization's Readiness Perform a "Data Flow Gap Analysis." Identify legacy systems lacking API support. Integration debt is the #1 cause of failed compliance automation in large-scale RCM environments. ### Assessing Your Organization's Readiness Before deployment, perform a Data Flow Inventory. Identify where ePHI is created, received, maintained, or transmitted across medical devices, IoT, and cloud SaaS. Organizations running legacy infrastructure without modern API support may face significant "integration debt" that must be addressed first. ### Step-by-Step Implementation Framework - Inventory & Scope: Map all assets and data flows to the NIST CSF 2.0 functions (Govern, Identify, Protect, Detect, Respond, Recover). - Enable Continuous Visibility: Deploy CCM tools to monitor configuration drift in real-time. - Automate Low-Complexity Tasks: Start with sanction screening, training tracking, and policy distribution. - Scale to High-Risk Areas: Implement automated risk scoring and BAA auditing. ### Measuring Success and ROI of Automation - Reduction in Audit Latency: Measured by the time required to produce a "defensible evidence pack" for OCR. - Cost-to-Collect Impact: Compliance automation reduces the "administrative drag" on RCM by 20–30%. - Cost Avoidance: The average healthcare settlement is $1.8 million per case. Quantify "Near Misses" caught by internal monitoring before they reached a regulator. - Operational Velocity: Organizations with operationalized compliance respond to government inquiries 40% faster and onboard new providers/locations in days rather than months. - Staff Capacity: Automated sanction screening and evidence collection can reclaim up to one full day per week for compliance professionals. ## Challenges and Solutions in Compliance Automation ### Overcoming Resistance to Change RCM staff often view automation as a threat. Frame the transition as a shift from "Data Entry Specialist" to "Risk Architect." Automation does not eliminate the need for compliance experts; it frees them to focus on high-judgment strategic risk management.H3: Overcoming Resistance to Change Frame the shift as moving from "Data Entry" to "Risk Architecture." Automation does not replace the Compliance Officer; it provides the telemetry needed for strategic decision-making. ### Addressing Common Implementation Pitfalls - The "Set and Forget" Fallacy: Automation must be updated after every EHR rollout or acquisition. - Vendor Compliance: Ensure your automation vendor signs a BAA and holds HITRUST/SOC 2 Type II certification. - The "Checkbox" Trap: Using automation as a static tool. If your automated risk assessment is not updated after a major system change or new EHR rollout, it becomes a liability during an OCR audit. - Vendor Trust: Avoid vendors who refuse to sign a BAA or those who cannot demonstrate HITRUST/SOC 2 Type II certification for their own platform. ## Future Trends in Compliance Automation in Healthcare ### Innovations on the Horizon - Agentic Governance: AI agents that autonomously adjust firewall rules or revoke access tokens based on detected anomalies in user behavior. - Blockchain for Credentialing: Emerging use of distributed ledgers to provide immutable, real-time verification of provider licenses and certifications across state lines. ### Preparing for Regulatory Changes As TEFCA networks and APIs scale through 2026, the intersection of Interoperability and HIPAA Right of Access will face increased scrutiny. Automated systems must be configured to handle record requests within the mandatory 30-day window (45 CFR 164.524) while strictly maintaining "minimum necessary" standards during exchange. At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # RCM Outsourcing in Healthcare | 2026 Canonical: https://www.flobotics.io/blog/rcm-outsourcing-healthcare Author: Bart Teodorczuk Published: 2026-02-02 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/RCM Outsourcing in Healthcare | 2026 [AI](https://www.flobotics.io/blog?category=ai)[Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # RCM Outsourcing in Healthcare | 2026 [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published February 02, 2026Updated September 1, 2026 On this page - [RCM Outsourcing | 2026 Perspective](#rcm-outsourcing-2026-perspective) - [RCM Outsourcing to Agentic AI | Key Features](#rcm-outsourcing-to-agentic-ai-key-features) - [Fast Docs Verification](#fast-docs-verification) - [Treating the cause, not the symptom](#treating-the-cause-not-the-symptom) - [Predictive Claim Scoring and AI Adjudication](#predictive-claim-scoring-and-ai-adjudication) - [Zero-Trust Compliance](#zero-trust-compliance) - [RCM Outsourcing | Managing the Risk Profile](#rcm-outsourcing-managing-the-risk-profile) - [Compliance in the Era of AI](#compliance-in-the-era-of-ai) - [RCM Outsourcing | Human-In-The-Loop](#rcm-outsourcing-human-in-the-loop) - [The Hybrid Outsourcing Matrix](#the-hybrid-outsourcing-matrix) - [Measuring Success Post-Outsourcing](#measuring-success-post-outsourcing) - [Key Performance Indicators (KPIs): The 2026 Dashboard](#key-performance-indicators-kpis-the-2026-dashboard) - [Summary](#summary) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## RCM Outsourcing | 2026 Perspective On average, people see Revenue Cycle Management (RCM) outsourcing as labor arbitrage. The logic behind it is simple: whenever the backlog spikes and denials go up, providers add more hands on deck - typically offshore headcount. Afterall, it’s much faster to hire specialists abroad than to search, hire, onboards and train people from the ground up. In 2026, that logic becomes outdated in the RCM world. Let’s face it - stuffing based on the Pakistani or India workforces is no longer sufficient in the RCM industry. Offshore outsourcing most often results in "information silosing". When billing teams are disconnected from the clinical reality of the practice - denial rates spike. Additionally, relying on the outsourced RCM team forces a stagnant "Cost to Collect" (CTC). That is exactly why the gap between “legacy billing companies" and automation supported RCM teams have significantly widened in 2025. All of these factors are important but not as much as agentic artificial intelligence. As payers began to deploy sophisticated AI to adjudicate (and reject) claims at scale, manual labor and basic clearinghouse edits have become increasingly insufficient. Moreover, selecting the right partner requires today an exhaustive vetting process that prioritizes technological depth, data transparency, and clinical-financial alignment. In short: Human-only teams could no longer keep pace with the sheer volume of algorithmic scrutiny. Leading RCM companies are moving from offshore outsourcing to agentic AI outsourcing. There are numbers of reasons to this shift, but mainly executives boards decide to invest in digital workforce because it: - operates 24/7, - cuts-down processing time, - unlocks RCM teams capacity, - ensures ROI within months. But most importantly, "Human-in-the-Loop" approach allows RCM specialists to invest their senior-level human oversight in complex appeals and payer negotiations, while high-speed automation takes over boring, repetitive tasks off their shoulders. We expect this trend to linger for a while. If you’d like to learn more about our prediction click here to read our article: [Top RCM Trends](https://www.flobotics.io/blog/top-rcm-trends-healthcare) | Staff Augmentation (“Stuffing”) | Offshore RCM Outsourcing | Agentic AI RCM Outsourcing | Trend Peak | 2018–2022 | 2022–2025 | 2025–2028 | Typical Locations | Onshore contractors | India, Pakistan, Philippines | Cloud-based (location-agnostic) | Operating Hours | Business hours | Limited by shifts | 24/7, always-on | Scalability | Linear (hire more people) | Semi-linear (add seats) | Exponential (scale compute) | Cost to Collect (CTC) Impact | Flat or rising | Often stagnant | ↓ 15–20% YoY | First-Pass Yield (FPY) | 85–92% | 83–90% | >95% | Data Visibility | Fragmented | Siloed | Unified, real-time dashboards | Clinical–Financial Alignment | Medium | Medium | High (“human-in-the-loop”) | Compliance Readiness (2026) | Medium | Medium | Strong (audit trails, AI logs) | Time to ROI | 12–24 months | 9–18 months | 3–6 months | ## RCM Outsourcing to Agentic AI | Key Features Not many people know, but AI doesn’t have to be implemented all at once. While in-house teams carry the burden of salary, benefits, and a 20-30% annual turnover rate (a chronic issue in 2025-2026) without clear ROI promise, the AI automations are available via outcome-based pricing. Unlike legacy outsourcing contracts that require linear head-count scaling, Agentic AI offers Decoupled Growth. Your volume can double, but your 'Cost to Collect' remains flat or shrinks as the agent's efficiency improves through reinforcement learning. ### Fast Docs Verification One of the most transformative technologies available via outsourcing is Automated Documentation Verification. AI agent compares clinical notes against billed procedures in real-time, highlighting gaps before the claim leaves the building. It is capable of verifying if a crown (D2740) has a matching X-ray or if an SRP claim includes periodontal charting with pocket depths of 4mm+. This ensures that your claims have "unassailable evidence" attached, which is crucial as payers increasingly use their own AI to find reasons to downcode restorative care. On top of that, AI agents can interact with your Practice Management System (PMS) just like a human. They click, type, and navigate – but at 10x the speed. This ensures 100% compatibility with any system (Open Dental, Dentrix, Eaglesoft) without the data silos or "lag" associated with older middleware. ### Treating the cause, not the symptom The most advanced automations have moved from reactive "denials processing" to "preventive denials scrubbing and management." Key features must include an AI-driven scoring engine that scans every claim for: - Missing clinical evidence: e.g., identifying a missing periodontal chart for a D4341 claim. - CDT Code Conflict: Flagging codes that payers in a specific region are currently downcoding. - Frequency Logic: Automatically checking the patient's "1-in-24" or "2-per-year" history across the entire payer network, not just your local database. If you’d like to learn more about it [click here to see our Denial Management Automation](https://www.flobotics.io/agents/denials-management-automation) ### Predictive Claim Scoring and AI Adjudication By 2026, the elite RCM partners utilize Agentic AI that scores every claim before submission. These tools analyze historical payer trends and AI-driven pattern recognition to tell your staff the exact likelihood of a denial. This moves the RCM team from a cycle of "appeals" to a cycle of "first-pass perfection." If you’d like to learn more about such solutions [click here to see our Claim Management Automation](https://www.flobotics.io/agents/claims-management-automation) ### Zero-Trust Compliance In terms of features, there’s also one last thing that has to be addressed: Digital workforce is safer than offshore labor. "Digital Workers" don't have personal devices, don't leave papers on desks, and operate within a Zero-Trust Framework where every click is logged and auditable. This means much better security standards compliance for the entire business. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## RCM Outsourcing | Managing the Risk Profile In 2026, the primary challenge during RCM outsourcing is no longer "communication lag," but algorithmic friction. If your outsourcing partner’s AI claim-scrubbers are not perfectly synced with the updated adjudication logic of major payers, you risk a "mass denial event" where thousands of claims are rejected in a single batch. Furthermore, data fragmentation remains a hurdle. When clinical notes reside in your local PMS but the billing happens in a third-party cloud, the RCM Director must manage the "latency" of information. If a payer requests an additional attachment, the time it takes for the outsourced team to retrieve that file from the local server is the new bottleneck in the "Claim-to-Cash" cycle. ### Compliance in the Era of AI RCM Directors must navigate a landscape where federal and state laws are specifically targeting the "Black Box" of automated billing. Here’s a short glimpse on regulatory environment of 2026 regarding AI usage in RCM world: The No Surprises Act (NSA) 2.0 As of 2026, the NSA has expanded to require even more granular Good Faith Estimates (GFE) for dental-medical crossover procedures. Your outsourcing partner must be able to generate these estimates within the 24-hour mandated window. State-Level AI Restrictions Several states have introduced legislation (following the 2025 "Transparency in Adjudication" acts) that requires healthcare providers to disclose when AI is used to code a claim. An RCM Director must ensure their partner is "Audit-Ready," with a clear trail showing exactly where AI made a coding decision and where a human certified it. Interoperability Mandates (CMS & ONC) New 2026 rules require dental groups to be able to share "Financial Health Data" with patients via standardized APIs. Your outsourcing partner must not only manage your claims but also support the backend data-sharing infrastructure that keeps you compliant with federal interoperability standards. ## RCM Outsourcing | Human-In-The-Loop Having in mind all those friction points, RCM leaders lean today towards a hybrid co-sourcing model. It allows to keep high-touch patient interactions in-house while delegating the "algorithmic heavy lifting" to AI agents. Current 2025 benchmarks show that outsourced RCM models utilizing Robotic Process Automation (RPA) can reduce administrative overhead by 25% while increasing topline revenue by 20%. 2025 benchmarks for AI agents are even higher. That’s why RCM automation is so important both in daily operations and scaling. If you’d like to learn more about it, [click here to read about agentic AI in healthcare](https://www.flobotics.io/blog/hottest-agentic-ai-examples-and-use-cases). ### The Hybrid Outsourcing Matrix Process Area | Ownership | Rationale | Front-End (Intake) | In-House | Ensures patient empathy and local data accuracy at the point of care. | Real-Time Eligibility | Partner (AI) | Scans for frequency limits and "1-in-24" rules 10x faster than humans. | Claim Scrubbing/Submission | Partner (AI) | Leverages "Collective Intelligence" to prevent regional denial trends. | Complex Appeals | Co-Managed | Provides the data/draft; In-house Clinical Director signs off. | Patient Collections | In-House | Preserves the clinical relationship and local reputation. | ## Measuring Success Post-Outsourcing The ultimate measure of success is the Net Collection Rate (NCR). While gross collections may fluctuate based on patient volume, the NCR reveals the partner’s ability to capture every dollar contractually owed. In a high-performing 2026 partnership, an RCM Director should expect a 98% or higher NCR on a rolling 90-day basis. If the rate falls below this, it typically indicates a breakdown in clinical documentation or a failure of the partner’s AI to keep pace with new payer adjudication logic. ### Key Performance Indicators (KPIs): The 2026 Dashboard To move beyond surface-level metrics, RCM Directors must track the "Big Five" KPIs that define modern dental fiscal health. These should be monitored in real-time, not via retrospective monthly reports. - Days Sales Outstanding (DSO): In 2026, the benchmark for elite DSOs is under 25 days. An outsourced partner using Agentic AI should be able to shave 10–15 days off the industry average by automating the "verification-to-submission" bridge. - First-Pass Yield (FPY): This measures the percentage of claims paid on the very first submission. A success threshold is >95%. A low FPY is a leading indicator of "administrative waste"–the high cost of rework that eats into your margins. - Clean Claim Rate (CCR): This tracks claims that pass all clearinghouse and internal AI scrubs without manual intervention. Success here indicates that your front-end team and RCM partner are perfectly aligned on data entry. - Denial Rate by Reason Code: You must track why claims are being rejected. If "Medical Necessity" is the top reason, the partner must work with your clinical directors to improve narratives. - Cost to Collect: This is the total cost of the outsourcing fee plus any remaining internal RCM labor. A successful partnership should see this metric drop by 15–20% compared to a fully in-house model. ### Summary leading RCM companies are moving from offshore outsourcing to agentic AI outsourcing. There are numbers of reasons to this shift, but mainly executives boards decide to invest in digital workforce because it: - Operates 24/7, - Boosts processing time, - Unlocks RCM teams capacity, - Ensures ROI within months. But most importantly, "Human-in-the-Loop" approach allows RCM specialists to invest their senior-level human oversight in complex appeals and payer negotiations, while high-speed automation takes over boring, repetitive tasks off their shoulders. Looking for a modern RCM outsourcing partner that specializes in healthcare automation? Our Agentic AI infrastructure prioritizes U.S. data residency, ensuring that while the workforce is digital and location-agnostic, your PHI remains within sovereign-compliant boundaries. Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) ‍ Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RCMAIHealthcare ### RCM Statistics | 2026 Overview RCM statistics for 2026: denial rates hover near 5% and cost-to-collect keeps rising as manual processes lose ground. See the data. Jędrzej SzymulaJanuary 07, 2026 ](https://www.flobotics.io/blog/rcm-statistics-overview)[ RCMAIHealthcare ### Top RCM Trends | 2026 Top RCM trends for 2026: what healthcare finance leaders at Deloitte, HFMA, and beyond are prioritizing to strengthen revenue cycles. Karl MielnickiNovember 24, 2025 ](https://www.flobotics.io/blog/top-rcm-trends-healthcare)[ RCMHealthcare ### RCM Automation in Healthcare | 2026 RCM automation in healthcare: how RPA, AI, and OCR cut billing errors, speed up claims, and reduce manual work in 2026 revenue cycle management. Bart TeodorczukFebruary 25, 2026 ](https://www.flobotics.io/blog/rcm-automation-healthcare) [All articles →](https://www.flobotics.io/blog) --- # Top Software Development Company in Indiana? Yes! According to DesignRush Canonical: https://www.flobotics.io/blog/flobotics-designrush-top-software-company-indiana Author: Jędrzej Szymula Published: 2026-01-29 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Top Software Development Company in Indiana? Yes!… [AI](https://www.flobotics.io/blog?category=ai)[RPA](https://www.flobotics.io/blog?category=rpa) # Top Software Development Company in Indiana? Yes! According to DesignRush [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published January 29, 2026Updated September 1, 2026 Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## DesignRush Names Us a Top Software Development Company in Indiana for 2026! Flobotics has officially been recognized by DesignRush as a leader in the Indiana software development landscape. Out of 52 vetted companies, Flobotics was selected for its ability to deliver custom, high-impact solutions that scale alongside our clients' businesses. This isn't just a list; it’s an expert assessment backed by a 4.8 average star rating from 264 verified reviews. In a market where reliability and technical depth are everything, this recognition proves that Flobotics is a top-tier choice for enterprises looking for more than just "code"—they are looking for a strategic partner. DesignRush analysts performed a deep dive into our operations, focusing on the core pillars that define a "Best Firm." According to the 2026 report, we stood out in three critical areas: - Scalable Custom Solutions: We don't build "one-size-fits-all" software. The report highlights our expertise in creating bespoke applications that allow businesses to add new functionality seamlessly as they grow. - Continuous Support & Maintenance: DesignRush recognized our commitment to the long-term health of our projects. We don't just launch and leave; we provide the ongoing maintenance and support necessary to ensure 100% uptime and performance. - Verified Client Success: With a stringent verification process, the 4.8-star rating reflects the real-world feedback of clients who have seen Flobotics transform their operations through technical precision and market-competitive rates. While our roots and office in Munster, Indiana, give us a local edge, this ranking acknowledges our ability to compete at the highest global levels. Whether it's streamlining local Indiana business workflows or architecting complex systems for our partners in the US and beyond, this award is a testament to our "get stuff done" philosophy. A massive thank you to our team for maintaining the excellence required to pass DesignRush’s expert assessment, and to our clients whose verified feedback made this #4.8 rating possible! Want to see the data for yourself? You can view our detailed profile and the full list of rankings here: ‍[Top Software Development Companies in Indiana - DesignRush 2026](https://www.designrush.com/agency/software-development/indiana) Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RCMRPA ### #5 Globally in GoodFirms’ Top RPA Companies for 2026! Flobotics ranked #5 globally among 857 vetted RPA companies by GoodFirms in 2026, recognized for non-invasive automation and verified client results. Jędrzej SzymulaFebruary 19, 2026 ](https://www.flobotics.io/blog/flobotics-goodfirms-top-rpa-companies-2026)[ AIRCM ### Forbes named us "#3 Best Polish Startup of 2025"! Flobotics named #3 on Forbes Poland's Best Polish Startups of 2025 (Service Company category) - recognized for scaling RPA and AI services in the US. Jędrzej SzymulaMarch 18, 2025 ](https://www.flobotics.io/blog/flobotics-forbes-polish-best-startups-2025)[ RPAAI ### We saved $2 Million from a 50% improvement for PRMG using UiPath! PRMG loan processing automation case study - see how UiPath RPA delivered a 6:1 ROI and $1.2M in labor savings over 36 months for this mortgage lender. Jędrzej SzymulaAugust 07, 2025 ](https://www.flobotics.io/blog/flobotics-prmg-loan-processing-rpa-automation) [All articles →](https://www.flobotics.io/blog) --- # We Are Among the Top Business Consulting Companies in the USA for 2026! Canonical: https://www.flobotics.io/blog/flobotics-top-business-consulting-companies-2026 Author: Jędrzej Szymula Published: 2026-01-26 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/We Are Among the Top Business Consulting Companies in the… [AI](https://www.flobotics.io/blog?category=ai)[RPA](https://www.flobotics.io/blog?category=rpa) # We Are Among the Top Business Consulting Companies in the USA for 2026! [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published January 26, 2026Updated September 1, 2026 Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Selectedfirms placed us in "Top Business Consulting Companies in the USA for 2026"! The verdict is in from Selectedfirms: Flobotics is officially ranked as a premier partner for business growth and strategy development. With a stellar 4.9 out of 5 rating based on 136 real, verified reviews, this recognition confirms that we are delivering the "unbiased, high-impact results" that modern enterprises demand. Selectedfirms doesn't just list every agency; they curate a specific selection of consultants who demonstrate proficiency in complex business scaling. Flobotics was selected because of our unique approach to Business Consulting & Strategy: - Market Analysis & Strategy Development: We don't just "install bots." The report highlights our expertise in analyzing market conditions and developing long-term strategies that align technology with business goals. - Driven by Real Reviews: Our 4.9-star rating is built on 136 real-world success stories. These aren't just testimonials; they are verified accounts of Flobotics helping companies navigate digital transformation and achieve sustainable growth. - Unbiased Evaluation: Selectedfirms uses a rigorous SF Score methodology. This ensures that our spot in the rankings is earned through proven performance, service quality, and our ability to solve the toughest "market analysis" struggles facing US businesses today. As Selectedfirms puts it, many companies struggle to find consultants who actually understand strategy development. This ranking proves that when Flobotics steps into a boardroom, we bring the market insights and technical foresight needed to turn "business growth" from a buzzword into a reality. Whether we are optimizing a supply chain or architecting an enterprise-wide automation strategy, this recognition from Selectedfirms is a testament to our team’s dedication to excellence and our clients' continued trust in our vision. Looking for a partner that understands the "Why" as well as the "How"? Check out our expert profile and the full list of Top Business Consultants here: [Top Business Consulting Companies in USA - Selectedfirms 2026](https://www.google.com/search?q=https://selectedfirms.co/directories/business-consultants/usa) Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPAAI ### We saved $2 Million from a 50% improvement for PRMG using UiPath! PRMG loan processing automation case study - see how UiPath RPA delivered a 6:1 ROI and $1.2M in labor savings over 36 months for this mortgage lender. Jędrzej SzymulaAugust 07, 2025 ](https://www.flobotics.io/blog/flobotics-prmg-loan-processing-rpa-automation)[ AIRPA ### We are a "Top Workday Implementation Partner for 2026" according to SuperbCompanies! Flobotics named a Top Workday Implementation Partner for 2026 by SuperbCompanies, ranked among 49 vetted firms for delivery and optimization results. Jędrzej SzymulaApril 05, 2026 ](https://www.flobotics.io/blog/flobotics-superbcompanies-top-workday-implementation-company-2026)[ RCMRPA ### #5 Globally in GoodFirms’ Top RPA Companies for 2026! Flobotics ranked #5 globally among 857 vetted RPA companies by GoodFirms in 2026, recognized for non-invasive automation and verified client results. Jędrzej SzymulaFebruary 19, 2026 ](https://www.flobotics.io/blog/flobotics-goodfirms-top-rpa-companies-2026) [All articles →](https://www.flobotics.io/blog) --- # RCM Statistics | 2026 Overview Canonical: https://www.flobotics.io/blog/rcm-statistics-overview Author: Jędrzej Szymula Published: 2026-01-07 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/RCM Statistics | 2026 Overview [AI](https://www.flobotics.io/blog?category=ai)[Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # RCM Statistics | 2026 Overview [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published January 07, 2026Updated September 1, 2026 On this page - [RCM Market Size | 2026](#rcm-market-size-2026) - [NPS & Patient Behavior | 2026](#nps-patient-behavior-2026) - [The “Walk-Away” Economy](#the-walk-away-economy) - [The Digital & Financial Wedge](#the-digital-financial-wedge) - [RCM Statistics | 2026](#rcm-statistics-2026) - [Denials Rate (DR) Up](#denials-rate-dr-up) - [Cost to Collect & Admin Burden](#cost-to-collect-admin-burden) - [Automation, AI & Outsourcing](#automation-ai-outsourcing) - [Patient Responsibility & Cash-flow Pressure](#patient-responsibility-cash-flow-pressure) - [Prior Authorization & Net Collections](#prior-authorization-net-collections) - [Days in A/R](#days-in-a-r) - [The Clean Claim Standard](#the-clean-claim-standard) - [RCM Statistics | Recent Years](#rcm-statistics-recent-years) - [RCM Statistics | Summary](#rcm-statistics-summary) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## RCM Market Size | 2026 Global RCM (software + services) was typically estimated around $160–170B in 2025. Different sources scope the U.S. market differently (software only vs software + services), but they all agree on strong double-digit growth and a large, maturing industry. They also estimate RCM growth at ~9–12% CAGR into the early 2030s. Ensemble’s targeted ~$13B valuation, Waystar/Iodine and R1 RCM buyout were good M&A signals that support this scope. Here’s our summary of the 2025 in terms of RCM statistics. Fig. 01 · RCM market $ billions RCM market size and growth, 2025–2034 - 2025$160–170B - 2030–2034 projection$360–410B ### NPS & Patient Behavior | 2026 The definition of patient loyalty has shifted. The passive patient who stayed with a provider out of habit is extinct. In their place is the 2025 healthcare consumer: - financially invested, - digitally empowered, - willing to churn. In other words: Patient loyalty in healthcare is increasingly shaped by operational experience rather than clinical outcomes alone. That is exactly why 2025 reports showed that B2B healthcare services lag significantly behind consumer expectations, with average NPS scores stagnating at +38. Traditional health systems are losing ground. Weighed down by disjointed care coordination and billing friction, many hospitals struggle to break the +50 mark. The message from the market is clear: clinical excellence is no longer enough to guarantee a high score. The experience gap between “retail healthcare” and “system healthcare” is widening. The industry average hovers near +61. Direct-to-consumer (B2C) models like One Medical or Hims are setting the pace, often exceeding scores of +70. They trade on retail-like convenience and seamless interfaces. Net Promoter Score (NPS) remains the industry’s North Star. But it is not the only KPI worth tracking. If you’d like to learn more about it, [click here to read our article on Key RCM Metrics](https://www.flobotics.io/blog/revenue-cycle-management-metrics). ### The “Walk-Away” Economy Digital “front doors” and transparent online reviews allow patients to shop for care like they shop for retail goods. That’s why 70% of healthcare consumers stated in 2025 they will switch providers if communication standards are not met. A Medical Economics report highlights the volatility of this new base. If communication fails to meet expectations, the majority of patients are now prepared to leave. The threshold for error is thin. In the general customer experience (CX) sector, 17% of consumers walk away after a single bad interaction. What drives a patient to recommend a hospital in 2025? It is not parking, and there are no wait times. It is the perception of safety. High perception of safety drives LTR to ~85.3, while a drop to “somewhat safe” crashes the score to 34.6. Press Ganey data uncovers a rigid hierarchy of needs. “Likelihood to Recommend” (LTR) is pegged directly to how safe a patient feels. Crucially, this is not just physical safety. It is emotional safety. Patients judge safety by teamwork. If they have to repeat their medical history to three different nurses, they perceive the team as disconnected. In short: Administrative friction is now interpreted by patients as a signal of system reliability. ### The Digital & Financial Wedge Healthcare NPS has declined by approximately 11 points over the last four years, driven largely by digital and administrative friction. The gap between high-performing B2C models and traditional providers is defined by digital friction. The “Amazon Effect” has normalized seamless transactions. Patients now expect their clinical and financial data to merge. Providers clinging to paper-based billing or opaque pricing models are bleeding loyalty. “Integrated Patient Pay” systems–where the bill clearly explains the clinical service and the cost–are now standard. 81% of consumers indicate that a superior digital experience, from scheduling to bill payment, directly influences their willingness to recommend a provider. The bill is no longer an administrative afterthought. If you’d like to learn more about the digital shift within the industry feel free to [read our article on RCM trends](https://www.flobotics.io/blog/top-rcm-trends-healthcare) Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## RCM Statistics | 2026 In 2025, revenue cycle performance was defined by friction rather than growth. Denials, administrative cost, and payer-driven complexity now shape cash flow more than volume or fee schedules. The data below shows how these forces are converging – and why traditional RCM operating models are failing to keep pace. Fig. 02 · RCM costs $ billions RCM administrative cost funnel - $90BTotal admin transaction cost - $20BAvoidable (22%) - $70BRemaining baseline ### Denials Rate (DR) Up In 2025 almost every source focused either on denials or payer friction. That’s probably the most characteristic theme of this year. [Experian’s 2025 State of Claims](https://www.experian.com/healthcare/resources-insights/thought-leadership/white-papers-insights/state-claims-report) survey was the main “anchor”. The report claimed that: In 2022, 30% of providers reported that at least 1/10 of claims were denied. In 2024, that number rose to 38%. In 2025, it’s now 41% of providers saying 1/10 of their claims are denied. So in short: organizations tend to fall into a “double-digit denial rate” bucket each year – including 2025. Denial rates above 10% are no longer manageable through staffing alone. Double-digit denial rates have become common enough to affect baseline financial planning. Experian ties this to: - Data errors at registration / intake - Staffing shortages - Outdated tech and fragmented systems feeding bad data into payers. Denials issue in 2025 was mainly defined in this report by an accelerating severity in dollar value. FierceHealthcare data reveals a sharp inflationary trend in rejected reimbursement, with the average value of denied inpatient claims rising 12% and outpatient claims 14% year-over-year. This value surge compounds a volume crisis where double-digit denial rates are no longer outliers. On top of that, over 41% of providers now report rates exceeding 10%, a figure reinforced by Kodiak Solutions’ benchmarking of an 11.8% industry average. Crucially, they attributed modeling challenges to the assumption that this is primarily a provider-side data failure: while 43% of denials stem from submission errors, a dominant 54% are driven by strategic shifts in payer policy. The mechanics of this friction are increasingly algorithmic and invasive, particularly in diagnostics. [Latest XiFin’s analysis of over 20 million claims](https://www.xifin.com/resource/white-paper/2025-payor-denial-impact-report/) highlights a distinct pivot toward AI-driven payer edits and automated medical necessity checks, which are aggressively targeting high-complexity molecular testing while expanding the battlefield from front-end rejections to post-payment recoupments. The aggregate economic toll is severe: Aptarro estimates that this cross-payer friction now consumes 3–5% of net patient revenue when lost income is combined with rework costs, cementing denials as a systemic tax on provider liquidity. Many 2025 sources still refer to a Change Healthcare estimate that U.S. hospitals lose roughly $262B annually due to denied claims (originally based on 2016 data). While not a fresh 2025 measurement, it sets the order of magnitude of the denial problem that current surveys are now tracking in more granular ways. ### Cost to Collect & Admin Burden In 2025, the industry definitively reframed “cost-to-collect” from a tactical back-office accounting metric into a primary strategic indicator. The sheer scale of the administrative friction remains staggering. CAQH data estimates the annual price tag for routine transactions–eligibility, prior authorizations, claims, and remits–at approximately $90 billion across the U.S. medical system. Crucially, the data suggests that fully automating these workflows could excise 22% of this burden, unlocking roughly $20 billion in immediate savings and reclaiming an estimated 70 minutes of administrative time per patient visit. But the 2025 shift is less about aggregate potential and more about rigorous, standardized accountability. While industry benchmarks, such as those cited by Zelis, typically place the cost-to-collect between 2% and 5% of net patient revenue, the definition has broadened to encompass the total weight of staffing, technology, vendor fees, and bad debt. This comprehensive view has now been formalized at the executive level. Kodiak Solutions launched a dedicated benchmarking survey late in the year to standardize the metric, while Black Book’s revamped framework at HFMA elevated cost-to-collect alongside denial write-offs as a central scorecard measure. Consequently, the operational reality of 2025 is defined not merely by the rising volume of denials, but by the increasing expense of resolving them, cementing audit burden and collection efficiency as the dominant KPIs of the modern revenue cycle. ### Automation, AI & Outsourcing While different sources state that vendor-circulated figures show nearly three-quarters of hospitals have deployed some form of RPA or AI, CAQH data indicates that a substantial “automation gap” remains, with 22% of administrative spending still retrievable through fully electronic workflows. The industry focus has consequently shifted from general experimentation to specific, high-yield applications: predictive denial prevention, intelligent worklist orchestration, and automated document classification. The divergence between casual adopters and digitally mature organizations is stark; high-performing entities now utilize AI bots to manage over 50% of eligibility workflows, reporting 30–40% reductions in denial rates and slashing labor costs per claim by approximately 35%. This technical complexity has catalyzed a parallel structural shift in labor strategy, where outsourcing has graduated from a temporary staffing stopgap to a permanent operational pillar. KLAS reports confirm a distinct migration toward end-to-end outsourcing partnerships, with health systems rigorously evaluating vendors on hard outcomes like denial performance and cost-to-collect rather than mere functional coverage. This evolution is further cemented by KPMG’s tracking of market consolidation, where private equity is aggressively fueling the merger of tech-enabled services and offshore operations. ### Patient Responsibility & Cash-flow Pressure Patient responsibility has become a primary source of cash-flow volatility. Beyond the sanitized averages of formal industry reports, the operational reality of 2025 is best illuminated by the friction visible at the practitioner level, where cash flow volatility has become the defining characteristic of the fiscal year. Field commentary suggests a crisis more acute than general benchmarks imply, with denial volumes surging 18–22% against recent baselines. Simultaneously, the revenue mix has undergone a perilous structural shift: Patient financial responsibility has swelled to constitute 35–40% of total revenue for many practices. This creates a precarious liquidity trap where providers are squeezed between aggressive payer adjudication and the difficulty of collecting large balances from consumers–a challenge exacerbated by worsening front-desk turnover that directly degrades collection performance at the point of service. This instability is rigorously quantified by Ensemble Health Partners, which notes that academic providers are enduring a compound annual growth rate in initial and final denials of 21% between 2022 and 2024. The resulting financial profile is one of asymmetric pressure. Even where patient volumes remain steady, the rising cost-to-collect and plunging cash collections per net patient revenue signal that the fundamental mechanics of provider liquidity are under siege. ### Prior Authorization & Net Collections 2025 benchmarks from the AMA indicate that physicians and their staff now spend an average of 12–14 hours per week navigating authorization protocols. According to the reports, companies process roughly 39 requests per physician weekly. This administrative drag is no longer just a clinical annoyance. It is a hard cost that directly impacts the Net Collection Rate (NCR). For 2025, the NCR benchmark–money actually collected vs. contractually allowed–must target 95–99%. An NCR below 95% implies that revenue is effectively being “donated” to payers through inefficient follow-up or abandoned denials. In a year defined by the “denial crisis,” maintaining a high NCR requires a rigorous defense of every billable dollar, ensuring that the friction of prior authorization does not translate into permanent revenue leakage. ### Days in A/R While strategy shifts, the fundamental speedometer of revenue cycle health remains Days in Accounts Receivable (A/R). In 2025, the margin for error has narrowed significantly. The industry standard for a healthy organization remains 30–40 days, but top-performing organizations leveraging AI-driven workflows are now pushing this benchmark below 25 days. The danger zone has also become more defined: consistent A/R days above 50 in 2025 signals a structural process breakdown, not just a temporary backlog. With the cost of capital remaining non-trivial, allowing claims to languish beyond this threshold is actively eroding margin. The 2025 mandate is clear: automation must be applied to compress the cycle time between service and settlement, turning A/R from a “waiting room” into a high-velocity clearinghouse. ### The Clean Claim Standard As the [HFMA (Healthcare Financial Management Association) “MAP Keys”](https://www.hfma.org/wp-content/uploads/2025/09/thestateoftheindustryin2025-fall2025stateconference-virginiadc.pdf) shows, the Clean Claim Rate (CCR) or First Pass Resolution has graduated from an efficiency metric to a survival metric. The 2025 gold standard for claims accepted without rejection on the first submission is 95% or higher. Falling below 90% is now considered a critical failure point, as it exposes the organization to the compounding costs of rework and the increasing likelihood of complex denials. Lower acceptance rates increase both administrative cost and payment latency. Industry data suggests a widening gap: While average performers hover around 95%, elite organizations using predictive claim scrubbing are consistently hitting 98%+. Every percentage point dropped in CCR correlates directly with increased administrative cost-to-collect and a delayed cash position, making front-end accuracy the single most effective lever for protecting net revenue. ​​Taken together, these forces turn denial management from an operational issue into a liquidity risk. ## RCM Statistics | Recent Years If the distinct data points of 2025 are assembled into a coherent whole, they reveal an industry defined not by gradual evolution, but by an aggressive structural reset. The prevailing narrative has shifted from “managing denials” to surviving a “denial crisis,” with practitioner discourse universally flagging a deterioration in payer behavior that is structurally worse than the 2022–2024 baseline. This is no longer just about initial rejections; the threat has expanded to include aggressive post-payment audits and recoupments, creating a scenario where claims that initially pay are increasingly clawed back. This escalation is driven by a visible AI arms race. Payers have successfully deployed automated logic for policy enforcement and utilization management, forcing providers to rapidly counter-arm with predictive analytics, autonomous coding, and algorithmic worklist orchestration simply to maintain parity. Fig. 03 · RCM Evolution How the RCM operating model has changed - Before 2020In-house, manual - 2020–2022Offshore outsourcing - 2025Automation This new volatility has reshaped the executive scorecard. “Cost-to-collect” has graduated from a secondary finance metric to a headline KPI, now positioned by HFMA, Black Book, and Kodiak alongside Days in A/R as a critical measure of organizational health. To manage this cost, the market has normalized outsourcing as a permanent strategic lever rather than a temporary staffing fix, while simultaneously attracting heavy venture capital and private equity investment into a new wave of tech-driven RCM startups like AKASA and PayZen. The result is a fundamental repositioning of the sector: RCM in 2025 is no longer a back-office administrative function, but an AI-intensive, capital-heavy industry operating on the front lines of financial defense. If 2025 proved anything, it’s that revenue cycle management is no longer something hospitals can afford to treat as background noise. The shift didn’t arrive with a single regulatory shock or headline-grabbing mandate. Instead, it showed up in spreadsheets, denial queues, and finance meetings that kept getting longer. Taken together, these trends point to rising operational risk within the revenue cycle. ## RCM Statistics | Summary Looking back, 2025 did not redefine revenue cycle management overnight. It did something quieter and more lasting. It made clear that getting paid had become a strategic discipline – one that demanded sustained attention, investment, and, above all, realism about how hard the work had become. Looking for an RCM automation partner specializing in the healthcare sector? Let’s talk! [👉 Book a 30-minute call](https://www.flobotics.io/book) Sources: - State of Claims 2025 – Experian Health - RCM KPI Benchmarking Report 2025 – Kodiak Solutions - Payor Denial Impact Report 2025 – XiFin - RCM Outsourcing & Performance Report 2025 – KLAS Research - Healthcare Cost-to-Collect Benchmarks 2025 – HFMA #### Like the article? Spread the word Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # What Is Agentic AI? | The Not-So-Obvious Guide Canonical: https://www.flobotics.io/blog/agentic-ai Author: Jędrzej Szymula Published: 2025-12-09 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/What Is Agentic AI? | The Not-So-Obvious Guide [AI](https://www.flobotics.io/blog?category=ai)[RPA](https://www.flobotics.io/blog?category=rpa) # What Is Agentic AI? | The Not-So-Obvious Guide [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published December 09, 2025Updated September 1, 2026 On this page - [Before You Read:](#before-you-read) - [What Is Agentic AI?](#what-is-agentic-ai) - [What’s not Agentic AI?](#whats-not-agentic-ai) - [Common Agentic AI Misconceptions](#common-agentic-ai-misconceptions) - [What Is Agentic AI? | Summary](#what-is-agentic-ai-summary) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ### Before You Read: Tool Agents Single-purpose, prompt-driven solutions powered by Large Language Models (LLMs) or other AI models. They can summarize, classify, extract, or generate text – but they do not act on their own. Every step requires human prompting or orchestration (Human in the loop). Agentic Workflows Automations that combine task interpretation with multi-step execution. Scalable and consistent, but limited to predefined paths. They read, use data (via APIs or AI tools), and follow structured sequences within specified guardrails. AI Workflows can’t self-direct beyond their design. Autonomous Agents It’s more of an idea than an actual solution. No fully general, unsupervised autonomous agent exists yet. What we call ‘autonomous agents’ today are advanced but still constrained agentic workflows with guardrails and human oversight – but they don’t have open-ended, self-directed autonomy. Fig. 01 · AI agents Cycle The agent operation cycle - 01Read - 02Reason - 03Act - 04Verify - 05Retry or escalate Repeats until the task is done ## What Is Agentic AI? So far, we’ve all heard about ChatGPT-style automations – generative AI tools that summarize notes, generate text or images, and provide likely answers to a question. Sora, Claude, Perplexity, they all share one defining trait: they wait for your instructions. Most of what gets labeled “agentic” today actually sits much lower on the intelligence scale than people think. Even though they seem intelligent, their reasoning is mainly statistical, not conceptual. Agentic AI is a much broader term. Agentic AI is the first generation of software capable of pursuing goals and automating multi-step workflows end-to-end with limited supervision – not just answering questions, but actually doing the work inside the guardrails you set. Until recently, AI could generate text or images but couldn’t take action. Even with prompts, plugins, and rule layers, today’s AI is still nowhere near a fully autonomous agent It’s the slice of AI that can take a goal, figure out the steps, act across your stack – and finish the job inside the guardrails you set. It simply sits between “autocomplete with extra steps” and “general intelligence” – close enough to the present to be useful, far enough from AGI to stay controllable. A simple way to think about the landscape is in four levels: - RPA & minor automations, - Tool agents, - Agentic workflows, - Fully autonomous agents. If you’d like to learn more about this topic, feel free to read our article: [“Agentic AI vs. RPA](https://www.flobotics.io/blog/agentic-ai-vs-rpa)“ ## What’s not Agentic AI? It’s important to draw a clear line between what’s agentic and what’s not. Most of what’s called “agentic” today actually lives in the middle: agentic workflows plus task-focused agents wired into real tools and real data. They can be impressively capable, but they operate inside guardrails. They don’t understand the world, they don’t have stable long-term memory or true causal reasoning, and they don’t run your business on their own. A lot of confusion comes from blurring these lines: - Prompt-driven tools (ChatGPT in a browser, image generators) are not agentic. - Dashboards, analytics, and simple integrations are not agentic. - RPA bots that click through portals are not agentic. All of them can be ingredients in an agentic architecture – but they only become agentic when you add goal-orientation, planning, tool use, state, and the ability to act across systems with limited supervision. Traditional RPA is not an agentic AI. These are the classic bots that follow fixed rules, click through portals, copy and paste values, or run scripts. They are fast and reliable, but completely rigid: the moment a screen changes, a field moves, or an exception appears, they break. They perform actions, but they cannot decide which actions to perform, and that alone disqualifies them from the agentic category. Prompt-driven generic tools are also not agentic. Traditional tools like ChatGPT–in–a–browser generate text or images. They are smart, fluent, and useful, but fundamentally passive. They wait for instructions, produce summaries, extract data, classify documents, or generate text and images. They provide output, but they do not take initiative. They cannot plan, sequence steps, or complete workflows unless a human orchestrates every move. Agentic AI uses the same intelligence but connects to tools, APIs, calendars, drives, CRMs, and apps – so it can actually execute work. Even API-based automations fall short of being agentic. Integrating systems, syncing data, or triggering simple workflows is valuable, but it lacks any reasoning layer. These systems move information from A to B, but they don’t interpret, adapt, or decide what to do next. They are connective tissue–not decision-makers. The same goes for dashboards, analytics platforms, and “AI insights” tools. They can measure, predict, and visualize, but they cannot act. They inform the operator but they don’t replace the operator. And how about Artificial General Intelligence (AGI)? It is not agentic AI – yet. Just like autonomous agents they require missing ingredients like: long–term memory, causal reasoning, stable identity, and generalizable understanding The reason AGI feels closer today and the reason people keep saying it’s “around the corner” is not because we built a breakthrough model. It’s because AI systems now behave in ways that resemble early forms of agency. They plan. They act. They revise. They even collaborate with other agents. These are not signs of general intelligence, but clearly show that we’re building architectures that look suspiciously like the skeleton of something more capable. AGI isn’t imminent, but it feels closer because the structural pieces that would support AGI – planning, tool use, memory, multi–step reasoning, coordination – are now being built for agentic systems. This is why the conversation gets interesting: the leap from today’s semi–autonomous agents to fully autonomous agents is almost the same leap as the one from fully autonomous agents to AGI. The barrier in both cases is the same set of unsolved problems: - How do you give a machine stable memory? - How do you make it understand a context that evolves across time? - How do you let it pursue goals without drifting into unsafe behavior? - How do you balance autonomy with control? - How do you give it the ability to generalize the way humans do effortlessly? So far, humanity hasn’t solved any of that. In short: Agentic AI is not everything that uses AI but it can use all of the digital assets if structured properly. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Common Agentic AI Misconceptions People see AI generate fluid explanations, clinically styled summaries, or step–by–step reasoning and assume the system actually grasps meaning the way a human does. It doesn’t. Here’s a bunch of misconceptions about agentic ai we often hear online: “AI understands / knows everything.” Modern models simulate understanding by predicting patterns across billions of examples. They don’t build mental models, they don’t interpret cause and effect, and they don’t know anything in the human sense of knowledge. This misconception inflates both trust and fear – teams overestimate AI’s autonomy while underestimating the need for oversight. Believing AI “understands” invites unsafe delegation and misplaced expectations, especially in workflows involving clinical nuance, legal constraints, or payer–specific rules that require actual reasoning. “Fluent language equals real comprehension.” Fluent language output triggers a cognitive bias: if it talks like us, it must think like us. But fluency is a surface feature, not a sign of cognition. This leads professionals to trust AI–generated explanations too quickly, assuming a coherent paragraph means the model reasoned its way to the answer. In reality, the model is generating the most statistically likely continuation. This misconception is dangerous because it creates a false sense of expertise – especially in complicated RCM scenarios where terminology looks authoritative but correctness depends entirely on context the model might not actually understand. “AI model that writes like a doctor reasons like one.” Medical–style language does not imply medical reasoning. Yet many clinicians and administrators fall into this trap. When an AI writes a clean eligibility interpretation or a compelling denial explanation, it’s easy to forget it lacks the domain experience that informs real decision–making. The risk is that organizations rely on AI as an authority rather than a tool – letting stylistic confidence mask conceptual shallowness. In RCM, this can lead to incorrect appeal logic, misunderstood payer rules, or confidently wrong benefit interpretations. It’s mistaken that AI possesses context, intentions, or understanding instead of patterns. Deep learning models thrive on pattern recognition, not situational comprehension. They don’t understand intentions or context beyond what appears in the prompt. This becomes a pain point when teams expect AI to “know” institutional rules, payer idiosyncrasies, task history, or organizational policy unless explicitly provided. Without structured memory and guardrails, AI forgets everything between interactions. Many failures in deployed systems come from expecting AI to “get it” without being given the necessary data every single time. “AI can operate fully on its own without guardrails.” Executives often expect a single AI system to run autonomously across complex operations, making safe and correct decisions indefinitely. But contemporary models require policy layers, identity controls, auditing, escalation logic, error monitoring, and human oversight. Without guardrails, AI becomes unpredictable. Autonomous capacity exists only within tight boundaries – outside them, workflows collapse or produce silent errors. Assuming full autonomy too early leads to failed deployments and loss of trust internally. “There’s an expectation that AI evolves into autonomy without design.” Many leaders assume agents will “naturally” learn to handle new workflows or complexities over time. But AI does not self–teach new domains or build its own operating procedures. Autonomy isn’t emergent – it’s engineered. Without deliberate design, updates, and guardrails, AI simply repeats patterns from its training or reinforcement loops. This misconception leads to disappointment when early experiments don’t scale across departments or when performance plateaus. “AI is just a fancy autocomplete for the big companies.” This misconception comes mainly from engineers who interacted with early generative models and froze their understanding at that level. They believe AI outputs are shallow surface–level continuations, and therefore dismiss its ability to plan multi–step tasks, reason across documents, or coordinate actions. Underestimating AI’s capabilities delays adoption and keeps organizations stuck in manual work long after automation could have replaced it. “Modern models cannot truly plan or reason.” That’s also not quite true. Many assume AI cannot connect steps or maintain logic across multiple actions. But contemporary systems, when combined with tool access and state tracking, can perform multi–step planning at a surprisingly operational level: retrieving data, interpreting rules, generating sequences, verifying work, and adjusting on the fly. Underestimating this makes organizations blind to automation opportunities hiding in workflows assumed to be “too complex” for AI. “AI must deliver flawless accuracy to be useful.” Executives often set unrealistic expectations: 99%+ accuracy, zero variance, zero hallucinations. But even we don’t operate at these levels either. AI only needs to be consistent and scalable – not perfect. A system that performs at 85–95% accuracy continuously can produce more reliable output than a human team fatigued by volume. Demanding perfection blocks adoption that would have delivered enormous ROI even at human–level error rates. “Errors mean the system is unfit for production.” In probabilistic systems, occasional errors are normal. With proper tuning, monitoring, and escalation paths, AI delivers strong outcomes despite variance. But many teams treat every mistake as catastrophic instead of expected, preventing iteration and improvement. “Intelligence alone can overcome chaotic inputs.” Teams assume AI will “figure out” inconsistent payer data, outdated forms, or messy clinical notes through sheer intelligence. But variability, not cognition, is the real obstacle. AI can handle complex reasoning, but not fragmented data pipelines without process redesign. Intelligence can’t compensate for operational chaos. “AI needs constant supervision” Yes, in the same way humans do: periodic QC, exception review, model updates, guardrail tuning, and monitoring. It does not need micromanagement, but it does require oversight. “AI is safest when isolated.” Some organizations try to confine AI to sandboxes that have no access to real systems. This avoids risk but also prevents value. AI that cannot act is just a sophisticated report generator. Useful AI requires controlled but meaningful system access, not total containment. “AI learns automatically once deployed.” A widespread fantasy is that AI improves simply by being used. Real improvement requires structured feedback, retraining, memory systems, or human reinforcement. When organizations expect self–evolving behavior, they misinterpret stagnation as failure. “AI will eliminate human jobs entirely.” This fear slows adoption and increases internal resistance. In reality, AI removes the repetitive burden around staff, allowing teams to focus on exceptions, complex judgment, and patient–facing impact. The work shifts; the workforce doesn’t disappear. “AI will replace entire departments immediately.” On the opposite side, some executives assume they can remove headcount rapidly. But AI requires supervision, exception handling, and governance. Overestimating how fast automation replaces staff leads to unrealistic timelines and failed deployments. “AI can be dropped into any workflow instantly.” Teams expect plug–and–play automation regardless of messy inputs. But AI needs clean interfaces, structured prompts, reliable data, and corrected upstream processes to perform well. Poor inputs produce poor outputs, no matter the model. “Why do AI implementations fail?” Most failures arise from misconceptions, not from model limitations: - treating AI like deterministic software - expecting perfection on day one - isolating AI instead of integrating it - misunderstanding the difference between tools and agents - expecting autonomy without guardrails - avoiding process redesign - skipping supervision and monitoring The technology works – adoption of frameworks not always. If you’d like to learn more about it, feel free to [read our article on Agentic AI Frameworks](https://www.flobotics.io/blog/agentic-ai-frameworks) ## What Is Agentic AI? | Summary Until recently, AI could generate text or images but couldn’t take action. Even with prompts, plugins, and rule layers, today’s AI is still nowhere near a fully autonomous agent A simple way to think about the landscape is in four levels: RPA & minor automations, Tool agents, Agentic workflows, and Fully autonomous agents. If you remember one thing from this 101, make it this: Agentic AI is not everything that uses AI. It’s the slice of AI that can take a goal, figure out the steps, act across your stack – and finish the job inside the guardrails you set. It simply sits between “autocomplete with extra steps” and “general intelligence” – close enough to the present to be useful, far enough from AGI to stay controllable. Time is revenue. Don’t lose either. Let’s talk! [👉 Book a 30-minute call](https://www.flobotics.io/book) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Agentic AI Frameworks | 2026 Canonical: https://www.flobotics.io/blog/agentic-ai-frameworks Author: Jędrzej Szymula Published: 2025-12-02 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Agentic AI Frameworks | 2026 [AI](https://www.flobotics.io/blog?category=ai)[RPA](https://www.flobotics.io/blog?category=rpa) # Agentic AI Frameworks | 2026 [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published December 02, 2025Updated September 1, 2026 On this page - [What Are Agentic AI Frameworks?](#what-are-agentic-ai-frameworks) - [Top 3 Agentic AI Frameworks | 2025](#top-3-agentic-ai-frameworks-2025) - [How to Choose Agentic AI Framework?](#how-to-choose-agentic-ai-framework) - [The CLEAR Standard](#the-clear-standard) - [Governance, Security, and Compliance](#governance-security-and-compliance) - [Agentic AI Frameworks Examples](#agentic-ai-frameworks-examples) - [phidata](#phidata) - [Agentic AI Frameworks | Lightweight Standards](#agentic-ai-frameworks-lightweight-standards) - [Flowise](#flowise) - [Stack AI](#stack-ai) - [Google Vertex AI Agent Builder](#google-vertex-ai-agent-builder) - [Amazon Bedrock Agents](#amazon-bedrock-agents) - [Agentic AI Frameworks | 2026 Predictions](#agentic-ai-frameworks-2026-predictions) - [Agentic AI Frameworks | Summary](#agentic-ai-frameworks-summary) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Are Agentic AI Frameworks? Agentic AI frameworks are sets of rules, decision gates, and task loops that guardrail Large Language Models (LLMs). They broaden their capabilities and push them into required directions. They dictate the overall direction and scope of behavior profile turning solutions like ChatGPT or Claude into goal-driven digital workers. They are focused on routing, governance, monitoring, and integration with APIs or apps. While AI agents aren’t fully autonomous yet, frameworks help them handle planning, tool calls, memory, safety, and orchestration correctly – but most importantly as expected. In short: The Agentic AI framework is the operational architecture that defines and guides the scope and autonomy of the digital workforce. Moreover, agentic AI frameworks transcend the capabilities of reactive, prompt-requiring models. If you’d like to learn more about it feel free to [read Agentic AI Tools and Platforms Overview >](https://www.flobotics.io/blog/agentic-ai-tools-platforms-overview) #### Agentic AI Layers Here’s a quick break down of modern AI layers: - AI tools are specific applications or software agents designed to perform discrete tasks. - AI workflows refer to the orchestration and sequence of automated steps. This moves beyond a single task to automating a chain of events, often handling the “handoffs” between different systems or people. - AI frameworks is the broadest term here. They represent the underlying infrastructure which allows tools and workflows to operate securely and scalably. This is the “foundation” that prevents a disjointed “Frankenstack” of incompatible tools. In short: AI Tools operate within an AI Workflow, which is built upon an AI Framework. #### Simple RAG vs. Agentic RAG RAG (Retrieval-Augmented Generation) is one of the most basic terms in the framework realm. Fundamentally, it is the architectural pattern that gives an AI access to your private data (like PDFs) so it doesn’t rely solely on public training data. However, the industry is now evolving from Simple RAG, which blindly fetches documents once like a search engine, to Agentic RAG, which acts like a researcher – actively reasoning, re-querying, and verifying facts until the answer is correct. Distinction between traditional Retrieval-Augmented Generation (RAG) and its advanced form, Agentic RAG is crucial in 2025. Here’s a graph illustrating the operational steps of agentic RAG: Fig. 01 · Agentic RAG Loop How agentic RAG works - 01User query - 02Agents - 03Check documents - 04Self-correct and reason - 05Final answer It repeats until the answer is good enough Distinction between traditional Retrieval-Augmented Generation (RAG) and its advanced form, Agentic RAG is crucial in 2025. Here’s a short differentiation: - Simple RAG operates via a static loop – the system receives a query, then fetches a document, and generates an answer. It lacks self-correction. - Agentic RAG acts like a researcher – It employs an autonomous reasoning layer to analyze initial results, rewrite queries if the data is insufficient, and cross-reference multiple sources. Since we explained all of the differentiations we can explore top 3 Agentic AI frameworks. ## Top 3 Agentic AI Frameworks | 2025 While there are many agentic AI frameworks used across the world, there are some that dominate in the West. Market data and developer adoption metrics indicate that 3 agentic ai frameworks rule in the Python ecosystem today. They are LangChain, AutoGen and CrewAI. LangChain is the definitive “go-to framework” used to connect LLMs with the external world. It is built around “chains” of reasoning, which allow developers to break down large tasks into smaller, more manageable steps. LangChain is a standard for integrating LLMs with external knowledge sources, APIs, and reasoning logic. It’s modular design makes LangChain highly effective for applications requiring complex, segmented workflows, such as financial risk modeling. LangChain’s most significant competitive advantage is its unrivaled interoperability. The framework offers the most extensive ecosystem available, boasting over 1,000 integrations across the entire GenAI stack, including various LLM providers, vector databases, document loaders, and deployment platforms. This ensures high flexibility and adaptability for production-grade systems. It is particularly evident in its extensive enterprise tool integrations. For example, LangChain facilitates deep interaction with Salesforce CRM, allowing developers to execute complex Salesforce Object Query Language (SOQL) queries and perform CRUD (Create, Read, Update, Delete) operations on Salesforce objects directly through the framework. LangChain has also been used by HubSpot, BigQuery, Slack, Notion, Jira, and many more. As applications increase in complexity, LangChain often necessitates significant developer time dedicated to manual prompt engineering and the configuration of intricate chains. While it offers unparalleled flexibility among AI frameworks, it also comes with a price – high scaling costs. High demand for low-level prompt expertise creates an architectural tension that justifies the existence of specialized, optimization-focused alternatives. Moreover, LangChain’s extensive adoption is validated by specific, named enterprise success stories: - Dun & Bradstreet: Leveraged LangChain to build the ChatD&B assistant, specifically for automating the explanation of complex credit-risk reasoning. - WEBTOON Entertainment: Employs the graph-based extension, LangGraph, to manage sophisticated visual-text content workflows However, traditional linear chains often prove inadequate for production-grade AI agents that require stateful memory and iterative decision-making. All of the aforementioned architectural constraints led to the necessary introduction of LangGraph. LangGraph is an extension that utilizes a graph-based approach to construct stateful, resilient, and inspectable multi-agent pipelines. the market is moving from basic LLM wrappers toward explicit control over multi-step, iterative execution. AutoGen is engineered specifically for building sophisticated multi-agent ecosystems where several specialized agents can communicate, debate, and collaborate to achieve a goal, mirroring human team dynamics. This capability is highly suited for applications such as collaborative problem-solving, negotiation, and brainstorming. AutoGen has demonstrated significant potential in pilot tests, where multi-agent systems reportedly outperformed human teams in tasks such as report generation and code debugging, largely due to built-in self-correction and negotiation features. AutoGen’s modular, conversational usage patterns successfully lower the entry barrier for organizations experimenting with multi-agent workflows. In recognition of the market’s need for a unified, robust standard, Microsoft is currently consolidating AutoGen (multi-agent orchestration) and Semantic Kernel (enterprise-grade features) into the Microsoft Agent Framework. #### Microsoft Agent Ecosystem (MAE) MAE it the default choice for enterprises on the Azure stack. Use MAF to write the code (connecting to local data or specialized logic) and Azure AI Agent Service to run it (handling scaling, auth, and history). Microsoft’s strategy has evolved from two separate libraries into a unified “Layer Cake” for enterprise agents: For years, developers had to choose between Semantic Kernel (great for single-agent enterprise integration) and AutoGen (great for multi-agent conversations). In late 2024, Microsoft unified these into the Microsoft Agent Framework (MAF). MAF is the “Best of Both Worlds” SDK. It takes the multi-agent orchestration patterns from AutoGen (agents talking to agents) and rebuilds them on the robust, type-safe foundations of Semantic Kernel. It introduces “Agent-to-Agent” (A2A) protocols. They’re responsible for agents built in Python that collaborate with an agent built in C# or Java. #### Azure AI Agent Service While MAF is the code, the Azure AI Agent Service is the infrastructure. It solves the “Day 2” problems of running agents in production: - State Persistence – Automatically saves conversation history so you don’t have to manage databases. - Enterprise Security – Uses Entra ID (formerly Azure AD) to ensure agents only access data they are authorized to see. - Scalability – Runs on serverless infrastructure, so you don’t need to manage GPU clusters for your agent orchestration layer. This unified successor provides critical enterprise-grade features, including robust thread-based state management, type safety, telemetry collection, filters, and explicit, graph-based workflows. These features are essential for granting developers explicit control over multi-agent execution paths in long-running or human-in-the-loop scenarios. Crucially, Microsoft has prioritized the solution to AI scaling and governance challenges with the introduction of Microsoft Agent 365, defining it as the “control plane for AI agents”. Given IDC’s prediction of 1.3 billion agents by 2028, enterprises require robust infrastructure to manage and govern this massive scale securely. Agent 365 addresses the primary concerns of IT leaders–sprawl, security, and compliance–by integrating agent management into the trusted Microsoft 365 Admin Center. This includes providing: A singular, comprehensive inventory of all agents in the organization, preventing “agent sprawl.” - Access Control – Leveraging Microsoft Entra ID for secure management and access. - Unified Observability – Delivering telemetry, dashboards, and alerts across the entire agent fleet. This strategic focus on governance and security demonstrates that Microsoft is addressing the C-suite’s biggest concern, ensuring the framework can transition successfully from developmental proof-of-concept to controlled, global enterprise deployment. Fig. 02 · Agentic AI The landscape Agentic AI frameworks and platforms Frameworks - LangChain - AutoGen - CrewAI - DSPy - LlamaIndex - Semantic Kernel - Pydantic AI - phidata - OpenAI Swarm - Microsoft Agent Framework Platforms and builders - OpenAI - Amazon Bedrock - Vertex AI - Microsoft Azure - StackAI - n8n - Langflow - Flowise - Model Context Protocol ## How to Choose Agentic AI Framework? The selection process for an agentic framework must be guided by technical compatibility, organizational fit, and long-term sustainability. Enterprise criteria that must be considered systematically include: - Scalability and Flexibility – The ability to support growing complexity and integrate custom components is vital. LangChain, with its vast ecosystem, is often cited as the most flexible, while AutoGen offers significant flexibility in designing multi-agent interactions. - Integration with Existing Systems – Compatibility with core business logic and enterprise resource planning (ERP) systems is non-negotiable. Frameworks must support seamless interfacing with APIs and databases, exemplified by LangChain’s ability to integrate with complex platforms like Salesforce. - Transparency and Explainability – For regulated industries or complex workflows, the agent’s execution must be traceable and inspectable, enabling debugging and regulatory compliance. - Security and Compliance – Production deployments require stringent adherence to security protocols and data compliance standards. - Cloud Infrastructure Fit – Organizations with significant cloud investment often benefit from native integrations. For example, Amazon Bedrock Agents offer the strongest native AWS integration and a fully managed deployment model, contrasting with the Do-It-Yourself (DIY) model common to AutoGen and CrewAI. ### The CLEAR Standard The CLEAR Framework (Cost, Latency, Efficacy, Assurance, Reliability), is a holistic evaluation standard specifically designed for assessing enterprise agent performance across five critical dimensions. The dimension of Cost is often highly overlooked, yet paramount for Return on Investment (ROI). Experimental evaluation has demonstrated that optimizing agents solely for accuracy (Efficacy) can result in systems that are up to x10 more expensive than cost-aware alternatives that achieve comparable task success rates. Therefore, enterprise deployment requires strategic, multi-objective optimization that balances performance against operational expense. The analysis of Latency reveals significant architectural challenges, particularly in web-interactive agents. Empirical findings demonstrate that the LLM API and the external web environment both contribute substantially to the total runtime. Specifically, the web environment latency–involving network fetching and HTML parsing–accounts for as much as 53.7% of the total execution time of a web-based agentic system. This significant contribution from non-LLM components proves that optimizing the core model or prompt is insufficient for production scaling. To mitigate this web environment overhead, specialized infrastructure solutions are required. The proposed technical solution is SpecCache, a caching framework augmented with speculative execution. It is an architectural optimization technique, not a downloadable framework like LangChain. SpecCache is designed to minimize network and parsing delays, reducing web environment overhead by up to x3 and improving the cache hit rate by up to x58 compared to random caching strategies. This highlights that latency reduction necessitates infrastructure-level intervention, moving beyond framework-specific tuning. ### Governance, Security, and Compliance The sheer scale of anticipated agent deployment–with 1.3 billion agents predicted by 2028 – creates an urgent need for centralized governance. Uncontrolled growth leads to the “agent sprawl problem,” posing severe security and compliance risks. The solution lies in implementing a unified control plane for managing autonomous systems. Frameworks like Microsoft Agent 365 directly address this gap by providing essential enterprise management capabilities: - Registry and Access Control – Agent 365 provides a single source of truth for all agents, eliminating blind spots and leveraging Microsoft Entra ID for secure access control and agent identification. - Security and Unified Observability – It enables IT leaders to monitor and govern the entire agent fleet through unified telemetry and alerts, ensuring compliance and reducing organizational risk. For large-scale organizations, the most robust strategy often involves a hybrid approach, leveraging the technical specialization of multiple frameworks (e.g., LangChain for integration, DSPy for reliability) while centralizing security, compliance, and management under a unified governance layer. Fig. 03 · Frameworks Comparison Use case and architecture fit Framework | Main use case | What sets it apart | Flexibility | Prompt management | LangChain | Extensive data integration (RAG, APIs) | Modular chains, tool calls, composability | Very flexible (broadest ecosystem) | Manual, configurable prompt engineering | AutoGen | Collaborative problem solving, negotiation | Agent-to-agent communication and orchestration | Highly flexible (multi-agent design) | Conversational, role-based prompting | DSPy | Complex multi-stage reasoning, reliability | Automated prompt optimization and LLM stacking | Flexible (optimization and evaluation only) | Declarative, programmatic prompt optimization | CrewAI | Structured, role-based teamwork | Simple definition of roles and goals | Moderate (easier entry point) | Role-based prompting (team-focused) | #### The “TL;DR” Decision Matrix: - For the “Microsoft Shop” Enterprise – Microsoft Agent Ecosystem (MAF + Azure) is the undisputed winner. It offers the tightest security, unified observability, and a seamless path from code (Semantic Kernel) to cloud (Azure Agent Service). - For Complex, Agnostic Orchestration – LangChain & LangGraph remain the industry heavyweights. If you need to chain 5 different models, connect to Salesforce, and manage complex loops, this is your toolkit—provided you are willing to manage the infrastructure. - For “Code-First” Engineering Teams – PydanticAI is the rebellion against complexity. It is the best choice for senior Python teams who want type safety, reliability, and zero “magic” abstractions. - For Data-Intensive & Financial Agents – Phidata and LlamaIndex dominate. Use them when your agent’s primary job is to read charts, parse messy PDFs, and output structured SQL or JSON data. - For Future-Proofing Connectivity – Model Context Protocol (MCP) is non-negotiable. Regardless of which framework you choose, ensuring your data layer is MCP-compliant guarantees you won’t be locked into a single vendor. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Agentic AI Frameworks Examples DSPy and LlamaIndex represent critical areas of specialization–LLM optimization and data orchestration–that often separate professional engineering solutions from experimental prototypes. Here’s why: DSPy (Declarative Self-improving Language Programs) introduces a fundamental shift away from manual, low-level prompt engineering. It employs a declarative paradigm, allowing developers to specify the desired high-level logic (the task and the data flow) while the framework systematically handles the complexities of prompt optimization and few-shot example selection automatically. The imperative for this specialized approach is rooted in the instability and difficulty of scaling manually tuned prompts. In complex multi-stage reasoning pipelines, involving stacked LLM calls and multi-hop logic, manual configuration becomes an untenable bottleneck. DSPy’s built-in optimizers transform prompt tuning from an unstable craft into a scalable engineering discipline, resulting in higher reliability and consistency. DSPy is uniquely suited for specific project types: - Complex Multi-Step Reasoning: It excels in projects involving many chained LLM calls, where its modular design and automated tuning create more reliable pipelines. - High Reliability Needs: For building robust conversational agents or complex information retrieval systems that require consistent, contextually accurate outputs, DSPy’s systematic optimization ensures a higher degree of robustness compared to traditional approaches. Architecturally, LangChain and DSPy serve complementary purposes. LangChain is the superior choice for breadth–integrating diverse data sources and APIs. DSPy, conversely, is superior for depth–optimizing the consistency, accuracy, and reliability of LLM outputs across complex reasoning steps. The rapid adoption and significant growth of DSPy’s community (16K GitHub stars by late 24) provides strong evidence that the market recognizes the need for automated optimization solutions in production-grade systems. LlamaIndex is the specialized open-source data orchestration framework that accelerates time-to-production for Generative AI applications requiring trusted, data-intensive agentic workflows. Its core strength lies fundamentally in advanced Retrieval-Augmented Generation (RAG) capabilities, focusing on data integration, indexing, and retrieval. The most frequent point of failure in enterprise GenAI/RAG deployments is not the LLM or the prompt, but the initial process of transforming complex, unstructured data into AI-ready formats. Enterprise data often resides in messy documents–complex PDFs, embedded images, nested tables, and handwritten notes LlamaIndex addresses this bottleneck directly through its commercial tools: For orchestration, LlamaIndex offers the Workflows engine. It is an event-driven, async-first engine that provides developers with granular control over stateful, multi-step AI processes. Workflows allow for complex operations such as looping, parallel path execution, and managed state maintenance. The asynchronous-first nature of Workflows is optimized for modern Python web applications, enabling highly efficient parallel execution and accelerating the time-to-production for GenAI applications. LlamaIndex’s authority in data-intensive environments is demonstrated by its successful deployment in critical sectors: - LlamaCloud and LlamaParse – These components deliver industry-leading document parsing and extraction ca - Carlyle (Private Equity) – Uses LlamaParse for high-accuracy financial document analysis, investment research, and due diligence. - KPMG – Utilizes LlamaIndex to provide essential context for data processing and analysis, thereby enhancing AI capabilities and delivering more accurate client insights. By dominating the high-accuracy data parsing and indexing segment, LlamaIndex has carved out a unique and necessary niche as the default framework for data-centric agentic applications. ### phidata Phidata is a specialized framework designed for building Multi-Modal Agents with long-term memory. Unlike LangChain (which is general-purpose), Phidata focuses heavily on “function calling” and structured data outputs. The “go-to” framework for financial analysts and data teams. While other frameworks struggle to output clean JSON from a PDF, Phidata excels at turning unstructured data (like a video or a messy Excel sheet) into structured database rows. It is frequently used for building “Investment Analyst” agents that can read charts, parse news, and output a structured report. #### Why is Phidata a “Hidden Gem”? Most agent frameworks focus on the reasoning loop (how the agent thinks). Phidata focuses on the memory and data layer (what the agent knows and keeps) capabilities. LlamaParse is explicitly cited as the premier solution for parsing complex documents in Enterprise RAG pipelines, due to its exceptional handling of intricate spatial layouts and nested tables. This specialization ensures data integrity, which is vital for building trustworthy agent-based models. - Memory as Infrastructure, Not an Afterthought – In LangChain, adding persistent memory (saving a conversation to a database) requires setting up complex chains of commands. In Phidata, it is a single line of code. This makes it incredibly fast to ship stateful agents that remember users across sessions. - Multi-Modal by Default – Phidata was one of the first frameworks to optimize for Gemini 1.5 Pro and GPT-4o’s vision capabilities. You can drop a video file into a Phidata agent, and it can analyze the visual frames and audio simultaneously—a capability that requires significant “glue code” in other frameworks. - The “Function Calling” Specialist – Phidata abstracts away the complexity of OpenAI/Anthropic function calling. Instead of writing complex JSON definitions for your tools, you simply pass a Python function. Phidata automatically generates the JSON schema, handles the argument parsing, and returns the result to the LLM. ### Agentic AI Frameworks | Lightweight Standards While frameworks like LangChain and Microsoft MAF aim to be “do-it-all” platforms, a powerful counter-movement emerged in 2025 focusing on simplicity and standardization. These tools are critical for engineering teams who prefer “code over configuration.” #### PydanticAI PydanticAI is a code-first agent framework. It rejects complex abstractions (like “Chains”) in favor of standard Python code and type hints. Business use: The top choice for senior Python engineering teams building production agents who want full control and zero “magic.” In 2024, many teams struggled to debug LangChain’s complex internal abstractions. PydanticAI offers a “what you see is what you get” experience. If you know Python, you know PydanticAI. It uses Python’s native type system to guarantee that the data your agent outputs matches exactly what your API expects. This prevents the most common source of agent runtime errors. #### The Model Context Protocol (MCP) MCP is an open standard (pioneered by Anthropic) that acts as a “USB-C port” for AI agents. It allows any agent to connect to any data source without writing custom integration code. Before MCP, connecting 3 AI assistants to 5 different tools required 15 different integrations. With MCP, you build the tool interface once, and Claude, ChatGPT, and your custom MAF agents can all use it instantly. As of 2025, MCP has become the de-facto standard for data connectivity, supported by major heavyweights including Microsoft, Anthropic, and Replit. Fig. 04 · Frameworks Lock-in Vendor lock-in vs orchestration control Feature | OpenAI Assistants API | OpenAI Swarm (experimental) | Open source (LangChain, MAF) | Main goal | Ease of use: "it just works" | Multi-agent research patterns | Full control and flexibility | State management | Managed by OpenAI (black box) | Client side (local) | Fully controlled (Postgres, Redis) | Vendor lock-in | High: hard to switch models | High: optimized for GPT-4o | None: swap models easily | #### Agentic AI Frameworks | Visuals & Low-Code #### Not every agent needs to be written in pure Python. In fact, a massive segment of the 2025 market – particularly Product Managers, Solution Architects, and “AI Ops” teams – has moved away from IDEs entirely. They rely on visual, drag-and-drop builders to prototype logic before handing it off to engineering, or increasingly, to deploy directly to production. This shift has given rise to a “Low-Code Rebellion,” where the barrier to entry for building complex reasoning agents is no longer knowing syntax, but understanding system design. If LangChain is the engine, Langflow is the dashboard. Originally a simple UI wrapper, Langflow has evolved into the industry standard for “Visual Python.” Its core premise is unique: every node you drag onto the canvas (a PDF loader, a Prompt, a Vector Store) is just a Python function under the hood. This means developers can “eject” to code at any time, eliminating the “black box” fear that plagues most no-code tools. Following its acquisition by DataStax, Langflow has graduated from a hobbyist tool to an enterprise staple. It is now the fastest way to demo a “Chat with PDF” or RAG prototype to stakeholders without writing a single line of boilerplate. ### Flowise While Langflow excels at data pipelines, Flowise has carved out a niche in logic pipelines. It is widely favored for more complex, enterprise-grade workflows that involve “If/Else” routing and stateful loops. Flowise is the tool of choice for “AI Operations” teams. When a business rule changes—for example, “If the customer is a VIP, route to GPT-4; otherwise, use GPT-4o-mini”—an Ops manager can tweak the logic node in Flowise visually, instantly updating the production agent without waiting for a developer to redeploy code. The most significant disruption in the low-code space in 2025 comes from n8n. Originally a workflow automation tool, n8n pivoted aggressively to become the “Action Layer” of the agentic economy. Unlike Langflow or Flowise, which focus on reasoning(how the agent thinks), n8n focuses on connectivity (what the agent does). It has become the de-facto “glue” for agents, offering native nodes that allow AI to autonomously control Slack, Email, CRMs, and ERPs. In short: n8n is the bridge between an abstract LLM and a concrete business outcome. In 2025, the most effective teams used Langflow to prototype the brain, n8ns to connect the hands, and Python only when absolute granular control is required. ### Stack AI For organizations that cannot afford the DevOps overhead of hosting open-source tools like Langflow or n8n, Stack AI is a go-to solution. It is a SOC2-compliant, fully hosted platform designed for Product Managers who need to ship production-ready backends instantly. It abstracts away the infrastructure entirely, focusing purely on the prompt chain and data connections. #### Agentic AI Frameworks | Enterprise Platforms To fully understand the [landscape of Agentic AI](https://www.flobotics.io/blog/agentic-ai-tools-platforms-overview), one must look beyond open-source libraries like LangChain and CrewAI. While those tools offer granular control, they often require significant engineering overhead to manage infrastructure, security, and scaling. Enterprise Platforms represent the “Managed Services” layer of the agentic stack. They are important because they solve the “Day 2” problems of deployment: - Governance, - Identity Management, - Serverless Scaling. For large organizations, these platforms are often the bridge that turns a fragile Python prototype into a compliant, production-grade business application. Here is how the two cloud giants are approaching agent architecture: ### Google Vertex AI Agent Builder Vertex AI Agent Builder is Google’s full-stack platform designed to build, scale, and govern enterprise agents directly on top of Gemini models and your existing Google Cloud Platform (GCP) data. It differentiates itself with a comprehensive Agent Development Kit (ADK) that unifies orchestration with production-grade observability and governance. In most cases, it is the best choice if your organization is already invested in the GCP / BigQuery ecosystem. It is ideal for building internal copilots, customer support agents, and data analysis agents where strict security controls and native data integration are non-negotiable. ### Amazon Bedrock Agents Amazon Bedrock Agents allow developers to define autonomous agents that utilize foundation models, APIs, and proprietary data to execute complex multi-step tasks. With the introduction of AgentCore (GA in Oct 2025), Amazon provides a dedicated agentic infrastructure to build, run, and monitor agents at scale without the need to provision servers. A strong choice for teams building on AWS who want managed security, scaling, and observability without running their own orchestration layer. It is particularly notable for its native support of Model Context Protocol (MCP) based tools, allowing for standardized connections to external data systems. ## Agentic AI Frameworks | 2026 Predictions According to Gartner, [40% of enterprise applications will feature embedded task-specific agents by 2026](https://www.gartner.com/en/newsroom/press-releases/2025-08-26-gartner-predicts-40-percent-of-enterprise-apps-will-feature-task-specific-ai-agents-by-2026-up-from-less-than-5-percent-in-2025) (up from less than 5% today). Here are the three trends that will define the next 12 months: - The “Agent-to-Agent” (A2A) Economy – In 2025, we’ve talked to agents. In 2026, agents will talk to agents. We will see the rise of “headless” marketplaces where a Marketing Agent (running on CrewAI) automatically hires a Research Agent (running on AutoGen) via the Model Context Protocol (MCP) to verify facts without human intervention. - From RAG to LAMs (Large Action Models) – Retrieval-Augmented Generation (RAG) solved the “knowledge” problem. The next frontier is the “action” problem. Frameworks will evolve to support Large Action Models (LAMs) – systems capable not just of reading a PDF, but of clicking buttons, filling forms, and navigating complex UI on your behalf. As “Agent Sprawl” becomes a security risk, IT departments will also mandate centralized control planes. The “Wild West” of deploying rogue Python scripts will end. Platforms like Azure AI Agent Service and Salesforce Agentforce will become the mandatory gatekeepers for enterprise deployment, forcing developers to build compliant, observable agents by default. ## Agentic AI Frameworks | Summary At Flobotics we think 2026 is going to be the end of the “Proof of Concept” era. The industry is not asking anymore: “Which LLM should I use?”, but rather “Which Framework to choose?”. And that’s a big shift. All surviving AI frameworks – whether heavyweights like LangChain or specialized standards like MCP – will eventually share one common trait: Reliability. But, transition from passive Chatbots to active Digital Workers requires a robust architectural foundation. Even the “best” frameworks still depend entirely on your engineering culture, existing tech-stack, and governance needs. If you’re about to choose a future-proof agentic AI framework, prioritize those offering: - Observability (to see what the agent is doing), - Control (to stop it when it errs), - Interoperability (to switch models when the next GPT-5 arrives). The future belongs to those who can govern their AI. Looking for an AI automation partner? Let’s talk! [👉 Book a 30-minute call](https://www.flobotics.io/book) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPAAI ### What Is Agentic AI? | The Not-So-Obvious Guide What is agentic AI? A clear guide to how autonomous AI agents reason, act, and differ from traditional rule-based automation. Jędrzej SzymulaDecember 09, 2025 ](https://www.flobotics.io/blog/agentic-ai)[ AI ### The Hottest Agentic AI Examples and Use Cases in 2026 Agentic AI examples and use cases: how AI agents are automating healthcare RCM, legal drafting, and retail inventory in 2026. Jędrzej SzymulaOctober 02, 2025 ](https://www.flobotics.io/blog/hottest-agentic-ai-examples-and-use-cases)[ RPAAI ### Agentic AI Tools and Platforms Overview 2026 Agentic AI platforms for 2026: an overview of the tools driving autonomous workflows, plus Gartner's cost-saving forecast. Jędrzej SzymulaSeptember 16, 2025 ](https://www.flobotics.io/blog/agentic-ai-tools-platforms-overview) [All articles →](https://www.flobotics.io/blog) --- # Top RCM Trends | 2026 Canonical: https://www.flobotics.io/blog/top-rcm-trends-healthcare Author: Karl Mielnicki Published: 2025-11-24 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Top RCM Trends | 2026 CTO Notes [AI](https://www.flobotics.io/blog?category=ai)[Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Top RCM Trends | 2026 [Karl MielnickiCTO & Co-Founder of Flobotics](https://www.flobotics.io/our-editorial-team#mielnicki) Published November 24, 2025Updated September 1, 2026 On this page - [Intro | 2025 as a Breaking Point](#intro-2025-as-a-breaking-point) - [Top RCM Trends in U.S. Healthcare | 2026 Edition](#top-rcm-trends-in-u-s-healthcare-2026-edition) - [Upcoming RCM Trends | 2030 Perspective](#upcoming-rcm-trends-2030-perspective) - [EHR Softwares on the rise:](#ehr-softwares-on-the-rise) - [Summary | Which Solutions To Choose?](#summary-which-solutions-to-choose) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) AI, Automation, and the Rise of Digital Workforces in the U.S. Healthcare ### Intro | 2025 as a Breaking Point 2025 was one of the most demanding years for healthcare finance. Rising denial rates, manual admin work, and shrinking margins dominate in last year's reports – from Deloitte to HFMA. The RCM market itself is projected to grow from ~$135B today to over $350B by 2034. It is a clear signal that financial operations in healthcare are becoming as critical as clinical delivery Unfortunetly, the U.S. still burns nearly $1 trillion a year on administrative overhead. Even top performers struggled to keep Cost-to-Collect under 4%. RCM teams faced staffing gaps, delayed reimbursements, and outdated tech that slowed more than it helped, while patients demanded transparency, speed, and digital-first billing. Amid tightening AI governance and compliance, automation and [agentic AI](https://www.flobotics.io/blog/agentic-ai-in-healthcare) became the only viable path to efficiency and ROI. With CMS introducing the WISeR Model in 2026 to drive AI-enabled prior authorizations and cut low-value services, the need for true RCM transformation has never been clearer. #### Before You Read - Agentic AI in RCM – an automation capable of executing multi-step workflows (e.g., eligibility checks, triggering appeals, and reconcile payments) using data from multiple systems via APIs. - FHIR – Fast Healthcare Interoperability Resources is the backbone of modern interoperability. It allows healthcare systems to exchange data across systems in real time – a major enabler of "no-touch" RCM workflows. - VBC (Value-Based Care) – A reimbursement model that ties provider payments to outcomes, efficiency, and patient satisfaction, not just service volume. For RCM teams, VBC requires integrated analytics, accurate coding, and automation to ensure compliance and timely reimbursement. Fig. 01 · RCM 11 trends Top RCM trends - AI in RCM - Big data and predictive analytics - Automation for staffing shortages - Interoperability between the EHR and other systems - Cybersecurity with blockchain - Automated pre-authorization and eligibility checks - Mobile-first patient financial engagement - Outsourcing for cost efficiency - Patient-centric payment options - Focus on denial management - Real-time revenue intelligence ### Top RCM Trends in U.S. Healthcare | 2026 Edition #### Agentic AI Rules! AI is no longer a side project or a test case in RCM. Analysts estimate nearly $1 trillion in U.S. administrative spend remains automatable. Deloitte's 2025 Global Health Care Outlook explicitly calls this out. Referrals, scheduling, data entry – these processes are prime targets for intelligent automation and AI. Early adopters report 3–5-point reductions in Cost-to-Collect, 30–50 percent faster cycle times, and payback periods measured in months. According to MedCity, over 90% of revenue cycle leaders are already prioritizing AI for business segments like collections, payer communication, and patient financial services. Budgets move only when automation can keep Cost-to-Collect below 3–4% of net revenue, cut denial rates, and shorten AR days. This means digital transformation is an operational necessity rather than an innovation project. Moreover, the digital workforce is already handling entire workflows that once demanded full teams. Agentic AI saves FTEs, cuts CTC, and allows the RCM team to focus on unique cases. Quantitative benchmarks are also shaping how executives evaluate automation success. The latest CAQH and AHA reports show that automating eligibility verification alone can deliver 77% savings per transaction, reducing national administrative waste from $83 billion to $65 billion. Metrics like these now serve as the financial foundation for automation ROI discussions at the board level. In practice, this means: - AI predicting denials before submission - Bots handling eligibility and pre-auth in real time - Automated claim scrubbing before clearinghouse submission - Patient-facing AI explaining balances and payment options instantly If you'd like to learn more about specific RCM automation case: [Click here to read PTCoA case study.](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) Multiple industry reports also call this trend a "hyperautomation shift". In short: Eligibility verification, claim submission, denial management, resubmission, payment posting – it's all going to be automated in the nearest future. #### Consumerization is Key Patient experience has officially moved from a "soft metric" to a core financial driver in RCM. 2025 trend reports all point in the same direction: - billing transparency, - self-service, - consumer-grade design These are now priorities for healthcare finance teams. With value-based care and NPS-style metrics gaining traction, satisfaction at financial touchpoints–clear estimates, real-time coverage checks, and fewer billing surprises–now feeds directly into contract performance, reimbursement rates, and long-term revenue growth. This shift is powered by technology. Cloud-based RCM platforms with open APIs have become the new standard, enabling real-time data exchange between payers, providers, and patients. Reports from Definitive Healthcare and HelixBeat highlight FHIR and payer API integration as key 2025 milestones–allowing instant claim visibility, faster status updates, and proactive issue resolution. Modern systems are expected to deliver automation-ready analytics and compliance by default, not as add-ons. The result? Patient financial experience is no longer a CX talking point–it's an operational KPI. Transparency, speed, and usability now define what "best-in-class RCM" means. No-touch eligibility and pre-authorization remove guesswork at the front desk, while automated, patient-friendly payment plans and reminders drive both collections and satisfaction. In short: Patients now expect billing to work like any other digital experience–fast, simple, and transparent. Providers that deliver that will win both loyalty and margin. #### Digital Workforce Delivers 2025 has made one thing clear – the labor problem isn't going away. ‍Late eligibility checks and delayed pre-authorizations remain one of the top drivers of denials and patient non-payment - which is why real-time, automated verification is becoming a baseline capability rather than a differentiator. Workforce shortages, burnout, and a stagnant labor supply continue to dominate headlines from Deloitte and the Financial Times. Across healthcare operations, automation and robotics are stepping in to take over the "busy work," giving clinical and RCM teams space to focus on tasks that actually move the needle. In revenue cycle management, the struggle remains real: denials are rising, payment cycles are slowing, and staffing gaps keep widening. That's why automation has shifted from a nice-to-have to a stabilizing force – the only lever that keeps teams operational as workloads grow. Recent case studies prove this shift is already paying off. Omega Healthcare, among others, reported 30–50% time savings across billing workflows like coding, posting, denial management, and even mailroom processing. Some organizations reclaimed over 15,000 hours per month using [AI-powered document handling](https://www.flobotics.io/blog/healthcare-document-processing) alone. In a market where patient volumes climb but hiring can't keep pace, automation is now the only scalable way to expand capacity without adding headcount. The next generation of "digital FTEs" isn't replacing people – it's protecting them from burnout while keeping operations moving at the speed the industry demands. Fig. 02 · Prior auth 5 tools Automation for pre-authorization and eligibility checks - Robotic process automationEligibility checks, patient details, submitting pre-authorization requests. - AI and machine learningPredicts denials and recommends the best approach. - Electronic data interchangeSmooth communication between providers and payers. - Natural language processingPulls details from clinical notes and insurance policies. - Cloud RCM platformsEligibility checks, prior auth tracking and payer contact in one place. Wondering what defined healthcare RCM in 2025 and where it's heading next? Here's our take on this – after all we focus solely on RCM;-) Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ### Upcoming RCM Trends | 2030 Perspective Healthcare revenue cycle management won't slow down – it will scale up. What began as isolated RPA pilots is now evolving into a connected ecosystem where EHRs, payer systems, and internal platforms communicate seamlessly through agentic workflows. The direction is clear: [end-to-end RCM automation](https://www.flobotics.io/rcm-automation). By the early 2030s, agentic AI will operate as the default RCM engine. Frameworks such as Genpact's "Gen AI as interface, Agentic AI as execution engine" will set the standard – conversational fronts, autonomous agents behind the scenes. Cost-to-Collect (CTC) and related efficiency metrics will become board-level priorities. Boards and investors will expect CTC to match best-in-class benchmarks; automation projects will be evaluated like capital investments – by NPV, IRR, and time-to-ROI. Inside RCM teams, capacity will be defined as something like: Y human FTE + Z digital FTE. Financial performance and automation maturity will become inseparable – a natural step forward. Patient financial experience and NPS will remain major competitive levers. Automation will influence payer negotiations, contract renewals, and retention, as billing experience competes equally with clinical quality for growth. Automation is also transforming patient affordability – enabling self-pay orchestration, digital statements, and personalized reminders that reduce bad debt and boost satisfaction. Governance will tighten. Every AI system touching financial or patient data must be auditable, explainable, and compliant with internal and federal regulations. Regulatory complexity – from the No Surprises Act to VBC expansion and Medicare PFS changes – is pushing automation toward API-native, rule-driven logic. ### EHR Softwares on the rise: - [Epic Systems ](https://www.epic.com/)– The most widely used EHR, known for its robust interoperability and RCM features. - [Cerner (Now Oracle Health)](https://www.oracle.com/health/) – A leading EHR with strong financial and billing integration capabilities. - [DrChrono](https://www.drchrono.com/) – A cloud-based EHR with integrated billing and practice management tools, designed for small and mid-sized practices. - [MEDITECH](https://ehr.meditech.com/meditech) – A widely adopted EHR, especially among community hospitals, with RCM-friendly features. - [eClinicalWorks](https://www.eclinicalworks.com/products-services/ehr/) – A popular choice among ambulatory care providers, offering integrated billing and claims management. - [PrognoCIS](https://prognocis.com/) – A flexible EHR solution that offers advanced billing features and telemedicine integration. - [NextGen Healthcare](https://www.nextgen.com/) – A preferred solution for specialty practices, focusing on revenue optimization and claims management. Automation maturity will also become a sales and partnership differentiator. Interoperability and visibility will define high-performing RCM ecosystems, where AI connects every point of the revenue cycle. Predictive analytics will forecast denials and optimize payer strategy, while clinical and financial data merge under value-based RCM models – linking care quality, risk, and reimbursement. That's Floboperspective on what's to come in RCM top trends. ### Summary | Which Solutions To Choose? Agentic AI, consumerization, and hyperautomation – these are the 2025 RCM trends that are here to stay for long. Payers can cut up to 35% of their operating costs using automation. Moreover providers rely on similar solutions to offset shrinking reimbursement rates and rising labor expenses. In short, the conversation shifts from whether to automate, to how deeply and how fast it can be done. And that's a good thing both for the revenue cycle management as for the patients. Which brings us to the following point: At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. [Click here to schedule a call with us >](https://www.flobotics.io/book) Written byKarl Mielnicki CTO & Co-Founder of Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RCMAIHealthcare ### RCM Statistics | 2026 Overview RCM statistics for 2026: denial rates hover near 5% and cost-to-collect keeps rising as manual processes lose ground. See the data. Jędrzej SzymulaJanuary 07, 2026 ](https://www.flobotics.io/blog/rcm-statistics-overview)[ RCMRPAAI ### AI vs. RPA vs. ML in Healthcare RCM: A Deep Dive AI vs. RPA vs. ML in healthcare RCM: how each technology improves efficiency, accuracy, and compliance, and which to adopt first. Krzysztof SzwedFebruary 22, 2025 ](https://www.flobotics.io/blog/ai-rpa-ml-rcm)[ RCMHealthcare ### RCM Automation in Healthcare | 2026 RCM automation in healthcare: how RPA, AI, and OCR cut billing errors, speed up claims, and reduce manual work in 2026 revenue cycle management. Bart TeodorczukFebruary 25, 2026 ](https://www.flobotics.io/blog/rcm-automation-healthcare) [All articles →](https://www.flobotics.io/blog) --- # Top 20 Healthcare Software Platforms in 2026 | The Execs’ Guide Canonical: https://www.flobotics.io/blog/top-20-healthcare-software-examples Author: Jędrzej Szymula Published: 2025-10-27 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Top 20 Healthcare Software Platforms in 2026 | The Execs’ Guide [AI](https://www.flobotics.io/blog?category=ai)[Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Top 20 Healthcare Software Platforms in 2026 | The Execs’ Guide [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published October 27, 2025Updated September 1, 2026 On this page - [Intro | Main Trends in U.S. Healthcare Software](#intro-main-trends-in-u-s-healthcare-software) - [Before You Read | Useful Definitions](#before-you-read-useful-definitions) - [Solutions | Top 20 Healthcare Software Platforms in 2026](#solutions-top-20-healthcare-softwares-in-2025) - [1. Epic Systems Corporation](#1-epic-systems-corporation) - [2. Athenahealth](#2-athenahealth) - [3. Meditech](#3-meditech) - [4. eClinicalWorks](#4-eclinicalworks) - [5. NextGen Healthcare](#5-nextgen-healthcare) - [6. Tebra](#6-tebra) - [7. Greenway Health](#7-greenway-health) - [8. AdvancedMD](#8-advancedmd) - [9. ModMed (Modernizing Medicine)](#9-modmed-modernizing-medicine) - [10. Praxis EMR](#10-praxis-emr) - [11. Altera Digital Health](#11-altera-digital-health) - [12. Innovaccer](#12-innovaccer) - [13. Careviso](#13-careviso) - [14. Kyruus Health](#14-kyruus-health) - [15. Phreesia](#15-phreesia) - [16. Qure4u](#16-qure4u) - [17. Merative](#17-merative) - [18. Yosi Health](#18-yosi-health) - [19. SAS Healthcare Analytics](#19-sas-healthcare-analytics) - [20. Optum Analytics](#20-optum-analytics) - [Also worth a look: Salesforce Health Cloud](#21-salesforce-health-cloud) - [Summary | Which Solutions To Choose?](#summary-which-solutions-to-choose) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Intro | Main Trends in U.S. Healthcare Software In 2026, U.S. healthcare industry stands at a pivotal inflection point. According to the [Deloitte US Center for Health Solutions’ Global Health Care Outlook](https://www.deloitte.com/us/en/insights/industry/health-care/life-sciences-and-health-care-industry-outlooks/2026-global-health-care-outlook.html), more than 70% of C-suite execs across five countries think of operational efficiency and productivity as top priorities. That sets the stage for three inter-connected trends shaping healthcare operations. First, data silos are finally breaking down. The “one system solves all” myth is gone. Today's healthcare platforms must integrate: provider workflows, payer data, patient devices, national registries. Interoperability became foundational – and that's good. The Deloitte report emphasizes that only systems capable of secure, real-time data exchange will support the efficiency, care-quality and agility required in 2026. Second, the model of care delivery is undergoing a hard shift. Care is no longer confined to the hospital or clinic; it's migrating into the home via software. Remote patient monitoring (RPM) devices, virtual visits, chronic-care apps – all are becoming embedded into daily workflows. It's a part of holistic approach to patient treatment, it helps doctors to do their job, but most importantly this shift means new billing codes, new payer models, and new operational rhythms. In turn, it opens fresh revenue-cycle pathways with a risk of growing backlog and RCM team burnout. Execs should be aware of this change. Third, artificial intelligence is finally gaining real traction in revenue-cycle management (RCM). Agentic AI platforms are capable of handling today eligibility checks, prior authorizations, and denial resolutions. They're taking over repetitive back-office workflows. The challenge now is scaling from 5-10% automation to 50%+ in organizations large and small. In short, here's our explanatory equation: 2026 in Healthcare = intelligent automation (AI) + distributed care (RPM/virtual) + connected data (interoperability). For organizations focused on RCM, the implications are profound. The vendor you pick must offer more than traditional claim-submission or EHR modules. Moreover, it must enable the end-to-end flow – from patient eligibility and pre-auth, through remote-care touchpoints, to clean claims, faster payments and real-time analytics – just like Flobotics;-) ### Before You Read | Useful Definitions Here are 3 terms we'll use throughout this post. If you're not living in healthcare tech every day, they're worth a quick skim: - TEFCA — A U.S. federal framework to promote standardized health data exchange across all providers and vendors. If a platform is TEFCA-compliant, it likely plays well with others. - ONC compliance — Refers to certification from the Office of the National Coordinator for Health IT. Indicates that a system meets federal health IT standards — especially around interoperability and patient access. - VBC (Value-Based Care) — A reimbursement model focused on patient outcomes and cost-efficiency rather than service volume. Many platforms (like Innovaccer) are designed to support this shift. - RPM (Remote Patient Monitoring) — The use of connected devices and apps to track patient vitals and health conditions outside of clinical settings. Often tied to chronic care programs and telehealth workflows. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Solutions | Top 20 Healthcare Software Platforms in 2026 ### 1. Epic Systems Corporation [Epic Systems Corporation](https://www.epic.com/) covers over 40% of the U.S. acute-care hospital market (2024 data). Used by over 350 health systems and 2,000+ hospitals. Known for stability, broad EHR+RCM integration, and regulatory alignment (e.g., TEFCA, ONC compliance). Best fit: Large hospital networks needing unified inpatient/outpatient workflows and mature interoperability. Considerations: High upfront implementation cost and long onboarding timelines. ### 2. Athenahealth [Athenahealth](https://www.athenahealth.com/) is a cloud-native platform with strong presence in outpatient and ambulatory settings. In 2024, reported client productivity gains of up to 50% in charge lag and billing cycle metrics. MIPS Quality scores for practices using athenahealth are consistently above national average (2023: 78.74 vs 74.63). Best fit: Mid-sized practices and multi-site outpatient groups prioritizing automation and quick ROI. Considerations: Limited customization options for enterprise hospitals. ### 3. Meditech [Meditech](https://ehr.meditech.com/) is a longstanding EHR vendor serving community hospitals and mid-size health systems. As of 2024, used in over 2,300 healthcare facilities. Expanse, its latest platform, emphasizes mobile-first and web-based usability. Best fit: Community hospitals seeking modern EHR functionality without full Epic-level scale. Considerations: Less depth in advanced analytics and AI tooling. ### 4. eClinicalWorks [eClinicalWorks](https://www.eclinicalworks.com/) is one of the most widely adopted outpatient EHRs, especially among independent physician groups. As of 2025, claims 180,000+ providers and over 850,000 medical professionals on the platform. Best fit: Small to mid-sized clinics needing reliable EHR + billing integration. Considerations: Past scrutiny on data interoperability and customer support. ### 5. NextGen Healthcare [NextGen Healthcare](https://www.nextgen.com/) is a company focused on specialty-driven practices. They offer tailored modules for orthopedics, behavioral health, OBGYN, and more. Publicly traded until 2023 acquisition by Thoma Bravo. Best fit: Specialty practices with unique documentation and workflow needs. Considerations: Less suitable for general-purpose hospitals. ### 6. Tebra [Tebra](https://www.tebra.com/), previously known as Kareo, is a company that targets small practices and medical billing companies. They're known for affordability, ease of use, and integrated billing. Now merged with PatientPop under the Tebra brand. Best fit: Solo and small group practices aiming for all-in-one billing + charting platform. Considerations: Limited configurability for complex use cases. ### 7. Greenway Health [Greenway Health](https://www.greenwayhealth.com/) is a practice management vendor serving 50,000+ providers. Focuses on integrated RCM and care coordination. Noted for customer support turnaround improvement in 2024. Best fit: Mid-sized practices needing end-to-end support from scheduling to collections. Considerations: Slower release cycle on new features compared to cloud-native rivals. ### 8. AdvancedMD [AdvancedMD](https://www.advancedmd.com/) is a SaaS platform offering EHR, PM, billing, and telehealth. Part of Global Payments Inc. system. Supports independent practices with multi-location tools. Best fit: Practices needing scalable support for virtual care and multi-site operations. Considerations: More business-facing than deeply clinical in interface. ### 9. ModMed (Modernizing Medicine) [ModMed (Modernizing Medicine)](https://www.modmed.com/) is a specialty-specific EHR with prebuilt templates and touch-based input. Used in dermatology, ophthalmology, and orthopedics. In 2023, ranked #1 for ambulatory specialty EHRs by Black Book. Best fit: Specialists seeking out-of-the-box content and fast charting. Considerations: Narrower applicability outside targeted specialties. ### 10. Praxis EMR [Praxis EMR](https://www.praxisemr.com/) is a template-free, AI-driven EMR focused on physician note automation. Users report improved documentation speed and accuracy. Operates outside Meaningful Use certification. Best fit: Independent physicians prioritizing documentation quality and speed. Considerations: Non-traditional interface with steep learning curve. ### 11. Altera Digital Health Altera Digital Health (prev. Allscripts) – owned currently by Harris Computer, offers Sunrise platform for hospitals and TouchWorks for large practices. Interoperability features strengthened post-acquisition. Best fit: Health systems needing modular platform options and long-term vendor stability. Considerations: Slower innovation cycle compared to cloud-native platforms. ### 12. Innovaccer [Innovaccer](https://innovaccer.com/) is a data platform used by 100+ health systems to unify clinical and claims data. Powers population health and analytics initiatives. Focused on value-based care enablement. Best fit: Organizations prioritizing data integration, care coordination, and VBC contracts. Considerations: Requires strong IT capacity to implement and maintain. ### 13. Careviso [Careviso](https://www.careviso.com/) provides real-time benefits verification, cost estimation, and prior-authorization management through its seeQer platform. Used by over 200,000 providers, it claims over 2 million prior-auths processed and 300,000+ admin hours saved annually. Best fit: Providers managing high volumes of insurance verifications, patient estimates, and prior-auth workflows. Considerations: Works as an add-on; requires integration with existing EHR/RCM stack. ### 14. Kyruus Health [Kyruus Health](https://kyruushealth.com/) is a platform for provider search, scheduling, and patient access. Deployed in large health systems like Mass General Brigham. Supports digital front door strategies. Best fit: Health systems aiming to streamline patient access and scheduling across departments. Considerations: Integrates best with large multi-specialty systems. ### 15. Phreesia [Phreesia](https://www.phreesia.com/) is a patient intake and engagement software used by over 3,000 practices. Offers digital forms, mobile check-in, and payment tools. Publicly traded under ticker PHR. Best fit: Practices looking to digitize front-desk workflows and increase collections. Considerations: ROI strongest with medium-to-high patient volumes. ### 16. Qure4u [Qure4u](https://www.qure4u.com/) is a patient engagement platform offering remote monitoring, telehealth, and care plans. Integrated with major EHRs. Focused on extending care beyond the visit. Best fit: Organizations expanding digital health and RPM initiatives. Considerations: Best results when combined with robust clinical workflows. ### 17. Merative [Merative](https://www.merative.com/) (prev. IBM Watson Health) offers clinical decision support, analytics, and imaging tools. Used in payer and provider orgs. Best fit: Enterprises requiring mature analytics and compliance-ready data tools. Considerations: Positioned more as enterprise data platform than EHR/RCM tool. ### 18. Yosi Health [Yosi Health](https://yosi.health/) is a check-in and pre-registration platform used by multi-location outpatient groups. Offers insurance verification and mobile intake. Used by CityMD and other urgent care providers. Best fit: High-volume outpatient groups prioritizing speed and throughput. Considerations: ROI depends on scale and check-in friction points. ### 19. SAS Healthcare Analytics [SAS Healthcare Analytics](https://www.sas.com/en_us/industry/health-care.html) provides predictive modeling and fraud detection tools. Used by CMS and large payers for analytics and audit functions. Best fit: Payers and health systems investing in advanced analytics or risk adjustment. Considerations: High expertise needed to build and manage models. ### 20. Optum Analytics [Optum Analytics](https://www.optum.com/) is a part of UnitedHealth Group. They offer data warehousing, performance metrics, and quality tracking. Their solution is commonly used in population health. Best fit: Large systems engaged in payer-provider collaboration or value-based contracts. Considerations: Deep ties to Optum ecosystem may limit vendor neutrality. ### Also worth a look: Salesforce Health Cloud [Salesforce Health Cloud](https://www.salesforce.com/healthcare/cloud/) is a CRM-style platform for patient engagement, care coordination, and call centers. Used in payer/provider hybrid settings. Best fit: Organizations with large call centers or care teams needing CRM + care tracking. Considerations: Not an EHR replacement; best used alongside core systems. ## Summary | Which Solutions To Choose? Software alone won't unclog your revenue streams. But the right stack—aligned with your workflows, built for your scale, and powered by agentic AI—can. If you're still relying on manual processes, you're leaking revenue. If your EHR feels like a cost center, not a growth tool, it's time to rethink. And if you're not automating denials, pre-auths, and eligibility by now… you're falling behind. If you’re still working out which kinds of software you need rather than which vendor, see our [overview of 30 types of healthcare software](https://www.flobotics.io/blog/healthcare-software). Time is revenue. Don't lose either. Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ AIHealthcareRPA ### Compliance Automation in Healthcare Healthcare compliance automation: how Continuous Control Monitoring and Agentic AI cut administrative drag by 20-30% in 2026. February 04, 2026 ](https://www.flobotics.io/blog/compliance-automation-healthcare)[ HealthcareRCMAI ### RCM Outsourcing in Healthcare | 2026 RCM outsourcing in 2026: why offshore labor arbitrage is failing, and how Agentic AI outsourcing is replacing it. Bart TeodorczukFebruary 02, 2026 ](https://www.flobotics.io/blog/rcm-outsourcing-healthcare)[ RCMAIHealthcare ### Agentic AI in Healthcare: From Hype to Real-World Impact Agentic AI in healthcare: how it differs from generative AI like ChatGPT and where it's already driving real clinical impact. Jędrzej SzymulaSeptember 22, 2025 ](https://www.flobotics.io/blog/agentic-ai-in-healthcare) [All articles →](https://www.flobotics.io/blog) --- # Fixing Denial Codes | Agentic AI in Revenue Cycle Management Canonical: https://www.flobotics.io/blog/fixing-denial-codes-rcm-automation Author: Jędrzej Szymula Published: 2025-10-11 Updated: 2026-09-08 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Fixing Denial Codes | Agentic AI in Revenue Cycle Management [AI](https://www.flobotics.io/blog?category=ai)[Denials](https://www.flobotics.io/blog?category=denials)[Eligibility](https://www.flobotics.io/blog?category=eligibility)[Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Fixing Denial Codes | Agentic AI in Revenue Cycle Management [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published October 11, 2025Updated September 8, 2026 On this page - [Before You Read | Useful Definitions](#before-you-read-useful-definitions) - [Intro | Fixing Denial Codes](#intro-fixing-denial-codes) - [Why Are Denial Codes Such a Challenge?](#why-are-denial-codes-such-a-challenge) - [Scope | The Hidden Cost of Doing Nothing](#scope-the-hidden-cost-of-doing-nothing) - [Advice | Automate Instead of Hiring](#advice-automate-instead-of-hiring) - [Examples | Fixing Denial Codes](#examples-fixing-denial-codes) - [Summary | Why AI Automation?](#summary-why-ai-automation) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ### Before You Read | Useful Definitions Denial codes are standardized alphanumeric codes used by insurance companies to explain why a reimbursement claim was rejected or denied. They act as short "reason statements" that show healthcare providers what went wrong and what needs fixing before resubmission. In short, denial codes explain why the insurer didn't pay for the provided healthcare service. Before we move forward, it's crucial to explain one thing: The higher the denial rate, the higher the cost of running healthcare services -> That's why fixing denial codes is so important in RCM field. ## Intro | Fixing Denial Codes Logging into payer portals, uploading medical records, checking claim statuses, resubmitting… Billing teams spend hours on repetitive corrections. On a larger scale, U.S. healthcare providers face: - Rising claim volumes - Stricter and constantly evolving payer requirements - Labor shortages in billing teams Recent industry data shows that [private payers are now denying 15% of all claims on the first submission](https://www.hfma.org/revenue-cycle/denials-management/navigating-the-rising-tide-of-denials/), with [ACA marketplace plans reaching a 19% in-network denial rate](https://www.hfma.org/fast-finance/aca-marketplace-plans-payment-denial/) — the highest level in nine years. (Source: HFMA, Aug 2024 & Feb 2025, citing Premier and KFF data — Tier 2) The cost to rework a single denied claim typically ranges from $25 to $180, depending on claim complexity and payer rules – most of it driven by avoidable administrative or documentation errors. According to [KFF's analysis of HealthCare.gov issuer data](https://www.kff.org/private-insurance/healthcare-gov-insurers-denied-nearly-1-in-5-in-network-claims-in-2023-but-information-about-reasons-is-limited-in-public-data/), insurers denied nearly 1 in 5 in-network claims in 2023. (Source: KFF, 2024 — Tier 2) ### Why Are Denial Codes Such a Challenge? Payers use X12 Claim Adjustment Reason Codes (CARCs) to explain payment adjustments, including denials. There are more than 300 active denial codes across U.S. payers – and their interpretations often vary slightly by insurer or region. Multiply that by hundreds (or thousands) of monthly rejections, and it's clear why denial management is one of the biggest pain points for RCM teams. This complexity makes denial management challenging in terms of both training and processing speed. Examples: - Denial Code: | Meaning: - CO 50 | Non-covered services - CO 96 | Non-covered charges - PI 252 | Missing or invalid data - N393 | Invalid modifier combination - OA 18 | Duplicate claim submission ## Scope | The Hidden Cost of Doing Nothing Let's face it: if your RCM team still handles denials manually, you're losing money every month. Even if your team resolves 95% of denials, the remaining 5% can still cost millions annually. Example of Cost Savings: - Process | Manual Work | Automation | Monthly Volume(avg.) | Hours Saved - Denial reconsiderations | 6 min | 0.5 min | 1,000 | 92 - CPT code corrections | 3 min | 0.3 min | 3,000 | 135 - Eligibility rechecks | 4 min | 0.2 min | 1,500 | 95 That's over 300 hours saved per month, or roughly 1.5–2 FTEs worth of productivity – and those are conservative estimates. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Advice | Automate Instead of Hiring Operational costs are a bitter pill most RCM teams have learned to swallow. Accepting inefficient reality isn't sustainable. Adding new people, expanding departments, to handle endless rework have long been treated as "just part of the process." But let's be real: Accepting inefficient reality isn't sustainable. We all know the formula: the higher your Cost to Collect (CTC), the lower your profitability. Every new full-time hire adds salary, benefits, onboarding, and training costs. Yet, despite all that investment, productivity doesn't always grow proportionally. This is where AI automation changes everything. According to Experian Health survey data cited by [HFMA](https://www.hfma.org/fast-finance/aca-marketplace-plans-payment-denial/), 84% of healthcare finance leaders say reducing denials is a top priority, and 45% planned to boost investment in claims-management technology within six months to address it. (Source: HFMA, Feb 2025, citing Experian Health — Tier 2) For the cost of a small implementation, one automation can do the work of multiple employees. Without fatigue, overtime pay, or human error. It runs around the clock, processes hundreds of claims a day, and maintains perfect consistency even when volumes spike. Instead of hiring more people to handle repetitive workflows, you extend the capacity of your existing team – scaling without recruiting. The ROI speaks for itself: Each digital worker amplifies human efficiency rather than replacing it, freeing staff to focus on high-value analysis, appeals, and process optimization. Simply put, [AI automation is the most scalable way to reduce CTC](https://www.flobotics.io/blog/agentic-ai-in-healthcare) – a smarter, more sustainable path to growth. #### How Does a Fully Automated Denial Management Process Works? Here is a short explanation – step by step: - Identify – Ai agent scans your EHR or billing platform (e.g., Xifin, Epic, or PrognoCIS) for newly denied claims. AI models classify denials by reason code, payer, and priority. - Retrieve – AI agents fetch supporting documentation – medical records, lab reports, or eligibility data – from internal systems or cloud storage. - Fix – If the denial matches a known pattern (e.g., CO 96 – missing documentation), the AI agent fills in the missing data automatically. - Resubmit – The AI agent logs into payer portals (UHC, BCBS, Aetna) or APIs, uploads documentation, and resubmits claims for reconsideration. - Update – Finally, it updates EHR/CRM systems with claim statuses, notes, and ticket numbers while sending real-time alerts via Slack or email. The entire cycle happens in seconds, not minutes – and 100% of the activity is logged for audit and compliance. Interested in how such automation works in real life? Here's a recording of a real world example of claims processing automation: ## Examples | Fixing Denial Codes Stil not convinced? Here's one of our case studies on AI automation: #### [PathGroup Case Study](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation): Challenge: PathGroup, one of the largest pathology providers in the U.S., faced thousands of denials and coding errors monthly. 90% of denials were due to small, fixable issues like missing data or incorrect CPT codes. Solution: We've built an automation suite that: - Identified repetitive denial codes (CO 50, PI 252) - Cross-checked each denial with internal rules - Corrected claims automatically Here's the ROI of this project: Monthly volume: ~3,000 errors/month corrected automatically Time savings: ¼ FTE/monthly #### Dart CHART Systems: Challenge: Manual reporting and data extraction were slowing operations and driving overtime. Employees spent up to 36 hours downloading hundreds of reports – time-consuming, error-prone, and costly. Solution: We've deployed UiPath automations to handle report generation and data processing. The automations completed tasks 3× faster, at one-third the cost, with full data security and zero downtime. ROI: - 66% faster processing - 500+ reports automated - 1-day implementation - 6 automations built ## Summary | Why AI Automation? AI automation offers a scalable, cost-effective alternative to traditional team expansion. Each digital worker amplifies human efficiency rather than replacing it, freeing staff to focus on high-value analysis, appeals, and process optimization. Simply put, AI automation is the most scalable way to more sustainable growth. Every automation we build is designed to deliver measurable returns – saving time, cutting costs, and improving cash flow. See how our [denials management automation](https://www.flobotics.io/agents/denials-management-automation) handles document gathering, supported corrections and payer follow-up. Ready to automate denials and boost ROI? Let's talk! [👉 Book a 30-minute call](https://www.flobotics.io/book) ## FAQ: What are the top 5 denials in medical billing? The most common causes are eligibility problems (inactive coverage, wrong plan code), missing or invalid claim data, missing or expired prior authorization, non-covered services, and missing supporting documentation. Eligibility, authorization, and non-covered-service denials tend to be the hardest to reverse, while missing data and documentation issues are usually correctable and resubmittable. What are the top 20 denial codes in medical billing? There's no single official 'top 20' ranking — the most frequent codes vary by payer, specialty, and claim type, and the full standardized code list runs into the hundreds. The codes discussed most often across the industry cluster around eligibility, authorization (CO-197), coding and documentation (CO-4, CO-252), and medical necessity (CO-50). What does CO4 mean? CO-4 means the procedure code billed is inconsistent with the modifier used, or that a required modifier is missing entirely. It's a coding-level issue, so it's typically a soft denial a coder can fix by correcting or adding the modifier and resubmitting. What does denial code CO 242 mean? CO-242 means the service wasn't provided by a network or primary care provider as the plan requires. It's a network or referral-related denial, and it tends to sit closer to a hard denial since it usually reflects a real plan-design restriction rather than a paperwork error. What is a 252 denial code? CO-252 means the payer needs an attachment or additional documentation before it will adjudicate the claim. It's one of the more automatable denial types in RCM, since the same missing-documentation request tends to repeat in a predictable, rule-based pattern. Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # The Hottest Agentic AI Examples and Use Cases in 2026 Canonical: https://www.flobotics.io/blog/hottest-agentic-ai-examples-and-use-cases Author: Jędrzej Szymula Published: 2025-10-02 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/The Hottest Agentic AI Examples and Use Cases in 2026 [AI](https://www.flobotics.io/blog?category=ai) # The Hottest Agentic AI Examples and Use Cases in 2026 [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published October 02, 2025Updated September 1, 2026 On this page - [Real-World Agentic AI Case Studies](#real-world-agentic-ai-case-studies) - [1. Healthcare RCM Automation with Agentic AI Agents](#1-healthcare-rcm-automation-with-agentic-ai-agents) - [2. Specialty Medication Prior‑Authorization Automation](#2-specialty-medication-priorauthorization-automation) - [3. ERP Modernization Through Autonomous Agents](#3-erp-modernization-through-autonomous-agents) - [4. Telecommunications Support Assistants at Scale](#4-telecommunications-support-assistants-at-scale) - [5. Legal Research & Drafting Assistant](#5-legal-research-drafting-assistant) - [6. Retail Inventory Forecasting & Restocking Automation](#6-retail-inventory-forecasting-restocking-automation) - [7. Cybersecurity Autonomous Threat Hunting & Response](#7-cybersecurity-autonomous-threat-hunting-response) - [8. Autonomous AIOps for Cloud Operations](#8-autonomous-aiops-for-cloud-operations) - [9. Insurance Claims & CRM Automation](#9-insurance-claims-crm-automation) - [10. Corporate Expense & Finance Automation](#10-corporate-expense-finance-automation) - [Conclusion: The Road Ahead for Agentic AI in Business](#conclusion-the-road-ahead-for-agentic-ai-in-business) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) The year 2025 has seen[ Agentic AI](https://www.flobotics.io/blog/agentic-ai-vs-rpa) emerge as one of the hottest tech trends in business. From Fortune 500 enterprises to agile startups, companies are experimenting with AI agents that don't just chat or predict – they. Unlike earlier AI systems that waited for commands, these autonomous agents take initiative, make decisions, and execute tasks in complex real-world workflows. The excitement is reflected in the market numbers: the global agentic AI market is projected to grow from $28 billion in 2024 to [$127 billion by 2029 (35% CAGR)](https://www.crn.com/news/ai/2025/10-hottest-agentic-ai-tools-and-agents-of-2025-so-far). [Gartner even predicts](https://www.gartner.com/en/newsroom/press-releases/2025-03-05-gartner-predicts-agentic-ai-will-autonomously-resolve-80-percent-of-common-customer-service-issues-without-human-intervention-by-20290) that by 2029, agentic AI will autonomously resolve 80% of common customer service issues, cutting operational costs by 30%. In other words, Agentic AI has moved from a futuristic concept to a business reality, promising game-changing boosts in productivity and customer experience. So, what exactly makes an AI system? Think of the difference between an AI content generator and a proactive digital employee. Traditional (like ChatGPT) is a brilliant content creator – it responds to prompts with essays, code, or designs. Agentic AI, by contrast, is about action and autonomy. It combines advanced AI reasoning with memory, tool usage, and goal-driven planning to not only generate answers but take independent initiative. As one [definition puts it,](https://akka.io/blog/agentic-ai-use-cases). In practical terms, an agentic AI might receive a high-level goal ("handle all incoming customer refund requests" or "optimize our AWS cloud costs this week") and then figure out the steps, gather data, and execute tasks across multiple systems to achieve that goal. This marks a significant leap from earlier automation, as the agentic AI now finds its way forward independently. ## Real-World Agentic AI Case Studies The real proof of agentic AI's value is in the use cases. Below, we explore the hottest agentic AI examples of 2025 across industries, showing how autonomous AI agents are transforming work for CTOs and business executives alike. ## 1. [Healthcare RCM Automation](https://www.flobotics.io/rcm-automation) with Agentic AI Agents Fig. 01 · Case Healthcare Easterseals Central Illinois: agentic AI for RCM GoalImprove cash flow and cut billing inefficiency across complex RCM workflowsSolution6 specialized AI agents for eligibility, prior auths, coding, claims, appeals and posting, coordinated across EHRs and payers 35 daysshorter average A/R 7%drop in primary denial rate <2%ABA denial rate Provider Organization , a non-profit health & disability services provider Challenge High accounts receivable (A/R) days and frequent claim denials, with billing teams spending excessive time on repetitive eligibility checks, coding, claims submission, and appeals. Manual workflow inefficiencies were causing delayed collections and distracting staff from strategic improvements. Agentic AI Implementation Thoughtful AI deployed specialized autonomous AI agents—Eva, Paula, Cody, Cam, Dan, and Phil—across RCM processes for Easterseals: - [Eligibility verification](https://www.flobotics.io/agents/eligibility-check-automation) automated by Eva - [Prior authorization](https://www.flobotics.io/agents/prior-authorization-automation) handled by Paula - Documentation coding by Cody - [Claims submission](https://www.flobotics.io/agents/claims-management-automation) via Cam - [Denials and appeals](https://www.flobotics.io/agents/denials-management-automation) managed by Dan - [Payment posting](https://www.flobotics.io/rcm-automation) done by Phil These agents work end-to-end, coordinating across EHR systems and payer portals, learning from prior denials and adapting workflows over time. #### Outcome - 35-day reduction in average A/R days - 7% reduction in primary denials - ABA (applied behavioral analysis) claim denials under 2% - Staff able to focus on process improvement rather than manual transactions—"time to focus on high-level RCM improvements" (testimony of Director of Performance Improvement) ## 2. Specialty Medication [Prior‑Authorization Automation](https://www.flobotics.io/agents/prior-authorization-automation) Provider Organization , a U.S. provider network specializing in administering infused specialty medications for chronic conditions like multiple sclerosis, oncology, and autoimmune disorders. Challenge Obtaining insurance approval for high-cost specialty drugs historically took up to 30 days, often delaying patient treatment and causing denials. The manual process involved staff contacting payers, faxing documents, and chasing re-submissions—resulting in errors, lost revenue, and delayed care. [Agentic AI Solution](https://www.flobotics.io/blog/benefits-artificial-intelligence-healthcare) A San Francisco–based startup [deployed its agentic AI agents ](https://www.wsj.com/articles/healthcare-ai-startup-mandolin-gets-vc-backing-to-the-tune-of-40-million-45f7e60e)to automate specialty medication prior-authorization: - The agent autonomously initiates insurance verification and prior auth submissions - It contacts payer systems to confirm coverage requirements - Escalates incomplete or complex cases to human staff - Learns from outcomes to improve success rates - Provides real-time case tracking dashboards for administrators #### Results OI Infusion Services cut approval times from around 30 days down to just three days, drastically reducing treatment delays and denials. AI agents reduced administrative overhead significantly, enabling staff to focus on exceptions and patient care rather than paperwork. ## 3. ERP Modernization Through Autonomous Agents Fig. 02 · Case Manufacturing Global consumer goods firm: ERP modernization GoalModernize SAP S/4HANA across global units with little disruption and fewer QA bottlenecksSolutionAutonomous testing agents that planned and ran ERP validation, prioritized risk-based tests and escalated anomalies 85%+of financial workflows run unattended 93%clean-core SAP instance 60%less business risk from test automation 10%faster ERP delivery Client A leading global consumer goods company (name confidential, delivered via Deloitte + [UiPath](https://www.uipath.com/ai/agentic-ai)) Challenge The company embarked on a major [ERP modernization initiative](https://www.uipath.com/resources/automation-case-studies/uipath-and-deloitte-revolutionizing-erp-modernization), involving a large-scale transition from legacy systems to a cloud-based SAP S/4HANA platform. The project spanned multiple regions and business units, with complex interdependencies across finance, supply chain, procurement, and compliance. Manual testing, change impact analysis, and regression validations created delays and bottlenecks—jeopardizing go-live deadlines and inflating transformation costs. Agentic AI Solution Deloitte and UiPath partnered to deploy a network of autonomous software agents leveraging[ UiPath's Test Suite](https://docs.uipath.com/test-suite/automation-cloud/latest) and automation platform. These agents were configured to: - Continuously monitor SAP change logs and business processes - Autonomously identify impacted business scenarios and test cases - Prioritize risk-based testing based on criticality and business value - Trigger test automation, validate results, and escalate anomalies—without manual oversight - Adapt testing strategies based on results and historical failures, optimizing coverage across regions and departments The result was an agentic automation framework that dynamically planned and executed testing workflows across thousands of scenarios, reducing dependency on static test plans or overworked QA teams. #### Results - Reduced manual test execution efforts by 60% - Accelerated defect identification across ERP modules - Minimized business disruption during phased ERP rollouts - Enabled faster regression cycles and reduced the risk of system downtime - Ensured global consistency in testing across multiple operating regions Gave leadership confidence in go-live timelines and quality assurance ## 4. Telecommunications Support Assistants at Scale Client [Telstra](https://www.telstra.com.au/) – Australia's largest telecom operator) Challenge Contact center agents struggled with disjointed data across systems, requiring time-consuming lookup of customer histories and product info; new agents were particularly challenged by learning the knowledge base. Agentic AI Solution Two AI agents were deployed: - One Sentence Summary: Generated concise summaries of a customer's history and context from recent interactions and transactions automatically on call. - Ask Telstra: Real-time AI assistant that retrieves answers from internal knowledge bases and presents them on demand as agents engage with customers. #### Results - 90% of users reported increased agent effectiveness; - follow-up call volume dropped by 20%; - agents resolved issues faster and more confidently, speeding up onboarding and improving CSAT. ## 5. Legal Research & Drafting Assistant Client [Allen & Overy](https://www.aoshearman.com/), aninternational law firm Challenge Allen & Overy faced mounting pressure to improve efficiency while maintaining high standards across increasingly complex legal workflows. Junior and mid-level associates were spending thousands of hours on: - Drafting legal clauses and contracts - Conducting multi-jurisdictional legal research - Summarizing and comparing case law and precedents - Reviewing NDAs, compliance forms, and transactional documents - Manually sifting through large document sets for M&A and litigation prep These tasks were repetitive, cognitively intensive, and prone to inconsistency across international teams. Agentic AI Solution Harvey ([a legal copilot agent](https://www.aoshearman.com/en/news/ao-shearman-and-harvey-to-roll-out-agentic-ai-agents-targeting-complex-legal-workflows)) was integrated firm-wide, autonomously handling: - Contract drafting (e.g., NDAs, IP clauses) based on jurisdiction and internal precedent - Clause suggestions and revisions tailored to client's position and risk - Legal research & case law summarization with citations - Comparative legal analysis for cross-border transactions - Due diligence reviews, scanning large contract sets for red flags - Compliance documentation automation Harvey doesn't just respond—it plans and executes tasks based on prompts like "Draft a UAE-compliant shareholder agreement." It uses memory, feedback loops, and firm-specific data to adapt output, significantly reducing manual effort. #### Results - Averaging ~40,000 requests per day across global teams - Cut down research and drafting time by up to 60% - Improved consistency across international contract teams - Freed up associates to focus on high-stakes advisory work, boosting client value - Enhanced scalability without linear headcount increases Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## [6. Retail Inventory](https://www.flobotics.io/blog/rpa-use-cases-retail) Forecasting & Restocking Automation Client Walmart – the largest U.S. retailer with over 4,700 physical stores and a massive e-commerce operation Challenge Walmart struggled with inventory misalignment across its sprawling store and warehouse network. Traditional forecasting systems were reactive and siloed, resulting in: - Frequent stockouts of high-demand products - Overstocking in underperforming locations - Missed e-commerce delivery windows - Excessive markdowns due to outdated replenishment logic With its strategic goal of driving 50% of sales through e-commerce by 2026, Walmart needed a smarter, more autonomous inventory engine to optimize stock placement in real time. Agentic AI Solution In 2025, [Walmart began scaling its internal "AI Super Agent"](https://aibusiness.com/agentic-ai/walmart-consolidates-ai-strategy-with-super-agents-)—an advanced agentic AI system that: - Ingests real-time POS data, supply chain inputs, web traffic, weather, and local trends - Autonomously forecasts demand per SKU per store or fulfillment center - Initiates just-in-time restocking or inter-location inventory transfers - Learns over time which product/store combinations under- or overperform - Collaborates across departments (buying, [logistics](https://www.flobotics.io/business-process-automation), and e-comm) via dynamic recommendations Unlike traditional [ML models](https://www.flobotics.io/blog/robotic-process-automation-vs-machine-learning) that require analysts to interpret results, this AI agent executes entire workflows without manual triggers: detecting signals, generating forecasts, and initiating inventory actions. #### Results - 22% increase in e-commerce sales in pilot regions by improving the availability of top-searched products - Significant reduction in out-of-stock incidents, especially for online orders - Lower operational costs by reducing unnecessary warehousing and overstock - Improved agility: stores could respond faster to regional demand surges (e.g., weather-related spikes or viral products) ## 7. Cybersecurity Autonomous Threat Hunting & Response Client State of Oklahoma (across multiple state agencies managed by the Office of Management and Enterprise Services) Challenge The State of Oklahoma faced an overwhelming flood of security alerts across its vast network infrastructure. With limited SOC staffing, the team struggled to triage thousands of incoming alerts daily—leading to alert fatigue, slow mean time to response, and increased risk of undetected malicious activity. Agentic AI Solution Darktrace [deployed its agentic AI system](https://digitaldefynd.com/IQ/agentic-ai-in-cybersecurity-case-studies/), Cyber AI Analyst™, which acts as a virtual security analyst operating autonomously. Key capabilities include: - Detection Triage: autonomously analyzes incoming alerts, determining which are real threats vs. noise - Incident Investigation: replicates human investigative reasoning—forms hypotheses, correlates anomalous events across cloud, email, identity, network, and OT systems - Agentic Workflows / Response: optionally enacts automated response actions within predefined security playbooks (e.g. network isolation, process termination), via its Agentic Response and Agentic Workflows capabilities built into the Cyber AI stack #### Results - From 3,142 alerts, Cyber AI Analyst condensed to 162 actionable incidents, and identified just 18 critical incidents - This translated into [~2,561 analyst-hours saved](https://www.darktrace.com/customers/state-of-oklahoma), effectively equivalent to adding 30 full-time SOC analysts - False positives reduced by approximately 90%, significantly lowering triage overhead - Autonomous response actions empowered off-hours protection with trust and control, allowing lean teams to "clear the table" on threats daily ## 8. Autonomous AIOps for Cloud Operations Fig. 03 · Case Manufacturing US manufacturer: autonomous AIOps GoalCut downtime and manual incident handling in multi-cloud operationsSolutionAgentic AI for alert triage, root-cause analysis and self-healing workflows 40%faster incident resolution (MTTR) 50%fewer alerts through smart grouping 30%less downtime Client Large U.S.-based manufacturing company (confidential client of IBM) Challenge The client operated a complex multi-cloud infrastructure supporting production systems. Their IT/DevOps teams suffered from: - Alert overload: thousands of noisy alerts daily, many false positives - Slow incident resolution: high Mean Time to Resolution (MTTR) due to manual triage - System instability: costly downtime and customer-impacting issues Agentic AI Solution IBM deployed its [Cloud Pak for Watson AIOps](https://medium.com/%40tahirbalarabe2/solving-incident-management-headache-with-ibm-cloud-pak-e3fcb3cda5c9) powered by goal-oriented agents—specifically, the Autonomous Threat Operations Machine (ATOM) framework and integrated incident response agents. These agents autonomously: - Ingest telemetry from logs, alerts, and performance metrics across cloud and on-prem environments - Triaging and correlating alerts, consolidating them into actionable incidents - Diagnose root causes using historic incident patterns and dependency mapping - Execute self-healing steps, such as: auto-restarting failed services or replicas; triggering rollbacks of faulty deployments; allocating additional resources during load spikes - Provide incident summaries, suggestions, and post-mortem drafts to human engineers for review These agents continuously adapt their behavior based on outcomes and evolving system patterns—freeing operations staff from routine firefighting. #### Results - 40% reduction in MTTR, enabling faster recovery from system issues - 50% decrease in alert volume, thanks to noise suppression and incident grouping - 30% reduction in downtime, improving system stability and production uptime - Significant reduction in manual toil—DevOps teams shifted from reactive responders to strategic managers - Operational cost savings and greater confidence in continuous delivery pipelines ## 9. Insurance Claims & CRM Automation Client [Zurich Insurance Group](https://www.zurich.com/), a global insurer serving over 55 million policyholders Challenge Support agents were experiencing slow and inconsistent customer service due to siloed systems, lengthy paperwork, and difficulties in quickly accessing customer policy and claim data. Improving agent effectiveness and reducing service times were top priorities. Agentic AI Solution Zurich's internal tech subsidiary ZCAM built a next-gen CRM platform powered by [embedded agentic AI](https://www.businessinsider.com/zurich-insurance-ai-customer-relationship-management-crm-system-helps-agents-2025-5). This platform: - Automatically aggregates policyholder data and claim history into a unified customer summary - Uses AI agents to proactively suggest product recommendations tailored to the customer's profile - Enables service agents to complete tasks following a "three‑click rule" for speed and consistency - Remotely surfaces scripting and response suggestions in real time #### Results - Reduced service completion times by over 70% - Increased agent productivity and reduced dropped calls - Enhanced customer experience and satisfaction with more personalized advice - Empowered agents to serve as consultative advisors rather than data look‑ups ## 10. Corporate Expense & Finance Automation Client [Ramp](https://ramp.com/), NY-based fintech and corporate finance platform used by over 40,000 businesses, including [Quora](https://www.quora.com/). Challenge Corporate finance teams were overwhelmed by manual expense audits, policy compliance reviews, and delays in invoice processing. Inefficiency in handling repetitive finance tasks strained productivity. Agentic AI Solution In July 2025, Ramp [launched its AI finance agent](https://ramp.com/blog/ramp-raised-500m-to-build-the-future-of-finance), integrated within their spend management and corporate card platform. The agentic AI: - Reads company policy documents and audits expenses autonomously, flagging violations automatically - Generates reimbursement approvals and sends notifications without manual review - Coordinates with procurement systems to preemptively verify vendor compliance - Learns from each decision, refining checks over time to reduce false alarms #### Results - Thousands of businesses adopted the agents within weeks - Significant reduction in manual audit hours for finance teams - Improved compliance scoring and faster reimbursements - Ramp raised a $500M funding round in part due to rapid agent adoption and evidence of productivity gains ## Conclusion: The Road Ahead for Agentic AI in Business From automating healthcare revenue cycles and legal drafting, to managing inventory for global retailers and mitigating cybersecurity threats, agentic AI is no longer confined to labs or pilots. As these real-world case studies show, AI agents are already delivering measurable[ impact across industries](https://www.flobotics.io/blog/rpa-use-cases-across-industries), executing complex workflows with autonomy, precision, and adaptability. The takeaway? Agentic AI is industry-agnostic and process-rich. Whether you're in banking, insurance, logistics, public service, or enterprise IT, there are high-value, repeatable tasks waiting to be handed off to intelligent agents. These systems don't just save time; they enhance human focus, improve decision-making, and unlock strategic capacity. At [Flobotics](https://www.flobotics.io/), we help businesses like yours turn agentic AI into a real operational advantage. From healthcare to finance to B2B automation, our team delivers tailored, production-ready AI agent solutions that go beyond simple chatbots or scripts. Ready to explore what Agentic AI could do for your workflows? At Flobotics we specialize in agentic AI automation – no generic bots here. Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ AI ### Agentic AI Workflows Agentic AI workflows, explained: how autonomous AI agents handle multi-step RCM tasks beyond traditional rule-based RPA. February 04, 2026 ](https://www.flobotics.io/blog/agentic-ai-workflows)[ RPAAI ### Agentic AI Frameworks | 2026 Agentic AI frameworks in 2026: which stacks Google and other leaders are betting on, explained with clear, research-backed answers. Jędrzej SzymulaDecember 02, 2025 ](https://www.flobotics.io/blog/agentic-ai-frameworks)[ RPAAI ### What Is Agentic AI? | The Not-So-Obvious Guide What is agentic AI? A clear guide to how autonomous AI agents reason, act, and differ from traditional rule-based automation. Jędrzej SzymulaDecember 09, 2025 ](https://www.flobotics.io/blog/agentic-ai) [All articles →](https://www.flobotics.io/blog) --- # Agentic AI in Healthcare: From Hype to Real-World Impact Canonical: https://www.flobotics.io/blog/agentic-ai-in-healthcare Author: Jędrzej Szymula Published: 2025-09-22 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Agentic AI in Healthcare: From Hype to Real-World Impact [AI](https://www.flobotics.io/blog?category=ai)[Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Agentic AI in Healthcare: From Hype to Real-World Impact [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published September 22, 2025Updated September 1, 2026 On this page - [How Agentic AI Works (vs. Traditional/ Generative AI )](#how-agentic-ai-works-vs-traditional-generative-ai) - [Why Agentic AI in Healthcare Is Gaining Traction?](#why-agentic-ai-in-healthcare-is-gaining-traction) - [How Agentic AI Transforms Healthcare – Use Cases](#how-agentic-ai-transforms-healthcare-use-cases) - [Revenue Cycle Management (RCM) : Automating the Full Payment Lifecycle](#revenue-cycle-management-rcm-automating-the-full-payment-lifecycle) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) From generative AI tools like ChatGPT to predictive algorithms powering diagnostics, AI is no stranger to healthcare. But a new wave of intelligence is arriving – Agentic AI and it's doing more than just analyzing data or suggesting answers. It's acting on behalf of humans, autonomously managing tasks, adapting to changing conditions, and even initiating multi-step processes with little to no human intervention. In short, Agentic AI in healthcare is not just a concept. It's already reshaping the way hospitals handle claims, patients book appointments, and health systems scale their operations. This article breaks down what Agentic AI means, how it differs from other types of automation, where it's driving tangible ROI (especially in [Revenue Cycle Management](https://www.flobotics.io/rcm-automation)), and what's coming next as major players like UiPath, Thoughtful AI, and Hyro double down on Agentic capabilities. ## How Agentic AI Works (vs. Traditional/[Generative AI](https://www.flobotics.io/blog/genai-in-healthcare)) Traditional automation, such as RPA, follows predefined rules. Generative AI, such as GPT-based models, generates content and provides answers in response to user prompts. But neither makes decisions nor takes action on its own. That's where Agentic AI comes in. An Agentic AI system doesn't just wait for instructions -it takes a goal, decides what steps to follow, and executes them. It can adjust its strategy, access external systems, and even enlist the help of other agents to complete the task. This kind of AI behaves more like a tireless virtual teammate than a passive tool. In healthcare, this means agents can: - Log in to payer portals to verify insurance - File [prior authorizations](https://www.flobotics.io/agents/prior-authorization-automation) or refile denials - [Manage billing workflows](https://www.flobotics.io/agents/claims-management-automation) end-to-end - Schedule appointments based on patient preferences - Monitor hospital beds and medication inventory, and take appropriate action. It's autonomy with accountability – most systems still operate within set guardrails, but the speed, resilience, and contextual awareness go far beyond what legacy bots or scripts can do. Unlike traditional AI, which offers insights or predictions, Agentic AI behaves more like an independent problem solver. It can make decisions, execute multi-step tasks, and adapt based on feedback – all without needing a person to micromanage each step. In other words, an Agentic AI in healthcare is like an intelligent assistant that prioritizes actions and handles tasks (e.g., scheduling follow-ups or coordinating care) much as a diligent human staffer would, but at digital speed. To clarify the jargon, it helps to contrast Agentic AI with other AI types: Fig. 01 · AI in healthcare 3 types Types of AI in healthcare | Predictive AI | Generative AI | Agentic AI | What it does | Forecasts events | Creates content | Takes action | Healthcare example | Predicting hospital readmission risk | Drafting discharge summaries | Verifies insurance, schedules follow-ups and updates the EHR | Limitation | No action; insight only | Needs human follow-up | Autonomy with guardrails | - analyzes data to forecast events ("What might happen?"). - [ (think ChatGPT)](https://www.flobotics.io/blog/chatgpt-for-healthcare) creates new content or suggestions in response to prompts, but it remains reactive, waiting for human instructions. , by contrast, acts proactively. It leverages techniques such as Large Language Models (LLMs), [Machine Learning](https://www.flobotics.io/blog/robotic-process-automation-vs-machine-learning), and automation to carry out tasks and achieve goals with minimal supervision. In short, generative AI creates, while Agentic AI acts. This means that Agentic AI might not wait for a specific prompt every time; once given an objective, it can figure out the steps and execute them, adjusting as conditions change. ### Why Agentic AI in Healthcare Is Gaining Traction? Several converging trends explain why now is the time for Agentic AI in healthcare. First, the industry is grappling with unprecedented administrative burdens and workforce challenges. Healthcare providers spend a considerable amount of time and money on paperwork, billing, and coordination tasks that don't directly improve patient outcomes. In the U.S. alone, an estimated [$60 billion](https://medcitynews.com/2023/02/healthcare-spent-18b-more-on-administrative-tasks-in-2022-than-year-prior/) was spent on administrative tasks in 2022 – a jump of $18 billion from the prior year. These tasks (like insurance eligibility checks, prior authorizations, claims processing, etc.) are necessary but labor-intensive. They also contribute to high error rates – [claim denial rates can reach up to 20%,](https://www.jorie.ai/post/why-automate-eligibility-checks-in-healthcare-rcm) resulting in billions of dollars in lost revenue. The situation has been worsened by staff shortages and burnout, which drive up costs and slow down operations. Agentic AI in healthcare directly addresses these pain points by automating high-volume, routine processes in a more intelligent manner than earlier technologies. Crucially, Agentic AI arrives at a time when AI technology itself has matured. The boom in generative AI has familiarized healthcare leaders with AI's potential (everyone saw what GPT-style models could do with text, images, and even medical knowledge). Agentic AI builds on that foundation: it uses advanced AI models under the hood, but ties them to actionable automation. For instance, a generative AI might draft a response to a patient query; the AI agent will that response, schedule a follow-up appointment based on the content, update the patient's record, and alert the care team if needed – all autonomously. Early examples of Agentic AI, such as autonomous chat assistants and scheduling bots, have demonstrated productivity boosts by automating end-to-end routine tasks. With Machine Learning and NLP now more reliable, and APIs enabling integration with hospital systems, the feasibility of deploying Agentic AI at scale is significantly higher in 2025 than it was even a couple of years ago. Finally, the economic pressure on healthcare systems can't be ignored. Automation is viewed as a key strategy for achieving more with less. Executives (CTOs, CFOs, etc.) are eyeing Agentic AI as a way to the workforce – essentially a digital labor force that can work 24/7, eliminate backlog, and reduce errors. A McKinsey analysis famously estimated that about 45% of work activities could be automated with current technology. Healthcare, with its mix of data-heavy and rules-based tasks, is ripe for this. In a nutshell, Agentic AI in healthcare provides timely relief, addressing cost and efficiency challenges while leveraging recent AI advancements. It aligns with the urgent need to improve operational resilience in an industry that's both highly complex and highly regulated. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## How Agentic AI Transforms Healthcare – Use Cases ### [Revenue Cycle Management (RCM)](https://www.flobotics.io/blog/revenue-cycle-management): Automating the Full Payment Lifecycle Agentic AI is redefining how providers manage the most critical operational function: getting paid. It automates nearly every component of the revenue cycle, including: - [Eligibility verification](https://www.flobotics.io/agents/eligibility-check-automation) - [Prior authorizations](https://www.flobotics.io/agents/prior-authorization-automation) - [Claims submission and tracking](https://www.flobotics.io/agents/claims-management-automation) - [Denial management](https://www.flobotics.io/agents/denials-management-automation) - [Payment posting and reconciliation](https://www.flobotics.io/rcm-automation) Unlike traditional bots, Agentic AI understands workflow context, learns payer rules, and can autonomously correct and refile claims, leading to faster reimbursements, fewer denials, and leaner staffing. #### Case Study – Flobotics for Claims Automation A U.S. clinic partnered with Flobotics to automate claims processing end-to-end. #### Results: - 449% ROI within months - Claims processed 10× faster - The rejection rate decreased significantly. Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RCMRPAAI ### AI vs. RPA vs. ML in Healthcare RCM: A Deep Dive AI vs. RPA vs. ML in healthcare RCM: how each technology improves efficiency, accuracy, and compliance, and which to adopt first. Krzysztof SzwedFebruary 22, 2025 ](https://www.flobotics.io/blog/ai-rpa-ml-rcm)[ Healthcare ### Top 30 Software Solutions for Healthcare in 2026 Healthcare software solutions: explore 30 essential tools for 2026, organized by function, to strengthen clinical care and streamline admin tasks. Yana PokoraDecember 23, 2024 ](https://www.flobotics.io/blog/healthcare-software)[ RCMHealthcare ### RCM Automation in Healthcare | 2026 RCM automation in healthcare: how RPA, AI, and OCR cut billing errors, speed up claims, and reduce manual work in 2026 revenue cycle management. Bart TeodorczukFebruary 25, 2026 ](https://www.flobotics.io/blog/rcm-automation-healthcare) [All articles →](https://www.flobotics.io/blog) --- # Agentic AI Tools and Platforms Overview 2026 Canonical: https://www.flobotics.io/blog/agentic-ai-tools-platforms-overview Author: Jędrzej Szymula Published: 2025-09-16 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Agentic AI Tools and Platforms Overview 2026 [AI](https://www.flobotics.io/blog?category=ai)[RPA](https://www.flobotics.io/blog?category=rpa) # Agentic AI Tools and Platforms Overview 2026 [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published September 16, 2025Updated September 1, 2026 On this page - [Understanding Agentic AI Tools](#understanding-agentic-ai-tools) - [Agentic AI Tools for Developers and Innovators](#agentic-ai-tools-for-developers-and-innovators) - [Agentic AI vs Generative AI – Key Differences](#agentic-ai-vs-generative-ai-key-differences) - [Agentic AI Platforms for Enterprises](#agentic-ai-platforms-for-enterprises) - [Big Tech Offerings: AWS, Google, Microsoft, IBM](#big-tech-offerings-aws-google-microsoft-ibm) - [AI Agents in Business Software: Salesforce, ServiceNow, Databricks, and More](#ai-agents-in-business-software-salesforce-servicenow-databricks-and-more) - [Benefits and Outlook for Agentic AI Tools](#benefits-and-outlook-for-agentic-ai-tools) - [Unprecedented Automation](#unprecedented-automation) - [Speed and Productivity](#speed-and-productivity) - [Cross-System Orchestration](#cross-system-orchestration) - [Adaptability and Learning](#adaptability-and-learning) - [Strategic Insights](#strategic-insights) - [Conclusion](#conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) In 2025, agentic AI tools have surged to the forefront of enterprise technology. These next-generation AI systems go beyond static chatbots or simple automations – they can [autonomously plan, execute, and adapt tasks](https://www.lasso.security/blog/top-13-agentic-ai-tools-in-2025-and-their-key-features) across complex workflows with minimal human intervention. For CTOs and business leaders, agentic AI represents a strategic shift: instead of assisting humans with information (as traditional AI copilots did), these agents take initiative and act on behalf of users to drive outcomes. Industry analysts have even pegged [ as one of the top strategic tech trends](https://www.ibm.com/think/ai-agents) of 2025, forecasting explosive growth. The global agentic AI market is projected to soar from $28 billion in 2024 to [$127 billion by 2029](https://www.crn.com/news/ai/2025/10-hottest-agentic-ai-tools-and-agents-of-2025-so-far), a 35% CAGR. By that time, [Gartner predicts](https://www.crn.com/news/ai/2025/10-hottest-agentic-ai-tools-and-agents-of-2025-so-far) AI agents will autonomously resolve 80% of common customer service issues, slashing operational costs by 30%. Such figures underscore why agentic AI tools are generating so much buzz in boardrooms and IT strategy sessions. ## Understanding Agentic AI Tools Agentic AI tools can be thought of as "digital employees" that understand high-level goals and carry them out through multi-step processes. An agentic AI (or AI agent) is essentially an AI system capable of autonomously performing tasks on behalf of a user or system by designing its own workflow and utilizing available tools. This means the AI not only chats or generates content – it can: logging into software, calling APIs, updating databases, controlling web browsers, or even orchestrating other AI models in order to fulfill a task. Crucially, agentic AI is distinguished from earlier-generation copilot assistants. Traditional AI copilots (like coding assistants or writing suggestions) were mostly reactive – they responded to prompts and helped with a narrow task. By contrast, an agentic AI tool proactively plans and orchestrates tasks across multiple applications without waiting for step-by-step instructions. For example, an agent might receive a goal like "update our inventory and notify sales of low stock," then proceed to fetch data from an ERP, cross-check it with recent sales trends, update a database, and send notifications via email – all without a human explicitly guiding each step. This autonomy is enabled by advances in several areas: - Powerful LLMs with reasoning ability: Modern Large Language Models (e.g. [GPT-4](https://www.flobotics.io/blog/chatgpt-for-healthcare), [Claude](https://www.googleadservices.com/pagead/aclk?sa=L&ai=DChsSEwiyqNrrlumOAxXDmYMHHR9aDY4YACICCAEQABoCZWY&co=1&ase=2&gclid=CjwKCAjwy7HEBhBJEiwA5hQNov1PKQSZZQyKZY93WBAX5oEQHUJcR6pzmCtka8HjQb1jqO6ELgk7WRoC6IUQAvD_BwE&ei=v3iMaPOtE6eOxc8P5YmHyAE&ohost=www.google.com&cid=CAESeuD2iL85CkgF6Pu5tMUR4CQFAq73GxTvM4kzYnT_gsbbNg2bKa-2FFIHH92Tm1Fst_WYC419i3UjFV3IfP1cIK9rrlb7_544whNaitVhtOB4EBwfgiOUNR7xZCMYuZro58vcnNdSpcOgWpOXh5o_3GujKzpJvCftnM9F&category=acrcp_v1_40&sig=AOD64_1qq2Rs1OZWeAgdQZDSVzeyhd8Xog&q&sqi=2&nis=4&adurl&ved=2ahUKEwizidXrlumOAxUnR_EDHeXEARkQ0Qx6BAgUEAE)) can perform chain-of-thought reasoning and tool usage, which agents leverage to decide on actions. - Tool integrations and APIs: Agentic platforms connect AI to software tools, databases, RPA bots, and web browsers. This allows agents to execute commands in the digital world (from clicking buttons to calling cloud services). - Memory and context: With long context windows and memory modules, agents maintain context across steps and sessions, learning from prior interactions to improve decisions. - Multi-agent collaboration: New frameworks allow multiple AI agents to specialize and collaborate on tasks, delegating subtasks among themselves. This mimics human teams and enables tackling complex, multi-faceted problems. In short, agentic AI tools combine the intelligence of advanced AI models with the agency to act in software environments. They can assess context, make decisions, and continuously adjust based on feedback – a game-changer for many business processes. As one [Gartner analyst](https://www.crn.com/news/ai/2025/10-hottest-agentic-ai-tools-and-agents-of-2025-so-far) put it, ### Agentic AI Tools for Developers and Innovators A number of Agentic AI tools have emerged aimed at developers, tech teams, and AI enthusiasts. These provide the building blocks to experiment with or build your AI agents: #### [LangChain](https://aws.amazon.com/what-is/langchain/) – Arguably the most popular developer framework in this space, LangChain allows you to chain together prompts, models, and tools to create sophisticated AI workflows. Developers can define an agent's "thought process" (using techniques like ReAct prompting) and equip it with tools – for example, hooking in a [Python](https://www.flobotics.io/rcm-automation) interpreter, web search API, or database connector. LangChain's modular design and support for multiple LLM providers made it a staple for anyone prototyping agentic AI applications in 2023-2025. It's been used to build everything from customer service bots with retrieval augmentation to AI that writes and debugs code. #### [Microsoft Autogen](https://microsoft.github.io/autogen/stable//index.html) – Announced via [Microsoft's Azure AI group](https://azure.microsoft.com/en-us/solutions/ai), Autogen is designed for scenarios where multiple AI agents collaborate to solve a problem. It provides libraries to create agents with different roles that can converse with each other (or with humans), coordinate on tasks, and even spawn new specialized agents as needed. Built for Azure, Autogen integrates with Microsoft's cloud services and offers enterprise-grade deployment for complex agentic systems. For example, a company could use Autogen to develop an IT support agent that, when faced with a complex request, delegates subtasks to a database query agent, a knowledge-base agent, and a diagnostics agent, then aggregates the results. #### [Semantic Kernel (Microsoft)](https://learn.microsoft.com/en-us/semantic-kernel/overview/) – The Semantic Kernel is an open-source SDK that helps developers integrate AI into existing applications with memory, skills (functions), and planning capabilities. It's not an "agent platform" per se, but it enables creating agentic behaviors within apps. For instance, a customer support portal might use Semantic Kernel to let an AI agent understand a user's request in context, pull relevant info via connectors, and take action like creating a support ticket. #### [CrewAI](https://www.crewai.com/) – CrewAI is a newer open-source project focused on multi-agent collaboration, allowing developers to spin up teams of agents that communicate and divide tasks. It emphasizes role-based agents (each agent given specific expertise or authority) and coordinated planning. Think of CrewAI as a toolkit to create an "AI crew" working together – useful for simulations, complex decision-making (like logistical planning with multiple constraints), or any case where one agent might not be enough. #### [AutoGPT and Open Interpreter ](https://autogpt.net/chatgpts-code-interpreter-a-game-changer-in-data-analysis/)– These started as experimental projects but remain popular among developers exploring what cutting-edge agentic AI can do. AutoGPT is an open-source Python application that, given a goal, will generate its sub-tasks and attempt to execute them in a loop – chaining GPT calls to plan and reflect, using tools like web search or file I/O to make progress. It demonstrated that an LLM could and iterate towards a goal with minimal user input. Open Interpreter provides an AI with direct control of your computer (in a safe sandbox), enabling it to run shell commands, read/write files, or use software as instructed via natural language. Developers have used it to automate local tasks, such as data cleaning or software configuration, using AI instructions. While these are more playground than production, they've greatly influenced the design of more robust agentic platforms. #### [Nvidia NeMo Agent](https://developer.nvidia.com/nemo-agent-toolkit) – Early examples of Agentic AI are emerging all around us. Autonomous vehicles are a form of Agentic AI – they perceive the environment and make driving decisions continuously without a human telling them each move. Advanced virtual assistants and [RPA bots](https://www.flobotics.io/blog/robotic-process-automation) with AI capabilities are another example; they can perform sequences of actions, such as scheduling meetings, sending reminders, or extracting and moving data between systems independently. In the enterprise, an Agentic AI might coordinate a complex process such as [invoice processing](https://www.flobotics.io/business-process-automation): receiving an email with an invoice, interpreting it, updating the accounting system, flagging any discrepancies, and issuing payment – all automatically. [IBM](https://www.ibm.com/think/topics/agentic-ai-vs-generative-ai) describes Agentic AI as combining the flexible reasoning of LLMs with the strict accuracy of traditional software to pursue complex goals with minimal supervision. Because Agentic AI is proactive, it changes how we interact with AI. Instead of a user constantly prompting the AI for the next step, an Agentic AI can carry on a workflow "in the background." Of course, this autonomy means businesses must implement proper oversight, constraints, and fail-safes. A poorly directed Agentic AI could stray off course or make decisions that require human review. For now, many Agentic AI deployments remain in, as organizations learn how to trust these autonomous agents in real-world scenarios. However, the potential is enormous – from handling routine customer service issues end-to-end to managing supply chain adjustments in real-time, to monitoring systems and resolving problems before anyone is even aware. Agentic AI systems essentially act as intelligent coordinators or operators, not just advisors. ## Agentic AI vs Generative AI – Key Differences Nvidia's NeMo toolkit for agents doesn't create agents from scratch; instead, it helps developers and researchers optimize and scale agentic systems. It provides profiling to reveal bottlenecks (like slow tool calls or model latencies) and tools to parallelize or cache operations in agent workflows. As companies deploy more AI agents, such performance engineering becomes vital – ensuring your AI workforce runs efficiently on GPUs/CPUs and stays cost-effective. Many other libraries and open projects exist (such as [LangGraph](https://www.langchain.com/langgraph) for graph-based task planning, and specialized agents for browsers like Cognosys or [DIA](https://www.diabrowser.com/) that automate web actions). The key takeaway is that developers in 2025 have a rich ecosystem of Agentic AI tools to explore and utilize. Whether using [Python](https://www.flobotics.io/blog/automation-python) or low-code interfaces, one can assemble an AI agent that connects to the digital world relatively quickly. This has led to a wave of innovation and also a need for best practices (as the line between powerful autonomy and chaotic unpredictability can be thin!). Next, we'll look at how major tech players and enterprise platforms are bringing agentic AI to businesses at scale. Fig. 01 · Agentic AI tools 4 building blocks What agentic AI tools are made of - LLMs that can reasonLarge language models (such as GPT-4 or Claude) reason step by step and use tools, which agents rely on to decide what to do. - Tool integrations and APIsAgentic platforms connect AI to software, databases, RPA bots and web browsers, so agents can act in real systems, from clicking buttons to calling cloud services. - Memory and contextLong context windows and memory modules let agents keep context across steps and sessions and learn from earlier interactions. - Multi-agent collaborationSeveral AI agents specialize and hand subtasks to each other, much like a human team, to solve complex problems. In simple terms, Agentic AI "acts," while Generative AI "creates." Generative AI might write the report, whereas Agentic AI will file the report, send it to the relevant parties, and initiate the next steps based on the report's findings. Generative AI is like a talented content producer or brainstormer at your disposal, and Agentic AI is like a smart, autonomous executive assistant that can handle tasks on your behalf. It's also worth noting that Agentic AI is relatively new to the scene. Many Generative AI applications are already mainstream (dozens of AI writing assistants, image generators, coding copilots, etc., in daily use), whereas Agentic AI applications are just starting to emerge beyond RPA. Tech companies are now racing to embed Agentic capabilities into their platforms. UiPath, a leading automation vendor, [released an ](https://www.uipath.com/ai/agentic-ai) update to its automation platform in 2025, reflecting the growing importance of the fusion of AI and action in the RPA world. In short, Generative AI vs Agentic AI is not about which is better – each has distinctive capabilities. The real power lies in their combined use. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Agentic AI Platforms for Enterprises While developers experiment in sandboxes, industry giants and startups alike have rolled out Agentic AI platforms tailored for real business use. Enterprises are embracing these to automate processes in IT, customer service, data analytics, and more. Here are some of the leading Agentic AI tools and platforms making waves in business: ### Big Tech Offerings: AWS, Google, Microsoft, IBM #### AWS – Strands Agents [Amazon Web Services introduced ](https://aws.amazon.com/blogs/opensource/introducing-strands-agents-an-open-source-ai-agents-sdk/), an open-source SDK to simplify building AI agents on AWS infrastructure. Strands takes a model-driven approach – developers merely provide a prompt describing the agent's task and a list of tools it can use, and Strands handles planning and tool usage under the hood. It leverages advanced reasoning in models to let them chain thoughts, call tools, and even self-reflect to improve plans. The idea is to lower the barrier so that even with a few lines of code, one can spin up an agent that's integrated with AWS services. For enterprises already in the AWS ecosystem, Strands offers a quick path to incorporate agentic workflows (from customer support bots that dig into databases, to DevOps agents that monitor and remediate systems). #### Google Cloud – Conversational Agents Console Google has enhanced its Contact Center AI and Dialogflow offerings with a unified. This platform lets businesses build AI agents with realistic conversational abilities – including lifelike text-to-speech voices and even emotion detection for adaptive responses. Under the hood, it uses Google's latest Gemini models for language and incorporates both generative AI and rules-based controls. An agent built here might handle a customer phone call or chat entirely: understanding the request, querying backend systems (via integrators), and responding in a natural, human-like voice. Google emphasizes evaluation and observability too – the console includes tools to benchmark agent performance and monitor quality at scale. This focus on reliable conversations is critical for industries like [finance](https://www.flobotics.io/business-process-automation) or healthcare, where an AI agent might be the first line of interaction with customers. #### Microsoft – Copilot and beyond Microsoft has been aggressive in the agentic AI space, expanding its "Copilot" brand from assistive AI to more autonomous capabilities. One notable initiative is Microsoft Copilot Studio, a low-code environment to design and deploy custom AI agents within the Microsoft 365 and Power Platform ecosystem. With Copilot Studio, even non-developers can configure an agent to, say, coordinate meeting scheduling across Outlook, update SharePoint files, notify teams on Teams – essentially automating those cross-app chores in the Microsoft stack with identity and governance handled via Entra ID. On the software development side, GitHub (owned by Microsoft) launched a [Copilot Coding Agent ](https://docs.github.com/copilot/concepts/about-copilot-coding-agent)in 2025 that acts as an AI DevOps helper. Integrated in GitHub and VS Code, this agent can autonomously refactor code, write tests, and generate pull requests for review. It works asynchronously in the background, making improvements to codebases and submitting drafts that engineers can approve. Microsoft's approach thus spans from business users orchestrating workflow agents in Office to developers getting AI-assisted coding via GitHub – all underpinned by the latest OpenAI GPT models and Azure AI services. #### IBM – Watsonx Orchestrate and AskAI IBM's focus is on enterprise-grade agents that align with business processes and compliance needs. [Watsonx Orchestrate](https://www.ibm.com/products/watsonx-orchestrate) (formerly just Watson Orchestrate) is IBM's agentic platform that comes with pre-built skills for common business domains like HR, finance, or procurement. It uses IBM's LLMs to understand natural language requests (e.g., "Find and onboard a new vendor"). Then it executes the multi-step workflow: perhaps pulling up vendor records, emailing forms, getting approvals, and updating a procurement system. A key advantage is the integration with IBM's governance tools (Watsonx.governance), ensuring data privacy, compliance, and audit trails, which are crucial for regulated industries. IBM also rolled out[ AskIAM](https://newsroom.ibm.com/blog-askiam-ibms-new-agentic-ai-for-identity-and-access-management), a specialized agent for Identity and Access Management tasks, such as handling user access requests and compliance audits. Built on Watsonx Assistant, AskIAM demonstrates how agentic AI can tackle niche but critical internal tasks – it can interact with IAM systems to automate access provisioning, flag security anomalies, and answer employees' access-related queries. IBM is thus packaging agentic AI to solve specific enterprise pain points with the necessary trust and verification layers in place. ### AI Agents in Business Software: Salesforce, ServiceNow, Databricks, and More Beyond the cloud giants, many enterprise software firms have infused agentic AI capabilities into their platforms: #### [UiPath – Agentic AI Agents](https://www.uipath.com/ai/agentic-ai) Long known for leading the RPA revolution, [UiPath](https://www.flobotics.io/blog/uipath-orchestrator-new-features) has evolved into a key player in agentic AI by embedding autonomous capabilities directly into its Business Automation Platform. Unlike traditional bots that require precise, pre-coded scripts, UiPath's new Agentic AI layer introduces agents that can interpret intent, work with unstructured data, and coordinate across systems using both UI automation and APIs. These agents don't just click through workflows—they reason, adapt, and self-correct. A UiPath agent, for example, might extract data from a document, interpret exceptions, decide whether to escalate or retry, and complete a task without explicit human input. Using UiPath Studio, enterprise teams can design these agents through a mix of visual workflows, integrated AI skills, and connectors to business apps. They can also loop in traditional bots for lower-level execution, creating hybrid pipelines where bots and agents collaborate. Critically, UiPath maintains the enterprise-grade backbone it's known for: auditability, governance, role-based access, and observability. This makes it ideal for organizations looking to bring autonomy into compliance-heavy workflows like finance, HR, and operations—without losing control. UiPath's approach is especially appealing for enterprises already deep into automation; instead of ripping and replacing, they can upgrade static bots into intelligent agents, blending the best of RPA with the adaptability of agentic AI. #### Salesforce – Agentforce Salesforce's AI push went from predictive analytics to generative AI, and now to agentic AI. In 2025 [Salesforce introduced Agentforce 3](https://www.salesforce.com/agentforce/), an upgrade to its platform that enables customers to deploy AI agents for CRM and business operations. A highlight is the Atlas architecture in Agentforce 3, which improved the reasoning, speed, and trustworthiness of agents for enterprise use. Salesforce built in over 100 prebuilt "actions" (like updating a contact, creating an opportunity, sending an email) which agents can use out-of-the-box, all while obeying CRM access controls. They've also embraced open interoperability with support for the [Model Context Protocol (MCP)](https://modelcontextprotocol.io/), an emerging standard that allows different agent systems and tools to communicate. With a new Agent Command Center, companies get a view to manage all AI agents – monitoring their performance, ensuring compliance, and sharing resources. Salesforce touts this as bringing order to the potential "chaos" of having myriad AI agents by providing central governance. For enterprises deeply invested in Salesforce for sales, support, and marketing, Agentforce promises to let them automate those workflows with intelligent agents natively within their ecosystem. #### [ServiceNow – AI Agent Orchestrator](https://www.servicenow.com/company/media/press-room/ai-agents-studio.html) ServiceNow, known for digital workflows and IT service management, launched an AI Agent Orchestrator on its platform. It acts as a coordinator for teams of specialized AI agents across various departments, including IT, HR, and customer service, ensuring they work in concert toward larger business goals. Out-of-the-box, ServiceNow provides thousands of pre-built mini agents (for tasks like password resets, ticket routing, employee onboarding steps) which enterprises can plug into their processes. The orchestrator enables agents to hand off tasks among themselves and provides management with a unified dashboard to oversee all agent activity. ServiceNow's vision is essentially an AI-powered digital workforce supervised through one pane of glass – as one exec described, when possibly millions of AI agents enter your business. Given ServiceNow's footprint in IT operations, this agentic addition helps companies automate routine service tasks with more intelligence and less human intervention, while still keeping oversight. #### Databricks – Agent Bricks Known for its data lakehouse and ML platform, Databricks made an interesting move by introducing [Agent Bricks ](https://docs.databricks.com/aws/en/generative-ai/agent-bricks/)in mid-2025. This is a workspace for building production-grade AI agents that work with an organization's data. Databricks realized that one challenge with agentic AI is tailoring a general LLM to a company's proprietary data and evaluating its actions. Agent Bricks addresses this by automating a lot of the heavy lifting: you give a high-level description of the agent's task and connect it to your enterprise data sources, and Agent Bricks will generate training data or fine-tune as needed, plus set up evaluation harnesses (LLM "judges" that critique the agent's outputs). Databricks is offering "AI agents as a service," allowing you to quickly spin up a customized agent (such as a data analysis assistant or an internal developer helper) that is optimized for your data and continuously monitored for quality. This appeals to enterprises seeking agentic AI solutions while also requiring control over data privacy and model performance. #### [Dataiku – AI Agents](https://www.dataiku.com/stories/detail/ai-agents/) Dataiku, a prominent AI platform, integrated AI Agents capabilities into its suite in 2025. Dataiku's approach is about governance and ease-of-use in a central AI hub. It introduced an LLM Mesh to manage access to various large language models (open-source or proprietary) and an Agent Connect interface to deploy and monitor agents across the organization. One notable aspect is the dual approach to creating agents: a Code Agent option for data scientists who want to script custom logic, and a Visual Agent builder for non-technical users to develop agents via a no-code interface. Dataiku also built guardrails: Safe Guard to enforce policies and tool usage limits for agents, and comprehensive observability with a [Trace Explorer](https://doc.dataiku.com/dss/latest/agents/tracing.html) to inspect agent decision flows, plus Quality Guard and Cost Guard to track performance and ROI. This reflects a key trend for enterprise agentic AI – giving business users the power to create AI agents, but within an IT-governed sandbox that watches the watchers, so to speak. Dataiku's inclusion of these features shows how important trust and manageability are when deploying numerous agents in a large company. #### Snowflake – Data Science Agent In the data analytics realm, Snowflake (the cloud data platform) unveiled a [Data Science Agent ](https://www.snowflake.com/en/product/ai/)at its 2025 summit. It's described as an for data scientists, automating many routine model development tasks. Within Snowflake's interface, a user can instruct the agent in plain English to, for example,. The agent, powered by Anthropic's Claude LLM, will then break the request into steps like data cleaning, feature engineering, model training, and evaluation. It executes these steps by generating SQL queries, [Python](https://www.flobotics.io/blog/uipath-python) code, or leveraging Snowflake's built-in ML functions, all while explaining its rationale. The goal is to accelerate data science workflows and lower the technical barrier – a business analyst could use it to get insights without writing all the code themselves. Snowflake's agent essentially acts as a brilliant co-worker in the data team that takes on the grunt work of pipeline prep and lets humans focus on higher-level strategy. It's another example of domain-specific agentic AI, tuned for a particular kind of task (in this case, machine learning pipelines). #### Other Noteworthy Agentic Tools A few other specialized agentic AI tools deserve mention. [Adept AI's](https://www.adept.ai/) forthcoming system (built on their ACT-1 model) takes a unique approach by observing and imitating how humans use software, thereby enabling AI to perform tasks via the UI just like a person would. This means even without APIs, the AI can navigate apps, click buttons, and enter data on the user's behalf – a promising avenue for automating legacy software tasks. Startups like [AskUI](https://www.askui.com/) have a similar bent, using computer vision to let AI agents understand and interact with on-screen elements in any application. These are particularly useful for bridging gaps where no formal integrations exist. Meanwhile, platforms like [Relevance AI ](https://relevanceai.com/)(targeting marketing analytics) and [Orby AI](https://www.orby.ai/) (focusing on compliance workflows) are delivering tailored agentic solutions for those niches, with an emphasis on visual workflow design and auditability. Even popular automation tools are getting AI makeovers – as mentioned, Zapier's AI agents can build and fix "Zaps" automatically, and others like Make.com or HubSpot are exploring similar capabilities. The landscape is diverse, but the common theme is clear: software across the board is evolving to include autonomous AI agents that work alongside human users. ## Benefits and Outlook for Agentic AI Tools Agentic AI tools are not just a flashy new tech for tech's sake – they're delivering real business value and reshaping work in tangible ways. Companies adopting these tools have reported benefits such as: ### Unprecedented Automation Tasks that once required multiple manual steps or human oversight can now be handled end-to-end by AI agents. This ranges from customer support (where an AI agent can resolve common inquiries without a live rep) to complex IT operations (agents that monitor systems, diagnose issues, and even take corrective action). [Gartner forecasts ](https://www.gartner.com/en/topics/artificial-intelligence)that by 2029, the majority of customer service interactions will be managed by agentic AI, drastically reducing wait times and labor costs. By automating routine but multi-step processes, businesses free up employees for higher-value work and scale operations without linear headcount growth. ### Speed and Productivity Agentic AI tools operate at digital speed – a procurement approval that might take a human manager a day or two to handle (checking budgets, verifying vendor data, etc.) can be done by an AI agent in minutes, 24/7. Development teams are shipping code faster with coding agents handling the repetitive and tedious parts of QA and refactoring. Marketing teams can let agents analyze campaign data and adjust on the fly daily, instead of monthly. This responsiveness and always-on productivity are a huge competitive advantage in fast-paced markets. ### Cross-System Orchestration One of the trickiest aspects of enterprise workflows is that they span many systems (CRM, ERP, databases, email, etc.). Humans often act as the glue, moving data from one system to another. Agentic AI platforms excel at integrating across tools and silos – since they can use APIs or even UIs, they serve as universal connectors. Agents don't get tired of the swivel-chair integration; they'll happily copy data from a legacy mainframe interface into a cloud app if that's what the workflow needs. This orchestration capability enables processes to be redesigned in a more fluid, end-to-end manner, rather than being constrained by system boundaries. ### Adaptability and Learning Unlike traditional RPA scripts that were brittle (one change in UI could break a bot), AI agents bring adaptability. They can be built with feedback loops – for instance, an agent monitoring network security might adjust its actions based on new threats detected, or a sales outreach agent could tweak its messaging strategy if responses are poor. Many agentic tools also incorporate reinforcement learning or continual fine-tuning behind the scenes, so the more they operate, the better they get at the task. This learning ability, combined with memory, means agentic AI can improve processes over time in a way static software cannot. ### Strategic Insights Interestingly, when AI agents are tasked with complex problem-solving, they often surface insights that benefit the business. For example, if you ask an autonomous agent to optimize your supply chain, in the process of doing so, it might highlight previously unnoticed inefficiencies or data issues. The agent's (which some platforms let you review) can reveal new strategies or considerations that human managers hadn't seen. In this way, deploying agentic AI can double as a consultancy – uncovering improvement areas as the agent tries to achieve its goals. Looking ahead, the momentum behind agentic AI tools is only increasing. All signs point to more ubiquitous "digital coworkers" in the near future. We can expect: - Broader Adoption Across Industries: While tech and finance were early adopters, sectors like manufacturing, healthcare, and government are testing agentic AI for their needs (from autonomous diagnostic assistants to policy compliance agents). - Standardization and Interoperability: Efforts such as the (MCP) and others are enabling vendors to work towards standards, allowing agents built on different frameworks to communicate and share tools. This could lead to an ecosystem where specialized agents from different vendors form hybrid teams seamlessly. - Enhanced Governance: As enterprises deploy hundreds or thousands of agents, governance and ethical AI oversight are paramount. We'll see more robust control towers like ServiceNow's, more fine-grained permissioning (e.g., an agent that can read customer data but not export it), and compliance auditing features. will likely be part of the broader AI governance initiatives that CIOs and CTOs institute. Human-AI Collaboration: Rather than AIs working in isolation, the successful paradigm is shaping up to be AI agents working hand-in-hand with humans. In 2025, we will already see agents that escalate to a human when unsure or take instructions from employees on the fly. This collaborative workflow will mature, with humans supervising fleets of agents (like managers to employees) and agents augmenting every professional's capabilities. The end game is not replacing people but amplifying what teams can accomplish – achieving by leveraging intelligent automation. ## Conclusion Agentic AI tools represent a significant leap forward in enterprise automation – bringing adaptability, intelligence, and proactivity into processes that once relied on rigid code or constant human oversight. From modular open-source frameworks like LangChain and AutoGen to full-featured platforms like Cognosys and OpenAI's agent solutions, organizations have a rich toolkit to choose from in 2025. The key is selecting the right mix of technologies that align with your company's goals, infrastructure, and expertise. This is where having an experienced guide becomes invaluable. Flobotics positions itself as not only a provider of agentic AI solutions but also as an expert advisor in navigating this landscape. With deep roots in intelligent automation and RPA, Flobotics understands how to [integrate autonomous AI agents](https://www.flobotics.io/) into existing enterprise ecosystems and workflows. We help CTOs and innovation leaders assess the myriad of options – open-source vs. commercial, on-prem vs. cloud, specialized agents vs. general platforms – and identify what will deliver [the best ROI for a given process](https://www.flobotics.io/roi-calculator). The journey to implementing agentic AI can be complex, but it doesn't have to be taken alone. Flobotics offers both the technical know-how and strategic insight to ensure that your adoption of agentic AI tools is successful, secure, and aligned with your business objectives. Whether you're looking to deploy your first AI agent as a proof of concept or scale up an entire fleet of digital workers across departments, our team can tailor the approach to your needs. In an era where those who harness autonomous AI stand to gain a competitive edge, having the right partner is crucial. [Flobotics](https://www.flobotics.io/) stands ready to assist – from choosing and deploying the ideal agentic AI platforms to fine-tuning them for any enterprise process. By embracing agentic AI with expert guidance, enterprises can confidently step into the future of automation, where AI agents work tirelessly alongside human teams to drive efficiency and innovation. Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPAAI ### Agentic AI Frameworks | 2026 Agentic AI frameworks in 2026: which stacks Google and other leaders are betting on, explained with clear, research-backed answers. Jędrzej SzymulaDecember 02, 2025 ](https://www.flobotics.io/blog/agentic-ai-frameworks)[ AI ### Agentic AI Workflows Agentic AI workflows, explained: how autonomous AI agents handle multi-step RCM tasks beyond traditional rule-based RPA. February 04, 2026 ](https://www.flobotics.io/blog/agentic-ai-workflows)[ RPAAI ### What Is Agentic AI? | The Not-So-Obvious Guide What is agentic AI? A clear guide to how autonomous AI agents reason, act, and differ from traditional rule-based automation. Jędrzej SzymulaDecember 09, 2025 ](https://www.flobotics.io/blog/agentic-ai) [All articles →](https://www.flobotics.io/blog) --- # Agentic AI vs Generative AI: The Next Frontier of Intelligent Automation Canonical: https://www.flobotics.io/blog/agentic-ai-vs-generative-ai Author: Jędrzej Szymula Published: 2025-09-08 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Agentic AI vs Generative AI: The Next Frontier of… [AI](https://www.flobotics.io/blog?category=ai)[RPA](https://www.flobotics.io/blog?category=rpa) # Agentic AI vs Generative AI: The Next Frontier of Intelligent Automation [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published September 08, 2025Updated September 1, 2026 On this page - [What is Generative AI?](#what-is-generative-ai) - [What is Agentic AI?](#what-is-agentic-ai) - [Key Characteristics of Agentic AI Include:](#key-characteristics-of-agentic-ai-include) - [Autonomy](#autonomy) - [Goal-Oriented Behavior](#goal-oriented-behavior) - [Adaptability](#adaptability) - [Tool Use and Environment Interaction](#tool-use-and-environment-interaction) - [Limited Oversight](#limited-oversight) - [Proactive by Design: Why Agentic AI Matters for the Enterprise](#proactive-by-design-why-agentic-ai-matters-for-the-enterprise) - [Agentic AI vs Generative AI – Key Differences](#agentic-ai-vs-generative-ai-key-differences) - [Better Together: Combining Generative and Agentic AI](#better-together-combining-generative-and-agentic-ai) - [Healthcare Revenue Cycle Management (RCM)](#healthcare-revenue-cycle-management-rcm) - [Customer Service Example](#customer-service-example) - [Banking Loan Processing](#banking-loan-processing) - [IT & DevOps Automation](#it-devops-automation) - [The Future: Towards Autonomous Intelligent Systems](#the-future-towards-autonomous-intelligent-systems) - [AI Co-workers and Autonomous Teams](#ai-co-workers-and-autonomous-teams) - [Blurring Lines Between Tools](#blurring-lines-between-tools) - [More Natural Interaction and Trust](#more-natural-interaction-and-trust) - [New Business Models and Opportunities](#new-business-models-and-opportunities) - [Summing Up](#summing-up) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What is Generative AI? Generative AI (GenAI) refers to AI systems designed to [generate original content](https://www.ibm.com/think/topics/agentic-ai-vs-generative-ai) – text, images, videos, audio, even software code – in response to user prompts. These models, often powered by large language models (LLMs) and deep learning, analyze vast training data to recognize patterns and produce new output that follows those patterns. In essence, Generative AI is about creativity and content creation on demand. A Generative AI system, such as GPT-4 or DALL·E, can produce a human-like response or design when given an example prompt. For instance, you could ask a GenAI chatbot to summarize a legal contract or draft a marketing blog post, and it will craft a coherent text based on its learned knowledge. [Generative AI excels](https://www.ibm.com/think/topics/agentic-ai-vs-generative-ai) at producing high-quality drafts, answers, images, or code snippets in real-time, making it incredibly valuable for content creation, brainstorming, and summarization tasks. Many professionals are already harnessing GenAI for productivity – from marketers auto-generating ad copy, to software developers having AI write boilerplate code, to analysts getting AI-written summaries of complex reports. Real-world example: Following the release of ChatGPT by OpenAI in late 2022, Generative AI adoption skyrocketed across various industries. By mid-2023, approximately one-third of companies reported [using Generative AI regularly](https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai) in at least one business function. Executives themselves have embraced it – nearly 25% of C-suite leaders say they personally use Generative AI tools for work. The appeal is clear: Generative AI can draft emails, create personalized customer responses, translate documents, and more in seconds. In enterprise settings, Generative models are being utilized to produce initial drafts of documents, generate product designs from specifications, provide code suggestions to accelerate development, and even simulate scenarios for training and forecasting. This content-generation ability is a game-changer for tasks that previously required significant human effort. However, Generative AI has its limitations. Because it relies on learned patterns, it may sometimes produce incorrect or nonsensical outputs (often called "hallucinations") if prompted beyond its knowledge. It typically requires human direction for each request – you provide a prompt, and it generates an output. Generative models don't "decide" to do things on their own; they react to the user's prompts. For business use, this means GenAI is incredibly useful for creating content or suggestions, but it won't autonomously execute a task without being asked. Quality control and guidance remain important – for example, an AI-generated report or email typically requires review to ensure accuracy and appropriateness. ## What is Agentic AI? If Generative AI is about content, Agentic AI is about action. Agentic AI refers to AI systems endowed with agency – the ability to [autonomously make decisions and execute tasks](https://www.atera.com/blog/agentic-ai-vs-generative-ai/) in pursuit of a goal, with minimal human intervention. In other words, an Agentic AI is not just answering a question or producing text; it's taking initiative to plan and act. These are sometimes referred to as AI agents or autonomous agents. They combine advanced AI (often LLMs, machine learning, and reasoning algorithms) with tool use, allowing them to interact with software, APIs, or even the physical world to carry out multi-step processes. Think of Agentic AI as an autopilot for workflows. Give an Agentic AI a high-level instruction, and it can break it down into sub-tasks, figure out what needs to be done, and then do it – all [while adjusting to new information](https://www.posh.ai/blog/generative-ai-vs-agentic-ai-in-banking-what-sets-them-apart) along the way. For example, an Agentic AI could be told to "organize our customer support tickets and schedule follow-ups for any urgent issues." It might then autonomously pull data from the ticketing system, identify priority cases, draft email responses (perhaps using a generative model as a sub-component), send those emails, and schedule calendar reminders for follow-up calls – without a person manually triggering each step. ### Key Characteristics of Agentic AI Include: ### Autonomy It operates with minimal human supervision, making real-time decisions on the next actions to take. The AI can continue working toward its goal until it's achieved or until it reaches a boundary condition. ### Goal-Oriented Behavior Instead of just doing one task when asked, Agentic AI is driven by achieving a specific objective. It can plan a sequence of actions (a workflow) to reach that objective. ### Adaptability Agentic systems monitor the results of their actions and the environment, and they adapt if things change. If one approach fails, they can try another, much like a human would adjust strategy on the fly. ### Tool Use and Environment Interaction Agentic AI often utilizes APIs, software tools, or even robotics. It might call external services, run database queries, or control robotic process automation (RPA) bots as part of executing tasks. ### Limited Oversight While humans set the goals and define boundaries or rules, the Agentic AI has the latitude to decide how to get there. This requires trust and robust testing, because you're letting the AI drive the process, not just produce outputs for a human to review. ## Proactive by Design: Why Agentic AI Matters for the Enterprise Early examples of Agentic AI are emerging all around us. Autonomous vehicles are a form of Agentic AI – they perceive the environment and make driving decisions continuously without a human telling them each move. Advanced virtual assistants and RPA bots with AI capabilities are another example; they can perform sequences of actions, such as scheduling meetings, sending reminders, or extracting and moving data between systems independently. In the enterprise, an Agentic AI might coordinate a complex process such as [invoice processing](https://www.flobotics.io/business-process-automation): receiving an email with an invoice, interpreting it, updating the accounting system, flagging any discrepancies, and issuing payment – all automatically. IBM describes Agentic AI as combining the flexible reasoning of LLMs with the strict accuracy of traditional software to pursue complex goals with minimal supervision. Because Agentic AI is proactive, it changes how we interact with AI. Instead of a user constantly prompting the AI for the next step, an Agentic AI can carry on a workflow "in the background." Of course, this autonomy means businesses must implement proper oversight, constraints, and fail-safes. A poorly directed Agentic AI could stray off course or make decisions that require human review. For now, many Agentic AI deployments remain in pilot and experimental stages, as organizations learn how to trust these autonomous agents in real-world scenarios. However, the potential is enormous – from handling routine customer service issues end-to-end to managing supply chain adjustments in real-time, to monitoring systems and resolving problems before anyone is even aware. Agentic AI systems essentially act as intelligent coordinators or operators, not just advisors. ## Agentic AI vs Generative AI – Key Differences Generative and Agentic AI differ fundamentally in their approaches. [It's often said](https://wursta.com/generative-ai-and-agentic-ai-a-beginners-guide-to-the-differences/) that Generative AI focuses on the "what" (creating outputs), while Agentic AI focuses on the "how" (achieving goals). Let's break down the core differences in a side-by-side comparison: Fig. 01 · Agentic vs generative AI Key differences Agentic AI vs generative AI Aspect | Generative AI | Agentic AI | Core function | Creates content in response to prompts (text, images, code) | Carries out multi-step tasks to reach a goal with few prompts | Main strength | Producing new, human-like output for a given input | Making decisions and acting on its own to move a process forward | Mode of operation | Reactive: answers each request one step at a time | Proactive: given a goal, it keeps working and adjusting until done | Task complexity | Best for simpler tasks; people fit the output into larger processes | Handles chained, complex tasks: research, analysis, decision and action in one flow | Autonomy | Low: needs user input for each action | High: works toward a defined goal on its own | Human interaction | The user starts every exchange and uses the output | The user sets the goal and rules; the agent asks only at decision points or when finished | Key benefit | Speeds up creative work, drafting and data synthesis | Handles complex tasks from start to finish, faster and more consistently | Watch out for | Output quality depends on the prompt and training data; needs fact-checking | Needs clear goals and constraints, oversight and validation checkpoints | In simple terms, Agentic AI "acts," while Generative AI "creates." Generative AI might write the report, whereas Agentic AI will file the report, send it to the relevant parties, and initiate the next steps based on the report's findings. Generative AI is like a talented content producer or brainstormer at your disposal, and Agentic AI is like a smart, autonomous executive assistant that can handle tasks on your behalf. It's also worth noting that Agentic AI is relatively new to the scene. Many Generative AI applications are already mainstream (dozens of AI writing assistants, image generators, coding copilots, etc., in daily use), whereas Agentic AI applications are just starting to emerge beyond RPA. Tech companies are now racing to embed Agentic capabilities into their platforms. UiPath, a leading automation vendor, [released an "Agentic AI"](https://www.uipath.com/ai/agentic-ai) update to its automation platform in 2025, reflecting the growing importance of the fusion of AI and action in the RPA world. In short, Generative AI vs Agentic AI is not about which is better – each has distinctive capabilities. The real power lies in their combined use. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Better Together: Combining Generative and Agentic AI Rather than "Agentic AI vs Generative AI" as an either/or choice, forward-thinking organizations see them as complementary. Generative and Agentic AI systems can be orchestrated to work in tandem, with Generative AI handling the creative or interpretative steps and Agentic AI handling the decision and action steps. This synergy can create end-to-end autonomous solutions that were previously impossible. Consider a few scenarios that illustrate the synergy: ### Healthcare [Revenue Cycle Management (RCM)](https://www.flobotics.io/rcm-automation) In a healthcare setting, Generative AI and Agentic AI can work together to streamline complex RCM workflows. For example, when a patient schedules an appointment, Generative AI can interpret unstructured inputs, such as uploaded insurance cards or free-text symptoms, and draft a personalized confirmation message. Agentic AI then steps in to verify insurance eligibility, initiate prior authorization if needed, and log the appointment details into the EHR and [billing system](https://www.flobotics.io/blog/medical-billing-management). After the visit, Generative AI can help summarize the physician's notes and suggest appropriate billing codes, while Agentic AI auto-populates and submits the claim, tracks payer responses, and even initiates appeal workflows for denied claims. This collaboration reduces administrative overhead, shortens the reimbursement cycle, and enhances the patient experience – all while maintaining human involvement for exception handling and compliance. ### Customer Service Example A customer sends an email complaining about a billing error. A Generative AI model can read the email and draft a personalized response apologizing and explaining the next steps. Then, an Agentic AI system takes over to execute those steps – it could log into the billing system, correct the error or flag it for human review, issue a refund, and finally send out the AI-crafted response to the customer. Here, Generative AI handles the language and empathy, while Agentic AI handles the workflow and actions. ## Banking Loan Processing Generative AI drafts a personalized loan approval letter for a customer. Then, Agentic AI validates all the loan details, files the necessary documents, sends the approval letter, and notifies the customer of the next steps. In this way, the creative content and the procedural execution are seamlessly integrated. ## IT & DevOps Automation Imagine an IT helpdesk scenario. A Generative AI assistant might handle an employee's chat request by generating a solution or explanation to a technical problem. If the issue requires action (e.g., resetting a password or provisioning access), an Agentic AI could then carry out those actions automatically on the backend systems. [Microsoft's GitHub Copilot](https://github.com/features/copilot), for instance, is generative (it suggests code), but paired with an Agentic system. It could not only write code but also decide to run tests, deploy the code, or roll back changes if an issue is detected – all without waiting on human prompts. These examples demonstrate a pattern: Generative AI provides the content or insight, while Agentic AI enables the autonomy to act on that insight. When combined, they enable a form of "closed-loop" intelligent automation. A task can progress from understanding to decision to action in a seamless, continuous flow. This can dramatically reduce cycle times – what once took days of human back-and-forth can potentially be done in minutes by an AI duo. No surprise, then, that experts predict most companies will use a combination of both Generative and Agentic AI to get the best results, rather than sticking to just one approach. ### The Future: Towards Autonomous Intelligent Systems Looking ahead, the future of AI in business will fuse generative and agentic capabilities even more deeply. We can anticipate AI systems that both generate sophisticated plans and content and execute them autonomously – essentially, self-driving corporate processes. In the next 2–3 years, we'll likely see: ## AI Co-workers and Autonomous Teams Just as today's AI can draft an email for you, tomorrow's AI agent might handle an entire project for you. For example, you could instruct an AI project manager, "Launch a market research project for our new product and prepare a report of findings by next month." The AI would then perhaps utilize Generative AI to formulate research questions, employ Agentic AI to commission surveys or gather data from various sources, analyze the data, and finally use Generative AI again to compile the report, notifying you when it's complete. ### Blurring Lines Between Tools We'll see traditional RPA, [BPM (Business Process Management),](https://www.flobotics.io/blog/bpm-vs-rpa-the-difference-and-what-it-means-for-your-business) and AI converge. Future automation platforms (like the latest from UiPath or Microsoft) are introducing built-in LLMs for generative tasks and agent orchestration for autonomous tasks within the same workflow. This means that when you design a business process in these platforms, you can insert a step where an AI generates a summary or makes a prediction, and another step where an AI agent takes action based on that. The tech stack is evolving to support hybrid AI workflows natively. In other words, "AI agents, automation, and people" will all collaborate in process flows, each doing what they do best. ### More Natural Interaction and Trust As Generative AI improves in understanding context and as Agentic AI proves itself reliable through narrow successes, executives and employees will grow more accustomed to trusting AI with autonomy. The user interface of AI may shift from a chatbox that gives answers to a dashboard that oversees your fleet of AI agents carrying out tasks. Natural language interfaces (thanks to Generative AI) will let managers give high-level directives like they're talking to a colleague: "AI, please handle the month-end reporting and alert me if any anomalies." And the Agentic AI will do it. The ease of instructing AI in plain language, combined with the confidence that it will get the job done, can truly democratize automation across the workforce. ## New Business Models and Opportunities Companies that harness both forms of AI can offer innovative services. For instance, at [Flobotics](https://www.flobotics.io/), we stay at the cutting edge by blending Generative and Agentic AI in our automation solutions – this is a key differentiator. We expect to see new startups and products emerge that advertise "autonomous AI solutions" for specific domains (e.g., [autonomous supply chain](https://www.flobotics.io/blog/rpa-logistics-supply-chain-management) manager, autonomous HR assistant), which essentially package domain expertise with Generative and Agentic AI under the hood. Forward-looking executives should be scouting ways to leverage these opportunities to gain an advantage or even create new revenue streams. Many industry experts agree that organizations that effectively integrate content generation and autonomous action are likely to leapfrog their competitors in terms of efficiency and customer experience. ## Summing Up In conclusion, the era of Agentic AI vs Generative AI isn't about choosing one over the other, but understanding the distinct role of each and leveraging them together. Generative AI opened the door to machines that can write, design, and converse, augmenting our creative and analytical capabilities. Agentic AI is now taking us a step further – machines that can decide and act, augmenting our ability to get things done on autopilot. At [Flobotics](https://www.flobotics.io/), we've seen firsthand that combining generative and Agentic capabilities yields transformative automation solutions. Now, by infusing those bots with Generative AI and advanced [Agentic AI](https://www.flobotics.io/blog/agentic-ai-vs-rpa) logic, we build intelligent automations that can handle unstructured data and make autonomous decisions like never before. For CTOs and business leaders, the mandate is clear: it's time to craft an AI strategy that unites creation with execution. Those who do will unlock unprecedented levels of automation, speed, and innovation, while those who don't risk falling behind in a world that's rapidly automating itself. At Flobotics, we're already helping companies bridge that gap. If you're ready to explore how Generative and Agentic AI can transform your workflows, [contact us](https://www.flobotics.io/contact), and let's build the future of automation together! #### Like the article? Spread the word Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # What Is RPA? | Robotic Process Automation Canonical: https://www.flobotics.io/blog/robotic-process-automation Author: Bart Teodorczuk Published: 2025-09-01 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/What Is RPA? | Robotic Process Automation [RPA](https://www.flobotics.io/blog?category=rpa) # What Is RPA? | Robotic Process Automation [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published September 01, 2025Updated September 1, 2026 On this page - [What is RPA?](#what-is-rpa) - [How RPA Works?](#how-rpa-works) - [The 3 Core Types of RPA](#the-3-core-types-of-rpa) - [Top Benefits (The "Why")](#top-benefits-the-why) - [Real-World Use Cases](#real-world-use-cases) - [RPA vs. AI: The Difference](#rpa-vs-ai-the-difference) - [Famous RPA Examples (Real-World Impact)](#famous-rpa-examples-real-world-impact) - [RPA:Why is it worth your money(and our time)?](#rpa-why-is-it-worth-your-money-and-our-time) - [What is Robotic Process Automation?Understanding the Technology and Business Models](#what-is-robotic-process-automation-understanding-the-technology-and-business-models) - [Attended Automation](#attended-automation) - [Unattended Automation](#unattended-automation) - [Hybrid Automation:What We Use(and Recommend)Most](#hybrid-automation-what-we-use-and-recommend-most) - [RPA-as-a-Product](#rpa-as-a-product) - [RPA-as-a-Service](#rpa-as-a-service) - [The Benefits of RPA:A Detailed Look](#the-benefits-of-rpa-a-detailed-look) - [Increased Speed and Productivity](#increased-speed-and-productivity) - [Improved Process Quality](#improved-process-quality) - [Reduced Operating Costs](#reduced-operating-costs) - [Decreased Workforce Gaps](#decreased-workforce-gaps) - [Fewer Errors](#fewer-errors) - [Reduced Employee Burnout](#reduced-employee-burnout) - [Impeccable Customer Experience](#impeccable-customer-experience) - [Enhanced Decision-Making](#enhanced-decision-making) - [Improved Regulatory Compliance](#improved-regulatory-compliance) - [RPA vs. Other Technologies](#rpa-vs-other-technologies) - [AI and RPA:Working in Tandem](#ai-and-rpa-working-in-tandem) - [Enter Generative AI](#enter-generative-ai) - [How AI(and GenAI)Enhance RPA Capabilities](#how-ai-and-genai-enhance-rpa-capabilities) - [RPA for Energy](#rpa-for-energy) - [RPA for Real Estate](#rpa-for-real-estate) - [RPA for IT Consulting](#rpa-for-it-consulting) - [RPA for E-Commerce](#rpa-for-e-commerce) - [RPA for Logistics and Transport](#rpa-for-logistics-and-transport) - [RPA for Telecom](#rpa-for-telecom) - [Popular RPA Tools and Their Importance](#popular-rpa-tools-and-their-importance) - [UiPath](#uipath) - [Blue Prism](#blue-prism) - [Automation Anywhere](#automation-anywhere) - [Python](#python) - [Microsoft Power Automate](#microsoft-power-automate) - [IBM Robotic Process Automation](#ibm-robotic-process-automation) - [Tungsten Automation(formerly Kofax)](#tungsten-automation-formerly-kofax) - [OpenBots](#openbots) - [WorkFusion RPA Express](#workfusion-rpa-express) - [A Step-by-Step Guide to Implementing RPA](#a-step-by-step-guide-to-implementing-rpa) - [How to Select the Perfect Process for Automation?](#how-to-select-the-perfect-process-for-automation) - [How to Measure your RPA Automation Results?](#how-to-measure-your-rpa-automation-results) - [Key Metrics to Track for RPA Success](#key-metrics-to-track-for-rpa-success) - [Value of Time Gains](#value-of-time-gains) - [Return on Investment(ROI)](#return-on-investment-roi) - [Gained Productivity](#gained-productivity) - [Process Automation Velocity](#process-automation-velocity) - [RPA Automation Uptime](#rpa-automation-uptime) - [Downtime Rate](#downtime-rate) - [Closing thoughts](#closing-thoughts) - [Top RPA Providers in 2026](#top-rpa-providers-in-2026) - [Article Summary](#article-summary) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What is RPA? At its core, Robotic Process Automation (RPA) is a software technology that makes it easy to build, deploy, and manage software robots (bots) that emulate human actions. - The "Robot": Not a physical machine, but a software script. - The "Process": A sequence of steps that follows a specific set of rules (e.g., "If an invoice is over $500, send it to the manager"). - The "Automation": The bot performs these tasks without human intervention, 24/7, with 100% accuracy. Key Distinction: Unlike traditional programming, RPA interacts with applications through the User Interface (UI), just like you do, rather than requiring complex back-end integrations or APIs. ## How RPA Works? RPA bots act as "digital coworkers" that watch what a human does and then replicate it. ### The 3 Core Types of RPA - Attended RPA: Lives on your desktop. It works alongside you, triggered by specific actions (e.g., a customer service agent clicking a button to auto-fill a form).‍ - Unattended RPA: Lives on a server. It runs in the background, triggered by schedules or events (e.g., processing all invoices received at midnight).‍ - Hybrid RPA: A combination where bots and humans pass tasks back and forth for complex workflows. ## Top Benefits (The "Why") The top 3 SERPs highlight these primary drivers for adoption: Benefit | Impact | Increased Efficiency | Bots work faster than humans and never sleep, increasing throughput. | Better Accuracy | Bots don't get bored or distracted; they eliminate "fat-finger" data entry errors. | Cost Savings | According to Deloitte, RPA can reduce operational costs by up to 30%. | Employee Morale | By removing "grunt work," employees can focus on creative, high-value strategy. | ## Real-World Use Cases RPA is most effective for tasks that are rule-based, repetitive, and involve structured data. - Finance: Processing invoices, reconciling bank statements, and automated payroll. - Customer Service: Chatbots pulling account info or resetting passwords instantly. - HR: Automating the data entry required for onboarding new employees across multiple systems. - Supply Chain: Tracking shipments and automatically updating inventory levels when stock is low. Click here to [read our article about RPA use cases >](https://www.flobotics.io/blog/rpa-use-cases-across-industries) ## RPA vs. AI: The Difference A common misconception is that RPA is the same as Artificial Intelligence. - RPA is the "Arms and Legs": It follows instructions to the letter ($If\ X, then\ Y$). It doesn't "think." - AI is the "Brain": It handles unstructured data (like reading a messy handwritten note) and makes probabilistic decisions. - Intelligent Automation (IA): This is the "sweet spot" where RPA and AI are combined to handle end-to-end complex processes. ### Famous RPA Examples (Real-World Impact) Companies across various sectors have moved beyond theory to save millions of hours using RPA: - Walmart: Deployed over 500 bots to handle everything from answering employee questions to identifying slow-moving inventory and managing "deadstock" in their warehouses. - Delta Airlines: Uses RPA to automate the check-in process, including passenger ID verification and boarding pass issuance, as well as complex back-end flight scheduling and route planning. - Santander Bank: Leveraged bots to automate the HR onboarding process for new hires, reducing the time it takes to get a new employee up and running from 6 weeks to just 2 days. - McDonald’s: Implemented RPA in their kitchens and self-service kiosks to automate order processing and beverage dispensing, significantly reducing waste and wait times. - Walgreens: During the COVID-19 vaccine rollout, used bots to automate dose registration, allowing medical staff to focus on patients rather than manual data entry. ## RPA:Why is it worth your money(and our time)? RPA has quietly become the backbone of how companies get work done. It’s not a nice-to-have tool—it’s now part of how innovative businesses operate daily. If you’re trying to scale without hiring more people, reduce mistakes, or simply get routine tasks out of your team’s way, this is what RPA is built for. It takes care of the repetitive, time-consuming stuff so your team can focus on things that actually require thinking. In this guide, we’ll walk you through what RPA really is, where it works best, how to choose the right tools, what to automate(and what not to), and how to measure whether it’s doing its job. ## What is Robotic Process Automation?Understanding the Technology and Business Models Robotic Process Automation(RPA)is a technology that leverages software bots to automate high-volume, repetitive, and rules-based tasks traditionally performed by humans. At its core, RPA mimics human actions, such as reading and entering data, processing transactions, and interacting with digital systems, without altering the underlying applications. There are two primary modes of operation: YouTube video player 1 ### Attended Automation These bots work alongside humans. User inputs activate them and help streamline front-office activities, such as assisting call center agents, guiding customer service representatives through processes, or providing real-time support during routine tasks. Because they follow a human-in-the-loop approach, attended bots ensure that complex decision points still benefit from human judgment while handling the more monotonous aspects of a task. ### Unattended Automation Designed to operate independently, unattended bots are pre-programmed to execute tasks without human input. They are typically scheduled or triggered by events and are best suited for back-office processes such as data reconciliation, invoice processing, or batch operations. Unattended automation runs around the clock, ensuring repetitive tasks are completed quickly and consistently. ## Hybrid Automation:What We Use(and Recommend)Most Most real-world automation setups aren’t strictly attended or unattended—they’re both. Let’s say a customer service agent uses an attended bot to pull account details during a call. At the same time, an unattended bot in the background updates the CRM,triggers a follow-up email, and logs the interaction. The entire flow is seamless and designed to minimize manual steps from start to finish. This hybrid setup is exactly what we implement most often at Flobotics. It gives teams real-time support when needed and lets bots handle everything else quietly in the background. When done right, hybrid automation becomes the glue between departments, tools, and teams. Attended vs. Unattended Bots operations Beyond these operational modes, RPA can be implemented under two distinct business models: ### RPA-as-a-Product RPA is a ready-made automation package explicitly designed for industry-specific processes. These solutions are fully integrated into existing systems and work seamlessly with ERPs, CRMs, billing platforms, and other enterprise software. Instead of developing an automation from scratch, businesses can pick a pre-built solution from an RPA agency and deploy it quickly. #### What’s in it: #### Defined Cost & Deployment Time Companies receive upfront pricing and clear implementation timelines. Costs can also be lower since existing automation code can be reused, reducing development efforts. That’s why working with an implementation partner with a portfolio of automation solutions within your industry is valuable, ensuring faster and more cost-effective deployment. #### Scalability Through an Automation Ecosystem Building an automation ecosystem is easier when automation works like a puzzle—each pre-built solution is another piece that requires only slight adjustments to fit the company’s environment, rather than painting the entire picture from scratch. This applies to attended and unattended bots, allowing businesses to scale automation efficiently across different functions. ### RPA-as-a-Service The approach is more flexible and consultative. It focuses on assessing a company's processes and determining what should be automated. Businesses engage an RPA expert, agency, or internal IT team to develop a tailored solution. Many details—technology, cost, deployment timeline, and scope—become more apparent during the assessment phase. #### What’s in it: #### Process Assessment & Consulting Experts analyze business operations and suggest which tasks should be automated. #### Technology Selection Happens Later The decision to use UiPath, Automation Anywhere, Power Automate, or a custom Python script depends on the complexity of the process and the company's needs. #### Cost and timeline are Uncertain Initially Unlike RPA as a product, where pricing is predefined, the cost of RPA is estimated based on effort, development complexity, and process adjustments. RPA as a Product VS RPA as a Service In both cases, the power of RPA lies in its ability to streamline operations, reduce human error, and free up employees for more strategic, value-added tasks. ## The Benefits of RPA:A Detailed Look RPA offers many benefits that extend well beyond mere task automation. Here’s a deeper dive into each key advantage: ### Increased Speed and Productivity Bots execute tasks at a pace far beyond human capabilities. They operate 24/7 without breaks, which means processes that once took hours or days can be completed in minutes. This rapid processing boosts productivity and accelerates overall business cycles, enabling companies to respond more quickly to market demands. ### Improved Process Quality RPA reduces the risk of human error by automating rule-based tasks. Consistent execution ensures that data remains accurate and processes run smoothly, which is critical in financial reconciliation or compliance reporting. This high level of consistency directly contributes to higher-quality outcomes and lower error rates. ### Reduced Operating Costs With minimal maintenance and a relatively low initial investment, RPA solutions cut down on labor costs. Companies can reallocate their human resources to more strategic initiatives by automating routine tasks. Reducing manual work and associated errors further translates into significant cost savings over time. ### Decreased Workforce Gaps RPA helps address human resources shortages by automating repetitive tasks, reducing the strain on existing employees. With automation handling time-consuming processes, businesses can continue operations smoothly even with fewer staff members or during times of high turnover. This enables HR teams to focus on more strategic roles while minimizing the impact of workforce gaps on overall productivity. ### Fewer Errors Unlike humans, bots perform tasks precisely as programmed—every single time. This precision is crucial in environments where even a tiny mistake can lead to large-scale discrepancies, such as in data entry or financial transactions. Cleaner, error-free processes provide more reliable outcomes and enhanced trust in system outputs. ### Reduced Employee Burnout By automating repetitive and mundane tasks, RPA helps prevent employee burnout, giving them more time to focus on creative problem-solving and strategic planning. This reduction in burnout boosts job satisfaction and fosters innovation, allowing employees to dedicate their energy to tasks that truly contribute value to the organization. ### Impeccable Customer Experience With RPA handling routine inquiries and processing requests instantly, customer service improves dramatically. The ability to provide 24/7 service, rapid response times, and accurate processing means that customers receive prompt, high-quality service, leading to enhanced customer loyalty and satisfaction. ### Enhanced Decision-Making RPA streamlines data collection and processing, providing leaders with up-to-date and accurate data. This rapid access to information facilitates timely, data-driven decisions, empowering organizations to pivot and adjust strategies quickly in response to market trends. ### Improved Regulatory Compliance RPA systems log every action they take, ensuring complete traceability and auditability. This inherent transparency helps organizations meet compliance requirements, reduce the risk of regulatory penalties, and build trust with regulators and customers. ROI Calculator_Banner ## RPA vs. Other Technologies While RPA is highly effective for automating rule-based, repetitive tasks, other technologies such as Artificial Intelligence(AI), Agentic AI,Document Understanding, and Machine Learning(ML)offer unique benefits. Modern enterprises are increasingly integrating AI with RPA to enhance automation capabilities, allowing businesses to go beyond structured processes and handle cognitive decision-making, unstructured data processing, and end-to-end workflow automation. Below is a comparison table highlighting the key features and differences between these automation technologies: RPA vs AI,RPA vs ML,RPA vs Agentic AI,RPA vs Doc Understanding ## AI and RPA:Working in Tandem Modern enterprises increasingly combine AI with RPA to build automation solutions beyond simple task execution. While RPA handles structured, rule-based work, AI can process unstructured data, like emails, images, scanned documents, or even voice messages. A key part of this blend is OCR(Optical Character Recognition)and Document Understanding.OCR lets bots extract text from scanned documents, PDFs, or handwritten forms.AI-driven Document Understanding takes it further by interpreting and organizing that data before passing it into RPA workflows—so the bots don’t just read data, they actually know what to do with it. But it doesn’t stop there. ## Enter Generative AI While traditional AI classifies, predicts, and analyzes, Generative AI creates. It can write email responses, summarize contracts, generate reports, or even produce code snippets, based on the context the RPA bot collects. This means RPA bots aren’t just pushing data between systems anymore. Paired with Generative AI,they can now pull in raw inputs, have GenAI draft content, and deliver ready-to-send outputs, take form data, and have GenAI write personalized onboarding emails or customer summaries, use GenAI to handle exceptions when workflows don't fit predefined rules. This combination of RPA + traditional AI + Generative AI is what enables true end-to-end automation—even in workflows that used to rely heavily on human input. ## How AI(and GenAI)Enhance RPA Capabilities Enhanced Data Processing:AI-powered OCR and Document Understanding extract and structure information from invoices, contracts, and records, giving RPA bots clean, usable input. Improved Decision-Making:AI can analyze large datasets, detect anomalies, and offer insights that guide bots through complex logic paths. Generated Content On-the-Fly:Generative AI enables bots to go beyond rules and dynamically create responses, summaries, or documents. Adaptive Workflows:The system continues learning and improving with every interaction, so the more it’s used, the better it gets. By combining AI,Generative AI,OCR,and RPA,companies can now automate work that used to be too unstructured, too fluid, or too unpredictable, turning hours of manual effort into seconds of seamless automation. ## RPA for Energy The energy sector handles complex workflows across billing, maintenance scheduling, compliance, and resource management.RPA supports operational continuity and data consistency. Typical processes automated: - Meter data collection and billing:Extracts readings, calculates bills, and updates customer accounts. - Compliance report generation:Automates environmental, safety, and financial reporting. - Customer account updates:Syncs changes across CRM and billing platforms. - Supplier onboarding:Collects documents, verifies credentials, and updates internal systems. Benefits: - Shorter billing cycles - Improved data accuracy for audits - Lower operational costs Case Study: Axpo, Switzerland’s leading renewable energy provider and a key player in international energy trading, faced challenges due to rapid growth. Their manual processes couldn’t keep up with the increasing volume of tasks, and compliance with international regulations was becoming more difficult. With the help of RPA,Axpo now automates the generation and correction of invoices for over 600 daily transactions. In addition, RPA bots help complete 27 days’ worth of work in a single day for the legally required pricing summary process, which was previously handled manually. As a result, Axpo can now scale operations efficiently, meeting regulatory demands while improving internal productivity. ## RPA for Real Estate Real estate teams deal with lease management, onboarding new clients, and handling a constant flow of documents.RPA in real estate reduces time spent on repetitive back-office work. Typical processes automated: - Lease data extraction:Reads and transfers key terms into property management software. - Contract generation:Automatically fills templates with tenant and property details. - Client onboarding:Collects documentation, verifies identity, and logs tenant data. - Compliance documentation:Gathers and stores audit trails and proof of compliance. Benefits: - Faster lease processing - Fewer document-related errors - Better team focus on sales and client relationships Case Study: Paramount Residential Mortgage Group(PRMG), a California-based mortgage banker operating across 48 states, struggled with manual, time-consuming, and inconsistent loan estimation and approval processes. What began as a simple single-bot solution for automating one part of the loan process quickly scaled into a comprehensive loan processing automation system.PRMG now relies on six bots, each dedicated to specific steps in the workflow, including retrieving and distributing disclosure packages, compiling data, and archiving it across various systems. This automation has significantly improved efficiency and accuracy, ensuring faster and more reliable loan processing. ## RPA for IT Consulting IT teams often spend too much time on routine tasks—ticketing, system monitoring, patch updates—that take away from more strategic initiatives.RPA handles the routine so your tech team can focus on problem-solving. Typical processes automated: - Help desk ticket triaging:Categorizes and routes tickets to the right team. - Software provisioning:Installs applications based on predefined user profiles. - System health checks:Runs diagnostics and sends alerts. - Password resets:Handles automated reset workflows based on user verification. Benefits: - Faster issue resolution - Lower support overhead - Happier IT teams Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## RPA for E-Commerce E-commerce businesses need speed, accuracy, and flexibility to handle everything from order fulfillment to customer service.RPA supports these goals without requiring more headcount. Typical processes automated: - Order processing and status updates:Captures order info, sends confirmations, and updates inventory. - Inventory syncing:Syncs stock levels across warehouses and online platforms. - Returns management:Validates returns, generates labels, and updates records. - Customer support ticket routing:Classifies incoming queries and forwards to the right team. - Personalized promotions:Generates discount codes and emails based on user behavior. Benefits: - Quicker order fulfillment - Reduced return handling time - Better customer experience at scale Case Study: Lotte, a leading South Korean e-commerce platform, faced challenges with managing a high volume of product listings and maintaining the accuracy of product information. Their manual processes for inspecting ads, filtering false or exaggerated content, and managing inventory were inefficient, leading to errors and delays in product listings. Lotte implemented OCR + RPA to automate key tasks: Product Inspection:RPA and OCR were used to filter through false or exaggerated ads, ensuring that only accurate product listings were displayed. Order Management:Bots automated the processing of incoming orders, verifying details and updating inventory in real time. Inventory Updates:RPA ensured accurate stock levels across platforms, syncing inventory information seamlessly. Results: 10,000 product inspections per month, filtering out false or exaggerated ads to maintain quality listings. Faster order processing and inventory updates, reducing errors and delays in fulfillment. Improved customer satisfaction due to more accurate product information and quicker response times. ## RPA for Logistics and Transport From shipment tracking to route optimization, logistics operations rely on timely data and efficient coordination.RPA in logistics helps automate routine steps to keep things moving smoothly. Typical processes automated: - Shipment status updates:Extracts tracking info from carriers and updates portals. - Route planning:Uses rules to select the fastest or most cost-effective routes. - Inventory reconciliation:Compares warehouse and system data to detect mismatches. - Carrier performance monitoring:Compiles delivery times and flags delays. Benefits: - Fewer delays - More accurate delivery tracking - Better planning based on real-time data Case Study: A leading logistics company was struggling with the inefficiencies of manual processes for shipment tracking, document handling, and data entry. These challenges led to high operational costs, delays in processing shipments, and an overwhelming volume of documents that required constant attention. The company implemented RPA to streamline and optimize several areas of its logistics operations: Shipment Deployment:RPA automated the dispatching of shipments, ensuring real-time updates and accurate tracking information. Document Processing:OCR and RPA were used to automatically extract data from invoices, bills of lading, and other shipping documents, reducing the manual input and improving accuracy. Inventory Management:Automation synced inventory data, ensuring stock levels were updated across all systems in real-time and preventing errors in stock tracking. Results: $35K in monthly cost savings by reducing manual labor and improving operational efficiency. 2.2K man-hours saved monthly, allowing staff to focus on more valuable tasks. 22K shipments are deployed monthly, improving throughput and speed of delivery. 45K average documents processed monthly, significantly reducing manual document handling and errors. ## RPA for Telecom Telecom companies manage many service requests, billing updates, and network changes.RPA helps reduce turnaround time and improve service reliability. Typical processes automated: - Service provisioning:Activates new services based on plan and account details. - Customer onboarding:Automates identity checks, data entry, and contract signing. - Billing adjustments:Applies plan changes, refunds, and late fees. - Network alert management:Monitors alerts and escalates based on severity. Benefits: - Faster resolution of customer issues - More accurate billing - Better use of internal resources Case Study: GPS nVISION,a Texas-based company specializing in tracking devices for cars, trailers, and other assets, needed to expedite two vital processes:device and SIM card activation and account deactivation. After analyzing the existing workflows, we implemented an RPA solution that continuously checks for activation requests, automatically sets up tracking devices, and configures user accounts. Similarly, the bot now deactivates unpaid accounts and trackers. The result?The execution time for these processes was reduced by four times, speeding up customer service and operations. RPA Telecom Case Study ## Popular RPA Tools and Their Importance Understanding the tools available in the RPA ecosystem is critical for selecting the right solution for your organization. Here’s an overview of the most popular platforms, what they do, and why they matter: ## UiPath What It Does:It offers a comprehensive and user-friendly platform supporting attended and unattended automation. Its low-code environment makes it accessible to non-technical users while providing robust capabilities for complex workflows. Importance:UiPath’s strong community support, free community edition, and continuous innovation make it a popular choice for organizations looking for rapid deployment and scalability. At Flobotics, UiPath is our go-to RPA technology, allowing us to build customized, scalable automation solutions for clients across industries. Our expertise in UiPath is backed by our UiPath Certification, ensuring that we deliver high-quality implementations with best practices in mind. ## Blue Prism What It Does:Provides a code-free, enterprise-grade RPA platform designed to automate back-office operations. Its drag-and-drop interface and extensive integration capabilities allow organizations to automate tasks across multiple systems. Importance:Blue Prism is particularly favored by large enterprises due to its scalability, strong governance features, and seamless integration with existing systems. ## Automation Anywhere What It Does:Combines traditional RPA with cognitive capabilities such as Natural Language Processing(NLP)and machine learning. It supports both cloud and on-premise deployments and offers tools for developing, deploying, and managing bots at scale. Importance:Automation Anywhere's versatility and ease of use make it ideal for organizations that need both basic and advanced automation features and the ability to handle complex data sets. ## Python What It Does:Python is a powerful scripting language that can be used to build custom automation workflows without traditional RPA tools. Many open-source RPA frameworks, including Robocorp, use Python. Importance:Python is highly customizable–great for businesses needing full automation control. There are no licensing costs; it’s open-source and free to use. Best for data science, AI,and Machine Learning applications, and can integrate with various systems via APIs.Python-based RPA is ideal for developers and businesses needing a tailored automation solution. ## Microsoft Power Automate What It Does:A cloud-based service that automates workflows across various applications and services. It supports both attended and unattended automation and is designed to integrate legacy systems with modern cloud-based applications. Importance:Its seamless integration with the Microsoft ecosystem, flexible workflow design, and AI-driven features make it a versatile tool for organizations looking to modernize their process automation without a steep learning curve. ## IBM Robotic Process Automation What It Does:IBM Robotic Process Automation integrates seamlessly with IBM’s suite of AI and automation solutions. It leverages AI-powered bots to automate business processes, integrate across multiple systems, and improve operational efficiency. Importance:IBM RPA is ideal for enterprises seeking AI-enhanced automation. It offers integration with IBM Watson, which allows it to perform cognitive tasks like data extraction, processing unstructured data, and decision-making. Its scalability and security make it a trusted choice for large organizations with complex automation needs. ## Tungsten Automation(formerly Kofax) What It Does:Tungsten Automation offers an RPA solution that combines robotic process automation with advanced data capture and document processing capabilities. It is designed to handle high-volume tasks such as invoice processing, claims management, and compliance reporting. Importance:Tungsten(formerly Kofax)is known for its powerful document automation features, including Optical Character Recognition(OCR)and document classification. It integrates with legacy and modern systems, making it highly effective in industries with significant documentation needs like finance, healthcare, and insurance. ## OpenBots What It Does:OpenBots is an open-source RPA platform designed for enterprises looking to scale automation while avoiding the high licensing costs associated with traditional RPA solutions. It provides tools for attended and unattended automation and integrates easily with existing systems. Importance:OpenBots’ open-source nature allows businesses to customize their RPA workflows without being tied to costly proprietary platforms. It's ideal for companies seeking cost-effective, scalable automation solutions without sacrificing functionality. ## WorkFusion RPA Express What It Does:WorkFusion RPA Express is a free, full-featured RPA platform that integrates automation, machine learning, and AI capabilities. It’s designed to automate complex tasks involving unstructured data, like document processing and customer service workflows. Importance:WorkFusion RPA Express combines traditional RPA with intelligent automation capabilities. It's ideal for businesses that need process automation and the ability to handle unstructured data, providing a complete automation solution that scales with growing business needs. ## A Step-by-Step Guide to Implementing RPA While RPA offers significant advantages, organizations must address particular challenges to ensure successful deployment. Here’s a strategic, step-by-step guide: - Select an Experienced Vendor - Conduct a Thorough Process Analysis - Educate and Upskill Employees - Start with Pilot Projects - Establish Clear Governance - Plan for Maintenance and Scaling - Engage Stakeholders Early ## How to Select the Perfect Process for Automation? RPA can do a lot, but that doesn’t mean you should throw bots at everything. The best wins come from picking the right tasks. Look for Processes That Are: - Repetitive–Same steps, same order, over and over. - Rule-based–If X,then Y.No decisions needed. - Frequent–Happens every day, not once a month. - Clean–Uses structured inputs like spreadsheets or forms. - Stable–Doesn’t change every two weeks. - Annoying–The kind of task people hate doing manually. What You Should Avoid(for Now): - Anything vague or open-ended. - Processes where people make judgment calls. - Workflows that aren’t documented or change constantly. Start with one or two tasks that tick most of these boxes. You’ll build momentum, show results quickly, and then scale. ## How to Measure your RPA Automation Results? After your bots go live, don’t just trust your gut—track the impact. Here’s what we recommend keeping an eye on: ## Key Metrics to Track for RPA Success These are the core metrics you should measure to assess the effectiveness and value of your RPA implementation. ### Value of Time Gains VTG=(EC–AC)/AC x 100% EC(Employee Costs):Total costs of processes handled by employees, including wages, taxes, and office-related expenses(rent, utilities, etc.). AC(Automation Costs):Costs of processes managed by bots, including license fees, development, hosting, and maintenance. Why It Matters: VTG calculates the cost savings from automation by comparing the costs of employee-delivered processes to bot-delivered ones, providing a key metric for assessing RPA’s ROI. ### Return on Investment(ROI) RPA ROI is calculated using Value of Time Gains(VTG), along with two additional factors: Value of Process Acceleration(VoPA):Measures the financial gain from speeding up processes, like reducing the client onboarding cycle, by calculating the difference in processed clients before and after automation, multiplied by the average gain per client. Value of Error Reduction(VoER):Calculates savings from eliminating errors, such as reduced costs from fixing mistakes manually or fewer lost deals due to errors. RPA ROI=[(VTG*AC + Value of process acceleration + Value of error reduction)–AC]/AC x 100% Where: VTG=Value of Time Gains AC=Automation Costs VoPA=Value of Process Acceleration VoER=Value of Error Reduction Why It Matters: RPA ROI provides a comprehensive view of the financial benefits of automation, considering time savings, process speed, and error reduction, ensuring that automation investments deliver measurable value. ### Gained Productivity This metric tracks the increase in productivity resulting from automation. How to Measure:Gained productivity can be calculated by comparing the time taken to complete processes before and after automation. Why It Matters:This shows how much more efficiently work is being done post-automation, often leading to higher output with fewer resources. ### Process Automation Velocity This metric measures the speed at which business processes are automated. How to Measure:It can be calculated by tracking the number of processes automated over a specific time period. Why It Matters:Faster automation velocity means quicker realization of automation benefits, enabling businesses to scale operations rapidly and handle more tasks. ### RPA Automation Uptime This metric tracks the amount of time that RPA bots are fully operational and performing tasks. How to Measure:Uptime is calculated by dividing the total bot operating time by the total possible operating time. Why It Matters:High uptime means that the automation system is reliable and consistently delivering value, minimizing disruptions and maximizing productivity. ### Downtime Rate Downtime rate measures the percentage of time that RPA bots are not operational due to technical issues or failures. Why It Matters:A lower downtime rate is crucial for maintaining continuous automation operations. High downtime can indicate system instability and affect overall performance. Ultimately, measuring your RPA results allows you to gain actionable insights that can help you drive continuous improvement, achieve greater ROI,and ensure that automation continues to deliver measurable value. The metrics discussed above are some of the primary metrics for tracking RPA success. However, many other important business and technical metrics must be measured to optimize and maintain RPA systems. These include bot performance, uptime, exception handling rates, etc. ## Closing thoughts For beginners, RPA may seem daunting, especially since many misconceptions about the technology prevail, such as the notion that automation bots will render people redundant. By outlining the main concepts related to Robotic Process Automation and demonstrating its strengths, we hope our guide has made RPA much more approachable and transparent. We honestly believe that Robotic Process Automation is a perfect solution for businesses that want to embark on a digital transformation journey but don’t have the budget to invest in experimentation. Unlike other emerging innovations, RPA—when implemented correctly—requires low-cost investment and delivers immediate impact. We recommend starting small to maximize the potential of RPA.Automate one or two key processes before adding more tasks to the pipeline. Once your first bots are up and running, scaling up will be smooth sailing. And you will be ready and eager to take the next step into more advanced intelligent automation. At Flobotics, our in-depth expertise in RPA means we are uniquely positioned to guide your organization through every step of transformation. Whether you’re considering RPA as a product for in-house control or a service for rapid deployment and scalability, we tailor our approach to meet your specific needs and objectives. Let's unlock the full power of automation-get in touch with us today! At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) ### Top RPA Providers in 2026 The following companies are the "Big Three" and their top competitors who dominate the automation market: Provider | Best Known For... | UiPath | The market leader; known for a massive user community and user-friendly "drag-and-drop" design tools. | Automation Anywhere | A cloud-native platform that excels in "Intelligent Automation" (combining RPA with built-in AI). | SS&C Blue Prism | Favored by large, highly regulated enterprises (like banks) for its heavy focus on security and governance. | Microsoft Power Automate | Best for small-to-medium businesses already using the Microsoft 365 ecosystem (Excel, Outlook, etc.). | SAP Build | The go-to choice for companies already running their business on SAP software to automate ERP workflows. | ### Article Summary In summary, Robotic Process Automation (RPA) is a non-invasive software technology that mimics human digital actions to perform repetitive, rule-based tasks with perfect accuracy. By deploying "digital workers," businesses can eliminate human error, operate 24/7, and significantly reduce costs - ultimately allowing their human employees to abandon "grunt work" in favor of high-value, creative strategy. At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### RPA Failures: 10 Most Common Reasons and How to Avoid Them RPA failures: Flobotics' CTO breaks down the 10 most common reasons automation projects fail and how to avoid them. Karl MielnickiJuly 06, 2021 ](https://www.flobotics.io/blog/rpa-failures)[ RPA ### RPA Reloaded: 50+ Robotic Process Automation Statistics to Know in 2026 RPA statistics 2026: 50+ data points on robotic process automation adoption, ROI, and where the technology is headed next. Yana PokoraApril 15, 2025 ](https://www.flobotics.io/blog/rpa-statistics)[ RPA ### Why Your Non-Technical RPA Developer Sucks RPA for non-technical developers: why coding skills still matter and where non-technical RPA developers fall short. Karl MielnickiJune 15, 2021 ](https://www.flobotics.io/blog/rpa-non-technical-developer) [All articles →](https://www.flobotics.io/blog) --- # Key Revenue Cycle Management Metrics | 2026 Canonical: https://www.flobotics.io/blog/revenue-cycle-management-metrics Author: Karl Mielnicki Published: 2025-08-26 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Key Revenue Cycle Management Metrics | 2026 CTO Notes [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Key Revenue Cycle Management Metrics | 2026 [Karl MielnickiCTO & Co-Founder of Flobotics](https://www.flobotics.io/our-editorial-team#mielnicki) Published August 26, 2025Updated September 1, 2026 On this page - [Top Revenue Cycle Management Metrics to Monitor in 2026](#top-revenue-cycle-management-metrics-to-monitor-in-2026) - [1. Denial Rate](#1-denial-rate) - [2. Denials by Category](#2-denials-by-category) - [3. Days in A/R](#3-days-in-a-r) - [4. A/R > 90 Days](#4-a-r-90-days) - [5. Net Collection Rate (NCR)](#5-net-collection-rate-ncr) - [6. Claim Rejection Rate](#6-claim-rejection-rate) - [7. Authorization Approval Rate](#7-authorization-approval-rate) - [8. Eligibility Verification Rate](#8-eligibility-verification-rate) - [9. Coding Accuracy Rate](#9-coding-accuracy-rate) - [10. Patient Collection Rate](#10-patient-collection-rate) - [11. Cost per Claim Processed](#11-cost-per-claim-processed) - [12. Cost per RCM Step](#12-cost-per-rcm-step) - [13. Staff Productivity](#13-staff-productivity) - [14. Bad Debt Rate](#14-bad-debt-rate) - [15. Charge Lag Days](#15-charge-lag-days) - [16. First Pass Resolution Rate (FPRR)](#16-first-pass-resolution-rate-fprr) - [17. Clean Claim Rate](#17-clean-claim-rate) - [18. Denial Overturn Rate](#18-denial-overturn-rate) - [19. Point-of-Service Collection Rate](#19-point-of-service-collection-rate) - [20. No-Touch Claim Rate](#20-no-touch-claim-rate) - [21. Effort per RCM Step](#21-effort-per-rcm-step) - [22. Compliance Audit Pass Rate](#22-compliance-audit-pass-rate) - [23. DNFB (Discharged Not Final Billed)](#23-dnfb-discharged-not-final-billed) - [24. Late Charge Rate](#24-late-charge-rate) - [25. Patient Financial Satisfaction](#25-patient-financial-satisfaction) - [TL;DR – RPA & AI in Action: Automating What Matters Most in RCM](#tl-dr-rpa-ai-in-action-automating-what-matters-most-in-rcm) - [Who Owns Revenue Cycle Management Metrics?](#who-owns-revenue-cycle-management-metrics) - [Final Thoughts: Measure What Matters, Automate What’s Measurable](#final-thoughts-measure-what-matters-automate-whats-measurable) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) In 2025, U.S. healthcare organizations face mounting financial pressures. Operating margins remain tight, bad debt is on the rise, and denials continue to waste billions annually. In this environment, tracking the right [Revenue Cycle Management ](https://www.flobotics.io/blog/revenue-cycle-management)metrics isn’t optional – it’s essential. Metrics tell the whole story: they show how fast you’re collecting, how much revenue you’re losing, how effective your teams are, and even how satisfied your patients are. Executives who rely solely on lagging indicators, such as cash on hand, miss the fundamental levers for sustainable improvement. Even more importantly, modern automation and AI tools now enable healthcare providers to both enhance performance and gain real-time visibility into these metrics. Automation no longer just helps execute tasks – it also empowers healthcare teams with predictive insights, proactive alerts, and cleaner data to inform better decision-making across finance, operations, and patient services. ## Top [Revenue Cycle Management](https://www.flobotics.io/rcm-automation) Metrics to Monitor in 2026 Fig. 01 · RCM metrics 25 metrics Top revenue cycle metrics to monitor - [Bad debt rate](#14-bad-debt-rate)% of charges written off as uncollectible - [Charge lag days](#15-charge-lag-days)Days between service and charge entry - [Denial rate](#1-denial-rate)% of claims denied on first submission - [First pass resolution rate](#16-first-pass-resolution-rate-fprr)% of claims paid without edits or resubmission - [Clean claim rate](#17-clean-claim-rate)% of claims submitted without errors - [Cost per claim](#11-cost-per-claim-processed)Labor and system cost to process one claim - [Net collection rate](#5-net-collection-rate-ncr)% of collectible revenue actually collected - [Days in A/R](#3-days-in-a-r)Average time to collect after service - [A/R over 90 days](#4-a-r-90-days)% of A/R older than 90 days - [Claim rejection rate](#6-claim-rejection-rate)% of claims rejected before reaching payers - [Denial overturn rate](#18-denial-overturn-rate)% of denied claims won on appeal - [Point-of-service collection rate](#19-point-of-service-collection-rate)Patient payment collected at check-in - [Patient collection rate](#10-patient-collection-rate)% of patient responsibility collected - [Authorization approval rate](#7-authorization-approval-rate)% of prior auths approved - [Eligibility verification rate](#8-eligibility-verification-rate)% of patients verified before service - [No-touch claim rate](#20-no-touch-claim-rate)% of claims with zero manual effort - [Effort per RCM step](#21-effort-per-rcm-step)Time or touches per RCM task - [Cost per RCM step](#12-cost-per-rcm-step)Spend on each revenue cycle task - [Staff productivity](#13-staff-productivity)Claims or dollars processed per person - [Coding accuracy rate](#9-coding-accuracy-rate)% of claims coded right first time - [Compliance audit pass rate](#22-compliance-audit-pass-rate)% of claims that pass audit - [DNFB](#23-dnfb-discharged-not-final-billed)Discharged, not final billed - [Late charge rate](#24-late-charge-rate)% of charges posted after deadlines - [Denials by category](#2-denials-by-category)Eligibility, medical necessity, prior auth and more - [Patient financial satisfaction](#25-patient-financial-satisfaction)How patients feel about billing ### 1. Denial Rate Denial Rate is the percentage of submitted claims that are denied by payers on the first submission. It’s calculated as (Number of claims denied on first pass) ÷ (Number of claims submitted) × 100%. For example, if you submit 100 claims and 15 come back denied initially, your denial rate is 15%. This Revenue Cycle Management metric captures how frequently payers are refusing to pay you the first time around. #### Formula (Denied Claims / Total Claims Submitted) × 100 #### Target Industry data indicate that approximately [10–15% of healthcare claims](https://www.statnews.com/2024/05/01/insurance-claim-denials-compromise-patient-care-provider-bottom-lines/) are initially denied on average. World-class performers try to keep denial rates in the single digits, often [under 5%.](https://whitespacehealth.com/blogs/alerts-for-key-rcm-metrics/) Common reasons for denials include coding errors, missing documentation, patient ineligibility (insurance issues), lack of prior authorization, or billing the wrong payer. A rising denial rate can signal issues in front-end processes (such as insurance verification or authorization), mid-cycle issues (coding or charge capture errors), or back-end issues (billing edits). It’s essentially a quality check on your entire revenue cycle. Beyond the financial hit, consider that, according to [Premier Inc.’s 2023 analysis, cited by Fierce Healthcare](https://www.fiercehealthcare.com/providers/providers-potentially-wasted-almost-18b-2023-overturning-claims-denials-premier-estimates), hospitals spent nearly $19–25 billion a year fighting denials, so a high denial rate also means high administrative costs. #### Automation Fix [AI can proactively analyze](https://www.flobotics.io/blog/genai-in-healthcare) large volumes of claim history to uncover [denial trends](https://www.flobotics.io/blog/top-rcm-trends-healthcare) and high-risk services. When integrated into the pre-submission process, AI can flag claims that are likely to be denied and provide feedback for correction. RPA complements this process by verifying claims for completeness, checking payer-specific requirements, and attaching all necessary documentation, which leads to fewer denied claims. ### 2. Denials by Category While not a single-number metric, tracking denials by category involves breaking down your overall denial rate into specific reasons (such as authorization-related, eligibility, coding, medical necessity, etc.) and examining the percentage each category contributes to total denials. For example, you might find that 30% of your denied claims are due to authorization not being obtained, 20% due to coding errors, and 15% due to the patient not being covered, etc. It’s essentially a profile of why you’re getting denials. #### Formula Number of Denials per Category #### Target Many organizations use denial category tracking as a KPI: for instance, aiming to reduce the percentage of denials due to avoidable front-end issues, quarter over quarter. Payers often supply reason codes on EOBs (such as CO-197 for authorization, CO-11 for coding, etc.), and grouping them into categories yields valuable insight. Knowing, for example, that “medical necessity” denials are 10% of your denials might prompt you to ensure better documentation or use of correct diagnosis codes to justify services. #### Automation Fix AI automatically tags denials based on root cause and visualizes trends across departments or service lines. RPA routes these insights to managers for training or workflow adjustments and tracks their resolution. ### 3. Days in A/R Days in A/R is the average number of days it takes for your claims to get paid – effectively the average age of your receivables. It’s calculated by dividing your current accounts receivable by the average daily charges (or collections) over a period. For example, if you have $600,000 in receivables and average $20,000 in charges per day, your Days in A/R is 30. It answers, “On average, how many days from the time you provide a service (or bill it) until you collect the payment?” #### Formula Total Accounts Receivable / Average Daily Charges #### Target A/R Days is a classic liquidity metric. Lower is better – it means you’re converting services into cash faster. Higher A/R days mean cash is tied up and may indicate problems such as slow payer processing, high denial levels (which delay payment), or lagging follow-ups. As a general rule, aiming for [a 30-50 day average in accounts receivable (A/R)](https://cadencecollaborative.com/blog/rcm-metrics/) is common, although this timeframe varies by payer mix and specialty. Many physician practices shoot for <40 days, whereas hospitals with a heavier insurance mix might be in the 40-50 range. If you’re creeping upwards (say 60 days, 80 days), it’s a sign of trouble – possibly lots of aged receivables that might turn into bad debt. #### Automation Fix RPA bots can conduct daily follow-ups on unpaid claims, automatically retrieve claim statuses from payer portals, and trigger reminders or escalations. AI enhances this by predicting which claims are most likely to delay and guiding proactive interventions, optimizing team efforts, and improving collection speed. ### 4. A/R > 90 Days This metric looks at the proportion of your Accounts Receivable that is aged beyond 90 days (or sometimes 120 days). It’s often expressed as a percentage of total A/R. For instance, if you have $1,000,000 in receivables and $150,000 of that is more than 90 days old, then 15% of your A/R is >90. It essentially measures the older, likely harder-to-collect portion of your receivables. Many reports will break aging into 0-30, 31-60, 61-90, >90 day buckets. #### Formula (A/R > 90 Days / Total A/R) × 100 #### Target The older a receivable becomes, the less likely you are to collect it. A/R over 90 days is at high risk of becoming bad debt. In healthcare, timely follow-up is critical because payer contracts often have deadlines for reconsiderations, and patient bills go cold as time passes. Providers strive to keep the >90 days A/R as low as possible, ideally under 15-20% of total A/R, though top performers can be much lower. In fact, some aim for virtually [0% of A/R over 90 days](https://strivanthealth.com/revenue-cycle-management-metrics-that-matter/) aside from truly difficult cases. A high percentage over 90 days indicates bottlenecks or neglect in your collections process – perhaps denials aren’t being worked, or patient bills are not followed up. It’s also an indicator of whether you might face write-offs soon, as balances age out. #### Automation Fix RPA helps by identifying and routing aged claims to dedicated resolution teams, escalating where needed. AI evaluates each account’s likelihood of recovery, allowing your staff to focus on high-probability cases. This targeted strategy prevents unnecessary write-offs and improves cash recovery. ### 5. Net Collection Rate (NCR) Net Collection Rate measures the effectiveness of collecting the revenue that you’re legally and contractually entitled to collect. It’s often defined as payments received divided by the net charges (charges after contractual adjustments) for a given period, expressed as a percentage. In simpler terms, “out of all the money you should have gotten paid (after write-offs for insurance contracts), how much did you actually collect?”. For example, suppose after adjusting for insurance discounts, your clinic had $100,000 in net billable charges last month. If you collected $92,000 of that, your net collection rate is 92%. #### Formula (Payments / Adjusted Charges) × 100 #### Target A high NCR (close to 100%) means you’re collecting nearly all possible revenue. A lower NCR indicates that revenue is being lost due to factors such as denials that were never recovered, patient bills that went unpaid, or other write-offs. Typically, an [NCR above 95%](https://cadencecollaborative.com/blog/rcm-metrics/) is considered excellent, while anything significantly lower (say 85-90%) signals that money is being left on the table. Even a few percentage points drop in NCR can translate into huge dollars for a hospital. This metric excludes approved contractual adjustments (since those aren’t collectible by design), focusing only on collectible revenue. #### Automation Fix AI can identify systemic underpayments, missed charges, and instances where payers are not reimbursing according to the contract. RPA bots can automate the secondary claims process, underpayment appeals, and even the generation of itemized billing corrections, helping you recover more of the revenue already earned. ### 6. Claim Rejection Rate Claim Rejection Rate is the percentage of claims that are rejected by clearinghouses or payers before they are accepted into the adjudication system. Rejections differ from denials: a rejection typically means the claim didn’t pass initial automated checks (perhaps due to invalid data or formatting issues) and must be corrected and resubmitted, whereas a denial means the payer adjudicated the claim and refused payment (often for policy reasons, medical necessity, etc.). If you submit 100 claims and 8 come back almost immediately as rejected (never received by the payer’s processing system), your rejection rate is 8%. #### Formula (Rejected Claims / Total Claims Submitted) × 100 #### Target High rejection rates mean your team is essentially doing double work on a lot of claims. Common causes of rejections include missing patient info, invalid insurance ID numbers, incorrect claim form fields, or technical format errors. A healthy revenue cycle will have a very low rejection rate, often in the low single digits (ideally <2-3%). If you’re seeing something like 10%+ rejection rates, there’s significant room for improvement. Rejections also tie up cash and can contribute to longer A/R days. The difference between a claim rejected in 1 day vs. paid in 14 days is huge for cash flow. #### Automation Fix RPA ensures claims are scrubbed using payer-specific rules and that all required data is present. AI enhances this by continuously learning from past rejections and surfacing patterns, so issues like code mismatches or eligibility errors can be corrected before the claim is submitted. ### 7. [Authorization Approval](https://www.flobotics.io/agents/prior-authorization-automation) Rate The Authorization Approval Rate represents the percentage of cases or services requiring prior authorization that are ultimately approved by payers. For instance, if 100 MRI orders required pre-authorization and 90 were approved (initially or after some back-and-forth), the approval rate is 90%. You can also consider the flip side – the authorization denial rate (how many requested authorizations are denied). This metric zooms in on the front-end insurance approval process. #### Formula (Approved Auths / Total Auth Requests) × 100 #### Target A high authorization approval rate indicates that your team excels at navigating payer requirements and securing approvals. A low rate indicates that either you’re not obtaining necessary approvals or payers are frequently denying requested services. Both are problems: services performed without auth can mean no reimbursement or burdensome retro-authorizations. Tracking this metric is an early warning indicator: if auth approvals drop, you can expect denial rates to rise down the line. #### Automation Fix RPA bots submit authorization requests the moment orders are placed, attach all required documentation, and track responses. AI predicts which services are at higher risk for denial and suggests alternatives when appropriate, reducing denials and delays at the front end. ### 8. [Eligibility Verification](https://www.flobotics.io/agents/eligibility-check-automation) Rate This metric tracks the percentage of patients whose insurance coverage is verified before the time of service (or at least at the time of service). Essentially, out of all scheduled patients, how many did we run an eligibility check on and confirm active coverage and benefits? For example, if 1,000 patients are seen in a month and 950 had their insurance verified in advance, the verification rate is 95%. #### Formula (Verified Patients / Total Scheduled Patients) × 100 #### Target A high eligibility verification rate means your front-end process is solid – you’re catching problems like inactive policies or the need for referrals before the patient is treated. A low rate means a lot of patients are coming in without checks, which is risky – you may only discover coverage issues after submitting a claim (too late). Essentially, 100% is the goal here, though emergencies or walk-ins can make that challenging. Every scheduled encounter should ideally have an eligibility confirmation at least one to two days in advance. #### Automation Fix RPA can automatically verify eligibility during scheduling and at the time of service using payer APIs. AI enhances the process by tracking verification failures over time and identifying recurring issues (e.g., data entry errors, outdated payer info), so they can be corrected systemically. ### 9. [Coding Accuracy](https://www.flobotics.io/rcm-automation) Rate Coding Accuracy Rate measures the correctness of medical coding, often determined by coding audits. For example, if an internal or external audit reviews 100 coded encounters and finds 5 with errors, the coding accuracy rate might be 95%. Alternatively, it can be tracked as an error rate (# of coding errors per number of charts coded). It encompasses elements such as accurate ICD-10 diagnosis codes, CPT procedure codes, modifiers, and adherence to coding guidelines. #### Formula (Accurate Codes / Total Codes Audited) × 100 #### Target A high coding accuracy rate means your coders are assigning codes correctly, which should correlate with fewer coding-related denials and less compliance exposure. It also means you’re capturing full reimbursement (not missing codes that could have been billed). For compliance, many organizations aim for coding accuracy rates in the high 90s. #### Automation Fix AI can interpret clinical notes and suggest the most accurate CPT and ICD codes, even flagging discrepancies in real time. RPA ensures that codes are properly formatted and that the claim package matches documentation before submission. ### 10. Patient Collection Rate The Patient Collection Rate measures the percentage of patient-responsible balances that you collect overall. Unlike the POS rate (which is specifically at the point of service), this metric examines all patient due amounts, whether collected at service or after, versus what was billed to patients. For example, if patients owe $100,000 (after insurance payments) and you ultimately collect $80,000 from them, your patient collection rate is 80%. This metric may also be referred to as the Self-Pay Collection Rate or Patient Pay Rate. #### Formula (Patient Payments / Patient Responsibility) × 100 #### Target If your patient collection rate is low, it directly contributes to the high bad debt rate (#1). It might also indicate issues in the patient billing experience or insufficient follow-up. There isn’t a one-size-fits-all benchmark for this, since specialties vary, but of course, 100% would be ideal (no patient ever defaults). Realistically, hospitals might collect somewhere in the range of 50-70% of patient balances, whereas a well-run practice could achieve a higher rate if it aggressively manages its accounts. #### Automation Fix Automation plays a huge role in improving patient payment completion. AI scores patient payment behavior and segments users based on likelihood to pay. RPA then delivers personalized reminders, enables self-service payment options, and monitors follow-through. Combined, they streamline patient engagement and increase collection rates with less friction. ### 11. Cost per [Claim Processed](https://www.flobotics.io/agents/claims-management-automation) This Revenue Cycle Management metric measures the cost incurred by your organization to process a single claim from start to finish. It’s essentially the cost to collect on a per-claim basis. It factors in all the expenses of the revenue cycle – billing staff salaries, billing software costs, clearinghouse fees, printing/mailing for patient bills, collection agency fees, etc., divided by the number of claims (or encounters) processed. For example, if your clinic spends $50,000 on all billing-related costs in a month and processes 5,000 claims, your cost per claim is $10. #### Formula Total RCM Costs / Number of Claims Processed #### Target A lower cost per claim means you’re collecting money efficiently, with minimal expense. A higher cost might indicate inefficiencies – perhaps overly manual processes or overstaffing, or it could be due to dealing with too many denied claims (which take more effort). According to industry benchmarks, the cost to collect in healthcare can range roughly from 2% to 5% of collections for hospitals (it varies widely). On a per-claim basis, the cost will vary by specialty and complexity, but the goal is always to reduce it without compromising effectiveness. #### Automation Fix Automation is one of the most direct ways to lower this metric. RPA eliminates the need for manual processing across multiple stages of the claim lifecycle (e.g., data entry, validation, follow-up), thereby reducing labor costs. AI helps identify bottlenecks or redundant steps, guiding continuous improvement toward a leaner, more cost-effective revenue cycle. ### 12. Cost per RCM Step Cost per Step is similar to the above, but measures the financial cost associated with each step of the RCM process, rather than time. It involves allocating expenses (primarily staff salaries, but also systems and overhead) to each function – [registration](https://www.flobotics.io/contact), coding, billing, follow-up, etc. – and computing a cost per unit for that function. For example, how much does each eligibility verification cost in terms of staff time and systems? How much does it cost to handle an appeal on average? It’s a granular look at the cost to collect by segment. #### Formula RCM Labor + Tech for Step / Volume of Task #### Target Breaking down the cost by step allows you to see where your revenue cycle is “spending” its resources. Perhaps you discover that the pre-authorization process is particularly expensive per case, maybe because it’s so labor-intensive with lots of phone calls and faxing. Or you find that denial management takes a big chunk of your budget. Understanding this can guide investments; if one area is very costly, that might be your prime candidate for process re-engineering or automation to get a better ROI. #### Automation Fix Granular cost tracking by RCM step reveals hidden inefficiencies. AI helps identify which steps have the highest resource utilization and why. RPA reduces these costs by streamlining operations and allowing teams to accomplish more with fewer resources. ### 13. Staff Productivity Staff Productivity in RCM can be measured in various ways, but a common one is the number of claims (or encounters or accounts) processed per full-time equivalent (FTE) staff in a given time period. For instance, a medical billing office might measure the number of claims each billing specialist processes per day or per hour. You can also track productivity by sub-function, such as claims coded per coder per day or payments posted per poster per hour, etc. Essentially, it gauges how efficiently your team is working. #### Formula (Claims Processed / FTEs) or (Net Collections / FTEs) #### Target Productivity metrics help ensure you have the right staffing levels and that your team is performing well. If one person can handle 100 claims a day and another similar person handles only 60, that’s a disparity to investigate (is it due to training, the complexity of work, or an issue?). Additionally, as you implement process improvements or automation, you can expect productivity per staff member to increase, which provides a way to quantify those gains. #### Automation Fix With automation handling routine tasks, staff are empowered to focus on high-impact areas such as denial resolution and complex billing issues. AI identifies where productivity dips occur (e.g., specific teams or times of day), while RPA streamlines workflows and reduces burnout, ultimately enhancing overall team output. ### 14. Bad Debt Rate Bad Debt Rate is the percentage of revenue that you had to write off as uncollectible. In simple terms, it’s the portion of patient bills or insurance balances that you could not collect and ultimately “give up” on as bad debt. This metric is a direct indicator of revenue leakage. A rising bad debt rate is a major red flag that more patients aren’t paying their bills or that internal collection efforts are faltering. #### Formula (Bad Debt / Gross Patient Revenue) × 100 #### Target An industry [benchmark for bad debt](https://www.mdclarity.com/rcm-metrics/bad-debt-percentage) is around 2–3% of net patient revenue. In other words, for every $100 in revenue, a well-performing hospital might only write off $2–3 as bad debt. If your bad debt rate is higher than that, it means real dollars are slipping away. A high bad debt rate can result from ineffective collection processes, a lack of financial counseling, or economic factors impacting patients. It’s also tightly linked to patient satisfaction – surprise bills or confusing billing can lead patients to ignore bills altogether. #### Automation Fix Automate pre-service [eligibility checks](https://www.flobotics.io/agents/eligibility-check-automation) using [RPA](https://www.flobotics.io/blog/robotic-process-automation) to validate insurance in real time. Use AI to predict payment risks based on patient history and behavior, triggering proactive payment plan offers, charity screenings, or financial counseling workflows. ### 15. Charge Lag Days Charge Lag Days (also called Billing Lag Days or Days to Bill) measure the number of days between the date a service is provided and the date the charges are entered or the claim is submitted for that service. Essentially, it’s how long it takes your organization to get a bill out the door after seeing a patient. #### Formula Date of Charge Entry – Date of Service #### Target A short charge lag (one or two days) indicates an efficient process where clinical documentation, coding, and charge entry are happening quickly. A long lag (e.g., a week or more) often signals process bottlenecks – perhaps providers are late signing charts, coders have a backlog, or there are manual workflow inefficiencies. Best practice is to submit claims [within 24–48 hours of service ](https://strivanthealth.com/revenue-cycle-management-metrics-that-matter/)whenever possible. Some organizations even strive for same-day billing for outpatient encounters. #### Automation Fix Reducing the time between service delivery and charge entry directly improves cash flow. RPA bots can be configured to [automatically extract charge data from EHRs ](https://www.flobotics.io/blog/ehr-implementation-plan)and submit it to the billing system on the same day. AI helps pinpoint root causes of delays — such as incomplete documentation or slow physician sign-off — allowing administrators to target training or process changes effectively. ### 16. First Pass Resolution Rate (FPRR) First Pass Resolution Rate (FPRR) measures the percentage of claims that get paid after the first submission without requiring any edits, re-submissions, or appeals. It is essentially the inverse of having denials or rejections. If out of 100 claims you submit, 85 are paid in full on the first try and the rest needed intervention, your FPRR is 85%. Sometimes this is also called First Pass Payment Rate or First Pass Yield. #### Formula (Clean Paid Claims / Total Claims) × 100 #### Target A high FPRR indicates that your team is getting things right the first time: claims are clean, complete, and compliant, ensuring that payers pay promptly. A low FPRR (and correspondingly high initial denial/rejection rates) means your staff is having to chase fixes and play catch-up on a significant portion of claims, which delays cash and drives up labor costs. Improving FPRR has a direct correlation with faster collections and lower Accounts Receivable. For context, many organizations aim for FPRR in the 90%+ range. In fact, with advanced automation, some organizations have achieved first-pass accuracy rates of 98–99% on claims. Every point increase in FPRR translates to fewer staff touches and a smoother revenue cycle. #### Automation Fix RPA ensures claims are built and submitted accurately the first time, while AI continuously learns from payer behavior to adapt claim preparation accordingly. Improvements here mean faster revenue recognition and lower administrative costs. ### 17. Clean Claim Rate Clean Claim Rate is the percentage of claims submitted that have no errors or issues and are accepted by the payer (or clearinghouse) on first submission. A “clean claim” meets all payer criteria and includes all necessary information so that it doesn’t bounce back as a rejection. For example, if you submit 100 claims and 95 are accepted without any edits, your clean claim rate is 95%. This metric typically focuses on initial submission quality – even before the payer adjudicates for payment, it checks whether your claim passes basic validations. #### Formula (Clean Claims / Total Claims Submitted) × 100 #### Target A high clean claim rate means your billing team (and systems) are doing an excellent job preparing claims. You avoid the time-consuming back-and-forth of corrections and resubmissions. A low clean claim rate indicates frequent claim rejections – perhaps due to missing information (such as patient DOB or insurance ID), incorrect coding, or other errors. Rejected claims usually never even entered the payer’s system for processing; they’re kicked back by clearinghouses or front-end edits. This is wasted effort and time. Clean claim rate is critical because it directly affects cash flow – the cleaner your claims, the faster you get paid. Industry-leading clean claim rates typically exceed [90%](https://whitespacehealth.com/blogs/alerts-for-key-rcm-metrics/). #### Automation Fix RPA bots validate that all necessary patient, provider, and insurance fields are completed and formatted correctly. Meanwhile, [AI tools ](https://www.flobotics.io/blog/ai-rpa-ml-rcm)can identify patterns of missing codes, documentation gaps, or inconsistent inputs, helping your billing team avoid costly errors before the claim even leaves your system. ### 18. Denial Overturn Rate Denial Overturn Rate is the percentage of [denied claims](https://www.flobotics.io/agents/denials-management-automation) that your team successfully overturns and ultimately gets paid. For example, if you had 100 denied claims last month and, through appeals or resubmissions, you got 60 of them paid, your denial overturn (or appeal success) rate is 60%. It essentially measures how effective your back-end team is at recovering revenue from initially denied claims. #### Formula (Overturned Denials / Denials Appealed) × 100 #### Target A high overturn rate (closer to 100%) is great – it means you fight for and win payment on most denials. A low rate means a lot of denials stay unpaid, which could indicate poor follow-up or perhaps that many denials are not appealable (which points back to needing to fix root causes). Interestingly, studies have shown that a large share of denied claims can be overturned. For instance, one analysis found that 60–80% of insurance denials were overturned on appeal [in California](https://www.invensis.net/blog/revenue-cycle-metrics). Improving this rate directly boosts revenue without increasing volume – it’s about capturing what you’ve earned. It also highlights the effectiveness of your denial management team or vendor. #### Automation Fix Every overturned denial is reclaimed revenue. AI supports this by generating personalized appeal letters tailored to the denial reason, using successful language from historical appeal wins. RPA submits these appeals with supporting documentation and tracks their resolution, speeding up turnaround time and maximizing recovery. ### 19. Point-of-Service Collection Rate Point-of-Service (POS) Collection Rate refers to the percentage of patient payments that are collected at the time of service. This typically includes co-pays, deductibles, co-insurance, or self-pay amounts that the patient is responsible for, which are collected during check-in or check-out, before the patient leaves the facility. For example, if a clinic had $50,000 in total patient-responsible charges in a month and they collected $20,000 of that at the visits, their POS collection rate is 40%. #### Formula (POS Collections / Total Patient Payments) × 100 #### Target Industry benchmarks suggest that aiming for around [35% of patient payments](https://www.mdclarity.com/rcm-metrics/point-of-service-pos-collections) to be collected at the point of service is a good target (though some organizations strive for even higher rates). This Revenue Cycle Management metric has grown in importance with the rise of high-deductible health plans; patients now have larger out-of-pocket liabilities, so capturing payments early is crucial. A high POS collection rate indicates effective financial counseling and front-end processes; a low rate might indicate staff reluctance to ask for payment or a lack of price transparency tools. #### Automation Fix AI generates accurate patient responsibility estimates based on benefits data and common reimbursement patterns. RPA delivers these estimates via SMS or web portal and facilitates real-time payments, increasing the likelihood of collecting upfront. ### 20. No-Touch Claim Rate This measures the share of claims that flow through the entire revenue cycle without any human intervention – from charge capture to claim submission to [payment posting.](https://www.flobotics.io/rcm-automation) For example, if out of 5,000 claims, 1,000 were processed end-to-end by automation (no manual touches), that’s 20% no-touch claims. It’s a newer metric that reflects the success of RPA and system integration. #### Formula (No-Touch Claims / Total Claims) × 100 #### Target A higher percentage means your tech systems ([EHR](https://www.flobotics.io/rcm-automation), billing, clearinghouse, etc.) are well-integrated and you’ve automated key steps. For instance, charges auto-flow from clinical systems, edits auto-fix common issues, claims auto-submit, and payments auto-post to the ledger. If a claim can go from service to paid with zero human clicks, that’s as efficient as it gets. It’s challenging to establish a benchmark since this is an evolving field, but some leading systems boast extremely high automation rates – for example, some claim that [80-90% of claims](https://www.flobotics.io/blog/rpa-statistics) can be processed without human involvement using advanced RPA and AI solutions. #### Automation Fix With fully integrated [RPA solutions](https://www.flobotics.io/rcm-automation), claims can be created, scrubbed, submitted, and even followed up on without manual input. AI ensures this workflow adapts to payer policy changes and detects anomalies that may require human oversight. ### 21. Effort per RCM Step This is an internal efficiency metric that examines the amount of staff effort (time) allocated to each step of the revenue cycle per unit of work. For example, how many minutes does it take to register a patient, or to code a chart, or to work a denial on average? It can be measured in minutes per claim for each sub-process, or FTEs dedicated to certain tasks relative to volume. Essentially, it’s breaking down the revenue cycle into steps and assessing productivity at each stage. #### Formula Hours Spent / Task Volume #### Target This Revenue Cycle Management metric aligns closely with cost-per-claim, but it’s measured in time, which can help highlight workflow issues that pure dollar figures might not. It’s especially useful for pinpointing where automation or process improvement could save time. Executives and managers can use it to justify changes: “If we reduce the effort per claim on coding from 5 minutes to 3 minutes through [better software](https://www.flobotics.io/blog/healthcare-software), that’s a 40% productivity gain.” #### Automation Fix RPA eliminates low-value, high-frequency tasks (e.g., data entry, status checks), while AI provides insight into time and resource usage. With both, organizations can continuously improve workflows, reduce team workload, and maintain performance even during staffing fluctuations. ### 22. [Compliance](https://www.flobotics.io/rcm-automation) Audit Pass Rate This metric assesses how well your billing and documentation withstand compliance audits, whether internal or external. It could be measured as the percentage of audited records that have no compliance issues. For instance, if an internal compliance audit reviews 50 encounters and finds 45 were billed and documented correctly with no major issues, the pass rate is 90%. It covers aspects such as proper documentation to support codes, adherence to billing rules (e.g., no unbundling or modifier misuse), and compliance with regulations, including Medicare’s guidelines. #### Formula (Passes / Total Audits) × 100 #### Target A high pass rate suggests your organization is doing things right – you’re likely safe in the event of a payer or government audit. A low pass rate is alarming; it means you are potentially overbilling or otherwise not following rules in a number of cases, which could lead to clawbacks or penalties if caught. Many compliance programs aim for >95% accuracy in documentation and billing compliance on internal audits. #### Automation Fix AI cross-checks submitted claims with payer rules and documentation requirements, while RPA preps audit packets, logs changes, and ensures that documentation is filed and accessible, making audits smoother and more successful. ### 23. DNFB (Discharged Not Final Billed) DNFB stands for “Discharged Not Final Billed.” It refers to patient encounters (usually hospital stays) that have been discharged (the patient left), but the claim hasn’t been billed yet. DNFB Days is often the average number of days accounts remain in that state. Sometimes it’s measured in terms of dollars – how much revenue is tied up in DNFB – or as a count of charts pending billing. Essentially, it’s a measure of your unbilled claims backlog. For example, if a hospital’s average DNFB is 5 days, it means that on average, it takes 5 days after discharge to process the claim. #### Formula Days from Discharge to Final Bill #### Target A low DNFB indicates a tight ship: patients are discharged promptly, charts are coded efficiently, and claims are sent out quickly. A high DNFB (say 10+ days) signals bottlenecks – often in coding or [documentation completion](https://www.flobotics.io/blog/healthcare-document-processing). It can also represent missed revenue if things fall through the cracks. Many aim for DNFB under a week. I’ve seen best practice targets [around 4–6 days for DNFB](https://www.besler.com/insights/key-revenue-cycle-management-metrics-podcast/) in many institutions. Some break it down by inpatient vs outpatient. It also correlates with revenue: if you have a spike in DNFB dollars, that’s a lot of money waiting to be billed. #### Automation Fix A high DNFB rate delays billing and clouds revenue projections. RPA tracks discharge events and monitors whether all documentation and coding are complete. If gaps exist, AI identifies the likely cause and routes tasks to appropriate staff, accelerating the time from discharge to billing. ### 24. Late Charge Rate Late Charge Rate is the proportion of total charges that were not included on the initial claim and had to be billed later (usually via a corrected claim or subsequent billing). These are charges that came in after the bill was initially dropped. It can be expressed as a percentage of total charges or the number of encounters with late charges. For example, if you billed $10 million in charges in a month and $200,000 of additional charges had to be added after the initial billing, that’s a 2% late charge rate. #### Formula (Late Charges / Total Charges) × 100 #### Target High late charge rates might mean revenue is leaking (if you miss the window to bill those charges, you lose money) or that billing is delayed because you wait to get all charges in. Keeping late charges minimal is part of a healthy revenue cycle. A best practice is often <1-2% of total charges as late charges, but it varies. The goal is to catch everything on the first claim whenever possible. #### Automation Fix RPA continuously monitors for missed or delayed entries and alerts responsible departments. AI analyzes trends behind late charges — such as certain departments or times of day — and supports targeted interventions. ### 25. Patient Financial Satisfaction The Patient Financial Satisfaction Score measures how satisfied patients are with the billing and payment aspects of their care experience. This could be measured via patient surveys specifically about billing (for example, on a scale or via Net Promoter Score questions related to billing), or metrics like the number of billing complaints vs. total visits. Essentially, it’s the “patient experience” metric for the revenue cycle. Some organizations include questions in post-visit surveys like “Were you satisfied with the clarity of the billing and payment process?” or “Rate your satisfaction with how your billing was handled.” #### Formula Post-visit survey score (e.g., NPS or custom billing satisfaction survey) #### Target Satisfied patients are more likely to pay promptly. This metric, though somewhat qualitative, is crucial for the hospital’s reputation and even revenue protection. A high patient financial satisfaction score indicates that your revenue cycle is not detracting from the overall care experience, but rather supporting it. #### Automation Fix AI generates accurate cost estimates and tailored payment plans before treatment begins. RPA supports instant payment processing, automated statements, and real-time updates, making the experience clear, convenient, and confidence-building. ## TL;DR – RPA & AI in Action: Automating What Matters Most in RCM Automation is a game-changer for RCM metrics: - RPA bots reduce manual workload and Charge Lag Days – Automating charge capture and entry ensures claims are created faster and more accurately, reducing delays and missed charges. - AI tools predict denials and clean claims before submission – By analyzing patterns in claim errors and payer rejections, AI tools help preempt issues, improving the clean claim rate and FPRR. - Dashboards provide real-time KPI alerts – Custom dashboards, powered by AI, monitor key metrics in real-time, triggering alerts when performance deviates from target ranges. - Automated intake and payment portals enhance patient collections – Digital tools allow patients to verify insurance, receive estimates, and pay upfront, improving eligibility verification, POS collection rate, and patient satisfaction. - Digital document processing and bots streamline prior authorization and appeal – Automation agents extract necessary information from EMRs, populate payer forms, and manage submission and follow-up, shortening turnaround times and increasing approval rates. At Flobotics, we’ve helped healthcare clients: - Achieve 98% clean claims with bots that pre-fill missing data and verify eligibility. - Cut pre-authorization processing times by up to 75% through automated routing. - Automate 90% of back-end claim tracking, freeing staff for complex exceptions. Whether you’re targeting faster A/R turnover, fewer denials, or a more satisfied patient base, automation can make your metrics work for you, not against you. ## Who Owns Revenue Cycle Management Metrics? Effective revenue cycle management is a team sport. Different roles in a healthcare organization will care about different metrics (though all ultimately aim for the same goal of financial stability and compliance). Let’s map out who “owns” or is primarily concerned with various Revenue Cycle Management metrics: Fig. 02 · RCM metrics Who owns what Who owns which RCM metrics - CFO - Bad debt rate - Net collection rate, days in A/R - A/R over 90 days - Effort and cost per RCM step - Cost per claim - Director of RCM - Denial rate - Clean claim rate - Charge lag days - First pass resolution rate - Claim rejection rate - Denial overturn and no-touch claim rates - Denials by category - Patient financial services - Point-of-service collection rate - Patient collection rate - Eligibility verification rate - Patient financial satisfaction - Authorization approval rate - Coding and billing managers - Staff productivity - Coding accuracy rate - DNFB - Late charge rate - Compliance officer - Compliance audit pass rate ## Final Thoughts: Measure What Matters, Automate What’s Measurable RCM success is about transitioning from a reactive to a proactive approach. With the right KPIs, your organization gains visibility to identify and address leaks, enhance collections, and improve both staff and patient experiences. Don’t drown in reports. Focus on the metrics that tie directly to cash, compliance, and care. And when you’re ready to free your team from manual grind, Flobotics is here to help you build an automated RCM engine that works 24/7. Want to see how RPA and AI can [improve your Revenue Cycle Management ](https://www.flobotics.io/rcm-automation)metrics? [Reach out to us.](https://www.flobotics.io/rcm-automation) #### Like the article? Spread the word Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byKarl Mielnicki CTO & Co-Founder of Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RCMAIHealthcare ### RCM Statistics | 2026 Overview RCM statistics for 2026: denial rates hover near 5% and cost-to-collect keeps rising as manual processes lose ground. See the data. Jędrzej SzymulaJanuary 07, 2026 ](https://www.flobotics.io/blog/rcm-statistics-overview)[ RCMHealthcare ### Revenue Cycle Management (RCM) in Healthcare Revenue cycle management, explained: how US hospitals and practices stay compliant with payer policy and keep cash flow steady in 2026. Bart TeodorczukSeptember 30, 2024 ](https://www.flobotics.io/blog/revenue-cycle-management)[ RCMAIHealthcare ### Top RCM Trends | 2026 Top RCM trends for 2026: what healthcare finance leaders at Deloitte, HFMA, and beyond are prioritizing to strengthen revenue cycles. Karl MielnickiNovember 24, 2025 ](https://www.flobotics.io/blog/top-rcm-trends-healthcare) [All articles →](https://www.flobotics.io/blog) --- # We saved $2 Million from a 50% improvement for PRMG using UiPath! Canonical: https://www.flobotics.io/blog/flobotics-prmg-loan-processing-rpa-automation Author: Jędrzej Szymula Published: 2025-08-07 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/We saved $2 Million from a 50% improvement for PRMG using… [AI](https://www.flobotics.io/blog?category=ai)[RPA](https://www.flobotics.io/blog?category=rpa) # We saved $2 Million from a 50% improvement for PRMG using UiPath! [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published August 07, 2025Updated September 1, 2026 Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) When [Paramount Residential Mortgage Group (PRMG)](https://www.prmg.net/) saw a massive surge in loan requests, their manual systems couldn't keep pace. Processing a single loan was taking weeks or even months, hampered by inconsistent data and human error. Flobotics stepped in to bridge the gap between their fragmented systems and modern efficiency. ‍"Our work with Flobotics helps facilitate the process. It leverages the capabilities of different systems to make it happen, as no individual system has the capability on it's own. We're very satisfied with their work." We didn't just provide a tool; we analyzed the entire mortgage lifecycle to break down complex workflows into sustainable automated subprocesses. Our agile approach allowed us to deploy robots with surgical precision. ‍"Within very short-term working sessions, they're able to automate the steps I communicate to them." By automating six core tasks - from retrieving disclosure packages to entering payment data - we transformed their daily operations. The results were immediate and measurable. The infrastructure now averages 550 automated tasks daily, saving 40 hours of manual labor every 24 hours. This efficiency led to a 50% improvement in daily underwriter productivity, which translates to $2 million in direct savings. ‍"With help from UiPath Silver Partner Flobotics, automated loan processing gives brokers near real-time data access and is saving PRMG millions of dollars." Beyond the immediate $1.2 million in labor savings expected over the first 36 months, the project achieved a staggering 6:1 ROI, proving that strategic automation is the ultimate multiplier for the mortgage industry. You can read the entire entry here: [Using UiPath, Flobotics Shows PRMG How to Save on Loan Processing with RPA](https://www.uipath.com/resources/automation-case-studies/prmg) Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ AIRPA ### We are a "Top Workday Implementation Partner for 2026" according to SuperbCompanies! Flobotics named a Top Workday Implementation Partner for 2026 by SuperbCompanies, ranked among 49 vetted firms for delivery and optimization results. Jędrzej SzymulaApril 05, 2026 ](https://www.flobotics.io/blog/flobotics-superbcompanies-top-workday-implementation-company-2026)[ RPAAI ### We Are Among the Top Business Consulting Companies in the USA for 2026! Flobotics named a top business consulting company in the USA for 2026 by Selectedfirms - recognized for business growth and strategy expertise. Jędrzej SzymulaJanuary 26, 2026 ](https://www.flobotics.io/blog/flobotics-top-business-consulting-companies-2026)[ RPAAI ### Top Software Development Company in Indiana? Yes! According to DesignRush Flobotics named a top Indiana software development company by DesignRush - see why we made the list among leading US automation and RPA firms. Jędrzej SzymulaJanuary 29, 2026 ](https://www.flobotics.io/blog/flobotics-designrush-top-software-company-indiana) [All articles →](https://www.flobotics.io/blog) --- # 10 Benefits of Artificial Intelligence in Healthcare Canonical: https://www.flobotics.io/blog/benefits-artificial-intelligence-healthcare Author: Bart Teodorczuk Published: 2025-07-22 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/10 Benefits of Artificial Intelligence in Healthcare [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RPA](https://www.flobotics.io/blog?category=rpa) # 10 Benefits of Artificial Intelligence in Healthcare [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published July 22, 2025Updated September 1, 2026 On this page - [The Role of Artificial Intelligence in Healthcare Today](#the-role-of-artificial-intelligence-in-healthcare-today) - [10 Tangible Business Benefits of AI in Healthcare](#10-tangible-business-benefits-of-ai-in-healthcare) - [1. Reduced Administrative Costs](#1-reduced-administrative-costs) - [2. Faster Revenue Collection](#2-faster-revenue-collection) - [3. Fewer Billing Errors and Claim Denials](#3-fewer-billing-errors-and-claim-denials) - [4. Improved Staff Efficiency](#4-improved-staff-efficiency) - [5. Enhanced Patient Experience](#5-enhanced-patient-experience) - [6. Increased Compliance & Audit Readiness](#6-increased-compliance-audit-readiness) - [7. Accelerated Prior Authorization Approvals](#7-accelerated-prior-authorization-approvals) - [8. Lower Risk of Burnout Among Admin Staff](#8-lower-risk-of-burnout-among-admin-staff) - [9. Improved Data Accuracy Across Systems](#9-improved-data-accuracy-across-systems) - [10. Scalability Without Hiring](#10-scalability-without-hiring) - [Beyond AI: How RPA + GenAI + Agentic AI Deliver Full Healthcare Automation](#beyond-ai-how-rpa-genai-agentic-ai-deliver-full-healthcare-automation) - [End-to-End Prior Authorization Handling](#end-to-end-prior-authorization-handling) - [Claims Validation and Submission](#claims-validation-and-submission) - [EHR Updates from Scanned Documents](#ehr-updates-from-scanned-documents) - [AI in Healthcare Isn’t a Maybe – It’s a Must](#ai-in-healthcare-isnt-a-maybe-its-a-must) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Artificial intelligence is rapidly transforming how healthcare organizations operate. No longer limited to cutting-edge diagnostics or research, AI is now streamlining everyday workflows in hospitals, clinics, and back offices. For healthcare executives facing rising costs and staff burnout, AI offers tangible solutions. Below, we explore the current role of [AI in healthcare](https://www.flobotics.io/blog/genai-in-healthcare) and 10 concrete business benefits it delivers – from reducing administrative costs to improving patient experience – with real examples and recent case studies. Fig. 01 · AI in healthcare 10 benefits 10 AI benefits at a glance - [Reduced administrative costs](#1-reduced-administrative-costs) - [Faster revenue collection](#2-faster-revenue-collection) - [Fewer billing errors and denials](#3-fewer-billing-errors-and-claim-denials) - [Improved staff efficiency](#4-improved-staff-efficiency) - [Enhanced patient experience](#5-enhanced-patient-experience) - [Increased compliance and audit readiness](#6-increased-compliance-audit-readiness) - [Accelerated prior authorization approvals](#7-accelerated-prior-authorization-approvals) - [Lower risk of burnout among admin staff](#8-lower-risk-of-burnout-among-admin-staff) - [Improved data accuracy across systems](#9-improved-data-accuracy-across-systems) - [Scalability without hiring](#10-scalability-without-hiring) ## The Role of Artificial Intelligence in Healthcare Today AI’s footprint in healthcare has expanded far beyond radiology reads or clinical decision support. Modern AI systems are being applied across the entire revenue cycle, including compliance checks and administrative workflows. Roughly a quarter of all healthcare spending is allocated to administrative tasks, and experts estimate that automation could save [25–30% of those costs](https://www.citigroup.com/global/insights/healthcare-admin-costs-how-ai-can-ease-the-pain-). This translates to tens of billions of dollars in potential savings by using AI to handle billing, claims, and paperwork. These efficiency gains are crucial as providers face financial pressures and strive to achieve more with limited resources. Equally important is the rise of AI “agents” and generative AI in healthcare. Unlike earlier narrow AI tools, generative AI and agentic AI can autonomously perform multi-step tasks and interact with systems and people in natural language. AI agents function like digital employees, utilizing large language models to comprehend context and subsequently taking action (e.g., booking an appointment or submitting a form) without requiring human intervention. This new generation of AI goes beyond offering insights – it takes initiative in executing tasks, which could be a game-changer for healthcare operations. These advancements come at a critical time, as healthcare organizations are under intense pressure from workforce burnout, rising costs, and inefficiencies. Clinicians today spend nearly [28 hours per week](https://www.fiercehealthcare.com/ai-and-machine-learning/innovaccer-introduces-ai-agents-providers-automate-scheduling-patient) on administrative tasks (with clerical staff spending even more). It’s no surprise that over 90% of physicians say excessive paperwork contributes to burnout. At the same time, labor shortages loom – a deficit of 100,000 healthcare workers is projected by 2028. AI can help alleviate these challenges by offloading repetitive work and augmenting the existing workforce. In a recent AMA survey, [57% of physicians](https://www.ama-assn.org/practice-management/digital-health/physicians-greatest-use-ai-cutting-administrative-burdens) said automating administrative burdens is the biggest opportunity for AI in healthcare, far outpacing other uses. In short, AI is evolving into a strategic operational tool in healthcare, not only improving clinical care but also optimizing business processes to reduce burnout and enhance the bottom line. ## 10 Tangible Business Benefits of AI in Healthcare Let’s delve into ten specific, tangible benefits that AI (including RPA, generative AI, and autonomous agents) is delivering for healthcare organizations. These benefits aren’t theoretical – many are already being realized in hospitals and clinics today, as illustrated by case studies and real-world deployments: ### 1. Reduced Administrative Costs By automating labor-intensive processes, AI dramatically cuts overhead. Once done manually, tasks like data entry, billing code assignment, and [claims triage](https://www.flobotics.io/agents/claims-management-automation) can be handled by AI-powered bots at a fraction of the cost. For instance, AI [document processing](https://www.flobotics.io/blog/automated-document-processing) can ingest forms or faxes and automatically input the data into EHRs or [billing systems,](https://www.flobotics.io/blog/how-to-build-automated-medical-billing-system) eliminating the need for human effort. Industry analyses suggest automating administrative workflows could save healthcare organizations around [25%–30% of their admin costs](https://www.citigroup.com/global/insights/healthcare-admin-costs-how-ai-can-ease-the-pain-). #### Real-World Application: Consider [prior authorization](https://www.flobotics.io/agents/prior-authorization-automation) paperwork: traditionally, staff had to gather clinical info, fill out forms, and follow up repeatedly – a slow process prone to delays. An AI “agent” can now handle prior auth end-to-end, extracting patient data, populating the request, and even navigating payer portals for status updates. One healthcare platform that automated its prior authorizations saw processing delays virtually eliminated, as the AI system handled the paperwork from start to finish without human intervention. The result is lower labor expenditure on routine tasks and more time available for staff to focus on higher-value work. ### 2. Faster Revenue Collection AI helps healthcare providers get paid faster by [streamlining the revenue cycle](https://www.flobotics.io/rcm-automation). Intelligent automation can [instantly verify insurance eligibility,](https://www.flobotics.io/agents/eligibility-check-automation) scrub claims for errors, and submit them more quickly to payers. On the back end, AI tools monitor payer responses and help resubmit or correct claims rapidly, reducing the accounts receivable days. By reducing manual bottlenecks, hospitals experience improved cash flow. #### Real-World Application: A hospital in Louisiana utilized AI-driven RPA to automate its billing and prior authorization processes, resulting in a [15% increase in collected payments](https://www.jorie.ai/post/prior-authorization-denials-reduced-to-0-21-how-rpa-is-transforming-healthcare) due to faster processing. In dollar terms, that meant an additional $2.28 million in cash flow, simply by getting claims approved and paid sooner. Faster submissions and fewer delays result in revenue arriving weeks sooner than before. In an industry where margins are thin, these cash acceleration benefits of AI directly impact the bottom line. ### 3. Fewer Billing Errors and [Claim Denials](https://www.flobotics.io/agents/denials-management-automation) Minor errors or omissions in claims cost healthcare providers billions in denied or delayed reimbursements. AI can act as a safeguard by auditing claims for accuracy before they are released. [Machine Learning](https://www.flobotics.io/blog/robotic-process-automation-vs-machine-learning) models, trained on historical billing data, can flag missing information or likely coding mistakes that would trigger a denial. They can also detect patterns – for instance, if certain procedures are often denied unless accompanied by specific documentation, the AI can alert staff to attach the necessary files. This proactive error-checking means cleaner claims and higher first-pass acceptance rates. #### Real-World Application: A hospital automated its claims and prior-authorization checks, it drove its authorization denial rate down to just 0.21%. Out of over 3,700 prior auth requests handled by the AI, only 44 needed manual follow-up – an almost 99% approval success rate. By catching mistakes and ensuring completeness, AI reduces the costly back-and-forth of rework and appeal, leading to far fewer denials. ### 4. Improved Staff Efficiency AI and automation technologies serve as a digital workforce, taking on the repetitive tasks that burden healthcare staff. [Robotic Process Automation (RPA)](https://www.flobotics.io/blog/robotic-process-automation) bots serve as tireless digital assistants, logging into systems, transferring data, and performing routine tasks and clicks around the clock. Meanwhile, generative AI “copilots” can assist human employees with tasks such as drafting emails, populating forms, or navigating complex software using voice commands. The net effect is that employees can accomplish more in less time, focusing on complex cases while the “digital workers” handle the busywork. Consider medical billing teams: instead of spending hours each day on copying data between an [EHR](https://www.flobotics.io/blog/ehr-implementation-plan), a clearinghouse website, and an Excel sheet, an RPA bot can do it in minutes. Staff are then free to focus on resolving tricky denial cases or improving patient outreach. #### Real-World Application: Clinicians and office staff currently waste [dozens of hours on admin tasks ](https://www.fiercehealthcare.com/ai-and-machine-learning/innovaccer-introduces-ai-agents-providers-automate-scheduling-patient)weekly, but organizations that implement automation have recouped most of that time. In one case, we at Flobotics helped a [Pain Treatment Center of America](https://www.ptcoa.com/) automate its insurance claims processing; the result was the work equivalent of 4 full-time employees (FTEs) freed up per month, and the provider achieved 100% ROI on the project in just 23 days. This kind of efficiency gain means that existing staff can handle higher volumes without experiencing burnout, or the organization can expand its services without incurring proportional increases in headcount. ### 5. Enhanced Patient Experience AI is also making a positive impact on the patient side of healthcare. Through [AI-powered chatbots](https://www.flobotics.io/blog/chatgpt-for-healthcare) and virtual assistants, patients can get 24/7 support and faster service. Routine inquiries – “How do I refill my prescription?” or “What’s my copay for an MRI?” – can be answered instantly by a chatbot on the clinic’s website or patient app. These AI assistants can also help patients [schedule appointments](https://www.flobotics.io/contact) online, complete intake forms before a visit, and receive reminders or follow-up instructions in a natural language. The benefit is that patients spend less time on hold or waiting for call-backs, and more time receiving actual care. In clinics that have implemented AI-driven scheduling and Q&A bots, wait times have dropped and patient satisfaction has climbed because needs are addressed promptly. Moreover, by reducing paperwork and bureaucratic delays, AI indirectly improves the patient experience – clinicians have more time to spend interacting with patients rather than doing clerical work, and approvals for care (such as prior authorization for a specialist visit) come through faster. #### Real-World Application: A 2024 survey found that [57% of doctors expect AI](https://www.ama-assn.org/practice-management/digital-health/physicians-greatest-use-ai-cutting-administrative-burdens) to improve patient convenience and access, and over half believe it will also enhance care coordination and safety. From a patient’s perspective, healthcare that runs on AI in the background feels smoother and more responsive, which greatly improves their overall experience. ### 6. [Increased Compliance](https://www.flobotics.io/rcm-automation) & Audit Readiness [Compliance](https://www.flobotics.io/blog/hipaa-compliance-rpa) is a critical concern in healthcare administration – mistakes in coding, [billing](https://www.flobotics.io/blog/how-to-build-automated-medical-billing-system), or privacy protocols can result in substantial penalties and fines. AI can act as a compliance sentinel by tracking documentation and ensuring that every process step is logged and follows regulations. For example, an AI system can automatically check that a claim has the necessary ICD-10 codes and physician signatures before submission, or that a patient consent form is on file as required. It can also monitor for anomalies that might indicate fraud or errors (such as an unusually high number of units billed for a certain drug) and flag them for review. These continuous checks mean fewer compliance slip-ups and easier audits. Agentic AI workflows are particularly valuable in this context – they can enforce standardized procedures every time, thereby reducing variability. All actions taken by bots are recorded in detailed logs, creating an audit trail that auditors can follow easily. #### Real-World Application: A hospital network utilized AI to ensure that every [insurance claim](https://www.flobotics.io/blog/insurance-claims-processing-rpa-automation-use-cases) matched the medical record and payer policy. This not only averted claim rejections but also meant that if an external auditor came knocking, the documentation was already sorted and accessible. Automation providers like Flobotics design solutions with healthcare regulations in mind – their RPA bots are built to be [HIPAA-compliant](https://www.flobotics.io/blog/compliance-automation) and secure by default. By having AI monitor compliance checkpoints, organizations minimize the risk of costly fines and can demonstrate their diligence to regulators with minimal additional effort. ### 7. Accelerated Prior Authorization Approvals Prior authorization is famously one of the most time-consuming and frustrating administrative processes in healthcare. Traditionally, a staff member might spend 20–30 minutes filling out a prior authorization request, fax it to the insurer, and then spend days chasing the approval, sometimes only to find out that additional information is needed, restarting the cycle. AI is changing this dramatically. An AI-powered prior auth solution can automatically read the patient’s medical records (to pull the necessary clinical data), generate the authorization request, submit it electronically, and even interact with payer systems or websites to push it through. By doing this in a matter of minutes – and following up in real-time – AI can reduce prior authorization turnaround from days to mere hours. #### Real-World Application: One case study showed that after implementing RPA for prior authorizations, a hospital reduced the typical [approval time by 70%](https://www.sprypt.com/blog/prior-authorization-software-electronic-solutions?utm_source=chatgpt.com) and saw a significant decrease in denial rates, as the automated system ensured that all necessary data was included upfront. By accelerating approvals, AI reduces the infamous administrative bottleneck that prior authorization represents, benefiting both patients and providers. ### 8. Lower Risk of Burnout Among Admin Staff Replacing repetitive manual tasks with AI isn’t just a cost-saving tactic – it’s also a workforce wellness strategy. Administrative staff in billing, scheduling, and records departments often face high volumes of mind-numbing tasks, which can lead to stress and job dissatisfaction over time. By offloading tasks such as data entry, form filling, or copying information between systems, AI helps make workloads more manageable. Employees can then engage in more meaningful work (such as interacting with patients or solving complex issues), which is inherently less draining than doing robotic tasks all day. This has a direct impact on morale and burnout rates. In surveys, [54% of physicians](https://www.ama-assn.org/practice-management/digital-health/physicians-greatest-use-ai-cutting-administrative-burdens) said they believe AI could help alleviate stress and burnout by easing their administrative burden, and the same principle applies to non-clinical staff. We already know that excessive administrative workload is a top driver of burnout in healthcare, so any technology that reduces this load will improve staff well-being. Indeed, hospitals that have embraced AI report higher retention in roles that were previously high-turnover, because employees are no longer just “paper-pushers” and feel their skills are better utilized. Fewer burnt-out employees also means better service quality and fewer errors, creating a positive cycle. In short, AI automation saves money and helps people avoid tedious tasks. ### 9. Improved Data Accuracy Across Systems Healthcare relies heavily on data, including patient records, billing information, and lab results, and any errors in this data can have serious consequences. AI enhances data accuracy by reliably transferring and translating information between systems, eliminating human typos and oversight gaps. [Generative AI](https://www.flobotics.io/blog/genai-in-healthcare) and NLP (Natural Language Processing) models can even extract structured data from unstructured sources (like a PDF lab report or a physician’s free-text notes) with high precision, ensuring that each system ([EHR](https://www.flobotics.io/blog/electronic-health-records-rpa), billing, scheduling, etc.) has consistent and correct information. This reduces the common problem of mismatched records (for example, a patient’s address or insurance info being different in the EHR vs. the billing system). Moreover, AI validation can cross-check data for consistency – if a patient’s recorded age and birthdate don’t match, the system can automatically flag the discrepancy. By keeping data clean and synchronized, AI prevents downstream errors such as [claim denials](https://www.flobotics.io/agents/denials-management-automation) (due to data entry mistakes) or even medical errors (due to outdated patient info). #### Real-World Application: In one [automation project,](https://www.invensis.net/blog/impact-of-ai-on-medical-billing?utm_) an AI system extracted data from physicians’ notes and automatically entered diagnoses and billing codes into the system, resulting in significantly fewer coding errors compared to manual entry. Jorie AI employed a similar approach for a hospital’s billing, utilizing AI-driven verification to ensure all fields were accurate, which significantly minimized errors and improved claim acceptance rates. In summary, AI serves as a diligent editor for healthcare data, considerably enhancing accuracy and integrity across interconnected systems. ### 10. Scalability Without Hiring Perhaps one of the most significant business benefits of AI in healthcare is the ability to scale up operations without a proportional increase in staff. Traditionally, if a medical group’s volume of patients or claims doubled, they might need to hire many new employees to handle the extra workload. But AI-driven automation allows organizations to handle greater volumes 24/7 with minimal additional cost. Need to process 1,000 claims tonight instead of 100? No problem – a fleet of software bots can be deployed in the cloud to tackle the load overnight, something human staff working 8-hour shifts could never do. These AI “workers” don’t take holidays, breaks, or sick leave, and they maintain high accuracy at high speeds. Moreover, the ROI on automation tends to improve with scale. #### Real-World Application: The initial investment to set up an AI or RPA solution can be quickly recovered through efficiency gains. According to industry analyses, the expected return on investment from RPA projects ranges from [30% to 200% in the first year ](https://www.flobotics.io/blog/rpa-statistics)and can reach as high as [300,000% ROI over several years](https://www.flobotics.io/case-studies/t-bank-automation). In one notable case, a provider automated its billing process and achieved a full return on investment within one month. After that, every extra claim handled by the bots was pure benefit. For healthcare organizations seeking to expand or better manage existing demand, AI provides a cost-effective means of scaling capacity without the challenges of recruiting, training, and retaining additional staff. Fig. 02 · AI in healthcare Before and after Before AI vs with AI When AI handles the routine, clinicians can focus on patients. Before AI - 01Endless paperwork - 026+ hours a day in the EHR - 0345-minute insurance calls - 04Missed patient risks - 05Nurse burnout With AI - 01Auto-generated clinical notes - 0241% less documentation time - 034× faster insurance verification - 04Early alerts for sepsis and deterioration - 05Virtual assistants for routine care Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Beyond AI: How RPA + GenAI + Agentic AI Deliver Full Healthcare Automation It’s essential to recognize that “AI in healthcare” is not a single, monolithic tool – it’s a combination of technologies working together. Today’s most powerful automation solutions blend [Robotic Process Automation](https://www.flobotics.io/blog/ai-rpa-ml-rcm), [Generative AI](https://www.flobotics.io/blog/genai-in-healthcare)[,](https://www.flobotics.io/blog/genai-in-healthcare) and Agentic AI (autonomous AI agents). Each plays a distinct role, akin to parts of a team: - RPA acts as the hands, executing tasks and moving data between systems; - Generative AI serves as the brain, understanding language, reading documents, and generating human-like responses. - Agentic AI is the orchestrator or operator, autonomously deciding what actions to take and coordinating the RPA bots and AI models towards a goal. [UiPath](https://www.uipath.com/) (a leader in automation) [describes this synergy well](https://keypointintelligence.com/keypoint-blogs/agentic-ai-ushers-in-new-era-of-autonomous-action#:~:text=Orchestration%20with%20RPA): the agentic AI provides the “reasoning and planning” intelligence, while RPA bots are the body that carries out the plan. Together, this trio can handle complex workflows that used to require multiple humans and decision points. Crucially, the agentic AI can adapt on the fly – if one step in the process fails or an exception occurs, it can re-plan and try an alternative path, much as a human would. This means even judgment-intensive or multi-step processes can be automated end-to-end, not just the simplistic tasks. Fig. 03 · Automation Key differences RPA vs generative AI vs agentic AI Technology | Role | What it does | Healthcare example | RPA | The hands | Carries out tasks and moves data | Submits claims into payer portals | Generative AI | The brain | Understands context; extracts and generates data | Extracts diagnoses from scanned clinical notes | Agentic AI | The operator | Makes decisions and runs end-to-end workflows | Handles a whole prior authorization, from reading the data to working in the payer site | What kinds of healthcare workflows can this combination tackle? Many high-impact use cases are emerging, for example: ### End-to-End [Prior Authorization](https://www.flobotics.io/agents/prior-authorization-automation) Handling An agentic AI can intake a prior authorization request (via an email or PDF form), use generative AI to read and extract required patient info and clinical notes, then invoke RPA bots to submit the request in the insurer’s portal and continuously check status. Once approved, it can notify the care team. This end-to-end automation relieves staff from days of follow-ups. ### [Claims Validation and Submission](https://www.flobotics.io/agents/claims-management-automation) Before a claim is filed, generative AI can review clinical documentation to verify that the billed services are accurately documented. The agent then uses RPA to enter the claim into the billing system or payer site. If any discrepancies or likely denial reasons are detected, they are flagged. This results in [near-instant claim submission](https://keypointintelligence.com/keypoint-blogs/agentic-ai-ushers-in-new-era-of-autonomous-action#:~:text=interactions) with high accuracy, drastically reducing denials and manual rework. Process automation ROI calculator See what automating a process could save you in a few minutes. [Calculate ROI →](https://www.flobotics.io/roi-calculator) ### [EHR Updates](https://www.flobotics.io/rcm-automation) from Scanned Documents RPA bots can watch a folder for incoming documents (e.g, lab results, referral letters). When a new document arrives, a generative AI model extracts key data (patient ID, findings, provider notes). The agentic AI then determines where that data should be sent – for example, creating a new lab result entry in the EHR and updating the patient’s record – and directs RPA bots to input the information into the EHR, ensuring all systems are up to date without requiring manual data entry. These are just a few examples. In practice, RPA, GenAI, and Agentic AI combinations can automate any rules-based workflow that requires an understanding of unstructured data or adaptive decision-making. This is how healthcare organizations can leverage AI: not as a piecemeal tool, but as a holistic automation layer across their operations. By integrating robotic precision, AI, and autonomous coordination, hospitals can achieve levels of efficiency and accuracy that were previously unattainable. It’s a future where much of the “busy work” in healthcare is handled by digital assistants, while human professionals focus on care, strategy, and innovation. ## AI in Healthcare Isn’t a Maybe – It’s a Must The benefits of artificial intelligence in healthcare aren’t just buzzwords or beta tests anymore — they’re tangible advantages already delivering ROI for hospitals and clinics. From accelerating prior authorizations to reducing burnout and scaling operations without hiring, AI has become a strategic asset for executives navigating cost pressure and workforce strain. However, realizing these benefits requires more than technology — it requires a partner who understands healthcare from the inside out. That’s where [Flobotics](https://www.flobotics.io/) comes in. As a UiPath-certified team specializing in healthcare automation, they bring HIPAA-compliant, fast-to-implement RPA and [AI solutions tailored to your workflows](https://www.flobotics.io/). From day one value to long-term scalability, we help healthcare organizations stop surviving and start operating smarter, powered by automation. Let’s [schedule a call!](https://www.flobotics.io/rcm-automation) #### Like the article? Spread the word Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Axpo | $186,000 of profit in year one Canonical: https://www.flobotics.io/blog/axpo-automation Author: Bart Teodorczuk Published: 2025-07-22 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Axpo | $186,000 of profit in year one [RPA](https://www.flobotics.io/blog?category=rpa) # Axpo | $186,000 of profit in year one [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published July 22, 2025Updated September 1, 2026 On this page - [Overview](#overview) - [Key metrics](#key-metrics) - [Client](#client) - [The challenge](#the-challenge) - [Solution](#solution) - [The outcome](#the-outcome) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Overview Client: Axpo. Location: Poland & Switzerland. Industry: Green energy (renewables and gas). The project was delivered by a team consisting of a Tech Coordinator, Senior RPA Developer, Agile Coach, and Project Manager. Technology used: UiPath. Timeframe: one year and ongoing. ## Key metrics The engagement resulted in 6.18 FTEs saved, $186,000 of profit generated in the first year, a 147% return on investment, approximately 54,000 automated actions per month, and an average bot accuracy exceeding 90%. ## Client Axpo is Switzerland’s largest producer of renewable energy and an international leader in energy trading and the marketing of solar, wind, and gas power. ## The challenge We were recommended to Axpo as a process automation agency by our technology partner UiPath, who were familiar with the scale and complexity of projects we had delivered previously. Axpo was experiencing rapid growth that existing processes could not support, relied on manual workflows in billing and switching departments that were no longer scalable, and operated under strict regulatory requirements across multiple energy markets. While both UiPath and Power Automate were initially considered, UiPath was selected due to its superior handling of complex processes and stronger orchestration capabilities. Axpo also brought a backlog of automation ideas, which were validated during workshops before development began. ## Solution To address these challenges, we built a network of RPA bots supporting Axpo’s billing and switching operations. One automation focused on generating and sending annual purchase summaries to approximately 1,500 partners by logging into multiple distribution network operator systems, extracting usage data, calculating costs, generating reports, and sending them for approval, reducing 27 days of manual work to a single day. Another automation targeted [invoicing and invoice corrections](https://www.flobotics.io/blog/invoice-automation), where bots queried Power BI to identify invoices ready for processing, logged into the CRM system, generated invoices, and corrected existing ones, resulting in more than 600 transactions automated daily and significantly improved invoicing speed and accuracy. ## The outcome After automating the initial set of processes, Axpo achieved savings equivalent to 6.18 FTEs with projected annual savings of $186,000. The collaboration continues, with ongoing identification of new automation opportunities and expansion of the RPA bot network. Axpo, thank you for your trust. If you are looking to automate processes in your energy company, discover what we can do for you. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Agentic AI vs RPA: The Next Frontier of Intelligent Automation Canonical: https://www.flobotics.io/blog/agentic-ai-vs-rpa Author: Bart Teodorczuk Published: 2025-07-14 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Agentic AI vs RPA: The Next Frontier of Intelligent… [AI](https://www.flobotics.io/blog?category=ai)[RPA](https://www.flobotics.io/blog?category=rpa) # Agentic AI vs RPA: The Next Frontier of Intelligent Automation [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published July 14, 2025Updated September 1, 2026 On this page - [RPA in a Nutshell: The First Wave of Automation](#rpa-in-a-nutshell-the-first-wave-of-automation) - [What is Agentic AI? The Rise of Autonomous AI Agents](#what-is-agentic-ai-the-rise-of-autonomous-ai-agents) - [1. Goal-Driven Autonomy](#1-goal-driven-autonomy) - [2. Dynamic Decision-Making](#2-dynamic-decision-making) - [3. Adaptability and Learning](#3-adaptability-and-learning) - [Agentic AI vs RPA: Key Differences](#agentic-ai-vs-rpa-key-differences) - [Use Cases and Real-World Impact](#use-cases-and-real-world-impact) - [IT and DevOps Automation](#it-and-devops-automation) - [Healthcare Administration](#healthcare-administration) - [Sales and Marketing Agents](#sales-and-marketing-agents) - [Customer Service and Chatbots](#customer-service-and-chatbots) - [End-to-End Process Orchestration](#end-to-end-process-orchestration) - [Benefits and Challenges for Businesses](#benefits-and-challenges-for-businesses) - [Greater Efficiency and Throughput](#greater-efficiency-and-throughput) - [Improved Adaptability](#improved-adaptability) - [Enhanced Decision Making](#enhanced-decision-making) - [Scalability and 24/7 Operation](#scalability-and-24-7-operation) - [Competitive Advantage and Innovation](#competitive-advantage-and-innovation) - [Key Challenges of Agentic AI and RPA Implementation](#key-challenges-of-agentic-ai-and-rpa-implementation) - [Trust and Quality Control](#trust-and-quality-control) - [Security and Integration Hurdles](#security-and-integration-hurdles) - [Cost and Complexity](#cost-and-complexity) - [Workforce Impact and Change Management](#workforce-impact-and-change-management) - [Ethical and Regulatory Considerations](#ethical-and-regulatory-considerations) - [Agentic AI vs RPA: Not an “Either/Or” but a “Both/And”](#agentic-ai-vs-rpa-not-an-either-or-but-a-both-and) - [RPA](#rpa) - [Agentic AI](#agentic-ai) - [Conclusion: Navigating the Agentic AI vs RPA Landscape with Flobotics](#conclusion-navigating-the-agentic-ai-vs-rpa-landscape-with-flobotics) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) As enterprise automation evolves, a new debate has emerged: Agentic AI vs RPA. In one corner, Robotic Process Automation has spent years as the go-to solution for streamlining repetitive tasks. On the other hand, a rising star – Agentic AI, or autonomous AI agents – promises to take automation to the next level. CTOs and business leaders across industries are now asking: What exactly is Agentic AI, how does it differ from RPA, and do we need to choose between them? This article demystifies the differences between Agentic AI and RPA, explaining their key distinctions, use cases, and how they can work together. We’ll explore why tech executives are buzzing about Agentic AI, how it builds on the foundation laid by RPA, and what it all means for the future of work and productivity. ## RPA in a Nutshell: The First Wave of Automation [Robotic Process Automation (RPA)](https://www.flobotics.io/blog/robotic-process-automation) refers to software “bots” that mimic human actions to perform well-defined, repetitive tasks across applications. Think of an RPA bot as a diligent assistant following a script – copying data from one system to another, processing invoices in a fixed format, or moving files on a schedule. RPA gained popularity in the 2010s because it delivers quick efficiency wins without requiring the overhaul of IT systems. By configuring bots to handle high-volume routine work, companies speed up processes and reduce human error. RPA’s impact has been significant. Surveys show that over [three-quarters of companies have already adopted RPA](https://scoop.market.us/robotic-process-automation-market-news/), with many planning to increase investment. The global RPA market continues to grow rapidly as organizations seek to reduce costs and improve scalability through automation. For example, Deloitte found that 78% of executives had implemented RPA, and an additional 16% were in the process of doing so. Businesses, ranging from [banking](https://www.flobotics.io/business-process-automation) to healthcare, utilize RPA to automate repetitive tasks such as data entry, report generation, and record reconciliation. However, traditional RPA has inherent limitations. RPA bots are only as intelligent as the rules we give them. They excel at structured, rules-based tasks in stable environments, but struggle with adaptability in changing circumstances. Even a minor change in a form or an unexpected input can cause a scripted RPA process to fail. Maintenance can become a headache when UIs update or exceptions occur. In short, RPA bots are “brilliant instruction followers” that do exactly what they’re told, yet they don’t truly understand the goal behind the task. This brittleness means RPA is not well-suited for processes that involve judgment calls, unstructured data (such as free-text documents), or changing conditions. To address some of these gaps, the past few years have seen the rise of Intelligent Automation, which integrates AI techniques (such as OCR, NLP, and Machine Learning) with RPA. This extended RPA’s capabilities a bit further. AI add-ons help RPA bots handle unstructured inputs (for instance, reading handwriting or emails) and make simple rule-based decisions. [According to NASSCOM](https://community.nasscom.in/communities/rpa/state-rpa-amid-rise-agentic-ai), such AI-enhanced RPA can process non-standard data and adapt to basic variations, closing some of the flexibility gap. Yet, even with these smarts, traditional RPA remains fundamentally script-driven. It doesn’t decide what to do – it only executes the predefined workflow. Enter Agentic AI – a new generation of automation that aims to overcome RPA’s constraints by giving software a degree of autonomy and “agency.” ## What is Agentic AI? The Rise of Autonomous AI Agents [Agentic AI refers to AI systems](https://gradientdivergence.com/agentic-ai-and-the-future-of-automation/) that are endowed with “agency”: the ability to autonomously plan, decide, and act in pursuit of high-level goals. In practical terms, an AI agent is more than just a passive tool; it’s an active problem-solver. You set a goal, and the agent determines the steps and executes them, often coordinating multiple tasks and adapting on the fly until the goal is achieved. Ever wonder how Agentic AI differs from the AI tools you’re already using? Jeff Su’s “AI Agents, Clearly Explained” video is a fantastic primer for executives and non‑technical audiences alike. It walks through three levels of AI evolution in under ten minutes: Sorry, your browser doesn't support embedded videos. [Source](https://www.youtube.com/watch?v=FwOTs4UxQS4&list=WL&index=11&t=23s&ab_channel=JeffSu): Jeff Su YouTube Channel #### Level 1 – LLMs (Generative AI) Chatbots like ChatGPT or Claude generate text in response to your prompt. They’re passive—they wait for input and then deliver an output. #### Level 2 – AI Workflows The AI gets access to tools (like calendars or APIs) but still follows a fixed script laid out by humans. It lacks autonomous decision-making. #### Level 3 – Agentic AI You assign a goal (e.g., “manage my schedule,” “file prior authorization”), and the AI agent does the reasoning, executes across tools, monitors results, and iterates until the objective is met—without step-by-step human instruction Three core capabilities characterize Agentic AI systems: ### 1. Goal-Driven Autonomy They focus on the outcome rather than following a fixed script. As [Steven Bryant describes](https://bryantresearch.ai/index.php/2025/06/24/from-instruction-follower-to-outcome-pursuer-why-agentic-ai-is-a-quantum-leap-beyond-rpa/) it, RPA bots are great “instruction followers,” whereas AI agents are “outcome pursuers”. The agent is aware of the broader goal and can make on-the-spot decisions to fulfill it. ### 2. Dynamic Decision-Making Agentic AI can analyze situations and make context-aware choices without human input. It uses AI reasoning or machine learning to decide the best next action, rather than a hard-coded if-then rule. In customer service, for instance, an AI agent could prioritize support tickets or suggest solutions based on context, customer sentiment, and past resolutions – something a static workflow can’t do. ### 3. Adaptability and Learning Agentic AI systems can handle variability and change. If an interface changes or an unexpected scenario arises, the agent tries to adapt by understanding the underlying intent or pattern. It can incorporate feedback and improve over time. This is in stark contrast to an RPA bot that might break if, say, a web page layout is updated. [As one expert noted](https://medium.com/@manavg/agentic-ai-vs-rpa-ab34d64015e0), “a minor change to a user interface…can cause [RPA] automation to break,”. In contrast, an AI agent can adjust its strategy by grasping the semantic meaning of the elements. Crucially, Agentic AI isn’t just theory – it’s already emerging in real-world tools. According to TechRadar, nearly 93% of IT executives are very interested in agentic AI, and 69% are already using or plan to use AI agents in the next six months. The C-suite sees autonomous agents as the next step in automation. The promise is alluring: internal analyses suggest that AI agents could save employees hours per week by handling routine digital tasks (such as summarizing meetings or searching for information), allowing staff to focus on higher-value work. But how exactly does Agentic AI vs RPA stack up in practice? Let’s compare them head-to-head on key dimensions. ## Agentic AI vs RPA: Key Differences To understand Agentic AI vs RPA, it helps to see how they differ on several fundamental aspects: Fig. 01 · Agentic AI vs RPA Key differences Agentic AI vs RPA Aspect | Traditional RPA | Agentic AI | Automation style | Follows predefined scripts and rules step by step; the bot runs a fixed workflow exactly as programmed | Pursues goals with flexible strategies; agents decide the steps needed to reach the end goal | Data handling | Best with structured, standard data; struggles with free text or images unless paired with AI | Handles unstructured and varied data; reads documents and images and adapts to new formats | Decision-making | Rule-based only: if-then logic or decision trees, limited to expected scenarios | Decides from context and real-time data; prioritizes and adjusts based on learned patterns | Adaptability | Reliable within known workflows; new scenarios usually need a person to update it | Adapts to change using machine learning and language understanding; improves from feedback | Scope of work | Task-centric: automates single tasks or steps (such as logging in and moving data) | Outcome-centric: runs an end-to-end process across several systems to reach a goal | In essence, RPA is about automating explicit procedures, whereas Agentic AI is about automating problem-solving. RPA handles the grunt work in a very controlled way. Agentic AI tackles the brain work, within bounds, figuring out the procedure as it goes. To make this concrete, consider a customer support scenario: - Using RPA, you might automate the process of looking up a customer’s order status and pasting it into an email template. The bot follows the same steps for every inquiry. - Using Agentic AI, you could delegate the entire customer inquiry to an AI agent. The agent could read the customer’s email (even if it’s a long, messy paragraph), understand the question and the customer’s sentiment, pull relevant data from multiple systems, decide on a tailored response or solution, and send a reply – all without a human driving each step. If the customer’s issue involves multiple back-and-forth interactions, the agent can handle those as well, keeping track of the context over time. ## Use Cases and Real-World Impact RPA has already proven its value in many domains. It’s widely used in finance (e.g., automating loan processing, invoice handling, and reconciliations), in healthcare (e.g., patient data entry and insurance claims filing), in HR (onboarding paperwork and payroll updates), and in other areas. Whenever there’s a high-volume, repetitive digital task, RPA is a strong candidate to reduce workloads. The technology has delivered impressive ROI, often yielding returns of 30-200%, by reducing labor hours and errors. Some RPA implementations have achieved [ROI figures as extreme as 300,000%](https://www.flobotics.io/case-studies/t-bank-automation) for simple yet high-impact automations. RPA’s contribution is primarily focused on efficiency and accuracy in well-defined processes. Agentic AI is relatively new, but its potential use cases are quickly emerging. Early implementations and pilots are showing that AI agents excel in scenarios that were traditionally too complex for automation. Some examples making waves: ### IT and DevOps Automation Imagine an AI agent that monitors software systems and takes action to fix incidents. Instead of just alerting a human, an Agentic AI could detect an outage, pinpoint the likely issue (say, a server overload), apply a fix or restart, test the system, and confirm resolution – all autonomously. Companies are exploring this for self-healing IT operations. ### Healthcare Administration In [Revenue Cycle Management (RCM),](https://www.flobotics.io/rcm-automation) Agentic AI can be assigned goals, such as “submit all corrected claims by end of day” or “check authorization status for pending cases every 6 hours. It’s an AI that understands the context, adapts to the results, and continues until it’s done. This is a game-changer for hospitals dealing with mountains of paperwork – the AI agent can take on tedious tasks (such as [claims processing](https://www.flobotics.io/agents/claims-management-automation), insurance checks, and [scheduling](https://www.flobotics.io/contact)) that usually require constant human follow-up, dramatically improving turnaround times and freeing staff for patient-focused work. While RPA can assist in these workflows by [automating data movement](https://www.flobotics.io/blog/data-entry-automation-healthcare) between systems, Agentic AI can manage the workflow itself, handling exceptions and communicating as needed to achieve the objective. ### Sales and Marketing Agents Agents can conduct market research or competitive analysis by autonomously surfing the web, gathering data, and compiling findings. They might also personalize marketing outreach by deciding the best content for a customer based on numerous data points. Unlike RPA, which may simply automate sending emails, an AI agent can adjust the messaging tone and timing for each prospect to achieve maximum engagement. ### Customer Service and Chatbots Traditional chatbots follow pre-written scripts. Agentic AI in customer service can hold more free-form conversations, understand complex requests, and resolve issues end-to-end (even performing transactions on the user’s behalf). For instance, an airline’s AI agent could handle a customer’s flight change, negotiate options, rebook the ticket, and issue vouchers for delays, all within a single interaction. This improves the customer experience by actually resolving the issue, not just passing it off. ### End-to-End Process Orchestration Perhaps the most transformative use case is when agents handle multi-step processes in their entirety, as in the earlier accounts payable example. Instead of piecemeal task automation, the AI agent becomes a virtual process manager that can coordinate multiple smaller bots or tools. It’s like having a digital project manager who never sleeps or gets tired. Early adopters have reported that employees save several hours per week by having AI agents take over time-consuming tasks, such as meeting documentation and status reporting. It’s essential to note that Agentic AI doesn’t replace all existing systems – it often operates in conjunction with them. For instance, an AI agent might still use RPA bots underneath for specific actions (like clicking through a legacy system), or call APIs, or invoke an OCR service to read a PDF. The difference is that now the AI agent is orchestrating those pieces with minimal human guidance. This leads to more resilient automation that can handle complexity. A recent TechRadar report described this as moving beyond using AI for insights to using AI for initiative – AI that doesn’t just answer a question, but takes action within business workflows. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Benefits and Challenges for Businesses For businesses, the emergence of Agentic AI presents exciting possibilities – but also raises new considerations. Here’s what tech and business leaders should keep in mind: Fig. 02 · Agentic AI Benefits and challenges What to plan for - 01Trust and oversightQuality control, hallucination risk - 02Integration hurdlesLegacy systems, API dependencies - 03Implementation costsPlatforms, AI specialists - 04Change managementUpskilling, reshaping the workforce - 05Ethical risksAI auditability, compliance, bias ### Greater Efficiency and Throughput By automating not only tasks but entire processes, Agentic AI can significantly enhance operational efficiency. Early deployments have shown significant productivity gains. One survey noted that companies using AI-enhanced automation reported a [56% increase in automation capacity](https://community.nasscom.in/communities/rpa/state-rpa-amid-rise-agentic-ai), meaning they could automate more complex work than before. Freeing employees from low-level, time-consuming tasks allows them to focus on strategic and creative tasks, which can boost overall productivity. ### Improved Adaptability Whereas traditional automation might falter when conditions change, AI agents thrive on change. They can adjust to new business rules, market conditions, or customer needs with minimal reprogramming. This adaptability is crucial in today’s fast-paced environment. Executives view this as a means to build more resilient operations that are less prone to breakdown due to minor variations. ### Enhanced Decision Making Agents can analyze data and provide recommendations or take actions in real time. In scenarios such as fraud detection, [supply chain](https://www.flobotics.io/blog/warehouse-automation-process) adjustments, or medical triage, having AI that reacts instantly and intelligently can lead to improved outcomes. Gartner estimates that AI-driven automation could significantly increase decision-making speed and accuracy in the next few years. ### Scalability and 24/7 Operation AI agents don’t eat, sleep, or take vacations. They can work around the clock and scale on cloud infrastructure as demand spikes. This makes it feasible to handle surges (like seasonal workloads or sudden incidents) without proportional increases in staff. RPA also offers 24/7 operation, but scaling RPA may involve spinning up many bot instances and maintaining them. In contrast, an AI agent can often handle a broader scope of work on its own, reducing the coordination overhead. ### Competitive Advantage and Innovation Just as RPA gave early adopters an edge in efficiency, Agentic AI could confer an edge in innovation. It enables new ways of working. Companies can design processes that were previously impossible or dramatically shorten project cycle times. A World Economic Forum analysis projected that AI (broadly) could add [around $15 trillion](https://gradientdivergence.com/agentic-ai-and-the-future-of-automation/) to the global economy by 2030. Agentic AI will likely contribute to this by unlocking automation of knowledge work and complex services. ## Key Challenges of Agentic AI and RPA Implementation ### Trust and Quality Control Handing more autonomy to AI raises questions about trust. Business leaders are understandably cautious – a Pega survey found many workers lack confidence in AI’s ability to fully replace human judgment. Concerns include the quality of AI’s work (33% of respondents) and its lack of human intuition or empathy (32%). There’s also the well-known issue of AI “hallucinations” or making incorrect decisions. If an AI agent makes a mistake in a high-stakes process, who is responsible for catching it and who is accountable? Organizations will need robust testing, validation, and human-in-the-loop oversight for critical use cases, at least until trust is built. ### Security and Integration Hurdles Introducing autonomous agents into your tech stack isn’t a plug-and-play process. IT execs cite integration with legacy systems (35%) and data security (56%) as top challenges to adopting Agentic AI. An AI agent may require broad access to systems and data to perform its tasks effectively, which raises significant security concerns. Ensuring these agents follow compliance rules and don’t become a new attack surface is paramount. Careful governance and perhaps restricting agents to sandbox environments initially can help. ### Cost and Complexity While RPA has its costs (licenses, development, maintenance), Agentic AI may involve substantial investments in AI platforms, talent, and computing resources. [In one survey](https://www.techradar.com/pro/businesses-are-keen-to-embrace-ai-agents-but-still-struggle-to-start), 37% of IT leaders flagged implementation cost as a barrier to Agentic AI. Additionally, deploying AI agents is technically more complex than deploying RPA bots. It requires AI expertise and possibly rethinking processes. Companies need to weigh the ROI – start with use cases where an agent’s success would bring significant value. ### Workforce Impact and Change Management Automation often leads to changes in job roles. Agentic AI will likely handle tasks performed by knowledge workers, not just clerical tasks. This means some jobs will evolve (people will supervise AI or focus on more analytical work), and some roles may become redundant. Proactive change management is essential. On the flip side, employees might welcome offloading drudge work – 79% of workers in one poll cited increased productivity and time savings as a benefit of automation, saving [~3.6 hours per week](https://scoop.market.us/robotic-process-automation-market-news/) on average, according to average. The key is to retrain staff for higher-value activities and ensure the human-AI collaboration is positive. ### Ethical and Regulatory Considerations An autonomous agent making decisions (especially in areas like finance, healthcare, or legal fields) raises ethical questions. How to prevent bias? How to audit its decisions? Regulations around AI accountability are still catching up. Companies adopting agentic AI should implement transparent logs of agent decisions, define escalation paths for exceptions, and comply with emerging AI governance standards. As [Booz Allen Hamilton noted](https://www.boozallen.com/insights/velocity/the-age-of-agentic-ai.html), this shift is “not just another technical upgrade” but a fundamental change that demands updated oversight frameworks. ## Agentic AI vs RPA: Not an “Either/Or” but a “Both/And” Despite the “vs” framing, it’s not actually Agentic AI versus RPA in a zero-sum fight. In reality, these technologies complement each other, and the most successful automation strategies will combine their strengths. RPA is a proven foundation for reliable, rule-based task automation, while Agentic AI is a frontier technology enabling intelligent autonomy. Fig. 03 · Agentic AI vs RPA How they work How agentic AI works vs RPA RPA: follows predefined steps - 01Trigger - 02Task - 03Result Agentic AI: decides in real time toward an outcome - 01Goal input - 02Task planning - 03Tool use (RPA bot, API, LLM) - 04Feedback integration - 05Adaptation and learning - 06Completion Industry experts suggest a hybrid approach: use RPA for what it does best, and layer Agentic AI on top for what it does best. In practical terms: ### RPA Remains ideal for well-defined, repetitive tasks that operate on structured data and require high accuracy. It’s relatively fast to deploy for these scenarios and highly cost-effective. ### Agentic AI Can be introduced for complex scenarios that involve decision-making, variability, or unstructured data. It can supervise and direct RPA bots, effectively serving as the “brain” while RPA bots are the “hands.” For example, an AI agent might determine that a specific set of transactions requires processing and then trigger RPA bots to execute those transactions across various systems. The agent handles exceptions and coordination, while RPA handles the detailed keystrokes. NASSCOM’s automation outlook stresses that RPA is not made obsolete by Agentic AI – instead, together they form an “automation ecosystem that’s both efficient and adaptable”. Companies that integrate both will automate a far wider range of processes, from the simplest to the most complex, compared to those using either alone. The endgame is full-spectrum automation: routine tasks handled by RPA, complex problem-solving guided by AI agents, all working in concert. From a strategic perspective, viewing Agentic AI as just “RPA 2.0” undersells its transformative potential. Yes, it’s the next evolution of automation, but it demands a mindset shift. Executives should plan not just to bolt AI onto existing processes, but to reimagine processes entirely. Those that do so can unlock new levels of operational excellence and innovation, while those that don’t may fall behind as competitors streamline and reinvent their workflows. Fig. 04 · Hybrid automation Before and after What hybrid agentic automation changes Before - 01Manual, repetitive tasks - 02Bottlenecks and errors - 03Human reviews After (RPA + agentic AI) - 01Agents set goals - 02RPA bots handle the steps - 03A feedback loop adapts tasks - 04People focus only on edge cases and strategic calls ## Conclusion: Navigating the Agentic AI vs RPA Landscape with Flobotics Automation is not slowing down – it’s accelerating, and the tools are becoming smarter. Businesses that thoughtfully embrace this evolution will boost productivity, reduce costs, and innovate more quickly than those that hesitate to do so. Agentic AI vs RPA isn’t a choice of one over the other, but an invitation to combine the reliability of RPA with the ingenuity of AI agents. The result is a digital workforce that can handle both mundane tasks and complex projects simultaneously, driving your organization forward in the modern age of automation. [Ready to explore](https://www.flobotics.io/) what Agentic AI and RPA together can do for your company? Now is the time to seize the advantage. As the saying goes, the future is already here – it’s just unevenly distributed. At [Flobotics,](https://www.flobotics.io/) we’ve witnessed firsthand how combining RPA with cutting-edge AI unleashes unprecedented value. We’ve built RPA bots that save thousands of hours in clerical tasks, and we’re now deploying Agentic AI solutions that tackle higher-order problems, such as Revenue Cycle Management and customer service inquiries. [Schedule a free consultancy call](https://www.flobotics.io/book) with us to explore how RPA and Agentic AI can work in your company. Let’s build your automation strategy—smarter, faster, together. #### Like the article? Spread the word Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # How Data Entry Automation Transforms Healthcare Operations Canonical: https://www.flobotics.io/blog/data-entry-automation-healthcare Author: Michał Rejman Published: 2025-06-30 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/How Data Entry Automation Transforms Healthcare Operations [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm)[RPA](https://www.flobotics.io/blog?category=rpa) # How Data Entry Automation Transforms Healthcare Operations [Michał RejmanChief Marketing Officer at Flobotics](https://www.flobotics.io/our-editorial-team#rejman) Published June 30, 2025Updated September 1, 2026 On this page - [The High Cost of Manual Data Entry in Healthcare](#the-high-cost-of-manual-data-entry-in-healthcare) - [What is Data Entry Automation?](#what-is-data-entry-automation) - [Top Healthcare Data Entry Processes Ready for Automation](#top-healthcare-data-entry-processes-ready-for-automation) - [Patient Intake Forms → EHR Updates](#patient-intake-forms-ehr-updates) - [Insurance Verification → Claims Systems](#insurance-verification-claims-systems) - [Medical Coding → Billing Software](#medical-coding-billing-software) - [Prior Authorization Paperwork → Payer Portals](#prior-authorization-paperwork-payer-portals) - [How Automated Data Entry Works in Healthcare](#how-automated-data-entry-works-in-healthcare) - [1. Data Capture (OCR and Extraction)](#1-data-capture-ocr-and-extraction) - [2. Field Validation and Business Rules](#2-field-validation-and-business-rules) - [3. Bot Entry into Target Systems](#3-bot-entry-into-target-systems) - [Key Benefits of Automated Data Entry for Healthcare Ops](#key-benefits-of-automated-data-entry-for-healthcare-ops) - [Fewer Errors, Fewer Headaches](#fewer-errors-fewer-headaches) - [Time Savings & Higher Productivity](#time-savings-higher-productivity) - [Cost Reduction](#cost-reduction) - [Improved Staff Morale (No More Soul-Crushing Tasks)](#improved-staff-morale-no-more-soul-crushing-tasks) - [Better Patient Experience](#better-patient-experience) - [Why Flobotics for Healthcare Data Entry Automation?](#why-flobotics-for-healthcare-data-entry-automation) - [Healthcare-Specific Expertise](#healthcare-specific-expertise) - [Rapid Deployment](#rapid-deployment) - [Scalability and Flexibility](#scalability-and-flexibility) - [End-to-End Support and Partnership](#end-to-end-support-and-partnership) - [From Data Chaos to Streamlined Care](#from-data-chaos-to-streamlined-care) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) You already know this: manual data entry is eating your day alive. Whether you’re running billing, overseeing scheduling, [managing claims](https://www.flobotics.io/blog/insurance-claims-processing-rpa-automation-use-cases), or keeping patient records in check, chances are you’re buried in forms, toggling between systems, and fixing avoidable mistakes. The frustrating part? None of it moves the needle for your patients, your bottom line, or your sanity. That’s where data entry automation comes in. We’re talking [about RPA (Robotic Process Automation)](https://www.flobotics.io/blog/robotic-process-automation), [AI-powered extraction](https://www.flobotics.io/blog/ai-rpa-ml-rcm), OCR, and tight integrations that enable your systems to actually communicate with each other. No more copy-pasting insurance info. No more manually uploading lab results. No more retyping the same patient name into five platforms. With the right tools in place, all of that happens in the background—accurately, securely, and in a fraction of the time. We’ll break down how automated data entry works in practice and the real-world benefits (from fewer errors to saved hours). Consider this a conversation with a Flobotics automation expert about how to help your team breathe easier, save time, and avoid repeating the same mistakes. ## The High Cost of Manual Data Entry in Healthcare Manual data entry isn’t just an inconvenience – it’s a massive hidden cost. Billing and coding errors alone cost the U.S. healthcare system [around $36 billion](https://www.hfma.org/revenue-cycle/navigating-regulatory-challenges-in-hospital-revenue-cycle-the-impact-on-rcm-teams-and-the-path-forward/) yearly in lost revenue, denied claims, and penalties. When humans enter codes or billing data, mistakes (such as a mistyped code or an extra zero) can lead to allegations being denied or underpaid, resulting in financial losses for hospitals and clinics. The impact goes beyond finances. Inaccurate patient records pose a direct risk to patient safety. If a nurse transposes a number in a medication dose or enters a diagnosis code incorrectly, it can result in incorrect treatments or delays. Data integrity failures – such as entering information into the wrong patient’s chart or having out-of-date data in the EHR – can lead to delayed or missed diagnoses, incorrect treatments, and potential patient harm. In healthcare, a simple data entry error can literally be life-threatening. There’s also a human toll on the workforce. Nurses, doctors, and administrative staff are drowning in digital paperwork. One survey found that staff spend [nearly 60% of their time on repetitive tasks,](https://www.businesswire.com/news/home/20220426005250/en/Majority-of-Healthcare-Workers-Worry-About-Burnout-from-Increasing-Burden-of-Administrative-Work) such as data entry and documentation. Think about that – more than half the workweek consumed by updating records, filling forms, and other admin drudgery. This contributes directly to burnout: caregivers feel like data clerks instead of healers. In fact, [37% of healthcare workers ](https://www.holonsolutions.com/survey-finds-majority-of-healthcare-workers-have-considered-leaving-their-roles-or-the-industry-altogether-in-the-past-year/)say excessive data entry cuts into patient time, and administrative burden is a top driver of workforce burnout. The more hours staff spend typing or fixing errors, the less time they have for patients, leading to frustration, overtime (“pajama time” spent finishing charts), and ultimately, people leaving the profession. Finally, consider regulatory and compliance risks. Healthcare data is highly sensitive, and manual handling can introduce security gaps. Paper forms and manual re-keying are slow and not secure, leaving organizations [vulnerable to HIPAA violations](https://www.digitechsystems.com/hipaa-compliance-brief/). Every time a staffer manually transcribes patient information, there’s a risk of exposing personal health information or misfiling a record, which can result in compliance fines. In short, the old way of doing things – stacks of forms, copying and pasting between systems, and human error – is enormously costly on all fronts: financially, clinically, and operationally. ## What is Data Entry Automation? So, what do we mean by data entry automation in healthcare? In simple terms, it means utilizing technology, often including RPA bots and AI, to automate the repetitive keystrokes and clicks that humans currently perform. Instead of a medical secretary manually entering referral details from an email into an [EHR](https://www.flobotics.io/blog/electronic-health-records-rpa), for example, a software bot can automatically populate the data into the correct fields. It’s like putting these mundane tasks on autopilot. The goal is for data to move seamlessly from one system to another (such as from a patient intake form to the hospital’s EHR and billing system) without requiring a person to retype it at every step. It’s important to note that not all automation is created equal. Basic [macros or scripts](https://www.uipath.com/blog/rpa/whats-the-difference-between-robots-and-macros) (think of a quick Excel macro) can perform simple, repetitive actions in one application, but they are limited in their capabilities. Modern healthcare data entry automation goes further. RPA bots are essentially the next generation of macros, capable of working across multiple applications and adapting to changes in real-time. Unlike a fixed macro, which only does exactly what it’s programmed to do in one software, an RPA robot can mimic a human’s actions on any software – it can click through a web portal, type into a legacy billing system, or navigate an EHR interface. In practice, RPA software bots “log in” just like a person would and input or transfer information between systems. They [mimic human clicks and typing](https://www.automationanywhere.com/rpa/intelligent-automation-vs-rpa) to interact with applications via the user interface, following rules that you set. For example, a bot could be instructed: “Whenever a new patient registration form comes in, pull the name, address, insurance info, etc., and enter them into our EHR.” Fig. 01 · Data entry Typical jobs Data entry automation in healthcare: typical jobs The jobThe outcome - Moving patient data between the EHR and other systemsNo more manual data handling and migration - Transferring diagnosis codes into billing softwareRecords stay clean and consistent across platforms - Pulling insurance data into a claims platformClaims go out with the right insurance details Adding Artificial Intelligence takes it up yet another notch. Traditional RPA is rule-based – very effective for structured, repetitive tasks. Combining RPA with AI enables the system to handle unstructured data and make informed decisions. This means tasks that involve reading scanned documents, [interpreting text,](https://www.flobotics.io/blog/document-understanding-tools) or making basic decisions (such as flagging an anomaly) can be automated. Simple script automation can handle moving data, but RPA and AI can actually understand it. For instance, AI-powered OCR can read a scanned doctor’s note, and the RPA bot can then extract key details and populate them into the appropriate system. In short, data entry automation ranges from basic to advanced: on one end, there are straightforward scripts for one application; on the other, intelligent bots that navigate entire workflows across EHRs, insurance portals, and billing platforms. The common thread is that your staff aren’t doing the mindless typing – the software for healthcare is. ## Top Healthcare Data Entry Processes Ready for Automation Not every task is ripe for automation, but many are – especially in healthcare, which has no shortage of form-filling and system-hopping. Here are some of the [top data entry processes in healthcare](https://phimed.com/2025/02/best-practice-rpa/) that are prime candidates for automation: Fig. 02 · Data entry 4 processes Healthcare data entry processes ready for automation - 01Patient intake forms → EHR updatesIntake data is extracted and entered into the EHR automatically. - 02Insurance verification → claims systemsInsurance is checked across payer portals at once and internal systems are updated. - 03Medical coding → billing softwareClinical data is coded and pushed into billing software automatically. - 04Prior authorization paperwork → payer portalsForms are filled in, submitted and tracked with no manual work. ### Patient Intake Forms → [EHR Updates](https://www.flobotics.io/blog/ehr-implementation-plan) From the moment a patient walks in, there’s data to be captured – contact info, medical history, insurance details, you name it. Often, patients fill out digital or paper intake forms, and staff then manually re-enter that information into the Electronic Health Record (EHR). This is tedious and error-prone. Automation can eliminate double entry: for example, scanning/OCR technology can digitize a paper form, and an RPA bot can automatically transfer that data into the EHR fields. The result is faster check-ins and more accurate records. No more deciphering messy handwriting or copying from a clipboard to a computer; the data goes straight from the patient’s form to the system. ### [Insurance Verification](https://www.flobotics.io/agents/eligibility-check-automation) → [Claims Systems](https://www.flobotics.io/agents/claims-management-automation) Verifying a patient’s insurance eligibility and coverage is a classic repetitive task. Typically, staff log into various payer websites or make phone calls, then input the responses into the practice management or claims system. An automated solution can check insurance eligibility in real time – bots can log into insurance portals (or use integration APIs) to retrieve coverage information and even cross-check the patient’s plan details. The bot then updates the internal system with the verified info (policy active/inactive, co-pay amounts, etc.). This means that insurance verification, which used to take 20+ minutes of hold music and website juggling, can now happen in seconds. By automating insurance checks, healthcare providers see fewer denied claims down the line (since coverage is confirmed upfront) and can process claims much faster. ### [Medical Coding](https://www.flobotics.io/blog/medical-coding) → [Billing Software](https://www.flobotics.io/blog/how-to-build-automated-medical-billing-system) Proper coding of diagnoses and procedures is critical for billing and analytics. In many organizations, medical coders or billers spend hours abstracting codes from charts and entering them into billing software. Automation can assist with medical coding by extracting keywords or phrases from clinical documentation (using NLP or OCR) and suggesting appropriate ICD-10 or CPT codes. While full AI coding is still emerging, even partial automation, like a bot that copies physician notes to a coding system or checks codes against a reference database, can save time. Once the codes are determined, an RPA bot can transfer those codes into the billing software or claims form automatically. This reduces coding errors and speeds up the billing cycle because when a doctor finishes a note, a bot could populate the billing system with the requisite codes for charge entry. ### [Prior Authorization](https://www.flobotics.io/agents/prior-authorization-automation) Paperwork → Payer Portals Prior authorizations (PAs) are a notorious administrative headache – faxing forms, waiting on approvals for medications or procedures. Data entry automation streamlines this by handling the information exchange with insurers. For example, a bot can retrieve the necessary patient information and procedure details from the EHR, complete the payer’s prior authorization request form (often accessed through a web portal or PDF), and submit it electronically. It can then continuously check the payer portal for a determination. The moment approval is granted, the bot grabs the auth number and updates the patient’s record. This end-to-end automation of prior authorizations means providers don’t have to have staff calling insurance companies repeatedly or retyping information into different forms – the bot orchestrates it all. Patients receive their approvals more quickly, and [schedulers ](https://www.flobotics.io/contact)can proceed with necessary care without administrative delays. These are just a few examples. Virtually any workflow where staff are “swivel-chairing” between systems – copying data from one screen to another – is a candidate for automated data entry. By targeting processes like the above, healthcare organizations can eliminate some of the most frustrating bottlenecks in their operations. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## How Automated Data Entry Works in Healthcare It sounds almost like magic: information simply “flows” from one system to another. But how does it actually work under the hood? Let’s break down the typical components of an automated data entry workflow in healthcare: Fig. 03 · Data entry How it works How automated data entry works in healthcare - 01Data captureOCR and AI extraction turn scanned forms and PDFs into structured data. - 02Validation and business rulesThe system checks and cleans the data: flags errors, applies formats, cross-checks values. - 03Bot entry into target systemsA bot enters the checked data into the EHR, billing or portals, like a person would or through APIs. ### 1. Data Capture (OCR and Extraction) The first step is getting analog or unstructured data into a digital, structured form. For any information that isn’t already electronic – say, a paper form or a fax – automation uses OCR (Optical Character Recognition) to convert it into text. For instance, new patient intake forms or referral letters can be scanned, and OCR software will recognize the text on those pages. Beyond plain OCR, AI-powered data extraction tools can pull specific fields from documents (e.g., patient name, ID number, [lab results](https://www.flobotics.io/blog/laboratory-automation-solutions) in a PDF report). The result is that the raw data is now in a usable form (like a data table or JSON) that the bot can work with. This step is like digitizing the input, ensuring the bot “sees” the same data a person would. ### 2. Field Validation and Business Rules Once the data is captured, automated workflows apply validation rules just like a diligent human would – only faster. For example, if a date of birth field is captured as 13/25/2025, the system can flag that as invalid. Bots can be programmed to verify that numeric fields contain only numbers, that medical codes have the proper format, or even cross-verify patient identifiers across systems. This ensures that clean, correct data is being entered. Say the OCR misreads an ‘O’ as ‘0’ in an insurance policy number – a validation rule can catch that discrepancy (since the policy format might be known to be letters followed by numbers). By enforcing these checks, automated data entry prevents garbage in and out. Many advanced RPA setups will also cross-reference data, such as whether the patient name on this form matches an existing record. If not, the bot can prompt a review. This validation layer is crucial in healthcare, where compliance and accuracy are paramount. ### 3. Bot Entry into Target Systems For the core action, the RPA bot functions as a speedy, error-free data clerk, enabling validated information to be input wherever it is needed. RPA bots can interact with virtually any system or software. They might use APIs when available, but they can also operate through the user interface, mimicking the exact clicks and keystrokes a human would do. For example, a bot could receive a structured dataset (such as a JSON file containing all the fields from a patient intake form) and then launch the hospital’s EHR application. It will navigate to the New Patient screen and systematically fill in name, DOB, address, etc., using the extracted data. It can do this very quickly – no breaks, no typos. Bots can also move data between multiple systems. For example, after updating the EHR, the same bot may log into a billing portal to enter insurance information. Crucially, bots can perform these tasks 24/7 and at high speed, which means overnight, it could update hundreds of records that would take staff days to complete. To illustrate, one RPA system can monitor a folder for incoming patient files and automatically upload that information into the appropriate database or EHR module when a new file appears. In short, the bot “hands off” the data to whatever system needs, with no human in the loop. Throughout this process, everything the bot does can be logged and audited. That’s a hidden benefit: you get a digital trail of what data was entered, where, and when, which is great for compliance. And if any step fails (say a portal is down), the bot can alert a human or retry automatically. By combining OCR for reading data, AI for interpreting and validating it, and RPA for inputting it, automated data entry creates an end-to-end pipeline: information goes from point A to point B (and C, and D) with minimal human intervention. The result? What used to be an hour of manual copying between systems happens in minutes or less, with near-perfect accuracy. ## Key Benefits of Automated Data Entry for Healthcare Ops Why are healthcare organizations embracing automated data entry? Let’s break down the most significant benefits of introducing some digital horsepower into your workflows. These are the outcomes our [Flobotics team](https://www.flobotics.io/about-us) sees consistently when we deploy RPA bots in hospitals and clinics: ### Fewer Errors, Fewer Headaches Automation dramatically improves data accuracy. With bots following set rules every time, typos and oversights plunge. Fewer errors mean fewer claim rejections and corrective rework. (Remember that 80% error rate in medical bills? Bots can bring that way down.) The result is lower denial rates and more reliable records, directly boosting your revenue cycle health. Consistent, clean data also keeps you on the right side of compliance. ### Time Savings & Higher Productivity Every minute your staff spend on copy-paste tasks is a minute they’re not helping patients or improving the business. Automated data entry gives you back those minutes (often thousands of hours in aggregate). For instance, one large NHS hospital trust in the UK saved 7,000 staff hours per year by deploying bots to automate their administrative tasks. Closer to home, automation can do routine processes that took days in seconds. Your team can finally tackle the important work on their plate, rather than being overwhelmed by paperwork. ### Cost Reduction When mundane tasks are automated, you simply don’t need as much staff overtime or contractor help to handle peak workloads. That translates to serious cost savings. Across the board, providers save on overhead, spending less money on fixing errors, chasing denials, or hiring temporary workers to clear backlogs. In fact, industry analyses estimate that shifting to automated workflows could save healthcare upwards of [$20 billion annually](https://www.caqh.org/blog/new-caqh-index-reveals-20b-savings-opportunity-to-cut-waste-reduce-costs-and-improve-patient-access) by eliminating inefficiencies. ### Improved Staff Morale (No More Soul-Crushing Tasks) Let’s be honest: data entry drudgery kills morale. When you empower your staff with automation, you’re not replacing them – you’re elevating them to do more meaningful work. Nurses, billing specialists, and admins can focus on patient care, customer service, and problem-solving, rather than punching keys all day. This leads to happier employees and helps combat burnout. Your team can leave on time more often, and they spend their days doing what humans do best, not what bots can do better. ### Better Patient Experience Patients may never see the bots working behind the scenes, but they’ll definitely feel the effects. Automation speeds up turnaround times (e.g., faster insurance checks, quicker billing), so patients get answers and bills sooner and with fewer errors. Fewer mistakes in data entry also mean fewer billing surprises for patients – an accuracy boost that builds trust. Automation creates a more responsive and caring experience for the people you serve by reallocating staff from data-intensive tasks to patient-facing roles. In summary, automated data entry transforms healthcare operations by attacking the very inefficiencies that have long plagued the industry. It’s about working smarter, not harder – doing more with the resources you have and doing it more accurately. Let’s examine how this transformation unfolds in real life. ## Why Flobotics for Healthcare Data Entry Automation? There’s a growing field of automation providers, but Flobotics stands out regarding healthcare data entry automation. Our approach combines technical expertise with in-depth knowledge of the healthcare domain, which is crucial for success. Here’s why [Flobotics is a trusted partner](https://www.flobotics.io/) for many healthcare organizations looking to automate their data entry and beyond: ### Healthcare-Specific Expertise We’re not generalists dabbling in healthcare; Flobotics has dedicated healthcare RPA specialists who understand the nuances of medical workflows, billing cycles, and [compliance requirements](https://www.flobotics.io/blog/compliance-automation). Healthcare [Revenue Cycle Management,](https://www.flobotics.io/blog/revenue-cycle-management) claims processing, HL7 integration, HIPAA privacy rules – our team speaks your language. This means we design automation solutions that fit your reality. ### Rapid Deployment We have a proven framework for identifying quick-win processes and deploying ready-to-use bots in under 30 days in many cases. Whether it’s automating patient onboarding or claim form entry, we strive to get a pilot up and running in a month or less – and then scale from there. ### Scalability and Flexibility Flobotics solutions are built to grow with you. We often start with one or two high-impact processes (for example, automating data entry for prior auths or referrals), and once you see the value, scaling up is straightforward. Do you need to add more bots during peak season? Do you need to extend automation to a new department? No problem. Our approach utilizes modular, reusable bot components and a robust orchestration platform, enabling quick and cost-efficient addition of capacity or new workflows. ### End-to-End Support and Partnership We don’t just drop off a piece of software and leave. Flobotics prides itself on being [a true partner in your automation journey.](https://clutch.co/profile/flobotics-uipath-rpa-development#summary) We’ve got you covered, from initial process discovery (identifying which data entry tasks will yield the best return on investment) to development, testing, and ongoing maintenance. In healthcare, where rules and systems are constantly evolving, we stay by your side to update and optimize your automations. Flobotics combines the latest technology (AI, OCR, RPA) with a human-centric approach to ensure the automation works in your context. ## From Data Chaos to Streamlined Care Picture your operations a few months after implementing automated data entry: forms flow effortlessly between systems, patient records update instantly, claims go out error-free on the first try, and your team finally has breathing room. The compliance department isn’t chasing missing information, and finance isn’t writing off as many denied claims. In short, your whole organization can breathe easier. With the right [automation partner](https://www.flobotics.io/) and a clear roadmap, you can start small, perhaps automating one painfully slow data entry task, and then scale up. It’s about working alongside your existing software, supercharging your staff with a digital workforce that handles the boring stuff. Ready to put data entry on autopilot? Flobotics specializes in helping healthcare teams implement automation smoothly and effectively. We’ve walked in your shoes and understand the unique challenges of healthcare ops. [Schedule a free consulting session](https://www.flobotics.io/book) with our healthcare automation experts to see how automated data entry could work in your environment – we’ll even show you a live demo of a bot in action. Let’s talk about plugging your leaks in time and accuracy, and map out a step-by-step plan to get you from chaos to calm. #### Like the article? Spread the word At Flobotics we specialize in automating processes that mattersmost in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byMichał Rejman Chief Marketing Officer at Flobotics. [More from Michał](https://www.flobotics.io/our-editorial-team#rejman) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### Document Understanding Tools Overview Document understanding tools compared: top platforms, use cases, and how they streamline document management workflows for teams. Krzysztof SzwedJuly 04, 2024 ](https://www.flobotics.io/blog/document-understanding-tools)[ RPA ### More Than Just Reading Text: Why Your Document Understanding Sucks Document understanding challenges, explained: why most automations underperform, what's really failing beyond the OCR tool, and how to fix it. Karl MielnickiJune 05, 2024 ](https://www.flobotics.io/blog/why-document-understanding-sucks)[ RPA ### Automated Document Processing: How to Do Away with Manual Paperwork? Automated document processing: how RPA turns insurance claims, loan statements, and patient forms into a paperwork-free workflow. Karl MielnickiFebruary 11, 2024 ](https://www.flobotics.io/blog/automated-document-processing) [All articles →](https://www.flobotics.io/blog) --- # How to Improve Revenue Cycle Management: 8 Strategies for Healthcare Leaders Canonical: https://www.flobotics.io/blog/revenue-cycle-management-strategy Author: Krzysztof Szwed Published: 2025-06-25 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/How to Improve Revenue Cycle Management: 8 Strategies for… [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # How to Improve Revenue Cycle Management: 8 Strategies for Healthcare Leaders [Krzysztof SzwedHead of Delivery at Flobotics](https://www.flobotics.io/our-editorial-team#szwed) Published June 25, 2025Updated September 1, 2026 On this page - [1. Optimize Patient Intake & Eligibility Verification](#1-optimize-patient-intake-eligibility-verification) - [Why it matters](#why-it-matters) - [How RPA/AI helps](#how-rpa-ai-helps) - [2. Ensure Accurate Coding and Documentation](#2-ensure-accurate-coding-and-documentation) - [Why it matters](#why-it-matters-2) - [How RPA/AI helps](#how-rpa-ai-helps-2) - [3. Streamline Claims Submission & Tracking](#3-streamline-claims-submission-tracking) - [Why it matters](#why-it-matters-3) - [How RPA/AI helps](#how-rpa-ai-helps-3) - [4. Strengthen Denial Management and Collections](#4-strengthen-denial-management-and-collections) - [Why it matters](#why-it-matters-4) - [How RPA/AI helps](#how-rpa-ai-helps-4) - [5. Embrace RCM Automation with RPA and AI](#5-embrace-rcm-automation-with-rpa-and-ai) - [Why It Matters](#why-it-matters-5) - [6. Enhance the Patient Financial Experience](#6-enhance-the-patient-financial-experience) - [Why it matters](#why-it-matters-6) - [How RPA/AI helps](#how-rpa-ai-helps-5) - [7. Leverage Data and KPIs for Continuous Improvement](#7-leverage-data-and-kpis-for-continuous-improvement) - [Why it matters](#why-it-matters-7) - [How RPA/AI helps](#how-rpa-ai-helps-6) - [8. Invest in Team Training and Cross-Functional Collaboration](#8-invest-in-team-training-and-cross-functional-collaboration) - [Why it matters](#why-it-matters-8) - [How RPA/AI helps](#how-rpa-ai-helps-7) - [Final Thoughts](#final-thoughts) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Hospital margins are under pressure, and revenue cycle inefficiencies are costing providers time and money. In 2023, [about 15% of initial claims were denied](https://www.mckinsey.com/industries/healthcare/our-insights/healthcare-blog/three-ways-to-ease-the-pressure-on-health-system-revenue-cycles#:~:text=This%20financial%20strain%20is%20compounded,accommodate%20new%20requests%20from%20payers), up from just 9% in 2016. The cost of handling administrative tasks like prior authorizations can run $6–$11 per claim. For healthcare leaders, this isn’t just a billing issue — it’s a financial imperative. [Revenue Cycle Management ](https://www.flobotics.io/rcm-automation)strategy isn’t about minor tweaks; it’s about rethinking how data, automation, and operations come together to ensure long-term success. This guide outlines eight core Revenue Cycle Management strategies for building a smarter, faster, and more resilient revenue cycle. From patient intake to collections, we’ll explore how clinics and hospitals can boost revenue performance, especially by leveraging technologies like [RPA (Robotic Process Automation)](https://www.flobotics.io/blog/robotic-process-automation) and AI (Artificial Intelligence). Fig. 01 · RCM strategy Blueprint RCM improvement blueprint - 01 Patient intake and eligibilityBots verify insurance in real time. - 02 Accurate coding and charge captureAI-assisted coding keeps documentation complete. - 03 Clean claimsBots catch errors before submission. - 04 Denial managementAI finds denial patterns and root causes. - 05 Patient financial experienceChatbots answer billing questions and give estimates. - 06 KPI trackingDashboards filled by automated data pulls. - 07 Staff enablementAutomation frees time for strategic work. - 08 Full-cycle automationRPA and agentic AI across the whole cycle. ## 1. Optimize Patient Intake & [Eligibility Verification](https://www.flobotics.io/agents/eligibility-check-automation) The revenue cycle starts before a patient ever receives care. Minor errors during patient intake – like a misspelled name, incorrect insurance ID, or missing prior authorization – can snowball into denied claims. Nearly [50% of claim denials stem from front-end issues](https://www.omegahms.com/blog/proactive-approaches-to-reducing-claims-denials/) such as registration/eligibility errors, missing claim data, or lack of pre-certification. These preventable mistakes directly impact cash flow: a claim denied for eligibility is revenue delayed (or lost entirely if not corrected in time). ### Why it matters Getting things right the first time means fewer headaches later. Industry experts advise aiming for a “clean” registration process, where all patient information and coverage details are verified upfront. This foundational step is critical to any effective Revenue Cycle Management strategy, as eliminating front-end errors helps organizations avoid a large portion of denials and the costly rework that follows. ### How RPA/AI helps RPA bots can automatically [verify insurance eligibility](https://www.flobotics.io/agents/eligibility-check-automation) in real-time as patients are scheduled, checking payer portals to confirm active coverage and benefits. This ensures you catch coverage issues before services are rendered. AI tools can also flag incomplete patient intake forms or prompt staff to collect missing information (like a referral or authorization) during check-in. The result is a smoother intake process with far fewer downstream billing surprises. In short, fixing the front-end with automation sets a solid foundation for your entire Revenue Cycle Management strategy. ## 2. Ensure Accurate Coding and Documentation Accurate coding and thorough documentation are the lifeblood of an effective RCM process. Every service must be documented and translated into the correct codes (ICD-10, CPT, etc.) and charges. If something isn’t documented or coded correctly, you won’t get paid for it – it’s that simple. Studies estimate that [1.5–2% of hospital claims fail to capture services](https://www.ruralhealth.us/blogs/2025/04/hidden-dollars-a-rural-hospital%E2%80%99s-guide-to-financial-survival) that were actually provided. Those are dollars left on the table due to missed charges or coding errors. Additionally, not correcting coding mistakes can lead to denials, underpayments, or even compliance risks. ### Why it matters In an era of tight margins, hospitals and clinics cannot afford to lose revenue due to avoidable documentation mistakes. Strengthening documentation and charge capture processes can have an immediate impact on revenue. For example, rigorous charge capture audits often uncover procedures or tests that were done but not billed. Even a small percentage of missed charges (say 2% of claims) can add up to significant annual revenue loss. Moreover, precise coding ensures you receive the appropriate reimbursement and reduces the chance of claims bouncing back from payers due to coding errors. ### How RPA/AI helps Automation and AI are game-changers for coding and documentation quality. AI-powered computer-assisted coding systems can scan clinical documentation and suggest proper codes, acting as a second set of eyes for human coders. This not only improves accuracy but also speeds up the coding process. RPA bots can assist with charge capture by cross-referencing appointment schedules, procedure logs, and billing systems to make sure every service is accounted for. For instance, if a bot notices a patient had a certain procedure documented in the EMR but no corresponding charge was generated, it can alert staff to investigate, preventing revenue from slipping through the cracks. By coding with precision and leveraging automation, healthcare organizations can significantly reduce denials related to coding and ensure no billable service goes unbilled. ## 3. Streamline [Claims Submission](https://www.flobotics.io/agents/claims-management-automation) & Tracking Filing insurance claims promptly and correctly is central to any [Revenue Cycle Management ](https://www.flobotics.io/blog/revenue-cycle-management)strategy. The goal is a high “first-pass” acceptance rate, meaning claims get paid on the first submission without edits or appeals. Every additional touch (resubmitting a claim, calling a payer, etc.) slows cash flow and drives up administrative costs. Industry data shows that roughly [15% of claims are initially denied](https://www.omegahms.com/blog/proactive-approaches-to-reducing-claims-denials/) by insurers, often due to avoidable errors or missing information. Furthermore, once a claim is submitted, the work isn’t over – consistent follow-up is needed to track claim status and handle any issues or delays. This can be incredibly time-consuming if done manually. ### Why it matters Efficient claims submission and follow-up directly impact how quickly your organization gets paid. High-performing RCM teams boast first-pass claim acceptance rates above 90%, which translates to faster reimbursement and fewer write-offs. On the flip side, if your process is sluggish or error-prone, accounts receivable days will balloon. Consider that manually checking the status of claims with payers is estimated to take 17–25 minutes per inquiry, time your staff could spend on more valuable work. Delayed follow-up can also result in missed appeal windows or even timely filing denials, where the insurer refuses payment because the claim wasn’t submitted or corrected in time. ### How RPA/AI helps RPA bots can scrub claims for errors (checking for missing data, invalid codes, or other common denial triggers) before submission, dramatically improving your clean claims rate. Some organizations have seen their first-pass resolution rate climb to 98% with claims automation, meaning almost all claims get approved on first try, leading to faster payments and fewer rework cycles. Additionally, bots can handle the tedious work of claims follow-up: automatically logging into payer websites or clearinghouses to check claim statuses and pulling back detailed info. The bots can even notify your team of pending issues (e.g. a claim that’s stuck or denied) so you can intervene quickly. All of this streamlines the revenue cycle, reduces days in A/R, and improves cash flow. Faster, error-free claims = healthier revenue. ## 4. Strengthen [Denial Management](https://www.flobotics.io/agents/denials-management-automation) and Collections Even with the best efforts on the front-end and claims submission, some denials are inevitable. Thus, a strong denial management process is crucial. This means not only working on denials to recover revenue, but also digging into why they occurred so you can prevent similar denials in the future. The scale of the denial problem in healthcare is significant: approximately [10–15% of claims get denied](https://www.healthcarefinancenews.com/news/revenue-cycle-challenged-low-collection-rates-high-denials) initially on average, and denial rates have been creeping upward yearly (one analysis noted a 15.7% increase in denials from 2020 to 2024). Each denial represents delayed or lost revenue, plus additional cost to appeal or correct the claim. ### Why it matters A high denial rate is essentially a sign of a broken revenue cycle process. Every denial is telling you something – maybe a trend (e.g., many denials from one payer for authorization, or a specific procedure being coded wrong). By analyzing root causes, healthcare leaders can fix systemic issues (like retraining staff on insurance eligibility, correcting a coding problem, or updating documentation protocols). The goal many experts recommend is to keep your [denial rate below 5% of claims](https://www.plutushealthinc.com/post/denial-management-in-revenue-cycle-management-workflows-strategies-and-automation). Achieving that level requires proactive management and continuous improvement. It’s worth the effort: reducing denials directly boosts revenue and also cuts out waste. Remember, more than half of denials are ultimately preventable through process improvements, especially those stemming from front-end and documentation issues. ### How RPA/AI helps Automation can significantly enhance denial management in two ways: reactive and proactive. On the reactive side, RPA bots can take over much of the manual work of denial processing – for example, retrieving denial codes and details from payer remittances, compiling the documentation needed for an appeal, and even submitting appeal letters through payer portals. This speeds up the response time and ensures no denial “falls through the cracks.” On the proactive side, AI analytics can sift through your denial data to spot patterns and root causes. Maybe an AI tool finds that a particular insurance company is denying 30% of claims for a certain procedure due to missing prior auth – insight that tells you to tighten your prior authorization checks for that insurer. By acting on root-cause insights, organizations can plug the leaks that cause denials in the first place. In practice, providers that embrace RCM automation report substantial improvements – [up to a 30% reduction in denial rates](https://trubridge.com/resources/transforming-healthcare-operations-the-power-of-revenue-cycle-management-automation/) after implementing automated claims and denial management solutions. Fewer denials mean more revenue captured and less money wasted on rework, which is a win-win for your RCM outcomes. Fig. 02 · Denials Root causes Claim denials: root causes and fixes Root causeFix - Eligibility issuesMissing or wrong insurance detailsRPA eligibility checks - Filing delaysLate submission to the payerRPA status checks - Coding errorsWrong or incomplete codesAI coding assistants - Incomplete documentationMissing supporting medical informationAI prompts for required data - Missing prior authorizationNo pre-approval obtainedAutomated prior auth bots ## 5. Embrace [RCM Automation](https://www.flobotics.io/rcm-automation) with RPA and AI Improving Revenue Cycle Management is ultimately a question of strategic resource allocation. Where are your teams spending the most time? Where is revenue slipping through the cracks? And which tasks are ripe for automation without compromising quality or compliance? Revenue Cycle Management strategy like RCM automation — using Robotic Process Automation (RPA) and Artificial Intelligence (AI) — offers a way to reallocate staff effort from manual busywork to high-impact analysis and patient service. While adoption is growing, many organizations still haven’t fully capitalized on automation’s ability to turn inefficient workflows into scalable, tech-enabled systems. ### Why It Matters RPA uses software bots to handle repetitive, rule-based tasks, like checking eligibility, submitting claims, or logging into payer portals, far faster and more accurately than human staff. These bots work 24/7, accelerating workflows and reducing burnout. On the intelligence side, AI adds a new layer of decision-making: Natural Language Processing (NLP) can extract billing codes from clinical notes, machine learning can identify denial patterns, and generative AI can assist in drafting appeal letters or explaining billing. #### Real-World Results: - [Auburn Community Hospital ](https://www.auburnhospital.org/)used RPA, NLP, and ML to cut 30–35 hours/week of manual appeal writing, improving speed and compliance ([AHA](https://www.aha.org/aha-center-health-innovation-market-scan/2024-06-04-3-ways-ai-can-improve-revenue-cycle-management#:~:text=in%20denials%20for%20services%20not,end%20appeals)). - [Banner Health](https://www.bannerhealth.com/) accelerated insurance discovery with an AI bot that integrated patient coverage into accounts in real time ([AHA](https://www.aha.org/aha-center-health-innovation-market-scan/2024-06-04-3-ways-ai-can-improve-revenue-cycle-management#:~:text=in%20denials%20for%20services%20not,end%20appeals)). [McKinsey estimates](https://www.mckinsey.com/industries/healthcare/our-insights/healthcare-blog/three-ways-to-ease-the-pressure-on-health-system-revenue-cycles#:~:text=Health%20systems%20have%20more%20tools,documentation%20improvement%2C%20and%20utilization%20management) that generative AI could reduce total U.S. healthcare spending by 5–10%, or up to $360 billion, mainly by automating administrative functions. Revenue cycle operations — with their high volume of manual tasks — are prime candidates for this transformation. Adopting automation in RCM isn’t as simple as flipping a switch. It takes careful planning, cross-functional alignment, and strong change management. Leaders must establish guardrails to manage AI risks and ensure human oversight. But when implemented strategically, RCM automation improves clean claim rates, lowers denial volumes, shortens reimbursement cycles, and empowers staff to focus on high-value work. It’s more than an operational upgrade — it’s a way to gain a lasting competitive advantage. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## 6. Enhance the Patient Financial Experience Today’s healthcare consumers expect a financial experience that is as clear and convenient as any other service they use. From price transparency before care to smooth billing and payment afterward, patient satisfaction now heavily depends on the financial side of their journey. This is not just a nicety – it has real revenue implications. Patients are now responsible for a larger share of healthcare costs, and [over 30% of provider revenue](https://www.mdclarity.com/blog/rcm-benchmarks) often comes directly from patients (through deductibles, co-pays, etc.). If the billing process is confusing or frustrating, those payments may be delayed or lost. Unfortunately, traditional medical billing often falls short: [surveys show](https://theconversation.com/got-an-unaffordable-or-incorrect-medical-bill-calling-your-hospital-billing-office-will-usually-get-you-a-discount-237743) 74% of patients find medical bills confusing, and 41% of patients are concerned their bills might contain errors, so much so that they may put off paying if they don’t trust the bill’s accuracy. Clearly, there is room to improve the patient financial experience. ### Why it matters A positive patient financial experience can lead to better collection rates and patient loyalty. When patients understand their bills and have easy ways to pay, they’re more likely to pay on time and in full. On the other hand, if bills are late, inaccurate, or opaque, providers may never collect what they’re owed and could even drive patients away. Consider that many patients now shop for healthcare with cost and billing experience in mind. Additionally, patient satisfaction scores are increasingly tied to billing: resolving billing questions and offering convenient payment methods can boost satisfaction ratings by a notable margin (one study cited a 15% increase in satisfaction when billing was clear and easy). In short, treating patients as valued customers in the revenue cycle isn’t just good ethics, it’s good business. ### How RPA/AI helps Automation and AI can significantly enhance the patient’s financial journey. For example, price estimation tools powered by AI can generate an accurate out-of-pocket cost estimate for patients before a procedure, pulling data from insurance contracts and patient benefits. This level of upfront transparency helps patients plan for expenses and reduces surprise bills. On the billing end, RPA can be used to send timely electronic statements and reminders. Chatbots and virtual assistants (often AI-driven) are another powerful tool: they can answer common billing questions 24/7, help patients set up payment plans, or even assist with checking insurance coverage, all without waiting for a phone call. These digital solutions meet patients where they are – on their smartphone or computer – and make the financial process more interactive and less intimidating. Automation can also minimize billing errors (for instance, by cross-verifying charges and payments), which builds patient trust. ## 7. Leverage Data and KPIs for Continuous Improvement You can’t improve what you don’t measure. An effective Revenue Cycle Management strategy requires regular tracking of KPIs and data-driven reviews. Rather than managing by gut feeling or anecdote, leading organizations use hard metrics to pinpoint bottlenecks and monitor improvements. There are several foundational RCM metrics every healthcare leader should monitor: - Days in Accounts Receivable (A/R) (how fast you collect) - Clean Claim Rate (percentage of claims paid on first submission) - Denial Rate (percentage of claims denied) - Net Collection Rate (how much of the owed revenue you actually collect, after adjustments) - and more. Tracking these over time and benchmarking against industry standards lets you identify where to focus your improvement efforts. The industry has rallied around data analytics in recent years: [FinThrive report found](https://revcosolutions.com/advancing-rcm-the-power-of-predictive-analytics/) RCM leaders are adopting analytics technology at a very high rate – 80–90% adoption in areas like A/R analytics, claims analytics, and coding analytics. Moreover, in one survey, 76% of healthcare CFOs planned to dedicate at least 10% of their tech budgets to predictive RCM analytics, recognizing the value of data-driven insights. This underscores that data and analytics are no longer optional – they’re a must-have for Reveny Cycle Management strategy. ### Why it matters Regular performance reviews using smart metrics create a continuous feedback loop for your revenue cycle. For instance, by reviewing your denial rate monthly, you might spot an uptick in denials from a particular payer, prompting a root cause analysis before the issue gets worse. Or by monitoring days in A/R, you might notice that one clinic or department lags others, indicating a workflow issue or staffing gap. Data-driven decisions tend to be more effective and targeted. They also help build a business case for investments: if you know your clean claim rate is only 85% and industry best practice is 95%+, you can quantify how much revenue is stuck in rework and justify spending on training or tools to improve it. The table below highlights a few key RCM metrics and commonly cited performance benchmarks: Fig. 03 · RCM metrics Benchmarks Key RCM metrics and benchmarks Metric | What it measures | Benchmark | Clean claim rate | % of claims paid on first submission, with no edits. Higher means better cash flow. | ≥95% for strong performers; many aim for 98% | Denial rate | % of claims denied by payers at first. Lower is better. | Industry average about 5–10%; top performers under 5% | Days in A/R | Average days from service to payment. Lower means faster collection. | 30–40 days for hospitals (HFMA); under 50 for practices | Net collection rate | % of allowed revenue collected after adjustments | Over 95%; best practice about 95–99% | Sources: [Clean Claim Rate](https://medwave.io/2024/10/what-is-a-clean-claim-rate/#:~:text=However%2C%20general%20industry%20benchmarks%20include%3A), [Denial Rate, Days in A/R, Net Collection Rate](https://www.mdclarity.com/blog/revenue-cycle-metrics-rcm-kpis) Healthcare leaders can run data-driven performance reviews monthly or quarterly by keeping a close eye on metrics like these. The data will spotlight where processes are slipping or succeeding. Over time, you can also see the impact of changes (e.g., if a new claims scrubber tool helped raise the clean claim rate, or if a staffing change reduced days in A/R). Celebrating improvements backed by data also boosts team morale – everyone can see the scoreboard. ### How RPA/AI helps RPA can automatically pull data from multiple sources (your [EHR](https://www.flobotics.io/blog/ehr-implementation-plan), billing system, clearinghouse, etc.) and populate dashboards or reports, saving analysts from tons of spreadsheet work. AI can take it a step further by providing predictive analytics – for example, forecasting next quarter’s cash flow based on current trends, or identifying patterns that human analysts might miss (such as subtle correlations between certain coding practices and denial rates). Some organizations employ [Machine Learning](https://www.flobotics.io/blog/robotic-process-automation-vs-machine-learning) models to predict which claims are most likely to be denied or which patient accounts are at risk of non-payment, allowing staff to prioritize those for intervention. Additionally, business intelligence dashboards can give real-time visibility into metrics across the revenue cycle, so managers aren’t waiting until month-end to spot a problem. The bottom line is that by automating the collection of KPI data and applying AI analytics, providers get actionable insights at their fingertips. This enables proactive management – you can course-correct in weeks or days instead of discovering issues months later. ## 8. Invest in [Team Training](https://www.flobotics.io/blog/automation-training) and Cross-Functional Collaboration At the heart of every revenue cycle are the people who make it happen, from front desk registrars and medical coders to billing specialists and denial coordinators. Investing in your RCM staff’s training and fostering cross-functional teamwork can yield significant dividends in efficiency and accuracy. Often, revenue cycle challenges arise not from bad intent but from knowledge gaps or siloed processes. For example, if front-line staff aren’t well-versed in the latest insurance requirements, they might collect incomplete info, leading to denials. Or if billing doesn’t communicate well with clinical departments, there may be disconnects in documentation and coding. When teams are understaffed or under-trained, errors and backlogs increase. Additionally, revenue cycle spans multiple departments, so alignment between them is crucial (hence the term “cross-functional alignment”). ### Why it matters Well-trained, knowledgeable staff can prevent errors before they happen. For instance, training front-end staff on insurance verification can directly reduce eligibility-related denials. Educating clinicians on documentation best practices can lead to more complete charts and fewer coding issues. Cross-functional alignment – such as regular huddles between the billing office, coding team, and clinical managers – ensures that everyone understands how their work impacts the revenue cycle downstream. It breaks down silos. The data supports this holistic approach: front-end knowledge gaps and staff shortages have been cited as major internal factors contributing to higher denials and [lower clean claim rates](https://www.omegahms.com/blog/proactive-approaches-to-reducing-claims-denials/). Conversely, organizations that emphasize ongoing RCM education and inter-department collaboration often see improvements in metrics like denial rates and days in A/R. In practice, this might involve initiatives like a Revenue Integrity Committee that brings together people from finance, coding, registration, and clinical operations to review performance and tackle issues collectively. ### How RPA/AI helps At first glance, automation might seem unrelated to staff training, but RPA and AI can augment your team and even improve job satisfaction. By automating the most tedious tasks (think copying data from one system to another, or trawling payer sites for claim info), RPA frees your staff to focus on higher-value activities that require human judgment and communication. This shift can make their jobs more fulfilling. It’s notable that [92% of companies reported](https://www.forbes.com/sites/forbestechcouncil/2022/09/28/how-healthcare-providers-can-improve-patient-experiences-with-rpa-ai-and-digital-workflows/?sh=ce963cf30557) improved employee satisfaction after implementing AI and RPA solutions, as mundane work was reduced. In terms of training, AI tools can be used to create smart training programs – for example, using analytics to identify common mistakes and then training staff specifically on those areas. Also, with less time spent on mind-numbing tasks, you can cross-train staff in multiple RCM functions (e.g., a person might get trained in both coding and billing follow-up), building a more flexible team that can cover each other’s duties. Ultimately, people + technology together yield the best results. Invest in your team’s skills and create an environment where automation is viewed as a helpful “digital coworker,” not a threat. ## Final Thoughts [Improving RCM ](https://www.flobotics.io/blog/ai-rpa-ml-rcm) is a journey of continuous refinement. These 8 Revenue Cycle Management strategies – from front-end fixes and coding precision to denial analytics and full-cycle automation – provide a roadmap for healthcare leaders to strengthen their RCM processes. The common thread is balancing people, process, and technology. By building a strong process foundation, investing in your team, and amplifying their efforts with RPA and AI, you create a revenue cycle that is efficient, resilient, patient-friendly, and ready for the future. In an industry where financial margins are tight, an optimized revenue cycle management strategy can deliver more than just revenue – it can free your staff to focus on patient care and strategic growth. Here’s to turning these strategies into practice and watching your organization’s financial performance improve, one smart change at a time. At [Flobotics](https://www.flobotics.io/), we specialize in RCM automation. From eligibility checks and claims processing to denial management and prior authorizations, we’ve helped healthcare providers slash costs, reduce errors, and scale operations easily. [Let’s discuss](https://www.flobotics.io/contact) how we can improve your Revenue Cycle Management strategy – together. #### Like the article? Spread the word Written byKrzysztof Szwed Head of Delivery at Flobotics. [More from Krzysztof](https://www.flobotics.io/our-editorial-team#szwed) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPAHealthcare ### Interoperability in Healthcare: What You Need to Know (And How to Get There with RPA) Healthcare interoperability, explained: how RPA connects clinics, insurers, and EHRs for faster, more reliable patient data flow. Michał RejmanOctober 03, 2023 ](https://www.flobotics.io/blog/interoperability-in-healthcare)[ Healthcare ### 5 Processes in the Healthcare Industry You Didn’t Know Could Be Automated Healthcare workflow automation: 5 everyday processes - from claims to billing - you can automate with RPA starting today. Michał RejmanAugust 01, 2022 ](https://www.flobotics.io/blog/healthcare-workflow-automation)[ AIHealthcareRPA ### Compliance Automation in Healthcare Healthcare compliance automation: how Continuous Control Monitoring and Agentic AI cut administrative drag by 20-30% in 2026. February 04, 2026 ](https://www.flobotics.io/blog/compliance-automation-healthcare) [All articles →](https://www.flobotics.io/blog) --- # Healthcare Document Processing: From Paperwork Pain to Automated Gain Canonical: https://www.flobotics.io/blog/healthcare-document-processing Author: Bart Teodorczuk Published: 2025-06-10 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Healthcare Document Processing: From Paperwork Pain to… [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm)[RPA](https://www.flobotics.io/blog?category=rpa) # Healthcare Document Processing: From Paperwork Pain to Automated Gain [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published June 10, 2025Updated September 1, 2026 On this page - [What Is Healthcare Document Processing Automation?](#what-is-healthcare-document-processing-automation) - [Insurance Claims and EOBs](#insurance-claims-and-eobs) - [Lab Results](#lab-results) - [Referrals and Authorizations](#referrals-and-authorizations) - [Patient Intake Forms](#patient-intake-forms) - [Other Paperwork](#other-paperwork) - [Where It Hurts Most: High-Volume Document Processes in Healthcare](#where-it-hurts-most-high-volume-document-processes-in-healthcare) - [Patient Intake & Records](#patient-intake-records) - [Insurance Claims Processing](#insurance-claims-processing) - [Prior Authorizations](#prior-authorizations) - [Patient Referrals](#patient-referrals) - [Medical Billing & Coding](#medical-billing-coding) - [How Automation Can Fix the Problem](#how-automation-can-fix-the-problem) - [1. Document Ingestion (Capture)](#1-document-ingestion-capture) - [2. OCR and Data Extraction](#2-ocr-and-data-extraction) - [3. Validation and Error Checking](#3-validation-and-error-checking) - [4. Integration and Processing](#4-integration-and-processing) - [5. Exception Handling & Learning](#5-exception-handling-learning) - [6. Archiving & Compliance](#6-archiving-compliance) - [Real-World Case Studies](#real-world-case-studies) - [Case Study #1: Automating Prior Authorizations for a Healthcare Platform](#case-study-1-automating-prior-authorizations-for-a-healthcare-platform) - [Case Study #2: Insurance Plan Comparison – Smarter, Faster, Cheaper](#case-study-2-insurance-plan-comparison-smarter-faster-cheaper) - [Final Diagnosis: Automation Is a Healthcare Necessity](#final-diagnosis-automation-is-a-healthcare-necessity) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Let’s not sugarcoat it: healthcare runs on documentation. And while saving lives might be the job, drowning in paperwork feels like the reality for most frontline workers, administrators, and even physicians. The problem? Healthcare documentation is: - endless - repetitive - manual - prone to errors - …and totally not what your team was trained for If you’re still relying on people to handle routine document tasks – copying data between systems, submitting claims, scanning forms – you’re bleeding time, money, and accuracy. The good news? Automation can fix this. And no, you don’t have to overhaul your entire tech stack to get started. ## What Is [Healthcare Document Processing](https://www.flobotics.io/blog/automated-document-processing) Automation? Healthcare organizations deal with an avalanche of documents every day. The document processing workflow touches almost every department, from administrative paperwork to clinical reports. It typically involves capturing incoming documents, extracting data, entering that data into systems (like EHRs or [billing systems](https://www.flobotics.io/blog/how-to-build-automated-medical-billing-system)), and then routing or storing the documents appropriately. Here are some of the most common document types in healthcare that clog inboxes and filing cabinets: ### [Insurance Claims](https://www.flobotics.io/blog/insurance-claims-processing-rpa-automation-use-cases) and EOBs Claim forms submitted to insurers and Explanation of Benefits (EOB) statements that detail what was paid. These often come in varying formats and require careful data entry and verification. ### [Lab Results](https://www.flobotics.io/blog/laboratory-automation-solutions) Laboratory test result forms (often PDFs or faxes) that need to be attached to patient records. They contain critical values, patient info, and physician notes that must be accurately transcribed. For document matching, missing records and payer correspondence, see our [laboratory automation workflows](https://www.flobotics.io/who-we-help/laboratories). ### Referrals and Authorizations Physician referral letters and prior authorization forms for treatments or medications. These are frequently faxed or emailed between providers and payers, and someone has to manually key in the details. ### Patient Intake Forms The [registration](https://www.flobotics.io/contact) and consent forms that new patients fill out (either on paper or viathe portal). This includes personal details, insurance information, medical history, etc., which staff must enter into electronic systems. ### Other Paperwork Prescription orders, discharge summaries, billing statements, and consent forms are just a few of the many documents circulating. Each requires data to be read, interpreted, and acted on. Fig. 01 · Documents 4 challenges Document challenges in healthcare - 01Regulatory compliance - 02Many different medical forms - 03Misplaced or lost information - 04Keeping data secure How does it all flow today? In a traditional workflow, a staff member receives the document (mail, fax, scan, or email), reads it, and then types the relevant information into another system (like an EMR, billing software, or a spreadsheet). They might then forward the document to the next department or file it away. If any information is missing or looks wrong, it might bounce back for clarification. This manual handling of documents is slow and error-prone, leading to serious challenges, which we’ll explore next. ## Where It Hurts Most: High-Volume Document Processes in Healthcare [Handling documents](https://www.flobotics.io/business-process-automation) in healthcare is notoriously cumbersome. Let’s face it – healthcare as an industry is still hooked on paperwork (yes, people still use fax machines in 2025 – healthcare, we’re looking at you!). Below, we spotlight the biggest pain points in specific healthcare processes where manual document processing hurts the most: ### Patient Intake & Records New patients often begin by filling out paper intake forms, which staff then must transcribe into [Electronic Health Record (EHR) systems](https://www.flobotics.io/blog/ehr-implementation-plan). This duplicate data entry is time-consuming and error-prone. Important patient information can be lost or mis-entered, especially if handwriting is hard to read. ### [Insurance Claims Processing](https://www.flobotics.io/agents/claims-management-automation) Filing and processing insurance claims involves mountains of forms and coding details. Every claim must be perfectly filled out, verified against the patient’s coverage, submitted, then often corrected or appealed if denied. Mistakes in data entry or missing information lead to rejections and rework, which delays reimbursement and strains the [revenue cycle](https://www.flobotics.io/rcm-automation). ### [Prior Authorizations](https://www.flobotics.io/agents/prior-authorization-automation) Obtaining prior authorization for treatments or medications is consistently cited as one of healthcare’s biggest administrative pain points. The process typically requires filling out forms and sending clinical notes to insurance for approval, often via fax or portal, then waiting for a response. It’s inefficient and frustrating for providers, staff, and patients alike. ### Patient Referrals When a provider refers a patient to a specialist or for outside services, there’s often a referral document or letter that needs to be sent along with relevant records. In theory, this could be digital, but in reality many referrals still get faxed or handed off as paper. Inefficient referral workflows mean patients fall through the cracks; one industry survey found as many as half of referrals never actually result in a completed appointment. Manual referral processes (phone calls, faxes, paper trails) contribute to those gaps in care. ### [Medical Billing](https://www.flobotics.io/rcm-automation) & [Coding](https://www.flobotics.io/blog/medical-coding) Turning clinical documentation into billing claims with proper codes is another document-heavy task. Often, coders or billers must review physician notes, lab reports, etc., and manually input codes and charges into billing systems. This is tedious and error-prone. Typos or coding errors can lead to claim denials. Additionally, billing staff have to generate patient invoices and statements (sometimes printing and mailing them – more documents!). The complexity of billing rules means that without automation, staff end up poring over documents and systems to reconcile accounts. Fig. 02 · Documents 7 types Healthcare documents you can automate - Prescriptions - Registration forms - Patient records - Medical transcription - Test results - Insurance claims - Billing forms These pain points highlight a common theme: manual document processing is slow, expensive, and error-prone. It burdens your staff (contributing to burnout), drains resources, delays revenue, and can even compromise patient care or compliance. The good news? It doesn’t have to be this way. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## How Automation Can Fix the Problem Modern automation technologies like [Robotic Process Automation (RPA)](https://www.flobotics.io/blog/robotic-process-automation), [Optical Character Recognition (OCR)](https://aws.amazon.com/what-is/ocr/), [Artificial Intelligence (AI)](https://www.flobotics.io/blog/ai-rpa-ml-rcm), and [Natural Language Processing (NLP)](https://www.ibm.com/think/topics/natural-language-processing), in plain terms, let you hand off the grunt work to software “bots” and intelligent algorithms. They can fetch, read, interpret, and input document data much faster and more accurately than humans, all while following the rules you set. Fig. 03 · Documents How it works How automation fixes document processing - 01Capture - OCR and AI pull data from scans, PDFs, emails and faxes - Identifies the document type - 02Extract and structure - NLP and OCR pull patient name, date of birth, diagnosis and codes - Turns them into usable data (JSON, CSV, API) - 03Validate - Business rules check completeness, logic and format - Flags missing fields and anomalies - 04Act and update systems - Bots enter data into the EHR, billing and payer portals - Trigger next steps: submit a claim, send a referral - 05Handle exceptions - Unclear documents go to a person - Learns from corrections - 06Archive - Files each document in the right place - Keeps an audit trail for HIPAA Let’s walk through a step-by-step example of how a document can move through an automated system, transforming a once-manual process into a streamlined digital flow: ### 1. Document Ingestion (Capture) The process kicks off by capturing the document automatically. Instead of a staff member printing out a form or downloading an email attachment, an intelligent capture system or RPA bot gathers the documents as soon as they arrive. For example, an incoming lab result fax could be grabbed from a fax server, or patient intake forms submitted online are automatically collected. No more piles of paper on a desk or hunting through email – the system has the document ready to go. ### 2. OCR and Data Extraction Once the system has the document, it uses OCR (Optical Character Recognition) and AI to read the content and extract key data. Think of this as a supercharged digital eye scanning the page. - For structured forms (like insurance claim forms or standard lab reports), the software locates each field (patient name, ID number, diagnosis codes, etc.) and converts the text or handwriting into machine-readable data. - For less structured documents (like a referral letter or a physician’s narrative report), AI and NLP algorithms interpret the text, picking out important details (e.g. patient info, referred specialist, urgency, medical terms). The output is organized data – for instance, a JSON or XML file with all the relevant fields and values. This happens in seconds, and modern intelligent document processing tools can achieve very high accuracy (often 90–99%+ accurate after tuning). ### 3. Validation and Error Checking Next up: quality control — but without the clipboard and red pen. The extracted data is automatically validated against business rules. Missing patient ID? Wrong date format? Billing code not matching a known set? The system flags it. Think of it like having a hypervigilant QA person built into the process. It prevents garbage data from leaking into downstream systems. If something’s off, the system can either fix it (minor OCR tweaks) or route it to a human reviewer. ### 4. [Integration and Processing](https://www.flobotics.io/blog/interoperability-in-healthcare) Here’s where RPA shines. With clean data in hand, software bots now take over the tedious work of entering data into the necessary systems and triggering next steps. For instance, an RPA bot can log into your EHR or [claims management](https://www.flobotics.io/agents/claims-management-automation) software and input the extracted data into the appropriate fields (emulating exactly how a human would click and type, but much faster). Or the bot might upload the document image and attach it to the patient’s record. If it’s an insurance claim, the bot can submit the claim through the insurer’s portal or via an API. All of this happens without your staff touching a keyboard. ### 5. Exception Handling & Learning Of course, not every document will be perfect. That’s where exception handling comes in. If something doesn’t pass validation — say, an illegible scan or missing signature — it’s flagged for manual review. But instead of reviewing everything, your team only checks what actually needs attention. And with a human-in-the-loop setup, the system can learn from corrections over time, reducing exceptions with every cycle. Bonus: Every action is logged, so you get full traceability — ideal for compliance, training, or just proving your bots are doing their job. ### 6. Archiving & [Compliance](https://www.flobotics.io/rcm-automation) Last but not least — every processed document needs a proper home. Once everything’s done, automation takes care of filing and storing the document in the right place: cloud folders, EHR archives, document management systems — wherever you need it. But this isn’t just digital tidying. Automation tools create a full audit trail of every step taken — when the document came in, what data was extracted, which systems were updated, and who (or what) did it. So when compliance season rolls around (hello, HIPAA), you’re ready. No scrambling through folders or guessing who updated what. Just clean, trackable, secure documentation — every time. By following these steps, automation handles the heavy lifting of document processing. No more printing emails, squinting at faxes, manually typing data into multiple systems, or shuffling files from desk to desk. The process becomes digital, fast, and human-friendly. These technologies – RPA bots, OCR engines, AI/NLP models – effectively become your digital back-office team. They work 24/7, don’t make mistakes, and scale effortlessly when volumes spike (say, during insurance claim surges or end-of-month reporting crunches). The result isn’t just speed — it’s smarter, cleaner, more compliant healthcare operations. Fig. 04 · Documents 5 benefits Benefits of automating document processing Benefit | Why it matters | Faster processing | Claims go out in minutes, not days | Fewer errors | No costly mistakes in patient data or billing codes | Lower cost | 70–80% of routine document handling automated at a fraction of the cost | Better compliance | Automatic audit trails and instant access to documents | Better patient experience | Staff spend less time on forms and more on care | ## [Real-World Case Studies](https://www.flobotics.io/blog/rpa-use-cases-across-industries) When healthcare organizations automate document processing, the gains aren’t just about time and money — they’re about care quality, patient satisfaction, and smoother operations. Here’s what our clients and partners typically see: #### Faster Patient Onboarding Intake forms are processed in real time. No more backlog at the front desk, and patients don’t have to repeat info 3 times. #### Cleaner EHRs With bots entering and validating the data, medical records are complete and accurate, which means fewer chart corrections down the line. #### Smoother Insurance Flow Claims go out correctly the first time. Less time chasing denials, more time getting reimbursed. #### Quicker Prior Authorizations Bots gather documents and submit them automatically. Patients don’t wait weeks just to start treatment. #### Happier Billing Teams No more digging through PDFs. Coders and billers get structured data ready to go. #### Audit-Ready Compliance Every document is logged, tracked, and stored — no scrambling when auditors knock. ### Case Study #1: Automating [Prior Authorizations for a Healthcare Platform](https://www.flobotics.io/agents/prior-authorization-automation) #### The Challenge: A healthcare platform faced significant delays in processing prior authorizations, leading to treatment bottlenecks and increased administrative workload. #### The Solution: We implemented an automated system that streamlined the prior authorization process. By integrating RPA and AI technologies, the platform could automatically gather necessary patient information, verify insurance details, and submit authorization requests without manual intervention. #### The Outcome: - 13 FTEs worth of manual work eliminated - 15,000 prior authorization items processed every month - ~$700,000 saved annually in labor and operational costs ### Case Study #2: [Insurance Plan Comparison](https://www.flobotics.io/case-studies) – Smarter, Faster, Cheaper #### The Challenge: [IHA](https://insurehelpagency.com/)’s agents were manually comparing insurance plans for clients, pulling in data from multiple providers. This took up valuable time and left too much room for human error. #### The Solution: We built a scalable automation setup that extracts plan data, compares variables like coverage and pricing, and delivers a neatly packaged result — all in seconds. #### The Outcome: - 0.5 FTE saved - $25,000 saved annually - 100% ROI achieved in under 12 months ## Final Diagnosis: Automation Is a Healthcare Necessity Healthcare organizations don’t have to be stuck in the paperwork grind. [Healthcare document processing](https://www.flobotics.io/healthcare-document-processing) can be faster, cheaper, and better with the right automation approach. By leveraging RPA, OCR, and AI, you can eliminate the most painful manual tasks in claims, authorizations, referrals, billing, and more. The payoff isn’t only in dollars saved or minutes shaved – it’s in a more agile organization that can devote resources to care and innovation instead of clerical work. If you’re tired of drowning in documents and want to explore automating your document-heavy processes, [get in touch with Flobotics](https://www.flobotics.io/contact). We have deep experience in healthcare automation and a track record of delivering practical, high-impact RPA solutions for providers, payers, and health tech companies. We’re happy to discuss your specific challenges and show how our bots and intelligent automation tools can relieve your team from the paperwork nightmare. It’s time to let technology do the boring stuff so your people can focus on what truly matters: delivering excellent healthcare! #### Like the article? Spread the word Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### Document Understanding Tools Overview Document understanding tools compared: top platforms, use cases, and how they streamline document management workflows for teams. Krzysztof SzwedJuly 04, 2024 ](https://www.flobotics.io/blog/document-understanding-tools)[ AIHealthcareRPA ### Compliance Automation in Healthcare Healthcare compliance automation: how Continuous Control Monitoring and Agentic AI cut administrative drag by 20-30% in 2026. February 04, 2026 ](https://www.flobotics.io/blog/compliance-automation-healthcare)[ Healthcare ### Healthcare Compliance Automation: Laws, Benefits and Examples Compliance automation software for healthcare: how RPA helps organizations meet evolving regulations without adding manual review work. Filip NasiadkoOctober 09, 2023 ](https://www.flobotics.io/blog/compliance-automation) [All articles →](https://www.flobotics.io/blog) --- # EHR Implementation: How to Not Screw It Up Canonical: https://www.flobotics.io/blog/ehr-implementation-plan Author: Yana Pokora Published: 2025-05-26 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/EHR Implementation: How to Not Screw It Up [AI](https://www.flobotics.io/blog?category=ai)[Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm)[RPA](https://www.flobotics.io/blog?category=rpa) # EHR Implementation: How to Not Screw It Up [Yana PokoraContent Manager at Flobotics](https://www.flobotics.io/our-editorial-team#pokora) Published May 26, 2025Updated September 1, 2026 On this page - [How Long Does EHR Implementation Take?](#how-long-does-ehr-implementation-take) - [1. EHR System Complexity](#1-ehr-system-complexity) - [2. Data Migration and Cleanup](#2-data-migration-and-cleanup) - [3. Customization and Configuration](#3-customization-and-configuration) - [4. Vendor Support and Responsiveness](#4-vendor-support-and-responsiveness) - [EHR Implementation Steps (Avoid the Common Screw-Ups)](#ehr-implementation-steps-avoid-the-common-screw-ups) - [Step 1: Define Your Goals](#step-1-define-your-goals) - [Step 2: Build Your Implementation Team](#step-2-build-your-implementation-team) - [Step 3: Map Out Current Workflows](#step-3-map-out-current-workflows) - [Step 4: Choose the Right EHR Software](#step-4-choose-the-right-ehr-software) - [Step 5: Data Migration & Integration](#step-5-data-migration-integration) - [Step 6: Staff Training](#step-6-staff-training) - [Step 7: Test the Hell Out of It](#step-7-test-the-hell-out-of-it) - [Step 8: Go Live (and Don’t Ghost Your Staff)](#step-8-go-live-and-dont-ghost-your-staff) - [EHR Implementation Risks: Don’t Step in These Traps](#ehr-implementation-risks-dont-step-in-these-traps) - [Risk #1: Poor Planning](#risk-1-poor-planning) - [Risk #2: Underestimating Training Needs](#risk-2-underestimating-training-needs) - [Risk #3: Bad Data Migration](#risk-3-bad-data-migration) - [Risk #4: Vendor Lock-In or Shitty Support](#risk-4-vendor-lock-in-or-shitty-support) - [Risk #5: Ignoring Compliance](#risk-5-ignoring-compliance) - [Risk #6: No Post-Go-Live Plan](#risk-6-no-post-go-live-plan) - [EHR Automation with RPA: The Power Add-On You Didn’t Know You Needed](#ehr-automation-with-rpa-the-power-add-on-you-didnt-know-you-needed) - [What You Get from Automating Your EHR](#what-you-get-from-automating-your-ehr) - [TL;DR — You’ve Got This](#tl-dr-youve-got-this) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) If you’re a clinic, hospital, or private practice, you probably already use some form of an EHR platform — or you’re about to. The problem? It’s not just about choosing a tool. It’s about integrating your existing systems and workflows into that EHR in a way that doesn’t break everything. That’s where most teams screw up. An EHR implementation plan isn’t about plugging in software and calling it a day. It’s about deploying the EHR so it seamlessly connects to your existing systems — appointments, billing, patient records, labs, even your Excel sheets if that’s what you’ve been using. Whether you’re switching EHRs or starting from scratch, integration is the name of the game. Let’s break down how to do it right. What Is EHR? And What Exactly Needs to Be Implemented? EHR stands for Electronic Health Record, and it’s not just a digital folder where you stuff patient files. It’s an entire ecosystem of patient data, workflows, medical histories, prescriptions, lab results, and communication tools — all in one place, accessible to the right people at the right time. Fig. 01 · EHR Who it connects Who the EHR system connects EHR system - 01Diagnostic lab - 02Physicians - 03Emergency services - 04Hospital - 05Nursing - 06Family and friends - 07Medical apps - 08Medical doctors That’s what actual EHR deployment looks like: - Migrating data from older systems or spreadsheets - Syncing with appointment scheduling, billing, insurance, and communication tools - Automating documentation - Making records accessible and usable in real-time, across your staff Let’s examine the results when it’s done correctly. #### According to ONC/HealthIT.gov (2024 data): - As of 2024, [91% of office-based physicians and over 99% of non-federal acute care hospitals had adopted a certified EHR](https://healthit.gov/data/quickstats/national-trends-hospital-and-physician-adoption-electronic-health-records/), up from just 17% and 9% respectively in 2008. ## How Long Does EHR Implementation Take? ### 1. EHR System Complexity Not all EHRs are built the same. Platforms like [Epic](https://www.epic.com/) or [Oracle Health, formerly Cerner (EHR in Practice)](https://www.ehrinpractice.com/cerner-ehr-vendor-profile-109.html) are powerful but come with steep learning curves, complex architecture, and stricter configuration requirements. Lighter platforms like [Athenahealth](https://www.athenahealth.com/solutions/electronic-health-records) or [NextGen](https://www.nextgen.com/) can be integrated faster but might offer fewer out-of-the-box customization options. The more features and modules you use, the longer the setup and integration timeline will be. ### 2. Data Migration and Cleanup Transferring legacy data into your EHR is one of the most time-consuming steps. If you’ve got years of patient records scattered across spreadsheets, outdated databases, or multiple software tools, the process of: - Extracting - Cleaning - De-duplicating - Standardizing - Importing It can take weeks or months, especially if you need to preserve compliance (e.g., [HIPAA](https://www.flobotics.io/blog/hipaa-compliance-rpa)) or map to new data structures. ### 3. Customization and Configuration EHR platforms don’t just plug and play. You’ll likely need to: - Customize workflows - Set up forms, templates, and permissions - Configure APIs or integrations with other tools (e.g., billing, lab systems, scheduling software) The more tailored you want your setup to be, the longer it will take. However, remember: a well-configured EHR system = smoother operations down the line. ### 4. Vendor Support and Responsiveness A slow or unresponsive EHR vendor can delay the entire deployment. On the flip side, vendors that offer strong onboarding support, detailed documentation, and responsive technical teams can speed things up significantly. If you’re working with an external deployment partner (like a dev agency that specializes in EHR integrations), their experience and relationship with EHR vendors can also streamline the entire process. #### Rough Timeframes to Give You an Idea: To help you understand what you might be looking at, here are some ballpark estimates based on typical scenarios: - Small clinics with minimal systems and essential integration needs: ~3–6 months - Mid-sized practices with moderate customization and data migration: ~6–12 months - Large hospitals or multi-location organizations with complex systems and deep integrations: 12–18+ months The more systems you integrate — and the more custom the solution — the more time you need. But rushing this step is the fastest way to break everything later. ## EHR Implementation Steps (Avoid the Common Screw-Ups) Here’s the list of steps it’s better to stick to if you want to get the maximum results from your EHR deployment — fewer headaches, smoother adoption, and a system that actually works for your team, not against it. These aren’t just “nice-to-haves” — they’re critical moves that separate successful implementations from painful messes. Fig. 02 · EHR 7 steps EHR implementation plan, step by step - 01Define your goalsSet clear objectives and KPIs. - 02Build your teamProject manager, clinical leads, IT and integration experts. - 03Map current workflowsUnderstand today’s admin, clinical and billing processes. - 04Choose the right EHRMatch platform strengths to your clinical workflows. - 05Data migration and integrationClean, standardize and import legacy data; connect the EHR. - 06Staff trainingSimulate real workflows and fix bugs before go-live. - 07Go live and supportReal-time support, feedback and post-launch tuning. ### Step 1: Define Your Goals What’s your endgame? Faster documentation? Better patient care? [Easier compliance](https://www.flobotics.io/blog/hipaa-compliance-rpa)? Write it down. Align it with KPIs. ### Step 2: Build Your Implementation Team You need: #### A project manager (the boss) The one keeps everything on track, communicates across teams, and ensures timelines and goals are met. This is your point of accountability. #### Clinical leaders (who actually use the thing) The nurses, doctors, and admin staff who will use the system daily. Their input is critical to ensure the EHR works in the real world, not just in theory. IT support (the nerds who save the day) These are your technical guardians. They ensure infrastructure, security, integrations, and troubleshooting are handled precisely. They’ll work closely with both the EHR vendor and any external partners. #### Vendor reps/Integration Experts (they know the ins and outs) This is where things get flexible. Your “vendor rep” doesn’t have to be someone on the EHR provider’s payroll. In fact, in most modern deployments, this role is filled by external EHR integration specialists or a [development agency](https://www.flobotics.io/) that handles implementation end-to-end. For example, we at [Flobotics](https://www.flobotics.io/) provide this as a productized service, meaning: - you get a ready-to-go team of automation engineers and healthcare tech experts - we work with your internal staff and chosen EHR vendor - you pay via a [subscription-based model](https://www.flobotics.io/blog/top-rcm-trends-healthcare), not unpredictable hourly billing - you receive a clearly defined EHR implementation plan, including scope, timelines, deliverables, and coverage of automation. The success of your EHR implementation plan depends heavily on the team driving it. Whether you’re building that team internally, bringing in specialized freelancers, or partnering with an experienced development agency, the key is making sure every role is covered — from clinical insight to tech execution. With the right mix of stakeholders, tech pros, and integration experts, your EHR deployment stops being a risky IT project. It becomes a structured, collaborative transformation of how your organization delivers care. ### Step 3: Map Out Current Workflows This step is critical — and often skipped. Before deciding how to implement an EHR, you must fully [understand your current processes](https://www.flobotics.io/blog/what-processes-to-automate). What’s working? What sucks? Only then should you design the new system Start by mapping: - Administrative tasks (e.g., [patient registration](https://www.flobotics.io/contact), intake forms) - Clinical workflows (e.g., charting, lab orders, prescribing) - Back-office ops (e.g., [billing](https://www.flobotics.io/agents/claims-management-automation), [claims](https://www.flobotics.io/agents/claims-management-automation), [RCM reporting](https://www.flobotics.io/rcm-automation)) Ask: - What’s working well? - What’s a bottleneck? - Where does data live, and how does it move? This workflow mapping serves as the blueprint for the entire integration process, outlining precisely what needs to be connected, what should be automated, and what can be optimized for improvement. You can tackle this internally if your team has a strong understanding of existing workflows and how they translate into digital systems. But you don’t have to do it alone. Many organizations choose to map processes together with their EHR vendor or integration partner. Experienced implementation teams can guide you through the process, help uncover inefficiencies, and highlight what’s worth automating, saving you time and future rework. Whether done in-house or collaboratively, this step lays the foundation for a smoother and more aligned EHR implementation plan. ### Step 4: Choose the Right [EHR Software](https://www.flobotics.io/blog/healthcare-software) One of the most strategic parts of your EHR implementation plan is choosing the right software to deploy — and it goes far beyond just picking the most popular name in the industry. The real question is: Which EHR system aligns best with the processes you want to automate? If your priority is streamlining appointment scheduling, patient intake, and daily clinical operations, you’ll likely need a different setup than a group focused on automating claims processing, insurance validation, or lab integrations. Each EHR platform has its strengths: - Some shine in large-scale enterprise environments with complex interoperability needs. - Others are better suited for agile outpatient practices or specialty clinics with specific workflows. - Some offer out-of-the-box simplicity, while others provide deep customization options, at the cost of complexity. Fig. 03 · EHR Matchmaker Which EHR fits your priorities EHR software | What it is good for | Epic | Enterprise-wide operations and complex multi-system integrations | Cerner | Clinical and financial automation at scale; hospital networks | athenahealth | Cloud-first setups with strong UX and core outpatient workflows | eClinicalWorks | Mid-sized practices that need broad customization | NextGen | Specialty clinics, population health, modular features | Kareo | Small practices; core admin automation (scheduling, billing, notes) | With so many overlapping features and pricing models, deciding on the right platform can easily stall progress, especially if you don’t have time to dive deep into every demo and documentation set. That’s where working with a healthcare-experienced development agency makes all the difference. Agencies that specialize in healthcare automation and EHR integration bring: - First-hand experience with different EHRs across clinical settings - Insights into what works (and what doesn’t) for practices like yours - A strategic view of how your systems can be integrated efficiently, not just configured An experienced team can guide you through the platform selection process based on your workflows, technical environment, and long-term goals, helping you avoid costly mismatches before they happen. ### Step 5: Data Migration & Integration Once your workflows are mapped and your software is selected, it’s time for the heavy lifting: moving your data and ensuring it flows properly between systems. Data migration isn’t just about dumping old records into a new system. It requires: - Cleaning and standardizing inconsistent data - De-duplicating patient records - Matching formats to your EHR’s schema - Migrating historical records, attachments, and documents — all while keeping data integrity intact This step is especially critical in healthcare, where messy or missing data doesn’t just slow you down — it can compromise patient safety and lead to legal compliance issues. Then comes integration — connecting your EHR to other systems you use, such as billing software, lab tools, scheduling platforms, and insurance APIs. This is where automation comes in. If done well, you reduce repetitive data entry, eliminate sync issues, and give your team a truly unified view of operations. #### Pro tip: Involve your dev/automation team early to align data structures and avoid future rework. A well-thought-out integration approach can save months of headaches later. ### Step 6: [Staff Training](https://www.flobotics.io/blog/automation-training) Your EHR is only as good as the people using it. Even the most potent system will cause chaos if your team isn’t confident and comfortable with it. And let’s be honest — change is hard, especially when it touches every part of daily work. Build training into your EHR implementation plan from day one. Plan for: - Role-based training (admin, clinical, billing) - Live walkthroughs and recorded videos - Quick-start guides and cheat sheets - A few “super users” or internal champions who can support their peers And remember, training is not a one-off. Plan for ongoing support, including regular check-ins and refreshers. We have written a comprehensive breakdown on how to approach automation training, particularly in clinical environments. Feel free to discover it. ### Step 7: Test the Hell Out of It Before you go live, you need to simulate reality as closely as possible. This isn’t the time for a quick demo run — it’s time to intentionally break things, identify gaps, and ensure everything works as intended before real patient data is involved. What to test: - End-to-end patient flows (registration → documentation → billing) - Third-party integrations (labs, billing systems, etc.) - User access levels, permissions, and security protocols - Data syncing and backups - Compliance checks (HIPAA, audit trails, etc.) This phase should include real staff running through real scenarios with fake data. It’s your last line of defense against confusion and disruption. ### Step 8: Go Live (and Don’t Ghost Your Staff) When the big day arrives, you need more than a green light — you need a support system. Expect hiccups, questions, and edge cases. That’s normal. What’s not normal is your team feeling abandoned during a stressful transition. During go-live week: - have IT and vendor support fully available — onsite or on-call; - set up a communication channel for rapid issue reporting ([Slack](https://slack.com/), [Microsoft Teams](https://www.microsoft.com/en-us/microsoft-teams/group-chat-software), or whatever internal system your team uses); - check in with departments daily to identify pain points early; - celebrate small wins and reassure your staff that support is ongoing. Post-launch, continue to optimize the system based on real-world usage. Ask for feedback, run minor improvements, and maintain a culture of openness around change. The EHR implementation plan doesn’t end at launch — it evolves with your team. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## EHR Implementation Risks: Don’t Step in These Traps You want to avoid chaos? Here’s what to watch out for: ### Risk #1: Poor Planning No timeline, no goals, no ownership = guaranteed failure. Your EHR implementation plan should be as detailed as a bomb defusal guide. ### Risk #2: Underestimating Training Needs Skipping training is like handing someone a plane and saying, “Fly it.” Invest time upfront, or pay for it later with frustrated staff and clinical errors. ### Risk #3: Bad Data Migration Junk in = junk out. Old records, inconsistent formats, duplicate files — clean it up before you migrate. ### Risk #4: Vendor Lock-In or Shitty Support Choose a vendor that doesn’t ghost you once the check clears. [Check reviews](https://clutch.co/profile/flobotics-uipath-rpa-development#summary), ask for references, and read the fine print in the contract. ### Risk #5: Ignoring [Compliance](https://www.flobotics.io/blog/compliance-automation) HIPAA doesn’t care if you’re new to EHR. Secure your system. Encrypt everything. Set access levels. And don’t even think about skipping audit trails. ### Risk #6: No Post-Go-Live Plan After launch, you’ll hit bugs, resistance, and adaptation issues. Plan for 3–6 months of follow-up optimization and support. ## EHR Automation with RPA: The Power Add-On You Didn’t Know You Needed Let’s be real: even the best EHR system — fully configured, custom-integrated, lovingly deployed — still has gaps. You’ll always find parts of your workflow that feel clunky, repetitive, or just unnecessarily manual. This is where [Robotic Process Automation](https://www.flobotics.io/blog/robotic-process-automation) steps in, serving as a digital sidekick. With RPA, you can layer automation over your EHR, adding extra functionality or replacing time-consuming manual work altogether. It’s not about replacing your people — it’s about freeing them up to do the work that actually matters. Think of it like this: - Your front desk is drowning in appointment scheduling? Automate it. - Does your billing team spend half the day on claims submissions? Automate it. - Your nurses are still typing up intake notes line-by-line? Yup — automate that too. We’ve helped healthcare teams automate everything from claims handling and patient onboarding to eligibility checks and EHR-to-billing platform syncs. And the results speak for themselves. Here are just a couple of examples from the trenches: #### Case Study: Automated patient data migration from multiple systems into one centralized EHR for Docplanner: - Reduced manual work time by over 40%, freeing up time for patient care - Cut human input errors by 70% #### SuperBill’s EHR integration between the EHR system and billing platforms: - Data processing time was cut by 95% - Reduced claims handling time from 30 minutes to under 2 minutes per case Want to See It Instead of Just Reading About It? We’ve also put together a few screencasts that walk through common EHR workflows — automated. Patient intake and appointment flow in PracticeQ EHR Patient registration & booking in SimplePractice EHR These aren’t mockups. These are real bots working in real systems. If you’re unsure what RPA might look like in your setup, these are a great starting point. ### What You Get from Automating Your EHR Still not convinced automation is worth the trouble? Let’s talk about what you actually unlock: #### Time Back for Your Team Your admin staff didn’t sign up to copy-paste patient IDs all day. Automation handles routine clicks, allowing them to focus on patients, not paperwork. That means fewer headaches, less burnout, and more value from your team. #### Fewer Mistakes, Better Compliance Mistakes in healthcare aren’t just annoying — they can be dangerous. RPA bots don’t get distracted, tired, or rushed. They follow the rules you set, every time. That means cleaner data, safer care, and smoother audits. #### Room to Grow Without Growing Pains When your clinic expands, do you hire five more people just to do the same work? With automation, you can scale your operations without scaling your overhead. Bots handle the volume so your team doesn’t get swamped. #### Real Savings Where It Counts Billing, eligibility checks, insurance verifications — all prime areas for RPA to save serious cash. You’re reducing costly delays, speeding up reimbursements, and cutting down on manual processing hours. #### A Better Experience for Everyone Faster scheduling. Fewer billing errors. Shorter wait times. When your back-end runs smoother, your front-end does too. And your patients notice. ## TL;DR — You’ve Got This Yes, EHR implementation can be a beast. There are a million ways to screw it up — insufficient data, wrong vendor, frustrated staff, integrations that don’t talk to each other. But when do you do it right – it’s a game-changer. You’ll streamline operations, cut manual work, reduce errors, and give your team time to focus on what matters most — the patients. The key is having a clear, structured EHR implementation plan, the right people on board, and experienced tech partners who know how to navigate the messy middle. And hey, you don’t have to figure this out alone. Need support with EHR integration, automation, or just want a second set of eyes on your plan?[ Contact us ](https://www.flobotics.io/)— we’ll help you make it clean, smooth, and scalable. You’ve got this. This can be one of the most innovative, most transformative projects you’ll roll out for your practice or organization — and we’re here to help make sure of it! #### Like the article? Spread the word Written byYana Pokora Content Manager at Flobotics. [More from Yana](https://www.flobotics.io/our-editorial-team#pokora) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RCMHealthcare ### Revenue Cycle Management (RCM) in Healthcare Revenue cycle management, explained: how US hospitals and practices stay compliant with payer policy and keep cash flow steady in 2026. Bart TeodorczukSeptember 30, 2024 ](https://www.flobotics.io/blog/revenue-cycle-management)[ RCMRPAAI ### AI vs. RPA vs. ML in Healthcare RCM: A Deep Dive AI vs. RPA vs. ML in healthcare RCM: how each technology improves efficiency, accuracy, and compliance, and which to adopt first. Krzysztof SzwedFebruary 22, 2025 ](https://www.flobotics.io/blog/ai-rpa-ml-rcm)[ HealthcareRCM ### No Surprises Act from an RCM Perspective | 2026 No Surprises Act, explained: key provisions, RCM impact, and the compliance steps that avoid costly billing disputes. Jędrzej SzymulaMarch 09, 2026 ](https://www.flobotics.io/blog/no-suprises-act-rcm) [All articles →](https://www.flobotics.io/blog) --- # UiPath Licensing Simplified: How BPO Makes Automation More Affordable Canonical: https://www.flobotics.io/blog/business-process-outsourcing Author: Karl Mielnicki Published: 2025-05-16 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/UiPath Licensing Simplified: How BPO Makes Automation More… CTO Notes [RPA](https://www.flobotics.io/blog?category=rpa) # UiPath Licensing Simplified: How BPO Makes Automation More Affordable [Karl MielnickiCTO & Co-Founder of Flobotics](https://www.flobotics.io/our-editorial-team#mielnicki) Published May 16, 2025Updated September 1, 2026 On this page - [What is Business Process Outsourcing (BPO)?](#what-is-business-process-outsourcing-bpo) - [Where BPO Meets Automation](#where-bpo-meets-automation) - [Why This Setup is So Damn Efficient?](#why-this-setup-is-so-damn-efficient) - [What If Automation Tools Raise Their Licensing Prices?](#what-if-automation-tools-raise-their-licensing-prices) - [How Healthcare Teams Use BPO + UiPath](#how-healthcare-teams-use-bpo-uipath) - [You Don’t Need a Shelf Full of Licenses](#you-dont-need-a-shelf-full-of-licenses) - [It’s Not Just About Cutting Costs](#its-not-just-about-cutting-costs) - [Wrapping It Up: Why BPO + Automation Just Makes Sense](#wrapping-it-up-why-bpo-automation-just-makes-sense) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Sick of paying full price for UiPath licenses you barely use? Wondering if there’s a smarter way to navigate [UiPath](https://licensing.uipath.com/) licensing without getting stuck in confusing tiers? Want to protect your company from surprise cost hikes down the line? You’re not alone—and yep, there is a better way. Let’s talk about how you can get all the benefits of [UiPath automation](https://www.flobotics.io/uipath-services) without the UiPath licensing headache, without overbuilding your in-house team, and without breaking the bank. Keep reading—this could save your ops a lot of time and money. ## What is Business Process Outsourcing (BPO)? Let’s face it—running a clinic, hospital, or even a tech-driven healthcare organization isn’t exactly a walk in the park. You’ve got a mountain of tasks that keep the operation moving: billing, scheduling, claims, paperwork, reports, and systems. It never stops. But here’s the thing: not every task needs to live in-house. You can keep your core team focused on what they do best, and let someone else handle the rest. That’s the idea behind Business Process Outsourcing (BPO). BPO isn’t just about slashing costs (although, yeah, that’s a big part of it). It’s about bringing in experts who already have the tools, systems, and people ready to roll. You get results faster, with fewer headaches, and without blowing up your payroll or tech stack. From patient billing to back-office admin, BPO helps organizations cut the clutter. You don’t have to build everything from scratch or reinvent the wheel. Someone else has already figured it out — and can deliver it more efficiently than you ever could internally. This kind of support is a game-changer, especially in healthcare, where every hour counts and budgets are constantly under pressure. Business Process Outsourcing is basically handing off specific tasks to someone else who can do them better, faster, or cheaper. We’re not talking about outsourcing your entire business here. It’s more like: “Hey, you handle the claims processing. We’ll stick to patient care.” Fig. 01 · BPO 9 tasks Healthcare tasks you can outsource with automation Outsource with automation - 01Payment posting - 02Claim denial management - 03RCM reporting - 04Claims processing - 05Charge capture - 06Patient registration - 07Prior authorization and verification - 08Medical coding - 09Appointment scheduling In healthcare, especially in [Revenue Cycle Management (RCM)](https://www.flobotics.io/blog/top-rcm-trends-healthcare), here are just some of the processes that can be outsourced: - Appointment Scheduling - [Patient Registration](https://www.flobotics.io/contact) - [Benefit and Eligibility Verification](https://www.flobotics.io/agents/eligibility-check-automation) - [Prior Authorization and Verification](https://www.flobotics.io/agents/prior-authorization-automation) - Charge Capture - Medical Coding - [Claims Processing](https://www.flobotics.io/agents/claims-management-automation) - [Claims Denial Management](https://www.flobotics.io/agents/denials-management-automation) - [Payment Posting](https://www.flobotics.io/rcm-automation) - [RCM Reporting](https://www.flobotics.io/rcm-automation) All of these can be handled by specialized teams outside your walls—teams who live and breathe these processes every day. Want a real-world [example of business process outsourcing](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks)? Take the Pain Treatment Centers of America (PTCoA), for instance. They partnered with us to automate their insurance claims processing using UiPath. By implementing over 10 RPA bots, PTCoA achieved a 449% return on investment (ROI) in just one year, saved the equivalent of six full-time employees’ salaries monthly, and reduced manual errors. This collaboration not only streamlined their operations but also led to significant cost savings. Fig. 02 · Case Pain Treatment Centers of America Pain Treatment Centers of America GoalStreamline insurance claims processing with BPOSolution10+ RPA bots across PTCOA processes, including retrieving and analyzing historical patient data 23 daysfrom launch to 100% ROI $400kprojected savings in year one 449%overall return on investment Flobotics [Read the case study →](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) That’s BPO in action. Simple, efficient, and surprisingly effective. ## Where BPO Meets Automation Okay, so you’ve got the gist of BPO. Now let’s talk about what happens when you bring automation into the picture. [Automation tools](https://www.flobotics.io/blog/uipath-python) can take repetitive, time-consuming tasks off your team’s plate entirely. However, setting up automation in-house can be a challenge: you need licenses, infrastructure, and developers who are knowledgeable about their work. This is where BPO becomes your secret weapon. A good BPO provider already has the necessary automation tools, technical expertise, and processes in place to roll out efficiently. You hand over the work, and they automate it for you. You get the benefits without the hassle. One of the most powerful automation platforms out there? That would be UiPath — and understanding how UiPath licensing works is key to using it smartly. Let’s dig into how that fits in next. When BPO providers use tools like [UiPath](https://www.uipath.com/) to automate the tasks you hand off to them, you’re getting the speed and precision of robots without paying for the licenses yourself. Typically, if your team wants to automate something, you’ve got to: - Buy UiPath licenses - Hire someone who knows how to build bots - Maintain the whole setup But through a BPO model? You skip all of that, and you avoid the complexities of UiPath licensing. You just pay for the outcome. The BPO owns the technology, manages the bots, and handles the behind-the-scenes wizardry. Fig. 03 · BPO + automation 5 gains Where BPO plus automation saves time and money - 01No license fees - 02No developers needed - 03Scales on demand - 04Fast deployment - 05Lower operational risk Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Why This Setup is So Damn Efficient? Here’s the magic of combining BPO with automation: - You don’t overpay for licenses you barely use. - You are only billed for what you actually use. - You scale up or down anytime. Let’s say you’re processing 1,000 claims per week. During the end-of-year crunch, that doubles. With BPO, you can double your automation capacity for just that period, then scale right back down after. You’re not locked into annual licensing fees. You’re not guessing how many bots you’ll need next month. You just flex as needed. We’re talking about on-demand UiPath robots without the licensing overhead. It’s automation-as-a-service, and it works. ## What If Automation Tools Raise Their Licensing Prices? It happens. Automation vendors adjust their pricing models, tweak their licensing structures, bundle in new features, or separate others. One day, you’re paying a flat rate; the next, there’s a tiered system that has you scratching your head. If you’ve built your automation setup in-house, these changes can hit hard. Every license, every adjustment—it’s all on you. But if you’re working with a BPO that delivers automation as part of their service, the risk shifts. They handle the licensing. They manage the changes. You just get the outcome you’re paying for. And when it comes to platforms like UiPath, this is a big deal. UiPath’s licensing model can be complex, with separate pricing for attended and unattended robots, orchestrators, and add-ons. If UiPath updates its pricing (and it does from time to time), a BPO provider often has an enterprise-level agreement that keeps things smooth and cost-effective for their clients. Long story short? When automation pricing shifts, a BPO setup helps shield you from the impact.. Vendors adjust pricing models, licensing terms change, and bundles shift around. But here’s the thing: - if you go directly and build your own automation setup in-house, you eat those price hikes. No way around it - If you’re working with a BPO, they handle the licensing. They’ve likely got enterprise-level deals with UiPath, which means better pricing and more flexibility than you’d get on your own. And if prices go up? They absorb the shock, adjust usage, or re-optimize processes to keep things affordable. That’s part of the deal. You can learn more about how UiPath licensing works here or dive deeper into our value-first approach to it in our[ UiPath licensing breakdown](https://www.flobotics.io/uipath-services#licenses) — but the big takeaway is this: you don’t have to worry about it if you’re not holding the license yourself. Fig. 04 · Licensing Full breakdown UiPath licensing vs the BPO model vs Traditional UiPath licensing - Initial license fees - Hiring developers and IT maintenance - Infrastructure costs - Risk of price increases - Hard to scale (fixed licenses) BPO + UiPath - No upfront license cost - No internal development team needed - Infrastructure handled for you - Protected from price increases - Scales on demand ## How Healthcare Teams Use BPO + UiPath Healthcare teams are buried in processes. Every claim, every report, every billing cycle is an opportunity to automate. But buying a bunch of software licenses and building a team to manage it? That’s a big lift. With a BPO partner running UiPath automation behind the scenes, healthcare orgs can: - Speed up billing - Automate claims processing - Handle patient intake faster - Clean up the revenue cycle And they can do it without adding full-time headcount or worrying about bot errors. Want to see what kind of return that gets? Check our[ ROI Calculator](https://www.flobotics.io/roi-calculator). ### You Don’t Need a Shelf Full of Licenses Most organizations overestimate their needs. They buy licenses “just in case,” and those sit unused while the CFO wonders where the money went. With BPO, you get: - No shelfware - No surprise IT maintenance costs - No internal license audits Just clean, efficient automation that adapts to your needs. And when things do scale up? Your BPO provider adjusts with you. ### It’s Not Just About Cutting Costs Sure, BPO helps you save money. But the benefits go way beyond just cost savings: #### Launch faster BPO providers already have the tools, workflows, and automation frameworks in place. You don’t need to wait months for setup and hiring. You can go from idea to execution in weeks, sometimes even faster. #### Get expert support You’re not just outsourcing tasks; you’re tapping into a team that knows healthcare, [RCM processes](https://www.flobotics.io/rcm-automation), automation platforms, and compliance. That level of domain-specific knowledge is hard (and expensive) to build in-house. #### Reduce operational risk With automation managed externally, you minimize the risk of downtime, security issues, or compliance errors. Your partner handles the heavy lifting and keeps everything running smoothly behind the scenes. #### Deliver a better experience for your team and your patients When your internal staff isn’t bogged down by repetitive work, they can focus on high-impact, human-centered tasks. That means happier teams and smoother experiences for your patients or clients. You’re not just outsourcing. You’re upgrading. Also, if you want to know how to measure whether your automation is actually working, check out our [RPA success metrics.](https://www.flobotics.io/blog/rpa-successs-metrics) ## Wrapping It Up: Why BPO + Automation Just Makes Sense Healthcare organizations have a multitude of responsibilities on their plate. The pressure to stay efficient, compliant, and financially lean has never been higher. That’s why Business Process Outsourcing, especially when paired with automation, is becoming a no-brainer. You hand over repetitive, complex processes to a partner who knows how to streamline them. They bring in automation tools, manage the tech, and deliver the results—while you stay focused on your core business. And when platforms like UiPath come into play, a BPO model helps you avoid costly licensing overhead and adapt easily to changes in pricing or demand. It’s flexible. It’s scalable. And it saves you from over-investing in tools or people you don’t need full-time. So if you’re looking for a way to scale smarter, spend more efficiently, and automate without the usual pain points, BPO might just be the way forward. Would you like to explore what that could look like for your team? [Let’s talk!](https://www.flobotics.io/contact) #### Like the article? Spread the word Written byKarl Mielnicki CTO & Co-Founder of Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ AI ### Agentic AI Workflows Agentic AI workflows, explained: how autonomous AI agents handle multi-step RCM tasks beyond traditional rule-based RPA. February 04, 2026 ](https://www.flobotics.io/blog/agentic-ai-workflows)[ RPA ### RPA Reloaded: 50+ Robotic Process Automation Statistics to Know in 2026 RPA statistics 2026: 50+ data points on robotic process automation adoption, ROI, and where the technology is headed next. Yana PokoraApril 15, 2025 ](https://www.flobotics.io/blog/rpa-statistics)[ RPAAI ### Agentic AI Frameworks | 2026 Agentic AI frameworks in 2026: which stacks Google and other leaders are betting on, explained with clear, research-backed answers. Jędrzej SzymulaDecember 02, 2025 ](https://www.flobotics.io/blog/agentic-ai-frameworks) [All articles →](https://www.flobotics.io/blog) --- # RPA Reloaded: 50+ Robotic Process Automation Statistics to Know in 2026 Canonical: https://www.flobotics.io/blog/rpa-statistics Author: Yana Pokora Published: 2025-04-15 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/RPA Reloaded: 50+ Robotic Process Automation Statistics to… [RPA](https://www.flobotics.io/blog?category=rpa) # RPA Reloaded: 50+ Robotic Process Automation Statistics to Know in 2026 [Yana PokoraContent Manager at Flobotics](https://www.flobotics.io/our-editorial-team#pokora) Published April 15, 2025Updated September 1, 2026 On this page - [What is RPA? Market Size & Growth Evolution](#what-is-rpa-market-size-growth-evolution) - [RPA Across the World: Market Growth by Region](#rpa-across-the-world-market-growth-by-region) - [RPA’s Effectiveness & Impact](#rpas-effectiveness-impact) - [RPA’s Global Structure: Types & Deployment](#rpas-global-structure-types-deployment) - [RPA Services](#rpa-services) - [RPA Products](#rpa-products) - [Top RPA Software Solutions in 2025](#top-rpa-software-solutions-in-2025) - [RPA Market by Industries](#rpa-market-by-industries) - [Finance & Banking](#finance-banking) - [Healthcare](#healthcare) - [Manufacturing](#manufacturing) - [Insurance](#insurance) - [Retail & Consumer Goods](#retail-consumer-goods) - [Logistics & Supply Chain](#logistics-supply-chain) - [RPA and Hyperautomation: The Future of Automation](#rpa-and-hyperautomation-the-future-of-automation) - [Final Thoughts](#final-thoughts) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Robotic Process Automation (RPA) has rapidly transitioned from an emerging technology to a critical enabler of digital transformation across industries. In 2025, RPA adoption is at an all-time high, fueled by Artificial Intelligence (AI), hyper-automation, and the increasing need for operational efficiency. This article provides a comprehensive analysis of the most impactful RPA statistics, market trends, industry insights, and software solutions, offering a data-driven perspective on the future of automation. ## What is RPA? Market Size & Growth Evolution The RPA market has grown exponentially, with businesses leveraging automation to improve efficiency and cut operational costs. As organizations continue to scale automation efforts, the global RPA industry will expand significantly in the coming years. 1. [Deloitte’s](https://www2.deloitte.com/us/en/insights/focus/technology-and-the-future-of-work/intelligent-automation-2022-survey-results.html) global Robotic Process Automation survey found that 53% of businesses have implemented RPA, with widespread adoption expected within the next two years. 2. McKinsey & Co. reports that 45% of business tasks can be automated. 3. The global RPA market was valued at $22.79 billion in 2024, with a projected CAGR of 43.9% from 2025 to 2030. 4. 78% of companies surveyed by Deloitte have implemented or planned to implement RPA. 5. 98% of IT leaders believe automation is essential for financial gains. [Robotic Process Automation: Top Statistics, Trends & Application](https://www.strategicmarketresearch.com/blogs/robotic-process-automation-statistics#:~:text=Top%20RPA%20Statistics,growing%20at%20a%2027%25%20CAGR) 6. 72% of organizations strongly support intelligent automation strategies, with IT departments being less supportive than other functions. 7. The expected ROI from RPA adoption can range from 30% to 200% in the first year, with a potential long-term ROI of up to 300%. Fig. 01 · RPA market $ billions RPA market size, 2023–2033 - $18.41 - $22.79 - $28.31 - $35.26 - $44.07 - $55.23 - $69.43 - $87.54 - $110.7 - $140.38 - $178.55 20232024202520262027202820292030203120322033 The continuous advancements in AI-driven automation and the increasing need for efficiency make RPA a key enterprise investment area. With adoption rates surging, businesses that fail to implement RPA risk being left behind in an increasingly competitive digital economy. ## RPA Across the World: Market Growth by Region RPA adoption varies by region, with North America leading in market size and Asia-Pacific demonstrating the fastest growth. The expansion of RPA is driven by digital transformation initiatives, increasing labor costs, and regulatory compliance requirements. Fig. 02 · RPA market Share, 2023 RPA market share by region, 2023 - North America39.34% - Europe27.86% - Asia Pacific24.2% - Latin America5.55% - Middle East and Africa3.05% North America remains the largest market. Asia-Pacific is the fastest-growing market, with a CAGR of 28.38% from 2024 to 2033. Europe’s RPA market was valued at $5.13 billion and is expected to grow at a CAGR of 26.07%. China’s RPA market was valued at $1.51 billion, growing at 27.07% CAGR. South Korea is a high-growth market with a CAGR of 33.67%. Germany’s RPA market was valued at $1.66 billion, projected to grow at a CAGR of 23.9%. [Precedence Research](https://www.precedenceresearch.com/robotic-process-automation-market) The RPA market is expanding rapidly worldwide, with Asia-Pacific emerging as a key player. Businesses looking to scale automation should consider regional trends and regulatory landscapes to optimize their RPA investments. ## RPA’s Effectiveness & Impact RPA has proven to be a game-changer in [Business Process Automation](https://www.flobotics.io/blog/bpm-vs-rpa-the-difference-and-what-it-means-for-your-business), improving efficiency, accuracy, and employee satisfaction. 1. 92% of businesses reported improved compliance with RPA. 2. 86% experienced increased productivity. 3. 59% saw cost reductions. 4. 89% of employees feel more satisfied with their jobs due to automation. [New Salesforce Research Links Lower Stress Levels and Business Automation](https://www.salesforce.com/news/stories/new-salesforce-research-links-lower-stress-levels-and-business-automation/) 5. 83% believe AI-powered automation reduces burnout. [UiPath 2023 Automation Generation Report](https://www.uipath.com/resources/automation-analyst-reports/automation-generation-report) Fig. 03 · Employees Survey People who use automation tools say they have more time to… 83%learn new skills 83%take on new, challenging tasks 77%build relationships with customers and stakeholders 6. 74% of automation tool users report completing tasks faster. 7. 91% of employees state that automation improves work-life balance. [New Salesforce Research Links Lower Stress Levels and Business Automation](https://www.salesforce.com/news/stories/new-salesforce-research-links-lower-stress-levels-and-business-automation/) 8. According to a survey, 30% of US workers are interested in learning about Robotic Process Automation. 68% believe RPA increases productivity, 68% believe RPA saves time, 52% believe RPA ensures a better work/life balance, and 43% believe RPA empowers workers to focus on more important work. [Precedence Research](https://www.precedenceresearch.com/robotic-process-automation-market) Fig. 04 · Automation Survey Why organizations resist investing in automation - It's not a priority33.3% - Other reasons26.7% - Not enough budget20% - Not convinced of the potential13.3% - Not enough resources6.7% The benefits of RPA extend beyond cost savings; automation enhances employee engagement and operational efficiency. Organizations must prioritize the right implementation strategies to maximize these advantages. ## RPA’s Global Structure: Types & Deployment RPA adoption isn’t uniform—businesses deploy automation in various ways, from cloud-based platforms to enterprise-wide solutions. Understanding the types and deployment methods of RPA solutions is crucial for organizations looking to optimize automation. Fig. 05 · RPA market Segments RPA market segmentation Type - Services - Consulting - Implementation - Training - Software Deployment - Cloud - On-premises Organization size - Large enterprises - SMEs Sorce: [Grand View Research ](https://www.grandviewresearch.com/horizon/outlook/robotic-process-automation-market-size/global) ### RPA Services RPA services encompass a range of offerings that help businesses implement, optimize, and scale automation solutions. These include: - Consulting Services – Assisting organizations in identifying automation opportunities and building RPA strategies. - Implementation Services – Deploying RPA tools and setting up workflows to streamline business processes. - Training Services – Educating employees and IT teams on how to use RPA solutions effectively. - Support & Maintenance – Ensuring continuous improvement and troubleshooting of automated processes. - Managed RPA Services – Outsourcing automation management to third-party providers for operational efficiency. ### RPA Products RPA solutions can be categorized into software tools that enable automation, available in different deployment models: #### 1. Deployment Models - Cloud-Based RPA: Offers scalability, remote accessibility, and lower infrastructure costs. These solutions represented over 53% of the market share in 2024, owing to lower infrastructure costs, ease of implementation, and scalability. - On-Premises RPA: Provides more control and security, which is preferred by enterprises handling sensitive data. #### 2. Software Solutions - Enterprise RPA Platforms (e.g., UiPath, Automation Anywhere, Blue Prism) - AI-Driven RPA Tools (e.g., WorkFusion, Pega Robotics) - Low-Code/No-Code RPA Solutions (e.g., Microsoft Power Automate) These services and products collectively drive the global RPA market by enabling businesses of all sizes, from SMEs to large enterprises, to leverage automation effectively. The services segment accounted for 64% of the RPA market revenue in 2024, including strategy, assessment, deployment, and support services. Fig. 06 · RPA market Share by type RPA market share by type By type - Services77.46% - Software22.54% With cloud-based solutions and AI-driven automation taking center stage, businesses must prioritize flexible, scalable deployment models to stay competitive. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Top RPA Software Solutions in 2025 The RPA software landscape is dominated by a few leading providers, each offering distinct capabilities. The demand for AI-powered automation, no-code/low-code development, and cloud-based solutions is shaping the future of RPA. - UiPath: Leading the market with an AI-enhanced automation platform, securing $1.2 billion in funding. - [Automation Anywhere](https://www.automationanywhere.com/): Provides cloud-native RPA solutions backed by $840 million in funding. - [Blue Prism:](https://www.flobotics.io/blog/blueprism-vs-uipath) Focuses on enterprise-grade RPA with strong security features, securing $182 million in funding. - [WorkFusion](https://www.workfusion.com/): Specializes in AI-driven intelligent automation, with $180 million in funding. [Crunchbase](https://www.crunchbase.com/) Fig. 07 · RPA vendors $ millions Funding raised by top RPA companies - UiPath$1.2B - Automation Anywhere$840M - Blue Prism$182M - WorkFusion$180M Source: [Market.us](https://scoop.market.us/robotic-process-automation-statistics/) With increasing competition and technological advancements, businesses must carefully evaluate RPA providers based on their automation needs, scalability, and integration capabilities. AI-driven automation and cloud-based solutions will be key differentiators in the coming years. ## RPA Market by Industries Industries leverage RPA to enhance workflows, reduce errors, and improve productivity. Some industries are leading in automation adoption, while others are gradually exploring its potential. Fig. 08 · RPA market CAGR by industry RPA market growth by industry (CAGR) Banking and insurance is the largest segment by revenue (about $6.8B in 2023); "other" and pharma and healthcare grow fastest. - Other59% - Pharma and healthcare58% - Manufacturing52.9% - Banking and insurance49.5% - Communication, media and education49% - Retail and consumer goods48.8% - IT and telecom48.2% - Logistics and energy46% Source: [Precedence Research](https://www.precedenceresearch.com/robotic-process-automation-market) ### [Finance & Banking](https://www.flobotics.io/business-process-automation) 1. 65% of finance firms plan to increase automation investment. (EY Report) 2. 92% of finance leaders associate RPA with business growth. ([Gartner](https://emt.gartnerweb.com/ngw/globalassets/en/finance/documents/trends/finance-top-strategic-technology-trends-whitepaper.pdf?_gl=1*o16uum*_ga*MTY0MTM3MzMzOC4xNzA1MTUyOTkz*_ga_R1W5CE5FEV*MTcwNTQxMDYwMC42LjEuMTcwNTQxMDY5Ny40OS4wLjA)) 3. 36% of tasks in banking and capital markets can be automated. ([Accenture](https://www.accenture.com/content/dam/accenture/final/accenture-com/document/Accenture-Total-Enterprise-Reinvention.pdf#zoom=40)) 4. 79% of finance companies report time savings, 69% see improved productivity, and 61% experience cost savings. (EY Report) 5. 90% of invoices that aren’t attached to a purchase order are processed manually, creating a perfect opportunity for automation. ([Accenture](https://www.accenture.com/content/dam/accenture/final/industry/high-tech/document/Accenture-The-automation-edge-for-High-Tech-Final.pdf)) ### Healthcare 1. The healthcare RPA market is expected to grow to $3.97 billion by 2029 at a CAGR of 14.8%. [The Business Search Company](https://www.thebusinessresearchcompany.com/report/robotic-process-automation-in-healthcare-global-market-report#:~:text=Robotic%20Process%20Automation%20In%20Healthcare%20Market%20Size%202025%20And%20Growth,(CAGR)%20of%2015.8%25.) Fig. 09 · RPA in healthcare $ billions RPA in healthcare: global market Expected to grow at a 14.8% CAGR to 2029. - $1.97B - $2.28B - $3.97B 202420252029 Source: [The Business Search Company](https://www.thebusinessresearchcompany.com/report/robotic-process-automation-in-healthcare-global-market-report#:~:text=Robotic%20Process%20Automation%20In%20Healthcare%20Market%20Size%202025%20And%20Growth,(CAGR)%20of%2015.8%25.) 2. RPA adoption could save the healthcare industry $17.6 billion annually. (Council for Affordable Quality Healthcare – CAQH) 3. Insurance verification and pre-authorization processing time can be reduced by 90%. (Journal of the American Medical Informatics Association) 4. 10% of healthcare organizations have adopted RPA, with significant growth expected. (Acceleration Economy) ### Manufacturing 1. 43% of manufacturers use RPA, and another 43% plan to implement it. [What Technology Do Manufacturers Use?](https://www.impactmybiz.com/blog/what-technology-do-manufacturers-use/) 2. Over 50% of industrial sector tasks can be automated. [Accenture](https://www.accenture.com/content/dam/accenture/final/accenture-com/document/Accenture-Total-Enterprise-Reinvention.pdf#zoom=40) 3. 92% of manufacturers report improved compliance due to RPA. [What Technology Do Manufacturers Use?](https://www.impactmybiz.com/blog/what-technology-do-manufacturers-use/) 4. Over half of procurement leaders have already deployed RPA or are scaling it. (Deloitte) 5. 85% of procurement leaders cite process standardization as the leading strategy for workload management. [Deloitte](https://www2.deloitte.com/content/dam/Deloitte/be/Documents/technology/us-global-chief-procurement-officer-survey-2023_deloitte-be_v2_report_en.pdf) ### Insurance 1. Automation can take over 37% of tasks in the insurance industry. [Accenture](https://www.accenture.com/content/dam/accenture/final/accenture-com/document/Accenture-Total-Enterprise-Reinvention.pdf#zoom=40) 2. RPA can process insurance claims up to 75% faster than humans. [AutomationEdge](https://automationedge.com/blogs/top-rpa-use-cases-in-insurance-industry/) 3. Automated claims processing reduces manual work by 80%. 4. RPA can complete form registration 40% faster with about half the staff. [Top Use Cases for Automation in the Insurance Industry](https://www.workfusion.com/blog/top-use-cases-for-automation-in-insurance/) ### Retail & Consumer Goods 1. Retail and Consumer Packaged Goods (CPG) report an 8% automation adoption rate. [Precedence Research](https://www.precedenceresearch.com/robotic-process-automation-market) 2. Companies in this sector leverage automation for inventory management, customer service, and supply chain optimization. ### Logistics & Supply Chain 1. Real-time fleet tracking and automation lead to significant cost savings. 2. U.S. logistics companies profit $12–$20 per $100 in e-commerce sales due to automation compared to $3–$5 in brick-and-mortar retail. [Precedence Research](https://www.precedenceresearch.com/robotic-process-automation-market) ## RPA and Hyperautomation: The Future of Automation The convergence of RPA, Artificial Intelligence, Machine Learning, and hyper-automation is reshaping the future of business automation. Organizations increasingly focus on full-scale automation strategies to enhance decision-making and operational efficiency. 1. The hyper-automation market is projected to reach $600 billion by 2025. 2. 59% of C-suite executives plan to increase investments in automation and AI. [Total Enterprise Reinvention](https://www.accenture.com/content/dam/accenture/final/accenture-com/document/Accenture-Total-Enterprise-Reinvention.pdf#zoom=40) 3. No-code/low-code automation is rising, enabling business users to automate tasks without technical expertise. Hyperautomation is the next phase of digital transformation, enabling end-to-end process automation. Organizations that leverage AI and RPA together will achieve greater agility and long-term growth. ## Final Thoughts RPA is no longer just an option but an absolute necessity for modern businesses. The numbers speak for themselves: companies worldwide are experiencing increased efficiency, reduced costs, improved compliance, and greater employee satisfaction through automation. RPA enables businesses to streamline operations, eliminate manual errors, enhance scalability, and drive digital transformation at an unprecedented pace. Beyond its immediate benefits, RPA is evolving. The market is shifting from solutions-oriented automation to product-oriented platforms, allowing businesses to leverage intelligent, scalable, and self-sufficient automation tools. With AI-driven automation, hyper-automation, and no-code solutions on the rise, RPA redefines how companies operate, innovate, and compete in the digital economy. At [Flobotics](https://www.flobotics.io/), we have been at the forefront of RPA’s evolution, helping businesses harness its power from its early growth stages. We firmly believe that automation shapes the future of global business and workforce efficiency. If you want to scale, optimize, and future-proof your business with automation, [contact us](https://www.flobotics.io/contact), and let’s build the future together. Written byYana Pokora Content Manager at Flobotics. [More from Yana](https://www.flobotics.io/our-editorial-team#pokora) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### What Is RPA? | Robotic Process Automation Robotic Process Automation (RPA), explained: how software bots run a 24/7 digital workforce that cuts costs and human error. Bart TeodorczukSeptember 01, 2025 ](https://www.flobotics.io/blog/robotic-process-automation)[ RPA ### Why Automation Training Is Key to Successful RPA Implementation RPA automation training: why employee training makes or breaks automation adoption, and how to prepare your team for working with bots. Karl MielnickiDecember 03, 2024 ](https://www.flobotics.io/blog/automation-training)[ RPA ### RPA Failures: 10 Most Common Reasons and How to Avoid Them RPA failures: Flobotics' CTO breaks down the 10 most common reasons automation projects fail and how to avoid them. Karl MielnickiJuly 06, 2021 ](https://www.flobotics.io/blog/rpa-failures) [All articles →](https://www.flobotics.io/blog) --- # Forbes named us "#3 Best Polish Startup of 2025"! Canonical: https://www.flobotics.io/blog/flobotics-forbes-polish-best-startups-2025 Author: Jędrzej Szymula Published: 2025-03-18 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Forbes named us "#3 Best Polish Startup of 2025"! [AI](https://www.flobotics.io/blog?category=ai)[RCM](https://www.flobotics.io/blog?category=rcm) # Forbes named us "#3 Best Polish Startup of 2025"! [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published March 18, 2025Updated September 1, 2026 Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## We're ranked #3 in Forbes Poland's "Best Polish Startups of 2025" in the SERVICE COMPANY category! 🥉 In a market often focused on pure software products, this proves you can build a high-growth, revenue-generating powerhouse by delivering elite services. 👉 Global Scale: We are proving that a Polish-born team can dominate the US market, serving top-tier enterprise customers with 100% precision. 👉 Real ROI: We don't just "consult"; we deliver. Our recent work featured by UiPath showed a 6:1 ROI for PRMG, saving them $2 Million and 40 hours of manual labor every single day. Read the [full PRMG loan-automation case study](https://www.flobotics.io/blog/flobotics-prmg-loan-processing-rpa-automation). ‍👉 Consistent Execution: Ranking #3 in a first-edition Forbes list isn't luck—it's the result of a team that simply gets stuff done. This milestone is a reflection of a bit of stubbornness, a lot of hard work, and a vision shared with my friend and co-founder, Filip. To our amazing team: you are the engine behind this #3 spot! 🚀 Huge congrats to the other winners RedStone, Nirby, and Rigby. Thank you Forbes Poland & Krzysztof Domaradzki for recognizing the impact of the service sector in this inaugural edition. This is the fuel we need to keep going faster! Click here to read more about [Best Polish Startups of 2025](https://www.forbes.pl/rankingi/najlepsze-start-upy-w-polsce-2025-ranking-forbes/rhwcj7x) Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPAAI ### We saved $2 Million from a 50% improvement for PRMG using UiPath! PRMG loan processing automation case study - see how UiPath RPA delivered a 6:1 ROI and $1.2M in labor savings over 36 months for this mortgage lender. Jędrzej SzymulaAugust 07, 2025 ](https://www.flobotics.io/blog/flobotics-prmg-loan-processing-rpa-automation)[ RPAAI ### We Are Among the Top Business Consulting Companies in the USA for 2026! Flobotics named a top business consulting company in the USA for 2026 by Selectedfirms - recognized for business growth and strategy expertise. Jędrzej SzymulaJanuary 26, 2026 ](https://www.flobotics.io/blog/flobotics-top-business-consulting-companies-2026)[ AIRPA ### We are a "Top Workday Implementation Partner for 2026" according to SuperbCompanies! Flobotics named a Top Workday Implementation Partner for 2026 by SuperbCompanies, ranked among 49 vetted firms for delivery and optimization results. Jędrzej SzymulaApril 05, 2026 ](https://www.flobotics.io/blog/flobotics-superbcompanies-top-workday-implementation-company-2026) [All articles →](https://www.flobotics.io/blog) --- # AI vs. RPA vs. ML in Healthcare RCM: A Deep Dive Canonical: https://www.flobotics.io/blog/ai-rpa-ml-rcm Author: Krzysztof Szwed Published: 2025-02-22 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/AI vs. RPA vs. ML in Healthcare RCM: A Deep Dive [AI](https://www.flobotics.io/blog?category=ai)[Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm)[RPA](https://www.flobotics.io/blog?category=rpa) # AI vs. RPA vs. ML in Healthcare RCM: A Deep Dive [Krzysztof SzwedHead of Delivery at Flobotics](https://www.flobotics.io/our-editorial-team#szwed) Published February 22, 2025Updated September 1, 2026 On this page - [Understanding AI, ML, and RPA in RCM](#understanding-ai-ml-and-rpa-in-rcm) - [Artificial Intelligence (AI)](#artificial-intelligence-ai) - [Robotic Process Automation (RPA)](#robotic-process-automation-rpa) - [Machine Learning (ML)](#machine-learning-ml) - [Combining AI, RPA, and ML: The Power of Hyperautomation](#combining-ai-rpa-and-ml-the-power-of-hyperautomation) - [How Healthcare Companies Can Benefit](#how-healthcare-companies-can-benefit) - [Summing Up](#summing-up) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) [Revenue Cycle Management (RCM)](https://www.flobotics.io/rcm-automation) is the backbone of financial stability for healthcare organizations. In an industry as complex and data-heavy as healthcare, automation, and intelligence are both luxuries and necessities. Artificial Intelligence (AI), Machine Learning (ML), and Robotic Process Automation (RPA) are three powerful technologies that are revolutionizing the way healthcare providers handle RCM processes. While they all play unique roles, understanding their differences and how they can complement one another is crucial for optimizing outcomes. This article explores AI vs. RPA vs. ML for RCM in healthcare, which is right for your healthcare organization’s RCM needs, and how combining them can lead to hyper-automation for maximum efficiency and accuracy. Let’s break it down. ## Understanding AI, ML, and RPA in RCM ### Artificial Intelligence (AI) AI refers to systems capable of mimicking human intelligence, performing tasks like decision-making, language understanding, and problem-solving. AI is the “brain” that makes systems smarter. For example, AI can mimic human intelligence for tasks like recognizing patterns and making decisions. [In RCM, AI](https://www.flobotics.io/blog/genai-in-healthcare) can: - automate decision-heavy tasks such as claim denials and fraud detection; - enable predictive analytics to forecast payment trends and patient behavior; - facilitate natural language processing (NLP) for data extraction from unstructured documents like medical records or insurance claims. #### Human involvement: Limited. AI typically operates autonomously but needs human oversight during implementation and to handle exceptions. #### Key features: - advanced problem-solving - self-learning capabilities - ability to process and analyze large datasets #### Case Study: [Montage Health](https://akasa.com/case-studies/montage-claim-status-case-study) implemented an AI-powered claims management solution to address inefficiencies in claim statuses. Their manual process involved hours of tracking claim statuses across multiple systems. By automating this with AI, the system used predictive analytics to identify potential denials and prioritize claims requiring attention. As a result, Montage Health reduced manual efforts by 75%, increased efficiency, and achieved faster claim resolution. ### Robotic Process Automation (RPA) RPA focuses on automating repetitive, rule-based tasks. It’s like the “muscle” of automation, performing precise actions like data entry, claims submission, or eligibility verification. While it doesn’t “think” like AI or “learn” like ML, RPA is efficient and reliable for straightforward processes. RPA uses bots to mimic repetitive, rule-based human tasks in software systems. In RCM, RPA can: - Automate [claims processing](https://www.flobotics.io/agents/claims-management-automation) by extracting, validating, and submitting claims. - Perform payment posting and reconciliation without manual intervention. Handle appointment scheduling and insurance [eligibility checks](https://www.flobotics.io/agents/eligibility-check-automation). Sorry, your browser doesn't support embedded videos. Check out this video to learn how we automated patient profile creation and appointment scheduling processes in TheraNest EHR. #### Human involvement: Minimal. Once configured, bots handle repetitive tasks but require monitoring to address errors or workflow changes. #### Key features: - high-speed task execution - accuracy in rule-based processes - easy to deploy and scale #### Case Study: [PathGroup implemented RPA](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation) to overhaul its claims submission process. The company relied on manual data entry, leading to bottlenecks and errors. By deploying RPA bots, PathGroup automated the entire claims process, achieving a 95% reduction in processing time and significantly improving accuracy. This saved the company thousands of work hours annually, increasing overall revenue cycle efficiency. ### Machine Learning (ML) ML is a subset of AI that focuses on creating systems capable of learning from data and improving over time. Instead of programming rules, ML uses algorithms to analyze data and optimize its output. In healthcare RCM, it’s like teaching a system to adapt by showing it what works and enhancing its decision-making capabilities. In RCM, ML can: - predict claim denials by analyzing historical claim data; - optimize pricing and reimbursement strategies through pattern recognition; - identify anomalies in financial data for fraud detection. #### Human involvement: Moderate. Human input is required to train ML models, validate predictions, and handle outliers. #### Key features: - continuous learning from data - high accuracy in predictive tasks - adaptability to new data trends #### Case Study: A healthcare provider integrated an ML-based model developed by 7T to optimize patient eligibility verification and insurance coverage checks. The model analyzed historical claim outcomes and adjusted its predictions dynamically, reducing rejected claims by 30%. Furthermore, it enhanced coding accuracy, enabling better compliance with payer requirements, which improved cash flow by 20%. Fig. 01 · AI, RPA and ML Comparison AI, RPA and ML in RCM compared | AI | RPA | ML | Core function | Decision-making and insight | Rule-based task automation | Learning from data patterns | Human involvement | Oversight and exceptions | Monitoring and error handling | Model training and validation | Learning | Adapts to new situations through various algorithms | No built-in learning | Keeps improving as it sees more data | Data handling | Structured and unstructured data | Works best with structured data | Needs structured data for training | Scalability | High | Moderate | Very high | Key benefit | Smart automation and insights | Task speed and precision | Data-driven decisions | Time to implement | Long (advanced setup) | Short (depends on the process) | Medium | Examples in RCM | Denial management, forecasting | Claims processing, patient registration | Coding accuracy, coverage checks | Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Combining AI, RPA, and ML: The Power of Hyperautomation While each technology offers unique benefits, the real game-changer lies in combining them through hyper-automation. Hyperautomation uses RPA for basic task automation, ML for predictive insights, and AI for complex decision-making, creating a seamless, end-to-end automated workflow. Imagine a scenario where: - RPA handles patient registration and insurance eligibility checks, pulling data from multiple sources. - ML predicts which claims will likely be denied and routes them for additional review. - AI analyzes patient records to identify errors in coding or discrepancies in billing. Together, these technologies reduce claim denials, speed up reimbursements, and improve cash flow. #### Hyperautomation Case Study: The Power of AI, ML, and RPA Together ##### Client: A UK-based RCM provider managing financial workflows for 55+ healthcare organizations. ##### Challenge: Manually logging into various healthcare portals to verify patient eligibility and benefits for upcoming appointments was time-intensive and error-prone. These inefficiencies jeopardized revenue collection and caused delays. ##### Solution: The RCM provider implemented Bautomate’s hyper-automation solution, combining RPA bots with AI-powered Optical Character Recognition (OCR) and Machine Learning. Here’s how the technologies were utilized: - RPA: Automated logging into portals and extracting patient information. - AI: Used OCR to process unstructured data from forms accurately. - ML: Learned patterns from previous claims to improve verification accuracy over time. A total of 10 bots were deployed, each tailored to specific portals, ensuring customized automation for maximum efficiency. Fig. 02 · Case study AI + ML + RPA What AI, ML and RPA achieved together 500+hours saved a month, so staff could move to higher-value work 98%fewer errors, with accurate information and compliance +15%revenue from faster verification and claim submission 70%faster turnaround, so providers schedule appointments sooner This case showcases the transformative power of hyper-automation in addressing complex RCM challenges. ## How Healthcare Companies Can Benefit - Improved Efficiency: Organizations can focus their human resources on high-value activities like patient care by automating repetitive and decision-heavy tasks. - Enhanced Accuracy: Automated systems reduce errors in billing and coding, ensuring compliance and minimizing claim rejections. - Cost Savings: Faster processes and reduced manual labor translate to significant operational cost reductions. - Scalability: With hyper-automation, organizations can scale operations effortlessly, even during peak periods. ## Summing Up When evaluating AI vs. [RPA vs. ML](https://www.flobotics.io/blog/robotic-process-automation-vs-machine-learning) for RCM, each technology offers distinct benefits tailored to specific challenges within healthcare. RPA excels in automating repetitive, rule-based tasks, ensuring speed and efficiency. ML thrives in analyzing patterns and improving accuracy over time, making it ideal for tasks like coding and claims prediction. AI, as the most advanced, enables predictive insights and decision-making that transform strategic processes like fraud detection and denial management. Healthcare organizations don’t need to adopt all three technologies simultaneously to see results. Even implementing one technology can drastically improve efficiency, accuracy, and compliance within RCM processes. Whether used separately or in combination, these technologies can reduce costs, enhance decision-making, and streamline operations. The right choice depends on your organization’s unique needs and goals. Regardless of your path, automation—in any form—is the key to optimizing healthcare RCM in today’s data-driven world. At Flobotics, we specialize in implementing any type of automation solutions tailored for healthcare. From automating claims processing to deploying AI-driven analytics, our expertise ensures your RCM processes [are streamlined and future-ready.](https://www.flobotics.io/roi-calculator) Let’s work together to unleash the full potential of automation in your organization! #### Like the article? Spread the word Written byKrzysztof Szwed Head of Delivery at Flobotics. [More from Krzysztof](https://www.flobotics.io/our-editorial-team#szwed) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Top Automation Trends in 2026 Canonical: https://www.flobotics.io/blog/top-automation-trends Author: Krzysztof Szwed Published: 2025-02-03 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Top Automation Trends in 2026 [RPA](https://www.flobotics.io/blog?category=rpa) # Top Automation Trends in 2026 [Krzysztof SzwedHead of Delivery at Flobotics](https://www.flobotics.io/our-editorial-team#szwed) Published February 03, 2025Updated September 1, 2026 On this page - [What’s Driving Automation in 2025? Automation Trends by Goals](#whats-driving-automation-in-2025-automation-trends-by-goals) - [#1 Hyper-automation: Fixing the Automation Patchwork](#1-hyper-automation-fixing-the-automation-patchwork) - [#2 Smarter Workforces: The Human-Robot Partnership](#2-smarter-workforces-the-human-robot-partnership) - [#3 Automated Cybersecurity : Protecting Data in the Digital Age](#3-automated-cybersecurity-protecting-data-in-the-digital-age) - [#4 Green Automation: Doing More While Saving the Planet](#4-green-automation-doing-more-while-saving-the-planet) - [#5 Autonomous Systems: The Rise of Self-Sufficient Technology](#5-autonomous-systems-the-rise-of-self-sufficient-technology) - [The Technologies Shaping Automation](#the-technologies-shaping-automation) - [#6 The AI Boom: Smarter Automation at Scale](#6-the-ai-boom-smarter-automation-at-scale) - [#7 RPA as a Product: The New Era of Scalable Automation](#7-rpa-as-a-product-the-new-era-of-scalable-automation) - [#8 Cloud Solutions: The Future of Automation Infrastructure](#8-cloud-solutions-the-future-of-automation-infrastructure) - [Why These Trends Matter](#why-these-trends-matter) - [Practical Applications for Enterprises](#practical-applications-for-enterprises) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Remember those sci-fi movies where robots performed all the tedious chores, cars flew, and everyone lived in a high-tech utopia? Just a few years ago, this seemed like a fantasy, but guess what? It’s 2025, and that future is our present. Automation is no longer a distant dream but a reality driving businesses, economies, and daily life forward. 2025 is a critical year to understand what’s next in automation. Why? Because keeping up with these trends isn’t just about staying relevant—it’s about prospering in a quickly changing world. Let’s dive into the hottest automation trends reshaping industries and explore how they make life smarter, greener, and more efficient. We’ve highlighted two lenses to view automation trends: one focuses on the goals driving automation—the big-picture reasons organizations invest in these tools. The other looks at the technologies powering these advancements—the nuts and bolts of how they work. This way, you can see the “why” behind automation and the “how” it’s shaping up to meet modern needs. Of course, this is just one way to break things down, but it’s a way to get a clear view of the landscape. Fig. 01 · Trends 8 trends 8 automation trends - HyperautomationFixing the automation patchwork - [Smarter workforces](#2-smarter-workforces-the-human-robot-partnership)The human-robot partnership - [Automated cybersecurity](#3-automated-cybersecurity-protecting-data-in-the-digital-age)Protecting data - [Green automation](#4-green-automation-doing-more-while-saving-the-planet)Doing more while saving the planet - [Autonomous systems](#5-autonomous-systems-the-rise-of-self-sufficient-technology)Self-sufficient technology - [The AI boom](#6-the-ai-boom-smarter-automation-at-scale)Smarter automation at scale - [Cloud solutions](#8-cloud-solutions-the-future-of-automation-infrastructure)The future of automation infrastructure - [RPA as a product](#7-rpa-as-a-product-the-new-era-of-scalable-automation)Scalable automation ## What’s Driving Automation in 2025? Automation Trends by Goals ### #1 Hyper-automation: Fixing the Automation Patchwork In the rush to automate as much as possible, many companies have ended up with a fragmented landscape of tools, platforms, and technologies. Different processes are automated in different ways, creating silos that hinder interoperability and flexibility. This disjointed approach can make scaling automation a nightmare, as teams struggle to manage and integrate multiple systems. Hyperautomation in 2025 is here to tackle this challenge head-on. It’s not just about automating more—it’s about automating smarter. Hyperautomation seeks to unify these disparate systems, creating a seamless ecosystem where all automated processes work together harmoniously. By leveraging advanced technologies like AI, RPA, machine learning, and data analytics, hyper-automation platforms gather and connect previously isolated automations. The result? Businesses can streamline operations, reduce redundancies, and achieve greater flexibility. Hyperautomation doesn’t simplify complexity—it transforms it into a competitive advantage, enabling organizations to adapt and innovate faster. Fig. 02 · Hyperautomation Ecosystem The hyperautomation ecosystem Hyperautomation - 01Robotic process automation - 02Intelligent business process management - 03Advanced analytics - 04Artificial intelligence ### #2 Smarter Workforces: The Human-Robot Partnership Forget the outdated narrative that robots steal jobs. In 2025, automation is revolutionizing workforces in ways beyond simple replacement and toward significant assistance. This shift is creating space for creativity, problem-solving, and innovation while also paving the way for entirely new roles that didn’t exist before. Consider positions like automation strategists, data analysts for AI-driven processes, or designers for human-machine collaboration tools. As operations become increasingly streamlined, humans are stepping into roles that demand ingenuity, adaptability, and leadership. The transformation isn’t just about what work gets done but how it’s approached. Employees are becoming collaborators with technology, utilizing it as a tool to amplify their productivity rather than as a competitor. This workforce evolution unlocks human potential on an unprecedented scale, marking a significant shift in how organizations view and structure their teams. ### #3 [Automated Cybersecurity](https://www.flobotics.io/blog/8-security-practices-for-rpa-implementation): Protecting Data in the Digital Age With so much data living online, cyberattacks are a constant threat. Cybersecurity automation is the answer to safeguarding sensitive information and systems. From detecting anomalies to responding to threats in real-time, these tools are a must-have for companies looking to stay ahead of hackers. Think of it as your 24/7 digital bodyguard. ### #4 Green Automation: Doing More While Saving the Planet Remember when automation was all about speed and cost savings? Today, it’s about sustainability, too. Businesses are embracing automation solutions that reduce their environmental impact—from optimizing factory energy use to implementing smarter logistics to cut emissions. Think of it as a double win: saving money while saving the planet. ### #5 Autonomous Systems: The Rise of Self-Sufficient Technology While there is a clear trend of automation acting as an assistant to humans and creating new jobs to support it, autonomous systems mark a significant shift. These technologies enable bots and machines to work entirely on their own without requiring human oversight. As a result, businesses can rely on automation that operates independently, pushing the boundaries of efficiency and innovation. This trend is driven by advancements in AI, sensors, and edge computing, which allow machines to process information and respond to their environments autonomously. For logistics, agriculture, and healthcare industries, autonomous systems are not just a convenience but a game-changer, offering greater efficiency, safety, and scalability. For instance, autonomous delivery drones speed up last-mile logistics, while innovative farming systems optimize crop yields by analyzing real-time soil data and weather conditions. In manufacturing, autonomous robots ensure precision and consistency on production lines, even in highly complex environments. As these systems evolve, they promise to redefine how tasks are performed across industries. This will pave the way for a future where machines and humans collaborate seamlessly to achieve new levels of productivity and innovation. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## The Technologies Shaping Automation ### #6 The AI Boom: Smarter Automation at Scale Artificial Intelligence (AI) is having its moment, and it’s a big one. The rapid evolution of technology has become a central pillar in automation strategies across industries. Among the most exciting advancements are: Fig. 03 · AI Breakdown AI advances, broken down - NLP - Better chatbots and virtual assistants - Simpler internal communication - Supports healthcare diagnostics - Generative AI - Images, reports and marketing content - Supports creative work - Automates routine content - Large language models - Analyze large datasets - Produce complex outputs quickly - Help with knowledge management #### Natural Language Processing (NLP) NLP has matured significantly, enabling machines to understand and respond to human language with greater nuance. Applications like intelligent chatbots and virtual assistants enhance customer service, simplify internal communications, and even assist in areas like healthcare diagnostics. NLP-driven tools understand commands and can have conversations, making human-machine interactions smoother and more natural. #### [Generative AI](https://www.flobotics.io/blog/genai-in-healthcare) This groundbreaking technology transforms industries by creating content, designs, and solutions from scratch. From generating realistic images to crafting detailed reports or marketing content, Generative AI is being adopted widely. It empowers creatives and marketers by handling routine tasks and augmenting their work with innovative ideas. #### Large Language Models (LLMs) Tools like ChatGPT and similar models have become essential for analyzing vast datasets, generating complex outputs, and simplifying decision-making processes. These LLMs are being integrated into automation workflows to manage knowledge bases, summarize information, and provide real-time insights, saving hours of manual work. The global AI market is projected to [hit $638.23 billion in 2025,](https://www.precedenceresearch.com/artificial-intelligence-market) a 19.1% jump from 2023. These technologies are set to reshape how businesses operate. AI isn’t just about automation; it’s about enabling smarter, more efficient processes that align with modern demands. Fig. 04 · AI What it adds What AI lets automation do AI lets automation… - 01Suggest insights in real time - 02Process unstructured data with OCR - 03Learn and improve itself - 04Handle complex tasks - 05Find inefficiencies - 06Talk with customers - 07Run predictive analytics ### #7 RPA as a Product: The New Era of Scalable Automation The RPA market [is expected to reach USD 63.24 billion](https://www.marketresearchfuture.com/reports/robotics-as-a-service-market-23970#:~:text=The%20Global%20Robotics%20as%20a%20Service%20(RaaS)%20Market%20is%20projected,25.5%25%20during%20the%20forecast%20period.) by 2032, reflecting a CAGR of 25.5% during the forecast period, signaling a major shift in how businesses adopt automation. Rather than relying on custom-built solutions, companies are increasingly turning to [RPA](https://www.flobotics.io/blog/automation-training) as a product, selecting from predefined automation packages, subscription-based models, and modular bot solutions that align with their operational needs. This transformation simplifies automation adoption, allowing businesses to purchase and deploy RPA solutions like a SaaS product—with flexible pricing, regular updates, and built-in scalability. Organizations can now subscribe to automation packages tailored for finance, HR, customer service, and other key business functions, reducing the need for extensive development while ensuring rapid implementation. Additionally, pre-configured RPA solutions lower barriers to entry, enabling mid-sized and even smaller companies to benefit from automation without the hefty upfront investment. The rise of low-code and no-code capabilities further democratizes RPA, allowing non-technical users to configure and expand automation workflows without deep technical expertise. As enterprises demand faster, more cost-effective automation, the shift to RPA as a product will drive greater adoption, efficiency, and flexibility. With businesses increasingly opting for subscription-based automation models, RPA is becoming a more predictable and scalable path to digital transformation across industries. ### #8 [Cloud Solutions:](https://www.flobotics.io/blog/uipath-vs-gcp) The Future of Automation Infrastructure Gone are the days of clunky on-premise systems. Cloud-based automation solutions offer businesses the flexibility and scalability to stay agile. Whether managing workflows, scaling operations, or enabling remote work, the cloud is where it’s at. And with lower upfront costs, it’s an easy win for companies of all sizes. ## Why These Trends Matter Automation trends in 2025 aren’t just buzzwords; they’re a blueprint for success. From hyper-automation to AI-driven solutions, these advancements are not just theoretical—they are practical, scalable, and ready to address real-world challenges. Industries across the spectrum, including healthcare, finance, insurance, and manufacturing, stand to benefit significantly by integrating these technologies into their operations. ### Practical Applications for Enterprises #### Healthcare Automation in clinical workflows, [Revenue Cycle Management (RCM)](https://www.flobotics.io/rcm-automation), and patient engagement can lead to [cost reductions of 15-30%](https://www.commonwealthfund.org/), improved compliance, and enhanced patient experiences. For example, streamlining [claims processing ](https://www.flobotics.io/agents/claims-management-automation)and patient scheduling systems can reduce administrative burdens and free up resources for direct care​​. #### Finance and Accounting Automating accounts payable, cash management, and regulatory reporting improves liquidity, reduces error rates, and accelerates the cash conversion cycle​​. #### Insurance Leveraging automation for claims processing, underwriting, and customer service can reduce operational costs by up to 40% and improve customer retention by delivering seamless, error-free experiences​. #### Manufacturing Automating production lines, supply chain management, and quality control reduces costs, addresses labor shortages, and increases operational agility​. At [Flobotics](https://www.flobotics.io/), we specialize in making these trends actionable. With our expertise in RPA and [Intelligent Automation](https://www.flobotics.io/rcm-automation), we provide end-to-end services, including process discovery, automation strategy, and deployment. Here’s what sets us apart: - Rapid Implementation: Average onboarding and implementation times under a month mean your enterprise starts seeing ROI faster​. - Scalability: We leverage reusable libraries and proven frameworks to scale automation across departments seamlessly​. - Custom Solutions: Whether integrating with legacy systems or adopting the latest AI-powered platforms, we tailor our solutions to your needs, ensuring long-term compatibility and flexibility​. We partner with organizations to implement these automation trends and unlock their full potential. By reducing costs, enhancing efficiency, and driving innovation, we empower companies to stay competitive in the rapidly evolving digital landscape. Ready to take the leap? [Let’s make automation work for you!](https://www.flobotics.io/contact) #### Like the article? Spread the word Written byKrzysztof Szwed Head of Delivery at Flobotics. [More from Krzysztof](https://www.flobotics.io/our-editorial-team#szwed) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RCMHealthcare ### RCM Automation in Healthcare | 2026 RCM automation in healthcare: how RPA, AI, and OCR cut billing errors, speed up claims, and reduce manual work in 2026 revenue cycle management. Bart TeodorczukFebruary 25, 2026 ](https://www.flobotics.io/blog/rcm-automation-healthcare)[ RCMAIHealthcare ### Agentic AI in Healthcare: From Hype to Real-World Impact Agentic AI in healthcare: how it differs from generative AI like ChatGPT and where it's already driving real clinical impact. Jędrzej SzymulaSeptember 22, 2025 ](https://www.flobotics.io/blog/agentic-ai-in-healthcare)[ Healthcare ### Healthcare Compliance Automation: Laws, Benefits and Examples Compliance automation software for healthcare: how RPA helps organizations meet evolving regulations without adding manual review work. Filip NasiadkoOctober 09, 2023 ](https://www.flobotics.io/blog/compliance-automation) [All articles →](https://www.flobotics.io/blog) --- # Top 30 Software Solutions for Healthcare in 2026 Canonical: https://www.flobotics.io/blog/healthcare-software Author: Yana Pokora Published: 2024-12-23 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Top 30 Software Solutions for Healthcare in 2026 [Healthcare](https://www.flobotics.io/blog?category=healthcare) # Top 30 Software Solutions for Healthcare in 2026 [Yana PokoraContent Manager at Flobotics](https://www.flobotics.io/our-editorial-team#pokora) Published December 23, 2024Updated September 1, 2026 On this page - [Core Patient Management Solutions](#core-patient-management-solutions) - [1. Electronic Health Records (EHR)](#1-electronic-health-records-ehr) - [2. Health Management Systems (HMS)](#2-health-management-systems-hms) - [3. Practice Management Software (PMS)](#3-practice-management-software-pms) - [4. Clinical Decision Support Systems (CDSS)](#4-clinical-decision-support-systems-cdss) - [5. Medical Imaging Software](#5-medical-imaging-software) - [6. Telemedicine Platforms](#6-telemedicine-platforms) - [7. Revenue Cycle Management (RCM)](#7-revenue-cycle-management-rcm) - [8. Patient Engagement Platforms](#8-patient-engagement-platforms) - [9. Pharmacy Management Software](#9-pharmacy-management-software) - [10. Laboratory Information Management Systems (LIMS)](#10-laboratory-information-management-systems-lims) - [Advanced Clinical Solutions](#advanced-clinical-solutions) - [11. Patient Monitoring Software](#11-patient-monitoring-software) - [12. Disease Management Platforms](#12-disease-management-platforms) - [13. Clinical Analytics Software](#13-clinical-analytics-software) - [14. AI-Powered Diagnostic Tools](#14-ai-powered-diagnostic-tools) - [15. Population Health Management Software](#15-population-health-management-software) - [Operational Efficiency Solutions](#operational-efficiency-solutions) - [16. Surgical Planning Software](#16-surgical-planning-software) - [17. Healthcare CRM](#17-healthcare-crm) - [18. Healthcare Compliance Software](#18-healthcare-compliance-software) - [19. Medical Billing Software](#19-medical-billing-software) - [20. Care Coordination Platforms](#20-care-coordination-platforms) - [Specialized Solutions](#specialized-solutions) - [21. Health Information Exchange (HIE)](#21-health-information-exchange-hie) - [22. Healthcare Chatbots](#22-healthcare-chatbots) - [23. Patient Portal Software](#23-patient-portal-software) - [24. Workflow Automation Software](#24-workflow-automation-software) - [25. Inventory Management Software](#25-inventory-management-software) - [26. Staff Scheduling Software](#26-staff-scheduling-software) - [27. Prescription Management Software](#27-prescription-management-software) - [28. Quality Management Software](#28-quality-management-software) - [29. Medical Device Integration Platforms](#29-medical-device-integration-platforms) - [30. Healthcare Data Analytics Platforms](#30-healthcare-data-analytics-platforms) - [Conclusion](#conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) As healthcare demands continue to grow, so does the need for effective and reliable software. The industry is increasingly focused on improving patient outcomes, streamlining administrative functions, and meeting strict regulatory requirements. Innovative software solutions are becoming more critical, enabling healthcare providers to address these challenges efficiently. In this blog, we'll explore 30 essential software solutions widely used in healthcare in 2026. Organized by function, each category highlights tools that enhance clinical care, streamline administrative tasks, and support operational efficiency, ultimately helping healthcare providers serve patients more effectively. Looking for specific vendors instead, such as Epic, athenahealth or NextGen? See our [list of top healthcare software platforms](https://www.flobotics.io/blog/top-20-healthcare-software-examples). ## Core Patient Management Solutions Core Patient Management Solutions Interface Example – Epic allows you to manage your patients comprehensively and provides a broad selection of features and options. ### 1. Electronic Health Records (EHR) #### How EHR Works: EHR systems digitize all patient data, creating a centralized record accessible to healthcare providers across departments. When a patient checks in, the EHR system logs their visit, records symptoms, updates medications and maintains treatment plans in a single, easily accessible file. Providers can utilize built-in templates for medical conditions to standardize data entry and simplify information retrieval. EHR systems often integrate with lab and radiology software, incorporating test results directly into the patient's file. This integration allows clinicians to access comprehensive health data without needing to switch between systems. #### Processes Involved: Patient data management, medication history, physician notes, lab results, care planning, and administrative tasks like billing and [coding](https://www.flobotics.io/blog/medical-coding). #### Use Case: Katzen Eye Group, a leading ophthalmology practice, faced challenges in managing patient volumes, maintaining accurate documentation, and streamlining billing processes. They [implemented NextGen Healthcare's integrated EHR](https://cdn.featuredcustomers.com/CustomerCaseStudy.document/nextgen-healthcare_katzen-eye-group_23474.pdf) and Practice Management (PM) solutions to address these issues. The system digitized patient records, automated appointment scheduling, and improved the efficiency of billing workflows. This led to significant time savings for staff, enhanced patient care through faster access to records, and reduced claim denials, which improved revenue collection. With these improvements, Katzen Eye Group optimized its operations and delivered higher-quality care to its growing patient base. #### Analytics Provided: EHR systems provide analytics on patient demographics, treatment outcomes, and resource use. Dr. Smith's clinic uses these analytics to track patient improvement rates, identify common conditions, and optimize appointment schedules. ##### Examples of EHR Software: [Epic Systems](https://www.epic.com/), [Cerner, Praxis](https://www.ehrinpractice.com/cerner-ambulatory-ehr-software-profile-113.html), [Evident](https://api.evident.com/), [Meditech](https://ehr.meditech.com/meditech), [NextGen EHR](https://www.nextgen.com/), [DrChrono](https://www.drchrono.com/), [PrognoCIS](https://prognocis.com/) ### 2. Health Management Systems (HMS) #### How HMSWorks: HMS provides a unified interface to manage various hospital functions. When patients are admitted, the system registers them, assigns a bed, and coordinates with nursing staff. It updates patient status across departments (e.g., transferring from ICU to a general ward), manages billing by integrating with insurers for pre-approvals and claims, and monitors bed occupancy rates to prevent overbooking. #### Processes Involved: HMS is involved in hospital operations, including patient admissions, bed management, staff allocation, billing, and inventory tracking. #### Use Case: A hospital faced challenges with manual processes in patients' admissions, billing, and resource management, leading to inefficiencies and communication gaps between departments. To address these issues, they [implemented Zenkins' Hospital Management Software (HMS)](https://zenkins.com/case-studies/hospital-management-software-a-case-study/), which integrated Electronic Health Records, appointment scheduling, inventory management, and interdepartmental communication tools. This integration resulted in streamlined operations, improved patient care, and enhanced administrative efficiency. #### Analytics Provided: HMS offers analytics on bed occupancy, patient wait times, staff allocation, and billing accuracy. Companies use these insights to adjust staffing during peak hours and optimize bed assignments. ##### Examples of HMS Software: [Oracle Cerner Millenium](https://docs.oracle.com/en/industries/health/millennium-platform-apis/), [MEDITECH Expanse](https://ehr.meditech.com/ehr-solutions/meditech-expanse), [SAP Health Management](https://www.sap.com/industries/life-sciences-healthcare.html), [Kareo Clinical](https://www.kareo.com/) ### 3. Practice Management Software (PMS) #### How PMS Works: PMS serves as the administrative backbone for small to medium-sized practices, managing the patient journey from appointment booking to checkout. When a patient books an appointment, their information is entered into the system, and automated reminders are sent. At checkout, the system generates a bill, processes payments, and files insurance claims. It also tracks follow-up visits, ensuring a seamless and continuous patient-provider relationship. #### Processes Involved: PMS covers administrative processes in smaller practices, such as appointment scheduling, patient billing, medical records, and claims management. #### Use Case: A leading UK-based healthcare center serving more than 100,000 patients annually sought [to develop a multi-clinic Practice Management System (PMS)](https://www.daffodilsw.com/case-study/practice-management-system-for-uk-based-chain-of-clinics/) to streamline and automate medical practices for clinical staff, general practitioners, and consultants. Daffodil's teamaudited the existing codebase, identifying reusable components, and developed a comprehensive PMS with modules for appointment booking, client record management, stock management, and referral management. The new system integrated with third-party software and hardware, including pathology analyzers and billing systems, and complied with HL7 standards. This implementation resulted in a 47% increase in operational efficiency, integration of over 30 clinics, and a saving of 20 man-months of effort. #### Analytics Provided: PMS provides analytics on no-show rates, revenue trends, and patient demographics, helping companies predict patient needs and optimize billing cycles. ##### Examples of PMS Software: [Athenahealth Practice Management](https://www.athenahealth.com/knowledge-hub/practice-management), [AdvancedMD](https://www.advancedmd.com/), [eClinicalWorks](https://www.eclinicalworks.com/), [Practice Fusion](https://www.practicefusion.com/), [DrChrono](https://www.drchrono.com/), [SimplePractice](https://www.simplepractice.com/) ### 4. Clinical Decision Support Systems (CDSS) #### How CDSS Works: CDSS uses clinical data and evidence-based guidelines to assist healthcare providers in decision-making. When a provider enters symptoms or diagnostic test results, the system offers potential diagnoses, treatment options, and dosing recommendations based on patient data and the latest medical literature. Some CDSS solutions, such as IBM Watson Health, employ AI to continuously learn from new cases, delivering increasingly accurate recommendations over time. #### Processes Involved: CDSS supports clinical processes, including diagnosis, treatment planning, medication management, and preventive care. #### Use Case: CommuniCare Advantage faced operational inefficiencies and compliance risks due to rapid growth through multiple acquisitions, which led to a complex mix of technology systems and processes. This complexity resulted in increased operational costs and declining reimbursements. To address these challenges, they partnered with Digital Scientists to [streamline their technology ecosystem with CDSS](https://digitalscientists.com/case-studies/communicare-advantage/). The collaboration led to a 25% reduction in their solution footprint and positioned the organization for a potential 20% annual revenue growth. Additionally, compliance was restored within six months, significantly enhancing operational efficiency and profitability. #### Analytics Provided: CDSS provides analytics on treatment efficacy, patient response rates, and drug side effects, which companies use to improve care protocols and predict treatment outcomes. ##### Examples of CDSS Software: [Epic Systems](https://www.epic.com/), [Wolters Kluwer UpToDate](https://www.wolterskluwer.com/en/solutions/uptodate), [IBM Watson Health](https://www.ibm.com/watson), [eClinicalWorks (CDSS Module)](https://www.eclinicalworks.com/about-us/partners/partners-clinical-decision-support-cds/), [Medscape Decision Point](https://decisionpoint.medscape.com/) ### 5. Medical Imaging Software #### How Medical Imaging Software Works: Medical imaging software integrates seamlessly with imaging devices (such as CT and MRI machines) to capture digital images and store them in a secure database. Radiologists can access these images from any authorized device, zoom in on details, or compare current and past scans. Advanced solutions, such as GE Centricity, leverage AI to highlight anomalies and suggest potential diagnoses based on imaging data. #### Processes Involved: Medical imaging software handles diagnostic image acquisition, storage, and analysis, supporting radiology, pathology, and other departments. #### Use Case: Siemens Healthineers wanted [to improve their medical imaging software capabilities](https://aws.amazon.com/solutions/case-studies/siemens-healthineers-imaging-case-study/) to deliver faster, more accurate diagnostics. By leveraging AWS, they developed the Syngo Carbon platform, which enables healthcareproviders to consolidate imaging data from multiple systems into a single, cloud-based platform. This integration reduced image processing times, improved collaboration among radiologists, and streamlined diagnostic workflows. With scalable cloud infrastructure, Siemens Healthineers empowered healthcare facilities to analyze large datasets efficiently, enhancing patient outcomes through quicker and more precise imaging interpretations. #### Analytics Provided: GE Centricity provides analytics on imaging volumes, interpretation times, and diagnostic accuracy, allowing Riverdale to allocate resources effectively and improve patient outcomes. ##### Examples of Medical Imaging Software: [GE Healthcare Centricity](https://www.gehealthcare.com/middle-east/products/centricity-services), [Siemens Healthineers syngo](https://www.siemens-healthineers.com/ua/digital-health-solutions/syngovia) ### 6. Telemedicine Platforms #### How Telemedicine Works: Telemedicine platforms enable virtual consultations between healthcare providers and patients through video, audio, and messaging technology. These platforms integrate with EHRs to give clinicians access to patient histories during consultations. Advanced telemedicine solutions may also include diagnostic tools, such as remote monitoring devices or AI-driven symptom checkers. #### Processes Involved: Remote consultations via secure video or audio calls, prescription generation and delivery, patient triage using symptom-checking AI, and integration with remote monitoring devices (e.g., wearable ECGs). #### Use Case: The Medical University of South Carolina (MUSC) [implemented a telestroke program](https://tateeda.com/blog/ai-in-telemedicine-use-cases) using Teladoc Health's platform to provide rapid assessment and treatment recommendations for stroke patients in rural areas. This initiative allowed specialists to evaluate patients remotely and provide guidance to on-site clinicians, ensuring timely and high-quality neurological care within the patients' communities. #### Analytics Provided: Patient engagement metrics, consult frequencies, geographic distribution of patients. ##### Examples of Telemedicine Platforms: [Teladoc Health](https://www.teladochealth.com/), [Amwell](https://business.amwell.com/), [Doxy.me](http://doxy.me/), [Mend](https://mend.com/) ### 7. Revenue Cycle Management (RCM) #### How RCM Works: RCM software manages the financial processes associated with patient care, from initial appointment scheduling and insurance verification to billing and payment collection. By automating claims submission and tracking tasks, [RCM systems](https://www.flobotics.io/rcm-automation) reduce manual errors and expedite reimbursements. They also provide tools for managing denials and optimizing revenue streams. #### Processes Involved: - Appointment scheduling, patient registration - [Benefit and eligibility verification:](https://www.flobotics.io/agents/eligibility-check-automation) Confirming patient insurance coverage and eligibility before service delivery - [Prior authorization and verification](https://www.flobotics.io/agents/prior-authorization-automation) - Charge capture - Medical coding - [Claims processing](https://www.flobotics.io/agents/claims-management-automation): Automating the submission of claims to insurers and tracking their status - [Claims denial management](https://www.flobotics.io/agents/denials-management-automation): Identifying, analyzing, and rectifying denied claims to ensure proper reimbursement - Payment posting: recording payments from insurers and patients into the system - [RCM reporting](https://www.flobotics.io/rcm-automation) - [Compliance automation](https://www.flobotics.io/rcm-automation) #### Use Case: A healthcare organization implemented [AI-driven RCM solutions](https://www.plutushealthinc.com/post/ai-in-revenue-cycle-management-how-it-improves-rcm-efficiency-and-revenue) to enhance efficiency and revenue. The integration of artificial intelligence improved patient and claims information accuracy, streamlined workflows, and reduced the need for manual follow-ups. This led to increased productivity, better claims management, fewer denied claims, and ultimately, increased revenue. #### Analytics Provided: - Claim Acceptance Rates: Monitoring the percentage of claims approved upon first submission. - Denial Trends: Identifying common reasons for claim denials to address underlying issues. - Revenue Cycle Duration: Measuring the time taken from patient intake to final payment. - Financial Performance Metrics: Assessing overall revenue, cash flow, and profitability. ##### Examples of Revenue Cycle Management Software: [AthenaCollector by Athenahealth](https://www.athenahealth.com/knowledge-hub/healthcare-technology/athenaone-athena-clinicals-collector-communicator), [AdvancedMD RCM](https://www.advancedmd.com/learn/rcm-process-overview/), [Kareo Billing](https://www.kareo.com/medical-billing-software), [Epic Resolute](https://www.epic.com/software/access-and-revenue-cycle/) ### 8. Patient Engagement Platforms #### How Patient Engagement Works: Patient engagement platforms empower individuals to take an active role in healthcare by providing access to personal health information, educational resources, and communication tools. These platforms often feature appointment scheduling, medication reminders, and secure messaging with healthcare providers, fostering a collaborative approach to health management. #### Processes Involved: Appointment Management, health education (providing access to articles, videos, and other resources tailored to patient conditions), medication adherence (sending reminders to patients to take medications as prescribed), feedback collection (gathering patient input on services to inform quality improvement efforts). #### Use Case: A healthcare provider [utilized a patient engagement platform](https://www.marketingscoop.com/ai/healthcare-api/) to enhance communication and streamline processes. The platform facilitated appointment scheduling, provided educational materials, and enabled secure messaging between patients and providers, improving patient satisfaction and operational efficiency. #### Analytics Provided: - Engagement Metrics: Tracking patient interactions with the platform's features. - Appointment Adherence Rates: Monitoring the frequency of kept versus missed appointments. - Patient Satisfaction Scores: Assessing feedback from patients regarding their experiences. - Health Outcome Trends: Analyzing data to correlate engagement levels with health outcomes. ##### Examples of Patient Engagement Platforms: [MyChart](https://www.mychart.org/), [SolutionReach](https://www.solutionreach.com/), [Well Health](https://well.company/), [Relatient](https://www.relatient.com/), [Luma Health](https://www.lumahealth.io/) ### 9. Pharmacy Management Software #### How Pharmacy Software Works: Pharmacy management software streamlines pharmacy operations by automating tasks such as prescription processing, inventory management, and billing. These systems ensure accurate medication dispensing, maintain optimal stock levels, and support compliance with regulatory standards. #### Processes Involved: Prescription Management (processing and verifying prescriptions received from healthcare providers), inventory control (tracking medication stock levels and generating alerts for reordering), billing and insurance claims (handling financial transactions and submitting claims to insurers), regulatory compliance (ensuring adherence to laws and guidelines governing pharmacy operations). #### Use Case: HealthPoint, a healthcare organization with multiple pharmacies, sought to enhance its pharmacy operations. By [implementing Liberty Software's](https://rxinsider.com/market-buzz/liberty-softwares-pharmacyone-a-comprehensive-platform-for-modern-pharmacy-management/) pharmacy management solution, HealthPoint improved prescription processing efficiency and accuracy, leading to better patient outcomes and streamlined pharmacy workflows. #### Analytics Provided: - Dispensing Accuracy Rates: Evaluating the precision of medication dispensing processes. - Inventory Turnover Ratios: Assessing the frequency at which inventory is replenished. ##### Examples of Pharmacy Management Software: [PioneerRx](https://www.pioneerrx.com/), [Liberty Software](https://libertysoftware.com/), [Rx30](https://www.outcomes.com/rx30), [McKesson Pharmacy Systems](https://www.mckesson.com/about-mckesson/businesses/mckesson-pharmacy-systems/), [QS/1](https://qs1.com/) ### 10. Laboratory Information Management Systems (LIMS) #### How LIMS Works: Laboratory Information Management Systems (LIMS) automate and streamline laboratory processes, such as sample tracking, test scheduling, and result reporting. These systems integrate with diagnostic equipment and databases to centralize data and support regulatory compliance. #### Processes Involved: - Sample Management: Tracks specimens from collection to disposal. - Workflow Automation: Automates lab processes like test scheduling, analysis, and result generation. - Data Integration: Links lab data to EHRs for streamlined reporting and accessibility. - Regulatory Compliance: Maintain audit trails and ensure adherence to CLIA or ISO 15189 standards. #### Use Case: A clinical laboratory implemented a LIMS to address challenges in sample management and data accuracy. The system enhanced sample tracking, reduced turnaround times, and improved data integrity, improving patient care and operational efficiency. #### Analytics Provided: - Turnaround Time Analysis: Evaluate the time taken for each process step to identify bottlenecks. - Quality Control Metrics: Monitors the accuracy and reliability of laboratory results. - Resource Utilization Reports: Assesses the usage of equipment and personnel to optimize operations. - Compliance Reports: Generates documentation required for regulatory audits and inspections. ##### Examples of Laboratory Information Management Systems: [LabWare LIMS](https://www.labware.com/), [STARLIMS](https://www.starlims.com/), [Thermo Fisher SampleManager LIMS](https://www.thermofisher.com/as/en/home/digital-solutions/lab-informatics/samplemanager-lims.html), [LabVantage](https://www.labvantage.com/), [Autoscribe Informatics Matrix Gemini LIMS](https://www.autoscribeinformatics.com/lims-laboratory-information-management-system/xybion-lims) ## Advanced Clinical Solutions Advanced Clinical Solutions Interface Example – Watson for Oncology is a cognitive computing solution that rapidly processes a patient's personal data, the growing body of medical literature, expert guidelines from recognized world-class authorities, and the expertise of specialists at Memorial Sloan Kettering. Using this information, Watson for Oncology delivers personalized treatment recommendations for oncologists to review and consider. ### 11. Patient Monitoring Software #### How Patient Monitoring Works: Patient MonitoringSoftware enables continuous observation of patients' vital signs and health metrics, facilitating real-time data collection and analysis. These systems integrate with medical devices and electronic health records (EHRs) to provide comprehensive monitoring and timely alerts to healthcare providers. #### Processes Involved: - Data Acquisition: Collects real-time data from medical devices such as heart rate monitors, blood pressure cuffs, and pulse oximeters. - Data Integration: Consolidates information into a centralized platform, often integrating with EHRs for a holistic view of patient health. - Alert Generation: Sets thresholds for vital signs and generates alerts when values fall outside normal ranges, enabling prompt intervention. - Reporting: Provides detailed reports on patient status over time to assist in clinical decision-making. #### Use Case: A healthcare facility [implemented remote patient monitoring software](https://jelvix.com/blog/use-cases-and-examples-of-remote-patient-monitoring-solutions) to manage patients with chronic conditions. This system allowed clinicians to monitor patient's health data in real-time, leading to early detection of potential issues and reducing hospital readmissions. #### Analytics Provided: - Trend Analysis: Identifies patterns in vital signs over time to predict potential health issues. - Compliance Monitoring: Tracks patient adherence to monitoring protocols and device usage. - Outcome Metrics: Evaluate the effectiveness of interventions based on monitored data. - Resource Allocation Reports: Assesses the efficiency of monitoring processes and resource utilization. ##### Examples of Patient Monitoring Software: [Philips IntelliVue](https://www.philips.ua/en/healthcare/clinical-solutions/intellivue-guardian-solution), [GE Healthcare CARESCAPE](https://www.gehealthcare.com/products/patient-monitoring/patient-monitors/carescape-one), [Masimo Patient SafetyNet](https://www.masimo.com/products/hospital-automation/surveillance/safetynet/), [Medtronic CareLink](https://carelink.minimed.com/) ### 12. Disease Management Platforms #### How Disease Management Works: Disease management platforms offer tools for monitoring and managing chronic conditions by integrating patient data, enabling communication between patients and healthcare providers, and providing educational resources. These platforms aim to enhance patient outcomes through personalized care plans and proactive management. #### Processes Involved: - Patient Enrollment: Registers patients into disease management programs tailored to their conditions. - Data Collection: Gathers health data from various sources, including patient-reported outcomes and wearable devices. - Care Plan Development: Creates individualized care plans based on clinical guidelines and patient data. - Patient Education: Provides resources to educate patients about their conditions and self-management strategies. #### Use Case: A healthcare provider utilized a [disease management platform](https://www.xevensolutions.com/blog/machine-learning-in-healthcare-15-real-world-use-cases/) to support patients with diabetes. The platform offered personalized care plans, regular monitoring, and educational materials, resulting in improved glycemic control and reduced complications among participants. #### Analytics Provided: - Patient Engagement Metrics: Measure patient interaction with the platform and adherence to care plans. - Health Outcome Tracking: Monitor key health indicators to assess disease progression or improvement. - Program Effectiveness Reports: Evaluate the success of disease management initiatives. - Cost Analysis: Assess the financial impact of disease management programs on healthcare spending. ##### Examples of Disease Management Platforms: [Livongo](https://www.livongo.com/), [Omada Health](https://www.omadahealth.com/), [Propeller Health](https://propellerhealth.com/), [Welldoc (BlueStar)](https://www.welldoc.com/solutions/chronic-care-management-platform/), [Health Catalyst](https://www.healthcatalyst.com/) ### 13. Clinical Analytics Software #### How Clinical Analytics Works: Clinical analytics software aggregates and analyzes healthcare data to deliver insights that support clinical decision-making, enhance patient outcomes, and improve operational efficiency. These systems leverage advanced algorithms and machine learning to identify patterns and forecast trends. #### Processes Involved: - Data Aggregation: Collects data from EHRs, laboratory systems, and other healthcare databases. - Data Analysis: Applies statistical methods and machine learning algorithms to interpret data. - Visualization: Presents data insights through dashboards and reports for easy interpretation. - Predictive Modeling: Forecasts future trends and outcomes based on historical data. #### Use Case: A hospital implemented [clinical analytics software](https://www.intuz.com/blog/use-cases-ai-predictive-analytics-in-healthcare) to reduce patient readmission rates. The software identified high-risk individuals by analyzing patient data and enabled targeted interventions, significantly decreasing readmissions. #### Analytics Provided: - Risk Stratification Reports: Identify patients at high risk for adverse outcomes. - Performance Metrics: Evaluate clinical performance indicators such as treatment efficacy. - Operational Efficiency Analysis: Assess workflow processes to identify areas for improvement. - Predictive Analytics: Provide forecasts on patient volumes, resource needs, and potential outbreaks. ##### Examples of Clinical Analytics Software: [Health Catalyst](https://www.healthcatalyst.com/), [IBM Watson Health](https://www.ibm.com/industries/healthcare), [SAS Health Analytics](https://www.sas.com/en_us/insights/health-analytics.html), [Tableau Healthcare Analytics](https://www.tableau.com/solutions/industries/healthcare-life-sciences), [MedeAnalytics](https://medeanalytics.com/) ### 14. AI-Powered Diagnostic Tools #### How AI Diagnostic Works: AI-powered diagnostic tools leverage machine learning and deep learning algorithms to process large datasets, including medical imaging, lab results, and patient records. These tools can identify patterns, anomalies, and disease indicators that may be overlooked by the human eye. They integrate with EHR systems and other diagnostic platforms to provide comprehensive analyses. #### Processes Involved: - Data Input: Medical images or lab data are uploaded for processing. - Pattern Recognition: AI analyzes the data using trained models to identify abnormalities or predict diseases. - Integration: Results are synced with EHRs for healthcare providers to review. - Continuous Learning: Algorithms improve over time with new data. #### Use Case: Massachusetts General Hospital (MGH) and the Massachusetts Institute of Technology (MIT) have partnered to [integrate AI into radiology](https://digitaldefynd.com/IQ/ai-in-healthcare-case-studies/), with a focus on enhancing diagnostic accuracy. By leveraging deep learning techniques, the AI system was trained on extensive datasets of annotated images to identify patterns associated with conditions such as cancers, fractures, and organ abnormalities. According to a study published in the Journal of the American Medical Association (JAMA), the AI achieved a 94% accuracy rate in detecting lung nodules, significantly outperforming human radiologists, whose accuracy rate was 65%. This breakthrough automates routine diagnostic tasks, allowing radiologists to focus on more complex cases and improving patient care through fasterdiagnoses and treatment. #### Analytics Provided: - Diagnostic Accuracy Rates: Measures the precision of [AI-generated](https://www.flobotics.io/blog/genai-in-healthcare) diagnoses. - Processing Times: Tracks the time taken to analyze data and produce reports. - Outcome Tracking: Monitors patient outcomes to assess the effectiveness of AI interventions. - Usage Metrics: Evaluate how frequently and effectively the AI tools are utilized. ##### Examples of AI-Powered Diagnostic Tools: [Aidoc](https://www.aidoc.com/), [Zebra Medical Vision](https://www.zebra.com/us/en/solutions/industry/healthcare.html), [PathAI](https://www.pathai.com/), [Viz.ai](http://viz.ai/), [Arterys](https://www.arterys.com/), [Google DeepMind Health](https://deepmind.google/discover/blog/codoc-developing-reliable-ai-tools-for-healthcare/), [Qure.ai](http://qure.ai/) ### 15. Population Health Management Software #### How Population Health Works: Population health management software collects and analyzes health data from diverse sources to monitor and enhance health outcomes for specific populations. This technology helps healthcare providers identify at-risk groups and implement targeted interventions effectively. #### Processes Involved: - Data Integration: Combining data from EHRs, claims, and other health information systems. - Risk Stratification: Classifying patients based on their risk levels for certain conditions. - Intervention Planning: Developing strategies to address identified health risks. - Outcome Monitoring: Tracking the effectiveness of interventions over time. #### Use Case: The Johns Hopkins ACG System was implemented by a payer organization to improve population health management and care coordination. The system utilized advanced analytics to stratify patients by risk, enabling targeted interventions for high-risk populations. By integrating clinical and claims data, the ACG System provided actionable insights to identify gaps in care and optimize resource allocation. Over two years, the program reduced hospital readmissions by 10% and emergency department visits by 12%, demonstrating a significant impact on both cost savings and patient outcomes. This approach streamlined care delivery, enhanced patient engagement, and fostered better alignment between providers and payers, showcasing the power of data-driven solutions in healthcare. #### Analytics Provided: - Population Health Metrics: Overall health indicators of the managed population. - Risk Assessment Scores: Evaluations of patients' risk levels for various conditions. - Intervention Outcomes: Results of implemented health strategies. - Cost Analysis: Financial impact of health management programs. ##### Examples of Population Health Management Software: [Epic Healthy Planet](https://www.epic.com/software/population-health/), [AthenaHealth](https://www.athenahealth.com/solutions/population-health), [Azara](https://www.azarahealthcare.com/), [Conifer Health Solutions](https://www.coniferhealth.com/solutions/population-health-management/), [i2i Population Health](https://www.i2ipophealth.com/), [NextGen Population Health Analytics](https://www.nextgen.com/solutions/value-based-care/population-health) ## Operational Efficiency Solutions Operational Efficiency Solutions Interface Example – Kareo Billing simplifies the work of billing managers by providing clear insights into patients' collections and charge information. This transparency allows managers to track claims independently, eliminating the need to rely on billers for updates. ### 16. Surgical Planning Software #### How Surgical Planning Works: Surgical planning software allows healthcare professionals to design and simulate surgeries using patient-specific data. By integrating imaging data, such as CT or MRI scans, it creates 3D models of the patient's anatomy. Surgeons can evaluate multiple surgical scenarios, anticipate potential complications, and determine the most effective approach. These tools can also connect with intraoperative devices to guide procedures in real-time. #### Processes Involved: - Data Acquisition: Collecting imaging and diagnostic data relevant to the surgery. - 3D Modeling: Creating detailed anatomical models of the surgical area. - Simulation: Allowing surgeons to practice and refine surgical techniques virtually. - Plan Integration: Incorporating the surgical plan intooperative procedures. #### Use Case: At Clarkson College in Omaha, Nebraska, a 10-year-old patient diagnosed with osteosarcoma in the proximal tibial bone required intricate surgical intervention. [The medical team utilized](https://www.enhatch.com/case-studies/patient-specific-bolus-devices-clarkson-college) Enhatch's 3D planning portal and 3D Systems Healthcare's 3D printing capabilities to develop patient-specific cutting guides. This approach enabled surgeons to execute the procedure with heightened accuracy, leading to improved surgical outcomes and reduced operative time. #### Analytics Provided: - Surgical Success Rates: Evaluate the outcomes of surgeries planned with the software. - Procedure Times: Monitors the duration of surgical procedures. - Complication Rates: Tracks the incidence of post-operative complications. - Resource Utilization:Assesses the use of surgical tools and personnel. ##### Examples of Surgical Planning Software: [Materialise Mimics Care Suite](https://www.materialise.com/en/healthcare/mimics-innovation-suite/mimics), [3D Slicer](https://slicer.org/), [Simpleware](https://www.synopsys.com/simpleware.html), [OsiriX MD](https://www.osirix-viewer.com/osirix/osirix-md/), [Stryker Mako](https://www.stryker.com/us/en/portfolios/orthopaedics/joint-replacement/mako-robotic-arm-assisted-surgery.html), [Medtronic StealthStation](https://www.medtronic.com/en-us/healthcare-professionals/products/surgical-navigation-imaging/surgical-navigation-systems/stealthstation-s8-navigation-platform.html) ### 17. Healthcare CRM #### How Healthcare CRM Works: Healthcare CRMs are designed to enhance patient engagement and streamline interactions between patients and providers. These systems store patient information, track communication history, and automate tasks such as sending appointment reminders or follow-up notifications. CRMs integrate with EHRs to provide a comprehensive view of the patient's medical journey. #### Processes Involved: - Patient Data Management: Storing and organizing patient contact informationand interaction history. - Communication Automation: Sending automated appointment reminders and follow-up messages. - Engagement Tracking: Monitoring patient responses and engagement levels. - Feedback Collection: Gathering patient feedback to improve services. #### Use Case: By [implementing Salesforce Health Cloud](https://bluewhaleapps.com/case-studies/revolutionizing-patient-outcomes-with-salesforce-health-cloud), the leading healthcare provider centralized all patient information into a single, accessible platform, enabling faster and more informed decision-making. The solution enhanced care team collaboration through real-time communication tools, reducing errors and improving care delivery efficiency. Advanced patient engagement features empowered individuals to actively participate in their healthcare, leading to a 50% increase in patient satisfaction, a 40% faster data access rate, and a 35% improvement in care coordination. #### Analytics Provided: - Engagement Metrics: Measures patient interaction with healthcare services. - Satisfaction Scores: Evaluates patient satisfaction levels. - Communication Effectiveness: Assesses the success of outreach efforts. - Retention Rates: Tracks the continuity of patient care. ##### Examples of Healthcare CRM: [Monday.com](http://monday.com/), [Zendesk](https://www.zendesk.com/healthcare/), [Salesforce](https://www.salesforce.com/eu/healthcare-life-sciences/), [Insightly](https://www.insightly.com/industry/crm-for-healthcare/), [Zoho](https://www.zoho.com/en-in/r/healthcare/), [Creatio](https://www.creatio.com/crm-healthcare), [HIPAA CRM](https://www.hipaacrm.com/) ### 18. Healthcare Compliance Software #### How Compliance Software Works: Healthcare compliance software automates adherence to legal and regulatory requirements, such as [HIPAA](https://www.flobotics.io/blog/hipaa-compliance-rpa), GDPR, and OSHA standards. It manages policy documentation, tracks staff training, audits workflows, and logs incidents to maintain accountability. Real-time alerts help organizations address compliance gaps promptly. #### Processes Involved: - Policy Management: Creating and updating compliance policies. - Training Administration: Managing staff training programs on compliance topics. - Audit Preparation: Organizing documentation for regulatory audits. - Incident Reporting: Logging and addressing compliance violations. #### Use Case: UNC Health Johnston faced challenges in managing the verification of medical staff licenses, a process [critical for compliance](https://www.flobotics.io/blog/compliance-automation) and patient safety. By [implementing EverCheck's](https://evercheck.com/case-study-unc-health-johnston-evercheck/) automated license verification software, the organization achieved real-time monitoring of staff credentials, significantly reducing administrative burdens and ensuring continuous compliance with regulatory requirements. #### Analytics Provided: - Compliance Rates: Monitors adherence to regulatory standards. - Training Completion: Tracks staff participation in compliance training. - Audit Readiness: Assesses preparedness for regulatory reviews. - Incident Trends: Identifies patterns in compliance violations. ##### Examples of Healthcare Compliance Software: [Healthicity Health](https://www.healthicity.com/home), [Compliancy Group](https://compliancy-group.com/), [HIPAA Secure Now](https://www.hipaasecurenow.com/), [ZenQMS](https://www.zenqms.com/), [Verge Health](https://www.vergehealth.com/) ### 19. Medical Billing Software #### How Billing Software Works: Medical billing software [automates the billing lifecycle](https://www.flobotics.io/blog/how-to-build-automated-medical-billing-system), from capturing charges to submitting claims and reconciling payments. It integrates with EHRs to extract billing codes and ensures compliance with insurance requirements, reducing errors and denials. #### Processes Involved: - Charge Capture: Extracts billing codes from patient records. - Claims Processing: Automates submission and tracks the status of claims with payers. - Payment Posting: Reconciles payments received from insurers and patients. - Denial Management: Identifies and resolves rejectedclaims. #### Use Case: A podiatry practice faced high denial rates due to invalid diagnosis codes. [Collaborating with Medical Billing Wholesalers](https://www.mbwrcm.com/case-study/case-study-accurate-coding-of-podiatry-encounters/), the practice improved coding accuracy, resulting in a 25% increase in collections and a 23% reduction in denials. #### Analytics Provided: Claims acceptance rates, revenue trends, billing cycle times. ##### Examples of Medical Billing Software: [MicroMD](https://www.micromd.com/), [Kareo](https://www.kareo.com/billing-companies), [WebPT](https://www.webpt.com/products/billing-software), [DrChrono](https://www.drchrono.com/medical-billing/), [Claimocity](https://claimocity.com/), [CollaborateMD](https://www.collaboratemd.com/solutions/medical-billing-software/), [eClinicalWorks](https://www.eclinicalworks.com/products-services/revenue-cycle-management/) ### 20. Care Coordination Platforms #### How Care Coordination Works: Care coordination platforms connect providers, patients, and caregivers to streamline communication and ensure seamless transitions between different stages of care. These systems consolidate patient data, track care plans, and monitor follow-up actions. #### Processes Involved: - Care Plan Development: Facilitates the creation of personalized care plans. - Communication Tools: Enables secure messaging among care teams. - Data Sharing: Consolidates patient records for coordinated decision-making. - Discharge Management: Streamlines transitions from hospital to home or rehabilitation facilities. #### Use Case: A university-based regional healthcare system [implemented PointClickCare's](https://pointclickcare.com/resource/acute-care-software/ebooks-white-papers/hospital-system-strengthening-care-coordination-case-study/) Comprehensive Care Collaboration platform to strengthen care management. The platform provided real-time data and automated processes, enabling staff to deliver better patient care through improved coordination and timely information sharing. #### Analytics Provided: Readmission rates, coordination times, and patient outcomes. ##### Examples of Care Coordination Platforms: [Birdie](https://www.birdie.care/blog/care-coordination-platform), [WellSky](https://wellsky.com/care-coordination-software/), [Nourish (CarePlanner)](https://nourishcare.com/careplanner/), [ShiftCare](https://shiftcare.com/care-management-software), [CareLineLive](https://carelinelive.com/), [CareCoordinations](https://carecoordinations.com/), [Buddy Healthcare](https://www.buddyhealthcare.com/en/care-coordination-software) ## Specialized Solutions Specialized Solutions Interface Example – AdvancedMD streamlines the daily workflow of medical practices by providing integrated solutions for practice management, electronic health record (EHR) management, and patient engagement. ### 21. Health Information Exchange (HIE) #### How HIE Works: HIE platforms allow the secure sharing of health data across different providers and organizations. [Integrating EHR systems](https://www.flobotics.io/blog/electronic-health-records-rpa) ensures that patient information is accessible to authorized users, facilitating continuity of care. #### Processes Involved: - Data Integration: Combines records from various healthcare entities. - Access Management: Ensures only authorized personnel can view data. - Data Standardization: Harmonizes information for interoperability. - Real-Time Updates: Synchronizes patient data instantly across systems. #### Use Case: With automated alerts for care transitions and streamlined public health reporting, HIE enhances operational efficiency and clinical decision-making. This improves patient safety, personalized treatments, and significant cost savings by minimizing duplicate tests and errors. HIE empowers providers with timely access to accurate information, improving outcomes and driving efficiency in healthcare delivery. #### Analytics Provided: Data exchange frequency, referral completion times, and continuity of care metrics. ##### Examples of Health Information Exchange software: [Andersen](https://andersenlab.com/industries/healthcare/health-information-exchange), [NextGen](https://www.nextgen.com/solutions/data-platforms), [Chetu](https://www.chetu.com/healthcare/health-information-exchange-software.php), [CleverDev Software](https://www.cleverdevsoftware.com/solutions/health-information-exchange-software), [ChartRequest](https://chartrequest.com/) ### 22. Healthcare Chatbots #### How Chatbots Work: Healthcare chatbots engage patients through AI-driven conversations, answering queries, providing symptom checks, and booking appointments. They integrate with backend systems like EHRs for more personalized responses. #### Processes Involved: - Symptom Triage: Assesses patient-reported symptoms using pre-set algorithms. - Appointment Scheduling: Book or reschedule visits based on availability. - Patient Education: Shares FAQs and health information. - Integration: Links with EHRs for personalized interactions. #### Use Case: [Babylon Health developed an AI-driven chatbot](https://www.researchgate.net/publication/358597321_User_Reception_of_Babylon_Health) that allows users to input symptoms and receive medical advice. The chatbot asks clarifying questions and suggests appropriate next steps, such as home remedies or booking a video consultation with a doctor. This service has expanded access to healthcare, especially in underserved areas, and has been instrumental in providing 24/7 medical support. #### Analytics Provided: Patient inquiries, resolution times, satisfaction scores. ##### Examples of Healthcare Chatbots: [Babylon Health](https://www.emed.com/uk), [Florence](https://florence.chat/), [Healthily](https://www.healthily.ai/), [Ada Health](https://ada.com/), [Sensely](http://www.sensely.com/) ### 23. Patient Portal Software #### How Patient Portals Work: Patient portals allow individuals to access their health records, schedule appointments, and communicate securely with providers. They integrate with EHR systems to display real-time updates on lab results and care plans. #### Processes Involved: - Data Access: Provides secure patient access to medical records. - Appointment Management: Simplifies scheduling and sends reminders. - Messaging Tools: Facilitates direct communication with healthcare providers. - Health Education: Offers personalized educational content based on conditions. #### Use Case: A healthcare company [developed a fully automated patient portal](https://www.elinext.com/case-study/patient-portal-for-healthcare-company/) to access patients' medical exam histories. The portal included built-in cloud storage and an image viewer, enabling doctors to access high-resolution images for diagnostic purposes. This system improved the efficiency of information sharing between patients and providers, enhancing the diagnostic process. #### Analytics Provided: Portal usage rates, appointment bookings, patient satisfaction. ##### Examples of Patient Portal Software: [SimplePractice](https://www.simplepractice.com/), [EHRYourWay](https://www.ehryourway.com/), [Jane](https://jane.app/guide/my-account-your-patient-client-portal), [MidexPRO](https://midexpro.com/), [My Client Plus](https://myclientsplus.com/login/), [Carepatron](https://www.carepatron.com/feature/patient-portal-software) ### 24. Workflow Automation Software #### How Automation Works: Workflow automation software uses robotic process automation (RPA) to handle repetitive administrative tasks, such as scheduling, data entry, and claims processing, improving accuracy and saving time. #### Processes Involved: - Task Automation: Replaces manual workflows with automated processes. - Integration: Links with existing software to consolidate operations. - Performance Tracking: Monitors task execution for optimization. #### Use Case: Women's Mental Health Specialists [implemented Keragon's no-code workflow automation](https://www.keragon.com/case-studies/womens-mental-health-specialists-increased-revenue-15pc-with-keragon) to manage patient referrals and data transfers. This automation saved an average of 5 hours per week, contributing to a 15% increase in revenue and improved response times. #### Analytics Provided: Task completion times, error rates, productivity gains. ##### Examples of Workflow Automation Software: [Kareo](https://www.tebra.com/), [Athenahealth](https://www.athenahealth.com/), [Cerner](https://cernerhealth.com/), [AdvancedMD](https://www.advancedmd.com/), [ZocDoc](https://www.zocdoc.com/), [Optum](https://www.optum.com/en/) ### 25. Inventory Management Software #### How Inventory Works: Inventory management software tracks medical supplies, automates reordering, and prevents stockouts. It integrates with procurement systems to streamline inventory control and reduce costs. #### Processes Involved: - Stock Monitoring: Provides real-time updates on inventory levels. - Reordering Automation: Places orders when stock falls below predefined thresholds. - Usage Tracking: Monitors consumption trends across departments. #### Use Case: Owensboro Regional Health transformed its 17-year practice of manual inventory management by implementing the DxONE [Inventory Manager software](https://www.beckmancoulter.com/learning-and-events/case-studies/owensboro-regional-health). This transition reduced the time dedicated to laboratory reagent inventory management from one day to under one hour weekly, significantly enhancing operational efficiency. #### Analytics Provided: Stock turnover rates, reordering frequencies, cost savings. ##### Examples of Inventory Management Software: [Zoho](https://www.zoho.com/inventory/free-inventory-management-software/), [MedSupply](https://www.medsupplysoftware.com/), [mymediset](https://mymediset.net/), [EZOfficeInventory](https://ezo.io/ezofficeinventory/), [Fishbowl](https://www.fishbowlinventory.com/industries/healthcare-and-pharmaceuticals), [Sortly](https://www.sortly.com/), [inFlow Inventory](https://www.inflowinventory.com/) ### 26. Staff Scheduling Software #### How Staff Scheduling Works: Staff scheduling software automates the creation of shift schedules, optimizes staffing levels based on demand, and allows healthcare providers to manage last-minute changes seamlessly. Managers input staffing requirements, and the software allocates shifts based on availability, skills, and workload. Notifications about shifts are automatically sent to staff, allowing for adjustments and real-time updates. #### Processes Involved: Nurse and physician scheduling, shift management, peak-hour staffing. #### Use Case: SEMO Health Network, a non-profit Federally Qualified Health Center in Southeast Missouri, faced challenges in managing staff schedules across multiple locations. By implementing Snap Schedule software, they streamlined the scheduling process, reducing administrative burdens and ensuring adequate staffing levels, which enhanced patient care and staff satisfaction. #### Analytics Provided: Shift adherence rates, overtime costs, workload balance, and peak-hour staffing effectiveness. ##### Examples of Staff Scheduling Software: [Shiftboard](https://www.shiftboard.com/industries/healthcare/), [Deputy](https://www.deputy.com/industry/healthcare), [Workforce](https://www.workforce.com/industry/hospitals), [MakeShift](https://www.makeshift.ca/), [Rotageek](https://www.rotageek.com/), [QGenda](https://www.qgenda.com/), [ShiftWizard](https://www.shiftwizard.com/), [OnShift](https://www.onshift.com/), [EasyShifts](https://easyshifts.com/) ### 27. Prescription Management Software #### How Prescription Management Works: Prescription management software automates the prescription process from order entry to fulfillment. It integrates with EHR systems to ensure that medications are tracked from the prescription point to the pharmacy. The system alerts providers for potential drug interactions or dosage errors and streamlines refill requests. #### Processes Involved: E-prescribing, refill management, medication tracking, compliance with controlled substances regulations. #### Use Case: Script Sense implemented a customized pharmacy management system to [automate prescription processing](https://www.daffodilsw.com/case-study/developing-a-pharmacy-management-system-script-sense/), inventory tracking, and billing. This automation reduced human errors, improved prescription accuracy, and decreased administrative burdens, allowing pharmacists to focus more on patient care. #### Analytics Provided: Prescription fill rates, medication adherence, error rates, compliance tracking. ##### Examples of Prescription Management Software: [Salesforce](https://www.salesforce.com/eu/healthcare-life-sciences/), [McKesson](https://www.mckesson.com/pharmacy-management/software/), [MyRx](https://myrx.in/), [ScriptPro](https://www.scriptpro.com/), [BestRx](https://www.bestrx.com/), [Mobisoft](https://mobisoftinfotech.com/products/prescription-management-software), [GO-Globe](https://www.go-globe.com/pharmacy-management-system.php) ### 28. Quality Management Software #### How Quality Management Works: Quality management software provides tools to monitor care quality, ensuring that healthcare facilities meet industry standards. It tracks various metrics, such as patient safety incidents, care outcomes, and compliance with regulations. Reports are generated regularly to support quality improvement and compliance audits. #### Processes Involved: Care quality monitoring, compliance reporting, patient safety initiatives, and performance tracking. #### Use Case: Radar Healthcare [implemented a QMS](https://www.nqa.com/en-us/resources/case-studies/radar-healthcare) to align with ISO 9001 (Quality Management) and ISO 27001 (Information Security Management) standards. This integration streamlined processes, improved data security, and enhanced overall service quality, leading to successful ISO certification. #### Analytics Provided: Incident rates, compliance scores, patient satisfaction metrics, and outcome trends. ##### Examples of Quality Management Software: [SimplerQMS](https://simplerqms.com/healthcare-quality-management-system/), [Qualityze](https://www.qualityze.com/healthcare-industry), [Intelex](https://www.intelex.com/industries/healthcare-and-medical/), [AlisQI](https://www.alisqi.com/), [ETQ Reliance](https://www.etq.com/), [Veeva Vault QMS](https://www.veeva.com/products/vault-qms/), [MasterControl](https://www.mastercontrol.com/), [Qualio](https://www.qualio.com/) ### 29. Medical Device Integration Platforms #### How Medical Device Integration Works: These platforms connect medical devices like monitors and imaging equipment to healthcare IT systems, allowing for seamless data transfer. Real-time data is stored in the EHR, enabling clinicians to monitor patient vitals continuously and access historical data for better-informed care. #### Processes Involved: Device data management, patient monitoring, and real-time data flow from medical devices to healthcare IT systems. #### Use Case: Memorial Healthcare System implemented the Philips Capsule [Medical Device Information Platform](https://www.usa.philips.com/healthcare/case-study/driving-the-benefits-of-capsule-medical-device-information-platform) (MDIP) across multiple care environments. This integration enabled automatic data collection from anesthesia equipment, physiological monitors, and mobile spot-check devices, ensuring comprehensive patient data was readily available in the electronic medical record (EMR). The system improved clinical decision-making and streamlined workflows by providing clinicians with timely and accurate patient information. #### Analytics Provided: Device utilization rates, response times to critical changes, data entry accuracy, and patient outcome data. ##### Examples ofMedical Device Integration Platforms: [Vara](https://www.vara.ai/), [Masimo](https://www.masimo.com/products/automation/medical-device-integration/), [MDI Solutions](https://www.mdisolutions.com/), [eUnity Enterprise Diagnostic Viewer](https://www.mach7t.com/solutions/enterprise-diagnostic-viewing), [Tricefy](https://triceimaging.com/product/), [Quantic](https://www.technix.it/products/quantic/) ### 30. Healthcare Data Analytics Platforms #### How Healthcare Analytics Works: Healthcare data analytics platforms aggregate and analyze vast amounts of data from patient records, treatment outcomes, and operational performance metrics. This data informs strategies for improving care, reducing costs, and optimizing resources. Advanced analytics also help predict patient needs and identify cost-saving opportunities. #### Processes Involved: Population health analysis, treatment efficacy assessment, and operational and financial trend analysis. #### Use Case: UCSF Health collaborated with GE Healthcare to [develop a predictive analytics platform](https://digitaldefynd.com/IQ/healthcare-analytics-case-studies/) utilizing GE's Mural Critical Care software. This platform analyzes real-time data from electronic health records (EHRs), vital signs monitors, and other sources to identify patterns indicative of potential patient deterioration. The platform aims to prevent adverse events in intensive care units (ICUs) by enabling proactive interventions. #### Analytics Provided: Readmission rates, treatment success rates, operational costs, patient demographics, and predictive trends. ##### Examples of Healthcare Data Analytics Platforms: [CitiusTech](https://www.citiustech.com/), [Datavant](https://www.datavant.com/), [Atropos Health](https://www.atroposhealth.com/), [HealthHelper](https://www.healthhelper.co/), [N1Health](https://www.n1health.com/), [SociallyDetermined](https://www.sociallydetermined.com/), [IBM Watson Health](https://www.ibm.com/products) ## Conclusion In the ever-evolvinglandscape of healthcare technology, the need for innovative solutions to streamline operations, enhance patient care, and ensure regulatory compliance has never been more critical. The top 30 software solutions showcased in this article represent a diverse array of tools that empower healthcare providers to revolutionize their workflows, optimize resource allocation, and improve patient outcomes. At [Flobotics](https://www.flobotics.io/), we go beyond traditional healthcare software solutions by specializing in Robotic Process Automation (RPA) and automation technologies tailored for the healthcare industry. Our focus on automating and optimizing healthcare processes ensures that organizations can achieve efficiency, accuracy, and compliance in their operations. By leveraging RPA and automation expertise, we enable healthcare providers to streamline billing operations, automate workflows, enhance patient engagement, and drive operational excellence. Let us be your partner in navigating the complexities of healthcare technology, unlocking the full potential of your processes, and delivering exceptional care to your patients. At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let's talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byYana Pokora Content Manager at Flobotics. [More from Yana](https://www.flobotics.io/our-editorial-team#pokora) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RCMRPAHealthcare ### Healthcare Document Processing: From Paperwork Pain to Automated Gain Healthcare document processing: see how automation turns intake forms, claims, and billing paperwork into a faster, error-free workflow. Bart TeodorczukJune 10, 2025 ](https://www.flobotics.io/blog/healthcare-document-processing)[ Healthcare ### Healthcare Compliance Automation: Laws, Benefits and Examples Compliance automation software for healthcare: how RPA helps organizations meet evolving regulations without adding manual review work. Filip NasiadkoOctober 09, 2023 ](https://www.flobotics.io/blog/compliance-automation)[ RCMAIHealthcare ### Top 20 Healthcare Software Platforms in 2026 | The Execs’ Guide Payer software and more: explore the top 20 healthcare software platforms for 2026, from claims tools to EHR systems cutting denial rates. Jędrzej SzymulaOctober 27, 2025 ](https://www.flobotics.io/blog/top-20-healthcare-software-examples) [All articles →](https://www.flobotics.io/blog) --- # Why Automation Training Is Key to Successful RPA Implementation Canonical: https://www.flobotics.io/blog/automation-training Author: Karl Mielnicki Published: 2024-12-03 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Why Automation Training Is Key to Successful RPA… CTO Notes [RPA](https://www.flobotics.io/blog?category=rpa) # Why Automation Training Is Key to Successful RPA Implementation [Karl MielnickiCTO & Co-Founder of Flobotics](https://www.flobotics.io/our-editorial-team#mielnicki) Published December 03, 2024Updated September 1, 2026 On this page - [Why Should Employees Be Involved in Automation from Day One?](#why-should-employees-be-involved-in-automation-from-day-one) - [How Do Employees Work with Automation?](#how-do-employees-work-with-automation) - [Handling Exceptions](#handling-exceptions) - [Bot Monitoring](#bot-monitoring) - [Human in the Loop](#human-in-the-loop) - [Identifying New Automation Opportunities](#identifying-new-automation-opportunities) - [Who in Your Company Needs Automation Training?](#who-in-your-company-needs-automation-training) - [Must-Have Departments for RPA Training](#must-have-departments-for-rpa-training) - [Optional Departments for RPA Training](#optional-departments-for-rpa-training) - [A Simple Guide to Training Your Employees on Automation](#a-simple-guide-to-training-your-employees-on-automation) - [Start with Early Education](#start-with-early-education) - [Provide Hands-On Training](#provide-hands-on-training) - [Practice in a Safe Environment](#practice-in-a-safe-environment) - [Keep Learning Ongoing](#keep-learning-ongoing) - [Collect Feedback and Adjust](#collect-feedback-and-adjust) - [Summary](#summary) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) [Robotic Process Automation (RPA)](https://www.flobotics.io/blog/rpa-use-cases-across-industries) is a game-changer. It helps businesses cut costs, streamline processes, and boost efficiency. But one critical piece that often gets overlooked is training your team to work with the bots. Employees need to understand how automation will impact their daily work and how to interact with the bots. Without proper training, your automation efforts may fall flat. Let’s break down why employee training is so important and how to make it work for your organization. ## Why Should Employees Be Involved in Automation from Day One? Automation doesn’t replace people—it works alongside them. Your employees play a vital role in ensuring that bots run smoothly. If they aren’t involved or don’t understand how bots work, automation can cause confusion and errors. Here are a few reasons why employee involvement is crucial: - Builds Trust – when employees know how automation works, they see it as a helpful tool, not a threat. Involving them early reduces fear and builds trust. - [Prevents Errors](https://www.flobotics.io/blog/rpa-failures) – trained employees can manage and oversee the bots, catching any mistakes or issues that arise. - [Maximizes Efficiency](https://www.flobotics.io/blog/what-processes-to-automate) – employees who understand automation can quickly adapt and keep things running smoothly, even when bots need a little human touch. ## How Do Employees Work with Automation? Your team’s involvement doesn’t end once the bots are live. In many cases, they will need to manage the bots daily. Here are some examples of how they interact with automation: ### Handling Exceptions Bots handle repetitive tasks, but when something unusual happens, your team steps in to resolve the issue and restart the process. ### Bot Monitoring Employees keep an eye on how the bots are performing, ensuring everything runs as it should. ### Human in the Loop In many automation processes, user input or data validation is required as part of the workflow. “Human in the Loop” enables human involvement at critical stages where automation needs support or a decision. It’s essential for the team to understand the entire process so they can effectively collaborate with the bots and seamlessly take over when necessary. ### Identifying New Automation Opportunities Your team knows the processes best. They can spot areas where automation could be expanded. ## Who in Your Company Needs Automation Training? Certain departments must be directly involved and fully trained for a smooth and successful RPA implementation. These teams will play a critical role in monitoring, maintaining, and interacting with the bots. Meanwhile, other departments could benefit from automation but, depending on whether their processes are automated, won’t necessarily require as much direct interaction. Fig. 01 · Automation training Who first Who to train on automation Train first - 01Operations teams - 02Finance and accounting - 03IT and support teams Train next How much depends on how closely their processes work with the bots. - 01HR - 02Procurement and supply chain - 03Customer service - 04Marketing ### Must-Have Departments for RPA Training These are the core departments that will be integral to your RPA implementation. They will interact with the bots daily, manage issues, and ensure smooth operation. Training for these teams is essential to the success of your [automation initiative.](https://www.flobotics.io/blog/automation-department-infographic) #### Operations Teams Since most automated processes are operational, this team will require extensive training. They must know how to handle exceptions, monitor bot performance, and ensure tasks are correctly executed. As the primary users of the bots, they will also be critical for troubleshooting. #### IT and Support Teams Your IT team will manage the technical aspects of RPA, including bot deployment, system integration, troubleshooting, and maintaining the platform. They need to be well-versed in RPA technology to keep everything running smoothly and resolve any technical issues that arise. ### Optional Departments for RPA Training These departments may not need as much training unless their processes are specifically selected for automation. Training for these teams will depend on how deeply their processes are integrated with the bots. #### Finance and Accounting Many financial processes—invoice processing, reporting, and reconciliation—are ideal for automation. However, not every company will begin by automating finance tasks. If your finance department’s processes are automated, they will need training on handling exceptions and monitoring the bots. Otherwise, training can be provided later. #### Human Resources (HR) Tasks like payroll, employee onboarding, and compliance tracking are often automated. If HR processes are chosen for automation, the team will need training to understand how bots will streamline these tasks. Otherwise, their involvement may be minimal. #### Customer Service Automation can manage routine tasks like routing inquiries or answering common customer questions. If customer service processes are automated, agents need basic training to understand how bots work and when to step in. However, this will depend on whether customer service automation is part of your RPA rollout. #### Procurement and Supply Chain Procurement teams may benefit from automating tasks like purchase order processing, supplier management, or inventory tracking. If these processes are automated, training will be required to manage the bots and address exceptions. The level of involvement will vary based on the scope of automation. #### Marketing If you automate tasks like campaign management, data entry, or CRM updates, your marketing team may need some training. However, this will largely depend on whether marketing processes are included in your automation roadmap. Relevant training will also be needed for any other departments whose processes you have chosen to automate. The level of involvement depends on the complexity and scope of the automation within their workflows. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## A Simple Guide to Training Your Employees on Automation Training your team to work with automation doesn’t have to be complicated. Here’s a step-by-step approach to make sure your team is ready to handle the bots: Fig. 02 · Automation training 5 steps How to train employees on automation - 01Start with early educationHelp people understand how automation works, what will change and how it helps them. - 02Give hands-on trainingRun sessions specific to each role. - 03Let the team practiceHave people try the bots in a controlled setting before go-live. - 04Keep learning goingGive ongoing access to training and resources. - 05Collect feedback and adjustOnce automation is live, ask the team what training they still need. ### Start with Early Education Before launching the bots, explain [the “why” behind automation](https://www.flobotics.io/blog/robotic-process-automation). Help your employees understand how it works, what it will change, and how it will benefit them. Early involvement creates buy-in and reduces resistance. ### Provide Hands-On Training Offer training sessions that are specific to each role. For example, the IT team will need to know how to maintain and troubleshoot the bots, while operations teams will need to understand how to interact with them during their daily work. ### Practice in a Safe Environment Let your team interact with the bots in a controlled setting before they go live. This allows them to get comfortable with automation without the pressure of real-time operations. ### Keep Learning Ongoing Automation isn’t a one-time event. As new bots are added or processes change, make sure your team has access to ongoing training and resources. ### Collect Feedback and Adjust Once the bots are live, gather feedback from your team. Are there any areas where they need more training? What challenges are they facing? Use this feedback to fine-tune your training program. ## Summary A successful [RPA implementation](https://www.flobotics.io/blog/rpa-challenges) isn’t just about deploying bots—it’s about ensuring your people are prepared to work with them. By providing the right training to key departments, you can maximize the benefits of automation while minimizing disruptions. Well-trained employees will be equipped to manage bots, handle exceptions, and even identify new opportunities for automation, driving continuous improvement in your operations. At [Flobotics](https://www.flobotics.io/blog/company-values-culture-case-study), we understand that a smooth transition to automation is about more than just technology—it’s about empowering your team. That’s why we offer comprehensive automation training services designed to prepare your employees to work confidently with bots. Whether you’re automating operations, [IT](https://www.flobotics.io/business-process-automation), or other departments, we provide tailored training solutions to fit your specific needs. #### Like the article? Spread the word Written byKarl Mielnicki CTO & Co-Founder of Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # GenAI in Healthcare: Unlocking New Opportunities for Care and Operations Canonical: https://www.flobotics.io/blog/genai-in-healthcare Author: Krzysztof Szwed Published: 2024-11-06 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/GenAI in Healthcare: Unlocking New Opportunities for Care… [AI](https://www.flobotics.io/blog?category=ai)[Healthcare](https://www.flobotics.io/blog?category=healthcare) # GenAI in Healthcare: Unlocking New Opportunities for Care and Operations [Krzysztof SzwedHead of Delivery at Flobotics](https://www.flobotics.io/our-editorial-team#szwed) Published November 06, 2024Updated September 1, 2026 On this page - [Automation vs. Generative AI: Understanding the Difference](#automation-vs-generative-ai-understanding-the-difference) - [GenAI’s Role in Healthcare](#genais-role-in-healthcare) - [1. Hospitals and Healthcare Systems](#1-hospitals-and-healthcare-systems) - [2. Physicians and Provider Groups](#2-physicians-and-provider-groups) - [3. Payers and Insurers](#3-payers-and-insurers) - [4. Laboratories and Diagnostic Centers](#4-laboratories-and-diagnostic-centers) - [5. Revenue Cycle Management (RCM)](#5-revenue-cycle-management-rcm) - [6. Pharmaceutical and Medical Device Companies](#6-pharmaceutical-and-medical-device-companies) - [The Real Benefits of GenAI in Healthcare](#the-real-benefits-of-genai-in-healthcare) - [1. Improved Patient Outcomes](#1-improved-patient-outcomes) - [2. Reduced Physician Burnout](#2-reduced-physician-burnout) - [3. Enhanced Fraud Detection and Risk Management](#3-enhanced-fraud-detection-and-risk-management) - [4. Streamlined Administrative Operations](#4-streamlined-administrative-operations) - [5. Faster Drug Discovery](#5-faster-drug-discovery) - [6. Accelerated Revenue Cycle Management](#6-accelerated-revenue-cycle-management) - [The Future of GenAI and Automation in Healthcare](#the-future-of-genai-and-automation-in-healthcare) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) The healthcare industry has long been at the forefront of adopting new technologies to address the rising demands of patient care, regulatory requirements, and operational efficiency. Organizations need innovative tools to thrive as challenges mount—whether from increasing patient loads, compliance pressures, or financial constraints. While technologies like [Robotic Process Automation (RPA)](https://www.flobotics.io/blog/robotic-process-automation) have already made a significant impact by automating repetitive tasks, [the arrival of Generative AI (GenAI) ](https://www.mckinsey.com/industries/healthcare/our-insights/tackling-healthcares-biggest-burdens-with-generative-ai)is poised to unlock even more transformative potential across healthcare. ## Automation vs. Generative AI: Understanding the Difference Robotic Process Automation (RPA) focuses on automating rule-based, repetitive tasks. It excels in streamlining administrative processes such as [claims processing](https://www.flobotics.io/agents/claims-management-automation), [billing](https://www.flobotics.io/rcm-automation), and data entry by mimicking human interactions with systems. RPA is valuable for eliminating manual work, reducing errors, and speeding up processes. On the other hand, Generative AI (GenAI) can create new content or synthesize complex information, going beyond the limits of rule-based tasks. It can interpret large datasets, generate predictive insights, and assist with patient diagnosis, personalized treatments, and medical research decision-making. GenAI offers more cognitive capabilities than RPA, making it a game-changer for tasks requiring human-like creativity and understanding. ## GenAI’s Role in Healthcare Each key player in the healthcare ecosystem—from hospitals and healthcare systems to insurers and pharmaceutical companies—can benefit differently from GenAI. Let’s explore the specific use cases for GenAI across various healthcare segments. Fig. 01 · GenAI Ecosystem GenAI's role in the healthcare ecosystem Healthcare ecosystem - 01Revenue cycleDenial management, faster coding and billing - 02Payers and insurersRisk analytics, claims, fraud detection - 03HospitalsDecision support, admin automation - 04LabsAutomated reports, predictive diagnostics - 05Pharma and devicesResearch, compliance automation - 06PhysiciansPersonalized treatment, clinical notes ### 1. Hospitals and Healthcare Systems #### Clinical Decision Support GenAI can assist doctors by synthesizing patient data, including medical history and diagnostics, to suggest treatment options or flag potential risks. By analyzing vast amounts of medical data in real-time, GenAI improves the speed and accuracy of diagnoses, enabling more effective treatments. #### Administrative Automation Hospitals struggle with vast paperwork and data management, especially compliance and patient records. GenAI can automatically generate reports, handle documentation, and [improve compliance](https://www.flobotics.io/blog/compliance-automation), reducing administrative burdens on hospital staff​​. ### 2. Physicians and Provider Groups #### Personalized Treatment Plans GenAI can generate individualized care plans by analyzing a patient’s genetic makeup, lifestyle, and medical history. This helps physicians provide more personalized and effective treatment strategies​. #### Automating Clinical Notes Physicians spend significant time on documentation. GenAI can listen to patient interactions and automatically create comprehensive clinical notes, reducing physician burnout and enabling more time for patient care​. ### 3. Payers and Insurers #### Claims Processing and Fraud Detection Insurers often deal with complex and high volumes of claims. GenAI can automatically process claims, identify patterns indicative of fraud, and ensure claims accuracy, which helps reduce operational costs and increases claims approval speed​​. #### Predictive Analytics for Risk Management By analyzing data on patient histories, GenAI can predict the likelihood of claims and assist insurers in optimizing their risk management strategies. It can also generate predictive models to identify potential health risks, enabling proactive interventions​. ### 4. [Laboratories](https://www.flobotics.io/blog/laboratory-automation-solutions) and Diagnostic Centers #### Automated Report Generation GenAI can synthesize test results and automatically generate detailed diagnostic reports. By cross-referencing these results with existing medical literature, GenAI can provide diagnostic insights that help doctors make informed decisions​​. #### Predictive Diagnostics In diagnostic centers, GenAI can analyze patterns in lab data to predict potential health issues before they fully develop, assisting physicians in preemptive treatments​. ### 5. [Revenue Cycle Management (RCM)](https://www.flobotics.io/rcm-automation) #### Automating [Denial Management ](https://www.flobotics.io/agents/denials-management-automation) One of the most complex areas of RCM is handling denied claims. GenAI can automatically analyze denial patterns and generate responses or appeal letters, reducing time-to-resolution and increasing recovery rates​​. #### Faster Coding and Billing GenAI can streamline the billing process by automatically coding procedures based on medical records and submitting claims, reducing administrative overheads and improving cash flow for healthcare providers​. ### 6. Pharmaceutical and Medical Device Companies #### Data Analysis and Research GenAI can analyze vast scientific literature, clinical trial data, and genomic information to discover new drug compounds or predict how patients might respond to treatments. This accelerates the R&D process, potentially reducing the time and cost associated with drug development​. #### Regulatory Compliance Automation Pharmaceutical companies can use GenAI to generate reports that ensure compliance with regulatory bodies, speeding up the approval process for new drugs or devices​. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## The Real Benefits of GenAI in Healthcare The specific value that GenAI brings to healthcare goes far beyond generic improvements like speed and efficiency. Its cognitive and creative capabilities are uniquely suited to the complex, data-driven challenges in the industry. Here are some clear, industry-specific benefits: Fig. 02 · GenAI 6 benefits The benefits of GenAI in healthcare - 01Streamlined admin work - 02Less physician burnout - 03Better fraud detection and risk management - 04Faster drug discovery - 05Better patient outcomes - 06Faster revenue cycle ### 1. Improved Patient Outcomes GenAI can provide personalized treatment recommendations by analyzing large datasets considering genetic, lifestyle, and environmental factors. This customized approach leads to more accurate diagnoses and more effective treatments​​. ### 2. Reduced Physician Burnout By automating the creation of clinical documentation and assisting with diagnostic processes, GenAI reduces physicians’ workloads, allowing them to spend more time with patients. This also lowers the risk of burnout, a growing issue in the healthcare sector. ### 3. Enhanced Fraud Detection and Risk Management For payers and insurers, GenAI analyzes claims data to identify fraudulent activities. It can also create predictive models to assess potential risks, leading to more accurate claims processing and better resource allocation​​. ### 4. Streamlined Administrative Operations Hospitals, clinics, and healthcare systems can leverage GenAI to automate the generation of patient records, compliance reports, and other administrative tasks. This reduces administrative costs and ensures data accuracy​​. ### 5. Faster Drug Discovery Pharmaceutical companies can drastically reduce the time it takes to discover new drugs. GenAI synthesizes information from various sources to identify promising compounds and predict their behavior in clinical trials​. ### 6. Accelerated Revenue Cycle Management In billing and RCM, GenAI can process claims, manage denials, and automate billing codes more efficiently than human administrators, shortening payment cycles and improving cash flow​​. ## The Future of GenAI and Automation in Healthcare At [Flobotics](https://www.flobotics.io/), we know the value of automation in healthcare and are committed to bringing the most advanced solutions, including Generative AI, to healthcare providers, payers, and pharmaceutical companies. Whether you want to improve clinical outcomes, streamline operations, or enhance financial management, we have the expertise to deliver the right solutions. By leveraging GenAI, you can ensure that your organization stays ahead in an increasingly complex industry while focusing on what matters most—delivering exceptional patient care. [Contact us](https://www.flobotics.io/contact) today to see how we can implement GenAI and automation solutions tailored to your needs. #### Like the article? Spread the word Written byKrzysztof Szwed Head of Delivery at Flobotics. [More from Krzysztof](https://www.flobotics.io/our-editorial-team#szwed) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RCMHealthcare ### RCM Automation in Healthcare | 2026 RCM automation in healthcare: how RPA, AI, and OCR cut billing errors, speed up claims, and reduce manual work in 2026 revenue cycle management. Bart TeodorczukFebruary 25, 2026 ](https://www.flobotics.io/blog/rcm-automation-healthcare)[ RCMRPAHealthcare ### Healthcare Document Processing: From Paperwork Pain to Automated Gain Healthcare document processing: see how automation turns intake forms, claims, and billing paperwork into a faster, error-free workflow. Bart TeodorczukJune 10, 2025 ](https://www.flobotics.io/blog/healthcare-document-processing)[ RCMRPAAI ### AI vs. RPA vs. ML in Healthcare RCM: A Deep Dive AI vs. RPA vs. ML in healthcare RCM: how each technology improves efficiency, accuracy, and compliance, and which to adopt first. Krzysztof SzwedFebruary 22, 2025 ](https://www.flobotics.io/blog/ai-rpa-ml-rcm) [All articles →](https://www.flobotics.io/blog) --- # Exploring the Distinction Between Attended and Unattended Bots in RPA Canonical: https://www.flobotics.io/blog/attended-unattended-bots Author: Jacek Żukowski Published: 2024-10-07 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Exploring the Distinction Between Attended and Unattended… [RPA](https://www.flobotics.io/blog?category=rpa) # Exploring the Distinction Between Attended and Unattended Bots in RPA [Jacek ŻukowskiAn RPA Consultant and Business Analyst](https://www.flobotics.io/our-editorial-team#zukowski) Published October 07, 2024Updated September 1, 2026 On this page - [Attended Bots: Enhancing Human Workflows](#attended-bots-enhancing-human-workflows) - [How Attended Bots Work](#how-attended-bots-work) - [Unattended Bots: Automating End-to-End Processes](#unattended-bots-automating-end-to-end-processes) - [How Unattended Bots Work?](#how-unattended-bots-work) - [Comparing Attended and Unattended Bots](#comparing-attended-and-unattended-bots) - [Choosing the Right Type of Bot for Your Needs](#choosing-the-right-type-of-bot-for-your-needs) - [Nature of the Task](#nature-of-the-task) - [Scalability and Volume:](#scalability-and-volume) - [Cost and ROI:](#cost-and-roi) - [Integration with Existing Systems:](#integration-with-existing-systems) - [Compliance and Security:](#compliance-and-security) - [Summary](#summary) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) In the realm of [Robotic Process Automation (RPA)](https://www.flobotics.io/blog/robotic-process-automation), using software robots to automate mundane tasks and streamline business processes has become increasingly prevalent. These bots come in different forms, each addressing specific automation needs within organizations. Two primary categories of RPA bots are attended and unattended, each serving distinct functions in enhancing operational efficiency and productivity. Let’s delve into the world of the bots to uncover their distinct objectives and functions, shedding light on why comprehending their roles is essential for optimizing automation strategies and driving business growth. Fig. 01 · RPA bots Two types Attended vs unattended robots - Attended Attended robotWorks side by side with people and helps them finish processes automatically. - Unattended Unattended robotWorks on its own, without anyone starting or watching it. ## Attended Bots: Enhancing Human Workflows Attended bots are designed to work alongside human employees, providing real-time assistance and enhancing user productivity in daily tasks. These bots operate on the user’s desktop and require human intervention to initiate and complete specific actions. Attended bots are ideal for scenarios where human judgment and decision-making are essential and the automation process involves user interaction. ### How Attended Bots Work How Attended Bots Work: #### 1. Trigger-Based Activation Attended bots are usually activated either manually by the user or automatically in response to predefined triggers. For instance, when a [customer service](https://www.flobotics.io/business-process-automation) representative receives a call, the bot can automatically pull up relevant customer details based on the incoming call information. #### 2. Real-Time Assistance Once triggered, the attended bot performs specific tasks that are either repetitive or data-intensive, freeing up the human worker to focus on more nuanced aspects of the task. For example, in healthcare, an attended bot might assist a doctor by pre-filling patient information into an [Electronic Health Record (EHR)](https://www.flobotics.io/rcm-automation) system during a consultation​. #### 3. Human-Bot Collaboration The key feature of attended bots is their collaborative nature. They assist in tasks that require frequent human decision-making or actions. For instance, in [finance](https://www.flobotics.io/business-process-automation), an attended bot might help an accountant process an invoice by extracting relevant data and filling in forms, but the final review and submission still require the accountant’s approval​. #### 4. Workflow Integration Attended bots are often integrated into users’ existing workflows. They can seamlessly interact with multiple applications, pulling data from one and pushing it into another, thereby reducing the need for manual data entry. In the [insurance sector](https://www.flobotics.io/), for instance, an attended bot might assist an underwriter by retrieving historical policy data and pre-populating forms, but the underwriter would still be responsible for final approval​. ## Unattended Bots: Automating End-to-End Processes Unattended bots operate independently without human oversight, executing predefined tasks autonomously in the background. Unattended bots are typically deployed on servers or virtual machines and can perform repetitive, rule-based tasks at scale without the need for human intervention. These bots excel in scenarios where 24/7 automation is required, such as batch processing, data migration, and report generation. ### How Unattended Bots Work? Here’s how unattended bots function: #### 1. Scheduled or Triggered Execution Unattended bots can be set to run on a specific schedule or triggered by certain events, such as the arrival of a new file in a folder or the completion of a preceding task. For example, an unattended bot might be scheduled to run every night to reconcile accounts, ensuring that all [financial records](https://www.flobotics.io/blog/rpa-for-finance) are updated by the start of the next business day​. #### 2. Autonomous Operation Once triggered, unattended bots operate autonomously, executing tasks without any human input. They can navigate multiple systems, extracting data from one, processing it, and then updating or entering it into another system. In healthcare, unattended bots can handle the entire [claims processing workflow,](https://www.flobotics.io/agents/claims-management-automation) from claims submission to [payment reconciliation](https://www.flobotics.io/rcm-automation), without any human involvement​​. #### 3. Complex [Workflow Management](https://www.flobotics.io/blog/workflow-automation) Unattended bots can handle complex, multi-step workflows involving various systems and large datasets. For instance, in the [insurance industry,](https://www.flobotics.io/blog/rpa-in-insurance-use-cases) an unattended bot might process claims by verifying customer information, checking policy details, calculating payouts, and then processing the payment without human oversight​. #### 4. Scalability and Efficiency These bots are highly scalable and can be deployed across multiple processes simultaneously. This makes them ideal for back-office operations where repetitive tasks can be standardized. In finance, unattended bots can handle processes such as [invoice processing](https://www.flobotics.io/business-process-automation), [payroll management](https://www.flobotics.io/blog/payroll-process-rpa), and compliance reporting with high accuracy and speed, significantly reducing operational costs. Fig. 02 · RPA bots How they operate How attended and unattended bots operate vs Attended bots - Real-time assistance - Started by a person (trigger-based) - Human-bot collaboration - Built into the workflow Unattended bots - Run on a schedule or trigger - Operate on their own - Manage complex workflows - Scale efficiently Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Comparing Attended and Unattended Bots The choice between attended and unattended bots depends on the specific automation requirements and the nature of the tasks to be automated. Here are key statements to consider when comparing these two types of bots Fig. 03 · RPA bots Side by side Attended vs unattended bots | Attended | Unattended | User interaction | Need a person to work with | Run on their own | Deployment | On user desktops, started manually | On servers, on a schedule or a trigger | Focus | Better experience and productivity in specific workflows | Large volumes of tasks at the same time | Compliance | More control, with user input | Strict security rules for data privacy and compliance | Best for | Front-office tasks that need real-time help | Back-office work that can be fully automated | ## Choosing the Right Type of Bot for Your Needs When deciding between attended and unattended bots for your business, it’s essential to consider the specific requirements of the tasks you want to automate. Here are key factors to pay attention to: ### Nature of the Task - If the task requires real-time interaction or frequent human decision-making, such as assisting customer service representatives during live calls or helping healthcare professionals with patient data entry, an attended bot is likely the better choice. Attended bots excel in scenarios where collaboration between the bot and the human user is necessary. - If the task is repetitive, rule-based, and can be completed without any human intervention, such as invoice processing, claims management, or data reconciliation, an unattended bot is more suitable. Unattended bots are designed to handle end-to-end processes autonomously, making them ideal for back-office operations that require consistent, error-free execution. ### Scalability and Volume: - Consider the volume of tasks and the need for scalability. Unattended bots are more scalable and can manage high volumes of transactions across multiple processes simultaneously, making them ideal for large-scale operations. - Attended bots are typically deployed on individual desktops and are better suited for processes that occur on a smaller scale or require immediate human oversight. ### Cost and ROI: - Evaluate the cost implications and expected return on investment (ROI). While potentially more expensive to deploy initially, unattended bots can deliver significant cost savings by automating large volumes of tasks and reducing the need for human labor. This often results in a faster ROI, where large-scale automation can substantially impact. - Attended bots, being more affordable and more accessible to deploy on a smaller scale, may offer a quicker and more cost-effective solution for tasks that require human interaction. They are particularly useful in environments that enhance [employee productivity](https://www.flobotics.io/blog/company-values-culture-case-study) rather than entirely replace manual processes. ### Integration with Existing Systems: - Consider how well the bot will integrate with your existing systems and workflows. Attended bots can be seamlessly integrated into your current desktop applications, providing immediate assistance without significant changes to your workflow. - On the other hand, unattended bots may require more extensive integration with your IT infrastructure, but they can operate across multiple systems and handle complex processes end-to-end. ### Compliance and Security: It’s crucial to ensure that the bots can maintain compliance and data security in industries with strict regulatory requirements, such as healthcare and finance. Both attended, and unattended bots can be designed with compliance in mind, but unattended bots, operating independently and often dealing with sensitive data, must have robust security measures in place. ## Summary Comparing attended and unattended bots reveals that each type is designed to solve specific process problems. Attended bots are best for tasks that require real-time human interaction and decision-making, while unattended bots excel at automating complete processes without human intervention. By carefully considering the nature of the task, scalability needs, cost implications, integration requirements, and [compliance concerns,](https://www.flobotics.io/rcm-automation) you can determine which type of bot is the most appropriate for your business. [At Flobotics,](https://www.flobotics.io/) we are here to help you analyze your processes and determine the best automation solution for your needs. Whether it’s implementing attended bots to enhance your team’s productivity or deploying unattended bots to automate complex workflows, we provide the expertise and support needed to achieve your[ automation goals.](https://www.flobotics.io/blog/rpa-successs-metrics) Let us help you unlock the full potential of RPA in your organization. #### Like the article? Spread the word Written byJacek Żukowski An RPA Consultant and Business Analyst. [More from Jacek](https://www.flobotics.io/our-editorial-team#zukowski) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### What Is RPA? | Robotic Process Automation Robotic Process Automation (RPA), explained: how software bots run a 24/7 digital workforce that cuts costs and human error. Bart TeodorczukSeptember 01, 2025 ](https://www.flobotics.io/blog/robotic-process-automation)[ RPAAI ### What Is Agentic AI? | The Not-So-Obvious Guide What is agentic AI? A clear guide to how autonomous AI agents reason, act, and differ from traditional rule-based automation. Jędrzej SzymulaDecember 09, 2025 ](https://www.flobotics.io/blog/agentic-ai)[ RPAAI ### Agentic AI vs Generative AI: The Next Frontier of Intelligent Automation Generative AI vs. Agentic AI, explained: from ChatGPT's 100 million users in two months to the rise of autonomous automation in 2026. Jędrzej SzymulaSeptember 08, 2025 ](https://www.flobotics.io/blog/agentic-ai-vs-generative-ai) [All articles →](https://www.flobotics.io/blog) --- # Revenue Cycle Management (RCM) in Healthcare Canonical: https://www.flobotics.io/blog/revenue-cycle-management Author: Bart Teodorczuk Published: 2024-09-30 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Revenue Cycle Management (RCM) in Healthcare [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Revenue Cycle Management (RCM) in Healthcare [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published September 30, 2024Updated September 1, 2026 On this page - [‍ What is Revenue Cycle Management in Healthcare?](#what-is-revenue-cycle-management-in-healthcare) - [2026 Law Changes: The Regulatory "Tsunami"](#2026-law-changes-the-regulatory-tsunami) - [1. The One Big Beautiful Bill Act (OBBBA)](#1-the-one-big-beautiful-bill-act-obbba) - [2. CMS Interoperability & Prior Authorization Final Rule](#2-cms-interoperability-prior-authorization-final-rule) - [3. ICD-10-CM 2026 Updates](#3-icd-10-cm-2026-updates) - [Technical Transaction Standards (The 837/835 Engine)](#technical-transaction-standards-the-837-835-engine) - [Contracts & Medical Necessity](#contracts-medical-necessity) - [CMS & HIPAA](#cms-hipaa) - [Why is RCM the financial spine of healthcare?](#why-is-rcm-the-financial-spine-of-healthcare) - [3 sides of RCM | Patient / Payer / Provider](#3-sides-of-rcm-patient-payer-provider) - [The 7-Stage Process: Front-End to Back-End](#the-7-stage-process-front-end-to-back-end) - [Revenue Cycle Management Solutions & Services](#revenue-cycle-management-solutions-services) - [Critical KPIs for RCM in Healthcare](#critical-kpis-for-rcm-in-healthcare) - [Operational Metrics: DNFB & RVU](#operational-metrics-dnfb-rvu) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) In 2026, Revenue Cycle Management (RCM) has transitioned from an administrative back-office function to a high-tech defensive strategy. The primary catalyst is the "Payer-Provider AI War," where insurers are using AI to deny claims at scale, forcing providers to deploy "Agentic AI" to protect their liquidity. Below is a deep research compilation of the latest 2026 facts, law changes, and an article structure that addresses the critical content gaps found in top search results. ## ‍ What is Revenue Cycle Management in Healthcare? Revenue cycle management (RCM) in healthcare refers to sets of repeating financial operations that require compliance with specific policies. It is quite a complex field that requires trained teams to run smoothly. Not so long ago, the RCM relied mostly on manual actions. After the 2021 however, the industry began to experiment with single-process automations. The mass-automation shift began around 2024, setting the ground for the agentic AI revolution in 2026. The whole industry began to lean towards means: patient data intake, medical coding, posting payments, denials management and many more. Claims processing All services required in terms of healthcare organizations use to manage the administrative and clinical functions associated with claims processing, payment, and revenue generation. It begins the moment a patient schedules an appointment and concludes when the final balance is collected. Healthcare revenue cycle management (RCM Healthcare) is the system that connects patient access, insurance validation, medical coding, claim submission, denial prevention, and collections into a single financial continuum. Understanding what revenue cycle management healthcare means in practice is the foundation of improving outcomes in 2025. As of early 2026, the benchmarks for "financial health" have tightened significantly due to rising operational costs and payer complexity. - The 10% Denial Crisis: Over 41% of providers now report denial rates exceeding 10% of initial submissions. In 2024, this figure was closer to 30% (Experian Health 2026). - The Cost of "Rework": Manually appealing a single denied claim now costs an average of $25 to $30 in labor. For high-cost claims (Specialty drugs, MRI), payers are using NLP (Natural Language Processing) to trigger automatic denials at a 20% higher rate than in 2024. - Clean Claim Rate (CCR) Floor: A CCR of 95% is no longer "excellent"; it is the baseline for survival. "Elite" organizations using predictive scrubbing are hitting 98.2% to 99% (I-Med Claims 2026). - The Bad Debt Peak: One in three hospitals now reports bad debt exceeding $10 million due to rising patient deductibles and the impact of Medicaid disenrollments. ## 2026 Law Changes: The Regulatory "Tsunami" Three major legislative forces are reshaping the revenue cycle this year: ### 1. The One Big Beautiful Bill Act (OBBBA) Signed into law in late 2025 and currently in its primary rollout phase (2026), this act mandates: - Consolidated Billing: Hospitals must provide patients with a single, easy-to-read, transparent bill for all services provided during an encounter (Facility + Professional fees). - Disenrollment Surge: The OBBBA’s stricter reporting minutiae is causing an estimated 10 million Americans to face "procedural disenrollment" from Medicaid, spiking uncompensated care for RCM teams. ### 2. CMS Interoperability & Prior Authorization Final Rule Effective January 2026, this rule forces a tech upgrade: - Response Deadlines: Payers must now respond to urgent prior auth requests within 72 hours and standard requests within 7 days. - Electronic PA: Providers must use APIs for prior authorization. Submitting via fax is now considered "non-compliant" and can trigger automatic technical denials. ### 3. ICD-10-CM 2026 Updates Effective October 1, 2025, for the 2026 fiscal year: - Hundreds of new codes were added for emerging conditions and social determinants of health (SDoH). - Deleted Codes: Using codes deleted as of Oct 2025 results in an automatic 100% denial rate with no grace period. ### Technical Transaction Standards (The 837/835 Engine) Modern RCM is built on Electronic Data Interchange (EDI). If your system isn't optimized for these specific HIPAA-mandated formats, your revenue is at risk: EDI 837 (The Claim): The electronic version of the paper CMS-1500 or UB-04. It transmits detailed diagnosis and procedure data from the provider to the payer. EDI 835 (The Receipt): Also known as Electronic Remittance Advice (ERA). This is the payer’s response, detailing what was paid, what was denied, and the specific Claim Adjustment Reason Codes (CARCs) used for adjustments. 834 & 270/271 Transactions: These handle benefits enrollment and real-time eligibility inquiries—the "front-end" defense against denials. High-performing cycles are optimized for EDI 837 (Claim Submission) and EDI 835 (Electronic Remittance Advice) transactions. These electronic handshakes between provider and payer, along with 834 Enrollment files, are the digital lifeblood of the 2026 revenue engine. ### Contracts & Medical Necessity Revenue is not "earned" until it survives the scrutiny of Payer Contracts and Medical Necessity reviews. In 2026, RCM is a negotiation. You must ensure your system automatically flags underpayments—when a payer pays less than the rate specified in your legally binding agreement. Payers increasingly use AI to deny claims that don't meet their specific clinical criteria. Robust RCM integrates Clinical Documentation Integrity (CDI) to prove that care was necessary before the claim is scrubbed. ### CMS & HIPAA RCM operates within a strict legal framework. Your strategy must explicitly account for: CMS (Centers for Medicare & Medicaid Services): The "primary payer" that sets the rules for the rest of the industry. In 2026, compliance with the CMS Interoperability and Prior Authorization Final Rule (CMS-0057-F) is mandatory for avoiding massive penalties. Understanding DNFB (Discharged, Not Final Billed) is critical for identifying revenue bottlenecks. Similarly, monitoring RVU (Relative Value Unit)—specifically the Work RVU (wRVU)—allows providers to measure productivity against CMS (Centers for Medicare & Medicaid Services) reimbursement standards. HIPAA & Cybersecurity: RCM involves the highest volume of Protected Health Information (PHI) exchange. Following the 2025 surge in breaches, 2026 RCM requires "Security-First" architectures, including Zero-Trust frameworks and encrypted EDI pipelines to remain HIPAA compliant. Every step must be filtered through HIPAA cybersecurity protocols and the latest CMS-0057-F interoperability rules. Starting in 2026, these rules mandate faster prior authorization turnarounds—72 hours for expedited requests—forcing a tighter integration between clinical and financial teams. - The Acronym Gap: - The Regulatory Guardrails: ### Why is RCM the financial spine of healthcare? In 2025, with Medicaid cuts and rising operational costs, a leaky revenue cycle can lead to a 15% loss in expected revenue. Ensures adherence to the No Surprises Act and shifting insurance regulations. Modern patients expect "Amazon-like" billing transparency. A smooth RCM process is now a key driver of patient loyalty. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## 3 sides of RCM | Patient / Payer / Provider Revenue Cycle Management is less a workflow than a negotiation between three parties. Each has different priorities; each controls a piece of information the others need. The cycle works only when those priorities align—which they rarely do. Patient Patients enter the system with data, expectations and an increasingly significant share of the bill. Errors here are small but costly: a mistyped policy number, a missing authorization, an assumption that insurance will “handle it.” When they don’t, the cycle stutters further downstream. With high-deductible plans, the patient is now the "third-largest payer." RCM must include Propensity to Pay analytics and Patient Financial Responsibility (PFR) modeling at the point of registration. The provider Providers deliver the care and are responsible for turning clinical reality into billable language: documentation, codes, modifiers, the bureaucratic grammar of reimbursement. In theory this should be straightforward. In practice, internal silos and uneven process discipline leak revenue long before a claim reaches the payer. Payers are using AI to increase denial friction. RCM performance is now a reflection of how well a provider anticipates Payer Logic and complies with Medical Necessity criteria before a claim is submitted. The payer (private insurer or public program) Players hold the gate - nothing new. It sets the rules, revises them without notice and adjudicates compliance after the fact. Payments are released when documentation satisfies criteria that shift more frequently than many hospitals’ operating margins can tolerate. The provider controls the only variable that can scale without negotiation: Process Maturity. By using Ambient AI to capture clinical intent, providers reduce the leverage payers have to deny claims. The tension is structural. Patients want clarity, providers want to be paid for care already delivered and payers want proof that every line item was necessary. RCM sits in the middle—not to reconcile these interests perfectly, but to ensure the cycle moves forward at all. Revenue Cycle Management sits at the intersection of three stakeholders. The strength of the cycle depends on how well each side passes information, verifies responsibility, and clears financial decisions before care is delivered. When one side fails, the entire cycle slows, margins shrink, and denial pressure rises. To stay updated click this link and read our article: “RCM Trends” Stakeholder | Role | Main Failure Points | Cycle Impact | What They Control | Patient | Responsibility + payment | Missing intake data, unclear costs | Billing delays, higher bad debt | Insurance accuracy, consent, payment responsiveness | Payer | Rules + reimbursement | Eligibility gaps, auth delays, policy nuances | Denials, underpayment, slower cash | Auth decisions, fee schedules, claim acceptance timing | Provider | Execution + documentation | Coding variance, workflow handoffs, silos | Revenue leakage, avoidable AR aging | Documentation quality, process discipline, staffing + automation | ‍ While RCM manages the flow of money, Revenue Integrity (RI) ensures that the money you receive is accurate and compliant. It is the specialized bridge between clinical care and the billing office. - Clinical Documentation Integrity (CDI): Revenue loss often starts in the exam room, not the billing office. If a clinician fails to document the specific severity (Complications or Comorbidities) correctly, the claim will be under-coded. - The RI Correction: Instead of simply "fixing" denials after they happen, 2026 organizations use CDI programs to ensure the medical record tells the full "patient story" upfront. This prevents Medical Necessity denials and protects the organization during increasing payer audits. ## The 7-Stage Process: Front-End to Back-End To rank for "process," use a structured breakdown of the patient journey: - Patient Access & Registration: Capturing demographics and insurance data upfront. Front-end accuracy determines whether revenue enters the system at all. Real-time eligibility verification and prior authorization workflows eliminate errors before they become costly denials. In 2025, organizations with the highest CCR integrate payer-specific rules at the point of patient registration, not after the claim is created. - Eligibility & Authorization: Using real-time tools to verify coverage with insurance companies before care is delivered. Insight: Eligibility issues account for 22% of preventable denials. - Charge Capture & Clinical Documentation: Recording services. 2025 sees a surge in "Ambient AI" to assist doctors in capturing every billable minute. - Medical Coding: Translating records into ICD-10/CPT codes. AI-powered coding is now standard for reducing human error. Clinical documentation integrity and accurate ICD-10/CPT coding are the foundation of the mid-cycle. Medical necessity has to be documented before a claim reaches the payer—otherwise the reimbursement process comes back as a denial. Ambient AI and GenAI now provide a “second-layer review,” reducing coding and documentation error rates by 20–40%. - Claim Submission: Scrubbing claims to ensure they are "clean" before hitting the payer portal. - Denial Management: Historically reactive, 2025 RCM is proactive, using predictive analytics to flag claims likely to be denied before submission. Modern RCM moves away from reactive denial work. Instead, it builds denial prevention and predictive flags before claims are submitted. Automated appeal letter generation and A/R automation shorten the revenue cycle and increase reimbursement—without adding headcount or expanding the billing team. - Patient Collections: Providing digital portals, text-to-pay, and personalized payment plans based on financial profiles.Revenue Intelligence & Value-Based Care - In value-based care models, reimbursement depends on outcomes, not volume. An RCM system has to report quality metrics at both the clinical and financial level to prove value delivered. This shifts the organization away from a traditional billing cycle toward a model driven by revenue intelligence. ## Revenue Cycle Management Solutions & Services Healthcare leaders must choose between point solutions (specific tools) and end-to-end platforms. Feature RCM Software (In-House) Managed RCM Services (Outsourced) Control High; total data ownership. Lower; relies on partner reporting. Cost Structure High upfront (SaaS fees). Percentage of collections. Best For Large systems with robust billing teams. Small-to-mid practices facing staffing shortages. 2025 Trend AI-driven "Agentic" workflows. Hybrid models (Human + AI co-management). In 2026, the industry has moved past simple Robotic Process Automation (RPA). While RPA follows rigid "if-then" rules to move data, Agentic AI acts as an autonomous digital teammate. - Autonomous Reasoning: Unlike older tools that just send a templated appeal, an AI Agent can "reason" through a denial. It autonomously navigates the Payer Contract, identifies the missing clinical data in the EHR, and attaches the specific medical record needed to overturn the rejection. - Predictive Orchestration: Agentic AI doesn't wait for a human to trigger a task. It proactively identifies claims at high risk for denial and initiates "pre-emptive scrubbing" to ensure a Clean Claim Rate (CCR) above 95%. ## Critical KPIs for RCM in Healthcare To stay competitive, organizations must benchmark against these 2025 gold standards: - Days in Accounts Receivable (A/R): Target < 35 days. Anything over 50 days indicates a breakdown in front-end verification. - Clean Claim Rate (CCR): Target > 95%. This is the ultimate measure of "first-pass excellence." - Net Collection Rate: Target > 96%. This measures how much of the "collectible" dollar you actually keep. - Patient Collection Rate: A rising metric; high-performers are seeing a 15% lift by using automated payment reminders. - Value-Based Care (VBC): RCM systems must now track "outcomes" rather than just "volume." This requires sophisticated data warehouses to prove quality metrics for reimbursement. - Generative AI: Beyond automation, GenAI is being used to draft complex appeal letters and summarize clinical notes for faster coding. - Cybersecurity: As data breaches rise, RCM leaders are prioritizing vendors with "Security-First" architectures to protect sensitive patient data. ### Operational Metrics: DNFB & RVU Beyond simple cash flow, 2026 leaders monitor these "under the hood" metrics: - DNFB (Discharged, Not Final Billed): This measures the dollar amount of claims held up by missing documentation or coding backlogs. A high DNFB is a leading indicator of an impending cash crunch. - RVU (Relative Value Unit): The standardized measure of value used by CMS to determine Medicare physician fees. Understanding your "Cost per RVU" is essential for measuring the actual profitability of your clinical staff. FAQ: Common RCM Challenges in 2025 Why are claims denied most often? Eligibility gaps, missing medical necessity, outdated payer rules, and coding variance to Medicare PFS adjustments. What slows down the revenue cycle? Silos between EHR and billing systems, manual appeals, and lack of payer-specific routing. How to improve patient collections? Pre-service cost estimates, mobile payment plans, automated text reminders, and financial counseling. - [Agentic RAG Workflows](https://www.flobotics.io/blog/agentic-ai-frameworks): Competitors mention "AI," but none explain Retrieval-Augmented Generation (RAG)—where the AI "reads" your specific payer contracts to argue denials based on your negotiated rates. - Machine Identity Security: As practices deploy 50+ bots, the security of those bots' credentials (Machine IDs) is a massive, unaddressed audit risk for 2026. - The "Site Neutrality" Threat: Medicare is eliminating the Inpatient-Only (IPO) List faster than expected (285 musculoskeletal codes removed as of Jan 1, 2026). Competitors fail to highlight the massive denial risk if hospitals bill these as inpatient without "extraordinary" documentation. At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RCMAIHealthcare ### RCM Statistics | 2026 Overview RCM statistics for 2026: denial rates hover near 5% and cost-to-collect keeps rising as manual processes lose ground. See the data. Jędrzej SzymulaJanuary 07, 2026 ](https://www.flobotics.io/blog/rcm-statistics-overview)[ RCMHealthcare ### RCM Automation in Healthcare | 2026 RCM automation in healthcare: how RPA, AI, and OCR cut billing errors, speed up claims, and reduce manual work in 2026 revenue cycle management. Bart TeodorczukFebruary 25, 2026 ](https://www.flobotics.io/blog/rcm-automation-healthcare)[ HealthcareRCMAI ### RCM Outsourcing in Healthcare | 2026 RCM outsourcing in 2026: why offshore labor arbitrage is failing, and how Agentic AI outsourcing is replacing it. Bart TeodorczukFebruary 02, 2026 ](https://www.flobotics.io/blog/rcm-outsourcing-healthcare) [All articles →](https://www.flobotics.io/blog) --- # Laboratory Automation Solutions: Enhancing Efficiency and Compliance in Healthcare Canonical: https://www.flobotics.io/blog/laboratory-automation-solutions Author: Bart Teodorczuk Published: 2024-09-24 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Laboratory Automation Solutions: Enhancing Efficiency and… [Healthcare](https://www.flobotics.io/blog?category=healthcare) # Laboratory Automation Solutions: Enhancing Efficiency and Compliance in Healthcare [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published September 24, 2024Updated September 1, 2026 On this page - [Processes in Laboratories That Can Benefit from Automation](#processes-in-laboratories-that-can-benefit-from-automation) - [Sample Processing](#sample-processing) - [Test Result Interpretation](#test-result-interpretation) - [Inventory Management](#inventory-management) - [Report Generation](#report-generation) - [Quality Control Checks](#quality-control-checks) - [Billing and Invoicing](#billing-and-invoicing) - [Equipment Maintenance](#equipment-maintenance) - [Compliance Monitoring](#compliance-monitoring) - [Case Study: RPA Implementation in Pathology Laboratory Operations](#case-study-rpa-implementation-in-pathology-laboratory-operations) - [The Broader Benefits of Laboratory Automation](#the-broader-benefits-of-laboratory-automation) - [1. Enhancement of Compliance with Healthcare Regulations](#1-enhancement-of-compliance-with-healthcare-regulations) - [2. Greater Accuracy in Laboratories Operations](#2-greater-accuracy-in-laboratories-operations) - [3. Broader Scalability](#3-broader-scalability) - [4.Improved Patient Care](#4-improved-patient-care) - [The Future of Laboratory Automation: What’s Next?](#the-future-of-laboratory-automation-whats-next) - [Integration of Artificial Intelligence (AI) and Machine Learning (ML)](#integration-of-artificial-intelligence-ai-and-machine-learning-ml) - [Automated Data Analytics and Predictive Insights](#automated-data-analytics-and-predictive-insights) - [Enhanced Interoperability and System Integration](#enhanced-interoperability-and-system-integration) - [Blockchain for Secure and Transparent Data Management](#blockchain-for-secure-and-transparent-data-management) - [Low-Code/No-Code Automation Platforms](#low-code-no-code-automation-platforms) - [Global Collaborative Networks](#global-collaborative-networks) - [Conclusion](#conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) The healthcare industry is undergoing significant changes driven by the adoption of automation technologies. As healthcare providers face increasing pressures to improve patient care, manage costs, and comply with stringent regulations, automation has emerged as a critical tool in meeting these challenges. One area where automation is making a substantial impact is laboratory operations. ## Processes in Laboratories That Can Benefit from Automation Laboratories are known for their complex and time-consuming processes that require meticulous attention to detail. From sample processing to test result interpretation, laboratories handle many tasks that can be optimized through automation. With the implementation of laboratory automation solutions with [Robotic Process Automation (RPA)](https://www.flobotics.io/blog/robotic-process-automation), many of these processes can be automated, freeing up valuable resources and ensuring greater accuracy. Here are eight specific laboratory operations that can benefit from laboratory automation solutions: Fig. 01 · Lab automation 9 processes Lab processes that benefit from automation Lab automation - 01Sample processing - 02Inventory management - 03Quality control checks - 04Test result analysis - 05Compliance monitoring - 06Report generation - 07Billing and invoicing - 08Equipment maintenance ### Sample Processing Laboratory automation solutions can streamline the handling of sample collection, tracking, labeling, and sorting, reducing human errors and expediting the initial phase of laboratory operations. ### Test Result Interpretation RPA, as part of laboratory automation solutions, can assist in interpreting test results, flagging abnormalities, and minimizing errors in result analysis, leading to more accurate diagnosis and treatment decisions. ### Inventory Management Automating inventory tracking, ordering, and restocking processes can optimize [supply chain management](https://www.flobotics.io/blog/warehouse-automation-process), prevent shortages, and reduce laboratory waste. ### Report Generation Automated report generation and distribution for test results can accelerate communication with healthcare providers and patients, improving overall efficiency. ### Quality Control Checks Laboratory automation solutions can facilitate continuous quality control checks, ensuring the accuracy and reliability of test results, thus maintaining high standards of laboratory operations. ### [Billing and Invoicing](https://www.flobotics.io/business-process-automation) RPA can streamline billing processes, automate insurance claims submissions, and reduce administrative burden, leading to faster reimbursements and improved financial management. ### Equipment Maintenance Automated alerts for scheduled maintenance and equipment monitoring can help laboratories ensure optimal performance, prevent breakdowns, and extend the lifespan of critical equipment. ### Compliance Monitoring Automation aids in monitoring regulatory compliance requirements such as HIPAA, ensuring data privacy and security, and safeguarding sensitive patient information from unauthorized access. ## Case Study: RPA Implementation in Pathology Laboratory Operations One of the most compelling examples of the impact of laboratory automation solutions in laboratory settings comes from [PathGroup](http://www.pathgroup.com/), a leading healthcare provider specializing in pathology services. PathGroup faced significant challenges in managing large volumes of data and ensuring compliance with healthcare regulations. To address these issues, they partnered with us to [implement laboratory automation solutions](https://www.flobotics.io/case-studies) tailored to their specific needs. We automated several key processes, including data entry and compliance reporting. Implementing these laboratory automation solutions improved data accuracy and ensured that all regulatory requirements were consistently met. With the manual work reduced, their team could focus on more important things like patient care. The result? Smoother operations, fewer errors, and overall better service for their patients. This successful implementation of laboratory automation solutions at PathGroup illustrates the transformative potential of automation in laboratory operations. Fig. 02 · Case Lab operations PathGroup: pathology lab operations GoalManage large volumes of data and stay compliant with healthcare regulationsSolutionAutomated lab tests, data entry and compliance reporting ~3,000errors a month fixed automatically 0.5FTE saved a month 10–20patient cases processed a day ## The Broader Benefits of Laboratory Automation The benefits of automation in laboratories extend beyond mere operational efficiency. ### 1. [Enhancement of Compliance](https://www.flobotics.io/rcm-automation) with Healthcare Regulations Laboratories are subject to a myriad of regulations, including HIPAA, which mandates the protection of patient data. Automated systems ensure that all processes, from data handling to reporting, comply with these regulations, reducing the risk of non-compliance and the associated penalties. ### 2. Greater Accuracy in Laboratories Operations Human error, which is a common cause of inaccuracies in manual processes, is significantly reduced when tasks are automated. This accuracy is particularly important in laboratory settings, where even small errors can seriously affect patient care. Automated systems ensure data is processed and recorded correctly, leading to more reliable test results and better-informed clinical decisions. ### 3. Broader Scalability As the demand for laboratory services continues to grow, particularly due to global health challenges such as pandemics, laboratories must scale their operations quickly and efficiently. Automation provides the flexibility to increase capacity without significant additional resources, ensuring that laboratories can meet rising demands without compromising quality. ### 4.Improved Patient Care Automated systems enable faster diagnosis and treatment by reducing the time required to process tests and deliver results. This speed is particularly important in critical care situations, where timely intervention can significantly affect patient outcomes. Furthermore, by freeing up laboratory staff from repetitive tasks, automation allows them to focus on more complex and value-added activities, such as analyzing complex cases and conducting research. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## The Future of Laboratory Automation: What’s Next? As we look ahead, laboratory automation’s future holds exciting possibilities beyond the current capabilities of [Robotic Process Automation (RPA).](https://www.flobotics.io/blog/rpa-successs-metrics) Emerging technologies and innovations are set to revolutionize laboratory operations further, enhancing the accuracy, efficiency, and scope of what can be automated. Here are some key trends and advancements that are likely to shape the future of laboratory automation: Fig. 03 · Lab automation 6 trends Trends shaping the future of lab automation - 01AI and ML integration - 02Blockchain for data management - 03Global collaborative networks - 04Better interoperability and system integration - 05Low-code and no-code platforms - 06Automated analytics and predictive insights ### Integration of Artificial Intelligence (AI) and [Machine Learning (ML)](https://www.flobotics.io/blog/robotic-process-automation-vs-machine-learning) While RPA efficiently handles repetitive, rule-based tasks, integrating AI and ML will enable laboratories to automate more complex processes that require decision-making and pattern recognition. For example, AI-driven automation could assist in interpreting test results, identifying anomalies, and even predicting outcomes based on historical data. This capability will allow laboratories to offer more personalized and precise diagnostics, ultimately improving patient care. ### Automated Data Analytics and Predictive Insights Future laboratory automation systems will likely incorporate advanced data analytics tools to process vast amounts of laboratory data in real-time. These systems will automate test results analysis and generate predictive insights that can help in early disease detection, trend analysis, and resource optimization. This move towards data-driven decision-making will be crucial in advancing precision medicine and improving healthcare outcomes. ### [Enhanced Interoperability](https://www.flobotics.io/blog/interoperability-in-healthcare) and System Integration As healthcare systems become more interconnected, the need for seamless data exchange between laboratory systems and other healthcare platforms will grow. Future automation solutions will enhance interoperability, enabling laboratories to integrate with [EHRs](https://www.flobotics.io/rcm-automation), Hospital Information Systems (HIS), and other medical databases effortlessly. This will ensure that laboratory data is readily accessible to healthcare providers, facilitating better care coordination and reducing the risk of errors. ### Blockchain for Secure and Transparent Data Management Secure and transparent data management systems are paramount as laboratories handle sensitive patient data. Blockchain technology, known for its ability to provide secure, immutable records, could be integrated into laboratory automation systems to ensure the integrity and security of laboratory data. This would enhance compliance with regulations such as [HIPAA](https://www.flobotics.io/blog/hipaa-compliance-rpa) and protect against data breaches and fraud. ### Low-Code/No-Code Automation Platforms The future will likely see an increase in the adoption of low-code and no-code platforms, making automation accessible to a broader range of users within the laboratory environment. These platforms allow non-technical staff to create and modify automation workflows with minimal coding knowledge, empowering laboratories to quickly adapt to new challenges and opportunities without relying heavily on IT resources. ### Global Collaborative Networks [Cloud technology](https://www.flobotics.io/blog/uipath-vs-gcp) and automation advancements allow laboratories across different regions to collaborate more effectively. Automated systems will enable real-time data sharing and joint analysis, fostering global research initiatives and speeding up the development of new diagnostic methods and treatments. This collaborative approach will be particularly valuable in responding to global health crises, where rapid data exchange and coordinated efforts are critical. ## Conclusion At [Flobotics,](https://www.flobotics.io/) we specialize in developing and implementing RPA solutions tailored to the healthcare industry, focusing on laboratory operations. As we look to the future, we are committed to staying at the forefront of these technological advancements to help our clients navigate the evolving landscape of laboratory automation. Whether you want to enhance your current operations or prepare for the next wave of innovation, our team guides you every step. If you’re ready to explore how automation can future-proof your laboratory, we invite you to [schedule a free consultation](https://www.flobotics.io/book) with our team. Let’s discuss your specific needs, identify the best processes for automation, and develop a customized solution that enhances efficiency, compliance, and patient care. Take the first step towards a more efficient and innovative laboratory operation! #### Like the article? Spread the word Bart Teodorczuk Head of AI at Flobotics. Automation consultant expert for the healthcare and finance industry. Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ Healthcare ### Top 30 Software Solutions for Healthcare in 2026 Healthcare software solutions: explore 30 essential tools for 2026, organized by function, to strengthen clinical care and streamline admin tasks. Yana PokoraDecember 23, 2024 ](https://www.flobotics.io/blog/healthcare-software)[ Healthcare ### Healthcare Compliance Automation: Laws, Benefits and Examples Compliance automation software for healthcare: how RPA helps organizations meet evolving regulations without adding manual review work. Filip NasiadkoOctober 09, 2023 ](https://www.flobotics.io/blog/compliance-automation)[ RPA ### Automation’s for Everyone: 100 Real-World RPA Use Cases Across Industries | 2026 RPA use cases across industries: see 100 real-world examples of process automation in action, from healthcare to manufacturing. Michał RejmanFebruary 23, 2024 ](https://www.flobotics.io/blog/rpa-use-cases-across-industries) [All articles →](https://www.flobotics.io/blog) --- # How to Build an Effective Automation Department in Your Company [+ Infographic] Canonical: https://www.flobotics.io/blog/automation-department-infographic Author: Jacek Żukowski Published: 2024-09-15 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/How to Build an Effective Automation Department in Your… [RPA](https://www.flobotics.io/blog?category=rpa) # How to Build an Effective Automation Department in Your Company [+ Infographic] [Jacek ŻukowskiAn RPA Consultant and Business Analyst](https://www.flobotics.io/our-editorial-team#zukowski) Published September 15, 2024Updated September 1, 2026 On this page - [What is an RPA Automation Department?](#what-is-an-rpa-automation-department) - [Why Do Companies Need an Automation Department?](#why-do-companies-need-an-automation-department) - [Strategic Alignment](#strategic-alignment) - [Resource Efficiency](#resource-efficiency) - [Standardization](#standardization) - [Scalability](#scalability) - [Governance and Compliance](#governance-and-compliance) - [Innovation and Continuous Improvement](#innovation-and-continuous-improvement) - [Distinguishing the Automation Department from a regular IT Department](#distinguishing-the-automation-department-from-a-regular-it-department) - [Steps to Building an Automation Department with RPA](#steps-to-building-an-automation-department-with-rpa) - [1. Define Objectives and Vision](#1-define-objectives-and-vision) - [2. Assess Current State and Identify Opportunities](#2-assess-current-state-and-identify-opportunities) - [3. Establish Governance and Framework](#3-establish-governance-and-framework) - [4. Select the Right Tools and Technologies](#4-select-the-right-tools-and-technologies) - [5. Build a Skilled Team](#5-build-a-skilled-team) - [6. Develop and Implement Pilot Projects](#6-develop-and-implement-pilot-projects) - [7. Scale Automation Efforts](#7-scale-automation-efforts) - [8. Monitor and Measure Performance](#8-monitor-and-measure-performance) - [9. Maintain and Support](#9-maintain-and-support) - [An Automation Department in Action](#an-automation-department-in-action) - [Conclusion](#conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Regarding Robotic Process Automation (RPA), we firmly believe in its tremendous potential to streamline operations, drive efficiency, and innovate how businesses operate. However, for organizations to optimally harness these benefits, it’s crucial to establish a dedicated framework that systematically leads the [implementation and governance of RPA](https://www.flobotics.io/blog/rpa-development-process). This is where an Automation Department (also known as a Center of Excellence) comes into play. In the realm of RPA, an Automation Department (AD) is not just another buzzword; it is a strategic investment that offers substantial dividends. Let me take you through what an AD is and why it’s indispensable for companies venturing into RPA. Fig. 01 · Automation department Overview Building an automation department in your company An automation department works as the company's automation factory: initiatives are not built in silos but coordinated across business units, which maximizes value and reduces risk. What it is made of - Technology infrastructureBuilding and maintaining the software, hardware and network that automation runs on. - Automation strategyA clear roadmap that ties automation to business goals. - GovernancePolicies and standards for deployments: compliance, security and consistency across the organization. - Process viabilityChoosing processes to automate based on feasibility, ROI and strategic fit. - Performance and benefits trackingMeasuring the impact of automation, tracking key metrics and ROI, and finding what to improve. - Operational change managementMoving to automated processes smoothly: address concerns, train people, minimize disruption. - MaintenanceKeeping bots working through regular updates, monitoring and support. Its main goals - 01StandardizeDeployment and management of RPA and other automation tools - 02OptimizeResource use and automation potential - 03ScaleAutomation consistently across business units - 04GovernCompliance, security and performance of automations What you gain - Higher automation ROI - More business agility - Better compliance - Scalable growth - Streamlined processes - Digital transformation Who you need The roles depend on your needs. A typical team: Automation leaderLeads the department, plans the work and reports to the board - Performance managersTrack RPA results against metrics and find areas to improve. - Change managersManage the move to automated processes with training and support. - IT supportFix technical issues and keep bots compatible with existing IT. - Compliance and risk officersMake sure processes meet regulations and flag risks. - Business analystsDevelop, test and deploy bots to the functional requirements. - Training and developmentDesign training so the team keeps learning as RPA evolves. - RPA developers and architectsFind automation opportunities, gather requirements and document processes. ## What is an RPA Automation Department? An Automation Department is a dedicated team consolidating leadership, training, best practices, and support for a specific focus area. Regarding RPA, an Automation Department serves as the “automation factory” for the entire enterprise, ensuring all RPA initiatives align with the company’s strategic goals. Indeed, an Automation Department functions just like a factory: every department and team comes to the AD with their unique idea, and the AD handles it from conception to execution. This includes idea evaluation, analysis, development, testing, and process automation. An Automation Department ensures that RPA initiatives are not deployed in silos but are harmonized across different business units, thereby maximizing value and minimizing risks. ## Why Do Companies Need an Automation Department? The importance of an Automation Department cannot be overstated. A structured approach becomes crucial as businesses scale their [automation efforts](https://www.flobotics.io/blog/rpa-development-process) to avoid chaos and inefficiencies. Here’s why an AD is essential: ### Strategic Alignment Ensures that RPA initiatives are aligned with the company’s overall strategy and goals. ### Resource Efficiency Streamlines resource allocation and avoids redundant efforts across departments. ### Standardization Establishes and enforces standards and [best practices](https://www.flobotics.io/blog/8-security-practices-for-rpa-implementation), leading to consistent quality and performance. ### Scalability Facilitates the scaling of RPA initiatives by creating reusable assets and [knowledge](https://www.flobotics.io/blog/robotic-process-automation). ### Governance and Compliance Maintains control over automation processes [to ensure compliance](https://www.flobotics.io/rcm-automation) with regulatory and internal policies. ### Innovation and Continuous Improvement Promotes a culture of continuous improvement and innovation by leveraging the latest advancements in RPA technology. ## Distinguishing the Automation Department from a regular IT Department The core difference between an Automation Department and a typical IT Department lies in their structure, function, and scope. A regular IT Department primarily focuses on maintaining and supporting the organization’s IT infrastructure. Its function is mainly technical, and its scope is usually limited to ensuring the smooth operation of IT systems, networks, and user support. Conversely, an Automation Department is open to more than just the [technical aspects](https://www.flobotics.io/blog/rpa-non-technical-developer) of IT. It takes a holistic approach that encompasses strategic planning, governance, change management, and continuous improvement in automation. The Automation Department provides direction, sets standards, manages resources, and drives [automation adoption](https://www.flobotics.io/blog/rpa-use-cases-across-industries) across the organization. This includes identifying [automation opportunities](https://www.flobotics.io/blog/what-processes-to-automate), developing and deploying bots, and ensuring the scalability and efficiency of automated processes. Fig. 02 · Automation department vs IT Automation department vs IT department | IT department | Automation department | Scope | Runs IT infrastructure, network security, software development and user support | Automates business processes and improves workflows toward larger automation goals | Governance | Manages IT risk, protects data and controls IT assets | Sets governance and controls for automation projects: compliance, resilience, strategy | Skills and resources | Broad technical skills: development, networks, cybersecurity, general support | Specialist skills in process automation, RPA development and workflow optimization | Scalability | Day-to-day IT operations and specific IT needs | Larger goals across connected systems and complex, extensive workflows | Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Steps to Building an Automation Department with RPA Building an Automation Department is a strategic initiative that can significantly transform business operations by enhancing efficiency, reducing costs, and improving customer experiences. A critical aspect of this process is assembling a skilled team that can effectively automate processes and drive continuous improvement. Below is a comprehensive step-by-step guide to help you establish an Automation Department within your organization. ### 1. Define Objectives and Vision Determine which specific processes are currently inefficient, resource-intensive, or prone to errors and would benefit from automation. Establish a clear vision for how automation will address these issues and support the overall business strategy. ### 2. Assess Current State and Identify Opportunities Conduct process audits and prioritize processes, ranking processes based on their potential impact, feasibility, and alignment with strategic goals. ### 3. Establish Governance and Framework Define roles, responsibilities, and decision-making processes for the automation department. Set standards for automation processes, data security, compliance, and change management. ### 4. Select the Right Tools and Technologies [Choose the appropriate RPA and AI tools ](https://www.flobotics.io/blog/automation-technologies)that align with your organization’s needs and technical requirements. Ensure the selected tools can integrate seamlessly with existing systems and technologies. ### 5. Build a Skilled Team Recruit or train individuals with the necessary skills to form a competent automation team. #### Key roles include: ##### RPA Developers They design, construct, and maintain the RPA bots. Their expertise lies in programming, problem-solving, and a comprehensive understanding of RPA tools. ##### Solution Architects They design the overall automation architecture and ensure alignment with IT infrastructure. ##### Business Analysts These experts analyze existing processes and identify automation opportunities. They bridge the gap between technical and non-technical stakeholders, translating business needs into functional requirements. ##### Project Managers These professionals ensure that all automation initiatives align with business objectives, coordinating efforts across teams to meet project goals on time and within budget. ##### IT Support These professionals ensure that RPA initiatives harmonize with existing IT systems and infrastructures. They troubleshoot technical issues and safeguard the smooth operation of the RPA bots. ##### Change Managers They oversee the transition phase, facilitating communication, training, and adjusting new operational methods. ##### Compliance and Risk Officers These professionals ensure the organization’s RPA activities align with regulatory obligations. They proactively identify and mitigate risks associated with RPA. ##### Performance Managers They measure the success of RPA implementations against established metrics, identifying areas of improvement. #### Business Roles (typically provided by the client): ##### Sponsor Typically, the sponsor is a senior executive who provides the necessary resources, removes roadblocks and ensures the alignment of automation initiatives with the organization’s strategic goals. ##### Business Representatives These individuals represent the end-users and business units, providing insights into the processes to be automated and validating that the solutions meet business needs. ### 6. Develop and Implement Pilot Projects Begin with pilot projects to demonstrate value and build confidence in automation solutions. Use feedback from pilot projects to refine processes and improve the implementation approach. ### 7. Scale Automation Efforts Develop a detailed roadmap for scaling automation across the organization, including timelines, milestones, and resource allocation. Gradually increase the scope of automation to include more complex and critical processes. ### 8. Monitor and Measure Performance Monitor [key performance indicators (KPIs)](https://www.flobotics.io/blog/rpa-successs-metrics) such as ROI, cost savings, process efficiency, and employee satisfaction. Regularly review and optimize automated processes to ensure they continue to deliver value. ### 9. Maintain and Support Establish a support structure to address issues, maintain automated processes, and ensure they remain up-to-date. Stay agile and adapt to new technologies and changing business needs to keep the automation strategy relevant. ## An Automation Department in Action An Automation Department can be created internally, hired externally, or outsourced. Here is an example of how we provided our [automation department services to Pain Treatment Centers of America](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) (PTCoA): [PTCoA](https://www.ptcoa.com/) approached us with the mission of automating their insurance [claims submission process. ](https://www.flobotics.io/agents/claims-management-automation)Within two weeks, we developed a bot that processed insurance claims automatically, reducing execution time to just 45 seconds. This MVP project achieved a 100% ROI in 23 days, projecting $180,000 in savings for the first year. Sorry, your browser doesn't support embedded videos. This success led PTCoA to create a rich backlog of automation ideas across various departments. As their outsourced automation department, we developed a comprehensive suite of bots tailored to their needs, significantly improving PTCoA’s operational efficiency. Our automation solutions enabled PTCoA to streamline various processes, reduce manual effort, and enhance its focus on patient care and strategic growth. Based on the projects’ overall costs (including two RPA developers and licenses) and the financial value delivered, [the ROI for year one](https://www.flobotics.io/roi-calculator) is predicted to be 449%, with total savings exceeding $400,000. The work is ongoing. We are still adding new processes to the backlog, validating their automation potential, and planning new bots to add to the network. PTCoA is set to scale, with happier employees, satisfied customers, and a strongly improved bottom line. Outsourcing your RPA development offers several advantages: faster deployment, immediate cost savings, and access to specialized expertise. Companies like PTCoA can focus on core operations while leveraging scalable, cost-efficient automation solutions that deliver high ROI quickly. Outsourcing also provides the flexibility to adapt resources based on project needs, all without the overhead of building and maintaining an internal team. ## Conclusion An Automation Department differs from a regular IT team through its comprehensive ‘factory’ model. The Department oversees the entire [automation process](https://www.flobotics.io/blog/rpa-statistics)—from the initial idea to full implementation—by standardizing processes, ensuring governance, and fostering innovative automated solutions. The Automation Department offers significant benefits, such as ensuring all automation initiatives align with the organization’s larger goals, establishing and maintaining standard processes, promoting inter-departmental communication and collaboration, and managing resources for maximum ROI. Establishing an Automation Department is the way to optimize your automation efforts and achieve sustainable success. At Flobotics, we’re dedicated to supporting you in building an Automation Department that delivers lasting value and aligns with your strategic goals. For further guidance or support, feel free to [reach out to our team](https://www.flobotics.io/contact) of experts. #### Like the article? Spread the word Written byJacek Żukowski An RPA Consultant and Business Analyst. [More from Jacek](https://www.flobotics.io/our-editorial-team#zukowski) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### Automated Document Processing: How to Do Away with Manual Paperwork? Automated document processing: how RPA turns insurance claims, loan statements, and patient forms into a paperwork-free workflow. Karl MielnickiFebruary 11, 2024 ](https://www.flobotics.io/blog/automated-document-processing)[ RPA ### Automation’s for Everyone: 100 Real-World RPA Use Cases Across Industries | 2026 RPA use cases across industries: see 100 real-world examples of process automation in action, from healthcare to manufacturing. Michał RejmanFebruary 23, 2024 ](https://www.flobotics.io/blog/rpa-use-cases-across-industries)[ RPA ### RPA Reloaded: 50+ Robotic Process Automation Statistics to Know in 2026 RPA statistics 2026: 50+ data points on robotic process automation adoption, ROI, and where the technology is headed next. Yana PokoraApril 15, 2025 ](https://www.flobotics.io/blog/rpa-statistics) [All articles →](https://www.flobotics.io/blog) --- # How Flobotics Built Its Company Values [Company Culture Case Study] Canonical: https://www.flobotics.io/blog/company-values-culture-case-study Author: Gosia Gomola Published: 2024-07-15 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/How Flobotics Built Its Company Values [Company Culture… [RPA](https://www.flobotics.io/blog?category=rpa) # How Flobotics Built Its Company Values [Company Culture Case Study] [Gosia GomolaHR Manager and member of the “People & Change” team at Flobotics](https://www.flobotics.io/our-editorial-team#gomola) Published July 15, 2024Updated September 1, 2026 On this page - [Personalized Value Creation Process: Refining What Matters to Us](#personalized-value-creation-process-refining-what-matters-to-us) - [1. One-on-one Team Interviews](#1-one-on-one-team-interviews) - [2. Values Workshop During Company Retreat](#2-values-workshop-during-company-retreat) - [3. Distilling the Outcomes](#3-distilling-the-outcomes) - [4. Presenting -> Collecting Feedback -> Rewriting](#4-presenting-collecting-feedback-rewriting) - [Flobovalues: Overview](#flobovalues-overview) - [1. FRIENDSHIP](#1-friendship) - [2. SMART QUALITY](#2-smart-quality) - [3. COURAGE](#3-courage) - [4. CLEAR COMMUNICATION](#4-clear-communication) - [5. EMPATHY-DRIVEN TRUST](#5-empathy-driven-trust) - [6. GROWTH AND CHANGE](#6-growth-and-change) - [7. FREEDOM-BASED OWNERSHIP](#7-freedom-based-ownership) - [8. FLOBOFUN!](#8-flobofun) - [Final Steps: Presenting and Implementing The Values](#final-steps-presenting-and-implementing-the-values) - [What can you learn from our process?](#what-can-you-learn-from-our-process) - [Final Words](#final-words) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) In the fast-paced world of tech, it’s easy to become consumed by KPIs and quarterly reports. However, at Flobotics, we took A LOT OF TIME to discuss something that powers our rocketship from within – our core values. Similar to updating software, we believe in refining the principles that drive our collective engine. For us, values are not just dry sentences or empty slogans. They are tangible instructions, alive in our emails, coffee chats, company trips, and projects. In their description, we aim to capture and preserve this authenticity as faithfully as possible. Our values shape how we collaborate and deliver outstanding outcomes to our Clients and Partners. They are not imposed by the leadership but created organically by our entire team. They serve as a compass for right actions and informed decision-making. Here is the story of how we created them and what we achieved as a result. The landscape that inspired us as we created values ## Personalized Value Creation Process: Refining What Matters to Us Creating our Fresh FloboValues was an extensive, collaborative project with multiple steps, and the whole company engaged. ### 1. One-on-one Team Interviews The process began with heartfelt one-on-one conversations with each employee to gather diverse perspectives on our company’s values and culture. The People & Culture team conducted these interviews to gather diverse perspectives on what attracts people to Flobotics, what makes them want to work here, what’s essential to the culture, what’s unique, and what they love about Flobotics. The team also asked about areas that could be improved and what is unacceptable in the company. Here are some questions we asked: - What in Flobotics has helped me improve myself? - What rules, attitudes, etc., should exist and do not exist? - What positive aspects of Flobotics do I consider when talking about work? - What attracts people to Flobotics? - What keeps you here? - If you could change one thing about Flobotics, what would it be? The insights gathered during these conversations were compiled into a collection of quotes. We transcribed them, selected all the meaningful quotes, printed them, and cut them down into little pieces of paper. We ended up with hundreds of quotes! ### 2. Values Workshop During Company Retreat The next step was inviting all the employees to a four-day company retreat fully dedicated to one goal – creating values together. The retreat occurred in the picturesque Polish Lake District, where we engaged in a highly creative values workshop. The fuel of the workshop was the very cards with quotes! We divided the quotes into categories to identify the most important values and then split them into categories to discuss them. At first glance, it was already quite clear what values were the most important for the team—these categories had the most quotes. The first part of the workshop – organizing hundreds of flashcards! Our discussions led to a deeper understanding of how we perceive specific values and how they resonate in our day-to-day culture. We worked together to determine what we want to embody as a team, what drives our growth, and why we value the Flobotics work environment. To make our activities more engaging, we organized brainstorming sessions in smaller groups, created visual posters, and presented our ideas to the whole group through humorous skits. We also openly shared our feelings and had lively discussions filled with laughter and emotion. The workshop lasted eight hours, and we ended up with a draft list of nine values with additional information on how Floboticans understand them. The second part of the workshop: in-group brainstorming ### 3. Distilling the Outcomes After identifying the most important values and their relevant elements to our culture, the next objective was to synthesize them, unify, and refine the language used to describe them so they were understandable and contained all the aspects important to the Floboticans. This happened back in the office and was taken care of by the CEO, Communication Team, and People & Change team. During two three-hour workshops, we carefully reviewed each value and created the first version of the values. ### 4. Presenting -> Collecting Feedback -> Rewriting After the first version of values was ready, we actively solicited feedback from all the team members. We presented the values during a series of small-team workshops. We discussed each value, asking Floboticans what they thought about how they were phrased and how they understood them. Then, we worked on the collected feedback and looked at what was recurring in people’s opinions. Checking how people understood what we had created was key for us. We wanted to ensure the entire team was on board with what we were creating. This was a challenging task, as we had to navigate an enormous amount of information and collective input to arrive at a shared vision. This process had few iterations. At every step, the feedback from the team was crucial! Finally, we ended up with eight Core Values, reflecting our team’s beliefs and aspirations that were ready to present to the team. ## Flobovalues: Overview There are eight core values in total – not one above the other, each equally pivotal and forming the essence of the Flobotics culture. The way we work, communicate, and the quality we’re known for would fundamentally change if even one of these values were missing from our daily practice. Fig. 01 · Flobovalues 8 values Flobotics values - 01 [Friendship](#1-friendship)Always put people first: they matter most.Treat colleagues as you would your own friends. Collaboration, inclusion and safety are what Flobo-friendship is built on. - 02 [Smart quality](#2-smart-quality)Do work that satisfies everyone involved.Aim for "wow" moments for clients, but not at the cost of your own satisfaction. Be business-minded and budget-aware, balancing value and cost. - 03 [Courage](#3-courage)Have the courage to think, speak and act.Think outside the box and speak up, especially when you see a problem. Value initiative and risk-taking in search of better solutions. Lead by example. - 04 [Clear communication](#4-clear-communication)Overcommunicate so the message is clear.Be thorough and transparent. Avoid assumptions: ask questions and repeat yourself if needed. Make sure you understand each other, and say so when people do good work. - 05 [Empathy-driven trust](#5-empathy-driven-trust)Encourage and presume good intentions.Trust your colleagues' intentions. Welcome different perspectives and respect different levels of knowledge, contexts and emotional states. - 06 [Growth and change](#6-growth-and-change)Embrace change and pursue growth.Improve through iteration. Reflect on yourself, care about each other's development and keep giving feedback: it makes us better. See change as a chance to grow. - 07 [Freedom-based ownership](#7-freedom-based-ownership)Take charge and make a difference, your way.Own your actions and deliver what you promise, whatever your methods or location. Stay flexible to make the biggest impact on projects, people and communities. - 08 [Flobofun!](#8-flobofun)Whatever you do, have fun.Fun fuels motivation, satisfaction and great results. It is never a waste of time: it is how we learn, grow and discover the world. The final version of our Flobovalues ### 1. FRIENDSHIP FOSTER FRIENDSHIP AND CREATE SAFE SPACES. Treat peers as you would your own friends. Remember that collaboration, inclusion, and safety are the pillars on which Flobofriendship is born. #### What do we mean by Friendship? At the heart of Flobotics is friendship – it’s where our story began, with the bond between two buddies, Filip and Karol, who turned their camaraderie into a thriving business. Every team member who joins us gets a taste of this genuine, friendly culture. It’s not about forced friendships or cheesy team-building exercises; it’s about creating a space where everyone feels comfortable, supported, and fired up to collaborate. #### What does Friendship look like on a daily basis? - For us, small talk is… a big talk.:) We always start the meetings with a few minutes of random chat or ask a specific, funny question, such as, “If you had to eat one meal for the rest of your life on a desert island, what would it be?” - On Wednesdays we have Office Day – necessarily with a shared lunch! - 2 times per year, we organize a company-wide retreat for all employers. - We also organize monthly local hang-outs in Warsaw: bowling, escape rooms, themed parties, board nights, painting with wine, cooking together, and much more:) - We have special channels on Slack for Remote workers to give them space to talk and feel included. - We invite people from outside Warsaw to visit us. Before their arrival, we plan the integration, take care of the common time in the office, and finance a few days’ stay. - If someone needs personal help, there is always someone to take care of the dog, water the flowers, or help fold the closet. Even outside working hours, we are there for each other! Flobotics Team in the bloom of summer:) ### 2. SMART QUALITY DO WORK THAT SATISFIES EVERYONE INVOLVED. Aim to create “WOW” moments for Clients, but not at the cost of your professional satisfaction. Be business-oriented and budget-aware to strike a healthy balance between value and cost. #### What do we mean by Smart Quality? At Flobotics, delivering quality isn’t just about meeting expectations; it’s about setting the industry standard. Our approach is that done is better than perfect. We understand that quality is not just about creating the perfect product but also about ensuring that it doesn’t burden our customers unnecessarily. For us, quality is not only the quality of the product but also a qualitative approach to the customer’s budget. When you ask our team about the level of quality within our ranks, there’s a unanimous consensus: everyone is committed to excellence in their area of work. #### What does Smart Quality look like on a daily basis? - We aim to achieve customer delight while ensuring our developers feel accomplished. - We do not sugarcoat our services. We focus on delivering practical solutions with real business value, always with an eye on the client’s budget and core needs. - When we hand over the project, we transfer knowledge and accurate documentation to make everything 100% understandable and usable. - We personalize our approach by matching projects to our developers’ strengths, ensuring high-quality work and team satisfaction. - Our goal is to deliver the product on time. We do not work on it endlessly, correcting irrelevant details. - We never take on projects that don’t provide a return on investment for the Client. - We go the extra mile to make clients say, “WOW.” Office days – with our international team Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## 3. COURAGE HAVE THE COURAGE TO THINK, SPEAK AND ACT. Encourage thinking outside the box and speaking out loud – especially if you see a problem. Value proactivity and risk-taking in the pursuit of better solutions. Don’t just follow – lead by example and empower others. #### What do we mean by Courage? At Flobotics, courage isn’t just a statement – it’s a core part of our culture. Embracing a bold spirit of openness, our team members are unafraid to speak their minds and actively encouraged to do so. We foster a climate of creativity and bold action by championing dissent, accountability, and thoughtful risk-taking. We never blame but appreciate honesty, openness, and attempts to experiment, even if they are unsuccessful. #### What does Courage look like on a daily basis? - We never punish for ideas, even the most ridiculous ones. Quirky and offbeat ideas are the staples of our brainstorming. - No idea is static. Every proposal has room to be debated, revisited, and refined, embodying our company’s dynamic spirit. - By asking tough and unusual questions, we push our thinking beyond the norm, sparking lively discussions that drive innovation. - Our flat hierarchy ensures that every team member has the right to present new ideas, suggest solutions, or contribute to discussions without fear of rank. - When an idea is proposed, it’s given thoughtful consideration, not dismissed without merit. - We actively provide opportunities for sharing ideas and receiving feedback, such as Gallup meetings and 360 feedback sessions. Courageous Flobotics team after running through the fire ### 4. CLEAR COMMUNICATION OVER COMMUNICATE TO CONVEY THE MESSAGE CLEARLY. Be thorough and aim for complete transparency. Avoid assumptions — ask questions and repeat yourself if necessary. Always ensure mutual understanding and speak love when people do valuable things! #### What do we mean by Clear Communication? At Flobotics, we firmly believe that assumptions are the enemy of clarity. Guessing can often lead to misunderstanding—a risk we simply cannot afford in our collaborative environment. That’s why we’ve wholeheartedly embraced the principle of over-communication: the belief that it’s always better to share too much information than too little. Most importantly, we always credit others’ work, so no one has to guess if they did well! #### What does Clear Communication look like on a daily basis? - We overcommunicate, always providing as much context as possible in project briefs and tasks, and hide nothing! - We conduct town hall meetings once a month, during which everyone can ask about anything company-related. Tough questions are welcome! - We try to keep communication in existing open Slack channels – and not to create chats among specific users and play Chinese whispers. - If something isn’t working, we speak up. We believe you’re an accomplice if you see a problem and don’t report it. - We don’t just hand off projects or instructions; we take the time to ensure the recipient has a clear understanding before moving forward. - Our #kudos channel on Slack appreciates each other’s work. No good work is left unnoticed! - Don’t assume! No question is stupid if you are not sure. - Everyone at Flobotics receives direct feedback, regardless of role or position. Our flat structure isn’t just a theory—the feedback goes from the bottom up and vice versa. Master Weekly meeting ### 5. EMPATHY-DRIVEN TRUST ENCOURAGE AND PRESUME GOOD INTENTIONS. Trust your colleagues’ positive intentions. Embrace diverse perspectives. Consistently consider individuals’ varying levels of knowledge, skills, contexts, mindsets, and emotional states. #### What do we mean by Empathy-driven Trust? At Flobotics, we appreciate the unique blend of knowledge, sensitivity, and personal experiences each team member brings to the table. Our aim is to create an environment where everyone can thrive professionally on their own terms. We believe in the positive intentions behind every action and place great trust in one another. This philosophy extends to how we communicate and deliver feedback—always with empathy and recognition of individuality. #### What does Empathy-driven trust look like on a daily basis? - We regularly examine our employees’ satisfaction levels with the [Gallup survey](https://www.gallup.com/q12/). This is one of our key company metrics! - We prioritize well-being and frequently inquire about it. - If someone posts on Slack about feeling bad, it’s okay and no one will judge. - We don’t monitor productivity – we trust that our employees do their jobs and deliver. - We offer psychological support for people in psychological crisis. - We don’t get upset at the knowledge gap – quite the opposite. We understand it and educate each other (with the patience of a saint;)). - Negative feedback does not exist for us – it is only constructive. - The People & Culture team arranges coffee meetings with colleagues, both in-office and remote, to check in on their well-being and needs. - Gallup meetings are a safe space to share about well-being, satisfaction, and needs. We listen carefully and work towards improvement. All aboard the blind train of trust! ### 6. GROWTH AND CHANGE EMBRACE CHANGE AND PURSUE GROWTH. Achieve excellence through iterations. Practice self-reflectiveness, care about each other’s development, and never stop providing feedback – it is a gift that makes us better. Be the agent of change – always perceive it as a growth opportunity! #### What do we mean by Growth and Change? Flobotics is all about riding the waves of change. Adapting to the shifting market landscape, new requirements, and new faces in the team that bring fresh perspectives – there are no two identical days with us! We acknowledge that one of our most crucial aspects is growth – which is impossible without change. We believe that creative chaos is a driving force for progress. Drumming workshop during company retreat #### What does Growth and Change look like on a daily basis? - We run a FloboAdvisory program that provides personalized support and guidance. Each developer is paired with a dedicated advisor, creating a nurturing environment for personal and professional growth. Advisors conduct regular one-on-one meetings, design unique development roadmaps, and analyze competency maps to ensure targeted skill development and career progression. - We work in Agile methodology. Nothing is perfect from Day One. We work in iterations, constantly improving our work and projects. - We encourage experimentation, testing, and retesting as part of our daily work. - We regularly plan Feedback Months, an initiative focused on improving feedback skills. Through workshops, we aim to enhance our understanding and application of feedback. - We regularly conduct evaluations and analyze our progress to ensure continuous development. - We believe in sharing knowledge, and to support knowledge acquisition, we offer a library of recommended books and courses for purchase. - We guarantee that our developers receive developer certifications while working with us. - We collaborate on a shared FloboWiki – which is our knowledge base. In ClickUp, we created a dedicated space with guidelines and articles on how to use various tools, track time on projects, what rules we have for online meetings, how to issue invoices, and much more. If you are looking for something about Flobotics operations – you will find everything in one place:) FloboWiki – a go-to resource and knowledge base for every Flobotican ### 7. FREEDOM-BASED OWNERSHIP TAKE CHARGE AND MAKE A DIFFERENCE – YOUR WAY. Be accountable for your actions and deliver what you promise, regardless of your methods and geographical location. Adopt flexibility to have the biggest impact on projects, people, and communities. #### What do we mean by Freedom-based Ownership? At our core, we embrace the notion that personal responsibility enhances agency and independence, leading to higher work quality and team well-being. We empower each team member to be accountable for their actions and projects, fostering a positive and productive workplace culture. #### What does Freedom-based ownership look like on a day-to-day basis? - We embrace remote! Whether you’re dialing in from the sunny beaches of Spain or the vibrant streets of Brazil, the location is up to you as long as the work gets done and you’re present for meetings. - Our standard practices include flexible work schedules and support for regular “workations” to balance work and play. - Every task, project, or initiative has a clearly defined owner. - We champion the idea that taking responsibility is more than an obligation— an opportunity to enhance personal agency and drive. - If you can improve something – do it! – It’s our essential principle. - We do not dictate a work style but rather offer guidance for improvement. - Our priority is the outcome achieved, not the process used to get there. Intense focus – we manage to have it from time to time;) ### 8. FLOBOFUN! WHATEVER YOU DO – HAVE FUN! Recognize that fun fuels motivation, workplace satisfaction, and delivering outstanding results. Never dismiss it as a waste of time – this is how we learn, grow, and discover the world around us. #### What do we mean by Flobofun? At Flobotics, we firmly believe that blending work with fun is the key to unlocking creativity and enhancing our understanding of the world. Just as children learn through play in a sandbox, we also explore, play, and discover the intricacies of our environment through joyful interactions. #### What does Flobofun look like on a daily basis? - Our work is more than mundane tasks and coding; it’s about joyful relationships, shared laughs, outings, parties, and unlimited breaks. We make time for it all, so we deliver our work well. - Our meetings, brainstorming sessions, and workshops must have a fun element— a silly warm-up question, relaxed chitchat, or free donuts for improving brain functions;) - We regularly organize team-building trips and outings. - Every team meeting is a celebration! We party like friends, not just co-workers, and create an atmosphere that is impossible to replicate. - We’re looking to make Wednesdays at the office more enjoyable with fresh croissants, popcorn breaks, Caesar salads, juice cocktails, and more. Fun is always on the menu! - The walls in our office hold a wealth of cherished memories – a lot of documented fun! - In addition to company-organized meetings, we brainstorm last-minute hangout ideas on our Slack #flobofun channel, such as hiking, silent disco, and movie nights (there are endless ideas!) - On Fridays, we have a dedicated calendar slots for playing games:) Our favorite one is creating memes – the best of which proudly adorn the walls of our office. Kayaking trip in full swing! ### Final Steps: Presenting and Implementing The Values The process of introducing values to our company went beyond simply posting them on our website. We implemented each value gradually, one by one, by announcing them at our Friday sum ups. Each value presentation included an introduction and a contest announcement, allowing employees to participate for a week. Afterward, we held a voting session to select the best contest response, and the winner received a prize related to the contest theme. We wanted to ensure that the values were not just presented in a dry manner but actually lived within the company. To do this, we organized various contests such as a photo competition for the “Friendship” value, a dish contest representing “Smart Quality, or a contest asking for a character that best represents “Courage.” We also held a group competition for “Clear Communication,” which was instruction for soft-boiling an egg as precisely as possible:) By presenting the values individually over time and incorporating fun contests, we aimed to enhance memorization, understanding, and practical application of the values. For the final value, “Flobofun,” we timed the announcement to coincide with another of our company retreats. This allowed us to combine the value announcement with workshops and, of course – good fun;) In addition to announcements at meetings, all our activities were regularly shared on a dedicated Slack channel, creating a space for discussion and observation exchanges. All these activities were designed to put the values into practice and integrate them into the company’s everyday thinking and operations. ### What can you learn from our process? We really went the extra mile in creating Flobotics values. We are quite happy with the result, and we see that the values actually live within the company. Want to achieve the same with your team? Here are some best tips that, in our view, can contribute to your success. - If you want to introduce values to your company, do not let a single individual or a narrow group create it. Engage the entire company, making everyone feel important, that their voice counts, and that they can even contribute to building something big. - It is best to introduce developed values in stages. Each stage requires much work, patience, and feedback gathering. - Focus on fun, a loose form of discussing values, and creativity. - Do not be afraid of change. Values live and change with the company and will never be 100% perfect. Do not expect perfection. Prepared values are better released earlier and gathered feedback from the company, based on which they can be gradually improved. Sometimes, too-long implementation of changes can make employees forget what they worked out at workshops and the idea behind creating values. ### Final Words The values at Flobotics are more than a backdrop – they are a compass for our everyday actions. They’re not just framed concepts; they’re the principles that animate our daily work and define us as a company. Our commitment to these values makes Flobotics not just a workplace but a thriving community where people come first, and excellence is a shared journey. And if our values resonate with you, why not jump on board and grow with us? Let’s make great things happen together! #### Like the article? Spread the word Written byGosia Gomola HR Manager and member of the “People & Change” team at Flobotics. [More from Gosia](https://www.flobotics.io/our-editorial-team#gomola) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Document Understanding Tools Overview Canonical: https://www.flobotics.io/blog/document-understanding-tools Author: Krzysztof Szwed Published: 2024-07-04 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Document Understanding Tools Overview [RPA](https://www.flobotics.io/blog?category=rpa) # Document Understanding Tools Overview [Krzysztof SzwedHead of Delivery at Flobotics](https://www.flobotics.io/our-editorial-team#szwed) Published July 04, 2024Updated September 1, 2026 On this page - [Document Understanding: Definition and Advantages](#document-understanding-definition-and-advantages) - [Implementing Document Understanding in Your Company: A Step-by-Step Guide](#implementing-document-understanding-in-your-company-a-step-by-step-guide) - [1. Assess Document Processing Needs:](#1-assess-document-processing-needs) - [2. Define Objectives](#2-define-objectives) - [3. Research Document Understanding Tools](#3-research-document-understanding-tools) - [4. Choose the Right Tool](#4-choose-the-right-tool) - [5. Implement the Tool](#5-implement-the-tool) - [6. Training and Testing](#6-training-and-testing) - [7. Continuous Monitoring and Optimization](#7-continuous-monitoring-and-optimization) - [Exploring Various Document Understanding Tools](#exploring-various-document-understanding-tools) - [1. UiPath Document Understanding](#1-uipath-document-understanding) - [2. Base64](#2-base64) - [3. Oracle Cloud Infrastructure (OCI)](#3-oracle-cloud-infrastructure-oci) - [The Case Study](#the-case-study) - [4. AWS Textract](#4-aws-textract) - [5. Azure AI Document Intelligence / Azure Cognitive Search](#5-azure-ai-document-intelligence-azure-cognitive-search) - [6. Google Document AI](#6-google-document-ai) - [7. IBM Watson Discovery](#7-ibm-watson-discovery) - [8. Rossum](#8-rossum) - [9. Hyperscience](#9-hyperscience) - [10. ABBYY FlexiCapture](#10-abbyy-flexicapture) - [11. Docsumo](#11-docsumo) - [Leveraging Document Understanding for Business Optimization](#leveraging-document-understanding-for-business-optimization) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Document Understanding Tools are pivotal in modernizing document management practices, streamlining workflows, and enhancing organizational efficiency. By leveraging technologies such as RPA, Machine Learning and AI, businesses can optimize document processing, improve accuracy, and unlock valuable insights from data. In this article, we take a closer look at the top Document Understanding tools available in the market, analyze use cases, and present the model Document Understanding process. Let’s dive in! ## Document Understanding: Definition and Advantages [Document Understanding](https://www.flobotics.io/business-process-automation) involves utilizing advanced technologies like Artificial Intelligence (AI) and [Machine Learning](https://www.flobotics.io/blog/robotic-process-automation-vs-machine-learning) to process, analyze, and extract information from various documents. By embracing Document Understanding Tools, businesses can achieve enhanced accuracy, reduced manual effort, faster processing times, and improved compliance with regulatory standards. The benefits extend to optimized operations, streamlined workflows, and data-driven decision-making. ## Implementing Document Understanding in Your Company: A Step-by-Step Guide Fig. 01 · Document understanding 7 steps Implementing document understanding, step by step - 01Assess your document processing needs - 02Define objectives - 03Research document understanding tools - 04Choose the right tool - 05Implement the tool - 06Train and test - 07Monitor and optimize continuously ### 1. Assess Document Processing Needs: - Identifying the document types: physical/digital, volumes (number of documents that are processed monthly) - Processing requirements within your organization (data accuracy, compliance, and security, integration, and scalability) ### 2. Define Objectives Determine the goals you aim to achieve through Document Understanding implementation. ### 3. Research Document Understanding Tools Explore available tools that align with your requirements and objectives. ### 4. Choose the Right Tool Select a Document Understanding tool based on features, integration capabilities, resource needs, and real-life use cases. ### 5. Implement the Tool Design and implement the document understanding flow within the selected tool ### 6. Training and Testing Provide training to users and conduct testing to ensure optimal tool performance. ### 7. Continuous Monitoring and Optimization Regularly monitor tool performance, gather feedback, and make necessary adjustments to improve efficiency. ## Exploring Various Document Understanding Tools ### 1. UiPath Document Understanding A frontrunner in RPA, [UiPath’s Document Understanding](https://www.uipath.com/product/document-understanding) combines RPA with AI to automate the processing of complex documents. It excels in extracting, interpreting, and processing information, catering to various industries like healthcare, finance, manufacturing, retail, telecommunications, and more. UiPath is renowned for its ease of integration and scalability, making it an ideal choice for businesses aiming to enhance operational efficiency and leverage AI-driven insights. As our tool of choice for automation, UiPath’s Document Understanding module offers high accuracy in data extraction, making it ideal for organizations seeking to streamline document processing workflows. With its customizable features, UiPath empowers businesses to tailor document automation solutions to their specific needs, driving efficiency and productivity gains. Category: On-premise available Key Traits: Combines RPA with AI, excels in data extraction, interpreting information #### The Case Study [Thermo Fisher Scientific’s Global Business Services](https://corporate.thermofisher.com/content/tfcorpsite/us/en/index.html) unit faced challenges during the COVID-19 pandemic, especially in managing vendor invoices and payments efficiently. To address these issues, they implemented UiPath Document Understanding to automate the process of Purchasing-to-pay (P2P) invoices. This solution, leveraging RPA and AI, significantly improved operational efficiency by automating the extraction and processing of data from PDFs. The automation led to a 70% reduction in invoice processing time and allowed 53% of invoices to be handled without human intervention, alleviating the workload for the finance team. Want to learn more about UiPath Document Understanding capabilities? We are an official UiPath Partner, and our developers know this platform inside out. We provide solution consultancy and licensing discounts. [Contact us](https://www.flobotics.io/contact) to learn more. ### 2. Base64 Specializing in data extraction and analysis, [Base64](https://base64.ai/demo/document-processing) offers tools that excel in converting documents into actionable insights. Its capabilities include advanced OCR technology and Natural Language Processing, making it suitable for industries requiring detailed document analysis and data extraction. It enables secure data transmission and storage across different systems and applications. Among its pros, Base64 has efficient data encoding for secure document handling and is suitable for data transfer and storage requirements. Category: Cloud-platform only Key Traits: Specializes in data extraction, advanced OCR technology, and Natural Language Processing #### The Case Study A leading bank in Turkey sought to enhance the accuracy, security, and speed of its [document processing workflows](https://base64.ai/resource/case-study-banking-innovator-sets-a-new-industry-standard-with-ai-powered-document-processing/). Together, the bank’s credit operations team and Base64.ai created custom document models for the bank’s internal forms and other government documents commonly utilized within the industry. This partnership resulted in significant improvements in document processing efficiency, faster loan application processing, cost reductions, and heightened security, positioning the bank as a more competitive player in Turkey’s banking sector. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## 3. Oracle Cloud Infrastructure (OCI) [OCI’s Document Understanding tool](https://www.oracle.com/artificial-intelligence/document-understanding/) is part of Oracle’s vast cloud services, which have AI and Machine Learning capabilities for document processing and analysis. It’s designed for seamless integration with other Oracle services, offering a robust solution for enterprises invested in the Oracle ecosystem. It includes document recognition, text extraction, and intelligent data handling functionalities. It’s great for seamless integration with Oracle cloud infrastructure. Suitable for organizations using Oracle services for document processing. Category: Cloud-platform only Key Traits: Features AI and Machine Learning capabilities for document processing and analysis ### The Case Study eCOMEX NSI developed the eCOMEX Digital Assistant [using OCI Document Understanding](https://blogs.oracle.com/ai-and-datascience/post/oci-document-understanding-custom-model-support) to automate the monthly processing of thousands of foreign trade documents, such as commercial invoices and bills of lading. This solution enabled extracting critical data fields like supplier and recipient information, pricing, and merchandise details, significantly reducing or eliminating manual data entry. Automating these processes resulted in cost savings, streamlined operations, and enhanced compliance, effectively addressing the challenges of handling large volumes of documents and scaling global operations. ### 4. AWS Textract Amazon’s offering in Document Understanding, [AWS Textract](https://aws.amazon.com/textract/?nc1=h_ls), goes beyond traditional OCR to accurately identify document contents. It is particularly effective in processing forms and tables, making it a powerful tool for businesses dealing with vast amounts of structured data. It requires an AWS account and integration with AWS services for document analysis. Category: Cloud-platform only Key Traits: Accurately identifies document contents, effective in processing forms and tables #### The Case Study Paytm, India’s largest digital payments platform, partnered with Amazon Web Services to revamp its KYC process by [integrating Amazon Textract](https://aws.amazon.com/solutions/case-studies/paytm-case-study/). This solution significantly improved the efficiency of user onboarding by extracting user data from identity documents with 97% accuracy and reducing the authentication process from months to minutes. Amazon Textract’s technology saved costs by 75%, avoiding the need for expensive third-party software. The successful deployment has enabled Paytm to explore further enhancements like facial recognition to continue advancing its service capabilities for over 24.4 million merchants and millions of users daily. ### 5. Azure AI Document Intelligence / Azure Cognitive Search [Azure AI Document Intelligence](https://azure.microsoft.com/en-us/products/ai-services/ai-document-intelligence) offers AI-powered document processing within the Azure cloud ecosystem. Microsoft’s Azure platform provides a comprehensive suite for document understanding and search capabilities. It integrates AI and machine learning to offer advanced data processing, supporting a wide range of document formats and languages. It includes text extraction, entity recognition, and language detection capabilities. Category: Cloud-platform only Key Traits: AI-powered document processing within Azure ecosystem, advanced data processing capabilities #### The Case Study [Emaar](https://www.emaar.com/) Malls partnered with [Data Semantics](https://datasemantics.co/) to [integrate Azure Cognitive Services](https://customers.microsoft.com/en-us/story/1459754150957690925-emaar-retailers-azure-en-united-arab-emirates) into their loyalty points collection process. This digital transformation allowed for automatic scanning of purchase receipts with over 92% accuracy, enabling customers to earn loyalty points more efficiently and track them through a mobile app. The initiative resulted in more than 50% cost savings in receipt processing and saved over 8,000 hours of manual work in six months. ### 6. Google Document AI [Google Document AI](https://cloud.google.com/document-ai) is Google’s solution that harnesses the power of its AI and machine learning expertise to provide a highly efficient document understanding service. It excels in processing and analyzing documents to extract valuable insights, suitable for businesses that leverage Google’s cloud services. This tool provides document analysis, entity extraction, and natural language processing functionalities. Category: Cloud-platform only Key Traits: Leverages Google’s AI and machine learning expertise #### The Case Study [Resistant AI](https://resistant.ai/) developed [Document Forensics](https://resistant.ai/products/documents/?utm_source=Blog&utm_medium=referral&utm_campaign=GCP), an API [integrated with Google Cloud’s Document AI](https://cloud.google.com/blog/topics/financial-services/resistant-ai-document-forensics-built-on-google-cloud-document-ai), to automate document fraud checks, addressing a significant challenge for FinTechs and financial institutions in adhering to KYC and AML regulations. With the high risk of fraud, such as fake accounts and tampered documents in financial services, Resistant AI’s solution ensures rapid, accurate verification of documents, identifying up to 17% of tampered bank statements and 15% of fake company registration certificates. The API improves document processing quality, accurately classifies documents, and verifies authenticity, reducing manual document fraud reviews significantly. For instance, [Payoneer](https://resistant.ai/case-studies/payoneer/) saw manual reviews drop to 18% of document intake. Habito detected 32% more fraud, reducing investigation time by 52 minutes per case, showcasing the API’s effectiveness in combating fraud and streamlining the customer onboarding process. ### 7. IBM Watson Discovery [IBM Watson Discovery](https://www.ibm.com/products/watson-discovery) is an AI-driven tool that specializes in uncovering connections in data across documents. Watson Discovery is ideal for complex document analysis, offering deep insights and trends that can drive strategic business decisions. The tool’s features include text classification, sentiment analysis, and entity extraction functionalities. It’s ideal for organizations seeking in-depth document insights. Category: Cloud-platform only Key Traits: Specializes in uncovering connections in data across documents #### The Case Study IBM business partner [ContractPodAi](https://contractpodai.com/?utm_source=ibm&utm_medium=blog&utm_campaign=ibm-think&utm_content=homepage) offers an end-to-end contract management solution designed by lawyers for lawyers. [Implementing IBM Watson Discovery](https://www.ibm.com/blog/watson-discovery-contractpodai-legal-excellence/) allows efficient management of potentially millions of contracts through a streamlined, centralized repository that aids in creating, signing, and managing contracts. With Watson Discovery’s AI capabilities, ContractPodAi empowers legal teams to quickly search and analyze vast amounts of data to find specific clauses and assess contract risks, thereby reducing the time for contract renewals by over 50% and aiding in compliance. This AI-enhanced approach minimizes the risk of non-compliance and associated costs. ### 8. Rossum Focusing on eliminating manual data entry, Rossum’s AI-driven approach to understanding documents automates data extraction from invoices and other structured documents. It’s designed to adapt to document variations, ensuring high accuracy levels. It’s very suitable for businesses that are processing extensive invoice data. Category: On-premise available Key Traits: Automated data extraction from invoices, adapts to document variations #### The Case Study Faced with the challenge of processing 150,000 invoices annually, NFI Industries sought to optimize its Accounts Payable (AP) operations. Collaborating with Rossum, it automated document processing, leveraging advanced AI to extract and validate data seamlessly. By integrating with Coupa and customizing solutions to match its business logic, NFI achieved enhanced efficiency, reduced costs, and embraced innovation in its AP processes. ### 9. Hyperscience This tool offers a Machine Learning-based solution to automate document processing and data capture. Hyperscience distinguishes itself with its ability to continuously learn from data, improving its accuracy and efficiency over time. The tool specializes in document classification, data extraction, and intelligent processing functionalities. Hyperscience is ideal for organizations looking to automate document workflows. Category: Cloud-platform only Key Traits: ML-based solution for document processing and data capture, continuously learns from data #### The Case Study Faced with challenges in processing incoming fax images, divvyDOSE sought to streamline its document processing. By [implementing Hyperscience’s](https://www.hyperscience.com/knowledge-base/divvydose-revolutionizes-document-processing-with-hyperscience/) Hyperautomation solution, divvyDOSE automated text extraction from fax images, significantly reducing manual effort and improving efficiency. The collaboration between divvyDOSE and Hyperscience ensured a seamless implementation, resulting in remarkable efficiency gains and enhanced productivity in document processing operations. ### 10. ABBYY FlexiCapture ABBYY’s FlexiCapture is an intelligent data capture and document processing platform renowned for its powerful OCR capabilities and flexibility in document processing. FlexiCapture excels at handling various types of documents, from forms to unstructured texts, making it versatile for multiple use cases. Its exceptional accuracy in data extraction is particularly beneficial for businesses with complex document processing needs. Category: On-premise available Key Traits: Intelligent data capture, powerful OCR capabilities, flexibility in document processing #### The Case Study [Companies House](http://www.companieshouse.gov.uk/), a public sector entity managing large volumes of paper-based documents, sought to digitize and streamline its processes. As a result of the [integration](https://www.abbyy.com/customer-stories/abbyy-flexicapture-software-helps-companies-house-on-its-journey-to-becoming-a-truly-digital-organisation/), staff at Companies House can now extract data from forms and documents and directly embed the information into workflows to automate, separate, and classify documents quickly. With reduced paper handling, improved accuracy, and cost-effective solutions, ABBYY FlexiCapture empowered Companies House to transition into a fully digital organization, setting a precedent for future enhancements. ### 11. Docsumo Specializing in extracting and processing data from financial documents, Docsumo leverages AI to streamline financial operations. It automates the extraction of key data fields from invoices, receipts, contracts, and other documents. Its focus on finance and accounting documents makes it a valuable tool for businesses in those sectors. Category: Cloud-platform only Key Traits: Specializes in extracting data from financial documents, AI-driven #### The Case Study [PayU](https://corporate.payu.com/), a multinational fintech company processing over 100,000 loan applications monthly, faced challenges handling unstructured verification documents and bank statements. Docsumo seamlessly ingested various types of documents, including bank statements, checks, and identification proofs, through API-based integration. Its advanced OCR module efficiently extracted data from unstructured text, even from documents with varying layouts and image quality. Additionally, Docsumo’s intelligent categorization framework rapidly learned from documents, accurately identifying key-value pairs and line items. By[ implementing Docsumo,](https://www.docsumo.com/customer-stories/digital-lender-process-automation) PayU achieved a 99%+ data extraction accuracy and 10x faster unstructured data processing, significantly reducing manual effort and improving efficiency.” ### Leveraging Document Understanding for Business Optimization By adopting advanced Document Understanding Tools, businesses can optimize document management practices, streamline workflows, and unlock valuable insights from data. Automating document processing workflows and extracting critical insights enables organizations to enhance operational efficiency, improve accuracy, and drive innovation. Choosing the right Document Understanding Tool involves evaluating factors such as document complexity, integration capabilities, and business requirements. At Flobotics, we help you navigate this process by collecting your requirements, analyzing your needs, and selecting the perfect tool. We ensure that the chosen solution aligns with your objectives and document processing needs, and we assist you in setting up the document understanding workflows. By carefully analyzing the features, resource needs, and advantages of each tool, businesses can make informed decisions that drive efficiency and productivity. Empower your organization with Document Understanding Tools to enhance document management practices, streamline operations, and unlock new opportunities for success. At Flobotics, we are committed to guiding you through this transformative journey. We provide personalized support to help you achieve your business goals effectively and efficiently. [Contact us](https://www.flobotics.io/) today to embark on a path to success with advanced Document Understanding solutions tailored to meet your unique needs. #### Like the article? Spread the word Written byKrzysztof Szwed Head of Delivery at Flobotics. [More from Krzysztof](https://www.flobotics.io/our-editorial-team#szwed) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### More Than Just Reading Text: Why Your Document Understanding Sucks Document understanding challenges, explained: why most automations underperform, what's really failing beyond the OCR tool, and how to fix it. Karl MielnickiJune 05, 2024 ](https://www.flobotics.io/blog/why-document-understanding-sucks)[ RPA ### Automated Document Processing: How to Do Away with Manual Paperwork? Automated document processing: how RPA turns insurance claims, loan statements, and patient forms into a paperwork-free workflow. Karl MielnickiFebruary 11, 2024 ](https://www.flobotics.io/blog/automated-document-processing)[ RCMRPAHealthcare ### Healthcare Document Processing: From Paperwork Pain to Automated Gain Healthcare document processing: see how automation turns intake forms, claims, and billing paperwork into a faster, error-free workflow. Bart TeodorczukJune 10, 2025 ](https://www.flobotics.io/blog/healthcare-document-processing) [All articles →](https://www.flobotics.io/blog) --- # 15 Use Cases of RPA in the Energy Sector Canonical: https://www.flobotics.io/blog/use-cases-rpa-in-energy Author: Yana Pokora Published: 2024-06-24 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/15 Use Cases of RPA in the Energy Sector [RPA](https://www.flobotics.io/blog?category=rpa) # 15 Use Cases of RPA in the Energy Sector [Yana PokoraContent Manager at Flobotics](https://www.flobotics.io/our-editorial-team#pokora) Published June 24, 2024Updated September 1, 2026 On this page - [Influence of RPA Automation in the Energy Sector](#influence-of-rpa-automation-in-the-energy-sector) - [Areas of Implementation for RPA in the Energy Sector](#areas-of-implementation-for-rpa-in-the-energy-sector) - [1. Billing and Invoicing](#1-billing-and-invoicing) - [2. Regulatory Compliance Reporting](#2-regulatory-compliance-reporting) - [3. Supplier and Vendor Management](#3-supplier-and-vendor-management) - [4. Data Migration and System Integration](#4-data-migration-and-system-integration) - [5. Meter Reading and Data Management](#5-meter-reading-and-data-management) - [6. Customer Service and Support](#6-customer-service-and-support) - [7. Energy Trading and Risk Management](#7-energy-trading-and-risk-management) - [8. Predictive Maintenance and Asset Management](#8-predictive-maintenance-and-asset-management) - [9. Workforce Management](#9-workforce-management) - [10. Accounts Payable and Receivable](#10-accounts-payable-and-receivable) - [11. Energy Consumption Analysis and Reporting](#11-energy-consumption-analysis-and-reporting) - [12. Inventory Management and Procurement](#12-inventory-management-and-procurement) - [13. Environmental Monitoring and Reporting](#13-environmental-monitoring-and-reporting) - [14. Outage Management and Restoration](#14-outage-management-and-restoration) - [15. Contract Management](#15-contract-management) - [Final Thoughts](#final-thoughts) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) As the energy sector grapples with rising demand, stringent regulations, and the need for operational efficiency, Robotic Process Automation (RPA) has emerged as a game-changer. Automating repetitive, rule-based tasks, RPA enables energy companies to streamline operations, reduce costs, and enhance productivity. Here are 15 impactful use cases of RPA in the energy sector, showcasing how this technology can transform various aspects of the industry. ## Influence of RPA Automation in the Energy Sector RPA automation has introduced advanced capabilities to handle routine tasks and intricate processes with precision and speed in the energy sector. By leveraging automation technologies, energy companies can achieve operational excellence, enhance compliance adherence, and drive innovation in their operations. RPA in the energy sector significantly reduces manual errors, accelerates data processing, and enables seamless integration with existing systems. This technology empowers energy organizations to focus on strategic initiatives, customer service improvement, and sustainable growth. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Areas of Implementation for RPA in the Energy Sector Fig. 01 · Energy 15 areas Where RPA helps in the energy sector - Billing and invoicing - Regulatory compliance reporting - Supplier and vendor management - Meter reading and data management - Data migration and system integration - Customer service and support - Energy trading and risk management - Outage management and restoration - Workforce management - Accounts payable and receivable - Environmental monitoring and reporting - Contract management - Predictive maintenance and asset management - Energy consumption analysis - Inventory management and procurement ### 1. Billing and Invoicing #### Process Automation: RPA streamlines the entire billing cycle, from generating invoices to validating charges and processing payments. #### Influence of RPA: [Billing and invoicing](https://www.flobotics.io/blog/invoice-automation) are critical functions that require high accuracy and efficiency. RPA bots can automate the extraction of consumption data, apply relevant tariffs and rates, generate detailed invoices, and distribute them electronically to customers. This process eliminates manual data entry errors, speeds up the billing cycle, and ensures that invoices are sent out promptly, improving cash flow and customer trust. #### Use Case: Energy companies can use RPA to automatically generate monthly invoices based on the latest meter readings, apply discounts or late fees as applicable, and reconcile payments received. This leads to faster invoice processing and reduces the burden on the finance team. Read how we have automated invoicing for Axpo, a renewable energy company from Switzerland. Fig. 02 · Case Operations Axpo: invoicing, reporting and provider switching GoalScale faster with no errors and full complianceSolutionAutomated invoicing, reporting and provider switching 6.18FTEs saved $186kprofit in year one 147%ROI 54,000automated actions a month 90%+average bot accuracy ### 2. Regulatory Compliance Reporting #### Process Automation: RPA automates the gathering, compiling, and submitting of data required for regulatory [compliance](https://www.flobotics.io/rcm-automation) reports. #### Influence of RPA: Energy companies must comply with various regulations regarding emissions, safety, and [financial reporting.](https://www.flobotics.io/business-process-automation) RPA can automatically collect data from multiple sources, compile it into the required formats, and ensure timely submission to regulatory authorities. This reduces the manual effort involved in compliance, minimizes the risk of non-compliance, and ensures that reports are always accurate and up-to-date. #### Use Case: An energy firm can deploy RPA bots to gather emissions data from different facilities, aggregate it into a single report, and submit it to environmental agencies. This automation ensures compliance and frees up employees to focus on more strategic tasks. ### 3. Supplier and Vendor Management #### Process Automation: RPA facilitates the management of supplier relationships by automating contract renewals, performance tracking, and payment processing. #### Influence of RPA: Managing supplier contracts and performance manually is often cumbersome and error-prone. RPA can automate the renewal of contracts based on predefined criteria, track supplier performance metrics such as delivery times and quality, and process payments. This ensures timely renewals, accurate performance tracking, and on-time payments, improving supplier relationships and operational efficiency. #### Use Case: An energy company can use RPA to monitor contract expiry dates, initiate renewal processes automatically, and ensure that suppliers meet agreed performance standards. This helps maintain smooth operations and avoids disruptions due to lapses in contract management. ### 4. Data Migration and System Integration #### Process Automation: RPA facilitates data migration between legacy systems and new platforms, ensuring smooth integration and data consistency. #### Influence of RPA: Energy companies often face the challenge of migrating large volumes of data from legacy systems when transitioning to new systems. RPA can automate data extraction from old systems, transform it as needed, and load it into the new system while ensuring data integrity. This automation reduces the risk of data loss or corruption and speeds up the migration process, allowing for a seamless transition with minimal disruption to operations. #### Use Case: During an ERP system upgrade, an energy company can use RPA to extract customer and billing data from the old system, convert it to the new system’s format, and upload it. This ensures a smooth transition and accurate data transfer. ### 5. Meter Reading and Data Management #### Process Automation: RPA automates the collection, validation, and entry of meter readings from remote sensors, smart meters, and IoT devices into central systems. #### Influence of RPA: Traditionally, manual meter reading involves sending personnel to physically record data from meters, which is time-consuming and prone to human error. [RPA](https://www.flobotics.io/contact) bots can remotely collect meter readings, validate them against historical data for anomalies, and update billing systems in real time. This automation not only reduces operational costs but also enhances data accuracy and timeliness, leading to more precise billing and improved [customer satisfaction.](https://www.flobotics.io/business-process-automation) #### Example: An energy company using RPA for meter reading can eliminate the need for manual data collection, reducing labor costs and the risk of errors associated with manual entry. This also allows for more frequent and accurate meter readings, facilitating better energy consumption monitoring and management. ### 6. Customer Service and Support #### Process Automation: [RPA enhances customer service](https://www.flobotics.io/business-process-automation) by automating responses to common inquiries, processing service requests, and resolving issues. #### Influence of RPA: [Customer service](https://www.flobotics.io/blog/rpa-customerexperience) in the energy sector often involves repetitive tasks such as handling account inquiries, processing service changes, and addressing billing questions. RPA bots can interact with customer service platforms to provide instant responses to frequently asked questions, process requests like address changes or service transfers, and resolve common issues. This improves response times, enhances customer satisfaction, and allows human agents to focus on more complex queries. #### Use Case: RPA can automate the handling of customer queries related to billing discrepancies, providing instant explanations based on the customer’s account history. This leads to faster resolution of issues and a better customer experience. ### 7. Energy Trading and Risk Management #### Process Automation: RPA automates data collection, analysis, and execution of trades in energy markets, along with risk assessment and management. #### Influence of RPA: Energy trading requires rapid data analysis and decision-making. RPA bots can collect market data from various sources, analyze it in real time, and execute trades based on predefined rules. They can also assess risks by analyzing historical data and market trends, providing traders with insights to make informed decisions. This automation enhances trading efficiency, reduces the risk of manual errors, and ensures that trading decisions are based on the latest data. #### Use Case: An energy trading firm can use RPA to automate the execution of buy or sell orders based on market conditions, ensuring that trades are executed at optimal times and prices. This improves trading performance and reduces the risk associated with human intervention. ### 8. Predictive Maintenance and Asset Management #### Process Automation: RPA automates the monitoring of equipment performance and schedules maintenance based on predictive analytics. #### Influence of RPA: Maintaining critical infrastructure like turbines, generators, and transformers is crucial in the energy sector. RPA bots can continuously monitor equipment performance data, detect anomalies that may indicate potential failures, and schedule maintenance before a breakdown occurs. This predictive approach reduces unplanned downtime, extends equipment life, and lowers maintenance costs by addressing issues before they escalate. #### Use Case: An energy company can deploy RPA to monitor the vibration levels and temperature of wind turbines. If the data indicates an unusual pattern that could signify wear or potential failure, the bot can schedule a maintenance check, preventing costly breakdowns and ensuring continuous operation. ### 9. Workforce Management #### Process Automation: RPA optimizes the scheduling, tracking, and management of field service teams, ensuring efficient deployment and task completion. #### Influence of RPA: Managing field service teams involves coordinating schedules, tracking progress, and adjusting to changes or emergencies. RPA can automate the scheduling of maintenance crews based on task priority, geographical location, and resource availability. Bots can also monitor the progress of field teams in real-time and adjust schedules dynamically in response to new information or emergencies. This ensures optimal resource use and minimizes service disruptions. #### Use Case: An energy utility can use RPA to automatically schedule service technicians for routine maintenance checks, track their movements in the field, and reroute them to handle urgent repairs. This improves service efficiency and reduces downtime. ### 10. Accounts Payable and Receivable #### Process Automation: RPA automates the processing of invoices, payment approvals, and reconciliation of accounts, streamlining financial operations. #### Influence of RPA: Managing accounts payable and receivable involves processing large volumes of invoices and payments. RPA bots can extract invoice details from emails or scanned documents, validate them against purchase orders, process payments, and update accounting systems. Similarly, they can automate the collection and reconciliation of accounts receivable, ensuring timely payments and reducing the risk of errors. This improves cash flow management and reduces the workload on finance teams. #### Use Case: An energy company can use RPA to process supplier invoices automatically, matching them against purchase orders, validating amounts, and scheduling payments. This reduces manual errors and ensures timely and accurate payments to suppliers. Process automation ROI calculator See what automating a process could save you in a few minutes. [Calculate ROI →](https://www.flobotics.io/roi-calculator) ### 11. Energy Consumption Analysis and Reporting #### Process Automation: RPA automates the collection and analysis of energy consumption data to generate detailed insights and reports. #### Influence of RPA: Energy companies need to monitor and analyze consumption data to optimize energy usage and identify opportunities for savings. RPA bots can collect consumption data from various sources, analyze it for trends and anomalies, and generate comprehensive reports. This provides valuable insights into energy usage patterns and helps make data-driven decisions to improve efficiency and reduce costs. #### Use Case: An energy company can use RPA to aggregate consumption data from multiple facilities, analyze it for peak usage times, and identify areas where energy savings can be achieved. This enables better energy management and cost reduction. ### 12. Inventory Management and Procurement #### Process Automation: RPA streamlines inventory tracking, procurement processes, and supplier coordination, ensuring efficient [supply chain management](https://www.flobotics.io/blog/warehouse-automation-process). #### Influence of RPA: [Managing inventory](https://www.flobotics.io/blog/rpa-use-cases-retail) and procurement in the energy sector involves tracking stock levels, processing orders, and coordinating with suppliers. RPA can automate the monitoring of inventory levels, trigger reorders when a stock falls below specified thresholds, and manage procurement processes. Bots can also handle supplier coordination, [ensuring timely delivery](https://www.flobotics.io/blog/rpa-logistics-supply-chain-management) of materials and preventing stockouts or overstock situations. This improves supply chain efficiency and reduces operational costs. #### Use Case: RPA can be used to monitor inventory levels of critical spare parts in a power plant, automatically reorder items when stock is low, and coordinate delivery schedules with suppliers. This ensures that the plant always has the necessary materials to maintain operations without delays. ### 13. Environmental Monitoring and Reporting #### Process Automation: RPA automates the collection and reporting of environmental impact data, such as emissions and waste management. #### Influence of RPA: Energy companies must monitor and report on their environmental impact, including emissions, waste management, and compliance with environmental regulations. RPA bots can automate the collection of environmental data from sensors and monitoring systems, compile it into reports, and ensure timely submission to regulatory authorities. This reduces manual effort, improves reporting accuracy, and ensures compliance with environmental standards. #### Use Case: An energy firm can use RPA to collect emissions data from its power plants, aggregate it into compliance reports, and submit them to environmental regulators. This automation ensures that the company meets its reporting obligations and minimizes the risk of non-compliance. ### 14. Outage Management and Restoration #### Process Automation: RPA assists in monitoring system performance, detecting outages, and automating response and restoration processes. #### Influence of RPA: Handling outages and restoring service quickly is critical in the energy sector. RPA can monitor system performance in real time, detect outages or anomalies, and initiate response protocols. Bots can also communicate with customers about the status of outages and expected restoration times, improving customer communication during disruptions. This ensures rapid response to outages and minimizes downtime, enhancing service reliability. #### Use Case: RPA can monitor the electrical grid for signs of outages or faults. If an issue is detected, the bot can alert maintenance teams, trigger backup systems, and update customers on the situation and expected restoration time. This leads to faster resolution of outages and improved customer satisfaction. ### 15. Contract Management #### Process Automation: RPA automates the creation, review, and management of contracts with customers, partners, and suppliers. #### Influence of RPA: Managing contracts in the energy sector involves generating, reviewing, and maintaining agreements with various stakeholders. RPA can automate the creation of [contract documents](https://www.flobotics.io/blog/automated-document-processing) based on predefined templates, validate them against company policies, and manage renewals or terminations. This ensures that contracts are processed efficiently and accurately, reducing the risk of errors and legal issues. #### Use Case: An energy company can use RPA to generate customer contracts for new service agreements, validate them for compliance with regulatory requirements, and manage contract renewals automatically. This streamlines contract management and ensures that all agreements are up-to-date and compliant. ## Final Thoughts [Robotic Process Automation](https://www.flobotics.io/blog/rpa-development-process) is revolutionizing the energy sector by automating a wide range of processes, from meter reading and billing to maintenance and compliance. These 15 use cases highlight how RPA can drive efficiency, reduce costs, and improve service quality across the energy industry. At [Flobotics,](https://www.flobotics.io/) we specialize in delivering tailored RPA solutions that meet the unique needs of energy companies, helping them stay ahead in a competitive market. Ready to transform your operations with RPA? Contact Flobotics today to learn more about our services and how we can help you implement [intelligent automation](https://www.flobotics.io/rcm-automation) in the energy sector. #### Like the article? Spread the word Written byYana Pokora Content Manager at Flobotics. [More from Yana](https://www.flobotics.io/our-editorial-team#pokora) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # DocPlanner | A super scalable automation for multiple EHRs Canonical: https://www.flobotics.io/blog/docplanner-automation Author: Jędrzej Szymula Published: 2024-06-24 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/DocPlanner | A super scalable automation for multiple EHRs [RPA](https://www.flobotics.io/blog?category=rpa) # DocPlanner | A super scalable automation for multiple EHRs [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published June 24, 2024Updated September 1, 2026 Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # More Than Just Reading Text: Why Your Document Understanding Sucks Canonical: https://www.flobotics.io/blog/why-document-understanding-sucks Author: Karl Mielnicki Published: 2024-06-05 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/More Than Just Reading Text: Why Your Document… CTO Notes [RPA](https://www.flobotics.io/blog?category=rpa) # More Than Just Reading Text: Why Your Document Understanding Sucks [Karl MielnickiCTO & Co-Founder of Flobotics](https://www.flobotics.io/our-editorial-team#mielnicki) Published June 05, 2024Updated September 1, 2026 On this page - [What Is Document Understanding?](#what-is-document-understanding) - [Why Document Understanding Alone Isn’t Enough](#why-document-understanding-alone-isnt-enough) - [1. Integration Challenges](#1-integration-challenges) - [2. Post-processing Complexities](#2-post-processing-complexities) - [The Solution: Automation Bots for Document Understanding](#the-solution-automation-bots-for-document-understanding) - [How To Do Document Understanding Right?](#how-to-do-document-understanding-right) - [Final Thoughts](#final-thoughts) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What Is Document Understanding? Imagine facing a mountain of paperwork - [invoices](https://www.flobotics.io/blog/invoice-automation), receipts, reports, contracts—all demanding your attention. Document Understanding acts like an adept assistant who scans through these papers, identifies the crucial information, and interprets it for practical use. This technology combines Optical Character Recognition (OCR), Artificial Intelligence, and Machine Learning to transform unstructured text into structured, actionable data. ## Why Document Understanding Alone Isn’t Enough I have often talked to clients with [Document Understanding needs](https://www.flobotics.io/blog/automated-document-processing) and have spoken to AWS, Microsoft, and Google about their software: [AWS Textract](https://aws.amazon.com/textract/), [Microsoft Azure Document Intelligence](https://azure.microsoft.com/en-us/products/ai-services/ai-document-intelligence), or [Google Cloud Document](https://www.flobotics.io/blog/uipath-vs-gcp) AI. These tools are top-tier—indeed, they are the same ones we use at Flobotics. Yet, there’s a significant caveat: these tools are not cure-alls. They excel at extracting data from documents, but consider this: Is merely extracting data from an invoice or purchase order sufficient? The real challenge is not just reading the document but effectively utilizing the extracted information: how the tools are being used and what they are being used for. Here’s where the real issues lie: ### 1. Integration Challenges Simply put, integration involves connecting the document understanding tool with existing business systems to ensure smooth data flow. The challenge is multifaceted: #### Data Input How do you consistently feed documents into these systems? This could involve scanning physical documents or importing them from digital sources, which can vary widely in format and quality, complicating the extraction process. #### System Compatibility Many organizations use a range of software solutions that may not naturally integrate well with these tools without customized connectors or APIs, which can be costly and time-consuming to develop. ### 2. Post-processing Complexities Once data is extracted, it needs to be used effectively. This stage is fraught with its own set of challenges: #### Data Validation and Correction Extracted data often requires validation or manual corrections to ensure accuracy, especially when dealing with sensitive or complex documents like contracts or detailed invoices. #### Utilization of Extracted Data Simply having data in a digital format isn’t enough. It needs to be appropriately formatted and entered into other business systems—like CRM or ERP systems—which can require additional processing or even bespoke solutions to ensure compatibility and usefulness. #### Automating Actions Based on Data The ultimate goal of extracting data is to enable automated actions, such as triggering orders, initiating billing, or updating customer records. Setting up these automated workflows requires a deep understanding of both the business processes and the technical capabilities of the systems involved. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## The Solution: Automation Bots for Document Understanding To fully harness the power of document understanding, it’s essential to integrate it with robust [automation solutions](https://www.flobotics.io/rcm-automation) - commonly referred to as “automation bots.” These bots, often powered by Robotic Process Automation (RPA), can take the output from document understanding tools and directly incorporate it into your business operations. Automation bots can bridge the gap between the document understanding output and business applications, automatically formatting and inputting data, making decisions based on the context of the extracted data, and even triggering specific actions based on information types and contents. This requires not just the technology but also the expertise of automation developers who are well-versed in both the [technical aspects](https://www.flobotics.io/blog/rpa-non-technical-developer) and the specific business contexts. These professionals ensure that automation strategies align perfectly with business objectives, enhancing efficiency and driving business value. ## How To Do Document Understanding Right? Here’s how to structure the process to transform document understanding from a simple tech demonstration into a vital business asset: #### 1. Streamline Document Input Utilize scanners or digital uploads to introduce documents into your Document Understanding tool consistently. #### 2. Automate Data Handling Ensure that the output from your Document Understanding tool is automatically integrated into your operational systems. Automation bots can facilitate this by linking with various business applications. #### 3. Close the Loop! Make sure that the data is processed and acted upon—whether that means generating reports, updating records, or conducting financial transactions. ## Final Thoughts Document Understanding is undeniably potent, but its true potential is only realized when integrated into a comprehensive, automated workflow that minimizes manual handling, reduces errors, and accelerates processes. At [Flobotics](https://www.flobotics.io/rcm-automation), we have extensive experience in [document understanding](https://www.flobotics.io/business-process-automation) and can automate the entire process to maximize utility for our clients. By establishing a streamlined, automated system, businesses can transform document management from a mundane task into a strategic advantage, freeing up time to focus on core business growth. [Reach out to us](https://www.flobotics.io/contact) to learn how we can help you optimize your document management and process automation needs! #### Like the article? Spread the word Written byKarl Mielnicki CTO & Co-Founder of Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Specific Content Limitations in UiPath [RPA Developer’s Investigation] Canonical: https://www.flobotics.io/blog/specific-content-limitations-in-uipath Author: Dominik Put Published: 2024-05-21 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Specific Content Limitations in UiPath [RPA Developer’s… [RPA](https://www.flobotics.io/blog?category=rpa) # Specific Content Limitations in UiPath [RPA Developer’s Investigation] [Dominik PutUiPath-certified RPA developer with extensive experience in automating healthcare, customer service, and HR processes. His keen interest lies in Document Understanding and OCR technologies.](https://www.flobotics.io/our-editorial-team#put) Published May 21, 2024Updated September 1, 2026 On this page - [The Great Disappearance](#the-great-disappearance) - [What Exactly Happened (And Will Happen)?](#what-exactly-happened-and-will-happen) - [Rate Limits:](#rate-limits) - [What Also Will be Removed?](#what-also-will-be-removed) - [How do I Get Specific Content for a Queue Now?](#how-do-i-get-specific-content-for-a-queue-now) - [Final Thoughts](#final-thoughts) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## The Great Disappearance Recently, a significant change in UiPath impacted many workflows, including mine—the Specific Content feature disappeared. This really cool feature allows for easier access and management of relevant data within a queue in UiPath’s Orchestrator. I initially didn’t realize this was the cause because it coincided with a widespread incident in UiPath across Europe in mid-March 2024, a communication mining outage in the EU region. At that time, I believed it affected my workflow, so the specific content from queue items was unavailable. However, a few days later, it became clear that the specific content was still missing, prompting me to investigate further. After checking the UiPath forum, I found many people faced the same issue. When attempting to retrieve Specific Content from transactions after using the “Get queue items” activity, it would return the reference, but the specific content would always return as null. An UiPath employee responded in the forum, stating they would no longer support retrieving specific content from the “Get queue items” activity. This change was announced in December. The rollout was slightly delayed but finally deployed to community tenants in mid-March. For enterprise tenants, this limitation will take effect in July 2024. ## What Exactly Happened (And Will Happen)? On December 15th, UiPath announced new rate limits, considered industry best practices for maintaining optimal performance levels, highly secure usage, and consistent service availability. The benefits include: - Ensuring a predictable system, - Improving performance, - Enhancing security, - Ensuring fair usage. ### Rate Limits: The following endpoints will be limited to 100 API requests per minute for each tenant: GET/odata/Jobs/? GET/odata/QueueItems/? Any requests exceeding this limit will receive an HTTP 429 response. These limits do not apply to adding queue items and processing jobs. Adding a queue item, removing it from a queue, setting its status, or starting and processing any number of jobs has no impact. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## What Also Will be Removed? So far, many processes have used the ‘Get Queue Items’ activity, which contains valuable information that was used later in the process. Among other data, we could fetch information from Specific Content. Currently, we receive null. Specific Content is not the only piece of data that has been deleted. The following fields will be removed from the Jobs and Queue Items GetAll endpoints: GET/odata/Jobs: - InputArguments, - OutputArguments GET/odata/QueueItems: - SpecificContent, - OutputData, - Analytics Data ## How do I Get Specific Content for a Queue Now? List(1) { QueueItem { AssignedTo=null, DeferDate=null, DueDate=null, Id=XXXXXXXXX, ItemKey=[XXXX-XXXX-XXXX-XXXX-XXXX], LastProcessingOn=”XX/XX/2024 XX:XX:XX”, Output=null, Priority=Normal, ProcessingException=null, Progress=null, QueueDefinitionId=XXXXXXXXX, QueueName=”X_Queue”, Reference=”XXXXXXXXX”, RetryNo=0, ReviewStatus=”None”, RowVersion=byte[8] { X, X, X, X, XX, XX, XX, XX }, SpecificContent=null, StartTransactionTime=[XX/XX/2024 XX:XX:XX], Status=Successful } } The GetQueueItems activity According to the changes, the SpecificContent is now always null. UiPath suggests using the GET/odata/QueueItems({key}) endpoint instead. Initially, I was confused because when I tried to send a request using the ItemKey, I received an error. It turns out that using the ID is necessary. I have added a loop to the dispatcher, which goes through all queue items, sends a GET request using the Id: “/odata/QueueItems(” + currentItem.Id.ToString() + “)”, and then deserializes the ‘JSON and reassigns the specific content to the queue item. ## Final Thoughts The change regarding the inability to receive Specific Content has impacted several processes I developed and maintained. I think such significant changes should be announced directly to the emails of Orchestrator admins. I only learned about the changes from a forum… Of course, I understand that the news section in the documentation is binding, but sometimes we miss something, and sometimes we don’t have time to browse the documentation. The current solution, which involves sending a request for each item separately, has significantly lengthened the process, which I had to explain to clients. I am not sure if UiPath Product team has thought it through. I get the reasons behind this decision, but it might have been solved in a different way. Have you encountered similar problems with your processes? What solutions have you applied? #### Like the article? Spread the word Written byDominik Put UiPath-certified RPA developer with extensive experience in automating healthcare, customer service, and HR processes. His keen interest lies in Document Understanding and OCR technologies.. [More from Dominik](https://www.flobotics.io/our-editorial-team#put) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Building Your Automation Toolkit: 100 Automation Technologies and Platforms You Should Know Canonical: https://www.flobotics.io/blog/automation-technologies Author: Karl Mielnicki Published: 2024-05-12 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Building Your Automation Toolkit: 100 Automation… CTO Notes [AI](https://www.flobotics.io/blog?category=ai)[RPA](https://www.flobotics.io/blog?category=rpa) # Building Your Automation Toolkit: 100 Automation Technologies and Platforms You Should Know [Karl MielnickiCTO & Co-Founder of Flobotics](https://www.flobotics.io/our-editorial-team#mielnicki) Published May 12, 2024Updated September 1, 2026 On this page - [Robotic Process Automation (RPA)](#robotic-process-automation-rpa) - [1. UiPath](#1-uipath) - [2. Automation Anywhere](#2-automation-anywhere) - [3. Blue Prism](#3-blue-prism) - [4. Power Automate](#4-power-automate) - [5. IBM Robotic Process Automation](#5-ibm-robotic-process-automation) - [6. ElectroNeek](#6-electroneek) - [7. Nintex](#7-nintex) - [8. Tungsten Automation (formerly Kofax)](#8-tungsten-automation-formerly-kofax) - [9. WorkFusion RPA Express](#9-workfusion-rpa-express) - [10. OpenBots](#10-openbots) - [11. Rocketbot](#11-rocketbot) - [13. akaBot](#13-akabot) - [14. AssistEdge](#14-assistedge) - [15. AutomationEdge](#15-automationedge) - [16. Resolve](#16-resolve) - [17. Datamatics TruBot](#17-datamatics-trubot) - [18. Cyclone Robotics](#18-cyclone-robotics) - [19. MuleSoft Automation](#19-mulesoft-automation) - [20. G1ant](#20-g1ant) - [21. GIBots](#21-gibots) - [22. Nividous RPA](#22-nividous-rpa) - [23. Bizagi](#23-bizagi) - [24. BotCity](#24-botcity) - [25. Automai RPA](#25-automai-rpa) - [26. Celaton inSTREAM](#26-celaton-instream) - [27. Cicero Automation](#27-cicero-automation) - [28. Cloudstorm](#28-cloudstorm) - [29. Turbotic](#29-turbotic) - [30. Fortra Automate](#30-fortra-automate) - [Business Process Automation (BPA)](#business-process-automation-bpa) - [31. Integrify](#31-integrify) - [32. Oracle Cloud Infrastructure Process Automation](#32-oracle-cloud-infrastructure-process-automation) - [33. CMW Lab](#33-cmw-lab) - [34. Pipefy](#34-pipefy) - [35. Kissflow](#35-kissflow) - [36. Appian](#36-appian) - [37. ProcessMaker](#37-processmaker) - [38. Camunda](#38-camunda) - [39. Pega](#39-pega) - [40. Process Street](#40-process-street) - [41. ActiveBatch](#41-activebatch) - [42. SAP Build Process Automation](#42-sap-build-process-automation) - [43. ARIS BPM](#43-aris-bpm) - [44. Aiwozo](#44-aiwozo) - [45. Bonitasoft](#45-bonitasoft) - [Workflow and Integration Platforms](#workflow-and-integration-platforms) - [46. Tray.io](#46-tray-io) - [47. Jenkins](#47-jenkins) - [48. Jitterbit](#48-jitterbit) - [49. Boomi](#49-boomi) - [50. Zapier](#50-zapier) - [51. Workato](#51-workato) - [52. ONEiO](#52-oneio) - [53. Celigo](#53-celigo) - [54. Make](#54-make) - [Document and Content Management Automation](#document-and-content-management-automation) - [55. Laserfiche](#55-laserfiche) - [56. OnBase](#56-onbase) - [57. Bit.ai](#57-bit-ai) - [58. Microsoft SharePoint](#58-microsoft-sharepoint) - [59. Box](#59-box) - [60. M-Files](#60-m-files) - [61. Alfresco](#61-alfresco) - [62. DocuWare](#62-docuware) - [63. OpenText](#63-opentext) - [64. Nuxeo](#64-nuxeo) - [65. OpenText Documentum](#65-opentext-documentum) - [Process Modeling and Visualization](#process-modeling-and-visualization) - [66. Lucidchart](#66-lucidchart) - [67. Microsoft Visio](#67-microsoft-visio) - [68. IBM Blueworks Live](#68-ibm-blueworks-live) - [69. Visual Paradigm](#69-visual-paradigm) - [70. Gliffy](#70-gliffy) - [Process Intelligence](#process-intelligence) - [71. Celonis](#71-celonis) - [72. BusinessOptix](#72-businessoptix) - [73. iGrafx](#73-igrafx) - [74. SAP Signavio](#74-sap-signavio) - [75. Workfellow](#75-workfellow) - [76. Fluxicon Disco](#76-fluxicon-disco) - [Collaboration and Project Management Automation](#collaboration-and-project-management-automation) - [77. Monday.com](#77-monday-com) - [78. Airtable](#78-airtable) - [79. Asana](#79-asana) - [80. ClickUp](#80-clickup) - [81. Trello](#81-trello) - [82. Jira](#82-jira) - [83. Wrike](#83-wrike) - [84. Slack](#84-slack) - [85. Microsoft Teams](#85-microsoft-teams) - [86. Basecamp](#86-basecamp) - [87. Smartsheet](#87-smartsheet) - [Niche Automation Platforms](#niche-automation-platforms) - [88. Puppet](#88-puppet) - [89. Alteryx](#89-alteryx) - [90. Worksoft](#90-worksoft) - [91. CORTEX](#91-cortex) - [92. Ansible](#92-ansible) - [93. Chef](#93-chef) - [94. IFTTT](#94-ifttt) - [95. Leapwork](#95-leapwork) - [96. Microsoft System Center Orchestrator](#96-microsoft-system-center-orchestrator) - [97. VisualCron](#97-visualcron) - [98. Verint](#98-verint) - [99. TensorFlow](#99-tensorflow) - [100. Ushur](#100-ushur) - [Build your automation tech stack with Flobotics](#build-your-automation-tech-stack-with-flobotics) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) "Automate or be automated." In today's race for efficiency, the paraphrase of GitHub co-founder Tom Preston-Werner rings truer than ever. With a flood of automation tech out there, how do you choose the best one for your business? And what if you need not one but a few to reach your productivity and revenue targets? Navigating the automation maze can be daunting, but we've done the hard work, so you don't have to. We've got 90+ curated options of automation tools with their pros, cons, features, and top use cases. Ready? ## Robotic Process Automation (RPA) ### 1. [UiPath](https://www.uipath.com/) UiPath leads Gartner's Magic Quadrant for RPA, offering comprehensive discovery, testing, analytics, and automation deployment features through an intuitive drag-and-drop interface. Its broad adoption is beneficial, warranting easy integration and a strong developer network. Industry focus: UiPath is versatile enough to serve organizations from any industry, from healthcare to retail Main features: Studio, Orchestrator, sequence capture and automation, screen scraping, AI Center, API integrations Pros: - Drag-and-drop framework supporting ease of use for non-developers and low level of entry - Intelligent automation features - Rich educational content, including UiPath Academy, community forums, and documentation - Dedicated features for all stages of automation, from discovery and development to deployment and debugging - Cloud deployment through UiPath Automation Cloud - Active community and large talent pool - A vast library of activity templates for various business purposes - Ready-made connectors for hundreds of business apps Cons: - Pricing may be steep for smaller organizations Pricing: free starter plan, pro plans starting at $420/month ([link](https://www.uipath.com/pricing)) ### 2. [Automation Anywhere](https://www.automationanywhere.com/) Like UiPath, Automation Anywhere stands out in RPA with robust automation tools for discovery, automation management, and scaling. The company is also diving deep into generative AI with features like Automation Document Automation and IQBot. Plus, it offers top-notch user support, documentation, and training content for all automation skill levels. Industry focus: Any, primarily healthcare, finance, IT, HR, operations, and manufacturing Main features: IQBot, Automation Success Platform, Document Automation, Automation 360 Pros: - A solid choice for all-purpose automation - Intelligent automation features - Focus on visual development and ease of use - Customer support Cons: - A more limited number of template processes and integrations when compared to UiPath - Complex license structure - Bugs are often reported upon new version releases Pricing: depends on the number of device licenses and automation products used ### 3. [Blue Prism](https://www.blueprism.com/) Blue Prism provides enterprise-grade RPA software with process discovery, analytics, and security features, excellent scaling capabilities, and flexible deployment options—on-premise, cloud, or hybrid. It prioritizes security and user-friendliness and excels in management and automation. Industry focus: Any, primarily healthcare, insurance, finance, public sector, energy, logistics, and hospitality Main features: Control Room, Decipher Intelligent Document Processing, UX Builder, Chorus BPM, Director Pros: - Ease of use - Enterprise focus - Strong debugging tools - Documenting and capturing features Cons: - Stability following new version releases - High cost - Weaker community engagement Pricing: subscription-based; consumption-based for additional bots ### 4. [Power Automate](https://www.microsoft.com/en/power-platform/products/power-automate) Microsoft's own RPA platform, Power Automate's main strength lies in its native integration with Windows and business suite tools like Office 365, Dynamics 365, OneDrive, SharePoint, etc. Beyond seamless automation of Microsoft apps, Power Automate offers pre-built connectors for other software, low-code automation programming, intelligent automation, and other features targeted at non-technical users. Industry focus: Any Main features: Copilot, Digital Process Automation, AI insights and recommendations, Center of Excellence, Managed Environments Pros: - Close integration with Windows and Microsoft app ecosystem - Focus on daily tasks based on well-known apps - Accessibility for non-technical users - Pre-programmed workflows - Great support and documentation Cons: - Low-code focus limits more complex automation - Troubleshooting can be difficult in the case of more complex, multi-app deployments Pricing: free trial available; attended automation $15/user, unattended automation $150/bot ([link](https://powerautomate.microsoft.com/en-us/pricing/)) ### 5. [IBM Robotic Process Automation](https://www.ibm.com/products/robotic-process-automation) IBM's RPA suite offers attended and unattended bots, API integrations, low-code tools, and process discovery features. Like other top platforms, IBM emphasizes user-friendly features like visual editing, collaboration, templates, and workflow tracking. Their standout in intelligent automation is Watsonx Orchestrate, a natural language automation hub. Industry focus: Any focus on IT, telecom, tech, insurance, finance Main features: Watsonx Orchestrate, task and process mining Pros: - Integrated with other IBM products - Focus on AI features - Support - Scaling features Cons: - Minor stability issues - Reviewers report difficulties during the setup - High entry-level difficulty - Pricing Pricing: 30-day trial available; separate options for SaaS and on-premise deployments that depend on the number of bots and environments; get the quote and assess RPA ROI ([link](https://www.ibm.com/products/robotic-process-automation/pricing)) ### 6. [ElectroNeek](https://electroneek.com/) ElectroNeek is an Intelligent Automation platform built around AI Software Bots and technologies like intelligent document processing, NLP, and generative language models. The solution prioritizes non-technical users, enabling them to build automation scripts with conversational, human-like commands and a no-code environment. Industry focus: IT, insurance, healthcare Main features: Easley AI, IntelliDocs, Automation Hub, Business Hub, Service Hub, SaaS Orchestrator, Bot Runner Pros: - AI focus - Low-/no-code approach - Easy and fast implementation - Competitive pricing Cons: - Limited features and integrations when compared to major RPA platforms - Performance issues - Support is responsive but not always available - Resources and documentation may be insufficient for more advanced purposes Pricing: free learning plan available; paid plans starting from $675 per month ([link](https://electroneek.com/pricing/)) ### 7. [Nintex](https://www.nintex.com/) Nintex is an end-to-end process automation platform created to help organizations discover, automate, and optimize their operations. It aims to simplify form automation, document creation, process mapping, and reporting while allowing developers to build custom applications. Industry focus: banking and finance, government services, energy, education, manufacturing, food & beverage Main features: Process Discovery, Process Manager, Forms Automation, DocGen Pros: - Integration with Adobe, Office 365, and Salesforce products - Solid documentation-focused functionalities like signatures and document creation Cons: - Relatively small user community - Falls behind major RPA platforms in terms of features, particularly AI Pricing: varies depending on the product ([link](https://www.nintex.com/pricing/#nwc)) ### 8. [Tungsten Automation (formerly Kofax)](https://www.tungstenautomation.com/) Tungsten Automation is a smart hub for data-heavy tasks like document handling, invoice processing, and streamlining workflows. Its AI excels in generative capabilities such as content creation and text comprehension while bridging businesses, suppliers, and finance. Industry focus: All; mainly banking and finance, healthcare, public sector, supply chain, insurance Main features: TotalAgility, e-Invoice Network, Insight, AP Essentials, Power PDF, ControlSuite Pros: - Strong invoice- and AP-oriented automation features - Focus on document automation and editing Cons: - Process discovery, scalability, recording, and other options lag behind major competitors Pricing: available upon request; demo available ### 9. [WorkFusion RPA Express](https://www.workfusion.com/) WorkFusion stands out by taking a more humane approach to automation. Instead of RPA bots, WorkFusion's customers gain access to AI Digital Workforce, a team of named, purpose-made intelligent assistants such as Casey, Customer Service Coordinator, or Isaac, Transaction Monitoring Investigator. Digital workers can be deployed jointly to enhance one another's capabilities. Users can also create customized Digital Workers to perform the predefined workflows independently or to support employees in their daily tasks. Industry focus: mostly banking and financial services Main features: Digital Workers, Intelligent Document Processing Pros: - Ease of use - Out-of-the-box automations for specific tasks - Easy customizability - Focus on the finance industry Cons: - Narrow application beyond the financial industry - Limited ML capabilities - Some users report insufficient processing speed Pricing: available upon request; demo available ### 10. [OpenBots](https://openbots.ai/) OpenBots is an RPA automation platform that streamlines document tasks: migrating documentation data into enterprise systems, creating forms, extracting specific details, and more. It uses generative AI to process structured and unstructured documents, gives users both cloud and on-premise deployment options, and solid low-code bot building, orchestration, and monitoring tools. Industry focus: any; banking and finance, healthcare, manufacturing, logistics, insurance, legal, construction, asset management Main features: Form Builder, Business Center, Studio, Process Discovery Pros: - Easy form and automated website creation - Zero-bot licensing - Scalability Cons: - Lacks advanced features offered by larger competitors - Slower support turnaround - No ML, process mining, and task mining functionalities Pricing: consumption-based, available upon request; demo available ### 11. [Rocketbot](https://www.rocketbot.com/en/) Rocketbot is a Python-based RPA platform that aims to combine the accessibility of ready-made automation components with the flexibility of custom coding. In addition to the necessary bot development, orchestration, and security functionalities, Rocketbot boasts additional features for customer experience, analysis, and text extraction. Industry focus: finance, retail, manufacturing, logistics, healthcare, insurance Main features: Xperience, Telescope, Studio, Orchestrator Pros: - Out-of-the-box automation segments - Customizable with Python coding Cons: - Limited AI functionalities - Possible performance issues when running large numbers of bots concurrently Pricing: see current plans and licensing options on the vendor’s public pricing page ([link](https://www.rocketbot.com/en/planes/)) ### 13. [akaBot](https://akabot.com) akaBot is a user-centric RPA platform that favors easy-to-use discovery, development, monitoring, and analytics tools. It excels at bot-human teamwork, with a particular focus on invoice handling. Plus, it provides auxiliary assessment, implementation, and migration services. Industry focus: accounting services across industries: banking, retail, services, manufacturing, healthcare, telecom, insurance, logistics Main features: Hub, Center, Vision, Collaboration, Studio, Insights, Agent Pros: - Excels at invoice processing - Additional RPA-related services Cons: - Limited customizability - Occasional OCR and data extraction accuracy issues Pricing: free trials are available for each plan; pricing available upon request ### 14. [AssistEdge](https://www.edgeverve.com/assistedge/) Developed by Infosys, AssistEdge is built around a Connected Enterprise where human employees, AI, and automation work together toward digital transformation. As a part of a larger automation ecosystem, AssistEdge is perfect for businesses that seek to improve their contract processing, supply chain, insurance underwriting, and customer care workflows. It's also integrated with PolarisEdge, an AI-based digital transformation support system. Industry focus: banking, supply chain, telecom, manufacturing, insurance, retail, legal Main features: Discover, Engage, XtractEdge Contract Analysis, XtractEdge Commercial Insurance, TradeEdge Network Pros: - Perfect for automating customer support and underwriting workflows - ML-driven contract analytics and insights - Aids in connecting supply chain links and automating logistics processes - Integrated with other Infosys products, including PolarisEdge Cons: - Limited integrations with third-party software - Occasionally clunky interface - Complex and time-consuming configuration Pricing: available upon request; demo available ### 15. [AutomationEdge](https://automationedge.com) Self-named hyperautomation platform, AutomationEdge is all about integrations, function-specific automation solutions, and AI. The platform seamlessly interacts with various structured and unstructured data sources and connects to many popular business apps via its Integration Platform. AutomationEdge also applies generative and cognitive AI to boost its intelligent document processing and communication between employees, clients, and partners through smart chatbots. Industry focus: healthcare, banking, insurance, manufacturing, telecom Main features: DocEdge, CogniBot, IT Process Automation, SolFlo Pros: - Combines features of no-code, low-code, and pro-code approaches - Extensive integration library - Vast pre-made, reusable automation solutions - Flexible pricing model - ML, NLP, and conversational AI functionalities Cons: - Issues when using a single account on multiple devices - The steep learning curve for more advanced features - Complex configuration Pricing: pay-as-you-go pricing; free starter plan available, paid plans available upon request ([link](https://automationedge.com/pricing/#pricing)) ### 16. [Resolve](https://resolve.io/) Resolve's approach is to focus on one thing, and one thing only: delivering purpose-built, intelligent automation solutions for IT departments for faster service delivery and troubleshooting at lower cost and effort. With Resolve, businesses can streamline all sorts of IT workflows: cloud operations, IT operations, dependency mapping, orchestration, service management, network operations, and discovery. Industry focus: IT, financial services Main features: Actions, Insights, Automation Exchange Pros: - Designed specifically for IT automation - Over 5,000 ready-made integrations and workflows - ML-enabled automation recommendations - Flexible, automation-as-a-service model Cons: - Limited use in departments other than IT - Stability issues Pricing: pricing is available upon request; demo is available ### 17. [Datamatics TruBot](https://www.datamatics.com/intelligent-automation/rpa-trubot) TruBot is a flexible RPA platform with intelligent automation capabilities that can be applied in any industry. It is built around three main activities: data extraction, automation, and analysis. As such, TruBot is an all-round solid choice for RPA automation with interesting features like Big Data pattern analytics, document management, or face recognition. Industry focus: banking and finance, real estate, insurance, healthcare, manufacturing, logistics Main features: TruCap+, TruBot, TruAI Pros: - Rich library of ready-made components - Unique features like Big Data pattern analytics, document administration, or biometric matching - Visual, low-code bot development Cons: - Some users report that the UI isn't intuitive enough - Limited customization features for advanced users - Limited discovery features Pricing: product and volume-based; demo available ### 18. [Cyclone Robotics](https://en.cyclone-robotics.com/) Cyclone Robotics, a top-tier Chinese RPA developer, offers a comprehensive automation platform with core features: discovery, bot creation, management hubs, smart document processing, low-code and no-code options, and task recording. They specialize in SMB automation and mobile-friendly automated workflow deployment, including creating, testing, and deploying selected automated workflows on mobile devices. Industry focus: logistics, finance, healthcare, governmental services, e-commerce, energy, supply chain Main features: EasyPie, RPA Mobile, AI Skill Studio, Intelligent Assistant Pros: - Mobile automation development - Dedicated automation features for small and medium businesses - Wide variety of tools for all automation purposes Cons: - Cyclone lags when it comes to more advanced automation features - Maintenance-heavy - Complex configuration Pricing: demo available, pricing available upon request ### 19. [MuleSoft Automation](https://www.mulesoft.com/) MuleSoft Automation is Salesforce's proprietary RPA platform, making it perfect for automating all workflows inside Salesforce CRM or related systems. This includes Anypoint Platform for API integrations and MuleSoft Composer, a business team-oriented app connector. MuleSoft enables no-code, code-based, and natural language bot scripting, task capture, and easy integration of AI into the existing systems. Industry focus: telecom, finance, government services, healthcare, education, insurance, manufacturing, retail Main features: Builder, Recorder, AI, Anypoint Platform, Composer Pros: - Part of the Salesforce ecosystem - Excellent support and a vast user community - Great integration functionalities - AI tools Cons: - Complex setup relying on external integrations - Compatibility issues upon new version releases - Steep learning curve Pricing: usage-based; free trial available ([link](https://www.mulesoft.com/automation-pricing)) ### 20. [G1ant](https://g1ant.com/main-english) G1ANT is a partially open-source RPA platform that allows developers to easily extend its core functionalities with self-made add-ons, commands, triggers, and more. Thanks to this flexibility, G1ANT is well-suited to the needs of enterprises of any size. Industry focus: finance, healthcare, education, insurance, manufacturing, QA, energy, logistics Main features: G1ANT.Studio, G1ANT.Orchestrator, G1ANT.ProcessMining Pros: - Open-source and code-based - Simple UI - Uses popular coding languages such as Java, Python, and C# - Customizability Cons: - Requires programming skills - Lack of educational content - Limited built-in features, integrations, and automation modules Pricing: available upon request ### 21. [GIBots](https://gibots.com/) GIBots is a no-code intelligent automation platform that applies generative AI, ML, and NLP to facilitate document digitization and all data-based decisions. The platform stands out from the competition thanks to its spatial data integration, background verification, and engineering drawing support features. Industry focus: engineering, telecom, energy, logistics, finance, healthcare, insurance Main features: GeoTwinX, Design2action, Smart Background Verification Pros: - Unique, niche features Cons: - Low maturity - Limited built-in features, integrations, and automation modules Pricing: available upon request ### 22. [Nividous RPA](https://nividous.com/) Nividous combines RPA, BPM, and AI technologies to help its customers automate structured and unstructured data operations, business processes, RCM, and more. In addition to automation development, Nividous offers digital transformation services like discovery, BPM management, consulting, and support. Industry focus: finance, healthcare, insurance, manufacturing, life science, logistics Main features: Studio, Smart Bots, Control Center, Accelerators Pros: - Ease of use - Mobile automation - Ready-made implementation accelerators Cons: - Insufficient educational resources and documentation - Limited integrations for less popular business apps Pricing: available upon request, [ROI calculator](https://nividous.com/intelligent-automation-roi-calculator/) and [free demo](https://nividous.com/request-demo/) available ### 23. [Bizagi](https://www.bizagi.com/en) Bizagi is built on three pillars: low-code enterprise applications, process automation, and AI. Experience Matrix informs developers about stakeholders, data, and interactions, allowing them to turn knowledge into automated workflows in drag-and-drop App Designer and App Studio. Before the automation goes live, users can simulate it in a safe testing environment. Industry focus: finance, healthcare, insurance, manufacturing, retail, energy, government services Main features: Ada AI Assistant, Experience Matrix, App Designer, Process Simulation Pros: - Solid library of connectors, accelerators, and visual widgets - Educational content, courses, and certifications Cons: - Limited customization - Reporting and monitoring issues Pricing: consumption-based; demo available ### 24. [BotCity](https://www.botcity.dev/) BotCity is an open-source, Python-based RPA and IDP platform that promises significantly better performance, scalability, and cost-efficiency than low-code tools without vendor lock-in. Users can leverage over 440,000 Python libraries, and as an open-source framework, BotCity is compatible with Java and JS, further expanding an already vast pool of developers who can work with the platform. Industry focus: any Main features: Studio, Frameworks, Runners, Maestro Orchestrator Pros: - Open-source - Large developer pool - More than 440,000 Python libraries are available - Flexibility Cons: - Unintuitive interface in Studio and Maestro Orchestrator - Requires coding skills Pricing: Pricing for paid plans is available upon request; a limited Community plan is available for free. ### 25. [Automai RPA](https://www.automai.com/) Automai RPA aims to host all automation efforts on one platform: performance testing, monitoring, and business processes through no-code RPA. Smart task recording, quick script editing, and integrations with all major business apps further reduce friction between developers, dev ops, and business teams. Industry focus: healthcare, finance, education, manufacturing Main features: Application Performance Monitoring, Functional Testing, Performance Testing Pros: - Code-free - Bringing all teams together into a single platform - Out-of-the-box automation solutions for popular business applications Cons: - Little focus on AI capabilities - Platform immaturity Pricing: available upon request; free trials and demos available for all core features ### 26. [Celaton inSTREAM](https://celaton.com/instream) The service is available in a SaaS model, allowing flexibility and scalability. Using Intelligent Process Automation, Celaton empowers users with efficient document processing and BPA workflows via inSTREAM. The platform features automatic data handling, no-code UI, and ongoing ML-driven improvements, all in a scalable SaaS format. Industry focus: retail, logistics, rail, travel, BPO, manufacturing Main features: Business Process Automation, Intelligent Document Processing Pros: - Excels at IDP and BPA - AI features - Self-improving - Consulting services Cons: - Limited integrations - Sparse educational resources Pricing: available upon request; demo available ### 27. [Cicero Automation](https://www.cicero-consulting.com/en/home-en/) The Austrian software consulting company Cicero offers an enterprise solutions suite, including CRM, ERP, and Document Management System (DMS). The latter allows businesses to quickly retrieve and file documentation, map and optimize document-heavy processes, and easily manage invoices, emails, and records without coding. Industry focus: banking, insurance, smart city, non-profit, sports Main features: DMS Pros: - Focus on document processing Cons: - Little in terms of AI or innovation - No educational content - Local focus - Narrow scope of services Pricing: available upon request ### 28. [Cloudstorm](https://www.cloudstorm.io/) While more modest than global RPA providers, Cloudstorm stands out from the RPA crowd in two ways. Firstly, it uses its proprietary Process Discovery tool Nika to collect feedback straight from employees, visualize processes, and validate automation business cases in a more human-centric way. Secondly, it offers end-to-end RPA services at a fixed cost rather than a usage-based price. Companies can also hire Cloudstorm developers remotely to scale up their existing RPA projects. Industry focus: transportation, tech, IT Main features: Nika, On-Demand RPA Developers Pros: - Human-centric Process discovery - Predictable pricing - RPA developer outsourcing Cons: - Lack of advanced features - Integrations with basic business apps only Pricing: Fixed monthly price starting at €500 for RPA services ([link](https://www.cloudstorm.io/end-to-end-rpa-service)) ### 29. [Turbotic](https://turbotic.com/) It is not an automation tool but rather an automation optimization platform. Turbotic is an end-to-end environment designed to help organizations scale, monitor, deploy, and manage their automation projects. Starting from consulting ideas and opportunities, Turbotic leverages AI to lead its customers through the entire automation journey, complete with implementing RPA solutions from leading vendors such as UiPath, Power Automate, Automation Anywhere, and Blue Prism. Industry focus: any Main features: LLM Orchestration, Monitoring, Access Manager Pros: - Dedicated orchestration tool - AI and LLM features - Integrated with all major RPA platforms Cons: - Minor UX issues Pricing: available upon request; free trial available ### 30. [Fortra Automate](https://www.fortra.com/product-lines/automate) Automate is the RPA component of a larger ecosystem from Fortra, a software company specializing in cybersecurity systems. The platform has fundamental automation features like API integrations, premade sequences, intelligent document processing, desktop and browser recording, and no-code bot building. One advantage that users often mention is simplicity: Fortra Automate is easy to configure, set up, and deploy. Industry focus: healthcare, banking, insurance Main features: UI Automation, API Integration Kit, Native Actions Pros: - Part of the larger Fortra suite - Educational resources and courses - Simple pricing scheme Cons: - Memory management issues - Steep learning curve Pricing: plans start from $5,000; free trial available ([link](https://www.fortra.com/product-lines/automate/pricing-details)) ## Business Process Automation (BPA) BPA platforms excel in streamlining and coordinating cross-platform processes like onboarding and sales. ### 31. [Integrify](https://www.integrify.com/) Integrify's BPA platform puts customization first: its users can build their own automations code-free, design smart forms and integrate them with company databases, create tailored self-service portals, track performance, and more. All automated processes are easy to scale and integrate with third-party apps via REST API or ready-made connectors. Industry focus: healthcare, finance, pharma, manufacturing, construction, non-profit, government services Main features: Process Builder, Form Designer, Custom Service Portal Pros: - Dedicated features for form and service portal building - Integrations - Ease of use Cons: - Limited reporting features - Users report issues with UI usability Pricing: available upon request; demos and trials available ### 32. [Oracle Cloud Infrastructure Process Automation](https://www.oracle.com/integration/process-automation/) Process Automation is a part of Oracle Cloud Infrastructure that enables developers and business users to streamline repetitive workflows through no-code automations across SaaS and on-premise apps. The platform is also compatible with user-built extensions and focuses on reusable components for faster development. Industry focus: healthcare, finance, pharma, manufacturing, government services, telecom, retail Main features: Intelligent Document Processing, Oracle Integration Pros: - Native part of Oracle Cloud Infrastructure - Rich documentation, educational content, certification, and more resources Cons: - Interface usability - Support responsiveness Pricing: usage-based; free trial available ([link](https://www.oracle.com/integration/process-automation/pricing/)) ### 33. [CMW Lab](https://www.cmwlab.com/) CMW streamlines Business Process Management with low-code tools, empowering business folks in automation and digital transformation. Visualize, model, and automate processes easily in-browser while centralizing tasks, docs, and teams in one collaborative, customizable hub. It democratizes process mapping, modeling, and automation through visualizations while allowing basic BPM functions like simple configuration, integration, and form building to be handled directly in a browser. CMW Platform is also a task management tool, centralizing all processes, documents, and people in a single, collaboration-oriented, low-code-configurable space. Industry focus: banking, logistics, education, IT Main features: Task Management, BPM, Process Automation Pros: - Low-code, visual configuration - Simple, intuitive design - Mobile support - Task management tools Cons: - Initial setup - High cost Pricing: solutions starting from $4,990; free trial available ([link](https://www.cmwlab.com/cmw-pricing/)) ### 34. [Pipefy](https://www.pipefy.com/) With a focus on simplicity and quick results, Pipefy leverages low-code automation, direct app creation, workflow templates, and AI. Its specialized HR and procurement tools, combined with flexible automation and integrations, suit any business. Industry focus: any Main features: Custom Workflows, Procure-to-Pay, HR Service Delivery Pros: - Over 300 integrations - Dedicated solutions for procurement and HR teams Cons: - Limited search and reporting functions Pricing: plans start from $20/user per month; free starter plan and demo available ([link](https://www.pipefy.com/pricing/)) ### 35. [Kissflow](https://kissflow.com/) Kissflow is the go-to no-/low-code platform for workflow automation, app development, and case management in enterprise settings. It has comprehensive features like forms, pages, boards, ample integrations, analytics, monitoring, auditing, and more. Still, despite targeting mainly enterprise users, it balances complexity and accessibility for big corporations and smaller companies alike. The platform has strong case management capabilities with bug tracking, ticketing, and helpdesk tools. Industry focus: finance, healthcare, energy, manufacturing, insurance, retail Main features: Application Development, Workflow Management, Case Management Pros: - No-code and low-code development - Case management features - Enterprise focus - Ease of use Cons: - Pricing for SMEs - Users report insufficient customer support Pricing: paid plans starting from $1500/month; free demo available ([link](https://kissflow.com/pricing/)) ### 36. [Appian](https://appian.com/) Appian delivers a full suite of enterprise-grade business process automation tools emphasizing quick builds, data cohesion, and simplicity for non-tech users. It leverages process mining, RPA, AI, APIs, and IDP in an accessible low-code framework to cater to business users. Industry focus: manufacturing, pharma, telecom, finance, governmental services, insurance Main features: Data Fabric, Case Management Studio Pros: - AI features - Mobile automation functionalities - Enterprise focus - Fast automation development Cons: - Limited customization - Price can be an issue for smaller organizations Pricing: available upon request; free trial available ### 37. [ProcessMaker](https://www.processmaker.com/) ProcessMaker is an AI-driven, low-code automation for streamlined workflows, document handling, and smart task support. With built-in next-gen AI features and natural language capabilities, the platform allows quick, code-free process mapping and translation, unstructured data processing, and efficient workflows for clear business insights. All without the need for extensive coding. Industry focus: finance, higher education, healthcare, government services, manufacturing, insurance, retail Main features: BPA, IDP, Decision Engine Pros: - Intelligent and generative AI capabilities - Decision support tools - Low-code Cons: - Performance issues on new update releases - Documentation isn't always up-to-date with new releases Pricing: available upon request; free demo available ([link](https://www.processmaker.com/products/pricing/)) ### 38. [Camunda](https://camunda.com/) Camunda excels in orchestrating processes and uniting teams, systems, and devices for digital transformation. Specifically, it links business and IT, manages human workflows, and boosts process transparency. Zeebee, their automation platform, thrives on collaboration and works with various programming languages. Industry focus: finance, insurance, media, telecom, public services Main features: Form Builder, Modeler, Tasklist, Zeebee, Optimize Pros: - Process orchestration focus - Visual programming - Features for non-automated tasks and human workflows - Vast resources and educational content - Flexible automation and decision platform Cons: - Limited discovery features - Version upgrade issues reported in the past Pricing: SaaS plans start from €99 monthly, pricing for self-managed and enterprise plans available upon request; free trial available ([link](https://camunda.com/pricing/)) ### 39. [Pega](https://www.pega.com/) Pega, a leader in enterprise management, now packs AI into its Business Process Automation platform. Beyond standard BPA features like low-code, process mining, and integrations, it delivers AI-powered real-time decisions and predictive analytics. Additionally, its generative AI streamlines process mapping, crafts personalized content, and aids customer care. Industry focus: finance, insurance, healthcare, media, telecom, public services Main features: GenAI, Process AI, Process Fabric, X-ray Vision, Agile Workbench Pros: - Gen AI features - Native integration with Pega CRM - Complete BPA suite - Dedicated tools for customer-oriented workflows Cons: - Steep learning curve - Cost, particularly for SMEs - Resource-intensive Pricing: product-based, Pega Platform plans starting from $35/user per month; free trial available ([link](https://www.pega.com/products/pricing)) ### 40. [Process Street](https://www.process.st/) Process Street is an AI-powered workflow automation platform allowing for easy automation of processes, forms, data sets, and documents. With Process Street, teams can automatically manage the stream of data into a centralized location to prevent siloes and keep all departments connected. Process AI aids users in process creation, content generation, and identifying improvements. The platform can also be managed remotely through dedicated apps for Android, iOS, Slack, and Microsoft Teams or dedicated integrations with Make, Zapier, and Power Automate. Industry focus: finance, property management, healthcare, tech Main features: Data Sets, Forms, Pages, Workflows, Process AI Pros: - Can be managed remotely from dedicated apps - AI features - Document and data processing and management functionalities Cons: - Sparse documentation - UX/UI issues Pricing: plans start from $100 per month; free trial available ([link](https://www.process.st/pricing/)) ### 41. [ActiveBatch](https://www.advsyscon.com/) ActiveBatch is a central management hub for all automation efforts across the organization. This is made possible thanks to full support for all major business applications and further expanded through its Super REST API Adapter. Another standout feature is a code-free job scheduling that allows business users to easily set complex triggers, automate workflows, and handle other orchestration tasks that normally require IT assistance. Industry focus: finance, public services, retail, telecom, healthcare Main features: Job Steps Library, Event Automation, SLA Monitor, Interfaces Pros: - Ease of use - Flexibility Cons: - The documentation and resources provided aren't detailed enough - Complex integration for less popular tools Pricing: available upon request; free demo available ([link](https://www.advsyscon.com/en-us/activebatch/pricing)) ### 42. [SAP Build Process Automation](https://www.sap.com/products/technology-platform/process-automation.html) SAP is already a leading global ERP platform, and its Build Process Automation is there to push its capabilities even further. Build Process Automation was designed with SAP automation in mind, making the tool particularly useful for big enterprises that want to streamline or scale up their SAP S/4HANA workflows or connect them with other products from the SAP Build suite. Industry focus: any, mostly enterprise-grade Main features: combines RPA, AI, and workflow automation with accessibility features like no-code or a task recorder Pros: - Native SAP integration - Connects with other SAP Build solutions - Enterprise focus - Ease of use for non-developers Cons: - Not as efficient with platforms other than SAP - Occasional performance issues Pricing: advanced user plan $180/user per year, additional users $24/user per year; attended and unattended automation $6,564 per year; free trial available ([link](https://www.sap.com/products/technology-platform/process-automation/pricing.html)) ### 43. [ARIS BPM](https://aris.com/) The ARIS stack offers BPA, process mining, automation, and risk management tools. Its mapping tool allows users to enjoy object reusability, AI-driven visualization, and detailed dashboards for informed process analysis and monitoring. Additionally, the platform accelerators enhance third-party app functionality and identify key process issues. Plus, there's a dedicated Community portal with resources, forums, and other materials for knowledge sharing and support. Industry focus: any Main features: Smart Modeling, dashboards and reports, Accelerators Pros: - ARIS Community portal - Dedicated risk and compliance tools - Purpose-made Accelerators for specific apps - AI-supported modelingakabot - Extensive process mining features Cons: - Complex pricing structure - Steep learning curve Pricing: Contributor plan: separate plans for each product; BPA from €125/user per month; Process Mining from €1200/user per month with free plan available; pricing for Automation and Risk & Compliance available upon request ([link](https://aris.com/aris-pricing/)) ### 44. [Aiwozo](https://aiwozo.com) Aiwozo is a one-stop automation solution, integrating RPA and AI to assist organizations during their digital transformation's discover, build, manage, and run stages. Its discovery tool auto-creates process maps and documentation and transfers them to the visual automation builder. AI, ML, and NLP features are used for text and image analysis and train bots to excel in new tasks. Industry focus: healthcare, finance, insurance, retail, shared services Main features: Discover, Studio, Task Capture, DocuBot, WorkZone, Insights Pros: - Automatic process map generation - AI and ML features - Complete intelligent automation package Cons: - Limited number of integrations - Lack of educational resources Pricing: plans starting from $14,000 per year; free plan available. ### 45. [Bonitasoft](https://www.bonitasoft.com/) Bonitasoft is an open-source BPM platform that relies both on visual and code-based development to allow business users and IT teams to collaborate and simplify project governance. Thanks to this flexibility, it is a perfect fit for developers, DevOps, and executives alike, assisting them in process automation, IT modernization, and orchestration. The platform's own capabilities are extended through partnerships with Amazon Web Services for cloud, DocuSign for signature management, Talend for data integration, and UiPath for RPA. Industry focus: finance, manufacturing, education, energy, telecom, healthcare, public services, retail Main features: offers end-to-end services, from PoC to rollout Pros: - Open-source - Visual and full-code development - Technological partnerships - Development services Cons: - UI can be confusing - Initial complexity Pricing: available upon request; free community edition available ([link](https://www.bonitasoft.com/pricing)) ## Workflow and Integration Platforms ### 46. [Tray.io](https://tray.io/) With APIs, many connectors, data pipeline automation, and reusable, easy-to-distribute integrations, Tray.io is a simple but potent automation and integration platform. Instead of focusing on one or two approaches to automation, It gives users the flexibility to build automations through a no-code visual interface, coding, or natural language-based chat. Industry focus: finance, tech, real estate, telecom Main features: Tray Build, Tray Code, Tray Chat, Merlin AI, Enterprise Core Pros: - Intuitive - Hundreds of app connectors - Code, visual, and chat-based automation - Customer service and resources Cons: - Occasionally fails to log and communicate errors Pricing: usage-based iPaaS pricing, plans available upon request; free trial and demo available ([link](https://tray.io/packages)) ### 47. [Jenkins](https://www.jenkins.io/) Jenkins is an open-source automation server with 1,900+ plugins, empowering developers to enhance their project tools. Powered by community contributions and donations, it is free to use, making it a viable option for small projects that are new to these kinds of solutions. Industry focus: any Main features: community, plugin Health Score Pros: - Open-source - Free to use - A multitude of plugins for projects of any scale - Empowers other tools and customizability - Built by developers for developers Cons: - Programming knowledge required - Lack of official support (other than the community and individual plugin documentation) - Security may be an issue for some plugins Pricing: doesn't apply ### 48. [Jitterbit](https://www.jitterbit.com/) Jitterbit brings automation, integration, and low-code app development to a single platform to boost the productivity of enterprise teams. Harmony, its iPaaS, allows for simple system connecting, electronic data interchange, API management, and workflow automation using a visual interface and third-party app connectors. Vinyl is a secure, scalable, compact app development tool for cloud, on-prem, and Jitterbit-hosted SaaS. Industry focus: IT Main features: API Manager, Management Console, Cloud Studio, Data Loader Pros: - Low-code, visual development - Easy integration building - Dedicated tool for Salesforce data management Cons: - Lacking tutorial and documentation Pricing: available upon request; free demo available ([link](https://www.jitterbit.com/harmony/pricing/)) ### 49. [Boomi](https://boomi.com/) Boomi supports businesses in bridging the gap between all their systems by providing thousands of prebuilt app connectors, API management, and real-time, event-based integrations aided by tips from self-learning generative AI. The platform also offers dedicated features for B2B communication and data centralization and its own no-code workflow automation engine. Industry focus: healthcare, manufacturing, finance, retail, public services, higher education Main features: API Management, Event Streams, Flow, B2B/EDI Management, Master Data Hub, Boomi AI Pros: - More than 300,000 app connectors supported - Variety of integration-centric tools - Gen AI features Cons: - Complex implementation - UI accessibility - Cost for smaller businesses Pricing: product and connector-based; free trial and demo available ([link](https://boomi.com/pricing/)) ### 50. [Zapier](https://zapier.com/) Zapier stands out as a premier automation and integration platform, blending ease of use with versatility—with no coding needed. Simple in use as it is, it adeptly orchestrates intricate workflows, bridging the gap between business tools. Zapier is also at the forefront of AI advancements in chatbots, workflow design, and virtual workforces, offering a rich suite of integrations, a user-friendly automation editor, and tailored database and app tools. Industry focus: any Main features: Zaps, Tables, Interfaces Pros: - Fit for any business size - Over 6,000 app connectors - Wide selection of pre-built workflows - Easy to customize - Popularity Cons: - Costs can add up quickly for task-intensive automation - Setting up more complicated workflows can be challenging for new users Pricing: usage-based; limited free plan and trials available ([link](https://zapier.com/pricing)) ### 51. [Workato](https://www.workato.com/) Workato is a code-free, AI-driven integration and automation platform created for business users and IT teams. With it, users can build custom applications, automation bots, and data integrations based on actions, triggers, and ready-made templates called recipes. AI-powered Copilots assist users in all these efforts, turning natural-language questions into app development, integration, and automation insights, while GEARS AI supports adoption, governance, and execution. Industry focus: any Main features: Recipes, Copilots, GEARS AI, Workflow Apps Pros: - AI features and integrations - Combines robust integration and automation features - Over 1,000 app integrations and a dedicated API management platform - Utilizes ML and internal data to self-improve - Simplicity Cons: - Complex new user onboarding - Occasional performance issues at heavier workloads Pricing: usage-based, available upon request; free trial and demo available ([link](https://www.workato.com/pricing)) ### 52. [ONEiO](https://www.oneio.cloud/) ONEiO is a cloud-based integration platform specializing in IT service management tools like ServiceNow, Jira, or Remedy, and popular business tools such as Salesforce, HubSpot, or Slack. The platform focuses on enterprise clients, promising zero downtimes no matter the scale and ready-made, no-code solutions even for complex integrations. ONEiO uses its own AI-based integration logic model to scale up and accelerate integration with multiple vendors and customers. Industry focus: IT, telecom, manufacturing Main features: ONEAi, Rule Robot Pros: - Over 1,000 integrations, including apps and service providers - Focus on IT, enterprises, and service providers - AI-powered integration engine Cons: - Limited integration lifecycle management features Pricing: separate plans for service providers and enterprises; free trial available ### 53. [Celigo](https://www.celigo.com/) Celigo is an iPaaS (Integration Platform as a service) built to give organizations full visibility into their teams, data, and tech stack and the ability to control them all from a single location. Celigo has a self-service, UX-focused interface for business users and a dedicated developer platform, including AI-assisted code writing in SQL, JavaScript, and Handlebars. Celigo's error management tool uses AI and ML, which auto-resolve errors, handle recovery, and send automated alerts. Users can connect applications through pre-built connectors or the API Management tool. Industry focus: insurance, healthcare, tech Main features: API Management, Code Assistant, AI/ML Error Management Pros: - Pre-built and universal connectors supporting over 100,000 apps - AI features for coding and error handling - Supports both no-code and pro-code approach Cons: - Error logs could be more detailed - Low customizability for pre-built connectors Pricing: usage-based; free trial and demo available ### 54. [Make](https://www.make.com/en) Two fundamental features of Make are visual workflow automation and quick idea execution. Thanks to its simple, drag-and-drop builder, workflow templates, and 1,000+ supported apps, business users can automate processes across all used systems without IT support. Scenarios can be effortlessly scheduled and monitored in real-time and then distributed and reused by team members. Make also facilitates execution history tracking, data manipulation, and error handling. Industry focus: insurance, healthcare, tech, retail Main features: Visual UI, template library Pros: - No-code automation and integration - Over 1,000 app connectors - Easy and intuitive Cons: - Lack of AI features - Limited documentation Pricing: usage- and product-based plans starting from $9/user per month; free plan available ([link](https://www.make.com/en/pricing)) ## Document and Content Management Automation Keeping all content produced and used within a company in check is crucial for operational consistency. Yet, growing businesses face escalating complexities in content management. With time, ensuring tight version control, managing access rights, and finding information become increasingly difficult. ### 55. [Laserfiche](https://www.laserfiche.com/) Laserfiche is a leading Enterprise Content Management (ECM) and Business Process Automation (BPA) platform that helps clients navigate all document-focused workflows. Its AI-based tools automatically handle data classification, transfer, extraction, and processing to manage high volumes of documentation quickly. Laserfiche's automation features revolve around document handoffs, approvals, versioning, and retrieval, while governance and security tools allow companies to maintain compliance and process visibility. Industry focus: healthcare, education, government services, finance, manufacturing, logistics Main features: Intelligent Data Capture, Document & Records Management, Solution Marketplace, Information Governance Pros: - Documentation workflow templates - Safety and compliance features - AI features for document processing - Low-code automation Cons: - Support response wait times - Differences between cloud and self-hosted versions Pricing: plans start at $50/user per month; free demo available ([link](https://www.laserfiche.com/products/pricing/)) ### 56. [OnBase](https://www.hyland.com/en/products/onbase) Part of the Hyland suite, OnBase is a content management tool for efficient document handling, from capture and classification to compliance checks and workflow automation. It boasts collaboration features like co-authoring, versioning, task management, and security, enabling comprehensive information lifecycle management and data tracking. Industry focus: insurance, healthcare, finance, public services Main features: Process automation, Retention, and records management, Automated multichannel capture Pros: - Wide variety of content-related tools - Part of the Hyland product suite - Integrations with major business systems Cons: - Difficult configuration and update processes - Support isn't always able to solve more complex issues Pricing: available upon request; free demo available ### 57. [Bit.ai](https://bit.ai/) Bit.ai is a simple but powerful knowledge and document management software that uses AI to aid users in content generation and brainstorming. Its document creator elevates the capabilities of standard writing tools with AI-assisted authoring, collaboration, custom elements, and support for rich media, code blocks, and more. This and other content can be structured, shared, connected, and centralized via Smart Wikis, embedded in websites, or turned into client portals such as knowledge centers or course platforms. Industry focus: any Main features: Smart Documents, Smart Wikis, Client Portal, AI Genius Writer, Workspaces Pros: - AI-assisted content and ideas generation - Advanced document edition - Easy wiki building and knowledge sharing - Customer portals Cons: - Insufficient training materials - Expensive when compared to other document management tools - Unintuitive interface Pricing: paid plans start from $12/user per month; free plan and demo available ([link](https://bit.ai/pricing)) ### 58. [Microsoft SharePoint](https://www.microsoft.com/en-us/microsoft-365/sharepoint/collaboration) SharePoint houses content created by other Microsoft tools, streamlining sharing and access across users and devices with fast search and mobile capabilities. It amplifies its features when integrated with Power Automate or Power Apps to create custom applications that can be accessed directly from SharePoint. Industry focus: any Main features: content management, collaboration Pros: - Native integration with other Microsoft products - Interface will seem familiar to Windows user - Easy cross-device sharing and access - Included in Microsoft 365 subscription plans Cons: - It may not fit well into more diverse software ecosystems Pricing: $5/user per month (OneDrive and Microsoft Lists included), $12.50/user per month (as a part of Microsoft 365) ([link](https://www.microsoft.com/en-us/microsoft-365/sharepoint/compare-sharepoint-plans)) ### 59. [Box](https://www.box.com/en-gb/home) Box was created to assist businesses in documentation workflows through the entire content lifecycle. It offers distinct tools for collaborative text-based and visual content creation supported by generative AI, publishing, document signing, workflow automation, migration, governance, and security. Box can easily integrate with other tools and platforms, either through API or ready-made connectors. Industry focus: finance, healthcare, media, government services, education, retail Main features: Notes, Canvas, Hubs, Sign, Relay Pros: - End-to-end content management and automation - Dedicated tools for all content-related processes - Over 1,500 integrations with third-party apps - Generative AI features for content creation and management - Security and compliance features Cons: - Mobile app performance - Relatively expensive, particularly at higher numbers of users Pricing: individual plans starting at €9/user per month; free plan available ([link](https://www.box.com/pricing/individual)) ### 60. [M-Files](https://www.m-files.com/) Designed for knowledge workers, M-Files simplifies document creation, distribution, and processing. Its AI model, Aino, automates classification, extracts vital details, and aligns content with context, freeing workers for higher-priority tasks. Hubshare builds and sustains client knowledge hubs, with extensive integrations to consolidate content from all apps. Industry focus: finance, legal, healthcare, manufacturing, energy, real estate Main features: Aino, Hubshare, Ment Pros: - Automated content templates - Security features - Generative AI capabilities Cons: - Limited customization - Unintuitive UI Pricing: available upon request; free demo available ### 61. [Alfresco](https://www.hyland.com/en/products/alfresco-platform) Developed by Hyland, Alfresco is a cloud content services platform serving as a central repository for varied content types, including video and images. Alfresco enables quick search through web-based viewing tools, extraction of key information, and integration with other content services. Industry focus: insurance, healthcare, finance, public services Main features: Governance Services Pros: - Part of the Hyland product suite - Integrations with major business systems - Content governance features Cons: - Performance issues - Complexity Pricing: available upon request; free demo available ### 62. [DocuWare](https://start.docuware.com/) DocuWare empowers businesses to facilitate documentation-oriented workflows through automated data capture, organization, import, and entry. The platform also offers vast editing, version and access control, task management, and workflow automation features that enable a seamless and secure flow of information. Industry focus: finance, healthcare, higher education, public services, manufacturing, logistics Main features: Forms, Electronic Signatures, Workflow Manager Pros: - Integrations with popular business platforms - Easy-to-build forms - Information indexing Cons: - Steep learning curve - Limited functionality of the mobile app Pricing: available upon request; free demo available ### 63. [OpenText](https://www.opentext.com/) OpenText is an AI-first enterprise information management platform powering seamless connectivity across organizations. It syncs documents, people, and processes with cloud-based tools, extending capabilities like unstructured data processing, intelligent analytics, data discovery, and self-service app development. The Aviator tool handles conversational search, translation, rich media management, and beyond. OpenText users can also leverage tools for app optimization, DevOps and developers, and connecting internal and external teams. Industry focus: automotive, banking, insurance, healthcare, energy, legal, manufacturing, public services Main features: Aviator, Content Cloud, Business Network Cloud, AI Cloud, Application Modernization, Experience Cloud Pros: - Plenty of AI features, including generative AI - Supports all content-focused operations - B2B integration tools - CX management features - Consulting services Cons: - Customer support availability Pricing: available upon request ### 64. [Nuxeo](https://www.hyland.com/en/products/nuxeo-platform) Another document-focused tool from Hyland, Nuxeo is a smart, low-code content application and workflow builder. With its help, business users can tailor custom digital asset management systems to automate and facilitate the flow of content and rich media throughout the organization. Nuxeo's cloud-based, modular architecture ensures performance and scalability, while its trainable AI aids search and data analytics. Industry focus: insurance, healthcare, finance, public services Main features: Adaptable AI, modular architecture, workflow automation Pros: - AI-supported search - Extensibility - Customization - Part of the Hyland suite Cons: - Complex setup - Debugging issues Pricing: available upon request; free demo available ### 65. [OpenText Documentum](https://www.opentext.com/products/documentum) Documentum is a cloud-native enterprise content platform from OpenText that serves as a secure single source of truth for all users within the organization. The platform encompasses a variety of tools for case management, app building, access control, and compliance to allow for agile but safe content operations. Documentum offers ready-made connectors for leading business platforms like SAP, Salesforce, Microsoft suite, and Epic EHR to extend its capabilities further. Industry focus: automotive, banking, insurance, healthcare, life sciences, energy, legal, manufacturing, public services Main features: xCP, Governance & Compliance, D2 Pros: - Part of the OpenText stack - Dedicated connectors for major business platforms - Focus on regulated industries like healthcare and life sciences - Extendability - Security and compliance features Cons: - Complex customization - Pricing can be an issue for smaller companies Pricing: available upon request ## Process Modeling and Visualization The visual approach has multiple applications, from brainstorming and collaboration to mapping network structures, automation diagrams, and org charts. What are the best diagram tools out there? ### 66. [Lucidchart](https://www.lucidchart.com/pages/) As a key component of the Lucid Visual Collaboration Suite—alongside Lucidspark and Lucidscale—Lucidchart empowers organizations to evolve ideas into visual strategies and actionable solutions. This platform allows teams to effortlessly design process diagrams through a shared visual language equipped with collaborative tools like in-editor chat, comments, and real-time co-authoring. Enhancements include integration with leading business applications, diagram templates, and a cutting-edge AI plugin. Industry focus: healthcare, finance, education, public services, consulting Main features: auto visualization, gen AI, live co-authoring Pros: - Part of the Lucid Visual Collaboration suite - Prebuilt and API app integrations - Automatically visualizes data imported from selected apps - Easy to link additional data to existing diagrams - Generative AI Cons: - Limited template customization - Price for smaller organizations Pricing: individual plans starting from $7.95/user per month; free plan available ([link](https://lucid.app/pricing/lucidchart#/pricing/chart)) ### 67. [Microsoft Visio](https://www.microsoft.com/en-us/microsoft-365/visio/flowchart-software) Visio is Microsoft's dedicated diagramming tool and part of its 365 suite. The platform's main advantage is its native integration, which allows users to translate data and content from any Microsoft app into a visual format, share it via SharePoint, collaborate on Teams, or use it as a base for Power Automate workflows. Features like Accessibility Checker or Narrator make Visio inclusive for all users. Industry focus: any Main features: Visio Viewer, Accessibility Checker Pros: - Native integration with other Microsoft 365 tools - Browsing on any device without a Visio license - Simplicity - Accessibility features Cons: - Subscription cost for smaller organizations - Limited customization Pricing: available as a part of Microsoft 365 or separately starting from $5/user per month; one-time purchase options starting from $309.99 ([link](https://www.microsoft.com/en-us/microsoft-365/visio/microsoft-visio-plans-and-pricing-compare-visio-options#x76ee93625e0141f9ad82db4313a96fbb)) ### 68. [IBM Blueworks Live](https://www.ibm.com/products/blueworkslive) Blueworks Live is an IBM cloud-based visual collaboration tool focused on easy diagram creation through drag-and-drop mapping, a wide selection of templates, and built-in tutorials. As a cloud platform, IBM Blueworks Live doesn't require installation and can be used from any device, anywhere. Collaboration is facilitated by role-, license-, and team-based access control, live co-authoring, and automated change notifications. Industry focus: any Main features: update notifications, automated export conversion Pros: - Natively integrated with other IBM tools - 200 process templates available - Flexible access control and sharing - Documents are converted automatically to the selected format upon export Cons: - Complex document exporting - Subscription cost Pricing: Contributor plan: $11.25/user per month; Editor plan: $56.2/user per month; group plans and free trial available ([link](https://www.ibm.com/products/blueworkslive/pricing)) ### 69. [Visual Paradigm](https://www.visual-paradigm.com/) Visual Paradigm is unique in that it tries to address all development-related visual design challenges. Its products include tools for visual mapping, business analysis and development, agile and scrum boards, wireframing, prototyping, generating documents, and more. With Visual Paradigm, development, DevOps, product design, analytics, project management, marketing, and many other teams can collaborate on any visual content. Industry focus: any Main features: UML Diagram, Business Model Canvas, User Story, Process Map Designer, Agile Process Tool Pros: - Versatility - Great variety of visualization tools - Templates for any purpose Cons: - No mobile compatibility - Complex integration with third-party apps Pricing: plans starting from $6/user per month; free trial and demo available ([link](https://www.visual-paradigm.com/shop/vp.jsp)) ### 70. [Gliffy](https://www.gliffy.com/) The technical diagramming tool Gliffy was developed by Perforce, an Atlassian partner. As such, it's natively integrated with Atlassian tools, which makes it the perfect visualization tool for companies that use platforms like Confluence and Jira. The Gliffy Online packs all diagram design features into a simple app available from the browser. Industry focus: any Main features: has features for UX designers, project managers, business modeling, analytics, and general monitoring Pros: - Native integration with Confluence and Jira - Ease of use - Gliffy Online Cons: - Pricing may be steep for individuals or smaller businesses Pricing: plans starting from $8/user per month for smaller teams; Gliffy for Confluence and Jira starting from $10/user per month for smaller teams; free trial and demo available ([link](https://www.visual-paradigm.com/shop/vp.jsp)) ## Process Intelligence Before any automation work gets done, businesses must first identify processes and workflows that need enhancement. This exploration can be demanding, particularly for larger or recently merged or acquired organizations. Fortunately, process intelligence tools handle all the dirty work, as a result, decision-makers receive hard data and insights ready to act upon. ### 71. [Celonis](https://www.celonis.com/) Celonis is a leader in enterprise-grade process intelligence solutions, helping businesses from all industries connect their teams, departments, and technologies for near-instant impact. For that, Celonis pulls huge volumes of business data and processes it using its proprietary AI model to create a Process Intelligence Graph—a central hub for process analytics. Celonis Studio enables custom dashboard creation, while real-time process monitoring and conversational AI Copilot ensure business users can get involved. Industry focus: any, with a focus on enterprises Main features: Process Intelligence Graph, Process Explorer, Studio, Business Miner, AI Copilot, Process Simulation Pros: - Enterprise focus - AI features - Vast selection of discovery tools - Over 300 pre-built process mining apps - Accessibility - Depth of process analytics Cons: - Mastering all features takes significant time and practice - Costs for SMEs - Customization can be complex Pricing: available upon request; free plan and demo available ([link](https://www.cmwlab.com/cmw-pricing/)) ### 72. [BusinessOptix](https://www.businessoptix.com/) BusinessOptix is a suite of business process management and intelligence tools, including process mining and mapping, content repository management, scenario modeling and simulation, and transformation planning. Using these tools, BusinessOptix customers can accurately evaluate automation potential, identify growth opportunities, manage governance, risk, and compliance, achieve operational excellence, and more. Industry focus: banking, healthcare, insurance, manufacturing, government services, tech, education, telecom, logistics Main features: Process Mining, Transformation Planning & Analysis, Target Operating Model Design Pros: - Digital twin capabilities - A complete suite of discovery tools Cons: - Unfit for smaller-case projects Pricing: available upon request; free trial and demo available ### 73. [iGrafx](https://www.igrafx.com/) iGrafx is primarily a suite of process intelligence tools that encompasses process mining, simulation, and design. It helps users automatically identify and monitor processes, run what-if analyses, map customer journeys, spot inefficiencies, and stay on top of compliance and legal requirements. It's also a workflow automation tool in its own right, enabling companies to turn the findings of its intelligence features into reality quickly. Industry focus: finance, insurance, healthcare, telecom, manufacturing Main features: Process360 Live, Process Mining, Scenario Simulation, Workflow Automation, Process Repository Pros: - Robust process intelligence functionalities - Process simulation - Intuitive - Vast educational resources and iGrafx University courses Cons: - Performance issues for bigger process maps Pricing: available upon request, demo available ### 74. [SAP Signavio](https://www.signavio.com/) SAP's Signavio is the company's robust process intelligence suite for organization-wide digital transformations. It offers AI-driven built-in tools for identifying opportunities, mapping processes and journeys, enhancing collaboration, and refining workflows at the enterprise scale, alongside full governance and monitoring capabilities. Industry focus: any, mostly enterprise-grade Main features: Process Mining, Process Insights, Process Governance, Journey Modeler, Process Collaboration Hub Pros: - smartsheetNative SAP integration - Enterprise focus - Testing and risk-assessment capabilities Cons: - Complex for new users - UI takes some time to get used to - Customization can be challenging for business users Pricing: available upon request; free trial available ([link](https://www.signavio.com/pricing/)) ### 75. [Workfellow](https://www.workfellow.ai/) Recently acquired by ProcessMaker, Workfellow is a process intelligence tool created to uncover insights to help businesses navigate their way to digital transformation, make the most out of their automation solutions, and improve current operations. Installing Workfellow doesn't require time-consuming integrations, and thanks to its proprietary Work API method, the platform is able to extract valuable process knowledge directly from employees' devices and apps. This delivers insights much faster than traditional process or task mining. Workfellow also has built-in KPI dashboards, road mapping tools, and automated work categorization. Industry focus: finance, insurance, banking, procurement Main features: Work API, Process Discovery, Process Intelligence Pros: - Plug-and-play setup - Work API discovery tool Cons: - Platform immaturity Pricing: available upon request; demo available ([link](https://www.workfellow.ai/)) ### 76. [Fluxicon Disco](https://fluxicon.com/disco/) Disco is a process mining tool that focuses on visual process mapping. Based on the discoveries and user-set level of abstraction, Disco automatically creates an animated visualization for even the most complex processes. For improved legibility, the graph is complemented by detailed statistics, robust filters, and a live search engine. Industry focus: any Main features: Cases, Filters, automated mapping and animation Pros: - Great for quick process mapping - Animation - Filtering and statistical features Cons: - Lacks collaboration features Pricing: available upon request ## Collaboration and Project Management Automation ### 77. [Monday.com](http://monday.com/) Monday.com is a customizable workplace productivity platform that enables teams to build the tools they need for all daily tasks, such as kanban boards, forms, or dashboards. Its automation features are built to eliminate repetitive tasks across the organization and its app stack through numerous integrations, no-code development, and ready-made modules. The combination of process automation and productivity tools makes Monday.com the perfect platform for everyday business use. Industry focus: intended for any business, regardless of the industry Main features: workdocs, Kanban, Gantt, Dashboards, Files Pros: - Automation integrated with a wider workplace ecosystem - Productivity and workplace management tools - Over 200 integrations with business apps, productivity tools, dev platforms, and more - Code-free automation - Educational resources Cons: - Inflexible pricing - Complex initial setup Pricing: fixed monthly price per seat; free trial available ([link](https://monday.com/pricing)) ### 78. [Airtable](https://www.airtable.com/) Airtable transforms traditional spreadsheets into a dynamic app-building platform, enabling teams to devise tailored solutions for daily tasks. Its intuitive, customizable tables double as a backend, morphing seamlessly into practical app interfaces. Integrations with key data apps position Airtable as the organizational hub for data, user, and app management. Enhanced with new AI capabilities, it leverages table data to generate insights, analyze trends, and perform advanced content functions like summarization and translation. Airtable's straightforward automation tools, compatible with visual programming or JavaScript, optimize routine workflows across connected applications. Industry focus: any Main features: Interface Designer, Tables, AI, Automations, Views Pros: - Customizability - Automatically turns databases into usable interfaces - Intuitive, user-friendly UI - Simple and effective database tool - Visual and code-based workflow automation Cons: - Initial learning curve - Price for smaller teams Pricing: plans starting from $20/user per month; free plan available ([link](https://airtable.com/pricing)) ### 79. [Asana](https://asana.com/) Thanks to its simplicity and flexibility, Asana is a leading project management tool used by companies of all sizes and industries. With mobile and desktop apps, time tracking, collaboration, reporting dashboards, and all popular kinds of task boards, Asana has all the features needed to orchestrate the work of any team. Its rule-based automation streamlines project management tasks such as assigning, data capture, notifications, content sharing, and onboarding to maintain procedural coherence and accelerate process completion, further aided by Asana's AI functionalities. Industry focus: any Main features: Tasks, Goals, Rules, Bundles, Forms, Intelligence Pros: - Complete project management suite - Hundreds of app integrations - Popularity - Workflow automation - AI features Cons: - Inflexible pricing structure - Initial complexity Pricing: plans start from $10.99/user per month; free plan available ([link](https://asana.com/pricing)) ### 80. [ClickUp](https://clickup.com/) Another all-in-one productivity platform, ClickUp, helps teams coordinate projects, collaborate, track resources and performance, and manage enterprise content. ClickUp has its own automation engine based on pre-built or custom workflows streamlining routine project management tasks. The built-in whiteboard tool is perfect for visual brainstorming or mapping. At the same time, knowledge management functionalities allow users to create company wikis, author documents, and find answers quickly using AI. Industry focus: any Main features: Tasks, ClickApps, Whiteboards, Knowledge Manager, Brain, Automations Pros: - Variety of product management tools - Knowledge management features - Visual collaboration and content functions - AI-supported search, content creation, automation, and more - Workspace customizability - Integrations Cons: - The number of features and complexity can be intimidating for new users - Performance issues with larger data volumes Pricing: plans starting from $7/user per month; free plan available ([link](https://asana.com/pricing)) ### 81. [Trello](https://trello.com/home) Trello is a task management platform from Atlassian made for cross-team collaboration, tracking progress, and visualizing projects in the clearest way possible. Trello's task boards are highly customizable and support kanban, agile, Gantt, and other methodologies, allowing users to choose the best fit for their team structure or project. With no-code, rule-based automation, Trello enables teams to relegate simple tasks like ticket creation, notifications, or sending emails to Butler, an intelligent task assistant. Integrations and Power-Up add-ons further enhance Trello and turn it into a project management tool for any business. Industry focus: any Main features: Views, Automation, Power-Ups Pros: - Easy to customize - Native support for Atlassian tools - Rule-based automation - A multitude of available integrations, templates, and add-ons Cons: - Project boards can get cluttered as the number of tasks grows Pricing: plans starting from $5/user per month; free plan available ([link](https://trello.com/pricing)) ### 82. [Jira](https://www.atlassian.com/software/jira) Jira is a household name in the software development world, unlike other industry-agnostic project management tools. Dedicated to DevOps, IT, and programmer teams, Jira is built specifically for agile and sprint-based project management, enabling software teams to track progress across the organization easily. Jira uses a drag-and-drop engine and templates for easy ticketing, reporting, task handovers, and team syncing automation. Industry focus: any; mostly for IT, developers, and DevOps teams Main features: Timelines, Automation, Reporting Pros: - Native support for Atlassian tools - Over 3,000 integrations - Popularity, especially in the software development community - Designed for agile - Intuitive automation features Cons: - Initial complexity - Cost for mid-sized teams that outsize the 10-seat free plan Pricing: plans start from $8.15/user per month; free plan available ([link](https://www.atlassian.com/software/jira/pricing)) ### 83. [Wrike](https://www.wrike.com/vak/) Wrike aims to bring all workflows, teams, and departments to a single source of truth. To make this happen, it gives its users access to multiple project visualization tools, cross-project visibility and workstream management, mobile and desktop apps, and real-time collaboration features. Wrike's automation tool aids users through handling repetitive tasks like reminders or status changes, improving itself along the way thanks to built-in AI capabilities. Industry focus: any Main features: Dashboards, Automation, Cross-Tagging, Proofing, Project Resource Planning Pros: - More than 400 integrations - AI features - Visibility and task management across teams and projects - Ease of use Cons: - Steep learning curve Pricing: plans start from $9.80/user per month; free plan and demo available ([link](https://www.wrike.com/price/)) ### 84. [Slack](https://slack.com/) Slack is perhaps the most popular team messaging platform, allowing teams to communicate via chat, video, audio, or short recording called Clips. Everyday statuses, communications, and updates can be automated using straightforward, no-code programming and out-of-the-box integrations. You can also use Slack as a knowledge-sharing tool for content like onboarding, summaries, product briefs, and more. Industry focus: any Main features: Channels, Clips, Canvas, Workflow Builder Pros: - Popularity - Enables communication over preferred channels on a single platform - Knowledge management tools - Automation features - Simplicity Cons: - Overwhelming notification management Pricing: plans start from $7.25/user per month; free plan available ([link](https://slack.com/pricing)) ### 85. [Microsoft Teams](https://www.microsoft.com/en/microsoft-teams/log-in) Microsoft Teams is an enterprise-grade central link between all other Microsoft apps and their users, enabling communication and collaboration in documents, spreadsheets, and more. It's also one of the leading video conferencing platforms, with features for calls, chats, break rooms, cloud phones, and captions. Teams also enable users to integrate, automate, and create low-code business apps to meet their unique needs. As an example, schools and universities can use its extensive virtual whiteboard, accessibility, and learning enhancement features to make learning more engaging and fulfilling digitally, also for learners with special educational needs. Industry focus: education, healthcare, retail, manufacturing Main features: Teams Rooms, Phone, Contact Center Pros: - Native integration with Microsoft 365 products - Familiarity - Enterprise focus - Over 700 app integrations Cons: - May be confusing for non-Teams users - Steep learning curve Pricing: plans start from $4.00/user per month ([link](https://www.microsoft.com/en/microsoft-teams/compare-microsoft-teams-business-options?activetab=pivot%3Aprimaryr1&market=af)) ### 86. [Basecamp](https://basecamp.com/) Basecamp combines communication, collaboration, and project management functionalities under one roof with the goal of keeping things simple and accessible. It has a centralized space for all documents and files, to-do lists, and detailed and top-down project monitoring tools, all presented in a clean, no-frills manner. Despite the visual minimalism, Basecamp lets you get into granular analytics with detailed reporting and analytics. Industry focus: any Main features: Mission Control, Lineup, Hill Charts, Doors, To-Dos Pros: - Simplicity - Notification management options - Multiple visualization tools - Detailed performance and progress analytics Cons: - Limited integrations when compared to competitors - Managing multiple projects at once can get challenging Pricing: plans start from $15.00/user per month; free demo available ([link](https://basecamp.com/pricing)) ### 87. Smartsheet Focusing mainly on enterprise customers, Smartsheet is a single platform for workflow automation, task management, and team collaboration. Smartsheet supports a multitude of project views, including an intuitive card view, and visibility with tools such as passive activity monitoring and dependency-based Gantt charts. The platform prioritizes security, warranted by in-depth admin features and data protection solutions. All repetitive task management and reporting activities can be automated, freeing up resources for more critical activities. Industry focus: finance, government services, construction, healthcare, life sciences, higher education, non-profit Main features: Admin Center, Event Reporting, Critical path, Activity Log, Resource Management, WorkApps Pros: - Enterprise focus - All-purpose productivity platform - Project and event tracking tools - Document creation, co-authoring, and e-signatures - Admin and data security features - API and connector-based integrations Cons: - Complex setup - Steep learning curve - The mobile version is clunky in comparison to the desktop app Pricing: plans starting from $7/user per month; free plan and demo available ## Niche Automation Platforms These platforms don't fit neatly into standard classifications but are essential for their targeted, niche applications in certain industries or for particular technological needs. ### 88. [Puppet](https://www.puppet.com/) Built for IT infrastructure automation, Puppet allows companies to deploy, manage, and scale their on-premise, cloud, or hybrid infrastructure faster and safer. Real-time monitoring and safety-oriented extensions help IT teams maintain the necessary security and compliance standards while its orchestration, code reusability, and community-built modules reduce time-to-production. Industry focus: IT Main features: Bolt, Forge, Automated Patch Management, Comply, Continuous Delivery Pros: - IT process focus - Safety features - Code reusability tools - An active community of developer contributors Cons: - Initial setup Pricing: Pricing for Puppet Enterprise available upon request; free, open-source edition and demo available ([link](https://www.puppet.com/pricing)) ### 89. [Alteryx](https://www.alteryx.com/) Alteryx stands out from other automation vendors by operating in its niche: data analytics. It's a low-code, self-service platform that allows organizations to streamline the automation, sharing, reusing, and scaling of data-oriented workflows and analytic apps powered by its proprietary AI model, AiDIN. The model stands at the core of all Alteryx tools, generating new insights, supporting automation mapping and design, and processing unstructured data. Industry focus: finance, healthcare, retail, higher education, energy, manufacturing, public sector Main features: AiDIN, Intelligence Suite, Auto Insights, Location Intelligence, Designer Cloud, Connect Pros: - Data analytics focus - Powerful AI features - Great for identifying insights, patterns, and exceptions - Ease of use Cons: - High cost - Limited Python and R implementation capabilities Pricing: product-based, plans starting from $4950/user per year; free trial available. ### 90. [Worksoft](https://www.worksoft.com/) Worksoft, a self-titled Connective Automation Platform, prioritizes bringing disparate systems and all stages of automation—discovery, testing, and deployment—to a single platform. Test automation is one of Worksoft's key differentiators, giving its users the tools to ramp up bot development, reduce time to rollout, and mitigate risks. Worksoft also offers testing solutions customized for specific platforms, mobile devices, cloud, and APIs. Industry focus: healthcare, manufacturing, tech, automotive, energy Main features: Process Intelligence, Certify® Automated Testing, Continuous Testing Manager, Impact Analysis Pros: - A wide array of test automation tools - Holistic approach - Educational content and courses Cons: - Customer support could be faster - Limited test report customizability Pricing: available upon request; demos and trials available ### 91. [CORTEX](https://www.wearecortex.com/) CORTEX is an intelligent automation platform operating solely in the communications service provider (CSP) niche that offers solutions for mature enterprises and providers wanting to scale up their automation efforts. CORTEX focuses on maximizing automation ROI, time to value, and sustainability. It offers a complete suite of automation solutions, including drag-and-drop automation building, premade components, exception handling, integrations, and more. Industry focus: telecom Main features: Growth Platform, Enterprise Platform Pros: - In-depth CSP automation expertise - Scalability - Flexible pricing Cons: - Unfit for businesses from other sectors Pricing: reusable automation blocks starting from $25 per year ([link](https://www.wearecortex.com/pricing/)) ### 92. [Ansible](https://www.ansible.com/) Red Hat Ansible, a Python-based open-source automation tool, streamlines IT operations across three distinct platforms. The Community and AWX editions, free and unsupported, are ideal for small projects and individual experimentation. For larger organizational needs, the subscription-based Ansible Automation Platform combines over 20 community projects backed by Red Hat for enhanced security, support, and analytics. This premium platform boasts AI-enhanced coding, advanced automation plugins, and event-driven capabilities. Industry focus: IT Main features: Lightspeed, Content Collections, Event-Driven, Playbook Pros: - Open-source - Free to use (Community Ansible) - Dedicated for IT processes - Flexibility and customization Cons: - Coding knowledge required - Provided documentation isn't sufficient for all features Pricing: Community Ansible is free to use; Red Hat Ansible Automation Platform is subscription-based with plans starting from $384/year and varying between products; free trial available ([link](https://www.redhat.com/en/store)) ### 93. [Chef](https://www.chef.io/products/chef-automate) Chef enables organizations to configure, deploy, and manage their IT tech stack effortlessly while warranting security and compliance. Its automation tools encompass app delivery, DevOps, auditing, and cross-environment packaging and orchestration. Chef Workstation is a single, easy-to-install package that allows organizations to start with policy-based configuration, testing, and deployment automation that are then applied remotely through Chef Infra. Industry focus: IT Main features: App Delivery, Automate, Edge Management, Habitat, Infra, Workstation Pros: - IT process focus - Safety and compliance features - Dedicated solution for edge management - Open-source version available for free - Large and active user community Cons: - Unintuitive interface - Steep learning curve - Insufficient documentation Pricing: available upon request; can also be purchased from AWS and Azure marketplaces; free trial available ([link](https://www.chef.io/how-to-buy)) ### 94. [IFTTT](https://ifttt.com/) IFTTT (aka If This Then That) is a low-code automation and connectivity platform targeted at personal users and businesses that seek to accelerate simple, day-to-day tasks. It helps its users schedule and cross-publish social media posts, sync calendars, and improve overall personal productivity. Its use cases include lead flow, notification, company SM, and customer care management. IFTTT even integrates smart home solutions with other software, allowing for advanced device programming and interconnection. Industry focus: any, including personal use Main features: Applets Pros: - Mobile apps for Android and iOS - AI content generation and SM assistants - Specific, everyday use-oriented automation - Unique niche - Hundreds of integrations with business software, personal and lifestyle apps, and SM channels - Simplicity Cons: - Unsuitable for more complex business use cases Pricing: paid plans starting from $2.92/month with free trials available; limited free plan available ([link](https://ifttt.com/plans)) ### 95. [Leapwork](https://www.leapwork.com/) Leapwork's test automation platform is unique in two ways. Firstly, it uses AI to record steps and data and turn them into workflows. Second, it's based on a universal visual language and intelligent building blocks, giving all users a graphic overview of the automated process and enabling easy development, debugging, and test management. These two standout features are built on solid foundations of orchestration, integration, reporting, and test scheduling tools. Industry focus: IT Main features: Application Monitoring, Continuous Testing, Functional UI Testing, Regression Testing, DevOps Pros: - Made specifically for all sorts of automation testing - Supports code-free, visual testing management - AI features Cons: - Mobile testing capabilities - Slow remote test execution Pricing: usage-based, available upon request; free trial available ### 96. [Microsoft System Center Orchestrator](https://learn.microsoft.com/en-us/system-center/orchestrator/learn-about-orchestrator?view=sc-orch-2022) System Center Orchestrator is a data center automation tool from Microsoft that allows for connecting disparate tasks into coherent processes using a visual interface called Runbook Designer. Doing so enables hardware- and platform-agnostic automation, enhances efficiency, and brings together systems from various vendors without programming. Industry focus: any Main features: Runbook Designer Pros: - Visual UI - No-code Cons: - Resource-intensive Pricing: part of Microsoft System Center – licenses starting at $1,323 ([link](https://www.microsoft.com/en-us/system-center/pricing)) ### 97. [VisualCron](https://www.visualcron.com/) VisualCron combines automation, scheduling, and integration features designed specifically for Windows. The platform utilizes technologies such as RPA and OCR, multiple transfer protocols (FTP and FTPS, SFTP, SCP), cloud services, and integrations, enabling various applications. Some of its use cases include the automation of SQL, Microsoft apps, encryption, PowerShell, virtual machines, Managed File Transfer, and Extract Transform Load. Industry focus: any Main features: Task Scheduler, BPA Pros: - Dedicated to Windows and Microsoft tools - A variety of app-specific, pre-built tasks Cons: - Clunky interface - Steep learning curve Pricing: available upon request; free trial and demo available ### 98. [Verint](https://www.verint.com/) Verint is another purpose-specific platform, this time focused on CX automation. To bring down costs while boosting customer care efficiency, Verint facilitates knowledge base management, CX QA and analytics, self-service, and more. Its proprietary Da Vinci AI powers all purpose-made Verint bots, trained on data collected in Engagement Data Hub, and weaved into CX workflows to aid human employees. Industry focus: banking, insurance, public sector, retail, telecom Main features: Da Vinci AI, Engagement Data Hub Pros: - Built specifically for CX automation - Open CX ecosystem that can be easily integrated with third-party software - AI and Self-learning capabilities Cons: - Complex setup - High licensing fees Pricing: available upon request, demo available ### 99. [TensorFlow](https://www.tensorflow.org/) TensorFlow is an open-source library for machine learning and deep learning. Based on Python, it trains and builds ML models for purposes such as speech and image recognition, NLP, data classification and understanding, and more. Industry focus: any Main features: extensions, developer tools Pros: - ML focus - Free to use - Uses Python - Support for other languages through extensions - Active community Cons: - Resource intensive Pricing: free ### 100. [Ushur](https://ushur.com/) Ushur is a specialized platform focused on automating customer experience workflows. AI is at the core of Ushur's offerings, managing everything from data extraction and document processing to intent detection, request classification, and routing. The platform features tailored mobile and desktop self-service solutions, an advanced email automation system, and AI-driven chatbots. All interaction data from these channels seamlessly integrates with other CX systems and databases. Industry focus: healthcare, insurance, banking Main features: AI Studio, Conversational Apps, Invisible App, Invisible Portal, SmartMail, Intelligent Document Automation Pros: - Customer experience focus - AI features - Omnichannel CX automation - Automates customer and interaction data collection Cons: - Reporting needs improvement - More complex workflows are difficult to set up and maintain Pricing: available upon request; free trial and demo available ## Build your automation tech stack with Flobotics With an overview of automation platforms and supporting software complete, the time has come to act and create your automation toolkit. Which tools do you find the most essential to optimize your work? Would you like to explore some of them further? If any of the above automation and work optimization platforms piqued your interest, here's the next step: [Consult the selection with our automation experts](https://www.flobotics.io/contact), who will help you expand your stack or build it from the ground up. Get in touch and start today! At Flobotics we specialize in automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byKarl Mielnicki CTO & Co-Founder of Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### Automation’s for Everyone: 100 Real-World RPA Use Cases Across Industries | 2026 RPA use cases across industries: see 100 real-world examples of process automation in action, from healthcare to manufacturing. Michał RejmanFebruary 23, 2024 ](https://www.flobotics.io/blog/rpa-use-cases-across-industries)[ RPA ### Top Automation Trends in 2026 Automation trends for 2026: eight shifts in RPA, AI, and workflow automation that will shape how businesses operate this year. Krzysztof SzwedFebruary 03, 2025 ](https://www.flobotics.io/blog/top-automation-trends)[ RPA ### eCommerce Automation: How Is RPA Disrupting Online Retail? Ecommerce automation: how RPA helps online retailers tackle order processing, inventory, and customer service challenges at scale. Filip NasiadkoNovember 07, 2022 ](https://www.flobotics.io/blog/ecommerce-automation) [All articles →](https://www.flobotics.io/blog) --- # Pay on Time, Every Time: Streamlining Invoice Workflows with Invoice Automation Canonical: https://www.flobotics.io/blog/invoice-automation Author: Karl Mielnicki Published: 2024-04-04 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Pay on Time, Every Time: Streamlining Invoice Workflows… CTO Notes [AI](https://www.flobotics.io/blog?category=ai)[RPA](https://www.flobotics.io/blog?category=rpa) # Pay on Time, Every Time: Streamlining Invoice Workflows with Invoice Automation [Karl MielnickiCTO & Co-Founder of Flobotics](https://www.flobotics.io/our-editorial-team#mielnicki) Published April 04, 2024Updated September 1, 2026 On this page - [What’s Invoice Automation?](#whats-invoice-automation) - [Why Is Automated Invoice Automation Necessary?](#why-is-automated-invoice-automation-necessary) - [Manual Data Entry](#manual-data-entry) - [High Error Rate](#high-error-rate) - [Lack of Visibility](#lack-of-visibility) - [Security and Compliance Issues](#security-and-compliance-issues) - [Slow Cycle Time](#slow-cycle-time) - [Cash Flow Disruptions](#cash-flow-disruptions) - [How Does Invoice Automation Work?](#how-does-invoice-automation-work) - [System Integration](#system-integration) - [Data Extraction](#data-extraction) - [Validation and Matching](#validation-and-matching) - [Approval and Exception Handling](#approval-and-exception-handling) - [Reporting and Analytics](#reporting-and-analytics) - [What Are the Benefits of Automated Invoice Processing?](#what-are-the-benefits-of-automated-invoice-processing) - [Invoice Automation in Practice: Automated Invoice Processing Case Studies](#invoice-automation-in-practice-automated-invoice-processing-case-studies) - [Canon: 6,000 hours saved through invoice automation](#canon-6000-hours-saved-through-invoice-automation) - [Central England Co-operative: 60% faster invoice reconciliation](#central-england-co-operative-60-faster-invoice-reconciliation) - [Capita Group: reducing invoice processing costs by 70%](#capita-group-reducing-invoice-processing-costs-by-70) - [Invoice Automation Trends: a Peek into the Future](#invoice-automation-trends-a-peek-into-the-future) - [Automate Your Invoice Workflows with Flobotics](#automate-your-invoice-workflows-with-flobotics) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) In a [2022 survey by PYMNTS.com](https://www.pymnts.com/accounts-payable/2022/9-in-10-cfos-focused-payments-automation-transformation/), 9 out of 10 CFOs reported that their companies had already started their digital transformation or planned to do so. However, with just 52% of [invoices received electronically](https://www.skynova.com/blog/invoicing-statistics) and the rest in paper format, finance businesses still have a long way to go. A crucial way to start is digitizing the mainstay of financial operations: invoice processing. Existing automation technologies—such as RPA (Robotic Process Automation), IA (Intelligent Automation), and OCR (Optical Character Recognition)—are all well-suited for handling many AP tasks, including invoice processing. As [Generative AI ](https://www.flobotics.io/blog/generative-ai-finance)and other solutions become more sophisticated, invoice automation capabilities will only improve. Keen to find out more about the ins and outs of invoice automation and what the future holds for invoice processing? Read on. ## What’s Invoice Automation? Let’s start with the essentials: what’s invoice automation? Put simply, it refers to handing over steps of invoice processing workflows to software. Invoice automation systems are integrated with other business platforms, such as ERP, which instantly extract and update AP information, supporting the transition to digitized accounting. Similar [finance automation](https://www.flobotics.io/business-process-automation) technologies are commonly applied in [payroll](https://www.flobotics.io/blog/payroll-process-rpa), [banking](https://www.flobotics.io/blog/rpa-for-finance), and [accounting](https://www.flobotics.io/blog/automating-accounting-processes). Invoice automation aims to reduce—and ideally replace—the manual effort, leading to lower costs, higher efficiency, improved accuracy, and less employee burnout. Sorry, your browser doesn't support embedded videos. Watch our RPA bot automatically processing an invoice submitted via ClickUp form. ## Why Is Automated Invoice Automation Necessary? Do traditional invoice processing methods work? Most of the time, they do. Do they work accurately and quickly? Most of the time, they don’t. Here are the most common challenges accounting departments face when dealing with invoices manually: ### Manual Data Entry Invoice IDs, addresses, dates, billing, and vendor details must all be extracted from the invoice and entered into your accounting system. This tedious chore requires hours of daily manual effort and prevents AP specialists from focusing on higher-value tasks. ### High Error Rate Time inefficiencies are only half of the story; worst of all, manual invoice processing inevitably leads to human error. These mistakes include duplicate invoices, misplacements, inconsistencies, incorrect payments, etc. ### Lack of Visibility Paper invoices may quickly pile up, and the more there are, the tougher it gets to screen accounting processes for errors and discrepancies continuously. Once invoices are processed, they end up scanned or, in the worst-case scenario, physically stored in files or folders, which makes them difficult to retrieve. ### Security and Compliance Issues Handling sensitive transactional data manually puts an organization at risk. Manual invoice processing leaves gaps that bad actors may seek to exploit, e.g., by submitting fraudulent bills. Manual auditing may also prove insufficient, potentially leading to non-compliance and severe penalties. ### Slow Cycle Time Manual approvals, handovers, version control, and managing past payments all contribute to slower invoice processing workflows. This forces businesses into a vicious cycle of endlessly recruiting additional accountants as the company grows. ### Cash Flow Disruptions All challenges listed above affect the cash flow in and out of your organization. Income bottlenecks can have profound consequences, especially for SMEs or businesses without emergency reserves. ## How Does Invoice Automation Work? Invoice automation processes are based on traditional AP workflows. After the accounting department receives an invoice, finance specialists match it to the corresponding purchase order. Then, they enter transaction details into the system and submit the invoice for approval. Automated invoice processing software can assist accountants at all steps of this process. Here are the key components of the automated invoice workflow. Fig. 01 · Invoices 6 steps Automated invoice processing, step by step - 01Extract data from paper or electronic invoices - 02Enter it into accounting systems - 03Validate and match - 04Approve and handle exceptions - 05Pay - 06Report ### System Integration Invoice automation solutions are designed to connect seamlessly with key accounting systems such as ERP. This helps keep all transactional data up to date across the organization and expedites approval and payment processes. The invoice automation platform also integrates with your business communication channels like email, chat, or task management platforms. ### Data Extraction Invoices can come in paper and electronic formats and vary in fields or layout. Invoice automation systems use OCR or ML (machine learning) to capture transaction information such as vendor details, invoice numbers, dates, etc. Based on that information, the software converts all invoices into a standardized format for further processing. ### Validation and Matching The invoice automation system matches the extracted invoice data to POs and bills. If the software detects errors or exceptions, it automatically flags them and submits them for manual review. Since automation significantly reduces the validation process, it enables organizations to implement more efficient—but also more time-consuming—verification measures such as three-way matching. ### Approval and Exception Handling Invoices that require approval or include exceptions are routed to predefined reviewers. Users define the approval workflow based on the supplier, invoice amount, general ledger code, or other criteria. The invoice is tracked along its way to prevent it from getting lost or sent to the wrong person. Reviewers receive automated notifications about incoming deadlines to ensure timely approval. An invoice can be moved to the next stage only once all discrepancies are corrected. ### Reporting and Analytics Some invoice automation platforms have built-in analytics features that monitor invoice processing workflows. Based on the analysis, the system generates insights into process performance, helping organizations identify issues and potential improvements. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## What Are the Benefits of Automated Invoice Processing? A recent study by Forrester revealed that[ invoice automation can speed up invoice processing by 80%](https://www.forrester.com/blogs/understand-todays-ar-invoice-automation-landscape/) compared to the manual workflow. Increased productivity is just one of the benefits of automated invoicing; here are several more that will convince even the staunchest non-believers: Fig. 02 · Invoices 10 advantages Advantages of invoice automation - 01Central recordsPaperless invoices live in one database, easy to manage. - 02Consistent formatInvoices from many suppliers are turned into one readable format. - 03Lower costsNo more postage and printing costs. - 04Faster approvalsMost invoices are checked automatically; people handle only exceptions. - 05Easier scalingHandle sudden growth in transactions without hiring. - 06More transparencyEvery invoice that goes through AP can be traced. - 07Time savedAccountants spend more time on cash flow, budgets and forecasts. - 08Fewer errorsNo mistakes from fatigue or piles of paperwork. - 09Better supplier relationshipsFaster payment, and early-payment discounts. - 10Fewer duplicatesDuplicate invoices and payments are caught. ## Invoice Automation in Practice: Automated Invoice Processing Case Studies To inspire you, we’ve collected some stories of companies that elevated their accounting processes to new heights by implementing invoice automation. ### Canon: 6,000 hours saved through invoice automation Even an international giant like [Canon ](https://www.uipath.com/resources/automation-case-studies/canon-leverages-ai-for-document-processing/)can face AP bottlenecks. Its USA branch was overwhelmed with paperwork, and its current automation invoice automation wasn’t accurate enough to reliably replace human reviewers. Switching to UiPath’s AI-based invoice automation service, Canon radically reduced the human intervention rate, delegating 90% of invoice processing effort to the software. 4,500 invoices are handled automatically each month, saving Canon 6,000 hours of employee time each year. ### Central England Co-operative: 60% faster invoice reconciliation Serving various services to its 250,000 members across 400 locations, [Central England Co-operative Society](https://www.blueprism.com/resources/case-studies/central-england-co-operative-reconciles-supplier-invoices-rpa/) is one of the largest independent retailers in the UK. The company wanted to introduce a more regular invoice reconciliation schedule, increasing the frequency from once or twice a year to once every month. Invoice automation was the only way to achieve that rate without compromising accuracy. The Society opted for Blue Prism’s document processing solution to handle the reconciliation of about 1,300 invoices from a broad range of suppliers monthly. If necessary, the process can run daily, with the same accuracy and friction of human effort. ### Capita Group: reducing invoice processing costs by 70% [Capita Group,](https://www.tungstenautomation.com/-/media/Files/E-books/EN/eb_5-case-studies-to-inspire-your-ap-automation-strategy_en.pdf) the UK’s primary business process outsourcing company, struggled with inefficient and error-prone manual data entry workflows and insufficient visibility. These challenges elevated the processing cost of a single invoice to £8, which is much more than the generally accepted standard. By implementing Kofax’s invoice automation system, Capita streamlined data extraction and entry into its SAP, invoice verification and approval, and overall traceability. Capita now uses the system to process more than 400,000 invoices annually at just over £2 per invoice cost. ## Invoice Automation Trends: a Peek into the Future While invoice automation already saves accounting departments thousands of hours, its capabilities will only improve as it integrates emerging technologies. What are they? Fig. 03 · Invoices 7 trends Future trends in invoice automation - Better supplier portals - Mobile invoice approval - Blockchain - Predictive analytics - Integration with AI and ML - End-to-end accounting automation - NLP-based invoice classification #### Integration with AI and ML AI has been the defining technology of the past couple of years, and it will impact AP processes just as much as any other business activity. From the invoice processing perspective, integrating AI will mean higher accuracy, better extraction regardless of invoice format, and truly intelligent, self-learning fraud detection systems. #### End-to-end Accounting Automation As more and more organizations adopt invoice automation, they begin to realize that this is just a stepping stone to overall financial process optimization. In the near future, we can expect automation service providers to offer end-to-end AP/AR solutions that will encompass invoicing, AP collections, and payment processing. #### Adoption of Blockchain Blockchain-based transaction ledgers offer several benefits: they are safe, tamper-proof, and easily track any changes made to the document. As such, it can potentially address transparency issues, fraud attempts, unauthorized access, and other security concerns. #### Predictive Analytics From budgeting and managing cash flow to avoiding late payment penalties, one cannot understate the importance of accurate payment timeline predictions. By applying ML and large volumes of historical data, predictive analytics will be able to forecast invoice payment times and enhance financial planning reliably. #### Mobile Invoice Approval Accounting teams know it all too well: an urgent invoice is sent for approval to a key manager who’s temporarily unavailable. Integrating mobile applications with automated invoice processing systems will allow stakeholders to review, approve, or reject invoices directly from their smartphones without missing a payment deadline. #### Better Supplier Portals Self-service invoice portals are beneficial both for accounting teams, which spend less time on invoice processing and for suppliers, who can take a more active role in ensuring timely payments. More and more companies will launch or improve their supplier platforms to streamline invoicing and promote collaboration with their partners. #### NLP-Powered Invoice Classification Rule-based invoice categorization is definitely faster than human accountants, but it’s not as good at identifying complex textual relationships or determining new patterns. NLP (natural language processing) has the potential to achieve near-human levels of text analysis in edge scenarios, improving classification accuracy while maintaining high processing efficiency. ### Automate Your Invoice Workflows with Flobotics As the lifeblood of any business, invoicing processes have a far-reaching impact on your organization. As such, automating these workflows holds the potential to enhance its overall operational efficiency. However, on your journey toward invoice automation, you’ll require the assistance of experienced automation developers and automation advisors. Our experts are here to help you and guide you to complex, end-to-end optimization. Just [get in touch](https://www.flobotics.io/contact)! #### Like the article? Spread the word Written byKarl Mielnicki CTO & Co-Founder of Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ Eligibility ### Payroll Process Improvement Ideas You Can Implement RPA in payroll: proven process-improvement ideas to cut manual work, reduce errors, and speed up your payroll cycle. Michał RejmanFebruary 07, 2022 ](https://www.flobotics.io/blog/rpa-payroll-process)[ AIEligibility ### Generative AI in Finance and Banking: What’s All the Buzz and Why You Should Care Generative AI in finance and banking: explore practical use cases, from fraud detection to reporting, transforming the sector in 2026. Michał RejmanJanuary 30, 2024 ](https://www.flobotics.io/blog/generative-ai-finance)[ RPAEligibility ### Bots You Can Bank On | What’s RPA for Finance and What’s in It for You? Finance process automation: how RPA helps banks and financial firms cut manual work in heavily regulated, data-intensive workflows. Filip NasiadkoNovember 21, 2022 ](https://www.flobotics.io/blog/rpa-for-finance) [All articles →](https://www.flobotics.io/blog) --- # Automation’s for Everyone: 100 Real-World RPA Use Cases Across Industries | 2026 Canonical: https://www.flobotics.io/blog/rpa-use-cases-across-industries Author: Michał Rejman Published: 2024-02-23 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Automation’s for Everyone: 100 Real-World RPA Use Cases… [RPA](https://www.flobotics.io/blog?category=rpa) # Automation’s for Everyone: 100 Real-World RPA Use Cases Across Industries | 2026 [Michał RejmanChief Marketing Officer at Flobotics](https://www.flobotics.io/our-editorial-team#rejman) Published February 23, 2024Updated September 1, 2026 On this page - [What is RPA exactly?](#what-is-rpa-exactly) - [RPA Use Cases — Introduction](#rpa-use-cases-introduction) - [100 RPA Use Cases from Major Industries](#100-rpa-use-cases-from-major-industries) - [RPA in Healthcare Use Cases](#rpa-in-healthcare-use-cases) - [RPA Healthcare Case Study: From Automated Claims Processing to Overall Operations Improvements](#rpa-healthcare-case-study-from-automated-claims-processing-to-overall-operations-improvements) - [RPA in Manufacturing Use Cases](#rpa-in-manufacturing-use-cases) - [RPA Manufacturing Case Study: SAP Automation](#rpa-manufacturing-case-study-sap-automation) - [RPA in Telecom Use Cases](#rpa-in-telecom-use-cases) - [RPA Telecom Case Study: Expedited Account Activation and Closure](#rpa-telecom-case-study-expedited-account-activation-and-closure) - [RPA in IT Use Cases](#rpa-in-it-use-cases) - [RPA IT Case Study](#rpa-it-case-study) - [RPA in Finance and Banking Use Cases](#rpa-in-finance-and-banking-use-cases) - [RPA Finance Case Study: Optimized Loan Processing](#rpa-finance-case-study-optimized-loan-processing) - [RPA Use Cases in Customer Service](#rpa-use-cases-in-customer-service) - [RPA Customer Service Case Study](#rpa-customer-service-case-study) - [RPA Use Cases in Retail](#rpa-use-cases-in-retail) - [RPA Retail Case Study: Automating Product Inspections](#rpa-retail-case-study-automating-product-inspections) - [RPA Use Cases in Administrative Processes](#rpa-use-cases-in-administrative-processes) - [RPA Administrative Work Case Study: Saving Time with Automated Data Entry](#rpa-administrative-work-case-study-saving-time-with-automated-data-entry) - [RPA Use Cases in HR](#rpa-use-cases-in-hr) - [RPA HR Case Study: RPA Powering Across-the-Board Transformation](#rpa-hr-case-study-rpa-powering-across-the-board-transformation) - [RPA in Insurance Use Cases](#rpa-in-insurance-use-cases) - [RPA Insurance Case Study: Ultra-Fast Document Migration and Processing](#rpa-insurance-case-study-ultra-fast-document-migration-and-processing) - [RPA Use Cases in Operations](#rpa-use-cases-in-operations) - [RPA Operations Case Study: Invoicing, Reporting, and Provider Management](#rpa-operations-case-study-invoicing-reporting-and-provider-management) - [RPA in Supply Chain Management and Logistics](#rpa-in-supply-chain-management-and-logistics) - [RPA Logistics Case Study: Automated Documentation for Seamless Supply Chain Management](#rpa-logistics-case-study-automated-documentation-for-seamless-supply-chain-management) - [Did You Find an RPA Use Case for Your Business?](#did-you-find-an-rpa-use-case-for-your-business) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) In the initial version of this article, RPA emerged as a disruptive force in various industries, a trend that continues to shape businesses today. Firmly establishing itself over the years, Robotic Process Automation is recognized as a versatile tool capable of replacing numerous manual processes. Today, RPA is a behemoth technology, with the [global RPA market](https://www.statista.com/statistics/1259903/robotic-process-automation-market-size-worldwide/) valued at $5.7 billion and projected to reach over $13 billion by 2030. Whether in healthcare or retail, you’ll almost certainly find its application in your business. Need some ideas on how it could help you optimize profits and outcomes? We’re here with a hot-off-the-press compilation of one hundred RPA use cases to optimize operations in your sector. ## What is RPA exactly? [Robotic Process Automation](https://www.flobotics.io/blog/robotic-process-automation) is a modern technological solution that comes to the rescue for automating many routine processes. For example, bank employees often, throughout the day, copy information from one system to another and transfer customer data to conclude an agreement with him or draw up an application for a loan. An employee can perform hundreds of such operations per day, requiring no talent other than attentiveness. RPA robotization is needed precisely to shift all these routine processes from humans to robots. ## RPA Use Cases — Introduction As a quick reminder, Robotic Process Automation, or RPA, is an automation technology that relies on deploying pre-programmed “bots” to execute specific tasks. These bots excel at repetitive, rule-based, and time-consuming workflows. However, when paired with AI technologies (which is increasingly common), RPA can also perform more complex tasks requiring cognitive abilities. RPA systems are capable of performing a large number of actions, including: - Opening and interacting with business apps, - Extracting, copying, and pasting data, - Navigating websites, pushing data into web forms, clicking buttons, - Recognizing and understanding the text, - Retrieving data from different sources and compiling it into a single location and vice versa, - Comparing and verifying information, - Communicating via email, notifications, and chatbots. For example, bank employees must copy information from one system to another and transfer customer data to conclude an agreement or draw up a loan application. These mundane tasks often consume several hours daily, drawing trained banking professionals from more demanding and satisfying work. Not to mention, it’s challenging to stay focused for a prolonged time and avoid simple human errors. Here’s where RPA steps in. This automation method aims to take over manual, tedious tasks such as data operations, increasing productivity, reducing errors, and improving employee satisfaction and customer outcomes. How does this look in practice? Let’s investigate! ## 100 RPA Use Cases from Major Industries With that, let’s explore RPA use cases in major business sectors: To illustrate them with specific, relatable examples, we also included real-life [RPA success stories](https://www.flobotics.io/case-studies) for each industry so you can see RPA in action. ## RPA in Healthcare Use Cases Relying on documentation and repetitive back-office tasks, the healthcare industry is full of opportunities for RPA automation. For example, according to a recent study, [43% of CFOs and revenue cycle leaders](https://revcycleintelligence.com/news/74-of-hospitals-use-some-revenue-cycle-automation) in US hospitals use RPA for revenue cycle automation. Joint research suggests that the technology yields the greatest impact on healthcare providers’ cost reduction in claims, customer service, and billing and enrollment. How else does it help medical facilities thrive? #### 1. [Payment Processing](https://www.flobotics.io/rcm-automation) Many finance-oriented healthcare processes, such as billing or invoicing, can be automated to reduce staff workload and eliminate errors. #### [2. Claims Management](https://www.flobotics.io/agents/claims-management-automation) RPA software bots can expedite claims management by collecting data, checking eligibility, and submitting claims to insurance providers. #### [3. Medical Billing](https://www.flobotics.io/rcm-automation) Nearly all stages of medical billing, including registration, claim generation, submission, coding, and adjudication, can be automated using RPA, streamlining payments, reducing manual effort, and improving compliance. #### 4. Patient Registration When done manually, data entry, identity verification, and creating new [health records](https://www.flobotics.io/blog/electronic-health-records-rpa) take dozens of hours each week. This is unless done by RPA, which efficiently handles large volumes of patient information precisely and consistently, minimizing the risks of inconsistency. #### 5. Appointment Scheduling RPA can optimize patient appointment scheduling based on physician availability, insurance information, location, and other factors. Bots can also send automated patient reminders, reducing no-show rates and improving the care flow. #### [6. Prior Authorization](https://www.flobotics.io/agents/prior-authorization-automation) RPA can easily compare the patient’s health plan coverage with the list of necessary prescriptions and procedures and then fill and submit the authorization form. #### 7. Medical Employee Onboarding By [automating HR tasks](https://www.flobotics.io/blog/rpa-in-hr-and-recruitment) such as employee onboarding, training tracking, and compliance management, back-office staff can focus on strategic initiatives and employee support. #### 8. Follow-up Communication RPA can send automated post-visit messages, surveys, and recommendations to collect patient feedback, monitor recovery progress, and ensure patient satisfaction. #### [9. EHR Tasks and Updates](https://www.flobotics.io/rcm-automation) By integrating the RPA bots with their EHR systems, clinicians can expedite patient data extraction, entry, and transfer. Record updates can also be handled automatically, ensuring that correct patient data is available across the organization. #### 10. Inventory Management Shortages, overstock, and other supply inefficiencies can seriously disrupt healthcare operations. RPA helps clinics avoid them by automating stock level tracking, order placement, and supplier communication tasks. #### 11. [Compliance Reporting](https://www.flobotics.io/rcm-automation) Non-compliance risks penalties and damages to healthcare institutions’ reputations. RPA will automatically generate reports required for regulatory [compliance](https://www.flobotics.io/blog/compliance-automation) to ensure adherence to industry guidelines. #### 12. Data Migration and Integration Integrating disparate healthcare systems is crucial for seamless data flow. RPA can assist in migrating data between them, maintaining data accuracy, reducing data entry errors, and improving interoperability. #### 13. Data Analytics Bots can be programmed to input, migrate, retrieve, and track healthcare data, facilitating analysis and enabling accurate diagnoses and individual treatment. ### RPA Healthcare Case Study: From Automated Claims Processing to Overall Operations Improvements Pain Treatment Centers of America (PTCoA), [Arkansas’s largest pain management practice network,](https://www.ptcoa.com/) faced a challenge that’s all too common in healthcare: inefficient claim processing. After our first collaboration exceeded PTCoA’s expectations, delivering a total ROI in 23 days, the network decided to scale up its automation efforts. Watch our bot automatically processes and submits insurance claims in PrognoCIS software As a result, we developed a small army of bots that handle eligibility checks, payment adjustments, approvals, price comparisons, lab order management… The list goes on and is still growing! Read full story and discover more details about the automation process [we implemented for PTCoA.](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) Interested in RPA in healthcare? Read more on our blog! ## RPA in Manufacturing Use Cases With dozens of paperwork tasks requiring communication with suppliers and vendors, there are many use cases for RPA in the manufacturing industry. As a result, it’s estimated that nearly half of manufacturers in developed countries use Robotic Process Automation to streamline production, improve quality, and reduce costs. Deloitte claims that [a typical procurement spend](https://www2.deloitte.com/us/en/pages/operations/articles/rpa-for-manufacturing-parts-proliferation.html) for manufacturing businesses can decrease from 4-12%, translating into millions of dollars in savings for many companies. Manufacturers benefit from RPA particularly in: #### 14. Administration and Reporting One of the main advantages of RPA in manufacturing is that it can generate accurate production reports and provide a clear picture of the status. This facilitates efficient decision-making and quick response to production needs. #### 15. Inventory Management RPA in inventory management allows manufacturers to automate emails, digitize documents, monitor inventory levels, and track product demand. #### 16. Material BOMs Manufacturing RPA use cases demonstrate how software bots can automate material billing by extracting data and ensuring data accuracy, reducing errors and transactional issues. #### 17. Vendor and [Supplier Management](https://www.flobotics.io/blog/warehouse-automation-process) To improve the overall coordination of the supply chain, manufacturers can leverage RPA to automate the onboarding of new vendors, communication with suppliers, and supplier performance tracking. #### 18. [Invoice Processing](https://www.flobotics.io/business-process-automation) With RPA, manufacturers can automate data extraction from invoices, validate transactional data, and update accounts payable systems for faster and more accurate invoice processing. #### 19. Purchase Order Creation Creating POs involving multiple vendors and product categories can be daunting. Instead of doing it manually, you can hand over the entire process to RPA to generate POs faster and error-free. #### 20. Production Planning and Scheduling To ensure efficiency and prevent production bottlenecks, manufacturers can use RPA to optimize production schedules based on demand forecasts, resource availability, and machine efficiency. #### 21. Order Management RPA bots can automatically extract order details from emails, upload them to the ERP system, update customers on product availability, and generate proof of delivery documents once the order is delivered. #### 22. Supply Chain Optimization RPA improves the overall [SCM process](https://www.flobotics.io/blog/warehouse-automation-process) by automating the supplier onboarding process, predicting demand, planning raw material usage, gathering data from various vendors, and performing credibility checks. #### 23. Data Management Migrating records, updating ERP data, processing unstructured documents, and conversion can all be delegated to RPA to save time and effort. ### RPA Manufacturing Case Study: SAP Automation Another of our clients, one of the largest sugar producers in the world, was seeking to optimize its SAP processes. The company already used an RPA solution developed by another provider but wasn’t fully satisfied with the outcome. Starting with the most crucial departments (controlling and finance), we gradually increased the scope of implementation, which resulted in a diverse range of purpose-made automations. These included a self-invoicing platform for clients, a EUR-pallet management solution, a customer status tracker, a web scrapper for stock index data, and a QA automation bot. Fig. 01 · Case Manufacturing Global sugar producer: SAP automation GoalManage processes in industry-standard SAP softwareSolutionAutomated key processes in controlling and finance, client service, sales and logistics 16bots built so far ~5,000 hof manual work saved a year 15×faster processes on average ## RPA in Telecom Use Cases Robotic Process Automation can be applied in the telecommunications sector in many ways, from automating manual sales order processing to improving average revenue per client. The technology covers many use cases, supporting telecom employees with providing on-time billing, efficient payment processing, speeding up document verification and SIM allotment, and other crucial tasks. #### 24. User Account Verification Account verification for telecom customers is an essential step of every contract but involves thousands of manual routine processes daily. Bots powered by Robotic Process Automation are meticulously programmed to execute them, operating around the clock and exhibiting unwavering diligence. #### 25. Reporting Traditionally, telecom operators must manually generate and submit reports on the market landscape, competitors, users, network performance and issues, and many others. RPA is best suited for this task, automating report generation and submission and reducing time-intensive tasks to minutes. #### 26. Easy Request Forwarding Based on preset parameters, RPA bots can receive emails and calls from users and other interested parties and automatically forward them to the relevant team. #### 27. Number Porting One of the best examples of Robotic Process Automation in the telecommunications industry is customer number porting. Customers switch providers frequently and don’t tolerate delays. To minimize these and provide prompt and flawless service, operators choose RPA. #### 28. Network Monitoring Telecom providers can delegate real-time network performance monitoring to RPA bots to ensure seamless services. These bots continuously analyze key parameters such as bandwidth usage, latency, and packet loss and send automated diagnostics, reports, and notifications in case of incidents or downtimes, significantly improving network stability. #### 29. Competitive Analysis Staying one step ahead of the competition requires constant monitoring of their offering, pricing, and features. RPA can extract this information by scraping competitors’ websites and other resources. It can also automate sentiment analysis by extracting and analyzing customer reviews, social media mentions, and feedback related to competitors and help track competitor pricing dynamics. #### 30. Customer Self-Service RPA bots can assist customers in solving simple, common issues by processing service requests, generating step-by-step instructions, and sharing the solution over the customer’s preferred channel. #### 31. First-Call Resolution If a customer decides to contact customer service, RPA can help agents address the issue without further follow-ups by retrieving customer info, details of the case, and possible solutions. ### RPA Telecom Case Study: Expedited Account Activation and Closure GPS nVISION, [a Texas-based provider of devices and software for tracking](https://www.gpsnvision.com/) cars, trailers, assets, and people, needed to shorten execution times of two vital processes: device and SIM card activation and deactivation. After a preliminary analysis, we opted for a low-code RPA solution that continuously looks for activation requests, sets up tracking devices, and configures user accounts. Similarly, the bot identifies, confirms, and deactivates unpaid accounts and trackers. The result? Four times faster execution time. Fig. 02 · Case Telecom GPS nVision: device and SIM activation GoalAutomate device and SIM card activation and deactivationSolutionA bot that does both in minutes, with safeguards against system errors 400%less process time 3 weeksto implement 1 botworking across 5 apps ## RPA in IT Use Cases Even though RPA bots are pieces of software, they can also work to optimize and facilitate the creation, testing, and deployment of other software. The tech sector has undoubtedly felt the impact of Robotic Process Automation, using it to streamline many software-oriented workloads: #### 32. Software Configuration RPA can automate software installation and initial configuration to save precious employee time and prevent costly disruptions. #### 33. Dev Environment Configuration Developers need to set up the environment in which they write code. RPA is best suited for automating the initial configuration on every system, as the process is the same. #### 34. Automated Software Testing Another great RPA use case in tech is automated testing. Manual user testing can be complicated and takes time. With RPA, common test scripts are automated and run after each update to ensure bugs are quickly found and fixed. #### 35. Automated Data Backup and Recovery RPA can monitor and schedule regular data backups, ensuring easy data recovery in case of incidents and enhancing data security. #### 36. [Security Management](https://www.flobotics.io/blog/8-security-practices-for-rpa-implementation) RPA bots can perform regular security checks and automatically detect threats. Once a breach attempt is identified, the bot can flag it, notify personnel, and deny access to targeted databases. #### 37. IT Maintenance Monitoring Routine, automated monitoring of IT systems reduces the risk of downtime that could hurt business operations. RPA will notify your staff whenever an issue is spotted, allowing for a timely intervention. #### 38. Patch Management RPA bots can continuously monitor for the release of new patches and updates from software vendors and then prioritize and test them. RPA-based patch deployment warrants regular software updates across all IT systems, improving overall system security. #### 39. Password Resetting Routine password resets are a necessary but mundane security measure. RPA can complete them quickly, regularly, and reliably by validating user identity through predefined security protocols, automating the generation of temporary passwords, communicating new credentials, and updating the information across relevant systems. ### RPA IT Case Study IT departments are the cornerstone of most business areas. Realizing that, Reckitt, a leading global manufacturer, set out to seek maximum efficiency in IT through automation. After years of gradual RPA deployment, Reckitt now uses more than 80 bots to streamline nearly 20% of [IT processes ](https://www.uipath.com/resources/automation-case-studies/reckitt-trailblazing-automation-within-its-it-operations)such as access management, password resets, service desk, and end-user computing. As a result, the IT department now saves 10,000 working hours each month and lowered operational costs by 20%. ## RPA in Finance and Banking Use Cases Banks and other financial institutions may be among the most document-reliant organizations. Gartner assesses that [8 in 10 finance leaders have either implemented RPA](https://www.gartner.com/en/finance/insights/robotics-in-finance) to offload routine tasks to automated bots or are planning to do so shortly. Robotic Process Automation is particularly valuable in streamlining these tasks: #### 40. Credit Checks RPA software bots can perform credit checks on potential loans and determine if they meet disbursement parameters, significantly reducing the loan processing time. #### 41. Data Entry By parsing documents, RPA robots can automatically fill data into forms by extracting them from documents, eliminating laborious manual data entry. #### 42. Know Your Customer (KYC) Suppose your company doesn’t use specialized KYC solutions. In that case, you can use RPA bots to automate parts of the KYC process, such as extracting information from documents, performing KYC checks, and populating customer profiles. #### 43. Verifying Applications RPA can extract vital personal details such as the customer’s name, address, income, and credit history, cross-check them with other sources, and enter data into the bank’s internal system, increasing speed and response times. #### 44. Customer Onboarding Another great use of robotic process automation in banking is opening accounts and connecting customers. This routine process involves mundane tasks such as verifying data accuracy, setting up accounts, and performing background checks. #### 45. Loan Processing RPA can assist bankers through the entire loan process: application processing, underwriting, and disbursement by extracting, retrieving, and entering data and verifying borrower information. #### 46. Fraud Detection and Prevention RPA can analyze transaction patterns, identify anomalies, and flag potentially fraudulent activities to improve data and account safety and prevent financial losses. #### 47. Financial Planning and Analysis Data collection, analysis, and reporting can all be automated with RPA to expedite financial planning, budgeting, and forecasting processes and improve decision-making. #### 48. Financial Reporting RPA enables the automated generation and distribution of financial reports, ensuring a timely and accurate flow of information while saving time and effort. #### 49. Risk Assessment RPA can automatically analyze various scenarios, identify risks based on audits and patterns, and report data. Automated risk assessment is faster and more accurate than manual analysis. #### 50. Loan Origination and Approval RPA can automate document verification, credit checks, and loan management systems updates to accelerate loan processing times and reduce the administrative burden on loan officers. #### 51. Account Reconciliation RPA robots will handle repetitive reconciliation tasks, allowing faster day-to-day transaction analyses or periodic compliance-oriented ledger reconciliation. #### 52. Tax Compliance Integrating RPA robots with existing tax compliance software to gather data, compile tax reports, and submit their results in enhanced legal procedures. #### 53. Account Closure Closing customer accounts is a regular, rule-based task that takes hundreds of hours monthly. Robotic Process Automation in finance can identify non-compliant or inactive accounts and close them automatically. #### 54. Financial Audits Besides automating manual auditing tasks like data extraction, RPA can improve error detection and flag discrepancies. Automated audit trails and change tracking streamline future audit processes. ### RPA Finance Case Study: Optimized Loan Processing Paramount Residential Mortgage Group (PRMG), [a California-based mortgage banker operating in 48 states](https://www.prmg.net/), struggled with manual, extremely time-consuming, and inconsistent loan estimation and granting processes. What started with a single-bot solution evolved into an end-to-end loan processing automation with six bots, each dedicated to a single step in the workflow. RPA now handles the entire process, from retrieving and distributing disclosure packages to compiling and archiving data across various systems for improved efficiency and accuracy. Fig. 03 · Case Finance and banking PRMG: loan processing GoalAutomate loan estimates and approvalsSolutionFive production bots automating six tasks, each one part of the process 600%less process time $2Msaved a year 5FTEs saved 1stprize, Process Innovation, ICE Mortgage ## RPA Use Cases in Customer Service Even though [customer service](https://www.flobotics.io/blog/rpa-customerexperience) relies heavily on human-to-human interactions, Robotic Process Automation helps enhance them by taking care of the back office work. RPA can be used to automate customer relationship management and generate valuable personalized service results, especially in the following areas: #### 55. Fast Initial Responses RPA software bots can sort common customer requests and deliver immediate responses, sorting out the issue of frustrating customers with lazy reactions to their inquiries. #### 56. Forwarding Requests RPA bots can sort requests into different categories based on preset parameters and automatically send them to the appropriate departments, reducing call hold times and excess interactions. #### 57. Customer Data Categorization Robotic Process Automation allows companies to categorize customers and define their paths for better targeting and more streamlined and personalized service. #### 58. Automated Emails By scanning company databases for relevant information, RPA can generate automated email responses to customer requests. Bots can also update customers on the progress of submitted tickets without involving human employees. #### 59. [Chatbot Integration](https://www.flobotics.io/blog/chatgpt-for-healthcare) RPA can support chatbots by automating backend processes, retrieving necessary information, and initiating follow-up procedures, allowing for more comprehensive responses and better customer experience. #### 60. Returns and Refund Processing Returns and refund procedures are highly repetitive, making them a perfect fit for RPA-based data entry, verification, and refund transaction automation. #### 61. Knowledge Base Maintenance Customers and CX agents rely on internal knowledge bases that must be constantly updated. RPA can automate this process by adding new information, editing articles, and archiving outdated content. #### 62. Feedback Analysis RPA can compile and analyze customer feedback across communication channels, providing insights into customer sentiments, preferences, and recurring issues. #### 63. Aiding Customer Care Agents With the aid of RPA bots, customer service reps can quickly retrieve customer details such as communication history, demographics, and previous orders or documents necessary to solve the issue, e.g., guidelines and invoices. #### 64. CRM Updates As customers interact with a business, its CRM must be regularly updated with new orders, lead scores, contact history, and other details. RPA can extract data from emails, chats, surveys, and other channels and upload it to the customer’s CRM profile. ### RPA Customer Service Case Study For CXP, a major contact center outsourcer, every minute saved per customer request has a significant impact. RPA can do just that. Between [automated customer data retrieval ](https://www.uipath.com/resources/automation-case-studies/cxp-revolutionizing-customer-experience-software-robots)and RPA-powered chatbots, automation didn’t only cut call times by 35% on average. An even more essential success metric is a 52% increase in Trust Pilot ratings—a true measure of customer satisfaction. ## RPA Use Cases in Retail Retail and [e-commerce](https://www.flobotics.io/blog/ecommerce-automation) are dynamic, consumer-driven industries prone to continual transformations. In such a highly dynamic setting, optimizing small but essential tasks is the key to earmarking more time for creative endeavors in designing products and campaigns and ensuring high-touch customer service. Statistics confirm this, with [60% of consumer and retail tasks suitable for automation](https://www.uipath.com/solutions/industry/cpg-retail-automation). What are they? Let’s get some examples. #### 65. Product Categorization RPA bots can extract SKU (Stock Keeping Unit) data to help companies quickly categorize products and determine their market share in different regions. They can be programmed to analyze product information, such as attributes, descriptions, and images, and assign them to the appropriate categories within the inventory. RPA can also dynamically create new categories. #### 66. Returns Returning a product spans a range of procedures and formalities. RPA bots allow retail businesses to verify purchase records and process refund transactions automatically. This can shorten online returns processing times from weeks to days or hours upon the product delivery to the seller. #### 67. Inventory Management Another great use case for RPA in retail is inventory management. Robotic Process Automation bots can monitor stock levels around the clock and send alerts in case of shortage or overflow. By automating tasks such as data entry, order processing, and stock level monitoring, retailers can minimize human errors, accelerate data processing, and maintain more accurate and up-to-date inventory records. #### 68. Price and Promotion Management Price updates require significant manual effort, particularly during large promotional events. RPA can automatically update prices, apply discounts, and ensure the offering stays consistent across all channels. #### 69. Customer Data Management By automating customer data entry and updates, RPA helps retail businesses keep customer records accurate and up-to-date across all internal systems. facilitating personalized marketing efforts and customer relationship management. #### 70. Loyalty Program Management Between updating customer points, processing rewards, and sending automated communications, many loyalty processes can be enhanced with RPA, allowing retailers more time to adapt to the changing markets quickly and develop more creative ways to engage customers. #### 71. Email Marketing Personalizing customer communications involves a lot of care and consideration for individual purchase history and preferences. By integrating RPA with customer databases, retail businesses can automate generating and distributing custom marketing emails. ### RPA Retail Case Study: Automating Product Inspections Lotte, a South Korean multinational retail giant and the first online shopping mall in the country, is no stranger to innovation. That’s why automation was a natural choice when Lotte decided that its product description review process needed a boost. The solution was to replace manual inspections with [UiPath](https://www.flobotics.io/blog/specific-content-limitations-in-uipath) robots paired with optical character recognition (OCR) technology. This combination more than doubled the throughput, from 4,400 to 10,000 cases reviewed monthly. ## RPA Use Cases in Administrative Processes Extracting, entering, retrieving, and generating data is where RPA shines. Depending on the process and team size, some estimates claim that larger companies can save 20-40 hours daily on automating mundane admin work. Other sources quote savings in the line of 25,000 horse annually. No wonder that Robotic Process Automation is every admin worker’s best friend, supporting them in tasks such as: #### 72. Invoice Processing RPA can process paper invoices using OCR, extract records, upload them to internal databases, and automatically send information to appropriate stakeholders. Sometimes, these automations can complete tasks up to 10 times faster than humans. #### 73. Data Entry Moving records, populating forms, filling Excel tables, and other tasks that involve entering data, particularly structured, are some of the primary RPA use cases. In industries such as healthcare, Robotic Process Automation can handle up to 90% of data entry-related tasks. #### 74. Storing Personal Information RPA software bots can easily extract customer or employee information from the initial forms they fill out to present in an easy-to-read format or upload it to your CRM. #### 75. [Document Processing](https://www.flobotics.io/blog/automated-document-processing) and Filing RPA can automate the classification, sorting, and archiving of documents based on their contents, type, tags, and other categories. A systematic arrangement reduces the risk of document misplacement and improves record management. #### 76. Meeting Minutes and Documentation RPA bots equipped with speech-to-text features can automate the generation of meeting minutes and summaries. Such a bot can extract information from recorded meetings and transcribe discussions to ensure that all significant details have been captured. ### RPA Administrative Work Case Study: Saving Time with Automated Data Entry “When people type data all day, data quality suffers.”—this quote from Dr. Everton Gomede, Head of Technology at System of Credit Unions of Brazil (Sicoob), perfectly captures the role of [RPA in data operations.](https://www.ibm.com/case-studies/system-of-credit-unions-of-brazil) For Sicoob, the objective of RPA automation was threefold: to reduce errors, save time, and free up employees so that they can focus on high-value tasks. By automating data entry, Sicoob expedited manual data processes by up to 80%, generated 10-20% cost savings, and had an immeasurable but significant effect on employee satisfaction. ## [RPA Use Cases in HR](https://www.flobotics.io/business-process-automation) Human resource management involves some of any organization’s most tedious and data-heavy tasks. By applying RPA, HR specialists can focus on strategic and value-added activities like talent management, employee engagement, and organizational development. Additionally, RPA enhances accuracy in data management, minimizing errors in payroll and personnel records. Doing so accelerates [HR workflows](https://www.flobotics.io/blog/rpa-in-hr-and-recruitment) and contributes to a more agile and responsive HR function. #### 77. Employee Sourcing RPA bots allow HR managers to search for suitable prospects and candidates based on preset parameters. The bots will automatically receive the data when the parameters match the prospect’s profile. #### 78. Improved Hiring RPA introduces several quality-of-life improvements for recruiters. Bots can track and suggest rejected candidates for openings that better suit their profile, verify digital copies of application documents, schedule interviews, and draft messages. #### 79. Onboarding Employees From reviewing personal information forms and creating employee accounts to automated communication and triggering tasks, RPA proves handy throughout onboarding, accelerating it up to 10 times, [according to UiPath](https://www.uipath.com/solutions/department/hr-automation). #### 80. Offboarding Employees Similarly, RPA can handle a range of offboarding processes: retrieving dismissal documents, requesting benefit termination, revoking access to internal systems, initiating the final settlement, and more. #### 81. [Payroll Automation](https://www.flobotics.io/blog/payroll-process-rpa) RPA software bots allow businesses to automate payroll by pulling data from timesheets and calculating payroll at the end of each month. Thanks to that, HR departments can compile accurate payrolls and determine individual salaries in seconds. #### 82. Travel and Expense Management RPA can be delegated to extracting and reviewing expense data from invoices, vouchers, tickets, etc. Following a preset rules approach, bots can recognize which expenses are valid and which don’t meet the established requirements. ### RPA HR Case Study: RPA Powering Across-the-Board Transformation TriNet delivers custom-made [HR solutions](https://www.automationanywhere.com/resources/customer-stories/trinet) for SMBs, enabling easier growth without worrying about HR complexities. TriNet launched its biggest transformation ever to improve its operational model, and RPA was central to that change. Over 4 years, the company has automated 120 workflows, including document processing and enhancement, payroll, and HR functions. These improvements helped the company maintain operational agility throughout the transition and beyond. Are you interested in RPA in HR and recruitment? Read more on our blog! ## RPA in Insurance Use Cases Insurance is another industry heavily dependent on paperwork, and as such, it can greatly benefit from automation. In fact, it’s estimated that over 200 insurance-related tasks can be automated. Here’s a bunch of them: #### 83. Claims Verification Robotic Process Automation enables insurance companies to verify claims faster based on predefined rules, minimizing fraudulent claims and eliminating delays in claims compensation. #### 84. [Claims Processing](https://www.flobotics.io/agents/claims-management-automation) Manual claims processing takes a long time due to laborious data extraction and subsequent filling of required forms. With RPA, insurance companies can accelerate claims settlement, reduce errors, and enhance overall efficiency. Accenture assesses that combining RPA and AI can [save up to 75% time on claims processing.](https://www.accenture.com/content/dam/accenture/final/a-com-migration/pdf/pdf-148/Accenture-Accelerating-Intelligent-Automation-Insurance.pdf) #### 85. Premium Management Robotic Process Automation enables insurance companies to verify claims faster based on predefined rules, minimizing fraudulent claims and eliminating delays in claims compensation. #### 86. Underwriting RPA can also streamline underwriting tasks such as data gathering, risk assessment, and policy pricing to improve efficiency and decision-making. #### 87. Policy Quoting and Comparison With RPA, insurers can automate several steps in the quoting process, such as extracting data from various sources, calculating premiums, compiling quote comparisons, and sharing quotes with customers. #### 88. Regulatory Compliance Manual compliance control is inefficient and prone to potentially costly human errors. RPA can perform the process quickly and securely, maintain a change log, validate customer data, generate compliance reports, and more. #### 89. Policy Cancellation Processing policy cancellation requests requires switching between email, CRM, Excel, and PDFs to find relevant data. RPA can do that automatically while also handling other steps in the process, like setting cancellation date tally, inception date, policy term, and more. #### 90. Legacy App Integration Insurance companies often use legacy apps for years, eventually leading to compatibility issues and inconsistent databases. RPA helps insurers bridge the gap between old and new systems through automated integration and data transfer. #### 91. Improving Business Processes Bots easily track, generate audit trails, and measure processed transactions and exceptions automatically. All that facilitates process analysis and supports business improvements. ### RPA Insurance Case Study: Ultra-Fast Document Migration and Processing When Ayr Farmers Mutual Insurance Company needed to move and process over 500,000 records from a legacy app, we knew it would be the perfect use case for RPA. Since the app was soon to be discontinued, we needed to act fast. The bot we developed ran on 5 computers, continuously downloading and archiving the documents in PDF format. The effort paid off: the project was completed 4 weeks before the deadline, and all documentation is now easily searchable, [r](https://www.flobotics.io/case-studies)[ead the full story](https://www.flobotics.io/case-studies) on our portfolio! Interested in RPA in insurance? Read more on [our blog!](https://www.flobotics.io/blog) ## RPA Use Cases in Operations Some processes are so fundamental that all businesses need them to sustain their operations. Unfortunately, they often use legacy automations to interface with their complex tech stack. These technologies are quite rigid and require heavy coding to implement changes, falling behind the dynamic changes to modern-day business operations. How can RPA help instead? #### 92. Data Migration Standardization, modernization, or even merging with another business—there are many reasons for transferring large volumes of data. Instead of relying on manual transfers, businesses can delegate this task to RPA, which will handle data migration faster and more consistently. #### 93. [Invoice Processing](https://www.flobotics.io/blog/invoice-automation) While businesses can’t eliminate invoicing completely, they can hand off invoice processing tasks to RPA. Preprogrammed bots can automatically extract data from transactional documentation, copy them to internal systems, and create invoices. #### 94. [Compliance](https://www.flobotics.io/rcm-automation) All industries are regulated in one way or another. RPA makes adhering to legal requirements much easier through automated compliance monitoring, reporting, and alerts when deviations occur. ### RPA Operations Case Study: Invoicing, Reporting, and Provider Management Axpo, [Switzerland’s leading renewable energy producer ](https://www.axpo.com/ch/en/about-us.html)and an international leader in energy trading, discovered that rapid growth is a double-edged sword. Their manual processes couldn’t cope with constantly growing volumes of tasks. Compliance with international regulations also proved to be a challenge. With the help of an RPA solution developed by Flobotics, Axpo can now generate and correct invoices for over 600 daily transactions. RPA bots also allow Axpo to complete 27 days’ days work in one day (!) for the crucial, legally required pricing summary process. Fig. 04 · Case Operations Axpo: invoicing, reporting and provider switching GoalScale faster with no errors and full complianceSolutionAutomated invoicing, reporting and provider switching 6.18FTEs saved $186kprofit in year one 147%ROI 54,000automated actions a month 90%+average bot accuracy [Read full story](https://www.flobotics.io/blog/axpo-automation) and find out how RPA bots allow Axpo to complete 27 days’ days work in one day (!) for the crucial, legally required pricing summary process. We can also help your energy company to [automate the mundane and time-consuming processes](https://www.flobotics.io/business-process-automation). Explore possibilities! Interested in RPA in process management and operations? Read more on our blog! ## [RPA in Supply Chain Management](https://www.flobotics.io/business-process-automation) and Logistics Shipping and storing products is an impressive logistical feat that usually requires transferring data across multiple entities subject to complex local regulations, all with their own systems. On average, standard [international trade transactions](https://supplychaindigital.com/technology/how-rpa-revolutionising-supply-chain-networks) involve sharing 35 documents between 25 parties that must comply with at least 600 regulations and more than 500 trade agreements. [RPA in logistics](https://www.flobotics.io/business-process-automation) can streamline these data operations and many other activities to make that task less challenging: #### 95. Shipment Scheduling RPA bots can extract data from letters, memos, and notes to plan shipments without confusion and conflicting schedules. They can also perform validation checks to ensure the accuracy and completeness of the shipment details. #### 96. Delivery Tracking RPA can track where the shipment is and alert the system when it reaches certain locations or fails to do so. This allows all involved businesses to coordinate the entire supply chain seamlessly and efficiently, without much manual work. #### 97. [Warehouse Management](https://www.flobotics.io/blog/warehouse-automation-process) RPA can automate thousands of warehouse management tasks, including inventory checks, allocation, tracking deadstock, and even suggesting stock-based pricing. Additionally, Robotic Process Automation may track real-time warehouse data and trigger instant alerts in case of irregularities. #### 98. Order Management RPA can use inventory data to automatically place resupply orders, including listing the necessary products, comparing prices, generating documentation, submitting the order for approval, and sending it to vendors. In some cases, these improvements can save up to 80% of time on managing customer orders. #### 99. Delivery Notifications Based on predefined rules, RPA can automatically update delivery progress and provide stage completion notifications to improve visibility and customer experience. #### 100. Supply and Demand Planning By analyzing historical data, market trends, stock levels, and other relevant factors, RPA is also invaluable in optimizing overall supply chain planning and ensuring better alignment with demand. #### 101. Freight Management Load matching, handling freight claims and charges, and picking optimal routes can all be done by RPA. Additionally, some solutions can analyze the performance of your supply chain and point to possible improvements. ### RPA Logistics Case Study: Automated Documentation for Seamless Supply Chain Management Extensive paperwork can turn international shipment tracking into a true headache, and every mistake can lead to severe consequences. Inter Aduaneira, a Brazilian trade consultancy, deals with tons of documentation in most of their workflows. In fact, these processes were so complicated that Inter Aduaneira decided to find a dedicated company to implement internal technological solutions. RPA was at the core of the [digital transformation](https://www.ibm.com/case-studies/inter-aduaneira), automating the retrieval and processing of thousands of documents and saving an average of 800 hours per analyst. ## Did You Find an RPA Use Case for Your Business? Even if the answer’s no, don’t worry - RPA can be easily customized for many purposes. As automation vendors continuously integrate their solutions with emerging technologies, the future looks bright for RPA and any business that uses it. You’ll need a reliable RPA partner to help you identify the most promising automation opportunities and bring them to life. For that, [get in touch with us.](https://www.flobotics.io/contact) Our consultants will analyze your industry and help you plan, map, and develop RPA solutions so you can achieve your business goals cheaper and faster. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byMichał Rejman Chief Marketing Officer at Flobotics. [More from Michał](https://www.flobotics.io/our-editorial-team#rejman) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### Automated Document Processing: How to Do Away with Manual Paperwork? Automated document processing: how RPA turns insurance claims, loan statements, and patient forms into a paperwork-free workflow. Karl MielnickiFebruary 11, 2024 ](https://www.flobotics.io/blog/automated-document-processing)[ RPA ### Top Automation Trends in 2026 Automation trends for 2026: eight shifts in RPA, AI, and workflow automation that will shape how businesses operate this year. Krzysztof SzwedFebruary 03, 2025 ](https://www.flobotics.io/blog/top-automation-trends)[ RPA ### UiPath vs. Python? Choosing the Right RPA Tool for Your Automation Job UiPath vs. Python: compare strengths, use cases, and when to choose code over low-code for your next automation project. Krzysztof SzwedDecember 11, 2023 ](https://www.flobotics.io/blog/uipath-python) [All articles →](https://www.flobotics.io/blog) --- # Automated Document Processing: How to Do Away with Manual Paperwork? Canonical: https://www.flobotics.io/blog/automated-document-processing Author: Karl Mielnicki Published: 2024-02-11 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Automated Document Processing: How to Do Away with Manual… CTO Notes [RPA](https://www.flobotics.io/blog?category=rpa) # Automated Document Processing: How to Do Away with Manual Paperwork? [Karl MielnickiCTO & Co-Founder of Flobotics](https://www.flobotics.io/our-editorial-team#mielnicki) Published February 11, 2024Updated September 1, 2026 On this page - [What’s Automated Document Processing?](#whats-automated-document-processing) - [Automated Document Processing and Intelligent Document Processing: What’s the Difference?](#automated-document-processing-and-intelligent-document-processing-whats-the-difference) - [Automated document processing vs. intelligent document processing](#automated-document-processing-vs-intelligent-document-processing) - [Technologies Used in Automated Document Processing and Understanding](#technologies-used-in-automated-document-processing-and-understanding) - [Robotic Process Automation (RPA)](#robotic-process-automation-rpa) - [Optical Character Recognition (OCR)](#optical-character-recognition-ocr) - [Machine Learning (ML)](#machine-learning-ml) - [Natural Language Processing (NLP)](#natural-language-processing-nlp) - [Generative AI](#generative-ai) - [Cognitive computing](#cognitive-computing) - [The Benefits of Automated Document Processing](#the-benefits-of-automated-document-processing) - [Automated Document Processing Across Industries](#automated-document-processing-across-industries) - [Healthcare](#healthcare) - [Finance & Banking](#finance-banking) - [Insurance](#insurance) - [Manufacturing](#manufacturing) - [Real estate](#real-estate) - [Automated Document Processing: Where to Start?](#automated-document-processing-where-to-start) - [Automated Document Processing with Flobotics](#automated-document-processing-with-flobotics) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Drowning in paperwork? Whether it’s insurance, finance, healthcare, or manufacturing, documents rule all industries, from insurance claims and loan statements to patient signoffs. To deal with them, organizations enter digitization. According to Forrester, [65% deem integrating document digitization with daily apps crucial](https://www.adobe.com/content/dam/dx-dc/pdf/ue/forrester-digital-documents-business-necessity-ue.pdf) to keep their work flowing. Automated document processing is a shortcut to ditching paperwork chaos and replacing it with document management efficiency, unleashing tech to manage, organize, and revolutionize documents effortlessly. To help you revolutionize document management, we are breaking down what it is, the tech behind it, and the game-changing benefits. Let’s dive in! ## What’s Automated Document Processing? Let’s start by explaining what document automated processing & understanding means. In essence, automated document processing is just what it sounds like—a set of technologies used together to streamline the handling and conversion of unstructured documents into structured formats. Each tool automates extracting, interpreting, or manipulating information from digital or scanned paper documents, images, PDFs, emails, or other documents. Fig. 01 · Documents Two types Structured vs unstructured data - Structured Structured documentsOrganized by preset rules, so they are easy to process. - Spreadsheets - SQL databases - Dates - Phone numbers - Email addresses - SEO tags - Form answers - Bank account details - Serial numbers - Unstructured Unstructured documentsDon't follow a standard; often visual or free text, so computers find them harder to read. - Emails and messages - Videos - Images - Audio files - Social media posts - Handwritten notes - Books Through AI and automation techniques, automated document processing systems can recognize and categorize data, extract relevant information, and perform predefined document-based tasks, eliminating manual effort. ## Automated Document Processing and Intelligent Document Processing: What’s the Difference? Intelligent document processing is an essential component of automated document processing. Both concepts are closely related and usually used together, due to which (and similarity in naming) they are often confused. Still, they aren’t the same. Automated document processing focuses on automating rule-based document processing tasks using technologies such as Optical Character Recognition (OCR) and software automation. These tasks include data extraction or sorting. While automated document processing can be efficient for specific tasks, it might require additional manual adjustments when applied independently to process unstructured documents or changes in document formats. Intelligent document processing goes beyond basic automation by leveraging AI technologies such as machine learning (ML) and natural language processing (NLP) to enable systems to interpret, categorize, and validate the extracted data. Doing so enables intelligent document processing to adapt to variations and better handle unstructured documents. Since automated document processing and intelligent document processing complement one another, automated document processing vendors often use these terms interchangeably. ### Automated document processing vs. intelligent document processing #### Automated document processing Automated Document Processing (ADP) involves using technology to streamline routine document-related tasks, typically relying on rule-based systems. It focuses on efficiently processing information in documents; hence, its main applications include automating data entry and improving document classification. #### Intelligent document processing Intelligent Document Processing (IDP) employs advanced technologies like artificial intelligence and machine learning to automate tasks and understand and interpret unstructured data. It goes beyond automated document processing, offering a more nuanced understanding of content, and making it especially adept at handling diverse and complex documents in finance, healthcare, and legal industries. ## Technologies Used in Automated Document Processing and Understanding To properly extract, interpret, and classify documents, automated document processing makes use of several technologies: ### Robotic Process Automation (RPA) [Robotic Process Automation](https://www.flobotics.io/blog/rpa-development-process) refers to handing over repetitive, manual tasks to rule-based algorithms (bots) that can perform them faster and with a lower margin of error than humans. When it comes to automated document processing, this simple but efficient solution is often combined with AI in tools such as [UiPath Document Processing](https://www.uipath.com/platform/agentic-automation/idp), [AA Document Automation](https://www.automationanywhere.com/products/document-automation), and [IBM Document Processing](https://www.ibm.com/products/document-processing). This pairing allows us to apply all of AI’s document understanding capabilities at scale and without human involvement. ### Optical Character Recognition (OCR) Optical Character Recognition identifies letters, numbers, and other characters in documents and images, which are then converted into accountable formats. This enables further automated data processing. OCR has as many applications as there are documents to extract data from invoices, orders, statements, recipes, etc. ### Machine Learning (ML) The use of AI algorithms, statistical models, and data to imitate the way humans learn. With [Machine Learning](https://www.flobotics.io/blog/robotic-process-automation-vs-machine-learning), AI doesn’t require explicit instructions. Instead, it can “study” data to gradually improve at specific tasks. ML allows AI to improve its accuracy with each document handled continuously in document processing. With that, outputs provided by artificial intelligence require less verification, giving humans more time to focus on other tasks. ### Natural Language Processing (NLP) Natural Language Processing aims to allow computers to interpret and generate human language through text or voice outputs. To achieve that “understanding,” NLP combines rule-based and statistical modeling with machine learning. NLP is a cornerstone of any language-centered application, like chatbots, virtual assistants, speech-to-text software, translation tools, and more. ### Generative AI With the release of Gen AI tools like Chat GPT or Midjourney, generative AI has been in constant spotlight due to its creative content-generation capabilities, previously unseen in machines. Gen AI finds a perfect application in automated document processing, where it’s used to humanize ADP tools through natural language prompts and produce content like document summaries or complex answers to user requests. ### Cognitive computing If natural language processing aims to mimic human linguistic capabilities, cognitive computing tries to reproduce our problem-solving and complex thinking processes. These skills are fundamental when processing unstructured data, exceptions, or deviations from patterns. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## The Benefits of Automated Document Processing Now, the part you’re probably the most interested in: what can you gain by implementing automated document processing? Fig. 02 · Document processing 6 gains What automated document processing improves - EfficiencyAI and RPA speed up many document-based tasks. - AccuracyFewer errors, and the error rate keeps falling as the system improves. - CostNo time and money lost on post-processing documents or fixing human errors. - ComplianceFewer accidental mistakes and strict, repeatable procedures help with legal compliance. - Decision-makingInformation flows across the organization, so decisions rest on facts. - ScalabilityAdd RPA bots or computing power to take on new document workloads. ## Automated Document Processing Across Industries Any company can reap the benefits of automated document processing from increased efficiency to faster decision-making, no matter the industry. However, documentation, data, and tasks vary depending on the sector. Here are some industry-specific applications of automated document processing. ### Healthcare The healthcare industry already relies largely on digital data formats. In the US, 78% of office-based physicians and [96% of non-federal hospitals use a certified EHR system](https://www.healthit.gov/data/quickstats/national-trends-hospital-and-physician-adoption-electronic-health-records). Automated document processing software is crucial for converting and organizing all medical records. - Patient record management: Automated document processing allows healthcare professionals to access critical patient data faster. - Clinical trial documentation: Between approvals, reports, reviews, and other documents, clinical trials involve lots of paperwork that laboratories can expedite through automated document processing. - Claims processing: With automated document processing, clinics and practitioners can accelerate reimbursement and handle insurance claims and medical bills without errors. ### Finance & Banking Finances Online says [knowledge workers lose 50% of their time preparing documentation](https://financesonline.com/cloud-file-document-management-software-statistics/). Automated document processing is the perfect answer to these inefficiencies, helping banks reduce manual document-focused tasks. - Loan processing: Through automated document processing, the verification of financial documents becomes much faster, expediting loan approval processes. - KYC processes: Automated document processing streamlines the extraction and verification of customer credentials and helps banks meet regulatory requirements. - Invoice processing: Automation improves the speed and accuracy of financial statement and invoice processing workflows. ### Insurance On average, [insurers handle over 100,000 documents annually](https://www.business-reporter.co.uk/finance/solving-the-problem-of-complex-document-processing-for-insurance-companies), 80% of which is unstructured data. This creates ample opportunity for automated document processing in insurance to take over mundane paperwork. - Policy administration: Managing insurance policies, processing policy applications, and extracting relevant data for underwriting can all be expedited through automated document processing. - Policy renewals: Automated document processing ensures that policy renewal documents are processed timely and that coverage is kept current. - Claims adjudication: With automated document processing, insurers can speed up the evaluation of claims documents and the entire claims review cycle. ### Manufacturing Manufacturing involves tons of documentation flowing internally and between each link of the production chain. The communication is still largely unautomated, with [o](https://www.digitalcommerce360.com/product/b2b-ecommerce-market-report/)[ver 40% of manufacturing orders being placed through fax or email ](https://www.digitalcommerce360.com/product/b2b-ecommerce-market-report/)and manually entered, according to Digital Commerce 360. - Supply chain management: Automated document processing helps companies efficiently manage sales orders, shipping documents, invoices, and customs paperwork, resulting in streamlined supply chain operations. - Quality control: By automating the handling of product control documents, manufacturers can ensure strict adherence to quality procedures. - Product manuals and compliance: Manufacturers can apply automated document processing to manuals, specifications, and compliance certificates to warrant that their products are accessible and follow industry standards. ### Real estate 64% of companies surveyed by Deloitte see many use cases for AI in real estate. One of the potential applications is relieving agents of mundane paperwork tasks. - Contract management: Data contained in contracts, lease agreements, invoices, and other transaction documents can be extracted and added to your management system automatically. - Mortgage Processing: Automated document processing streamlines the processing of mortgage documents, such as applications, appraisals, and title deeds, for faster mortgage approval and disbursement. - Property valuation: Automated document processing can quickly extract property-related data needed in the property valuation process. ## Automated Document Processing: Where to Start? Automated document processing has the undeniable potential to revolutionize documentation-focused workflows in your business. However, to get to that point, you must consider various factors. Fig. 03 · Document processing 7 steps Building an automated document processing system - 01Analyze requirementsReview document types and volumes. Ask employees which tasks take longest, then set priorities and goals. - 02Prioritize complianceFocus on legally binding documents and research regulatory requirements with your vendor or developers. - 03Plan system integrationMake sure the tool works with the systems you already use, so documents are managed in one place. - 04Plan for security and privacyUse encryption, access control and audit trails to reduce data leaks and fines. - 05Test the systemCheck functionality, usability and security before launch, and gather user feedback. - 06Train your teamShow employees what the system does, which documents it handles and which tasks it covers. - 07Maintain and upgradeAudit and update the system regularly as the business and technology change. ### Automated Document Processing with Flobotics Now that you know what automated document processing is, how it works, and what it can do for your business, there’s only one thing to do: build your document automation system. At Flobotics, we can guide you through the entire process. From assessment and deciding [what process to automate](https://www.flobotics.io/blog/what-processes-to-automate) to implementation and testing, our experts will help you replace manual documentation tasks with efficient, automated workflows. [Let’s get started!](https://www.flobotics.io/) #### Like the article? Spread the word Written byKarl Mielnicki CTO & Co-Founder of Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### Document Understanding Tools Overview Document understanding tools compared: top platforms, use cases, and how they streamline document management workflows for teams. Krzysztof SzwedJuly 04, 2024 ](https://www.flobotics.io/blog/document-understanding-tools)[ RPA ### More Than Just Reading Text: Why Your Document Understanding Sucks Document understanding challenges, explained: why most automations underperform, what's really failing beyond the OCR tool, and how to fix it. Karl MielnickiJune 05, 2024 ](https://www.flobotics.io/blog/why-document-understanding-sucks)[ RCMRPAHealthcare ### Healthcare Document Processing: From Paperwork Pain to Automated Gain Healthcare document processing: see how automation turns intake forms, claims, and billing paperwork into a faster, error-free workflow. Bart TeodorczukJune 10, 2025 ](https://www.flobotics.io/blog/healthcare-document-processing) [All articles →](https://www.flobotics.io/blog) --- # Generative AI in Finance and Banking: What’s All the Buzz and Why You Should Care Canonical: https://www.flobotics.io/blog/generative-ai-finance Author: Michał Rejman Published: 2024-01-30 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Generative AI in Finance and Banking: What’s All the Buzz… [AI](https://www.flobotics.io/blog?category=ai)[Eligibility](https://www.flobotics.io/blog?category=eligibility) # Generative AI in Finance and Banking: What’s All the Buzz and Why You Should Care [Michał RejmanChief Marketing Officer at Flobotics](https://www.flobotics.io/our-editorial-team#rejman) Published January 30, 2024Updated September 1, 2026 On this page - [What’s Generative AI in Finance and Banking?](#whats-generative-ai-in-finance-and-banking) - [Overcoming Banking Challenges with Generative AI in Finance](#overcoming-banking-challenges-with-generative-ai-in-finance) - [Fraud Detection and Prevention](#fraud-detection-and-prevention) - [Personalized Financial Services and Support](#personalized-financial-services-and-support) - [Risk Assessment and Credit Scoring](#risk-assessment-and-credit-scoring) - [Operational Efficiency](#operational-efficiency) - [Compliance and Regulatory Challenges](#compliance-and-regulatory-challenges) - [Market and Investment Analysis](#market-and-investment-analysis) - [How Do Financial Institutions Use Generative AI in Finance?](#how-do-financial-institutions-use-generative-ai-in-finance) - [Morgan Stanley — Supporting Financial Decisions](#morgan-stanley-supporting-financial-decisions) - [Deutsche Bank — Operational Improvements Across the Board](#deutsche-bank-operational-improvements-across-the-board) - [Mastercard — Your Personal Shopping Assistant](#mastercard-your-personal-shopping-assistant) - [Reshaping the Industry with Generative AI in Banking](#reshaping-the-industry-with-generative-ai-in-banking) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) When you think of potential use cases for generative AI, many things may spring to mind, from songwriting to coding, but using the technology in the financial sector most likely isn’t the first of them. However, just like [Chat GPT in healthcare](https://www.flobotics.io/blog/chatgpt-for-healthcare), GenAI has many applications in finance and banking. In fact, we should go one step further to say that generative AI in finance is a dynamically developing field that has created an equally expanding market. It is estimated to [grow at a CAGR of 28.1%](https://marketresearch.biz/report/generative-ai-in-financial-services-market/), reaching a total value of almost $9.5 billion by 2032. The steadily growing valuation proves that GenAI is widely recognized as a vital technology worth investing in. However, there are many other reasons why financial institutions can’t afford to ignore generative AI in banking. In this article, we’ll look into the advantages of GenAI and the challenges it helps address in the [finance and banking industry](https://www.flobotics.io/blog/rpa-for-finance). ## What’s Generative AI in Finance and Banking? As a quick reminder, generative AI, or GenAI, refers to AI-based solutions that use deep learning algorithms to mimic human-like creativity and [produce new content](https://www.veed.io/tools/ai-video/ai-video-editor). The output can range from text and images to music, programming code, and other formats. GenAI has found ample applications in virtually every industry thanks to its capabilities. - Generative AI is used for content production and generating ideas in marketing and creative industries. - In IT, GenAI automates and expedites code writing. - Generative AI also aids healthcare professionals in medical imaging, drug discovery, and personalized treatment. - Additionally, the technology serves general purposes in any sector, such as administrative tasks, customer support, and text processing. And what about the role of generative AI in finance? In the banking sector, its applications range from industry-specific to generic. GenAI is used mainly to help financial institutions overcome existing challenges and advance their services by analyzing financial data and producing reliable outputs faster than human employees could. But more about it in a moment. ## Overcoming Banking Challenges with Generative AI in Finance Belonging to a heavily decision-driven industry, financial institutions have always sought solutions that could lower the risk and margin of error. As one such solution, [AI has a long history of use](https://www.turing.ac.uk/sites/default/files/2019-04/artificial_intelligence_in_finance_-_turing_report_0.pdf) in the banking industry, going back to the ‘80s. But what challenges has it helped address since? ### Fraud Detection and Prevention Credit card information, personal records, bank account details—there’s no shortage of vulnerable data in finance, which makes the sector one of the [primary targets for cyberattacks](https://www.statista.com/statistics/221293/cyber-crime-target-industries/). Data protection is among the top priorities for financial institutions, and generative AI helps them achieve it. Here, GenAI tools are used in tandem with fraud detection algorithms. These algorithms use machine learning (ML) to self-train on past fraud attempt data, but when faced with ever-evolving techniques, they often struggle to keep up. Generative AI finds and replicates patterns in fraud data to create large volumes of synthetic “anomalies”. Synthetic data is then used to refine detection algorithms, allowing them to stay ahead of fraudsters. Consequently, cybersecurity algorithms require less supervision, allowing for a higher level of automation and better efficiency at identifying cyber attack attempts. As a result, the combination of GenAI and fraud detection algorithms prevents financial losses and boosts customer trust. ### Personalized Financial Services and Support According to [J.D. Power’s 2022 U.S. Retail Banking Satisfaction Study](https://www.jdpower.com/business/press-releases/2022-us-retail-banking-satisfaction-study), 78% of consumers expect personalized support from their bank. However, only 44% of them felt that they received it. Personalized services and support can be an important differentiating factor, reflected by the fact that personalization at scale can lead to a [10% increase in yearly revenue](https://www.bcg.com/publications/2019/what-does-personalization-banking-really-mean). Currently, scaling up proves challenging for financial institutions. Providing personalized support and services requires processing vast amounts of customer data: transaction history, spending preferences, financial products, saving goals, and more. Generative AI can use that information to develop custom-made recommendations quickly and offers for each customer, creating cross-selling opportunities for companies and boosting customer satisfaction. Moreover, generative AI for finance enables better self-service through intelligent virtual assistants or automated form submission. Thanks to GenAI, these solutions can faster process data and generate human-like answers, mimicking real customer care agents. With that, customers can receive the help they need much faster, while banks reduce operational costs and improve customer engagement. ### Risk Assessment and Credit Scoring Financial institutions need to evaluate each customer’s creditworthiness and assess potential risks before making lending decisions. Credit scoring is an integral part of this process, and it involves assigning credit scores to individuals or businesses based on their credit history and financial information. Traditional credit scoring and risk assessment methods use historical data and predefined rules. However, these methods are inflexible and may fail to capture credit risk complexity and dynamic nature. Additionally, due to a near-zero margin of error, both processes require constant monitoring and thorough data analysis, which makes them very time-consuming. Here, GenAI is used similarly for fraud detection. Generative algorithms create synthetic data that closely resembles accurate financial data for possible scenarios. Next, it’s compiled with actual data to create datasets for training predictive analytics tools. A more diverse example base refines the analytics engine, making its predictions more accurate. At the same time, GenAI can factor in large volumes of dynamic data, resulting in more reliable and truthful credit scores without excessive manual effort. ### Operational Efficiency As with all forms of [Intelligent Automation](https://www.flobotics.io/rcm-automation), generative AI in finance can save banks thousands of working hours by streamlining routine tasks. Insider Intelligence estimates that [AI-based applications can save financial institutions $447 billion](https://www.insiderintelligence.com/insights/ai-in-finance/). In large part, these savings are generated through reducing human error. GenAI can process large volumes of financial data without overlooking details and produce consistent reports. GenAI can also serve finance professionals as a personal, intelligent assistant thanks to its language interpreting and [content creation](https://www.veed.io/tools/ai-video) capabilities. Fig. 01 · GenAI in finance 10 tasks What a GenAI finance assistant can do - Draft pitch documents and presentations - Summarize long documents - Assess and manage risk - Analyze investments - Retrieve financial documents - Extract data from financial documents - Financial research - Client service - Detect and flag fraud - Compile reports Relaying tedious but necessary daily tasks to GenAI, bankers can devote more time to working directly with clients. As a result, operational efficiency and customer satisfaction increase, generating savings and driving additional revenue. ### Compliance and Regulatory Challenges Regulatory compliance is an essential banking activity linked to risk assessment and human error. Financial institutions are legally obliged to follow regulations covering operations, confidentiality, security, and best practices. Meeting these criteria requires thorough data collection, extensive analyses, and reporting, all of which are prone to errors and highly time-consuming. Banks can offload many of these tasks to GenAI. - Generative AI in finance can produce synthetic data to boost the accuracy of internal compliance controls and quality assurance. - GenAI’s data processing and generating capabilities enable fast, consistent, and error-free compliance reporting. - Generative AI can monitor compliance continuously and send automated notifications to compliance teams when a violation occurs. Overall, generative AI in banking helps financial institutions avoid costly fines, reduce manual effort, and build their reputation as safe and compliant organizations. ### Market and Investment Analysis Financial analysis involves working with large datasets, including market trends, reports, event transcripts, estimates, company filings, etc. To keep up with the shifting financial landscape and spot investment opportunities on time, analysts must monitor all that data continuously, which takes significant time and effort. GenAI algorithms can easily go through vast historical records to identify patterns and anomalies that could go unnoticed by human analysts. Based on automated analysis, generative AI generates insights and creates trading parameters such as optimal entry and exit points for specific financial assets, stop-loss levels, and position sizing. This gives banks a competitive advantage, a better understanding of market conditions, and enables data-driven strategizing. Fig. 02 · GenAI in banking Comparison GenAI and traditional banking processes Process | Traditional method | With GenAI | Fraud prevention | Detection algorithms that must be trained and updated regularly | Generates synthetic training data quickly, cutting upkeep | Personalized services | Heavy data analysis takes advisers away from clients | Scans customer data for recommendations so advisers can prioritize and build trust | Customer care | Chatbots handle simple requests; people solve the rest | Pulls real-time information to help agents and answers complex questions | Compliance | Controls and updates are slow, error-prone and risk penalties | Synthetic data improves monitoring; systems flag non-compliance on their own | Investment analysis | Analysts can miss information in large datasets | Monitors volumes for opportunities; analysts combine reports with their expertise | Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## How Do Financial Institutions Use Generative AI in Finance? Organizations within the finance industry are starting to recognize the benefits of generative AI in banking. Here are some real-life examples of how they do it. ### Morgan Stanley — Supporting Financial Decisions As a major player in the wealth management sector, Morgan Stanley stands at the forefront of innovation in finance. In March 2023, it announced a [strategic partnership with OpenAI,](https://www.morganstanley.com/press-releases/key-milestone-in-innovation-journey-with-openai) granting Morgan Stanley early access to new solutions developed by the GenAI firm. It’s the next step toward wider GenAI adoption, which started beforehand with internally built solutions like Next Best Action. The engine was trained on 100,000 company documents to support Morgan Stanley’s financial advisors and clients through customized financial advice and answers to questions on investment, markets, and internal processes. ### Deutsche Bank — Operational Improvements Across the Board In another big partnership, Deutsche Bank is working with Google to develop [generative AI engines](https://cloud.google.com/blog/products/ai-machine-learning/google-cloud-at-io-2023) and large language models that could provide insights to financial analysts and improve operational efficiency and execution speed. Deutsche Bank’s goals are far-reaching. With the help of GenAI, the bank hopes to expedite processes and financial analysis, increase employee productivity, enhance customer data privacy, and improve overall system security. ### Mastercard — Your Personal Shopping Assistant Mastercard plans to use a GenAI-based shopping recommendation engine for a more customer-oriented example. Shopping Muse will offer personalized product suggestions by analyzing the user’s shopping habits, history, on-site behavior, and retailer’s product catalog. Shopping Muse’s most innovative feature is how it interacts with customers. Its advanced language interpretation functionalities allow shoppers to ask the tool questions in colloquial language to receive personalized shopping advice. Though this example stands closer to the retail industry, financial institutions can use it as an inspiration for enhancing customer experience, support, and engagement through generative AI in banking. ### Reshaping the Industry with Generative AI in Banking With well-established AI systems in the banking and finance sector, it’s time to take it one step further. From personalized care to operational improvements, generative AI creates new opportunities for financial institutions. Now, if your organization needs help in adopting generative AI in finance, you’re in the right place. Just [get in touch,](https://www.flobotics.io/contact) and let’s discuss the future of your business. #### Like the article? Spread the word Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byMichał Rejman Chief Marketing Officer at Flobotics. [More from Michał](https://www.flobotics.io/our-editorial-team#rejman) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ Eligibility ### How Is Robotic Process Automation Disrupting the Banking and Finance Industry? RPA in banking and finance: top reasons automation and financial institutions work well together, with real use cases inside. Filip NasiadkoJanuary 15, 2021 ](https://www.flobotics.io/blog/rpa-in-finance-and-banking)[ RPA ### RPA Reloaded: 50+ Robotic Process Automation Statistics to Know in 2026 RPA statistics 2026: 50+ data points on robotic process automation adoption, ROI, and where the technology is headed next. Yana PokoraApril 15, 2025 ](https://www.flobotics.io/blog/rpa-statistics)[ RPAEligibility ### Bots You Can Bank On | What’s RPA for Finance and What’s in It for You? Finance process automation: how RPA helps banks and financial firms cut manual work in heavily regulated, data-intensive workflows. Filip NasiadkoNovember 21, 2022 ](https://www.flobotics.io/blog/rpa-for-finance) [All articles →](https://www.flobotics.io/blog) --- # Solutions Management Feature in UiPath - How Does It Work? [Dev's Perspective] Canonical: https://www.flobotics.io/blog/uipath-orchestrator-new-features Author: Dominik Put Published: 2024-01-24 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Solutions Management Feature in UiPath - How Does It Work?… [RPA](https://www.flobotics.io/blog?category=rpa) # Solutions Management Feature in UiPath - How Does It Work? [Dev's Perspective] [Dominik PutUiPath-certified RPA developer with extensive experience in automating healthcare, customer service, and HR processes. His keen interest lies in Document Understanding and OCR technologies.](https://www.flobotics.io/our-editorial-team#put) Published January 24, 2024Updated September 1, 2026 On this page - [Solutions Management – Overview](#solutions-management-overview) - [Why UiPath Solution Management?](#why-uipath-solution-management) - [Conclusions](#conclusions) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Transferring data between orchestrators can be quite a challenge. Until now, all assets, triggers, etc. had to be moved manually, which caused a lot of potential errors. But, after all, we work in the intelligent automation industry, right? No surprise, it has to be done more efficiently! Recently, UiPath presented [a new feature](https://docs.uipath.com/solutions-management/automation-cloud/latest/user-guide/solutions-management-overview) for developers who most often work on separate test orchestrators or scale their solutions to new clients. Here is how it works in practice. ## Solutions Management – Overview So. What is a solution? A solution is a package that is a collection of components created and configured on the UiPath platform. It can be a simple, single process or a more complex solution – several processes, applications, and their dependencies. Instead of manually transferring components from the UiPath platform, we can now pack everything into Solutions, manage versions, and deploy it between orchestrators. The tool that UiPath presented was aimed at facilitating the transfer of data. The Solutions Management is available in the Automation Ops tab in the orchestrator. Solutions management combines many components, such as processes, assets, queues, etc., into one package, which can be downloaded and deployed in another target orchestrator. Solutions Builder is an auxiliary tool for creating a package. It also allows editing the package – adding, removing, or modifying components. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Why UiPath Solution Management? Solutions Management helps deal with the following problems: - transferring configured components between orchestrators, - process deployment – the created package in solution management is very easy to deploy in a new environment, which helps to prevent errors in data transfer - management – you can manage your packages by updating and releasing new versions. Packages are created per tenant – when entering the solutions management tab; we first have to choose the tenant for whom we want to create a solution package. To load a solution package, you need to: - go to the management of the solution in the target orchestrator, - select under the appropriate tenant the option “upload solution package”, - choose the right file. Simple as that! Remember that credentials are not transferred between orchestrators, and when deploying a new package, you need to fill in the assets of the Credential type. You can learn more about the Solution Management feature from this video published by UiPath: ## Conclusions I have been eagerly awaiting this feature for a loooong time. I typically use a test orchestrator to trial my automations and then have to manually transfer all the assets, which effectively doubles the workload. Creating a package with a solution is convenient and helps minimize errors. The only limitation is that not all data can be transferred yet. Currently, we can transfer the following data: processes, assets, queues, storage buckets, and triggers. I look forward to expanding the solution to include additional components such as users (including types of permissions), robots, and connected machines – this will make my [UiPath development](https://www.flobotics.io/about-us) even more efficient! UiPath team, I hope you read that;) #### Liked what You've read? Spread the word! At Flobotics we specialize in U.S. healthcare revenue cycle management process automation – no generic bots here. Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byDominik Put UiPath-certified RPA developer with extensive experience in automating healthcare, customer service, and HR processes. His keen interest lies in Document Understanding and OCR technologies.. [More from Dominik](https://www.flobotics.io/our-editorial-team#put) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### UiPath Licensing Simplified: How BPO Makes Automation More Affordable Business process outsourcing for UiPath licensing: cut costs, avoid confusing tiers, and scale automation without overhiring. Karl MielnickiMay 16, 2025 ](https://www.flobotics.io/blog/business-process-outsourcing)[ RPA ### What Does The "UiPath Certified Developer" Title Actually Mean? UiPath Certified Developer title, explained: what the certification actually proves - and what to check before you hire. Karl MielnickiNovember 26, 2021 ](https://www.flobotics.io/blog/uipath-certified-developer-title-meaning)[ RPA ### Specific Content Limitations in UiPath [RPA Developer’s Investigation] UiPath content limitations: Specific Content was removed from Get Queue Items in 2024 - see what fields disappeared and how to retrieve queue data now. Dominik PutMay 21, 2024 ](https://www.flobotics.io/blog/specific-content-limitations-in-uipath) [All articles →](https://www.flobotics.io/blog) --- # Small Effort, Big Impact: What Is RPA Testing, How to Do It & Why It Matters Canonical: https://www.flobotics.io/blog/rpa-testing Author: Bart Teodorczuk Published: 2024-01-02 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Small Effort, Big Impact: What Is RPA Testing, How to Do… [RPA](https://www.flobotics.io/blog?category=rpa) # Small Effort, Big Impact: What Is RPA Testing, How to Do It & Why It Matters [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published January 02, 2024Updated September 1, 2026 On this page - [What is RPA testing, and why is it important?](#what-is-rpa-testing-and-why-is-it-important) - [Improved security](#improved-security) - [Preventing errors](#preventing-errors) - [Quality assurance and improvements](#quality-assurance-and-improvements) - [Better user experience](#better-user-experience) - [RPA testing methods](#rpa-testing-methods) - [RPA testing challenges & how to solve them](#rpa-testing-challenges-how-to-solve-them) - [RPA testing: where to start?](#rpa-testing-where-to-start) - [Bottom line](#bottom-line) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) If you’ve been following our blog for a while, we don’t need to convince you that Robotic Process Automation is rising. But in case you’re new here, here are a couple of RPA stats to help you understand its impact: - By 2025, [4 million RPA bots will perform](https://blog.gitnux.com/rpa-industry-statistics/) various office, administrative, and sales tasks. - The [RPA market value](https://www.statista.com/statistics/1259903/robotic-process-automation-market-size-worldwide/) is expected to reach over $13 billion by 2030. - Companies that adopted RPA report an average of 40% time savings in the first year. But no matter if you’re an automation aficionado or an RPA rookie, one thing can’t be stressed enough: all that advancement wouldn’t be possible without RPA testing. Proper testing reduces the overall cost and effort needed for a successful RPA implementation. Regardless, RPA testing is often neglected by RPA specialists and companies seeking to implement [workflow automation](https://www.flobotics.io/blog/workflow-automation). In this article, we’ll challenge that [false notion](https://www.flobotics.io/blog/medical-billing-management) by defining various types of RPA testing, explaining its role, and listing tools used in the process. ## What is RPA testing, and why is it important? Let’s be honest: complex RPA implementation requires an investment like any other software project. While small, single-process deployments are mostly affordable, license and implementation costs of large automation projects spanning multiple departments and applications may quickly add up. Still, companies agree to pay the price because the productivity boost far outweighs the initial expenditure. Provided RPA is working as intended. If it’s not, the costs will continue to stack up. An RPA bot performs up to thousands of daily instances of the same task. Given this scope, even a single mistake can affect every single execution, generating severe losses before the error is detected. Then, the bot must be fixed, which takes even more precious time. Luckily, there’s an easy way to increase the odds of a fast ROI and prevent costly errors and downtime. Yes, you guessed it: devoting some time before the launch to thoroughly test the bot. What are the benefits of thorough RPA testing that make it a crucial stage of the implementation process? Let’s see. ### Improved security Testing RPA for cyber attacks, tampering, unauthorized access, and other dangers warrants that the automated process is secure and doesn’t put the organization and its members at risk. Identifying weak spots is one thing; another is checking the existing safety measures. Here, RPA testing helps verify if protection features, like logging, monitoring, user authentication, and access control, function correctly and can nullify the threats. ### Preventing errors One of the main advantages of RPA is reducing the margin of error for manual processes. However, this is only attainable if the bot doesn’t replicate or commit its own mistakes. RPA testing allows developers to identify errors early in the development cycle and ensure that the bots run the process consistently. This way, errors can be addressed before the launch, when fixing them becomes more challenging and expensive. ### Quality assurance and improvements Besides bug wrangling, RPA tests are essential to ensure that the RPA solution meets the desired performance standards. By running performance tests, RPA developers can spot inefficiencies before the launch so that the automated process is executed correctly. In some cases, testing the solution can even lead to new discoveries and guide developers toward tweaks that further enhance it. ### Better user experience Sometimes, particularly during more complex implementations, it’s easy to lose sight of how the final solution will be used daily. RPA tests are the perfect opportunity to see how end-users interact with it and ensure that the automated processes are user-friendly. It’s essential in the case of bots that will assist non-technical staff in everyday tasks like document retrieval or data entry. Effectively, RPA testing leads to a better outcome for everyone: - developers, who deliver a more reliable solution that they will require less of their time to maintain; - end-users who enjoy a bug-free and more intuitive tool that expedites cumbersome work; - business owners who see substantial growth in productivity and faster ROI on RPA implementations. Fig. 01 · RPA testing Who benefits RPA testing pays off for everyone - DevelopersStructured workflow, fewer bugs, less post-launch maintenance. - UsersFewer disruptions, shorter downtime, better UX. - OrganizationsFaster ROI, more stability, lower maintenance costs. ## RPA testing methods There are 5 main methods of RPA testing, each with its defined purpose. - Unit testing — In unit testing, the performance of all RPA components and workflows is verified individually in both standard and edge cases. Breaking down the entire solution into smaller units and testing them individually allows automation developers to focus on one functionality or bot action, e.g., clicking a button or filling data fields. Thus, they can easily spot defects in specific areas. - Integration testing — RPA workflows often rely on integrations between the automation platform and one or more business apps. The role of integration testing is to make sure that all third-party systems, APIs, and RPA components involved in the automated process are well-coordinated and can cooperate seamlessly, e.g., when moving data. Integration testing usually takes place once all relevant components have been unit-tested. - Regression testing — RPA development is a gradual process. Constant modifications are necessary, but with each round of changes, there’s a chance that previously working code will crash, produce errors, or otherwise stop functioning. Regression tests focus strictly on these defects. Regression testing can involve other testing methods to pinpoint the change that causes the defect. - Security testing — A separate risk assessment phase that verifies if necessary safety measures (governance, authentication, access control, traceability, etc.) are present and whether automation makes the organization vulnerable to any threats. - User acceptance testing (UAT) — A user-oriented testing method that aims to confirm if the bot is executing the task as intended in terms of performance, usability, and functionality. In the case of attended RPA bots triggered by human employees, UAT also determines how intuitive and practical the automation is to its users. It’s worth noting that since all testing methodologies have a distinct purpose, it’s not a matter of choosing one over another. Each of them has its use at different stages of development, and combining them is the best way to guarantee a secure, stable, and highly-performing RPA automation. Fig. 02 · RPA testing 5 methods What each testing method checks - Unit testingSmall components or sequence steps - Integration testingConnections with other software - Regression testingDefects caused by new changes - Security testingSafety of systems - User acceptance testingUsability and fit with business needs Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## RPA testing challenges & how to solve them Invaluable as it is, RPA testing isn’t free from its challenges. Here are the main obstacles you must consider and how to overcome them. - RPA complexity — Sophisticated, enterprise-wide RPA deployments require significantly more test rounds, scenarios, tools, and methods. You can also work with subject matter experts, RPA consultants, and business analysts to simplify the process, e.g., by double-checking it for unnecessary steps or reducing the number of exceptions. - Costs and scheduling — Though RPA testing is fundamental for effective implementation, thorough checks take time, affecting the project timeline and end budget. Advocate for allocating time and resources for RPA testing right from the start and make sure that all stakeholders are on the same page about its importance. - Improperly defined scenarios — Rather than using generic testing scenarios, select or create cases that are relevant to specific bots. Aim to cover distinct use cases, exceptions, input variations, etc. - Lack of test data — RPA teams often work under strict deadlines imposed by the business teams, which can lead to missing data for some scenarios. Convince your business team that providing test data for all scenarios will go a long way and result in a more stable deployment. - Insufficient business expertise — Misalignment with business objectives is a common pitfall that can be easily avoided by collaborating with a business analyst throughout the testing process. Understanding the business requirements is necessary for verifying if they were met during the development phase. - Using unrealistic data — To check if bots will perform well in real-life scenarios, use datasets that will be relevant to these tasks. Include incomplete and incorrect records to test if the bot can identify missing fields, typos, etc. - Lack of a dedicated test environment — RPA bots usually automate other applications, and often, the client doesn’t have a separate test/sandbox environment to test. Create a dedicated testing environment that matches the production setup to easily isolate issues without affecting the actual automation. - Fragmented testing — While unit testing is vital, don’t forget to ensure the process runs correctly from start to finish through end-to-end testing. Running holistic tests will also help you validate the automation’s business logic, data flow, and usability. - Single testing environment — Unless you’re absolutely sure that your bots will only be used on one platform, verify that they can work on desktop, web, and mobile. Account for version changes and software updates by equipping bots with self-diagnose, reporting, and recovery functionalities. Fig. 03 · RPA testing 5 steps An example testing process - 01Define scopeChoose what to test; split into smaller parts if needed. - 02Prepare dataA dataset like the one the bot will meet in real life. - 03Verify the flowCheck the sequence is error-free and complete. - 04Run the processUse your testing tool to record the run and log errors. - 05Implement or fixAct on the results. ## RPA testing: where to start? Now that you know the basics of RPA testing with its benefits and challenges, it’s time to implement your own testing process. But before you start, here’s a bunch of useful beginner tips: - Build RPA bots with testing in mind — You can (and should) prepare your automation for testing as early as in the planning phase. Assign separate, dedicated workflows to each task, break down processes into small, well-defined blocks, and include logging and reporting functionalities. - List all scenarios — Taking the time to create a simple document or spreadsheet containing all the scenarios will allow you to define the expected behavior of the automation and precisely assess the scope of testing. - Focus on readability — A simple but often overlooked method that facilitates testing, particularly in larger teams. Established naming conventions, adding comments explaining complex workflows, and creating a detailed process definition document will all contribute to easier RPA testing. - Create effective test cases — Test cases should reflect real-life scenarios and cover all outcomes for a given step. Keep test cases independent of each other to prevent incompatibilities and assign one purpose to every test case. - Run and update tests regularly — Once you’re done implementing an RPA testing solution, remember to use it whenever you make a change to a given step (here’s when having small, dedicated workflows comes in handy). Test cases themselves should also be kept up-to-date with all relevant changes. ## Bottom line Between extra post-launch fixes, slower ROI, more downtimes, and defects, cutting corners on proper RPA testing is a minuscule saving that’s not worth it in the long run. Instead of learning it the hard way, use our short guide during your next automation project: test your process multiple times before it goes live with different methods and tools to build an RPA that’s a boost, not a burden. At Flobotics, testing is a mainstay of our RPA development process. Want to talk about that or anything RPA-related? [Give us a call](https://www.flobotics.io/contact). #### Like the article? Spread the word Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### Why Automation Training Is Key to Successful RPA Implementation RPA automation training: why employee training makes or breaks automation adoption, and how to prepare your team for working with bots. Karl MielnickiDecember 03, 2024 ](https://www.flobotics.io/blog/automation-training)[ RPA ### What Should the Model RPA Development and Implementation Process Look Like? RPA development lifecycle: what to expect from an automation implementation partner and the key steps in a successful RPA project. Radek MoczydlowskiJanuary 25, 2022 ](https://www.flobotics.io/blog/rpa-development-process)[ RPA ### Unearthing RPA Potential: What You Need to Know About Task Mining & UiPath UiPath task mining, explained: see how its process-discovery tools help you find and prioritize the best tasks to automate. Bart TeodorczukJuly 28, 2023 ](https://www.flobotics.io/blog/task-mining-uipath) [All articles →](https://www.flobotics.io/blog) --- # UiPath vs. Python? Choosing the Right RPA Tool for Your Automation Job Canonical: https://www.flobotics.io/blog/uipath-python Author: Krzysztof Szwed Published: 2023-12-11 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/UiPath vs. Python? Choosing the Right RPA Tool for Your… [RPA](https://www.flobotics.io/blog?category=rpa) # UiPath vs. Python? Choosing the Right RPA Tool for Your Automation Job [Krzysztof SzwedHead of Delivery at Flobotics](https://www.flobotics.io/our-editorial-team#szwed) Published December 11, 2023Updated September 1, 2026 On this page - [UiPath vs. Python: what are they?](#uipath-vs-python-what-are-they) - [UiPath – the RPA Powerhouse](#uipath-the-rpa-powerhouse) - [Python – Simple and Flexible](#python-simple-and-flexible) - [UiPath vs. Python: How Do They Compare?](#uipath-vs-python-how-do-they-compare) - [UiPath & Python: RPA Features and Capabilities](#uipath-python-rpa-features-and-capabilities) - [Talent Base and Resources](#talent-base-and-resources) - [Pricing](#pricing) - [Which One to Choose?](#which-one-to-choose) - [UiPath — Large-Scale Automation](#uipath-large-scale-automation) - [Python — Small RPA Deployments](#python-small-rpa-deployments) - [UiPath vs. Python: the Complete RPA Toolbox](#uipath-vs-python-the-complete-rpa-toolbox) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) What would you rather use to nail a photo of your baby (or a baby pet) to the wall? A pneumatic drill or a good old hammer? This question doesn’t seem so absurd when you think that the right tool makes a huge difference in both home improvements and [Robotic Process Automation](https://www.flobotics.io/blog/robotic-process-automation). And just as there are numerous utensils in one’s DYI kit, many RPA tools serve various businesses, goals, and needs. At Flobotics, we mainly use those two RPA technologies: UiPath & Python. How do they differ? What use cases do they excel at? Which one’s the drill, and which one’s the hammer? Let’s find out. ## UiPath vs. Python: what are they? ### UiPath – the RPA Powerhouse Founded in 2005, [UiPath](https://www.uipath.com/) has become a household name in the automation industry. It is consistently named an RPA leader in the yearly [Gartner RPA Magic Quadrant report](https://www.gartner.com/en/documents/4016876) and for plenty of good reasons. UiPath boasts a full set of automation discovery, management, monitoring, and testing features packed in a user-friendly interface suited for non-technical users. ### Python – Simple and Flexible Python is an interpreted, open-source programming language known for its flexibility. Thanks to its accessibility and customizability, it’s become one of [the most popular programming languages](https://madnight.github.io/githut/#/pull_requests/2023/3), with readily available libraries and modules for all purposes—including automation. Another thing that makes Python so successful is its simplicity and applicability to repetitive tasks. Data operations, web scraping, processing spreadsheets, moving files, and similar tasks are all good candidates for Python RPA automation. ## UiPath vs. Python: How Do They Compare? As you can see, all three solutions are either made with RPA in mind or can be applied to automation. What makes them different? That’s where we go back to our intro: the difference lies in which one is a drill and which is a hammer. ### UiPath & Python: RPA Features and Capabilities The primary consideration when choosing RPA tools is what they are capable of. What are the standout features of UiPath and Python? #### UiPath Features As a leading RPA platform, UiPath has much to offer regarding features, which fall into three categories: - Discover (identifying automation opportunities), - Automate (RPA development and implementation), - and Operate (analytics, management, and monitoring). These categories encompass a broad selection of automation-related tools, such as [task](https://www.uipath.com/platform/discover/task-mining) and [process mining](https://www.uipath.com/platform/discover/process-mining), AI-based features like [intelligent document processing](https://www.uipath.com/platform/automate/intelligent-document-processing-and-specialized-ai) or [GPT functionalities](https://www.uipath.com/platform/automate/generative-ai-and-experiences), ROI and [KPI analytics, and visualization](https://www.uipath.com/platform/operate/real-time-and-trend-analytics). To help these functionalities connect seamlessly to the rest of your applications, UiPath has over 1,400 integrations with various software, such as [Google Cloud](https://www.flobotics.io/blog/uipath-vs-gcp) or Microsoft apps, all available on [the UiPath Marketplace](https://marketplace.uipath.com/). UiPath is well-suited for automating modern software and legacy platforms. It offers many ways to integrate with older apps, including computer vision and useful tools such as application mapping. Thanks to that and all its out-of-the-box features, UiPath allows you to automate virtually any process in any software. #### Python Features - On its own, Python is as barebone as an RPA tool can be, which is both good and bad. If you opt for Python, you’ll need a custom setup and development, including tools for post-deployment activities like analytics, monitoring, and management. - On a positive note, thanks to the many libraries and modules available, Python allows you to build automations that fit your needs like a glove… - … as long as you want to automate a newer, web-based app. Desktop apps and software not designed with automation in mind can be more tricky or even impossible to automate using Python. - As an interpreted, dynamically typed language, Python allows for rapid prototyping and iterating. This allows developers to quickly adapt the code to changing business conditions and remove bugs in automation. - Finally, Python is relatively easy to learn compared to other programming languages. It is less accessible to non-programmers than the other two tools but allows faster adoption by users who already work with Python. Fig. 01 · UiPath vs Python Key features UiPath and Python: key features UiPath - Scalability - Accessibility - Task and process mining - Integrations - Orchestrator - Drag-and-drop interface - AI features Python - Flexibility - Simplicity - Fast prototyping and iteration - Community - Open source - Libraries and modules ### Talent Base and Resources Ironically, automation cannot be implemented and maintained without the right people. Thus, the availability of developers and training materials is just as important as the RPA platform’s technical capabilities. #### UiPath Developers and Resources While finding [certified UiPath developers](https://www.flobotics.io/uipath-services) isn’t as easy as in the case of Python, UiPath is doing its best to train users on how to use the platform: - Automation adepts may enroll in one of the RPA courses in the UiPath Academy, while more experienced [UiPath developers](https://www.flobotics.io/about-us) can find specific answers in the vast documentation library. - There’s also the bustling community forum, responsive customer support, events, webinars, and more. - It’s also worth mentioning that using automations daily is easy to learn thanks to the intuitive user-facing interface. Once set up, everyday use doesn’t require coding knowledge. #### Python Developers and Resources Python’s popularity gives it a big advantage over other tools regarding the developer pool. There’s no lack of devs with Python expertise, including specifically in automation. Thanks to that, you can be picky and target candidates with additional strengths, such as good soft skills or experience in your industry. ### Pricing Price is the final decisive factor – although, for many organizations, RPA cost may actually be the first thing to consider. #### UiPath Pricing Most of the time, UiPath will be the most expensive tool of the three. The license is billed monthly, with Pro plans starting at $420 monthly and Enterprise plans priced individually. There’s also a free plan that offers limited, basic features. It’s worth noting that lower operational costs partially mitigate the relatively high entry cost of UiPath. Since the platform has everything you need, no custom development is required to get it up and running. To give you a better idea of the costs, a sample project that involves one runtime and allows to automate 10-15 processes would cost roughly $14,400 per year. #### Python Pricing A free, open-source programming language, Python has no license price. The only cost is the developer’s salary. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Which One to Choose? Now that you better understand all three tools let’s see which ones fit specific automation projects. ### UiPath — Large-Scale Automation All things considered, UiPath is an automation powerhouse—or a pneumatic drill, to continue with our analogy. The number of features, integrations, scalability, support, and educational resources justifies its relatively high cost. That’s why UiPath will deliver the best ROI in bigger automation projects. - The perfect use case would encompass automating multiple processes (e.g., 6 or more) within a department or even across the company that involves many business tools and applications, including legacy software. - UiPath’s built-in control functionalities, such as Orchestrator, Automation Suite, or Insights, facilitate managing and maintaining the deployed automations regardless of scale. Out of the three solutions, we believe that UiPath is the best for post-implementation automation management and monitoring. - Another advantage of UiPath for large organizations is its accessibility for the end user. With its intuitive drag-and-drop interface, low-code features, and wealth of instructional materials, non-technical employees can easily operate automated tasks, build their own automations, or even participate in monitoring and management processes. - Scalability and company size were two of the main reasons why we chose UiPath to help mortgage banker Paramount Residential Mortgage Group (PRMG) with [loan process automation](https://www.flobotics.io/case-studies). As a result, PRMG saves 40 working hours per day and $2 million yearly. - Finally, larger deployments create more opportunities to use all advanced features fully. For smaller or less complex projects, sophisticated functionalities may be overkill and end up unused. In these cases, one of the other tools may be more suitable. Fig. 02 · UiPath Pros and cons UiPath: pros and cons Pros - Extensive features - Excellent monitoring and management - Easy to use - Mature platform - Integrations Cons - License cost ### Python — Small RPA Deployments Overall, Python is an extremely flexible tool—and one that you’ll have to assemble by yourself. It works best when you need it to automate one task and one task only so that you can take advantage of its customizability while nullifying its weaknesses. - Small, single-purpose deployments that won’t require you to build complex yet user-friendly monitoring and management systems. In larger RPA projects, these tasks are often partially relegated to non-technical staff, but with Python, business users would find them difficult without programming knowledge. However, if there are only a few processes to monitor, the job can be handled by a single developer. - It’s also important to consider app integrations. Although Python is flexible, the older the software you want to automate, the harder it will be to find the right integration libraries. Ensure your target applications are modern, web-based, or have APIs to facilitate communication with Python. - Due to potential development complexities, carefully selecting the most promising processes to automate is particularly important in the case of [Python automation](https://www.flobotics.io/rcm-automation). For maximum gains, aim for very time-consuming processes (e.g., with a volume of over 100,000 transactions per month). A good example is patient data transfer, and [insurance claims automation](https://www.flobotics.io/case-studies) we built for healthcare software provider SuperBill. With the use of Python-based RPA bots, SuperBill is now able to process 4000 patients each day. Fig. 03 · Python Pros and cons Python RPA with Robocorp: pros and cons Pros - Python-based - Interface - Built-in monitoring and management tools - Developer tools - More accessible than plain Python Cons - May still need coding - Lacks advanced features ## UiPath vs. Python: the Complete RPA Toolbox Fig. 04 · UiPath vs Python Comparison UiPath vs Python: how they compare | UiPath | Python | Features | Full set of automation, monitoring and management features | None built in; add them with existing modules | Scalability | Best | Lowest | License costs | Yes | None | Operating costs | Low: monitoring and management are built in | Fairly high, due to custom development | Ease of use for non-developers | Easy: many no-code modules | Coding required | Talent pool | Solid | Large | Training resources | UiPath Academy, certifications, videos, docs, community | Many free tutorials and courses from users | Best for | Large, enterprise-wide deployments across many processes and apps | Not suited to desktop automation | As you can see, none of the three automation platforms is inherently bad; there are only wrong ways to use them. UiPath and Python can hugely boost efficiency and reduce manual workloads depending on the context and your needs. At Flobotics, we use the full RPA toolkit to address any business inefficiencies best. Not sure which platform is the best fit for your organization? [Schedule a call with us](https://www.flobotics.io/book), and we’ll help you choose and implement the RPA tool that will elevate your productivity. #### Like the article? Spread the word At Flobotics we specialize in U.S. healthcare revenue cycle management process automation – no generic bots here. Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byKrzysztof Szwed Head of Delivery at Flobotics. [More from Krzysztof](https://www.flobotics.io/our-editorial-team#szwed) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### UiPath vs. Power Automate - Which RPA Tool To Choose? UiPath vs. Power Automate: compare features and pricing to decide which RPA tool best fits your 2026 process automation needs. Bart TeodorczukJune 27, 2022 ](https://www.flobotics.io/blog/uipath-vs-powerautomate)[ RPAAI ### UiPath vs. Celonis vs. Kyp.ai: Comparing Top Task Mining Tools UiPath vs. Celonis vs. Kyp.ai: features and pricing compared to help you pick the right task mining tool for 2026. Bart TeodorczukNovember 20, 2023 ](https://www.flobotics.io/blog/uipath-vs-celonis-vs-kypai)[ RPA ### UiPath vs. Automation Anywhere: Choose Your Perfect RPA Tool UiPath vs. Automation Anywhere: compare features and capabilities to find the right RPA platform for your organization. Bart TeodorczukSeptember 07, 2022 ](https://www.flobotics.io/blog/uipath-vs-aa) [All articles →](https://www.flobotics.io/blog) --- # Effective Naming Conventions in UiPath: A Comparative Analysis Canonical: https://www.flobotics.io/blog/naming-conventions-uipath Author: Maciek Matuszczak Published: 2023-12-03 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Effective Naming Conventions in UiPath: A Comparative… [RPA](https://www.flobotics.io/blog?category=rpa) # Effective Naming Conventions in UiPath: A Comparative Analysis [Maciek MatuszczakSenior RPA Developer at Flobotics](https://www.flobotics.io/our-editorial-team#matuszczak) Published December 03, 2023Updated September 1, 2026 On this page - [Object repository: overview](#object-repository-overview) - [Library](#library) - [Business naming convention](#business-naming-convention) - [Conclusions](#conclusions) - [What to avoid?](#what-to-avoid) - [Summary](#summary) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Using effective naming conventions is vital for clear code, teamwork, and debugging. It also plays a crucial role in maintaining automation scripts and frameworks. This article discusses an approach to naming and folder structure in a UiPath library project with an Object Repository. It provides insights for automation engineers and teams looking to improve their [RPA](https://www.flobotics.io/blog/robotic-process-automation) practices. Let’s analyze the approach used at Flobotics, considering its pros and cons and identifying what to avoid! ## Object repository: overview An Object Repository is a part of a Library project that enables the creation of a set of reusable user interface elements. The Object Repository ensures the management, reusability, and reliability of UI elements by capturing them as objects in a DOM-like repository, shareable across projects. It allows for creating and reusing UI taxonomies inside and across automation projects. Some key features of the Object Repository include: - UI elements across the project are managed, updated, and modified from a centralized place - Drag-and-drop elements from the Object Repository panel - Objects are reusable in a local project or across projects when packaged as libraries These key features are why, at Flobotics, we employ the Object Repository as a project practice. In the next step, we will show the practical implementation of the theoretical assumptions. We will present internal principles, naming conventions, and a specific usage example. Before we started building the nomenclature standard, we assumed that the application operates in a single web browser. A developer should include this information in the project description. The current approach used in Flobotics follows the naming scheme: Application -> [Application name] Example: NameCRM Screen -> [Screen name] Examples: Login PPList Element -> [Element type]_[Element name] (For dynamic selectors, it is recommended to add the prefix “Dyn” to increase readability.) Examples: Button_Login Link_Dyn_SettlementId Checkbox_PPRow [OPTIONAL] Group -> Group_[Group name] Examples: Group_MessageBox Group_Common A screenshot showing the object repository project According to the assumption, using the object repository should make work easier. In the chosen naming convention, we prioritize simplicity and clarity. For more complex elements, we suggest adding a description to the element. ## Library A library is a project that contains one or more workflows that can be reused as activities in other projects. Libraries are saved as NUPKG files when published and can be installed as dependencies from the Package Manager. When creating a library, it’s advisable to follow the same principles we employ for the Object Repository. The names of individual tree elements should be precise and clear. It’s crucial to define and establish the project structure early on, even for complex applications. Changing the workflow name or path affects the project using the library. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Business naming convention In the diagram below, we have introduced an approach that is consistent with the expectations discussed in the previous chapter. The naming convention is business-oriented: Folder -> [Application name]_[Screen name] Example: NameCRM_Login Workflow -> [Screen name]_[Action name] Example: SettlementList_ClickClearFilter SettlementList_FillPPNumber A screenshot showing the library project ## Conclusions Let’s now explore the approach’s pros and cons, which we have drawn from observations and practical use. Fig. 01 · Naming Pros and cons The Flobotics way of naming: pros and cons Pros - Clear, understandable and intuitive - Element names, structure and the object repository can be changed freely - You can add logical screens that are not separate windows (message boxes, pop-ups, forms) - Activities are named by business function, not technical function - An activity is not limited to one item - Developers do not need full knowledge of the application Cons - Naming can become inconsistent in complex applications - A developer has to open the activity to see exactly which element it uses ## What to avoid? In this article section, we’ll discuss what to avoid when setting up the Object Repository and library: - A technical approach in which activity names do not reflect the business context, - Repetitive xaml names – Click.xaml, Click.xaml, Click.xaml, hard to work on and easy to get wrong, - Restrictions on use, approach in which we can not add more than one action to the activity, - The naming convention that causes difficulty in navigation when building a process – filtering by name returns a lot of similar results, - Artificial granularity of activities, for example, where one activity is responsible for inputting values (Type into), and another is for verifying execution (Check App State, Get text). ## Summary The proposed naming convention approach has met the Object Repository and library project objectives. Clarity, ease of use, and maintainability of such projects should be a priority. We have applied this approach, demonstrating its versatility in various projects. It has proven effective on both small and large scales. If you are eager to delve deeper into UiPath’s features, consider exploring our article on task mining capabilities in UiPath. Additionally, you can gain valuable insights by comparing UiPath with other automation tools such as [Blue Prism,](https://www.flobotics.io/blog/blueprism-vs-uipath) [Power Automate](https://www.flobotics.io/blog/uipath-vs-powerautomate), or [Google Cloud](https://www.flobotics.io/blog/uipath-vs-gcp). Stay informed and empowered in your automation journey. #### Like the article? Spread the word At Flobotics we specialize in automating processes that mattersmost in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byMaciek Matuszczak Senior RPA Developer at Flobotics. [More from Maciek](https://www.flobotics.io/our-editorial-team#matuszczak) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### What Does The "UiPath Certified Developer" Title Actually Mean? UiPath Certified Developer title, explained: what the certification actually proves - and what to check before you hire. Karl MielnickiNovember 26, 2021 ](https://www.flobotics.io/blog/uipath-certified-developer-title-meaning)[ RPA ### UiPath vs. Automation Anywhere: Choose Your Perfect RPA Tool UiPath vs. Automation Anywhere: compare features and capabilities to find the right RPA platform for your organization. Bart TeodorczukSeptember 07, 2022 ](https://www.flobotics.io/blog/uipath-vs-aa)[ RPA ### Specific Content Limitations in UiPath [RPA Developer’s Investigation] UiPath content limitations: Specific Content was removed from Get Queue Items in 2024 - see what fields disappeared and how to retrieve queue data now. Dominik PutMay 21, 2024 ](https://www.flobotics.io/blog/specific-content-limitations-in-uipath) [All articles →](https://www.flobotics.io/blog) --- # UiPath vs. Celonis vs. Kyp.ai: Comparing Top Task Mining Tools Canonical: https://www.flobotics.io/blog/uipath-vs-celonis-vs-kypai Author: Bart Teodorczuk Published: 2023-11-20 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/UiPath vs. Celonis vs. Kyp.ai: Comparing Top Task Mining… [AI](https://www.flobotics.io/blog?category=ai)[RPA](https://www.flobotics.io/blog?category=rpa) # UiPath vs. Celonis vs. Kyp.ai: Comparing Top Task Mining Tools [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published November 20, 2023Updated September 1, 2026 On this page - [UiPath vs. Celonis vs. Kyp.ai: integrations](#uipath-vs-celonis-vs-kyp-ai-integrations) - [UiPath](#uipath) - [Celonis](#celonis) - [Kyp.ai](#kyp-ai) - [UiPath vs. Celonis vs. Kyp.ai: features](#uipath-vs-celonis-vs-kyp-ai-features) - [UiPath](#uipath-2) - [Celonis](#celonis-2) - [Kyp.ai](#kyp-ai-2) - [UiPath vs. Celonis vs. Kyp.ai: customer support](#uipath-vs-celonis-vs-kyp-ai-customer-support) - [UiPath](#uipath-3) - [Celonis](#celonis-3) - [Kyp.ai](#kyp-ai-3) - [UiPath vs. Celonis vs. Kyp.ai: industries](#uipath-vs-celonis-vs-kyp-ai-industries) - [UiPath vs. Celonis vs. Kyp.ai: pricing](#uipath-vs-celonis-vs-kyp-ai-pricing) - [The verdict? You be the judge - but we can help](#the-verdict-you-be-the-judge-but-we-can-help) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) In [the previous article](https://www.flobotics.io/blog/task-mining-tools) in our mini-series, we recapped the basics of task mining, listed its benefits, and gave some examples of use cases across different industries. We also named and briefly characterized the three solutions we consider the leading task-mining tools: [UiPath](https://www.uipath.com/product/task-mining), [Celonis](https://www.celonis.com/insights/topics/what-is-task-mining), and [Kyp.ai](https://kyp.ai/platform/). Now, it’s time to see how they stack up against one another in a direct UiPath vs. Celonis vs. Kyp.ai comparison. Let’s start with a bit of a spoiler: there’s no single best task-mining tool. All three options below can perform advanced task-mining processes and boast robust features. So, instead of trying (and failing) to choose “the best” task mining tool, we compared them in several key areas that every business must consider before opting for any task mining solution. Our UiPath vs. Celonis vs. Kyp.ai showdown will allow you to select the one that best fits the current needs of your business. ## UiPath vs. Celonis vs. Kyp.ai: integrations Since task mining tools should be closely knit with the software your workforce uses daily, bridging the gap between task mining platforms and the rest of your tech stack is essential. Let’s see how the three tools fare when it comes to integrations. ### UiPath As UiPath is primarily an RPA platform, its task and process mining solutions have an in-built integration with RPA and other automation tools the suite offers. Users can set up integrations with third-party platforms in the UiPath Integration Service using pre-built API connectors. UiPath’s connector library has dozens of official integrations to connect the platform with popular enterprise tools like Google Workspace, Confluence, Salesforce, NetSuite, and more. In case a connector for an app is missing from the library, users can create and share custom ones in Connector Builder. Recorded applications are selected on a per-project basis by the project admin. UiPath can extract data from various external sources, including enterprise application integration platforms like MuleSoft or IBM App Connect, Business Process Management (BPM), or cloud-based integration software. Another option is to record user activity on selected websites, e.g., company CMS or internal portals. However, while [UiPath task mining ](https://www.flobotics.io/blog/task-mining-uipath)integration capabilities are vast compared to the two next contenders, some of these connections may require considerable effort and the assistance of [UiPath developers](https://www.flobotics.io/uipath-services). ### Celonis Celonis provides an advanced data merger, conversion, modification, and management suite that integrates with major business applications, suites, and databases. These include ERP and CMS systems and business collaboration solutions (like SAP, Salesforce, Oracle, and Google Suite). It also has connectors to integrate with RPA bots. Users can set up connections in its Execution Management System by importing out-of-the-box templates from Celonis Marketplace or by creating a new one from scratch. Still, Celonis makes it necessary to integrate each source system separately due to the tool’s robust architecture. Effectively managing various connection types can entail investment in data engineering for the merging and setup phase. ### Kyp.ai Kyp.ai has been specifically designed for rapid deployment and easy integration. With the PLUG-AND-ROI philosophy embedded in its architecture, the solution swiftly integrates with the same business apps as its peers while also providing effortless integrations with chatbots, RPA bots, NLP predictive analytics systems, and other components. In line with the latest automation trends, Kyp.ai takes a no-code approach to integration. This allows easier implementation and integration and grants non-programmer users the ability to adapt the tools to shifting business needs. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## UiPath vs. Celonis vs. Kyp.ai: features UiPath, Celonis, and Kyp.ai are all capable of monitoring user interactions. The differences lie in how they do it, what features they offer beyond that, and what they allow you to do with the findings of task mining. ### UiPath - Assisted and unassisted task mining: UiPath allows users to capture variations of known tasks (assisted task mining) or discover potential improvements based on AI insights (unassisted task mining). - Process mining: Besides capturing user interactions, UiPath allows you to zoom out and analyze end-to-end business processes, visualize them, and optimize performance. - Communications Mining: A discovery tool dedicated to analyzing all business communications to improve them through AI and large language model automation. - Automation Hub: A central dashboard for collecting and managing all automation opportunities and ongoing RPA projects. - In-built RPA and automation support: Being primarily an RPA platform, UiPath makes it easy to turn insights generated with task mining into automation projects seamlessly. The entire process, from discovery to [RPA implementation](https://www.flobotics.io/rcm-automation), takes place on a single platform. UiPath Automation Hub allows you to manage all discoveries and automation projects in one location. (image source: UiPath) ### Celonis - Process mining: As a leader in process mining, Celonis focuses on granting users maximum visibility into their processes through its business intelligence features. - Team Insights: A dashboard that calculates metrics such as uptime or productivity for individual groups of predefined users, e.g., teams, regions, or roles. - Conformance checking: This feature enables users to compare their current process to the reference model representing the intended outcome to identify deviations and set goals. - Process simulation: By creating a [process digital twin](https://www.celonis.com/blog/what-is-a-digital-twin-the-answer-is-evolving-due-to-process-mining/), users can create and test various scenarios to choose the improvements that warrant the best possible outcome. - Live Event Monitor: Shows data captured by the Task Mining Client in real-time, helping users verify if records are collected correctly. - Automatic task documentation: Task Mining Client creates step-by-step instructions by recording user actions, including variations. Celonis users can easily assess and compare team productivity in Team Insights. (image source: Celonis) ### Kyp.ai - Process mining: Kyp.ai leverages automation and AI to discover, map, and document business processes, variations, and bottlenecks at scale. - Generative AI potential detection: Kyp.ai assists businesses in identifying gen AI use opportunities and finding high-gain scenarios for its application. - People Excellence: A workforce-oriented solution that helps organizations detect and reduce productivity-affecting distractions, repetitive tasks, and passive work time. - Activity Heatmap: A visual matrix that shows repetitive operations performed between each app (e.g., copy-pasting between documents and spreadsheets) to help you find the best automation candidates. - Technology Excellence: With this feature, Kyp.ai allows businesses to examine their hardware, software, and network use as processes are executed, enabling performance and cost optimization. Activity Heatmap is an easy way to spot inefficient activities across all used applications in Kyp.ai. (image source: Kyp.ai) ## UiPath vs. Celonis vs. Kyp.ai: customer support Making the best use of discovery tools in specific business cases can be difficult. Luckily, all three vendors offer ways to help you fix issues and make the most out of their solutions. ### UiPath UiPath offers extensive customer support available on its [support hub](https://www.uipath.com/support). It features product documentation and guides, support team contact information, FAQ, and [UiPath’s Academy](https://www.uipath.com/rpa/academy), focusing on delivering free RPA courses. The users can also head to the community forum to ask and answer peer questions and check out the user blog. ### Celonis Apart from the standard contact form and assistance from a sales representative, Celonis can also boast a [robust community of users](https://www.celopeers.com/s/?language=en_US) who provide peer-to-peer support, as well as its own [Celonis Academy](https://academy.celonis.com/), featuring over 400 hours worth of educational content about task and process mining and the product itself. The academy can be used for self-study learning but also provides certification opportunities. Most of the content is free of charge. ### Kyp.ai As a developing company, Kyp.ai primarily provides support through its [partner network](https://kyp.ai/partners/). Therefore, it focuses greatly on partner training and mentorship through a resource hub, certification program, and product webinars that help its partners keep their finger on the pulse of the product’s constant innovations. ## UiPath vs. Celonis vs. Kyp.ai: industries In recent years, automation has made significant inroads into all major industries, driving the demand for task mining services. As highly flexible process and task mining solutions, UiPath, Celonis, and Kyp.ai can all be applied in any sector. However, based on our research and information shared by vendors, each excels in certain areas. Fig. 01 · Task mining Industries Where each tool is strongest UiPath - Finance - Accounting - HR - IT - Manufacturing - Healthcare - Insurance - Public sector - Retail - Telecom Celonis - Banking - Consumer goods - Healthcare - High tech - Insurance - Life sciences and pharma - Manufacturing - Oil and gas - Public sector - Telecom - Retail - Utilities KYP.ai - Customer service - Order management - Finance - Supply chain - Master data management - Procurement - IT support - HR ## UiPath vs. Celonis vs. Kyp.ai: pricing Last but not least, there’s the cost factor. The price of the task mining tool determines how scalable it is and its availability to organizations of different sizes. Fig. 02 · Task mining Pricing Pricing compared - UiPath $100–$500 per user a monthEnterprise plan, on average, depending on the number of licenses. - Celonis $100–$500 a year (basic plans)From a free starter plan to custom enterprise pricing, depending on contract and company size. - KYP.ai Price not publishedQuotes come through partners as part of their project offering. ## The verdict? You be the judge - but we can help When you’re about to invest significant money and resources to make a far-reaching positive impact on the productivity of your business, knowing your options is crucial. But in the end, choosing the best task-mining tool for your organization comes down not only to understanding the available tools but also your needs. So, if you’re in doubt, we’re here to help. We can assess your processes, advise you on the [task mining opportunities,](https://www.flobotics.io/business-process-automation) and help you pick the solutions that will jump-start the digital transformation of your business. [Let’s talk!](https://www.flobotics.io/contact) #### Like the article? Spread the word Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPAAI ### Task Mining Tools Explained: Benefits, Use Cases and Leading Options Task mining tools introduced: an overview of UiPath, Celonis, and Kyp.ai to help you pick the right software for automation discovery. Bart TeodorczukNovember 20, 2023 ](https://www.flobotics.io/blog/task-mining-tools)[ RPA ### Unearthing RPA Potential: What You Need to Know About Task Mining & UiPath UiPath task mining, explained: see how its process-discovery tools help you find and prioritize the best tasks to automate. Bart TeodorczukJuly 28, 2023 ](https://www.flobotics.io/blog/task-mining-uipath)[ RPA ### Process Mining vs RPA: How They Work Together to Improve The Efficiency of Your Business Process mining and RPA: how combining the two turns automation candidates into measurable efficiency gains for your business. Bart TeodorczukJanuary 30, 2023 ](https://www.flobotics.io/blog/process-mining-automation) [All articles →](https://www.flobotics.io/blog) --- # Task Mining Tools Explained: Benefits, Use Cases and Leading Options Canonical: https://www.flobotics.io/blog/task-mining-tools Author: Bart Teodorczuk Published: 2023-11-20 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Task Mining Tools Explained: Benefits, Use Cases and… [AI](https://www.flobotics.io/blog?category=ai)[RPA](https://www.flobotics.io/blog?category=rpa) # Task Mining Tools Explained: Benefits, Use Cases and Leading Options [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published November 20, 2023Updated September 1, 2026 On this page - [Task mining: Everything you need to know](#task-mining-everything-you-need-to-know) - [Understanding Task Mining Tools](#understanding-task-mining-tools) - [What task-mining tools are out there?](#what-task-mining-tools-are-out-there) - [How Task Mining Tools Help Improve Business Processes](#how-task-mining-tools-help-improve-business-processes) - [Focus on UiPath vs. Celonis vs. Kyp.ai](#focus-on-uipath-vs-celonis-vs-kyp-ai) - [UiPath. Key Features and Benefits](#uipath-key-features-and-benefits) - [Celonis. Key Features and Benefits](#celonis-key-features-and-benefits) - [Kyp.ai. Key Features and Benefits](#kyp-ai-key-features-and-benefits) - [Conclusion](#conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Let’s return to the groovy era and imagine ourselves in a typical office in the 1970s. Your employees probably punch a clock in the morning and out when they’re done. Then, you do multiple daily rounds, closely supervising their work. Each week, you sit down to review their work logs and notes detailing all activities performed and tasks completed. These methods, while trust-based, made it challenging to obtain reliable data on employee activities. They were also heavily manual, involving a lot of effort on the employee’s and employer’s side while leaving plenty of room for error and omission. Fortunately, today, [task mining](https://www.flobotics.io/business-process-automation) makes it possible to achieve 99% accuracy in tracking teamwork efficiently. The only question remains, “Which task-mining solution should I go for?” In our two-article series, we’ll help you make the optimal choice by reviewing and comparing task mining tools like UiPath, Celonis, and Kyp.ai, and learning how to use them to support your teams better. Let’s begin by covering the basics of task mining and briefly looking at some leading solutions. ## Task mining: Everything you need to know Task mining is a technology-driven approach that traces and analyzes user interaction data to optimize task efficiency. These user interactions include employees’ activities on their computers, mobile devices, and software applications to accomplish assigned jobs, such as keystrokes, mouse clicks, or data input. Contemporary task mining tools combine them with various techniques, including optical character recognition (OCR), heat maps, natural language processing (NLP), and machine learning algorithms to interpret user actions and recommend improvements to optimize task execution and make it faster, more efficient, and streamlined. Task mining or process mining. What’s the difference? When we employ task mining tools to whole processes, not just individual tasks, we speak of process mining, which typically uses a broader scope of data sources than just user interactions, also ingesting data from ERP systems, CRM tools, Product Information Management platforms (PIM), and other software. In addition, process mining aims to discover, visualize, and evaluate the actual processes as they occur, helping organizations understand how tasks are related and where that relationship underperforms. Meanwhile, as already mentioned, task mining is primarily concerned with analyzing and optimizing the execution of specific tasks. ### Understanding Task Mining Tools Since task mining is an automated procedure, we need software that executes it. Many applications help record and analyze user interactions by scraping desktop or mobile device-level events from individual or cohort workstations. Depending on the technologies they draw from, they can be more or less advanced. For example, some older-generation, basic task-mining tools gather basic information based on mechanical user interactions like clicks, scrolls, screenshots, and time stamps. Advanced, AI-based solutions employ artificial intelligence to go deeper and capture information from the workstation and screens, offering a more detailed, insightful analysis of user activity. ### What task-mining tools are out there? There’s full steam ahead for [the task mining tools market](https://www.everestgrp.com/press-releases/task-mining-software-market.html), growing at 85-95% yearly, so competition is ripe, with new players coming each year. The leaders of dozens of task- and process-mining applications include [UiPath](https://www.uipath.com/platform/discover/task-mining), [Celonis](https://www.celonis.com/process-mining/what-is-task-mining/), [Kyp.ai](https://kyp.ai/), IBM Process Mining, Fluxicon Disco, and Process 360 Live. In this and the next article, we focus on the first three. And why this choice? UiPath is the first platform that combines task mining capabilities with RPA (Robotic Process Automation); Celonis is [a leading process management platform](https://www.celonis.com/blog/celonis-a-leader-in-process-mining-assessment/) with a revenue of $365 million in 2023 and over 1,000 customers worldwide. Finally, Kyp.ai is a truly ingenious proposal heavily relying on the latest automation trends and AI innovations. We will analyze the three competitors closely in a second, but first, let’s see how they can generally make a meaningful difference to your tasks and processes. ## How Task Mining Tools Help Improve Business Processes Task mining tools help optimize each step of process analysis by identifying inefficiencies and bottlenecks in individual tasks. Then, the compounded effect of task optimization enhances the entire process flow. Regarding business process analysis and optimization, task mining tools particularly help with: - Enhancing workflow visibility. Task mining makes work more transparent. This makes it easier to spot inefficacies and eliminate them from workflows. Simplified workflows, on the other hand, lead to better process efficiency. - Measuring performance. One of the key functions of task mining is assessing and analyzing task execution to get insights into how individual performance can be improved. Again, when this happens, and employees improve their outcomes on the task level, it will positively affect the entire process. - Reducing process gaps. Analyzing a team’s task efficiency helps capture areas that require revision and optimization. By extension, these will help eliminate process defects. - Impacting process improvements. One example may be data entry. If you use task mining to pinpoint why it takes so long and then apply automation to speed it up, all the following tasks in the process will see faster execution. Same with quality assurance. Rooting out quality issues thanks to task mining enhances quality at a task level. This naturally improves the quality of the whole process and reduces the time and effort spent on retroactive problem-solving. Fig. 01 · Task mining 6 benefits The benefits of task mining tools - Higher productivityFinds bottlenecks, repetitive tasks and unnecessary steps. - Time savingsTeams save large amounts of time. - Better complianceTransparency and early risk detection. - Lower costsManagers remove inefficiencies without hurting service. - Less excess workloadMore efficient workflows free people for higher-value work. - Happier employeesNo more tedious, unfulfilling tasks. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Focus on UiPath vs. Celonis vs. Kyp.ai Now that we’ve covered some basic information about task mining technology and tools let’s dig into specific solutions to give you an exact view of what you might expect from task mining. We will see how UiPath v. Celonis v. Kyp.ai stack up against each other to choose the best one for your needs. Mind you that all three tools we selected slightly differ regarding their strengths and core applications. The choice between them is not an easy one and should be dictated by a variety of factors. If in doubt, you are always welcome to turn to our task-mining expert team. They will carefully analyze your work patterns and advise on the optimal task-mining tool for your teams. ### UiPath. Key Features and Benefits UiPath, a global software company founded in Romania in 2005, specializes in automation solutions, primarily in Robotic Process Automation (RPA). With over 4,000 employees and a presence in 30+ countries, UiPath’s platform has expanded to encompass various automation tools like chatbots, AI, and ML for business processes. The solution’s [task capture and mining](https://www.uipath.com/platform/discover/task-mining) feature uncovers and documents processes for automation. It captures tasks in the background, translating them into visual and textual reports, allowing workflow improvements. Managers can share their desktops, capturing interactions seamlessly. AI-driven analysis suggests task optimization for specific business goals. These insights are visualized on graphs for easy exploration and can be exported to documents or UiPath Studio, an RPA creation dashboard, with a single click. #### UiPath Task Mining Core Features UiPath distinguishes itself from other task-mining tools with the following: - Scenario analysis. With the tool, it’s possible to explore the variations of the same task to address an issue meticulously and choose the best solution. - RPA integration. Since UiPath is a Robotic Process Automation company at its core, naturally, [UiPath Task Mining](https://www.flobotics.io/blog/task-mining-uipath) engine seamlessly combines with RPA capabilities. This means that instead of using two separate tools—one for identifying automation opportunities via data capture and one for automating them with chatbots—the company offers a complete platform where both can be accomplished. - Business applications integrations. As a complete automation platform, UiPath offers more than ‘just’ task or process mining. It’s a complex machine that integrates with hundreds of business applications, data management systems, and cloud services. This is especially valuable for large enterprises that want to minimize disruptions, keep their workflows flowing, and reduce technology stack despite using vast data. And there are plenty of [seasoned UiPath developers](https://www.flobotics.io/about-us) available to support you with this task. Fig. 02 · UiPath Pros and cons UiPath Task Mining: pros and cons Pros - Simple to useTemplates and a familiar interface for existing UiPath users - ScalableHandles large data volumes and deploys to desktops easily - Built-in AI and automationCovers the automation cycle end to end Cons - IntegrationsConnecting business apps often needs professional help - VisualizationData analysis could be presented more clearly #### How UiPath Task Mining Helped Dexcom Unlock 200,000 Hours with Automation Company: Dexcom Industry: Healthcare As a multinational company with years of experience in the automation market, UiPath has served thousands of clients, accumulating dozens of use cases on its website. While its task mining offering is relatively new, we can find a few strong success stories documenting the company’s achievements in this respect, too. The one we’ve chosen to feature is that of Dexcom, a US manufacturer of glucose control devices. It was looking to optimize its operations and reduce costs through RPA, employing task mining first to spot the areas for optimization and finally deciding to employ AI to take maximum advantage of automation. All in one tool. What started the transformation: An increasing volume of data entry tasks; an increase from 300 to 600 prescriptions manually entered into the system by Dexcom agents each week. How task mining was used: The first step was implementing UiPath’s Task Mining to understand how work is done in Dexcom, what tasks are performed, and which applications are employed. What results were achieved: Automating the prescriptions will save about 200,000 hours a year on manual processes. [Read more](https://www.uipath.com/resources/automation-case-studies/ai-powered-automation-transforms-dexcom-efficiency) ### Celonis. Key Features and Benefits Celonis is [a leading enterprise-grade provider of cloud-based process mining](https://www.celonis.com/) and analytics software (in 2020, it held 60% of the market). The company started in Europe in 2011, focusing specifically on process mining. In over a decade, it has grown to serve more than 5,000 enterprise customers who remain its main focus. Celonis platform helps organizations visualize, analyze, and optimize their business processes through a platform called the “Execution Management System” (EMS). It extracts and analyzes logs from different data sources, such as CMS or ERP systems, and integrates them with clicks, copy/pastes, time spent, and other user interaction data. The platform incorporates [task-mining software](https://www.celonis.com/process-mining/what-is-task-mining/) as one of its components. #### Celonis Task Mining Core Features In terms of task mining capabilities, Celonis’s enterprise platform offers the following: - End-to-end task and process analysis. As a comprehensive platform, Celonis combines task-mining features with other components of its vast platform. Once its software captures user interaction data, it integrates it into a Celonis Process Data Model, then to be processed by the Celonis Process Data Engine. So, there’s no need for integrations with external process mining software. - Detailed event log extraction. With an expansive customer base, years of experience, and a sophisticated software suite, Celonis excels at extracting insightful data for task and process analysis. All data is collected in the background without disrupting user’s workflows. - Enterprise focus. Since day one, Celonis has aimed at enterprise customers, so it is well-suited to the complexity and scale of larger organizations. It can support a high volume of data, users, and diverse business processes. Fig. 03 · Celonis Pros and cons Celonis: pros and cons Pros - Large task and user volumesScales easily to thousands of users - Rich analyticsA broad catalog of charts, tables and dashboards - Built-in AIAnalysis improves as it takes in more data Cons - Enterprise focusCan be too much for small and mid-sized companies - High costExpensive, especially with few users - SupportEmail or ticket support costs extra #### How Pepsi Used Celonis to Decrease Rejected Sales Orders By 86% Company: Pepsi Industry: Consumer Industries Like UiPath, Celonis can boast a massive portfolio of data mining and automation use cases featuring the world’s most recognized brands. One of them is Pepsi, the food and beverage giant, undergoing a transformative journey to better respond to modern consumers’ tastes. The company’s Global Process Excellence team came to Celonis with the challenge of quantifying its tasks and processes to optimize them and “take out the work out of the work,” in the words of Chris Knapik, Senior Director of Process Transformation. This was actually a bigger use case, focusing on optimizing nine processes, including Accounts Receivable and Accounts Payable, Procure-to-Pay, Order-to-Cash, and Make-to-Deploy. As happens with all big corporations, complex, multifaceted processes and tasks within them are often riddled with inconsistencies, discrepancies, and complexities. Therefore, the project’s main goal was to provide a detailed view of its teams’ work and to dig into specifics to make working at Pepsi easier, more productive, and more enjoyable. What started the transformation: Strategic, end-to-end global brand transformation based on data insights and evidence. How task mining was used: Pepsi used out-of-the-box Celonis’ capabilities to identify areas that needed improvement in the first place and carried the biggest potential. This was Days Sales Outstanding, which was broken down into individual tasks. The first action performed by the task mining tool was the identification of delinquent accounts and ranking them by invoice value so that the team knew which of them to prioritize. Then, step-by-step optimizations based on close task and process analysis were applied to the other areas. What results were achieved: Streamlining payment collection and processing activities released millions of dollars in free cash flow for Pepsi. By pinpointing faulty procedures and automating and facilitating some tasks, the order rejection rate has lowered to 4%. Automated identification of split invoices saves the accounting team over 1,000 hours per year on manual tracking. [Read more](https://www.celonis.com/customer-success-stories/pepsico-process-transformation/) ### Kyp.ai. Key Features and Benefits [KYP.ai](https://kyp.ai/) is an AI-powered process mining platform for real-time process and task data analysis. It excels in pinpointing areas for enhancement and offers intelligent suggestions for streamlining operations and enhancing task efficiency. Thanks to its heavy use of artificial intelligence and machine learning algorithms, KYP.ai offers precise and timely performance data, swiftly detects task anomalies, and identifies risks, empowering companies to optimize operations for maximum efficiency and cost savings. Its flexible architecture fits easily and nicely into every company’s tech stack and doesn’t require much coding to configure. Compared to the other two solutions, Kyp.ai seems to take a more holistic approach to business tasks and processes, making business pain points and optimization central to its platform and features. #### Kyp.ai Task Mining Core Features The following are core differentiators of Kyp.ai regarding task and process mining: - Embedded generative AI capabilities. When evaluating a company’s optimization areas, Kyp.ai also determines the potential of embedding generative AI to improve its task and process performance and ROI. - ROI-driven automation. Built with ROI growth in mind, Kyp.ai embeds profitability into its engine. In practice, the system’s intelligence allows users to distinguish and prioritize tasks with the greatest financial return potential. - Real-life, interactive insights. Kyp.ai stands out with its immersive and neat interface that gives users detailed yet straightforward cues and insights into actions and processes. All data is ingested in real-time, and advanced AI algorithms constantly digest and process it to reflect the current state of the organization and past performance for more comprehensive analysis. #### The highs and not-so-highs of Kyp.ai Task Mining This quick feature summary already shows that Kyp.ai stands out with its AI-powered, futuristic approach. Some other elements make it a unique task-mining solution. Fig. 04 · KYP.ai Pros and cons KYP.ai: pros and cons Pros - Actionable optimizationAI-based recommendations with practical solutions - Modern interfaceComplex data in clear sections and visualizations - Plug-in, no-code setupCuts deployment time, effort and cost Cons - Youngest solutionA smaller client portfolio so far - Not strictly enterprise-gradeComplex legacy environments may need expert help #### How Mindsprint Delivers Instant Insights Equivalent to 15 Years of Manual Analysis Company: Mindsprint Industry: Technology & Business Services While Kyp.ai is a more recent task and process mining solution, it has already amassed an impressive number of clients and several powerful case studies. One of them is that of Mindsprint, formerly known as Olam Technology and Business Services. The Singapore-based company is a digital and business transformation partner offering digital solutions, enterprise technology, business process services, and cybersecurity platforms. A business that stays on top of technological advancements was seeking cutting-edge task and process optimization solutions to boost operational efficiency and retain competitive win on the market. What started the transformation: The company had over 600 intricate processes to manage by more than 1,300 agents supporting 55 countries. With that span, it needed improved insights into task and process efficiency and a tool to help automate some of them to become more manageable and easier to monitor. How task mining was used: The project started from a smaller in-scope Proof of Concept and quickly evolved over 1,200 machines from which data of different types and granularity were being captured. Kyp.ai was used to capture 100 events over those machines and present their analyses on tailored data-driven dashboards. What results were achieved: With Kyp.ai, Mindsprint got hold of instant insights into its task and process efficiency, equivalent to 15 years of manual data collection and analysis. The value stream mapping delivered by the tool has also allowed the company to improve its data and process flows without spending an extra dollar. [Read more](https://kyp.ai/success-story/mindsprint-olam/) ## Conclusion As you can see, UiPath, Celonis, and Kyp.ai all have their unique strengths and weaknesses. With that knowledge and the understanding of task mining and its potential, you’re now better equipped to choose the most fitting solution for the needs of your organization. However, before you make that strategic decision, it’s worth checking how all three platforms match against one another. That’s why we prepared [an additional article covering a detailed UiPath vs. Celonis vs. Kyp.ai comparison](https://www.flobotics.io/blog/uipath-vs-celonis-vs-kypai). Check it out to see which one is top in key areas like integrations, capabilities, support, and more. #### Like the article? Spread the word Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### UiPath vs. Power Automate - Which RPA Tool To Choose? UiPath vs. Power Automate: compare features and pricing to decide which RPA tool best fits your 2026 process automation needs. Bart TeodorczukJune 27, 2022 ](https://www.flobotics.io/blog/uipath-vs-powerautomate)[ RPA ### UiPath vs. Python? Choosing the Right RPA Tool for Your Automation Job UiPath vs. Python: compare strengths, use cases, and when to choose code over low-code for your next automation project. Krzysztof SzwedDecember 11, 2023 ](https://www.flobotics.io/blog/uipath-python)[ RPA ### UiPath vs. GCP (Google Cloud Platform): Which to Choose for Your Next Automation Project? UiPath vs. Google Cloud Platform: compare RPA capabilities, pricing, and scalability to pick the right automation tool for your 2026 project. Krzysztof SzwedMay 30, 2023 ](https://www.flobotics.io/blog/uipath-vs-gcp) [All articles →](https://www.flobotics.io/blog) --- # Streamlining Supply Chains: Transforming Warehousing and Transport with RPA Canonical: https://www.flobotics.io/blog/warehouse-automation-process Author: Yana Pokora Published: 2023-10-17 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Streamlining Supply Chains: Transforming Warehousing and… [RPA](https://www.flobotics.io/blog?category=rpa) # Streamlining Supply Chains: Transforming Warehousing and Transport with RPA [Yana PokoraContent Manager at Flobotics](https://www.flobotics.io/our-editorial-team#pokora) Published October 17, 2023Updated September 1, 2026 On this page - [Unlocking Efficiency in Warehousing with RPA Logistics](#unlocking-efficiency-in-warehousing-with-rpa-logistics) - [RPA in Warehousing: Case Study](#rpa-in-warehousing-case-study) - [Optimizing Transport Management with RPA](#optimizing-transport-management-with-rpa) - [Route Optimization: Efficiency Redefined](#route-optimization-efficiency-redefined) - [Shipment Tracking: Real-time Visibility](#shipment-tracking-real-time-visibility) - [Invoice and Billing: Streamlined Processes](#invoice-and-billing-streamlined-processes) - [Compliance and Documentation: Navigating Regulations](#compliance-and-documentation-navigating-regulations) - [Sustainability in Transport](#sustainability-in-transport) - [The Wider Impact on the Supply Chain](#the-wider-impact-on-the-supply-chain) - [Demand Forecasting: Precision Planning](#demand-forecasting-precision-planning) - [Supplier Management: Strengthening Relationships](#supplier-management-strengthening-relationships) - [Customer Service: Enhancing Satisfaction](#customer-service-enhancing-satisfaction) - [Holistic Supply Chain Visibility](#holistic-supply-chain-visibility) - [Embracing the RPA Revolution](#embracing-the-rpa-revolution) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) The modern business landscape relies heavily on supply chains, intricate networks that facilitate the seamless movement of goods from manufacturers to consumers. These supply chains are not without their challenges; optimizing them has been a long-standing business goal. In recent years, automation, particularly [Robotic Process Automation (RPA)](https://en.wikipedia.org/wiki/Robotic_process_automation), has emerged as a transformative force in supply chain management. This article takes an in-depth look at how RPA is revolutionizing supply chains, focusing on warehousing and transport management. Before we delve into the specific ways RPA is reshaping supply chains, it’s essential to understand why this technological revolution is happening. Supply chain optimization has always been a priority for businesses looking to enhance efficiency, reduce costs, and meet customer demands promptly. Traditionally, supply chain management was labor-intensive and rife with opportunities for errors and delays. Human involvement introduced inefficiencies, inaccuracies, and bottlenecks. However, automation technologies like RPA have [opened up new possibilities](https://www.flobotics.io/blog/what-processes-to-automate) for optimizing supply chains. ## Unlocking Efficiency in Warehousing with RPA Logistics Warehousing is a linchpin in the supply chain, serving as the hub where goods are received, stored, and dispatched. RPA, with its capacity to automate repetitive tasks and streamline processes, is fundamentally changing how warehousing operations are managed. Fig. 01 · Warehousing 5 processes Which warehousing processes RPA can improve - Inventory managementTracks stock levels and expiry dates and keeps counts accurate. - SafetyRoutine safety inspections, equipment monitoring, protocol compliance. - Quality assuranceChecks incoming and outgoing goods and flags defects. - Data managementData entry, reconciliation and reporting. - Order fulfillmentOrder processing, picking and packing. #### Inventory Management: Precision and Efficiency Inventory management involves a delicate balance of supply and demand. It includes tracking stock levels, monitoring product expiration dates, and ensuring accurate stock counts. RPA is a game-changer in this area, automating tasks to maintain optimal inventory levels and reduce carrying costs. In contrast, a full-scale [warehouse management system](https://balloonone.com/our-solutions/warehouse-management/) would be ideal. #### Order Fulfillment: Speed and Accuracy The speed and accuracy of order fulfillment are paramount in satisfying [customer expectations](https://www.flobotics.io/blog/rpa-customerexperience). RPA automates order processing, picking, and packing, significantly reducing errors and enhancing order turnaround times. This ensures customers receive their orders promptly, increasing satisfaction and loyalty. #### Quality Assurance: Ensuring Excellence Quality control and assurance are integral to any warehousing operation. RPA can be programmed to conduct quality checks on incoming and outgoing goods, flagging any discrepancies or defects. This maintains product quality and reduces the likelihood of costly returns and replacements. #### Data Management: Precision and Timeliness Warehouses generate vast amounts of data daily. RPA handles data entry, reconciliation, and reporting tasks efficiently. This ensures decision-makers can access accurate and up-to-date information, enabling better strategic planning and forecasting. #### Enhancing Warehouse Automation Process & Safety Safety is paramount in warehousing operations. RPA can augment safety measures by automating routine safety inspections, monitoring equipment conditions, and ensuring compliance with safety protocols. This enhances the well-being of warehouse staff and reduces the risk of accidents and disruptions. ### RPA in Warehousing: Case Study An illustrative case of successful [RPA implementation](https://www.flobotics.io/blog/rpa-use-cases-retail) is Expo Group, which implemented an attended software robot to streamline its operations. Prior to RPA, employees at Expo Group were spending an average of 8.35 hours each day on inefficient tasks. However, with the introduction of RPA, this time was dramatically reduced to just 48 minutes, resulting in a remarkable 87.23% reduction in working hours. Furthermore, the implementation of RPA at Expo Group led to a staggering 99.97% decrease in error rates. This improvement not only saved time but also significantly enhanced the accuracy and reliability of the company’s processes. These results underscore the transformative potential of RPA in not only driving operational efficiency but also in elevating the overall quality of services provided to customers. These real-world examples demonstrate how RPA can bring about rapid and substantial improvements in operational efficiency, resource utilization, and customer satisfaction, making it a compelling choice for businesses seeking to stay competitive in today’s dynamic market landscape. Fig. 02 · Case Expo Group Expo Group, Bangladesh: export bookings GoalBetter customer satisfaction and process excellence while growingSolutionA UiPath bot runs the process from confirming export bookings to dispatching shipments, including exceptions 87%working hours saved 99%lower error rate Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Optimizing Transport Management with RPA Transportation management is another critical aspect of the supply chain that faces its own unique set of challenges. RPA offers innovative solutions to address these hurdles. Fig. 03 · Transport 5 areas What RPA can automate in transport management - 01Route optimizationUses historical data, weather and traffic to plan routes. - 02Shipment trackingShows where shipments are and their status. - 03SustainabilityFuel-efficient routes and automated sustainability reports. - 04Compliance and documentationCreates and checks shipping documents and customs declarations. - 05Invoicing and billingCreates and sends invoices and matches them to delivery confirmations. ### Route Optimization: Efficiency Redefined Efficient route planning is essential for minimizing transportation costs and delivery times. RPA algorithms analyze historical data, weather conditions, traffic patterns, and other factors to [optimize delivery routes](https://geo2.com/). This not only reduces fuel consumption but also ensures timely deliveries. ### Shipment Tracking: Real-time Visibility Real-time tracking of shipments is crucial for businesses and customers alike. RPA enables automated tracking, providing visibility into the location and status of shipments. This transparency enhances customer trust and enables businesses to proactively address any delays or issues. ### Invoice and Billing: Streamlined Processes Accurate and timely invoicing is vital for cash flow management. RPA automates the generation and dispatch of invoices, ensuring they are error-free and sent promptly. Additionally, it can reconcile invoices with delivery confirmations, reducing disputes and delays in payment processing. ### Compliance and Documentation: Navigating Regulations Transporting goods often involves regulatory compliance and extensive documentation. RPA assists in managing compliance requirements by automating the creation and validation of shipping documents, customs declarations, and other essential paperwork. This minimizes the risk of costly compliance errors and delays at border crossings. ### Sustainability in Transport Sustainability is a growing concern in logistics. RPA can contribute to sustainable transport management by optimizing routes for fuel efficiency, reducing emissions, and helping businesses meet their environmental goals. Additionally, it can automate reporting on sustainability metrics, ensuring transparency and accountability. ## The Wider Impact on the Supply Chain The transformative power of RPA extends beyond warehousing and transport management, influencing other critical aspects of supply chain management. ### Demand Forecasting: Precision Planning Accurate demand forecasting is essential for minimizing excess inventory and stockouts. RPA analyzes historical sales data, market trends, and other variables to provide more precise demand forecasts. This enables businesses to optimize production and inventory levels, reducing costs and increasing customer satisfaction. ### Supplier Management: Strengthening Relationships Managing supplier relationships is vital for ensuring a reliable supply of materials and components. RPA automates supplier communication, order placement, and performance tracking. This streamlines the procurement process, reduces lead times, and minimizes supply chain disruptions and [supply challenges](https://www.flobotics.io/blog/rpa-challenges). ### Customer Service: Enhancing Satisfaction Exceptional customer service sets businesses apart in today’s market. [RPA enhances customer service](https://www.uipath.com/resources/automation-case-studies/dsb-on-track-to-rpa-success) by automating routine inquiries, order status updates, and returns processing. This allows human agents to focus on complex customer interactions, leading to [improved customer satisfaction](https://www.flobotics.io/business-process-automation). ### Holistic Supply Chain Visibility RPA can provide a holistic view of the entire supply chain by integrating data from various sources and systems. This enables businesses to make informed decisions, quickly identify and address issues, and improve overall supply chain performance. ## Embracing the RPA Revolution In conclusion, Robotic Process Automation (RPA) is not just [a technological trend](https://www.linkedin.com/pulse/5-ways-rpa-revolutionizing-logistics-industry-veera-arun-karthikeyan/); it represents a fundamental shift in the [operations of supply chains](https://www.automationanywhere.com/resources/customer-stories/chain-solution-company). The integration of RPA in warehousing, transport management, and other supply chain functions has the potential to unlock unprecedented efficiencies, cost savings, and customer satisfaction. At Flobotics, we understand the transformative power of automation. We can help evaluate your business processes and implement automation solutions tailored to your needs. Automation through RPA is not a mere option; it’s the future of supply chain management. [Let’s start a conversation](https://www.flobotics.io/contact) about how Flobotics can assist your business on this journey to efficiency and excellence. With the power of RPA, your supply chain can achieve new heights of efficiency and productivity, ensuring your business thrives in the ever-evolving landscape of commerce. We can provide more insights into RPA challenges, use cases, and its impact on logistics and supply chain management and also showcase explore our successful automation implementations. #### Like the article? Spread the word Written byYana Pokora Content Manager at Flobotics. [More from Yana](https://www.flobotics.io/our-editorial-team#pokora) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### From Warehouse to Delivery: 12 Best RPA Use Cases in the Retail Industry RPA in retail: 12 use cases from warehouse to delivery that help retailers cut costs and improve the shopping experience. Michał RejmanJune 15, 2023 ](https://www.flobotics.io/blog/rpa-use-cases-retail)[ RPA ### How RPA Is Changing the Logistics Industry and Supply Chain Management RPA in logistics: see which supply chain management processes to automate first and how companies streamline logistics operations with robots. Michał RejmanOctober 18, 2022 ](https://www.flobotics.io/blog/rpa-logistics-supply-chain-management)[ RPA ### RPA in Supply Chain Management: Pros, Cons and The Best Use Examples RPA supply chain use cases: pros, cons, and real examples of how automation cuts costs across the logistics industry. Michał RejmanMay 07, 2021 ](https://www.flobotics.io/blog/rpa-in-supply-chain-management-use-examples) [All articles →](https://www.flobotics.io/blog) --- # Healthcare Compliance Automation: Laws, Benefits and Examples Canonical: https://www.flobotics.io/blog/compliance-automation Author: Filip Nasiadko Published: 2023-10-09 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Healthcare Compliance Automation: Laws, Benefits and Examples CEO Notes [Healthcare](https://www.flobotics.io/blog?category=healthcare) # Healthcare Compliance Automation: Laws, Benefits and Examples [Filip NasiadkoCEO and Co-founder at Flobotics](https://www.flobotics.io/our-editorial-team#nasiadko) Published October 09, 2023Updated September 1, 2026 On this page - [Why is healthcare compliance important?](#why-is-healthcare-compliance-important) - [Security breaches](#security-breaches) - [Costly fines](#costly-fines) - [Lower patient care quality](#lower-patient-care-quality) - [Patient distrust](#patient-distrust) - [Legal Requirements in the US Regarding Compliance](#legal-requirements-in-the-us-regarding-compliance) - [Health Insurance Portability and Accountability Act (HIPAA)](#health-insurance-portability-and-accountability-act-hipaa) - [Health Information Technology for Economic and Clinical Health Act (HITECH)](#health-information-technology-for-economic-and-clinical-health-act-hitech) - [Affordable Care Act (ACA)](#affordable-care-act-aca) - [Patient Safety and Quality Improvement Act (PSQIA)](#patient-safety-and-quality-improvement-act-psqia) - [Emergency Medical Treatment and Active Labor Act (EMTALA)](#emergency-medical-treatment-and-active-labor-act-emtala) - [What tasks can you streamline with compliance automation?](#what-tasks-can-you-streamline-with-compliance-automation) - [What are the benefits of using compliance automation?](#what-are-the-benefits-of-using-compliance-automation) - [Improved accuracy](#improved-accuracy) - [Reduced risk of penalties](#reduced-risk-of-penalties) - [Centralized data](#centralized-data) - [Enhanced data security and privacy](#enhanced-data-security-and-privacy) - [Increased efficiency](#increased-efficiency) - [Financial gains](#financial-gains) - [Quicker adapting to shifting regulations](#quicker-adapting-to-shifting-regulations) - [Better patient experience and trust](#better-patient-experience-and-trust) - [Compliance automation examples](#compliance-automation-examples) - [Faster and smarter medical billing with RPA](#faster-and-smarter-medical-billing-with-rpa) - [Bringing multiple EHRs together](#bringing-multiple-ehrs-together) - [Healthcare RPA: your way to compliance](#healthcare-rpa-your-way-to-compliance) - [Understanding Healthcare Compliance Requirements](#understanding-healthcare-compliance-requirements) - [Key Regulations and Standards](#key-regulations-and-standards) - [Compliance Documentation Necessities](#compliance-documentation-necessities) - [The Landscape of Compliance Automation Technologies](#the-landscape-of-compliance-automation-technologies) - [Types of Automation Tools Available](#types-of-automation-tools-available) - [Features to Look For in Automation Solutions](#features-to-look-for-in-automation-solutions) - [Implementing Compliance Automation: A Practical Guide](#implementing-compliance-automation-a-practical-guide) - [Assessing Your Organization's Readiness](#assessing-your-organization-s-readiness) - [Step-by-Step Implementation Framework](#step-by-step-implementation-framework) - [Measuring Success and ROI of Automation](#measuring-success-and-roi-of-automation) - [Challenges and Solutions in Compliance Automation](#challenges-and-solutions-in-compliance-automation) - [Overcoming Resistance to Change](#overcoming-resistance-to-change) - [Addressing Common Implementation Pitfalls](#addressing-common-implementation-pitfalls) - [Future Trends in Compliance Automation in Healthcare](#future-trends-in-compliance-automation-in-healthcare) - [Innovations on the Horizon](#innovations-on-the-horizon) - [Preparing for Regulatory Changes](#preparing-for-regulatory-changes) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) $16 million—that’s the highest HIPAA non-compliance penalty to date, paid by Anthem Inc., one of the largest health benefits companies in the US. In 2015, cyber-attackers exploited Anthem’s insufficient access control procedures, stealing the ePHI of nearly 79 million policyholders. In a more recent [healthcare data violation](https://therecord.media/at-least-34-healthcare-orgs-affected-by-alleged-ransomware-attack-on-onetouchpoint), a 2022 ransomware attack targeted at a printing and mailing vendor, OneTouchPoint, affected 34 healthcare organizations that were the company’s customers. As a result, records of over 2.5 million people were compromised. These and dozens of other cases each year share the same root cause: non-compliance with safety measures required by acts such as HIPAA or the HITECH Act. Exorbitant penalties aside, failing to adhere to the increasingly complicated healthcare regulations entails risks much more severe than financial losses. Luckily, with the help of RPA-based [compliance automation](https://www.flobotics.io/blog/hipaa-compliance-rpa), meeting legal requirements is more effortless than ever. Why? And what regulations are these? You’ll find it out in a moment—welcome to our overview of the most critical healthcare-related regulations in the US and how RPA can help you meet them. ## Why is healthcare compliance important? Despite the million-dollar fines and all the talk about the importance of compliance, [healthcare data breaches](https://www.hipaajournal.com/healthcare-data-breach-statistics/) had been on a 14-year rise until a slight decrease in 2022. So, before discussing regulations, let’s see what makes following them vital. ### Security breaches While the large cases involving millions of policyholders get the most media coverage, they are far from the only ones. The US Department of Health and Human Services’ Office for Civil Rights (OCR) reports hundreds of [healthcare regulation breaches](https://www.hipaaguide.net/healthcare-data-breach-statistics/) yearly, with an all-time high of 715 in 2021 alone. ### Costly fines Settlements and monetary penalties cost healthcare organizations millions of dollars each year. Just in 2023, [non-compliance fines ](https://www.hipaajournal.com/healthcare-data-breach-statistics/)amounted to more than $3 million, which is still relatively small compared to most previous years. ### Lower patient care quality Financial losses resulting from non-compliance can severely disrupt the operational capabilities of your healthcare organization. Lower funds mean reduced investments, fewer equipment upgrades, discontinued services, and even layoffs. ### Patient distrust Though eroding trust can’t be measured with numbers, it’s the ultimate consequence of non-compliance. The blow to reputation following a sensitive data breach is hard to recover from, leading to further financial losses. ## Legal Requirements in the US Regarding Compliance As healthcare and data technologies developed, many policies were implemented to ensure healthcare services’ efficiency and protect sensitive information. Today, multiple laws regulate healthcare data sharing and safeguarding in the US. Here are some of the most essential ones. ### Health Insurance Portability and Accountability Act (HIPAA) The most well-known healthcare data regulation, HIPAA, was established in 1996 to govern the use and sharing of patient records in all formats, whether verbal, written, or electronic. Under HIPAA, the Department of Health and Human Services (HHS) sets boundaries on using and sharing health information, safeguards to protect patients’ records, and penalties for violations. Eventually, additional rules were established to build on HIPAA. The HIPAA Privacy Rule introduced nationwide standards for securing, using, and sharing PHI, and it outlines how entities can use these records without a patient’s explicit authorization. It also gives patients control over their information, including the right to examine, obtain, and issue copies of their health records and to request necessary corrections. HIPAA Security Rule puts these standards into action, requiring providers to assess risk and then implement appropriate administrative, physical, and technical measures to keep electronic PHI (ePHI) safe. Fig. 01 · HIPAA Who it covers Who does HIPAA apply to? Any organization that uses, stores or shares protected health information (PHI). Healthcare providers - Health systems - Hospitals - Clinic chains - Medical practices - Chiropractors - Dentists - Nursing homes - Pharmacies - Psychologists Services that handle patient data - Data administrators - Benefit managers for health plans - RCM and billing companies - Accountants - Legal advisors - Administrative staff ### Health Information Technology for Economic and Clinical Health Act (HITECH) As EHR breach attempts grew more sophisticated, new regulations were needed to help entities fight them, which led to the creation of the HITECH Act in 2009. HITECH Act focuses on standardizing EHRs, their security, and sharing. Under HITECH, ePHI can only be transferred using secured channels, not traditional methods like emails. The regulation requires providers to notify patients about unauthorized access or use of their records. HITECH also obliges HHS to conduct regular audits and exact penalties on non-compliant providers. Another goal of the HITECH Act is to promote the adoption and use of EHR—to encourage providers to switch to electronic data systems, the law offers financial incentives. ### Affordable Care Act (ACA) The overarching goal of ACA, introduced in 2010, is to make healthcare insurance accessible and affordable to more people. This is done by subsidizing health services for lower-income households, expanding the coverage of the Medicaid program, and requiring subject businesses to offer minimum essential health insurance to their employees. ### Patient Safety and Quality Improvement Act (PSQIA) Released in 2005, PSQIA is a reporting system designed to reduce costly and dangerous medical errors. PSQIA created a framework for establishing patient safety organizations (PSOs) that could collect and analyze patient information from healthcare providers. Importantly, PSQIA warrants the confidentiality of patient records featured in the reports, allowing for anonymized and safe sharing of sensitive data. ### Emergency Medical Treatment and Active Labor Act (EMTALA) As another law concerned with increasing the availability of healthcare, EMTALA requires hospitals to run preliminary screenings of admitted uninsured or Medicaid-covered patients in emergency cases before transferring them to public hospitals. Under EMTALA, patients can only be transferred if these screenings determine that their condition is stable or if the medical benefits of moving the patients outweigh the risks. From the data point of view, hospitals must also provide copies of patient’s medical records to the facility they are transferred to. ## What tasks can you streamline with compliance automation? Meeting all legal requirements involves processing huge volumes of data between test results, patient personal data, [insurance claims](https://www.flobotics.io/agents/claims-management-automation), and other documents. Due to that, compliance-related workflows can take a heavy toll on your time and resources. However, the same reliance on data processing makes many tasks the perfect candidates for automation using technologies like RPA. So, what can you relegate to healthcare compliance automation? - Moving medical records — whether you need to update your EHR, migrate data to a cloud-based one, unify disjointed datasets into a centralized source, or simply retrieve specific patient records, RPA can [automate mundane healthcare tasks](https://www.flobotics.io/rcm-automation) involving moving medical data. - Data entry — RPA is equally apt at filling standardized paperwork and preparing the necessary documents continuously and with a near-zero error rate. - Document digitization — with the help of optical character recognition (OCR), RPA can read even paper-based documents, allowing organizations to convert medical documentation into digital format quickly. - Monitoring and auditing — RPA allows providers to monitor incoming records and run routine compliance checks of massive datasets without stretching their back-office staff too thin. - [Reporting](https://www.flobotics.io/rcm-automation) — once the check is complete, RPA will compile its findings into a report to share with the selected team members. - Automated alerts — should RPA bots detect errors or inconsistencies that could lead to non-compliance, they will automatically flag them and notify your staff. - Access monitoring — bots can be programmed to monitor PHI access and identify deviations from the usual pattern, indicating potential breaches, theft attempts, and other dangers. - Suggesting improvements — automation solutions can inspect current processes at higher levels of advancement to find inefficiencies and identify potential improvements. ## What are the benefits of using compliance automation? Automating compliance-related tasks makes it much easier for healthcare organizations to meet all legal requirements, but the benefits of RPA in healthcare don’t end there. ### Improved accuracy By automatically handling error-prone manual tasks like copy-pasting medical data, filling in documentation, or moving files containing sensitive records, RPA helps bring the rate of human error down almost to zero. ### Reduced risk of penalties RPA limits the risk of a data breach in several ways, thus reducing the likelihood of receiving violation fines. And, in the unlikely case that security is compromised, showing diligence helps settle for a lower penalty. ### Centralized data Automated data operations make it much easier for companies to unify all their records and avoid siloed datasets. This, in turn, allows for better safety measures, monitoring, access control, and, ultimately, higher compliance. ### Enhanced data security and privacy RPA bots can monitor sensitive datasets around the clock and, unlike humans, won’t overlook suspicious activity due to distraction. They can also be used to implement internal self-assessment systems and prevent external controls from government agencies. ### Increased efficiency Regulatory tasks require a lot of effort, diverting your employees from higher-impact duties. With RPA, they can devote more of their time and energy to innovation or strategic decisions. ### Financial gains Automation lowers your spending by cutting operational costs and helping you avoid fines. Additionally, it can boost your earnings by increasing productivity and allowing you to accept more patients. ### Quicker adapting to shifting regulations Adjusting your compliance procedures to regulatory changes requires retraining staff and changing processes, causing confusion, costing time, and leading to potential errors. At the same time, everything that RPA bots need to run the updated procedures is one-time reprogramming and testing. ### Better patient experience and trust Ultimately, it’s not just your organization that benefits from all these improvements. Compliance automation translates into faster and more reliable care delivery for your patients and certainty that their sensitive information is kept safe. Fig. 02 · Compliance automation 8 gains What you get from compliance automation The eight benefits covered above, in one view. - Improved accuracy - Lower risk of penalties - All data in one place - Better data security and privacy - Higher efficiency - Financial gains - Faster response to new rules - Better patient experience and trust Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Compliance automation examples Global industry leaders are already using RPA for healthcare automation. This includes some of our clients. ### Faster and smarter medical billing with RPA Transferring medical records between all entities involved in the patient journey safely and efficiently is a long-term healthcare challenge. For that, we created dedicated SuperPay accounts for each of their clients and then designed RPA bots that automatically logged into that account and scanned each provider’s EHR database for eligible patients. The bots would also send automated SuperPay invites to these patients and handle a range of other activities, such as patient account creation, payment method updates, or retrieving claim details. The benefits were threefold: less time spent on each patient billed, faster data transfers, and reduced cost. ### Bringing multiple EHRs together Integrating healthcare systems with third-party software proved challenging for the Evidence-Based Treatment Centers of Seattle (EBTCS), a network of mental health centers. In this case, their EHR, Valant, lacked publicly-accessed API, preventing EBTCS from connecting it to Salesforce, and effectively forcing its staff to move records manually. Following a close analysis of the system, we suggested a Python automation solution, Robocorp. Using the tool, we created a bot that regularly compared Valant and Salesforce databases and automatically created patient profiles in the [EHR system](https://www.flobotics.io/rcm-automation) based on sales data. It doesn’t end there: the bot also updates Salesforce client status, pulls data from Valant and documents from Salesforce to EHR, transcribes emails, and notifies team members of relevant changes. All that allows for seamless communication between EHR, the sales platform, and EBTCS staff. Fig. 03 · Case EBTCS, Seattle Evidence-Based Treatment Centers of Seattle GoalConnect sales with the patient management software.What we automatedComparing records across databases, creating patient profiles in the EHR, updating client status, moving data into the EHR and transcribing emails. 20×faster on a single process $0in licensing costs ~20cases processed a week Flobotics [Read the case study →](https://www.flobotics.io/blog/evidence-based-treatment-centers-of-seattle-ebtcs) ## Healthcare RPA: your way to compliance As healthcare is becoming more reliant on data and technology, regulations must keep up to warrant the safety and quality of healthcare services. The same applies to providers, who, through [compliance](https://www.flobotics.io/rcm-automation), can directly improve their effectiveness and integrity. Compliance automation and RPA offer healthcare organizations a shortcut to achieving this goal with the added benefits of increased productivity, savings, and optimized operations. Curious to find out more? [Drop us a line.](https://www.flobotics.io/contact) For how to choose and roll out compliance automation tools, see our [guide to implementing compliance automation in healthcare](https://www.flobotics.io/blog/compliance-automation-healthcare). Written byFilip Nasiadko CEO and Co-founder at Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Interoperability in Healthcare: What You Need to Know (And How to Get There with RPA) Canonical: https://www.flobotics.io/blog/interoperability-in-healthcare Author: Michał Rejman Published: 2023-10-03 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Interoperability in Healthcare: What You Need to Know (And… [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RPA](https://www.flobotics.io/blog?category=rpa) # Interoperability in Healthcare: What You Need to Know (And How to Get There with RPA) [Michał RejmanChief Marketing Officer at Flobotics](https://www.flobotics.io/our-editorial-team#rejman) Published October 03, 2023Updated September 1, 2026 On this page - [What is Interoperability in Healthcare?](#what-is-interoperability-in-healthcare) - [Healthcare Interoperability Levels](#healthcare-interoperability-levels) - [Challenges with Ensuring Healthcare Interoperability](#challenges-with-ensuring-healthcare-interoperability) - [Why is Interoperability Important?](#why-is-interoperability-important) - [What Systems Can Be Interconnected?](#what-systems-can-be-interconnected) - [Electronic Health Records (EHRs)](#electronic-health-records-ehrs) - [Medical Devices](#medical-devices) - [Health Information Exchanges (HIEs)](#health-information-exchanges-hies) - [Regulations and Interoperability Standards in Healthcare](#regulations-and-interoperability-standards-in-healthcare) - [Achieve Full Interoperability in Healthcare with RPA Automation](#achieve-full-interoperability-in-healthcare-with-rpa-automation) - [DocPlanner: Faster Patient Profile Creation](#docplanner-faster-patient-profile-creation) - [Pain Treatment Centers of America: Streamlined Claim Submission](#pain-treatment-centers-of-america-streamlined-claim-submission) - [Interoperability through Automation](#interoperability-through-automation) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Picture a standard medical procedure. You visit your primary care physician for the initial diagnosis. They prescribe a medication or refer you to another specialist. Some cases may require lab tests, long-term treatment, or hospitalization. All key details are saved in your patient history once the treatment is complete, covered, and paid for. Behind the scenes, this rudimentary procedure involves moving heaps of medical records between healthcare providers, facilities, labs, pharmacies, and insurers. Typically, all of them use their internal systems to store patient data, so for all this process to function with minimum error and delays, healthcare organizations need one crucial ingredient: interoperability. But what is interoperability in healthcare, really? What software systems are involved, which regulations and standards apply, and—crucial from the RPA perspective—how can automation support healthcare organizations in connecting seamlessly? Let’s find out. ## What is Interoperability in Healthcare? In healthcare, interoperability means the ability of multiple software systems (such as [Electronic Health Record ](https://www.flobotics.io/data-integrations)software—EHR, Hospital Management Systems, Medical Billing Software, etc.) to exchange and use medical data. An interoperable medical records network allows all entities involved in the patient’s journey to retrieve and view consistent medical records at multiple locations simultaneously. As a result, providers can easily go through historical patient data to better understand each case and achieve the most optimal outcomes based on data. And patients don’t need to worry about forwarding or carrying around their documentation, insurance coverage, or lab results, regardless of where or which provider they need to consult. Seems excellent, right? ## Healthcare Interoperability Levels The Healthcare Information and Management Systems Society (HIMSS) distinguishes four healthcare interoperability levels that describe how interconnected a system is. Fig. 01 · Interoperability 4 levels The levels of EHR interoperability - 01FoundationalSystems can exchange medical data but not interpret it. - 02StructuralSystems send and receive data in a standard format and interpret it. - 03SemanticSystems exchange, interpret and fully use data across different EHRs. - 04OrganizationalCovers data governance, policy, social, legal and organizational issues. ## Challenges with Ensuring Healthcare Interoperability One thing to note here is that true interoperability in EHR and other healthcare systems involves the transfer, interpretation, use, and governance of medical data. The transmitted data must be standardized to allow it so that all systems can understand it. However, connecting dozens of disparate EHR systems can be a challenge. This is largely due to differences in terminology used by different providers, EHR functions, or technical specifications, and disparate data structure, which may lead to duplicate or faulty records, missing information, and, as a result, substandard and delayed services. Another important hurdle comes from cultural differences. Some healthcare providers may share incomplete records and use siloed or fragmented data. In the most extreme cases, providers may deliberately [block or limit the flow of patient records](https://pmc.ncbi.nlm.nih.gov/articles/PMC5565131/#:~:text=In%20a%20survey,market%20dominance.13) to increase their revenue and market position. To make matters even more complicated, there’s the sheer variety of data. Patient history, personal data, treatment plans, doctor’s notes, test results, prescriptions, imaging, and diagnostic reports must all be kept in formats that enable easy sharing and access for all involved parties, from physicians to insurers. ## Why is Interoperability Important? Healthcare delivery is a team effort where all involved entities work toward a positive patient outcome. This is only possible if all roles can communicate and exchange information efficiently, meaning that interoperability in healthcare is paramount to their success. Through the past decade, providers have made significant progress in transitioning from physical data storage to easier-to-share EHRs and other systems. As of 2021, 78% of office-based physicians in the USA and [nearly all non-federal acute care hospitals (96%) adopted a certified EHR](https://www.healthit.gov/data/quickstats/national-trends-hospital-and-physician-adoption-electronic-health-records#:~:text=As%20of%202021%2C%20nearly%204,physicians%20had%20adopted%20an%20EHR.&text=Measures%20of%20EHR%20adoption%20differ%20over%20time.). Europe follows this trend, with increasing numbers of healthcare providers, hospitals, and practices deploying software systems to streamline their services. This is a step in a good direction, as interoperability in EHR aims to ensure that all providers can exchange and use patient records. Aside from improved cooperation, it has a far-reaching positive impact on multiple aspects of healthcare operations: - Higher productivity and revenue — EHR interoperability allows all involved entities to do more faster by improving data access. Instead of spending their time retrieving patient data, physicians can accept more patients. - Data safety and compliance — A well-synergized and [regulation-compliant](https://www.flobotics.io/rcm-automation) data-sharing system is the best way to prevent leaks during patient data transfer. - Lower costs — Better data operations translate into savings: fewer non-compliance fees, no-shows, and negative payment adjustments, combined with optimized patient transfers, improved analytics, and faster payments. - Reduced physician burnout — On average, [physicians spend 4.5 hours each day working with EHRs](https://www.medicaleconomics.com/view/physicians-spend-4-5-hours-a-day-on-electronic-health-records). Interoperability helps prevent physician burnout by reducing paperwork, manual data entry, and the time needed to retrieve the necessary records. - Improved quality of care — With complete access to all medical details of each patient, physicians can diagnose the problem with better accuracy and suggest tailored, targeted treatment. On an organizational level, providers can use data to monitor care quality and identify improvement opportunities. - Patient education — By connecting EHR systems with patient portals, physicians can communicate directly with patients to update them on test results, give recommendations, or suggest further care. ## What Systems Can Be Interconnected? Interoperability requires synergizing a range of systems involved in healthcare. What are they? ### Electronic Health Records (EHRs) Coordinating [Electronic Health Records](https://www.flobotics.io/data-integrations) systems is essential for providing efficient patient healthcare services. This is especially true for those with complicated health issues who require the assistance of multiple providers. Interoperability reduces the time needed to retrieve records and eliminates the time-consuming process of unifying siloed data from various entities. Seamless access to EHR data from all sources helps providers streamline diagnostics and ensure timely and high-quality treatment. To ensure the interoperability of two or more EHRs, all must be able to communicate, retrieve, and interpret patient data. There are several technologies they can use for that. Fig. 02 · Interoperability 4 standards The most common EHR interoperability standards - FHIR Fast Healthcare Interoperability Resources - TEFCA Trusted Exchange Framework and Common Agreement - USCDI United States Core Data for Interoperability - CMS-0057-P Advancing Interoperability and Improving Prior Authorization Processes (proposed rule) ### Medical Devices Clinicians can leverage the network connection capabilities of modern medical devices to reduce manual record-keeping tasks. Instead of manually copying the relevant information, physicians can pull it directly from these connected devices in near real-time, enhancing care quality, safety, and efficiency. For instance, connected medical devices like telemetry monitors or ventilators could alert physicians of an urgent patient condition. Connected equipment can also handle routine patient check-ups, saving hospital staff daily hours. ### Health Information Exchanges (HIEs) Health information exchange (HIE) is the ability to transfer healthcare data among medical facilities. This exchange can occur on patient portals, mobile apps, and other devices. The term can also refer to organizations overseeing the standards governing the exchange of health records. By enabling healthcare systems to communicate with one another, HIEs play a crucial role in developing interoperability in EHR systems. However, it must be remembered that transferring the records is only the first step—next; it must be interpreted and used by all receiving systems. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Regulations and Interoperability Standards in Healthcare Healthcare is a strategic sector involving many entities. As such, regulations and standardization are crucial for the efficient and secure functioning of all the contributors to the industry. In the USA, one such regulation is the [Health Insurance Portability and Accountability Act (HIPAA)](https://www.hhs.gov/hipaa/index.html). It has revolutionized healthcare data protection in the country by introducing security and privacy standards for protected health information (PHI). But as much as HIPAA focuses on privacy and security, it also recognizes the need for health data to flow through the healthcare ecosystem. For that purpose, HIPAA defines what records can be shared and how to make the transfer secure. The regulation establishes three areas where providers can share PHI without explicit patient consent: treatment, payment, and healthcare operations. With that, physicians and health systems can freely access patient records if they’re used to treat, get payment for services, or improve operations. Other uses include consulting with other providers about treatment, sharing information as part of a claim for payment to a health plan, and health plans using PHI to provide patient service. Thus, despite its focus on data privacy and protection, [HIPAA](https://www.flobotics.io/rcm-automation) supports interoperability by enabling providers to share PHI seamlessly required for patient care, quality improvement, and other core activities. Similar regulations govern the use and sharing of healthcare records in other regions. In the EU, information concerning health is considered a special data category under the [General Data Protection Regulation (GDPR)](https://www.consilium.europa.eu/en/policies/data-protection/data-protection-regulation/), the EU’s main data privacy act. For healthcare-specific purposes, GDPR is extended further by the [European Health Data Space](https://health.ec.europa.eu/ehealth-digital-health-and-care/european-health-data-space_en)—a set of rules and standards created to support patients and healthcare-oriented organizations in managing and using data. Although GDPR applies only to EU member states and non-EU organizations that process EU resident data, it sets a standard for other countries seeking to regulate data usage and protection. Among national data policies inspired by GDPR are Brazil’s LGPD, Turkey’s LPPD, and Egypt’s DPL. More recently, standards were developed that are concerned precisely with facilitating interoperability. Notable examples include [Fast Healthcare Interoperability Resources (FHIR)](https://www.hl7.org/fhir/overview.html) created by the standards development organization Health Level 7 (HL7) or [Trusted Exchange Framework and Common Agreement (TEFCA)](https://rce.sequoiaproject.org/tefca/). Their main goal is to reduce the gap between disparate healthcare IT systems and enable their unification. This is done by: - encouraging the use of common data exchange technologies like REST API, - adopting standards and concepts familiar to software developers like XML, JSON, HTTP, and OAuth, - prioritizing ease of use and implementation, - basing development on widely available resources and tools, - focusing on modern security standards. These standards aim to make interoperability easier to adopt and enable faster and simpler application creation. The need for standardization was recognized by WHO, which recently announced plans to cooperate with HL7 on its global [health interoperability strategy.](https://www.healthcareitnews.com/news/who-and-hl7-collaborate-global-interoperability-adoption) ## Achieve Full Interoperability in Healthcare with RPA Automation Although standards and regulations offer crucial support for connecting EHR systems, dealing with large volumes of data remains challenging. Healthcare organizations are increasingly adopting automation technologies such as Robotic Process Automation (RPA) to facilitate EHR operations. The primary use of RPA in interoperability is to facilitate data transfer through [EHR automation](https://www.flobotics.io/rcm-automation). Accessing and moving records requires healthcare staff to log into and out of multiple applications and copy-paste patient records between them. This manual workflow is inefficient and prone to errors and inconsistencies in critical datasets. [RPA healthcare solutions](https://www.flobotics.io/) may automatically extract and exchange patient data between disparate EMR/EHR platforms, billing systems, physician dashboards, and other programs. With that, providers save time and combine all data into a single ecosystem. Centralizing data prevents patient records from ending up in silos within healthcare organizations, reducing the cost and effort necessary to retrieve and move them between entities. All that without errors or records getting lost along the way. ### DocPlanner: Faster Patient Profile Creation Fig. 03 · Case Docplanner Docplanner: faster patient profile creation GoalConnect several legacy EHR systems to the Docplanner app, speed up key processes and save doctors timeSolutionAutomated patient profile creation, booking and rescheduling in the EHRs, and the data flow between legacy EHRs and the app 3%better sales conversion $150ksaved a year from the first launch 20×faster processes on average 500+clinicians using the app Flobotics [Read the case study →](https://www.flobotics.io/case-studies/docplanner) To illustrate that, let’s look at the story of DocPlanner. The leading medical scheduling platform turned to us to automate the integration between their system and EHRs/EMRs used by providers. With RPA EHR automation, DocPlanner could expedite patient profile creation and move all necessary data from their partners’ systems. From there, we’ve gradually added multiple additional features, such as automated data migration between all connected apps or visit rescheduling and cancellation. Most importantly, readily available patient data opens up further healthcare process automation opportunities. RPA developers can support healthcare providers in: - medical billing and [coding](https://www.flobotics.io/blog/medical-coding), - [claims processing](https://www.flobotics.io/agents/claims-management-automation), - appointment scheduling, - data migration, - placing lab and medical supply orders, - customer service, - invoicing, and many more mundane, data-based healthcare workflows. ### Pain Treatment Centers of America: Streamlined Claim Submission Another case from our portfolio demonstrates how a single automation project can become an ongoing, organization-wide improvement process. Our collaboration with the Pain Treatment Centers of America practice network started with a simple task: [automating the claim submission process](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks). Encouraged by the successful deployment, our customer decided to scale up their automation. As a result, we created dozens of purpose-made bots that handle a range of healthcare processes across the network, from payment eligibility checks to write-offs and data retrieval. Fig. 04 · Case Pain Treatment Centers of America Pain Treatment Centers of America: faster claim submission GoalSpeed up insurance claims and use backlog data that could not be processed by handSolution10+ RPA bots across PTCOA processes, including retrieving and analyzing historical patient data 23 daysfrom launch to 100% ROI $400kprojected savings in year one 449%overall return on investment Flobotics [Read the case study →](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) ## Interoperability through Automation From clinics to insurers, connecting all entities involved in the treatment process is crucial for a positive patient outcome. The better the interoperability, the faster and more reliable that process becomes—and with RPA, you can bring all your systems closer together through efficient data processes. Want to find out more about automation and healthcare interoperability? [Get in touch!](https://www.flobotics.io/contact) Or, check out our [automation ROI calculator](https://www.flobotics.io/roi-calculator) to assess the expected return on RPA investment in your organization. #### Like the article? Spread the word Written byMichał Rejman Chief Marketing Officer at Flobotics. [More from Michał](https://www.flobotics.io/our-editorial-team#rejman) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ Healthcare ### 5 Processes in the Healthcare Industry You Didn’t Know Could Be Automated Healthcare workflow automation: 5 everyday processes - from claims to billing - you can automate with RPA starting today. Michał RejmanAugust 01, 2022 ](https://www.flobotics.io/blog/healthcare-workflow-automation)[ HealthcareRCMAI ### RCM Outsourcing in Healthcare | 2026 RCM outsourcing in 2026: why offshore labor arbitrage is failing, and how Agentic AI outsourcing is replacing it. Bart TeodorczukFebruary 02, 2026 ](https://www.flobotics.io/blog/rcm-outsourcing-healthcare)[ Healthcare ### Top 30 Software Solutions for Healthcare in 2026 Healthcare software solutions: explore 30 essential tools for 2026, organized by function, to strengthen clinical care and streamline admin tasks. Yana PokoraDecember 23, 2024 ](https://www.flobotics.io/blog/healthcare-software) [All articles →](https://www.flobotics.io/blog) --- # Canada Satellite | Hundreds of SIM cards & healthy CRM Canonical: https://www.flobotics.io/blog/canada-satelite Author: Bart Teodorczuk Published: 2023-09-25 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Canada Satellite | Hundreds of SIM cards & healthy CRM [RPA](https://www.flobotics.io/blog?category=rpa) # Canada Satellite | Hundreds of SIM cards & healthy CRM [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published September 25, 2023Updated September 1, 2026 On this page - [Client](#client) - [The challenge](#the-challenge) - [The solution](#the-solution) - [The outcome](#the-outcome) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Client Canada Satellite provides satellite services and devices, including satellite phones, satellite TV, and satellite internet. With offshore branches such as Africa Satellite, Asia Satellite, Australia Satellite, Europe Satellite, and American Satellite, the company operates globally and supports customers across multiple regions and markets. ## The challenge Canada Satellite sells prepaid and postpaid satellite SIM cards through its online shop, where customer accounts and services are created automatically. The shop backend, however, was unable to handle critical logic related to prepaid SIM balances, expiration dates, and recharge decisions, as well as postpaid usage limits and overage costs that impact monthly invoicing. While the CRM system could track usage, balances, and invoices, checkout and credit card processing had to be executed in the shop backend, creating a disconnect between systems and introducing operational risk, manual work, and billing inaccuracies. ## The solution We implemented an RPA-based automation layer connecting the CRM and shop backend, leveraging the fact that both prepaid and postpaid processes were rule-based with a shared starting point in the CRM and a shared endpoint in the shop system. Automation began with the auto-recharge process, where bots retrieved data from the CRM database, validated it against business rules, and either triggered notifications in case of missing or invalid data or created customers and processed checkout automatically when validation succeeded. The automation handled payment failures by notifying customers via email and satellite SMS and successfully completed paid transactions by writing order details back into the CRM to trigger vendor top-up processes. Full reporting was implemented at every step, with all exceptions, edge cases, and successes reflected in CRM status updates. Building on this foundation, the postpaid process was automated quickly by reusing and extending the existing logic, adjusting database queries, and adding additional scenarios. ## The outcome The automated auto-recharge and postpaid processes now handle hundreds of SIM cards each month, ensuring uninterrupted satellite services that are often critical in emergency situations. Manual, repetitive work was eliminated, freeing Canada Satellite’s teams from error-prone processing and significantly improving operational reliability. At the same time, data consistency across systems increased, resulting in a more unified and healthier CRM environment for Canada Satellite and its global subsidiaries. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # What's Workflow Automation? How It Works, How It Helps & What Software to Use Canonical: https://www.flobotics.io/blog/workflow-automation Author: Filip Nasiadko Published: 2023-09-17 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/What's Workflow Automation? How It Works, How It Helps &… CEO Notes [RPA](https://www.flobotics.io/blog?category=rpa) # What's Workflow Automation? How It Works, How It Helps & What Software to Use [Filip NasiadkoCEO and Co-founder at Flobotics](https://www.flobotics.io/our-editorial-team#nasiadko) Published September 17, 2023Updated September 1, 2026 On this page - [What’s workflow automation?](#whats-workflow-automation) - [How does workflow automation work?](#how-does-workflow-automation-work) - [Workflow automation vs. RPA](#workflow-automation-vs-rpa) - [What is the best software for workflow automation?](#what-is-the-best-software-for-workflow-automation) - [Zapier](#zapier) - [monday.com](#monday-com) - [Nintex](#nintex) - [ProcessMaker](#processmaker) - [Integrify](#integrify) - [Use-cases of workflow automation](#use-cases-of-workflow-automation) - [Zoom x Nintex — rapid scaling through automation](#zoom-x-nintex-rapid-scaling-through-automation) - [Integrify x SONY — getting more from reporting.](#integrify-x-sony-getting-more-from-reporting) - [monday.com x Canva — creative campaigns on a global scale](#monday-com-x-canva-creative-campaigns-on-a-global-scale) - [What’s workflow automation got to offer your business?](#whats-workflow-automation-got-to-offer-your-business) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Whether it’s marketing, sales, finance, or customer service, tedious, manual tasks are a part of everyday jobs in any team. According to the state of business automation report by Zapier, 94% of workers admit that they perform [repetitive, time-consuming tasks](https://zapier.com/blog/state-of-business-automation-2021/). At the same time, 74% of managers and employees think their jobs could be [partially automated](https://www.workmarket.com/press/workmarket-2020-insight-report-what-artificial-intelligence-automation-mean-for-work). Realizing the need to streamline workflows, executives and business owners are increasingly pursuing new solutions such as workflow automation. Their goal: save time, money, and effort spent on manual tasks to redirect resources to higher-value tasks. But as with all new solutions, adopting automation comes with many questions. What’s workflow automation? How does it work? How do businesses use it? This article has you covered. ## What’s workflow automation? Workflow automation refers to using technology and software to streamline and automate sequences of tasks. Users define a series of actions that must be performed to achieve that. As a result, they create a digital representation of a workflow and rules that dictate how each sequence step should be executed. Following the sequence, workflow automation software can handle manual business processes end-to-end. Workflow automation aims to: - relieve workers from the manual effort, - enhance efficiency, - minimize errors, - reduce employee frustration, - improve collaboration, - enhance accountability, - standardize task execution. Workflow automation is a flexible tool that can be applied to various business processes in all departments. Fig. 01 · Workflows By team Which workflows you can automate - FinanceBudget approval, vendor contracts, payment tracking, purchase requests - SalesLead qualification, status and deal-stage updates, tasks for reps, follow-ups - MarketingSocial scheduling, welcoming new users, design requests, campaign subscriptions - Customer serviceOnboarding, ticket creation and priority, issue flagging - HROnboarding and offboarding, recruiting, feedback, candidate communication ## How does workflow automation work? Workflow automation implementation starts with identifying optimal processes and breaking them down into steps. Mapping the process onto a diagram or flowchart helps everyone involved learn more about the workflow, find potential challenges, and see which apps are used. First and foremost, this analysis enables you to assess if the workflow is suitable for automation and [evaluate automation ROI](https://www.flobotics.io/roi-calculator). Once you choose the process to automate and map out its steps, it’s time to configure the workflow steps. Workflow automation systems use an if-then, event-based logic. It serves as a blueprint for the software to follow when executing the sequence and how to move from one step to the next. With properly defined logic and conditions, the sequence can be performed end-to-end without human intervention. These blueprints are made up of three main components: - Triggers: Events that automatically initiate the workflow once they occur. Workflows can be triggered by various conditions, such as form completion, scheduled date, or data reaching a specific value. - Actions: Steps that are performed in the sequence, like data entry, document approval, or sending notifications. - Conditions: Conditions dictate how the system should execute actions depending on variable criteria. For instance, an approval process might follow different paths for different amounts requested. Integrating third-party software used in the workflow is an important part of the configuration. [Automating SAP](https://www.flobotics.io/blog/sap-automation), Salesforce, Jira, Slack, and other critical applications is necessary for the workflow to function correctly. Before deploying your workflow automation, you must test it to see if it works as intended. Plug the workflow into test datasets to ensure that it produces the expected results without errors. Still, no matter how well-programmed and carefully tested workflow automation is, exceptions will happen eventually. These exceptions may be business-related (e.g., missing or incomplete records that are required to perform a step) or caused by technical reasons (e.g., apps used in the process failing to load). In both cases, unexpected errors can bring the execution of the workflow to a halt. Exception-handling systems help you handle errors differently depending on the event. For some actions, a simple retry may troubleshoot the problem; for others, the system may notify an employee to fix the issue. Exception handling can also be programmed to try an alternative approach. That’s why setting up methods of dealing with unexpected errors is vital during workflow automation implementation. Fig. 02 · Workflows 7 steps Implementing workflow automation, step by step - 01Identify the process - 02Define the steps - 03Map the process - 04Deploy the automation - 05Test - 06Configure the system - 07Monitor and improve ### Workflow automation vs. RPA If all that sounds familiar, you’re on the right track: in some respects, workflow automation and RPA (Robotic Process Automation) share some common characteristics. They both aim to streamline business processes and offer similar benefits. Where they differ is scope. Workflow automation focuses on streamlining and connecting all steps of a more extensive business process, such as employee onboarding or invoice management. RPA, on the other hand, replicates human behavior to automate individual tedious tasks like data entry or document verification. Despite these differences, the two can successfully complement each other. Mapping step sequence before implementing workflow automation can reveal high-effort, manual tasks that can be expedited through RPA. In the combined approach, workflow automation links together individual tasks, which can be executed faster thanks to RPA. It’s also worth mentioning that leading automation platforms such as [UiPath and Power Automate](https://www.flobotics.io/blog/uipath-vs-powerautomate) combine both approaches to offer their users the best of the two worlds. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## What is the best software for workflow automation? Workflow automation tools combine mapping, configuring, monitoring, and other essential features you need to streamline business processes. But with dozens of workflow automation platforms, which one do you choose? Fig. 03 · Workflows 6 criteria What to look for in workflow automation software - 01Ease of use - 02Cost - 03Integrations - 04Customer support - 05Security - 06Scalability To help you out, we’ve selected five workflow automation platforms that will meet the needs of all organizations. ### Zapier Easy-to-use and set-up automation software that offers thousands of integrations with popular business apps. [Zapier](https://zapier.com/) serves as a connector between them, allowing users to automate multi-platform workflows seamlessly. With the free plan, users can automate up to 100 simple tasks per month, which makes it a good option for first-time workflow automation. Advanced users can also use Zapier’s developer platform to create custom applications for more complex sequences. ### monday.com [monday.com](http://monday.com) is a user-friendly project management platform with simple yet efficient workflow automation features and integrations. You can use one of its many purpose-made automation templates or build a custom workflow. The main focus is on standardizing and expediting workflows across teams by automating statuses, notifications, updates, comments, and other routine work management tasks. monday.com takes a visual approach, allowing managers to automate and monitor processes from customizable dashboards. ### Nintex Low-code workflow automation software that relies on drag-and-drop automation design tools to facilitate visualizing and automating even complicated tasks. Pre-built process maps and automation templates allow you to develop workflow automations quickly. Its standout features include e-signatures that enable users to produce, share soon, and sign documents, as well as robust reporting, analytics, and monitoring. Overall, [Nintex](https://www.nintex.com/) is a scalable platform suitable for businesses of any size. ### ProcessMaker Being an open-source workflow automation platform, [Process Maker](https://www.processmaker.com/) puts customization first. Automation developers can leverage API access to adjust the platform to their organization’s specific needs. On the other hand, Process Maker is built around an intuitive drag-and-drop interface that allows all users to design processes without coding. Similarly to monday.com, users can track workflows and KPIs from a configurable dashboard. ### Integrify A scalable workflow automation tool targeted medium- and large-sized businesses with more complex automation requirements. [Integrify](https://www.integrify.com/) focuses on enabling communication between departments during the implementation process. It also offers enhanced testing and auditing features for faster and more secure deployment. As a long-standing workflow automation company, Integrify offers exceptional customer support and consulting services. ## Use-cases of workflow automation Workflow automation is a flexible solution that can be applied in all industries. Let’s take a look at three success stories from various sectors. ### Zoom x Nintex — rapid scaling through automation Although the pandemic hampered the growth of most businesses, many others experienced a sudden surge in new users. One was Zoom, with a 354% increase in customers compared to the previous year. Zoom needed to expedite manual processes that used email and spreadsheets, such as order management, to accommodate that demand. The company offloaded these processes to an automated integration between Zendesk and Salesforce built with [Nintex](https://www.nintex.com/case-study/zoom-supports-boom-in-channel-business-with-nintex/) that automates all steps from order intake through confirmation and provisioning. As a result, the automation now handles 90% of all orders, allowing Zoom to scale its customer base quickly. Fig. 04 · Case Zoom × Nintex Zoom: scaling through automation GoalSpeed up manual processes run on email and spreadsheetsSolutionAn automated Zendesk–Salesforce integration built with Nintex 50%of all orders handled automatically ### Integrify x SONY — getting more from reporting. As SONY added new features to its Network Entertainment service, its Content Operations team struggled to keep the platform updated and personalized without detailed metrics. SONY turned to [Integrify](https://www.integrify.com/customers/sony-entertainment/) to help improve its data capture and reporting tools. Integrify’s solution was to improve ticket request prioritization and categorization. The deployment was entirely cloud-based, eliminating the need to install software and reducing the overall implementation time. The results came in quickly: SONY achieved an ROI in less than three months, reducing workflow costs by over 30% and the process management cycle by half. Fig. 05 · Case Sony × Integrify Sony: more from reporting GoalBetter data capture and reporting toolsSolutionAutomated Excel exports of open requests, prioritized by an algorithm 3 monthsto 100% ROI 30%lower workflow costs 50%shorter workflow cycle ### monday.com x Canva — creative campaigns on a global scale Canva, an online visual design platform, was going through a period of hypergrowth that overwhelmed its creative and marketing teams. To efficiently manage project progress, creative requests, and new employee onboarding while launching ad campaigns in over 20 new markets, Canva needed help. The answer was threefold: automate creative request management, increase project status transparency, and improve communication through automated Slack notifications. The team did all that using [monday.com](https://monday.com/customers/canva), replacing 657 manual actions, increasing creative output three times, and reducing production time by 40%. Fig. 06 · Case Canva × monday.com Canva: creative campaigns at global scale GoalSimpler processes for creative and marketing teamsSolutionAutomated creative requests, clearer project status, better communication 40%less production time 657manual actions automated ## What’s workflow automation got to offer your business? Zooming beyond individual tasks is essential when looking for new ways to optimize business operations. By looking at workflows, organizations can get a complete picture of their processes and automate them from start to finish, achieving more with less. At Flobotics, we know everything about automation, whether it’s relegating high-effort tasks to bots or improving business processes end-to-end. #### Like the article? Spread the word At Flobotics we specialize in automating processes that mattersmost in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byFilip Nasiadko CEO and Co-founder at Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### Automation’s for Everyone: 100 Real-World RPA Use Cases Across Industries | 2026 RPA use cases across industries: see 100 real-world examples of process automation in action, from healthcare to manufacturing. Michał RejmanFebruary 23, 2024 ](https://www.flobotics.io/blog/rpa-use-cases-across-industries)[ RPA ### Top Automation Trends in 2026 Automation trends for 2026: eight shifts in RPA, AI, and workflow automation that will shape how businesses operate this year. Krzysztof SzwedFebruary 03, 2025 ](https://www.flobotics.io/blog/top-automation-trends)[ RPA ### Robotic Process Automation vs. Machine Learning: Differences, Similarities, and Synergies RPA vs. machine learning: key differences, overlaps, and how combining both technologies can boost your automation strategy. Bart TeodorczukJune 21, 2023 ](https://www.flobotics.io/blog/robotic-process-automation-vs-machine-learning) [All articles →](https://www.flobotics.io/blog) --- # Top 10 RPA Implementation Challenges to Be Aware of Canonical: https://www.flobotics.io/blog/rpa-challenges Author: Krzysztof Szwed Published: 2023-08-22 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Top 10 RPA Implementation Challenges to Be Aware of [RPA](https://www.flobotics.io/blog?category=rpa) # Top 10 RPA Implementation Challenges to Be Aware of [Krzysztof SzwedHead of Delivery at Flobotics](https://www.flobotics.io/our-editorial-team#szwed) Published August 22, 2023Updated September 1, 2026 On this page - [Top 10 RPA Implementation Challenges](#top-10-rpa-implementation-challenges) - [Technical Challenges](#technical-challenges) - [Business Challenges](#business-challenges) - [Regulatory and Compliance Challenges](#regulatory-and-compliance-challenges) - [How to Overcome RPA Implementation Challenges?](#how-to-overcome-rpa-implementation-challenges) - [Your Next Move Toward RPA](#your-next-move-toward-rpa) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) According to a study by Ernst & Young, up to 50% of initial RPA (Robotic Process Automation) projects fail. A knee-jerk response to this metric would be to write off the technology as moderately effective and turn to other solutions. But hold on for a minute… …because the same study shows that RPA projects fail because of the technology and how RPA is implemented. Handled by [experts in automation deployment](https://www.flobotics.io/), RPA can significantly impact process efficiency, resulting in time and cost savings, productivity boosts, and operational flexibility. Just have a look at dozens of [successful RPA implementations](https://www.flobotics.io/blog/rpa-use-cases-across-industries) across industries. But to reap those rewards, you need to know how to recognize and deal with common issues affecting RPA projects. To get you started, we’ll investigate the most notorious RPA challenges and the strategies to overcome or prevent them. ## Top 10 RPA Implementation Challenges From our experience, the most common RPA challenges organizations meet fall into three categories: technical, business, and regulatory. Let’s see how they differ. Fig. 01 · RPA Challenges The most common RPA implementation challenges - Technical - A stable infrastructure - Integration with existing systems - Scalability - Long-term maintenance and monitoring - Business - A change management strategy - Employee resistance and retraining - Finding and prioritizing processes - Clear cost and ROI analysis - Safety and compliance - Meeting regulations - Fighting cybersecurity threats ### Technical Challenges #### Integration with Existing Systems One of the first challenges businesses must consider when planning RPA implementation is compatibility with the currently used software. PwC reports that [45% of companies using AI ](https://www.pwc.com/gx/en/services/people-organisation/workforce-of-the-future/workforce-of-the-future-the-competing-forces-shaping-2030-pwc.pdf)and robotics have encountered difficulties with deployment or integration. A company’s existing systems often combine different technologies, user interfaces, and protocols that need to stay in sync. An inappropriate data type can also be an issue: RPA works best with structured data and may require additional technologies like AI or OCR (optical character recognition) to process unstructured datasets. Moreover, organizations may implement RPA alongside other solutions like IoT devices, mobile apps, SaaS platforms, or other connected data sources. The role of RPA is to link and orchestrate them. However, RPA solutions can be limited by the number and types of endpoints to which they can connect. Major RPA platforms such as UiPath offer out-of-the-box [RPA integration](https://www.uipath.com/solutions/technology) with popular third-party enterprise systems like SAP, Salesforce, or Amazon Web Services. For custom integrations, it’s best to involve an experienced RPA implementation team. #### Scalability As organizations grow, their data flow and workload volumes increase. Along the way, some automated processes change or must be adjusted for regulatory updates. At this point, RPA systems built to support smaller capacities may start underperforming. One possible solution is to assign more robots to accommodate the growing workload, but this will quickly start eating up your resources. For this reason, scalability may be particularly challenging for smaller organizations that can’t afford to throw extra robots at the increasingly demanding processes infinitely. RPA systems should be built with expansion in mind right from the start to prevent scalability issues. A [report by McKinsey](https://www.mckinsey.com/capabilities/operations/our-insights/the-imperatives-for-automation-success) hints at communication between departments as an important enabler of RPA scaling. Planning for gradual growth will allow for a thoughtful and dynamic distribution of robots between tasks depending on the demand for processing power rather than complicating the processes. Another solution may be uncovering improvements with process mining tools. #### Infrastructure RPA bots need a robust and reliable IT infrastructure to operate efficiently. It should ensure enough processing power and storage capacity to accommodate the additional stress placed on the system by RPA and keep all scripts running. The infrastructure must also be stable to allow bots to work reliably around the clock. For that, consider limiting the influence of external factors or deploying a failover server. Another requirement is [security](https://www.flobotics.io/blog/8-security-practices-for-rpa-implementation). RPA bots often process sensitive customer data, and organizations must implement adequate protection measures to keep these records safe. There are multiple ways to ensure that, from ensuring unique log credentials for each bot and avoiding using hard-coded access rights to regular review and validation of RPA scripts. All activities like that should be a part of a strategic, overarching security framework that requires expert analysis and planning. #### Long-Term Maintenance and Monitoring It’s easy to assume that bots can be left to themselves once deployed. But in reality, the true work begins only after the RPA implementation is complete. Any deviation from the pre-programmed sequence can confuse RPA bots and cause errors. Still, changes are inevitable as your RPA platform must be adjusted for regulation updates, changing business requirements, and new additions to your tech stack. Even when the system operates properly, it will eventually degrade without any modifications. The RPA tool will accumulate bugs, or a database can reach its capacity, leading to memory overflow. Monitoring and testing these changes will help you quickly find and fix errors and find issues that went unnoticed during [RPA implementation](https://www.flobotics.io/blog/rpa-development-process). Observe the performance of your RPA system and regularly check for updates. Automate regular maintenance operations such as running stress tests, cleaning cache registers, or copying data from temporary storage to a larger unit, and appoint an RPA owner who’ll oversee the condition of your RPA bots. Process automation ROI calculator See what automating a process could save you in a few minutes. [Calculate ROI →](https://www.flobotics.io/roi-calculator) ### Business Challenges #### Change Management New technologies give rise to new possibilities but also new challenges. RPA implementation is no different and will affect how your business operates. To pave the way for digital transformation, you must plan for it from a purely technological perspective and consider people and processes. If you ignore the people relevant to the automated processes, you will likely face fear or even outright aversion to the new technology. Getting executive buy-in is crucial and a good place to start, as senior management can influence company culture and lead by example. Regarding processes, treating RPA implementation as an opportunity to revisit your current operations is essential. Develop a clear vision of what you want to achieve by automating each workflow, and don’t overlook the improvements that can be made along the way without automation. #### Employee Resistance and Retraining Usually, any change to the tried and true ways of doing things is met with strong resistance from employees, even if the change will eventually be for the better. RPA is no different—resistance to change is the third [most common barrier](https://www.deloitte.com/us/en/insights/topics/talent/intelligent-automation-2022-survey-results.html) for companies launching robotic automation. Before the benefits of RPA implementation kick in, the daily schedules of some of your employees will likely be disrupted. Also, using RPA in daily work needs constant communication and training in new, often [technical skills](https://www.flobotics.io/blog/rpa-non-technical-developer). You can address these RPA challenges by educating your staff about the benefits of working alongside bots and financing employee training. As with any automated solutions, some of your employees will fear that RPA bots will replace them. Focus on dispelling these fears early by presenting bots as tools rather than competitors. #### Process Identification and Prioritization Just because a process can be automated does not mean it should be. This is for several reasons. Firstly, not all steps in the sequence can be suitable for automation. Finding that out halfway through the RPA implementation process can derail the entire initiative or even make it completely pointless. Then, it’s important to remember that despite its flexibility, RPA isn’t suitable for automating all tasks. The technology performs at its best, automating repetitive, unvarying, lower-value work, but may prove inefficient with highly complex or inconsistent tasks. The final reason is the lack of a clear objective. What is the goal of the automation project? [What tasks to automate?](https://www.flobotics.io/blog/what-processes-to-automate) Could you prioritize automating this particular task over others? Knowing the answers to these questions is paramount for the success of any RPA project. Fig. 02 · RPA What to avoid Tasks to avoid automating with RPA Avoid tasks that… - 01Are too complex - 02Need human judgment or creativity - 03Vary too much - 04Change often - 05Run rarely #### Cost and [ROI Analysis](https://www.flobotics.io/roi-calculator) The most essential factor to consider when picking candidates for [RPA implementation](https://www.flobotics.io/blog/rpa-development-process) is finding whether automation will bring profits. Tempted by the promises of massive savings, companies often assign RPA to tasks with the highest headcount. Unfortunately, these processes usually involve heavy workloads and lots of exception handling, ultimately leading to their failure. Another common mistake is to undervalue the costs of RPA implementation relative to the benefits. Depending on license costs, the scope of the project, its complexity, and any additional infrastructure needed, expenses can ramp up quickly. It’s also easy to forget about long-term maintenance costs, which is crucial for RPA success. These early RPA failures have a lasting impact on future automation adoption, as decision-makers within the company will be less willing to invest in solutions that previously didn’t deliver the expected results. All that said, RPA implementation can bring quick ROI, given enough planning and careful selection of automated tasks. Auditing your processes and working with an [RPA consultant](https://www.flobotics.io/about-us) are great starting points for achieving a quick ROI. ### Regulatory and Compliance Challenges #### Regulatory Compliance Legal requirements pose another major challenge for organizations considering RPA. Depending on the automated process, bots may process sensitive data such as customer records, financial data, and personal information that you’re legally obligated to keep secure. From the RPA implementation perspective, regulatory requirements have several implications. You must establish RPA governance rules defining responsibilities and ownership at all automation and data processing stages. Companies must place authorization measures like securely stored passwords or two-factor authentication to prevent accidental leaks or insider threats. Lastly, protecting personal data, in the long run, will require data usage monitoring and running regular, security-oriented audits of your automated processes. #### Cybersecurity Threats Like any new addition to your tech stack, RPA implementation adds another potential surface for cyber threats. Falling victim to any attack puts your business, its customers, and reputation at risk. Even worse, these attacks can incur non-compliance fines in privacy-sensitive industries like healthcare, finance, or insurance. Keeping yourself safe from cyber threats will require additional security measures: - Monitor the use of safety data to identify threats early. - Minimize the risk by limiting third-party services, connections, and excessive data input. - Encrypt sensitive data to ensure it stays secure even if a leak happens. - Store activity logs on another system to ensure their integrity. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## How to Overcome RPA Implementation Challenges? As you can see, there’s a lot to wrap your head around before starting your RPA implementation. We’ve already given you some tips when discussing these RPA challenges, but here are more strategic ways to approach them. Fig. 03 · RPA 5 pillars 5 pillars of a successful RPA implementation - 01Business process evaluation - 02An ROI-first approach - 03A complete implementation plan - 04Employee buy-in - 05Security and compliance measures - Assess business processes: Define the expected benefits of automating the target process. Prioritize low- or medium-complexity processes for your first RPA implementation. You don’t need to automate the entire workflow: focus on critical steps within the process with the highest relative impact. - Create a detailed RPA implementation roadmap: How will you [measure the results of RPA implementation](https://www.flobotics.io/blog/rpa-successs-metrics)? What are your plans for scaling? Are there any other technologies you could leverage? Defining an RPA implementation strategy and answering these questions in advance will go a long way in the future. - Focus on ROI and savings: Generally, automating high-effort, standardized, customer-facing tasks stands a much higher chance of bringing ROI than more complex ones. Remember that a full RPA implementation in a more minor task is often much more beneficial than taking a long time and excessive resources trying to automate an extensive process end-to-end. - Get everyone involved: With your eyes set on the tangible benefits, it’s easy to forget that the primary goal of RPA is to aid employees in their daily tasks. To get everyone on board, you must educate your employees, ask for feedback, show them the benefits of RPA implementation, and promote cross-department alignment. To effectively automate a process, you’ll need the involvement of different parts of your organization, such as IT, marketing, customer service, or finance. - Prioritize security and compliance: Warranting safe operations of your RPA bots is something you must consider from the beginning. Implement auditing and monitoring systems, and move sensitive data from insecure locations to encrypted, central ones. Develop a risk management framework for all your RPA operations, covering access rights, data governance, and activity logging. - Build a strong relationship with your RPA vendor: Find an RPA vendor with [technical automation experience](https://www.flobotics.io/blog/rpa-non-technical-developer) and a track record of working with diverse clients and projects of all scales. Establish efficient communication with your [RPA developer](https://www.flobotics.io/contact) and be clear about your expectations while staying open to their suggestions. Don’t be afraid to rely on your vendor’s expertise to identify the optimal automation candidates and guide you through the implementation process. ## Your Next Move Toward RPA Whether it’s linking RPA with existing software or promoting an automation-friendly company culture, Flobotics has helped [dozens of clients](https://www.flobotics.io/case-studies) overcome RPA implementation challenges. Contacct us to see what we can do for your business. #### Like the article? Spread the word Written byKrzysztof Szwed Head of Delivery at Flobotics. [More from Krzysztof](https://www.flobotics.io/our-editorial-team#szwed) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Unearthing RPA Potential: What You Need to Know About Task Mining & UiPath Canonical: https://www.flobotics.io/blog/task-mining-uipath Author: Bart Teodorczuk Published: 2023-07-28 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Unearthing RPA Potential: What You Need to Know About Task… [RPA](https://www.flobotics.io/blog?category=rpa) # Unearthing RPA Potential: What You Need to Know About Task Mining & UiPath [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published July 28, 2023Updated September 1, 2026 On this page - [What is task mining?](#what-is-task-mining) - [How does task mining work?](#how-does-task-mining-work) - [Task mining vs. process mining](#task-mining-vs-process-mining) - [Task Mining & UiPath](#task-mining-uipath) - [Assisted and unassisted task mining in UiPath](#assisted-and-unassisted-task-mining-in-uipath) - [Integrations between Task Mining & UiPath tools](#integrations-between-task-mining-uipath-tools) - [Task mining & UiPath: what are the benefits?](#task-mining-uipath-what-are-the-benefits) - [Better task understanding](#better-task-understanding) - [Identifying automation opportunities](#identifying-automation-opportunities) - [Enhanced process optimization](#enhanced-process-optimization) - [Employee experience and engagement](#employee-experience-and-engagement) - [Integration with UiPath RPA Platform](#integration-with-uipath-rpa-platform) - [What to keep in mind before implementing task mining?](#what-to-keep-in-mind-before-implementing-task-mining) - [Bottom line](#bottom-line) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Regarding business process optimization, RPA (Robotic Process Automation) and other automation technologies have been getting much attention recently, and it’s easy to understand why. Companies that have implemented RPA report multiple benefits, including increased productivity, improved accuracy, higher compliance, and cost savings. No wonder increased RPA adoption is one of the predominant current automation trends. But what many automation enthusiasts don’t talk about is how RPA adopters get to the point where they can benefit from these advantages. Or, more specifically, how they know which tasks to automate. This is a crucial question, as recognizing proper automation candidates can make the difference between an RPA success and an RPA failure. Luckily, leading-edge RPA platforms offer the tools to support organizations in discovering and selecting [the best processes to automate](https://www.flobotics.io/blog/what-processes-to-automate). One of them is task mining. Today, we’ll discuss the task mining capabilities of our RPA tool of choice—UiPath—and how they empower its users to find the tasks that will benefit the most from automation. ## What is task mining? Before tackling anything else, let’s look at the definition of task mining. Task mining automatically captures and analyzes user interactions to uncover and map all steps within the workflows these users perform. In practice, task mining involves recording or logging user behavior, such as mouse clicks, keyboard inputs, and screen transitions, to gain insights into the sequence of actions that make up specific tasks. And why bother recording all these actions meticulously? Because task mining helps identify patterns, bottlenecks, variations, and inefficiencies in workflows, enabling organizations to streamline processes, improve productivity, and identify areas for optimization. Indeed, more and more organizations realize that potential, stimulating the growth of the task-mining tools market. In the coming years, [the task mining software industry will grow](https://www.everestgrp.com/press-releases/task-mining-software-market.html) by 75-85%. To see how UiPath’s task mining compares with Celonis and Kyp.ai, read our [guide to the leading task mining tools](https://www.flobotics.io/blog/task-mining-tools). ### How does task mining work? - Data collection from user devices. The first step in task mining is collecting data from users’ machines. The records captured can include keystrokes, clicks, scrolls, user inputs, recordings, screenshots, and more. Task mining tools often use OCR (optical character recognition) and NLP (natural language processing) to extract additional context details from this data. - Segmenting and dividing collected data. Next, machine learning algorithms break down this data into specific tasks such as purchase order creation or customer service ticket submission. The data can be combined with event log data to help contextualize performance. This view of the data allows businesses to discover and fix bottlenecks accordingly. Task mining is particularly beneficial from the standpoint of RPA. Through monitoring user interactions with applications, task mining allows organizations to identify repetitive, rule-based tasks that are the best candidates for automation. With that, businesses can pinpoint and prioritize areas where RPA can be applied most effectively to reduce manual effort and free up valuable human resources for more strategic tasks. By automating mundane and repetitive tasks through RPA, organizations can significantly boost productivity and reduce error rates. All in all, task mining acts as an automation enabler, guiding organizations toward unlocking the full potential of RPA to drive their digital transformation. ### Task mining vs. process mining If you’ve heard the term “[process mining](https://www.flobotics.io/blog/process-mining-automation)” before, you’re probably wondering how it differs from task mining. The two are related and often performed together. Still, they aren’t the same. Process mining focuses on optimizing business processes as a whole, e.g., supply chain or customer service. Task mining, on the other hand, aims to improve individual tasks that may be parts of larger processes. The two also rely on different metrics. Process mining uses business data pulled from systems like CRM or ERP, while task mining uses desktop activities and interaction data such as clicks, keystrokes, screenshots, and recordings. Put shortly, process mining focuses on the large picture, and task mining is concerned with the individual parts of each process. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Task Mining & UiPath We’ve already said that we’ll be explaining task mining using the example of UiPath, which we usually choose to work with for these types of projects. It’s not just a matter of our preference for the tool that makes us go with it most of the time. Among the top RPA platforms, such as Automation Anywhere, Blue Prism, Power Automate, or [Google Cloud Platform](https://www.flobotics.io/blog/uipath-vs-gcp), UiPath has consistently been named the industry leader. It’s also the tool we decided to use due to its features and capabilities, both on the side of the developer and the end-user. When it comes to task mining capabilities, UiPath has its own tool called simply [UiPath Task Mining](https://www.uipath.com/product/task-mining). It’s an AI-based solution that leverages machine learning to investigate user desktop activity and identify automation opportunities. ### Assisted and unassisted task mining in UiPath What is also worth knowing regarding the combination of the UiPath automation platform and task mining technology is that UiPath offers two types of task mining: assisted and unassisted. - Assisted task mining is concerned with analyzing known tasks for potential improvements. For that, users need to capture the steps that make up the sequence using UiPath’s recorder or build a diagram independently. Then, they can tweak the process by adding, removing, and labeling each step, creating an accurate task mapping. The collaborative process can be shared with other team members to reflect better any task variations that will later be merged into a top-down workflow overview. Once the overview is complete, users can export it as a document that will inform automation development. With Task Mining, UiPath users can map all stages of any task into a clear diagram. (image source: [UiPath](https://www.uipath.com/product/task-mining)) - In contrast, unassisted task mining aims to discover new insights and repetitive tasks by recording user activity. Normally, this analysis would involve weeks of interviews, workshops, and guesswork without the guarantee that it’ll identify any new automation candidates. Unassisted task mining allows users to gather that information automatically without disrupting your team’s work. First, invite your colleagues to participate in the task mining project. The task miner will then monitor activities in the specified applications. After enough data is captured, the records are processed by UiPath’s machine learning algorithm, which provides users with a per-app overview of activities, time spent on individual tasks, their occurrences, and the number of actions needed to complete them. Each task can be presented visually, with screenshots of all actions taken to understand the workflow better. ### Integrations between Task Mining & UiPath tools UiPath offers users a complete suite of discovery and automation tools by integrating other systems with Task Mining. As mentioned earlier, task mining is an integral part of process mining, and the same holds for UiPath. UiPath has its own [Process Mining](https://www.uipath.com/product/process-mining) tool that gives you a birds-eye view of all your workflows. From there, you can zoom in on individual sequences using Task Mining to understand better how users interact with applications when working on specific tasks on a desktop level. UiPath Process Mining gives you an overview of all end-to-end business processes. (image source: [UiPath](https://www.uipath.com/product/process-mining)) Once you identify automation opportunities using Task Mining, [UiPath Automation Hub](https://www.uipath.com/product/automation-hub) helps you automate inefficient manual sequences. Automation Hub is a one-stop management center for all your UiPath automation projects. You can export any traces found using UiPath Task Mining to Automation Hub, complete with screenshots, descriptions, relevant links, and documentation. With that, you can set priorities for your RPA ideas and collaborate with other stakeholders to streamline the development of automation projects. ## Task mining & UiPath: what are the benefits? ### Better task understanding With UiPath’s task mining capabilities, organizations can gain a comprehensive, granular understanding of how their employees handle their tasks and how it varies between employees. For instance, managers may understand how and why real-life task execution varies from the set standards and whether it’s more or less efficient. This analysis serves as a solid foundation for process improvement and automation initiatives. ### Identifying automation opportunities Since enabling automation is one of the primary goals of task mining, UiPath also gives organizations the tools necessary to spot RPA opportunities. By dissecting each task into a sequence of steps and automatically mapping them onto clear diagrams, Task Mining helps reveal inefficiencies. With this knowledge, businesses can prioritize their automation efforts and focus on the highest-impact areas. ### Enhanced process optimization While automation is a significant step toward maximizing the effectiveness of business processes, it’s far from the only one. In addition to implementing RPA, businesses can streamline their workflows by removing unnecessary steps, simplifying the remaining ones, and consolidating data. UiPath Task Mining enables all these improvements by helping organizations identify bottlenecks, find task variations, and increase transparency. ### Employee experience and engagement Assisted task mining makes it easy to get all team members involved in the optimization process. With that, managers can ensure everyone’s voice is heard and that the entire team works together to simplify everyday duties. And if you’re looking for new insights, unassisted task mining will allow you to get them without forcing everyone to participate in long and potentially redundant workshops. ### Integration with UiPath RPA Platform As a part of a larger UiPath RPA suite, Task Mining connects seamlessly with other tools such as Process Mining and Automation Hub. This allows organizations to use a single platform throughout the entire automation implementation process, from research and discovery to deployment, eliminating friction. ## What to keep in mind before implementing task mining? Despite all the benefits of task mining, there are a couple of factors you need to consider before you get down to implementation. - Assess the benefits: Weigh the costs and time it will require against the potential benefits. For instance, processes in smaller organizations are normally less complex and easier to understand, so task mining may not be necessary. (If you aren’t sure how to balance that, our [UiPath implementation specialists](https://www.flobotics.io/uipath-services) are here to help). - Get employees’ buy-in: Some people resist change, and others may feel that task-mining tools are being used to spy on them. To remove these roadblocks, make sure that you communicate the benefits of task mining and automation to your team members. - Configuring the task mining tool: Setting the Task Mining UiPath tool for end users can be complicated and may require the assistance of experienced UiPath developers. Once set up, creating and managing task-mining projects can be done without programming skills. - Ensure data privacy: Task mining involves recording user actions, which may raise privacy concerns. To dispel these worries, you should inform your users, get their approval, and protect their data through anonymization. - Get the full context: The key to successful automation is prioritizing the tasks that have the greatest impact on your business relevant to the implementation effort. Running tasks and process mining is a good idea to ensure you get the full picture. ## Bottom line From our own experience, we know that any successful RPA project starts with finding the right automation opportunities. Task mining is the first step toward making that discovery. If you want to hear more, [let us know](https://www.flobotics.io/contact)—we can help you with everything related to task mining, UiPath, and RPA and set your businesses on the path to process understanding and optimization. #### Like the article? Spread the word Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPAAI ### UiPath vs. Celonis vs. Kyp.ai: Comparing Top Task Mining Tools UiPath vs. Celonis vs. Kyp.ai: features and pricing compared to help you pick the right task mining tool for 2026. Bart TeodorczukNovember 20, 2023 ](https://www.flobotics.io/blog/uipath-vs-celonis-vs-kypai)[ RPA ### Process Mining vs RPA: How They Work Together to Improve The Efficiency of Your Business Process mining and RPA: how combining the two turns automation candidates into measurable efficiency gains for your business. Bart TeodorczukJanuary 30, 2023 ](https://www.flobotics.io/blog/process-mining-automation)[ RPA ### Why Your Non-Technical RPA Developer Sucks RPA for non-technical developers: why coding skills still matter and where non-technical RPA developers fall short. Karl MielnickiJune 15, 2021 ](https://www.flobotics.io/blog/rpa-non-technical-developer) [All articles →](https://www.flobotics.io/blog) --- # Medical Billing Management: Best Practices, Key Metrics and Automation Canonical: https://www.flobotics.io/blog/medical-billing-management Author: Yana Pokora Published: 2023-07-25 Updated: 2026-09-08 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Medical Billing Management: Best Practices, Key Metrics… [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm)[RPA](https://www.flobotics.io/blog?category=rpa) # Medical Billing Management: Best Practices, Key Metrics and Automation [Yana PokoraContent Manager at Flobotics](https://www.flobotics.io/our-editorial-team#pokora) Published July 25, 2023Updated September 8, 2026 On this page - [The Numbers Don’t Lie](#the-numbers-dont-lie) - [What Is Medical Billing Management?](#what-is-medical-billing-management) - [Medical Billing Management vs. Revenue Cycle Management: What’s the Difference?](#medical-billing-management-vs-revenue-cycle-management-whats-the-difference) - [The 8-Stage Medical Billing Cycle](#the-8-stage-medical-billing-cycle) - [1. Patient Registration and Demographic Verification](#1-patient-registration-and-demographic-verification) - [2. Insurance Eligibility Verification](#2-insurance-eligibility-verification) - [3. Prior Authorization](#3-prior-authorization) - [4. Clinical Documentation and Charge Capture](#4-clinical-documentation-and-charge-capture) - [5. Medical Coding](#5-medical-coding) - [6. Claims Submission and Scrubbing](#6-claims-submission-and-scrubbing) - [7. Payment Posting and Reconciliation](#7-payment-posting-and-reconciliation) - [8. Denial Management and Patient Collections](#8-denial-management-and-patient-collections) - [5 Key Medical Billing Metrics – and What “Good” Actually Looks Like](#5-key-medical-billing-metrics-and-what-good-actually-looks-like) - [The 5 Billing Reports That Surface Revenue Leakage](#the-5-billing-reports-that-surface-revenue-leakage) - [1. Accounts Receivable Aging Report](#1-accounts-receivable-aging-report) - [2. Key Performance Indicators (KPI) Report](#2-key-performance-indicators-kpi-report) - [3. Top Carrier / Insurance Analysis Report](#3-top-carrier-insurance-analysis-report) - [4. Denial Analysis Report](#4-denial-analysis-report) - [5. Patient Payment Collection Report](#5-patient-payment-collection-report) - [The 5 Most Common Root Causes of Billing Failure](#the-5-most-common-root-causes-of-billing-failure) - [1. Front-End Eligibility and Demographic Errors](#1-front-end-eligibility-and-demographic-errors) - [2. Authorization Gaps](#2-authorization-gaps) - [3. Coding Inaccuracies and Documentation Gaps](#3-coding-inaccuracies-and-documentation-gaps) - [4. Denial Write-Offs](#4-denial-write-offs) - [5. Underpayment Absorption](#5-underpayment-absorption) - [8 Best Practices to Improve Medical Billing Management](#5-best-practices-to-improve-medical-billing-management) - [1. Verify Eligibility at Every Relevant Touchpoint, Not Just Once](#1-verify-eligibility-at-every-relevant-touchpoint-not-just-once) - [2. Implement Pre-Submission Claim Scrubbing With Payer-Specific Rules](#2-implement-pre-submission-claim-scrubbing-with-payer-specific-rules) - [3. Work Denials by Root Cause, Not by Claim](#3-work-denials-by-root-cause-not-by-claim) - [4. Automate Payment Posting and Underpayment Detection](#4-automate-payment-posting-and-underpayment-detection) - [5. Run Your Five Core Reports on a Fixed Monthly Cadence](#5-run-your-five-core-reports-on-a-fixed-monthly-cadence) - [6. Offer Flexible Payment Plans](#6-offer-flexible-payment-plans) - [7. Reduce Missed Appointments](#7-reduce-missed-appointments) - [8. Train Your Team](#8-train-your-team) - [Compliance: What Has Changed and What Billing Teams Must Know](#compliance-in-2025-what-has-changed-and-what-billing-teams-must-know) - [The No Surprises Act](#the-no-surprises-act) - [HIPAA Administrative Simplification](#hipaa-administrative-simplification) - [Prior Authorization Reform](#prior-authorization-reform) - [How Automation Transforms Medical Billing Management](#how-automation-transforms-medical-billing-management) - [What Would a 3% Improvement Cost You to Ignore?](#what-would-a-3-improvement-cost-you-to-ignore) - [Ready to Fix Your Billing Cycle?](#ready-to-fix-your-billing-cycle) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## The Numbers Don’t Lie Medical billing management is one of the most consequential back-office functions in healthcare – and one of the most poorly optimized. Consider: - U.S. healthcare loses over $16 billion annually to revenue cycle inefficiencies (MGMA) - 11–12% of all claims are denied on first submission, with some payers reaching 17–19% (Experian State of Claims 2025) - 65% of denied claims are never reworked – they're written off as unrecoverable (HFMA) - 40 cents of every dollar spent in U.S. healthcare goes to billing and administrative overhead (CMS / NEJM) - The average cost to rework a single denied claim: $25–$180 depending on complexity (HFMA) The financial stakes of poor billing management are not abstract. They show up in your Days in AR, your Net Collection Rate, and in your practice’s ability to invest in care quality. This guide covers what medical billing management involves, the complete medical billing cycle, the KPIs that separate high performers from the rest, the reports that surface where revenue is leaking, and what modern automation actually changes in practice. ## What Is Medical Billing Management? Medical billing is submitting claims to health insurance companies and following up on them, so that a healthcare provider or medical billing company gets paid for its services. Three parties take part: - The patient - The healthcare provider (hospitals, physicians, physical therapists, emergency rooms, outpatient facilities, and other places where medical services are performed) - The insurance company or payer Medical billing management arranges [payment](https://www.flobotics.io/rcm-automation) between these three parties: the billing manager makes sure providers are paid for their services by billing patients and payers. The job includes: - Working with insurance companies on contracts - Training and supervising the team so everyone follows proper medical coding practices - Accepting payments from patients, insurers and government health programs - Keeping all paperwork and records in order - Talking to patients about their bills - Tracking payments from insurers and patients, and managing patient accounts receivable - Testing billing software to make sure the system runs efficiently - Making sure employees and patients follow all policies Many of these tasks are manual and repetitive, which is where automation makes the biggest difference. ## Medical Billing Management vs. Revenue Cycle Management: What’s the Difference? Medical billing management refers specifically to the processes concerned with submitting and following up on claims with payers – coding, claim submission, denial management, and payment posting. It is the financial transaction layer of patient care. Revenue Cycle Management (RCM) is the broader end-to-end workflow that encompasses everything from the moment a patient schedules an appointment through the final zero balance on their account. Billing is a critical component of RCM, but RCM also includes pre-authorization, eligibility verification, clinical documentation, patient financial communication, and reporting. In practice: improving medical billing management is often the highest-leverage intervention within a broader [RCM improvement program](https://www.flobotics.io/rcm-automation). ## The 8-Stage Medical Billing Cycle Understanding where money gets stuck requires mapping every stage of the billing cycle from start to finish. ### 1. Patient Registration and Demographic Verification Accurate billing starts at registration. Patient name, date of birth, insurance ID, and subscriber information must match payer records exactly. A single transposed digit in a member ID generates an eligibility denial at claim submission. The Advisory Board reports that demographic and technical errors have increased 100% in recent years as a denial driver – making front-end data quality the most controllable and highest-leverage variable in the billing cycle. ### 2. Insurance Eligibility Verification Before every appointment, the practice must confirm that the patient’s insurance is active, the services planned are covered, and the patient’s cost-sharing obligations are understood. Eligibility errors are the most common first-pass denial trigger across all specialties. Automated [eligibility verification](https://www.flobotics.io/agents/eligibility-check-automation) run 24–48 hours before the appointment catches coverage issues before they become billing problems. ### 3. Prior Authorization For procedures, imaging, specialist referrals, and specialty medications requiring payer approval, prior authorization must be obtained, confirmed, and documented before the service is rendered. Authorization-related denials are among the top three denial categories across all specialties – and are among the most expensive to recover retroactively. [Automated prior authorization workflows](https://www.flobotics.io/agents/prior-authorization-automation) reduce the average auth cycle from 20–45 minutes to minutes. ### 4. Clinical Documentation and Charge Capture Every service delivered must be documented in the clinical record and captured as a billable charge. Documentation specificity determines which diagnosis and procedure codes can legitimately be assigned. Vague or incomplete documentation is the primary driver of medical necessity denials and DRG downgrades in inpatient settings. ### 5. Medical Coding Clinical documentation is translated into standardized ICD-10 diagnosis codes and CPT/HCPCS procedure codes. Coding accuracy determines whether claims will be accepted by payers and at what reimbursement rate. AHIMA estimates that coding errors account for 30–40% of all claim rejections. It’s also worth noting: CPT codes must be verified at the start of each calendar year – using an expired CPT code guarantees an immediate rejection. ### 6. Claims Submission and Scrubbing Coded claims are submitted electronically to payers via clearinghouse, using the ANSI X12 837 standard. Before submission, claims undergo scrubbing – a rules-based review that catches common errors and payer-specific requirement violations. Best-in-class practices achieve a Clean Claim Rate (CCR) of 98–99%, eliminating the compounding rework costs that low CCR generates. ### 7. Payment Posting and Reconciliation When payers process claims, they return Electronic Remittance Advice (ERA/835) files detailing payment amounts, contractual adjustments, and reason codes for denials or underpayments. Accurate, timely payment posting is foundational to AR management – unprocessed remittance creates artificial AR inflation and masks denial patterns. Automated posting processes ERA files at thousands of claim lines per hour versus 20–40 manually. ### 8. Denial Management and Patient Collections Denied claims require investigation, correction, and resubmission or formal appeal within payer-specific timelines. Patient balances are billed to the patient after insurance adjudication. Both processes are resource-intensive and time-sensitive. [Automated denial management](https://www.flobotics.io/agents/denials-management-automation) classifies and routes every denial, ensuring nothing ages toward write-off by default. ## 5 Key Medical Billing Metrics – and What “Good” Actually Looks Like You cannot improve what you do not measure. These five metrics collectively define billing performance and reveal where revenue is leaking. Metric | Definition | Best-in-Class | Industry Average | At Risk | Clean Claim Rate (CCR) | % of claims accepted first-pass by payers | 98–99% | 90–95% | <90% | Denial Rate | % of submitted claims denied on first submission | <5% | 8–12% | >15% | Days in AR (DAR) | Average days from service to payment receipt | 25–35 days | 40–50 days | >60 days | Net Collection Rate (NCR) | % of collectible revenue actually collected | 97–99% | 90–95% | <88% | Cost to Collect (CTC) | Total cost to collect $1 of net revenue | 3–4% | 6–8% | >10% | What does a gap from average to best-in-class look like in practice? A sub-200-bed hospital in the Midwest ran an AR aging analysis and discovered its held claims were 27% above peer benchmarks – representing $5.24 million in stuck revenue. The director of patient financial services pulled a claims-held review and made AR release the top priority. Within six weeks, AR days on held claims dropped from 3.5 to 1.0 days, cutting stuck revenue to $1.41 million. That recovery came entirely from running the right reports and acting on what they showed. ## The 5 Billing Reports That Surface Revenue Leakage Most practices generate billing data constantly but review it reactionally – only after a problem becomes too large to ignore. The practices that maintain best-in-class metrics run five core reports proactively, on a defined cadence, using them as an early warning system rather than a post-mortem. ### 1. Accounts Receivable Aging Report This is the most fundamental gauge of billing department health. It segments outstanding claims by age bucket (0–30, 31–60, 61–90, 91–120, 120+ days) and flags what is at risk. Best practice: claims should be paid before 45 days. Any claim unpaid at 90 days requires urgent escalation – it is either rejected, pending appeal, or approaching timely filing risk. The report should be segmented by payer and by CPT code, giving two different lenses on the same problem: which insurers are slow, and which procedures are generating disproportionate AR age. ### 2. Key Performance Indicators (KPI) Report The KPI report tracks total encounters, procedures, charges, collections, outstanding AR, and adjustments in one view. Its real value is trend detection: if charges increase in month one but collections do not increase in month two, a systemic problem exists somewhere in the cycle. If collections that have been consistent suddenly drop, the KPI report is the first place it becomes visible – before the damage compounds further. In the past, generating this report took up to a month manually. Today it should be available in real time. ### 3. Top Carrier / Insurance Analysis Report This report shows the top 10 payers by volume, tracks payments, collections, and CPT performance by payer, and enables direct comparison of what different insurers are actually paying per procedure relative to your contracted rates. One of its highest-value uses: identifying carriers that are systematically paying below other commercial payers for the same procedures. That analysis alone can save a practice up to $50,000 per year – either by renegotiating rates or, when renegotiation fails, by dropping the underperforming carrier and redirecting capacity to better-reimbursed payer relationships. ### 4. Denial Analysis Report The Advisory Board’s research on denial trends reveals a picture that has worsened significantly in recent years: commercial payer denials now account for 26% of all denied claims, demographic and technical errors have doubled as a denial category, and the success rate for appealing denied claims sits at 50–56%. A denial analysis report segments denials by top CPTs denied and top payers denying, creating the data foundation required to build a payer-specific strategy. Without this segmentation, denial management is reactive. With it, it becomes pattern-based prevention. “If office procedures are good in gathering correct information and submitting clean claims, you can still expect to see at least 5% of denials. Claims are mostly denied due to errors – and if the staff reading the EOB misses those errors, there is a high chance of losing revenue.” – Michele Redmond, V.P. Solutions, Medical Billing ### 5. Patient Payment Collection Report As high-deductible health plans proliferate and employer cost-shifting accelerates, patient financial responsibility is no longer a secondary concern in billing management. McKinsey & Co. research shows that in some hospitals, bad debt rates for insured patients exceed 30% annually. Tracking patient payment collection – by service type, by payer, by balance amount – is now as operationally critical as tracking insurance reimbursement. Practices that automate patient statement generation, payment reminders, and balance estimates at point of service collect more, faster, with less manual follow-up. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## The 5 Most Common Root Causes of Billing Failure Most billing problems are not random. They concentrate in predictable failure categories that analysis consistently reveals. ### 1. Front-End Eligibility and Demographic Errors The Advisory Board estimates that 90% of avoidable denials originate at the front end — eligibility errors, wrong demographic data, and missing or expired authorizations that could have been caught before the appointment. These are the cheapest denials to prevent and the most expensive to ignore. ### 2. Authorization Gaps Services delivered without valid prior authorization are immediately denied by payers. The AMA reports that physicians and staff spend an average of 13 hours per physician per week on prior authorization activities, and 86% say auth delays lead to patients abandoning recommended treatment. Authorization management at scale is not sustainable manually. ### 3. Coding Inaccuracies and Documentation Gaps ICD-10 and CPT code mismatches, missing modifiers, unsupported diagnoses, and bundling violations generate complex, time-consuming claim rejections. The root cause is almost always documentation — care delivered correctly but documented in terms that don’t support the codes the billing team needs. ### 4. Denial Write-Offs HFMA data shows that 65% of denied claims are never reworked. Staff work the highest-value denials manually and let the rest age toward write-off by default. This is not negligence — it is a capacity problem. Manual denial management cannot scale to work every denial economically, so practices implicitly accept revenue loss on lower-value claims. ### 5. Underpayment Absorption Payers frequently process claims below contracted rates through fee schedule errors, DRG downgrades, or contract misinterpretation. Without systematic comparison of each payment against contracted allowables at the point of posting, these discrepancies accumulate silently. Industry estimates place underpayment rates at 3–10% of paid claims. For a practice collecting $5M annually, that represents $150,000–$500,000 in revenue paid but underdelivered. ## 8 Best Practices to Improve Medical Billing Management ### 1. Verify Eligibility at Every Relevant Touchpoint, Not Just Once Eligibility changes. Insurance lapses mid-treatment, patients switch plans, coverage limits are consumed by earlier services. Best-in-class practices run automated eligibility checks at scheduling, again 24–48 hours before the appointment, and again at claim generation. The cost of automation is measured in cents per verification; the cost of an eligibility denial is $25–$100 in rework. ### 2. Implement Pre-Submission Claim Scrubbing With Payer-Specific Rules Generic claim editing catches generic errors. Payer-specific rule sets catch the errors that actually get denied by that specific payer. Build claim editing logic that reflects the current requirements of your top 10 payers by volume, and update it when payers issue policy changes. A 2% CCR improvement on 10,000 monthly claims means 200 fewer denials per month. ### 3. Work Denials by Root Cause, Not by Claim Most practices work denials transactionally — one claim at a time. High-performing operations work denials by root cause — identifying the payer-code-provider combinations driving the highest volumes and correcting the upstream process failure producing them. A denial from payer X for reason code CO-16 is not just one claim to fix; it is a signal that a specific process step is failing systematically. ### 4. Automate Payment Posting and Underpayment Detection ERA files arrive daily. Manual posting creates backlogs that inflate DAR, delay denial identification, and mask underpayment patterns. Automated ERA posting clears remittances same-day, updates AR accurately, and can cross-reference each payment line against contracted allowables in real time — flagging underpayments for recovery while the dispute window is still open. ### 5. Run Your Five Core Reports on a Fixed Monthly Cadence Billing performance does not degrade overnight. It drifts. A payer changes a policy, a coder leaves, a new service line launches without updated coding guidelines. Monthly review of AR Aging, KPI, Insurance Analysis, Denial Analysis, and Patient Collection reports — segmented by payer and by provider — identifies drift before it becomes structural. The practices that maintain best-in-class metrics measure consistently. They do not set it and forget it. ### 6. Offer Flexible Payment Plans Payments are a big part of the patient experience but are often an afterthought. A card on file, online prices and payment plans give patients convenient and private ways to pay, which makes billing more efficient and brings in more revenue. ### 7. Reduce Missed Appointments No-shows and late cancellations can cost thousands of dollars each year. A cancellation policy with a fee can help, and so can virtual visits: patients who don’t have to brave traffic or take time off are much less likely to skip their appointments. ### 8. Train Your Team Well-trained, up-to-date employees give patients a better experience and do their work faster and better. Training programs and career development show you’re willing to invest in people, and employees return it with loyalty and better results. ## Compliance: What Has Changed and What Billing Teams Must Know ### The No Surprises Act Effective January 2022 and enforced with increasing intensity since, the No Surprises Act prohibits surprise billing for emergency services, out-of-network services at in-network facilities, and air ambulance services without informed patient consent. For billing teams, this means new disclosure requirements, Good Faith Estimate workflows for uninsured and self-pay patients, and Independent Dispute Resolution processes for payer disputes. Practices that have not updated billing workflows to reflect NSA compliance requirements face both regulatory risk and increased patient disputes. ### HIPAA Administrative Simplification CMS continues to push adoption of standardized electronic transaction formats: X12 5010 for claims, 270/271 for eligibility, 276/277 for claim status, 835 for remittance. Practices relying on paper-based workflows face rising compliance pressure and competitive disadvantage in processing speed and cost. ### Prior Authorization Reform CMS issued a final rule in January 2024 requiring Medicare Advantage and Medicaid managed care plans to respond to standard prior authorization requests within 7 days and urgent requests within 72 hours, and to include specific denial reasons. This changes the dynamics of auth management and makes automated status tracking and denial routing more critical than ever. ## How Automation Transforms Medical Billing Management The best practices above are achievable without automation — but they are not sustainable at scale without it. The volume of transactions in a mid-size billing operation exceeds the practical capacity of manual processes at acceptable cost and accuracy. AI-powered billing automation changes the math fundamentally: - [Eligibility verification automation](https://www.flobotics.io/agents/eligibility-check-automation) runs batch checks overnight on every scheduled patient for the next 48 hours. Zero manual lookup time. - [Prior authorization automation](https://www.flobotics.io/agents/prior-authorization-automation) submits auth requests within minutes of scheduling confirmation, monitors status daily, and alerts staff only when human judgment is required. - [Claims management automation](https://www.flobotics.io/agents/claims-management-automation) applies payer-specific scrubbing rules before submission and monitors payer portals for claim status, flagging pended claims within 24 hours. - Automated payment posting processes ERA feeds same-day with automated contract comparison for underpayment detection. - [Denial management automation](https://www.flobotics.io/agents/denials-management-automation) classifies every denial, routes it to the correct workflow, and ensures nothing ages toward write-off by default. Fig. 01 · Medical billing 9 processes What automation can do in medical billing ProcessWhat the bot does - Payment postingProcesses high volumes of payments at once, flags unpaid claims and handles refunds or takebacks - EHR processingFills in EHR forms in bulk and copies key data across systems - Claims administration and submissionEnters charges, checks payer rules and submits claims - Patient communicationSends automatic emails about questions and updates - Cost estimationLinks the patient profile to services and calculates the cost - Data entryCollects data from many systems and sends it to the right database, EHR or CRM - Claim denialsFixes simple errors and resubmits corrected claims - Prior authorizationsPuts data straight into the hospital information system (HIS) - Patient experienceFaster, better answers According to Experian’s State of Claims 2025, 69% of providers using AI report reduced denials or increased resubmission success. Our client results show Cost-to-Collect improvements of 30–50% within 12 months, DAR reductions of 30–45%, and Clean Claim Rate improvements from the mid-80s to 96–98%. See the specific results in our [healthcare automation case studies](https://www.flobotics.io/case-studies), including PathGroup’s [80% throughput improvement in denials management](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation) and documented FTE savings across eligibility and prior auth workflows. ## What Would a 3% Improvement Cost You to Ignore? A medical practice collecting $5M in annual net revenue operating at industry-average metrics vs. best-in-class faces approximately: - $150,000–$250,000 in excess Cost-to-Collect (6–8% vs. 3–4%) - $250,000–$500,000 in unrecovered NCR gap (93–95% vs. 97–99%) - $150,000–$500,000 in unidentified underpayments (3–10% of paid claims) That is $550,000–$1.25M in annual revenue impact from the gap between average and best-in-class billing performance — on a $5M practice. Use our [RCM automation ROI calculator](https://www.flobotics.io/roi-calculator) to model this for your specific volumes and payer mix. ## Ready to Fix Your Billing Cycle? Every week of delay in addressing billing inefficiencies has a measurable cost. Whether the starting point is eligibility, denials, payment posting, or a full-cycle audit, Flobotics deploys automation that delivers measurable ROI within 30–90 days of go-live. Let’s look at your numbers together. [👉 Book a 30-minute call](https://www.flobotics.io/book) ## FAQ: Should a practice outsource its medical billing? It depends on volume and resources. Outsourcing brings dedicated expertise for a percentage of collections (commonly 4 to 10 percent) without fixed headcount costs; in-house billing gives more direct control but carries the full cost of staff, training, and software regardless of volume. Is medical billing a good career? It offers a positive job outlook, a median salary around $50,250 a year, and increasingly remote or hybrid flexibility, though it rewards people who are comfortable with detail-heavy, rules-based work and ongoing learning as codes and payer policies change. What is a clean claim? A claim that's accepted and paid the first time it's submitted, with no missing information, coding errors, or additional documentation requests from the payer. Written byYana Pokora Content Manager at Flobotics. [More from Yana](https://www.flobotics.io/our-editorial-team#pokora) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Cohen | 2 FTEs saved via full invoice processing automation Canonical: https://www.flobotics.io/blog/rpa-in-accounting Author: Jędrzej Szymula Published: 2023-07-25 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Cohen | 2 FTEs saved via full invoice processing automation [RPA](https://www.flobotics.io/blog?category=rpa) # Cohen | 2 FTEs saved via full invoice processing automation [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published July 25, 2023Updated September 1, 2026 On this page - [Client](#client) - [The challenge](#the-challenge) - [The solution](#the-solution) - [The outcome](#the-outcome) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Client Cohen & Company offers a full range of accounting, tax, and consulting services to clients in the United States and internationally, focusing on private companies, the investment industry, real estate, and private equity. ## The challenge Cohen & Company approached us with a clear vision of which processes should be automated using RPA, including invoice creation and upload, invoice data extraction and upload, and purchase order data creation and upload. Despite their importance to the business, all of these processes relied heavily on manual work, creating employee stress and a constant risk of errors. ## The solution We first advised on the appropriate automation technology and selected UiPath as a secure, fast, and industry-standard platform that enables rapid implementation. Because multiple processes were involved, the solution was designed modularly. For invoice processing, two robots were implemented: one responsible for generating PDF invoices according to defined business rules, and another responsible for importing the generated invoices into the target system with the correct parameters. Additionally, the automation extracted invoice data from a designated mailbox and inserted it directly into the appropriate system. The same automation logic was applied to purchase order data creation, resulting in a consistent and scalable solution. ## The outcome The automation delivered measurable operational impact, saving the equivalent of two full-time employees per month, or approximately 320 hours of manual work. Instead of processing invoices manually, operators now review exception reports and handle only the few cases where automation requires intervention. This shift allows teams to focus on higher-value, strategic work while maintaining accuracy and process reliability. According to Cohen & Company, the solution met aggressive timelines, stayed within budget, and fully delivered on the project scope. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # A Day Ahead, Not a Single Dollar Short: A Quick Guide to RPA in Payroll Canonical: https://www.flobotics.io/blog/payroll-process-rpa Author: Michał Rejman Published: 2023-07-20 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/A Day Ahead, Not a Single Dollar Short: A Quick Guide to… [Eligibility](https://www.flobotics.io/blog?category=eligibility)[RPA](https://www.flobotics.io/blog?category=rpa) # A Day Ahead, Not a Single Dollar Short: A Quick Guide to RPA in Payroll [Michał RejmanChief Marketing Officer at Flobotics](https://www.flobotics.io/our-editorial-team#rejman) Published July 20, 2023Updated September 1, 2026 On this page - [What is RPA payroll automation?](#what-is-rpa-payroll-automation) - [What are the benefits of RPA payroll automation?](#what-are-the-benefits-of-rpa-payroll-automation) - [Time and cost savings](#time-and-cost-savings) - [Reduced errors](#reduced-errors) - [Compliance](#compliance) - [Improved access to payroll data](#improved-access-to-payroll-data) - [Increased employee satisfaction](#increased-employee-satisfaction) - [What payroll processes to automate?](#what-payroll-processes-to-automate) - [How do companies use RPA in payroll?](#how-do-companies-use-rpa-in-payroll) - [Lenovo — 6,000 hours saved per year](#lenovo-6-000-hours-saved-per-year) - [BAE Systems — 7x faster payroll data upload](#bae-systems-7x-faster-payroll-data-upload) - [Global Upside Corporation — 15% less payroll leakage](#global-upside-corporation-15-less-payroll-leakage) - [Automating payroll with Flobotics](#automating-payroll-with-flobotics) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) According to The Workforce Institute, 49% of American workers will start searching for a new job after just two [issues with their paycheck](https://www.businesswire.com/news/home/20170606005972/en/Payroll-Problems-May-Undermine-Employee-Experience-Finds-Workforce-Institute-at-Kronos-Survey). And there’s a good reason for that: 72% of employees admit they would experience [financial difficulties](https://www.prnewswire.com/news-releases/number-of-americans-living-paycheck-to-paycheck-has-increased-301624801.html) if their paychecks were delayed by 1 week. Severe as delays and errors are, even experienced HR and accounting teams can have a hard time preventing them. That’s because of the inescapable challenges all payroll professionals know too well: changing regulations, country- or state-specific tax policies, and loads of employee data. On top of that, there are dozens of moving parts like overtime, raises, or holidays that vary for every single employee. These difficulties lead to mistakes, and mistakes cost money. In 2020 alone, Internal Revenue Service fined US companies $6 billion for [payroll errors](https://www.paycom.com/resources/blog/3-ways-payroll-errors-harm-employees/). The fact that 34% of small businesses [run payroll manually](https://quickbooks.intuit.com/r/news/small-business-cash-flow-the-state-of-payroll-2020/) using spreadsheets raises the risk of penalty even further. Luckily, there’s a solution: RPA payroll automation. Let’s investigate the technology, its benefits, payroll processes that can be automated, and examples of companies that thrive thanks to RPA in payroll. ## What is RPA payroll automation? Payroll automation refers to the technology used to streamline payroll processing and management workflows. Payroll automation software can help payroll teams better handle tasks like entering and updating employee info, filling forms, and sending payments. RPA ([Robotic Process Automation](https://www.flobotics.io/rcm-automation)) is one of the most common automation technologies. It uses automated scripts (or bots) that operate on preset rules to perform defined tasks faster and more accurately than human workers. RPA excels at handling processes that are based on rules, repetitive, involve large datasets, and are prone to errors. The payroll cycle consists of many tasks that fit this profile and could benefit greatly from RPA automation. For example, in [Deloitte Global Payroll Benchmarking Survey](https://www.deloitte.com/content/dam/assets-zone3/us/en/docs/services/consulting/2024/us-apa-payroll-congress-survey-report.pdf), 30% of respondents named the manual entry of inputs as the most time-consuming task in the payroll process. But what exactly can companies get from payroll process RPA? Fig. 01 · Payroll 5 reasons Why RPA suits payroll automation - ScalabilityRPA fits a business of any size and grows with it. - Fewer errorsPrecise bots prevent disruptive payroll mistakes. - Self-serviceEmployees take part in the process, so it is faster and more accurate. - Around the clockBots work without breaks, even at month-end or year-end. - No manual workRoutine payroll tasks are automated. ## What are the benefits of RPA payroll automation? Automation solutions such as RPA have already found their way into many industries. In the Global Deloitte RPA Survey, 53% of respondents said they have already started using or [implementing RPA](https://www.flobotics.io/blog/rpa-statistics). This includes sectors where daily operations involve large volumes of sensitive data, such as [healthcare](https://www.flobotics.io/blog/interoperability-in-healthcare) or [banking](https://www.flobotics.io/case-studies/t-bank-automation). HR is no different. We’ve already described how to use [RPA in recruitment](https://www.flobotics.io/blog/rpa-in-hr-and-recruitment) to make better decisions in a shorter time. Running the payroll process is another essential function of HR teams, usually shared with finance and accounting departments. How can they all take advantage of the payroll process RPA? Fig. 02 · Payroll 6 risks The risks of manual payroll - 01More errors - 02Delays and missed deadlines - 03Higher costs - 04Inconsistencies - 05Non-compliance - 06Frustrated employees ### Time and cost savings Calculating, auditing, and submitting payslips is a time-consuming process that involves dozens of files and documents, usually stored in various formats and places. This creates a lot of room for time and cost inefficiencies. Automated payroll solutions have a proven track record of decreasing these inefficiencies. It’s estimated that implementing automation can [reduce the costs of payroll processes](https://www.zenefits.com/wp-content/uploads/2021/10/HR-Cost-Savings-Through-Automation.pdf) by up to 80%. This is achieved by improving access to necessary documentation, eliminating manual data input and duplicated tasks, handling complicated calculations, and tracking changes to employee information. ### Reduced errors A study by Ernst & Young found that [1 in 5 payrolls in the US includes errors](https://eyquest.com/files/Cost_and_Risks_Due_to_Payroll_Errors_2022_Final.pdf). While 80% accuracy is enough in some areas, in payroll, it just won’t cut it. The same report reveals that each payroll mistake costs organizations $291 on average. Even the best HR specialists make mistakes when dozens of factors, such as deductions, overtime, bonuses, or PTO, must be considered. With payroll process RPA, you will no longer need to worry about entering this data manually, which will reduce the number of mistakes. Self-service is another convenient feature of an automated payroll system that allows employees to update their details independently to prevent further errors. ### Compliance Another thing to consider is staying compliant with constantly changing regulations that vary between countries and states. This became even more problematic after the pandemic when companies became more open to hiring remote workers. As a result, 74% of organizations must use dedicated payroll systems for each locale rather than a centralized one. Here, automation can help companies observe policies through automatic tax filing, data entry, and policy updates. Automation will also make migrating to a single, centralized, and global payroll system easier. Process automation ROI calculator See what automating a process could save you in a few minutes. [Calculate ROI →](https://www.flobotics.io/roi-calculator) ### Improved access to payroll data Tax documents, deductions, leave records, employee data, reimbursement forms… We could go on listing all documents used in the payroll process. Even worse, they usually come in several formats and are scattered across various sources. Payroll process RPA makes it easier to store and organize your payroll data digitally, allowing HR professionals to retrieve the necessary data quickly. This improves not only the daily payroll operations but also reporting. Additionally, automatic encryption and security settings help you keep sensitive information safe. ### Increased employee satisfaction On a more personal level, making sure that your staff is paid the correct amount on the correct date is a fair thing to do. Businesses that fail to do that put themselves at risk of hurting their employees’ trust and motivation or even losing them completely. In that context, warranting timely and error-free payouts is necessary for businesses that want to preserve their workforce and keep morale high. Automation helps these organizations achieve their goal by streamlining the payroll team’s work and reducing delays. But it’s important to be aware of challenges with [RPA implementation.](https://www.flobotics.io/blog/rpa-challenges) Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## What payroll processes to automate? RPA is a flexible tool. With the help of [experienced RPA developers](https://www.flobotics.io/blog/rpa-non-technical-developer), it can be used to expedite tasks across the entire payroll workflow. Here are 12 payroll processes to automate with RPA: - Managing payroll data — Automation software keeps payroll records up-to-date across all systems as soon as changes are made. - Time tracking — Payroll software will pull and verify timecards from all systems and ask for approval if it finds any discrepancies. - Employee onboarding and transfer — Automation expedites cross-verification, data entry, and updates across multiple platforms required in both processes. - Calculating overtime and bonuses — Based on employee information and timesheets, payroll software will quickly determine any extra rates needed to calculate the final salary. - Termination processing — RPA bots can regularly scan the company’s HR systems for terminated employees and automatically calculate their final paycheck. - Tax management — The payroll system will calculate the withholding amount from each payslip and automatically file the necessary taxes. - Direct deposits — On a set date, the payroll algorithm will send the calculated and verified sum to employees via direct deposit. - Calculating salaries — Payroll scripts will quickly calculate the correct amount, factoring in overtime, bonuses, pay raises, benefits, and more. - Post-close administration — RPA can take over fiscal year-end tasks like tax reconciliation, handling leftover payroll journal entries, or reconciliation against benefit invoices. - Benefits administration — No matter how sophisticated your benefits program is, payroll automation will enable you to easily track and update subscriptions and enrollments. - Payroll reporting — Automation software allows HR professionals to generate various payroll reports with one click for faster and more informed decision-making. - Employee self-service — With automation, employees can independently handle operations like personal information management or employment verification, saving your HR team time and effort. Find out what can be automated in all [accounting processes](https://www.flobotics.io/business-process-automation) with RPA. Fig. 03 · Payroll 12 processes Top payroll processes to automate with RPA - Managing payroll data - Time tracking - Onboarding and transfers - Overtime and bonuses - Terminations - Tax management - Direct deposits - Salary calculation - Post-close administration - Benefits administration - Payroll reporting - Employee self-service ## How do companies use RPA in payroll? Companies from various industries have adopted RPA to streamline their payroll operations. Here are three examples of organizations that already benefit from automated payroll processes. ### Lenovo — 6,000 hours saved per year As a part of its digital transformation efforts, Lenovo has set out to improve its payroll processes. Here, the challenge was navigating a network of interdependent systems like SAP, Workday, and PeopleSoft, replacing manual tasks that the company relied on for years. To do that, [UiPath RPA bots](https://www.uipath.com/resources/automation-case-studies/lenovo-rpa-release-hyperautomation-value) were deployed to several workflows, including tax processing, expense reimbursement, payroll calendar scheduling, and employee self-service. As a result, Lenovo’s HR team has freed up 6,000 hours yearly, while its process efficiency has increased by 5-8 times. Fig. 04 · Case Lenovo Lenovo: payroll automation GoalImprove payroll processesSolutionAutomated tax processing, expense reimbursement, payroll calendar scheduling and employee self-service 6,000 hsaved a year 7.5×more efficient process ### BAE Systems — 7x faster payroll data upload Leaders at [BAE Systems](https://www.baesystems.com/en/home), a defense, aerospace, and security company, recognized the need to improve their HR and finance operations. That included payroll, which faced two main problems: multiple payroll cycles and a limited number of clerks who could access the system simultaneously. Using the [Automation Anywhere](https://www.automationanywhere.com/resources/customer-stories/bae-systems-scales-processes-with-rpa) platform, BAE Systems delegated uploading, processing, and updating data to RPA bots. Overall, the company has automated 50 processes, speeding up the payroll data upload by 7 times and saving over 2,600 hours per year. Fig. 05 · Case BAE Systems BAE Systems: HR and finance automation GoalImprove HR and finance operations, including payrollSolutionRPA bots that upload, process and update data 2,600 hsaved a year 7×faster payroll data upload ### Global Upside Corporation — 15% less payroll leakage The best testament to the potential of RPA in payroll is that even specialized payroll outsources use it themselves. Such was the case of [Global Upside Corporation.](https://www.safeguardglobal.com/) The company worked with an automation partner to identify issues and create an automation roadmap. Based on this analysis, RPA bots were tasked with generating, verifying, and distributing payslips, collecting data, reporting, and more. Automation has led to a 15% reduction in payroll leakage, compliance issues, and manual errors and has increased employee performance by 10%. Fig. 06 · Case Global Upside Global Upside: faster payroll GoalSpeed up payroll processingSolutionRPA bots that generate, check and send payslips, collect data and report 15%less payroll leakage 10%better employee performance ### Automating payroll with Flobotics Payroll automation is an excellent example of one change making a company-wide impact. Relaying manual payroll tasks to RPA bots doesn’t just help your HR and finance departments work more efficiently; it also increases the quality of life for every single employee. Not every payroll fix needs a bot, though. For other ways to improve the process, such as connecting payroll to time tracking and giving employees 24/7 access, see our [payroll process improvement ideas](https://www.flobotics.io/blog/rpa-payroll-process). If you want to see how payroll process RPA can help your business, [Flobotics](https://www.flobotics.io/) is the right partner. Tell us about your business, and we’ll launch a free automation trial suited to your needs. [Get started](https://www.flobotics.io/contact) with RPA in payroll today! #### Like the article? Spread the word Written byMichał Rejman Chief Marketing Officer at Flobotics. [More from Michał](https://www.flobotics.io/our-editorial-team#rejman) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # SAP Automation Tools and You: Which One to Choose (And Why RPA Is Our Pick) Canonical: https://www.flobotics.io/blog/sap-automation Author: Karl Mielnicki Published: 2023-07-11 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/SAP Automation Tools and You: Which One to Choose (And Why… CTO Notes [RPA](https://www.flobotics.io/blog?category=rpa) # SAP Automation Tools and You: Which One to Choose (And Why RPA Is Our Pick) [Karl MielnickiCTO & Co-Founder of Flobotics](https://www.flobotics.io/our-editorial-team#mielnicki) Published July 11, 2023Updated September 1, 2026 On this page - [SAP automation: introduction](#sap-automation-introduction) - [SAP automation tools overview](#sap-automation-tools-overview) - [UiPath: The preferred RPA technology for SAP automation](#uipath-the-preferred-rpa-technology-for-sap-automation) - [SAP integration capabilities](#sap-integration-capabilities) - [Ease of use](#ease-of-use) - [Scalability](#scalability) - [Thriving community](#thriving-community) - [Strategic partnership with SAP](#strategic-partnership-with-sap) - [Flobotics is an official UiPath partner](#flobotics-is-an-official-uipath-partner) - [Find SAP automation tools that work](#find-sap-automation-tools-that-work) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Founded in 1972, [SAP Software Solutions](https://www.sap.com/) has been around for more than 50 years. Given the stories of spectacular failures of tech giants like Atari, Commodore, or Sun Microsystems, the company’s longevity is an achievement. But SAP doesn’t just survive—it thrives. Today, 99 of the 100 largest global companies use [SAP software](https://www.sap.com/documents/2017/04/4666ecdd-b67c-0010-82c7-eda71af511fa.html), and there are many reasons for that. A major one is SAP’s ability to innovate and adapt to technological trends such as automation. The most recent example is the newly announced strategic partnership between [SAP and UiPath](https://www.uipath.com/newsroom/uipath-to-offer-uipath-platform-as-sap-endorsed-application), a leader in the RPA [(Robotic Process Automation)](https://www.flobotics.io/blog/robotic-process-automation) market. It sends a clear message to all organizations that use SAP: automation is the future. This article will examine different SAP automation tools companies can choose from when optimizing their SAP functions. We’ll also explain what the partnership with UiPath means and why it makes RPA a preferred automation option for SAP. ## SAP automation: introduction The overarching aim of SAP is to streamline and centralize everyday [business processes](https://www.flobotics.io/blog/what-processes-to-automate). Many of these repetitive workflows involve manual labor: sending emails, moving records, invoice processing, reporting, or data validation. In this context, automation is the natural solution. SAP automation tools use various technologies to optimize processes and accomplish set business goals. All these automation methods share a similar purpose and bring three main benefits: increased efficiency, reduced error rate, and higher productivity—all through replacing slow and frustrating manual processes with automated solutions. As a result, automation leads to many secondary benefits, such as time and cost savings, smoother digital transformation, better customer outcomes, and improved employee satisfaction. And, in the current fierce competitive climate, all these benefits help organizations get an edge. Fig. 01 · SAP 6 areas Which SAP functions can be automated - HR and recruitment - Training - Onboarding and offboarding - People management - Workforce scheduling - Candidate checks - CVs and references - Assessments - Finance - Payroll - Payables and receivables - Reporting - Journal entries - Invoices - Customer service - Chatbots - Retrieving customer records - Personalized service - Data operations - Data entry - Form filling - Data migration - Comparing data fields - Compliance - Auditing - Access management - Safety procedures and compliance checks - Supply chain - Stock monitoring - Purchase orders - Inventory alerts ## SAP automation tools overview SAP automation isn’t a single technology but several tools that can intertwine and be used together for an even better effect. What are the most common SAP automation tools? Let’s see: - Robotic Process Automation (RPA): RPA uses software robots that mimic human actions to automate repetitive and rule-based workflows within the SAP ecosystem. RPA streamlines business processes by replacing manual tasks, enhancing efficiency, and reducing human errors. As a flexible and scalable automation solution, RPA can be used by large enterprises and SMEs from any industry. - Business Process Management (BPM): More of a strategy than an automation method, BPM is a broad concept focused on efficient management and optimization of end-to-end business processes in SAP. BPM enables organizations to streamline workflows, allocate resources, and respond swiftly to shifting business needs. To that end, BPM involves using automation technologies. - Scripting and custom development: Scripting and custom development in SAP involve writing and modifying code to tailor SAP systems to specific requirements. It allows organizations to extend SAP functionalities, develop custom applications, and integrate SAP with third-party systems. Common custom development tools include SAP GUI scripting and languages like ABAP. - Integration Platforms: Middleware or enterprise service buses (ESBs) like SAP Integration Suite facilitate the seamless data exchange and communication between different systems, applications, and technologies. They provide a unified interface connecting SAP systems with external automation services, cloud platforms, databases, and APIs. Integration platforms enable enterprises to sync data in real time, orchestrate processes, and connect all critical features within a single platform. - Artificial Intelligence (AI) and Machine Learning (ML): Rather than automating repetitive tasks, AI technologies assist companies in intelligent decision-making, data analysis, and forecasting. ML is particularly helpful here: ML algorithms analyze vast amounts of data to identify patterns, make predictions, and optimize processes. AI techniques are often used alongside other automation systems in intelligent automation. For instance, natural language processing and computer vision enable SAP systems to understand and interpret text and image content. Ultimately, the choice of an SAP automation tool will depend on specific business requirements, the complexity of processes, and the organization’s goals. RPA has many advantages that make it an all-around great option for SAP. Fig. 02 · SAP 10 benefits The benefits of automating SAP with RPA - Removes repetitive, rule-based manual tasks - Better efficiency and fewer human errors - Frees employees for strategic work - Works with existing SAP systems with little integration - Easier compliance through standard, traceable processes - No major changes to underlying infrastructure - Quick to implement, quick ROI - Scales easily as needs change - Works across many industries and functions - Combines with other SAP tools, AI and integration platforms Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## UiPath: The preferred RPA technology for SAP automation In recent years, more and more businesses have been realizing the potential of RPA. The increased demand has led to the birth of new RPA platforms. Today, many solutions are available, the market leaders being UiPath, BluePrism, [Power Automate](https://www.flobotics.io/blog/uipath-vs-powerautomate), and Automation Anywhere. Though all have pros and cons, our RPA tool of choice is UiPath. We also believe that it's best suited specifically for SAP automation. Why? ### SAP integration capabilities UiPath offers dedicated integrations for seamless automation with SAP applications without the need for complex scripting or custom development. Native integrations such as SAP BAPI, RFC, and OData provide various activities specifically designed for SAP systems. UiPath is compatible with all SAP implementations, including SAP S/4HANA, SAP ECC, SAP FIORI, SAP S/4HANA Cloud, SAP WinGUI, SAP WebGUI, and SAP Business Client. On top of that, UiPath has over 300 native integrations with other applications, allowing you to weave together and automate all tools with SAP. Together, all these features ensure stable and secure communication between UiPath and SAP. This streamlines the SAP automation process, reduces implementation time, and allows you to harness the full potential of UiPath's RPA capabilities within your SAP system. ### Ease of use UiPath RPA platform stands out for its user-friendly features, making automation accessible to users with varying technical backgrounds. Once UiPath is set up, Its visual interface enables the creation of automation workflows through a drag-and-drop approach, eliminating the need for complex coding. The platform also offers a rich library of ready-made automation components and activities that employees can use to build automation sequences quickly. To further simplify and expedite the automation process, [UiPath Studio](https://www.uipath.com/product/studio) gives you the ability to record specific tasks. This feature captures on-screen user activities within a workflow and translates the recording into automation sequences. Additionally, UiPath goes a long way to ensure that users can easily learn and master the platform by themselves. Extensive documentation, online training materials, a proprietary automation training platform, and active community support foster a user-friendly experience for RPA development and deployment. ### Scalability Organizations can efficiently scale their SAP automation initiatives with [UiPath's Orchestrator](https://www.uipath.com/product/orchestrator), a centralized RPA management platform. Orchestrator provides a secure and scalable infrastructure to deploy, monitor, and manage many RPA robots that can be used across multiple of your SAP systems. It empowers enterprises to add new bots easily as the demand grows. All workflows built in UiPath can be easily reused in multiple processes. UiPath encourages sharing automated processes across all teams, where they can be adjusted to fit specific purposes. This scalability ensures that automation can keep up with growing business demands so that organizations can seamlessly handle increased volumes of SAP processes. UiPath's robust architecture and flexible deployment options allow enterprises to expand their SAP automation initiatives while maintaining high performance, reliability, and compliance. ### Thriving community UiPath has won the following of a large and active community that provides significant benefits for SAP automation. UiPath has its [knowledge-sharing platform](https://community.uipath.com/), allowing professionals to discuss, ask questions, and exchange insights, best practices, and solutions for SAP-specific challenges. Collaboration opportunities enable users to work together on SAP automation projects, fostering efficient development and problem-solving. The community also offers pre-built automation components tailored for SAP systems, reducing development time. [UiPath Marketplace](https://marketplace.uipath.com/collections/sap) enables RPA developers to share their projects beyond their organizations. That gives other members of the UiPath community access to reusable SAP automation components and accelerators for specific SAP activities. Moreover, troubleshooting and support are readily available, with experienced community members and UiPath experts offering assistance. Overall, UiPath's active community is a huge asset for SAP automation, enhancing the work of each employee or developer and accelerating projects. ### Strategic partnership with SAP As mentioned earlier, UiPath has established a strategic partnership with SAP by becoming an [SAP Endorsed App](https://store.sap.com/dcp/en/news-blogs/blogs/sap-endorsed-apps-helping-customers-become-best-run-intelligent-enterprises). To acquire this designation, a solution must comply with SAP's security and performance standards. By implementing an SAP Endorsed App such as UiPath alongside SAP, organizations are sure to work with safe and highest-quality solutions. From the user's perspective, this partnership also ensures compatibility and alignment with SAP technologies, enhancing the effectiveness of SAP automation with UiPath. With that, SAP users can take full advantage of all the benefits of UiPath SAP automation. ### Flobotics is an official UiPath partner UiPath Partner Network is a group of the best-performing RPA leaders who have proven their automation expertise. Simply put, when you [hire a certified UiPath developer](https://www.flobotics.io/about-us), you can be sure that your automation initiative is in good hands. Here at Flobotics, we're proud to hold the title of a [UiPath-certified RPA agency](https://www.flobotics.io/uipath-services). With dozens of successful implementations under our belt, we have experience automating processes for companies from any industry, including healthcare, finance, and real estate. ## Find SAP automation tools that work Choosing the SAP automation tool that will fit your company's needs is no mean feat. Each has its strengths and weaknesses, but they all have a place in your SAP automation stack. In our view, UiPath RPA is the best stepping stone for your SAP automation initiative, and there's no better proof of that than the strategic partnership between the two companies. Keen to find out more about optimizing your SAP systems with UiPath RPA? You're on the right track — [give us a call](https://www.flobotics.io/), and let's talk. #### Like the article? Spread the word Written byKarl Mielnicki CTO & Co-Founder of Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### Small Effort, Big Impact: What Is RPA Testing, How to Do It & Why It Matters RPA testing, explained: why skipping it leads to costly post-launch fixes, and how to test your automation before it goes live. Bart TeodorczukJanuary 02, 2024 ](https://www.flobotics.io/blog/rpa-testing)[ RPAAI ### Building Your Automation Toolkit: 100 Automation Technologies and Platforms You Should Know RPA programming and automation technologies: explore our curated toolkit of 100 platforms, with pros, cons, and top use cases for 2026. Karl MielnickiMay 12, 2024 ](https://www.flobotics.io/blog/automation-technologies)[ EligibilityClaims ### Insurance Claims Processing Automation With RPA: Reasons for Implementation and Use Cases Insurance claims processing automation: how RPA speeds up claims handling, with reasons to implement it and real case studies. Michał RejmanJuly 21, 2021 ](https://www.flobotics.io/blog/insurance-claims-processing-rpa-automation-use-cases) [All articles →](https://www.flobotics.io/blog) --- # Your 6-Minute Guide to Process Automation with Python: Pros, Cons, Use Cases & Examples Canonical: https://www.flobotics.io/blog/automation-python Author: Krzysztof Szwed Published: 2023-07-05 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Your 6-Minute Guide to Process Automation with Python:… [RPA](https://www.flobotics.io/blog?category=rpa) # Your 6-Minute Guide to Process Automation with Python: Pros, Cons, Use Cases & Examples [Krzysztof SzwedHead of Delivery at Flobotics](https://www.flobotics.io/our-editorial-team#szwed) Published July 05, 2023Updated September 1, 2026 On this page - [Advantages of Python for business automation](#advantages-of-python-for-business-automation) - [Easy to learn and read](#easy-to-learn-and-read) - [Flexibility](#flexibility) - [Community support and documentation](#community-support-and-documentation) - [A broad range of libraries and frameworks](#a-broad-range-of-libraries-and-frameworks) - [Platform independence](#platform-independence) - [Integration capabilities](#integration-capabilities) - [Rapid development and prototyping](#rapid-development-and-prototyping) - [Performance in RPA](#performance-in-rpa) - [Cost-effective solution](#cost-effective-solution) - [Disadvantages of Python](#disadvantages-of-python) - [Memory consumption](#memory-consumption) - [Global Interpreter Lock (GIL)](#global-interpreter-lock-gil) - [Limited mobile development capabilities](#limited-mobile-development-capabilities) - [Runtime errors](#runtime-errors) - [Version compatibility issues](#version-compatibility-issues) - [What processes can you automate with Python?](#what-processes-can-you-automate-with-python) - [Automation with Python — our work](#automation-with-python-our-work) - [eSky — 1.5 full-time equivalent saved monthly on partner monitoring](#esky-1-5-full-time-equivalent-saved-monthly-on-partner-monitoring) - [EBTCS — integrating crucial systems](#ebtcs-integrating-crucial-systems) - [What can automation with Python do for your business?](#what-can-automation-with-python-do-for-your-business) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) One day in the late 80s, a sudden thought dawned on [Guido van Rossum](https://blog.dropbox.com/topics/work-culture/-the-mind-at-work--guido-van-rossum-on-how-python-makes-thinking): “Isn’t it crazy that all those people have computers, and very few of them learn to program?” Personal computers have been used for around 20 years, but coding wasn’t as standard among everyday users back then. Inspired by his work with the ABC programming language, van Rossum set out to make coding more accessible. In 1989, after a few years of development, the first version of his own interpreted, open-source programming language was implemented. Van Rossum named it Python after the popular BBC show Monty Python’s Flying Circus. Today, Python is the second [most popular programming language](https://github.blog/news-insights/octoverse/octoverse-a-new-developer-joins-github-every-second-as-ai-leads-typescript-to-1/) on GitHub, ranking only behind JavaScript. It’s established itself as a potent, multi-purpose language in data science, data analysis and visualization, machine learning, and web development. Python is also a perfect fit for [RPA development](https://www.flobotics.io/blog/rpa-development-process), and its relative simplicity means even non-technical users can leverage it for basic automation. This article investigates its strengths and weaknesses, uses, and case studies featuring automation with Python. ## Advantages of Python for business automation For more than 30 years since its inception, Python has become one of the preferred programming languages for process automation. Why is that? ### Easy to learn and read Accessibility was the guiding principle for van Rossum. Python has a simple, logical syntax that resembles English, making it easy to understand. As a high-level language, Python doesn’t require an in-depth understanding of how computers work, although it helps. Python is also an interpreted language, meaning each code line can be run and checked immediately. This is a plus for beginners and experienced programmers, too, as Python enables faster development and easier maintenance of automation scripts. ### Flexibility Unlike domain-specific languages such as HTML or SQL, Python wasn’t created to serve any single specific purpose. Instead, it’s a general-use language that can be applied to automate tasks like organizing data, web scraping, sending emails, etc. ### Community support and documentation As an open-source language with a relatively low learning curve, Python has garnered a large and thriving community that actively contributes to its development. With so many engaged users, it’s easy to find answers to questions regarding automation with Python or a fellow programmer willing to help. ### A broad range of libraries and frameworks Another benefit of Python’s large community is a vast ecosystem of user-created libraries and frameworks. They are designed for specific purposes, including various automation tasks, adding to Python’s great versatility. And considering its ease of use, there’s a good chance that even users with basic Python language knowledge can understand and reuse code made by others rather than writing it from scratch. ### Platform independence Python is also a cross-platform language, meaning that automation scripts developed in Python can run on multiple operating systems, including Windows, macOS, and Linux. Thanks to that, programs written in Python are easier to share and deploy at scale across various platforms. ### Integration capabilities Python provides excellent integration capabilities with other programming languages and systems. This includes many languages commonly used in enterprise-scale development, such as Java, PHP, and.NET, which is why Python is well-suited for large and diverse environments. ### Rapid development and prototyping Simplicity, a vast number of high-level libraries, and the fact that it’s an interpreted language all make Python the perfect prototyping tool. Automation allows programmers to quickly iterate, debug, and find the best way to expedite the process. ### Performance in RPA Python is a dynamically typed language, meaning developers don’t need to declare each variable’s type explicitly. Instead, the type of the variable is verified at runtime. While this feature further increases Python’s flexibility and ease of use, it takes its toll on execution time, making Python slower when compared to most general-purpose languages. However, this isn’t an issue from the RPA perspective. Firstly, in terms of speed, Python is on par with other languages used specifically in RPA. Additionally, workloads can often be parallelized, i.e., divided into smaller parts, which allows for optimized efficiency. Python is also highly performant when it comes to tasks that involve data uploads and downloads through a network, e.g., making HTTP requests. ### Cost-effective solution Python requires no license fees to use and distribute as an open-source language. Combine that with the wide choice of available libraries, rapid development, and short delivery times, and you have an efficient and affordable programming language. ## Disadvantages of Python Despite all its advantages, Python has some flaws that must be considered. What are they? ### Memory consumption Python’s flexibility and ease of use come at the cost of high memory consumption. This might become a concern when dealing with large-scale automation processes or memory-constrained systems. ### Global Interpreter Lock (GIL) To help address memory management, Python uses a Global Interpreter Lock. This feature allows only one thread to execute Python bytecode simultaneously, increasing execution speed for single-thread programs. However, it can also affect the performance of multithreaded Python applications, especially in the case of CPU-bound tasks. That said, some Python implementations don’t use GIL and can take full advantage of multithreading. It’s also worth noting that GIL isn’t a factor when automating tasks that rely on network capabilities rather than computing power. In such tasks, Python can be applied even to multithreaded programs without compromising execution speed. ### Limited mobile development capabilities Due to its high memory usage and relatively slow performance, Python is subpar regarding mobile-specific automation features or cross-platform mobile app development. Other languages like Swift, Kotlin, or JavaScript may be more suitable. ### Runtime errors The fact that Python is a dynamically typed language means that the data type of any variable can change at any time. Also, Python doesn’t compile until runtime, so many problems go unnoticed up to that point. This may lead to runtime issues like syntax errors. ### Version compatibility issues Python has been around for over 30 years, and throughout that time, it has seen many upgrades. Though new versions expand Python’s capabilities, they also cause incompatibility with some runtimes in cloud environments. Fig. 01 · Python Pros and cons Python for automation: strengths and weaknesses Strengths - Easy to use and learn - Versatile - Large, active community - Many user-made libraries and frameworks - Works on any platform - Integrates well with other systems and languages - Fast development and prototyping - Open source Weaknesses - Relatively slow - High memory use - New versions break older libraries - Not suited to mobile development - Prone to runtime errors - Global interpreter lock Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## What processes can you automate with Python? Considering all strengths and weaknesses of the language, let’s see some of the best use cases for automation with Python. - Email automation — Python has a built-in smptlib module, allowing easy integration with Simple Mail Transfer Protocol (SMTP), the communication protocol used by all email systems. Once a connection is set up, you can use Python to bulk-send personalized emails, organize your inbox, or sort messages from different mailboxes. - Web scraping — With specialized libraries, Python allows you to automatically collect and parse data directly from the website’s HTML. This has a range of applications, from comparing prices or product listings to statistical research. - File conversion — Python scripts can quickly convert high volumes of files from one format to another. Examples include text, image, and even text-to-speech conversion. - Document reading and editing — No matter the size of your CSV table, a Python script can scan it in seconds and make the necessary changes. The algorithm can also be used to fill online forms automatically. - File upload — When done manually, moving thousands of files to a new location can take days. Python can handle data uploads between devices or cloud storage much more efficiently. - Web search automation — Tasks like web mining or SEO auditing require constant, repetitive Google searching for the exact keywords. Python scripts will scrape search results quickly, accurately, and in real-time. - Customer segmentation — Dividing your clients based on their characteristics involves reading and manipulating extensive records. Scripts created in Python can scan these datasets for shared customer features such as behavior or demographic data and then group them into segments for further analysis. - Integrations — Python can be used for integrating systems that have no native way of connecting with each other (you’ll probably word it better than me, but you get the point) Fig. 02 · Python 7 tasks What you can automate with Python - Sending and sorting emails - Reading and editing documents - Customer segmentation - Converting files - Web scraping - Web searches - Uploading files ## Automation with Python — our work Enough theory—let’s see how automation with Python fares in real-life scenarios based on two client stories from our Flobotics portfolio. ### eSky — 1.5 full-time equivalent saved monthly on partner monitoring Fig. 03 · Case eSky eSky: luggage policy monitoring GoalSpot changes in airline luggage policies and improve customer experienceSolutionA bot that monitors luggage policies 200+web pages monitored daily 1.5FTEs saved a month 100%ROI within 2 months Flobotics [Read the case study →](https://www.flobotics.io/case-studies/esky-luggage-tracking-automation) [eSky](https://www.flobotics.io/case-studies/esky-luggage-tracking-automation) is a leading travel portal offering many services, including flights, accommodation, holiday packages, and travel-related services: car rental, insurance, tours, and more. With an offering this varied, eSky needs to constantly monitor the websites of external providers (e.g., airlines or insurance companies) for any pricing or policy changes. Tracking is particularly problematic in the case of luggage policies which are often hard to find and updated irregularly. Due to that, updates were handled manually, which led to errors and outdated information being posted on eSky’s website. We decided to use two technologies after an introductory workshop with the client. First, our developers created a prototype bot in Python. Here, the properties of the language allowed us to validate the concept and make the necessary tweaks on the go. When the prototype passed the feasibility test, we started working on the final automation using Robocorp, a Python-based tool. The result was an efficient but easy-to-maintain automation solution that tracks real-time luggage policy changes on over 200 pages. The investment paid for itself in just 2 months and helped eSky save 1.5 full-time equivalents each month. ### EBTCS — integrating crucial systems Fig. 04 · Case EBTCS, Seattle Evidence-Based Treatment Centers of Seattle GoalConnect sales with the patient management softwareSolutionAn interoperability bot between Salesforce and the EHR 20×faster on a single process $0in licensing costs ~20cases processed a week Flobotics [Read the case study →](https://www.flobotics.io/blog/evidence-based-treatment-centers-of-seattle-ebtcs) [The Evidence-Based Treatment Centers of Seattle (EBTCS)](https://ebtseattle.com/) is a Seattle-based network of specialty mental health centers. EBTCS struggled to integrate its sales portal (Salesforce) with the EHR system (Valant), which doesn’t have an open API. So, to keep all data up to date across both platforms, a whole team was needed to move records manually between Salesforce and Valant every day. At first, the client wanted to use UiPath, our RPA technology of choice. However, after a short analysis, we decided to again go for Python and Robocorp. Python’s integration capabilities would allow us to build a bot that worked with Valant without using its interface, expediting the process significantly. Also, based on the average monthly usage, Robocorp was the most cost-efficient solution. The bot checks EBTCS’ Salesforce every three hours and compares patient data with the list of patients in Valant. The algorithm pulls all their data from Salesforce into Valant if new patients are registered. Once the transfer is complete, the bot automatically updates the patient status and sends a short report to all relevant team members. We’ve also implemented additional features, such as the automated transfer of personal data and PDF documents between the platforms, a billing error prevention system for Valant, and a bot performance monitoring dashboard. The bot now handles up to hundreds of cases per week, and the processing time for each case was reduced from 5 minutes to just 15 seconds. EBTCS paid nothing for the license since Robocorp’s free plan covered the project scope. ## What can automation with Python do for your business? Simplicity, user-friendly features, and flexibility make Python a versatile tool well-suited for various purposes. One of them is automating processes crucial to daily operations in any industry. At Flobotics, we specialize in helping businesses streamline their processes using automation solutions like [UiPath](https://www.flobotics.io/blog/uipath-vs-powerautomate), [Blue Prism](https://www.flobotics.io/blog/blueprism-vs-uipath), [Automation Anywhere](https://www.flobotics.io/blog/uipath-vs-aa), and more—including Python. Want to find out more? [Drop us a line](https://www.flobotics.io/contact), schedule a free consultation, and let’s talk about the best automation technology for your business. #### Like the article? Spread the word Written byKrzysztof Szwed Head of Delivery at Flobotics. [More from Krzysztof](https://www.flobotics.io/our-editorial-team#szwed) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### UiPath vs. Python? Choosing the Right RPA Tool for Your Automation Job UiPath vs. Python: compare strengths, use cases, and when to choose code over low-code for your next automation project. Krzysztof SzwedDecember 11, 2023 ](https://www.flobotics.io/blog/uipath-python)[ RPA ### RPA Reloaded: 50+ Robotic Process Automation Statistics to Know in 2026 RPA statistics 2026: 50+ data points on robotic process automation adoption, ROI, and where the technology is headed next. Yana PokoraApril 15, 2025 ](https://www.flobotics.io/blog/rpa-statistics)[ RPAAI ### Agentic AI Tools and Platforms Overview 2026 Agentic AI platforms for 2026: an overview of the tools driving autonomous workflows, plus Gartner's cost-saving forecast. Jędrzej SzymulaSeptember 16, 2025 ](https://www.flobotics.io/blog/agentic-ai-tools-platforms-overview) [All articles →](https://www.flobotics.io/blog) --- # Robotic Process Automation vs. Machine Learning: Differences, Similarities, and Synergies Canonical: https://www.flobotics.io/blog/robotic-process-automation-vs-machine-learning Author: Bart Teodorczuk Published: 2023-06-21 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Robotic Process Automation vs. Machine Learning:… [RPA](https://www.flobotics.io/blog?category=rpa) # Robotic Process Automation vs. Machine Learning: Differences, Similarities, and Synergies [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published June 21, 2023Updated September 1, 2026 On this page - [RPA — doing more for less](#rpa-doing-more-for-less) - [What are the benefits of RPA?](#what-are-the-benefits-of-rpa) - [RPA use cases for all businesses](#rpa-use-cases-for-all-businesses) - [ML — teaching machines to learn](#ml-teaching-machines-to-learn) - [What are the benefits of ML?](#what-are-the-benefits-of-ml) - [How can businesses use ML?](#how-can-businesses-use-ml) - [Robotic process automation vs. machine learning: a comparison](#robotic-process-automation-vs-machine-learning-a-comparison) - [Robotic Process Automation vs Machine Learning: what are they best at?](#robotic-process-automation-vs-machine-learning-what-are-they-best-at) - [Robotic Process Automation vs. Machine Learning: the synergy](#robotic-process-automation-vs-machine-learning-the-synergy) - [ML vs. RPA: make the right choice with Flobotics](#ml-vs-rpa-make-the-right-choice-with-flobotics) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) In the early 2000s, [Robotic Process Automation](https://www.uipath.com/blog/rpa/the-evolution-of-rpa-past-present-and-future) (RPA) was a budding tool that relied on established technologies, such as screen scraping or workflow automation. Over the years, RPA has become the go-to automation tool used in all industries. The [RPA market](https://www.gartner.com/en/documents/6842834) has achieved a total size of about USD 4 billion and is projected to surpass USD 13 billion by 2030. Today, we’re experiencing a similar revolution as more and more companies adopt AI technologies such as Machine Learning (ML). They do that for a good reason—73% of business leaders believe that ML can [double the productivity](https://www.zippia.com/advice/machine-learning-statistics/#:~:text=Machine%20Learning%20Industry%20Statistics&text=As%20of%202022%2C%20the%20global,are%20continually%20investing%20in%20AI) of their workers. Thinking of Robotic Process Automation vs. Machine Learning intertwining increasingly, it’s important to know what they are, how they differ, and how you can benefit from them. This article discusses the topic of robotic process automation vs. machine learning to provide you with everything you need to know before you get started with either—or both. ## RPA — doing more for less In the case of [Robotic Process Automation](https://www.flobotics.io/blog/robotic-process-automation), the name says it all: it’s a solution that uses robots or bots, i.e., pre-programmed algorithms, to automate business processes. By mimicking human behavior and combining it with their machine-like efficiency, RPA bots can quickly handle data-heavy, mundane tasks. These include data entry, copy-pasting records, compiling reports, and more. This speed doesn’t come at the expense of accuracy. On the contrary, a well-implemented RPA bot with high-quality data sources can achieve a near-zero margin of error. Machines don’t get distracted, which eliminates common mistakes like typos. RPA works best for tasks based on pre-defined rules and using structured data such as spreadsheets, databases, forms, etc. Another important aspect is volume—the true power of automation is its efficiency, so companies can capitalize on RPA the most by delegating bots to high-volume processes. If all that sounds like RPA is a menace to human employees, don’t worry. RPA excels at the same tasks human workers despise most—mundane, repetitive processes that feel like they could be performed by… a machine. These jobs are crucial to the everyday functioning of your business, but they take your specialists’ focus away from more creative and complex tasks. By teaming up with bots, human employees can spend more time on self-development, seeking new business opportunities, or finding operational improvements. That’s why it’s better to think of RPA as a tool rather than a replacement for your workforce. ### What are the benefits of RPA? Relaying repetitive and time-consuming tasks to RPA bots offers a range of benefits. What are they? - Increased productivity — Bots can perform repetitive workflows much faster than human employees and assist them in other tasks, increasing overall productivity. - Reduced costs — Higher efficiency lowers operational costs and brings cumulative savings in the long run. - Optimized processes — RPA eliminates errors and streamlines workflows, leading to faster project completion. - Fewer errors — Thanks to their accuracy, RPA bots help maintain data consistency and avoid costly mistakes. - Better compliance — RPA follows preset rules with 100% accuracy, minimizing compliance risk. - Improved customer experience — Automation helps reduce response times and solve customer service queries faster. - Higher employee satisfaction — RPA relieves employees from the workflows they dislike and improves their performance at more fulfilling tasks. - Data-based decision-making — By cleaning datasets and making them more accessible, RPA gives all the information to make better decisions. Fig. 01 · RPA 8 gains How RPA helps your business RPA bringsWhich means - Streamlined workflowsBetter processes - Automated tasksHigher productivity - Procedures followed every timeBetter compliance - Faster responsesBetter customer experience - Repetitive tasks taken overHappier employees - Better data quality and accessData-based decisions - Accuracy and consistencyFewer errors - Time and cost efficiencyOperational savings ### RPA use cases for all businesses RPA is a flexible solution that can be customized for various processes. This includes generic workflows that are vital for any business, regardless of the industry: - Invoice processing — Manual invoice processing takes time and is prone to errors. Bots can fulfill invoice-related subtasks like data extraction and entry or error reconciliation quickly and without mistakes. - HR processes — RPA can handle time-consuming tasks such as payroll, recruitment, onboarding, or data verification. This helps HR departments avoid delays caused by errors while increasing employee satisfaction. - Customer service — RPA bots can handle less complex interaction scenarios autonomously or assist your agents in solving more complex ones faster. Bots and voice assistants are also available around the clock. - Data operations — Whether it’s CRM, ERS, ERP, or other software, automation can greatly improve the data flow between all your systems. RPA bots will keep your datasets up-to-date and easy to find and retrieve. - Sales orders — Sales reps spend hours moving data between various systems, verifying it, and creating sales orders. RPA bots relieve them from all these tasks, allowing them to focus on prospecting leads instead. However, RPA usability doesn’t end here, as the technology can also serve more industry-specific purposes. Examples of sectors where RPA has long been used with great success include healthcare, [finance and banking](https://www.flobotics.io/case-studies/t-bank-automation), insurance, supply chain, and manufacturing. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## ML — teaching machines to learn Machine Learning (ML) is a subset of artificial intelligence. AI is concerned with developing technologies allowing machines to think like humans. ML is specifically focused on imitating our ability to learn. Unlike RPA, ML algorithms aren’t programmed to follow specific patterns. Instead, they use historical data to build logical models. Then, these models can be fed new data to make predictions, find patterns, improve performance, or draw conclusions. The more data is put into the model, the more accurate it becomes. The ultimate goal is to solve advanced problems that require analyzing rather than processing data. But isn’t data analysis something we can do by ourselves? This is correct. However, the problem arises when we consider how much information there is. We produce over [1 trillion MB of data](https://financesonline.com/how-much-data-is-created-every-day/) every day. Of course, businesses only make use of a fraction of this data. Still, it’s hard to imagine how one would sort such volumes manually, let alone make sense of them. At the same time, success stories of companies like [Spotify](https://www.aidataanalytics.network/data-monetization/articles/data-visualization-monetization-and-personalization-spotify) or [Uber](https://neilpatel.com/blog/how-uber-uses-data/) show that big data can be a true treasure trove for companies that can use it correctly. That’s where ML steps in. ### What are the benefits of ML? Machine learning allows companies to tap into information better than ever before. This presents them with new opportunities such as: - Better customer understanding — ML models can give invaluable knowledge about the customer base, e.g., client preferences, behavior patterns, or purchasing decisions. - New business models — Data can empower new product features or entire business models. For instance, machine learning drives [Netflix’s ](https://onlinemasters.ohio.edu/blog/netflix-data/)and [Amazon’s](https://www.godatafeed.com/blog/how-amazon-uses-ai-to-dominate-ecommerce) recommendation engines, [Google ads optimization](https://ppcexpo.com/blog/examples-of-machine-learning-in-marketing), and Uber’s driver-rider matching. - Personalized experience — Insights gained from customer data analysis allow businesses to deliver experiences tailored to the specific needs of their customers. - Constant self-improvement — ML algorithms get better with every new dataset received. Over time, they will learn how to make more accurate conclusions faster. - Operational improvements — Inward-focused ML algorithms can help businesses evaluate their processes, find inefficiencies, and develop solutions. - Tighter security — When paired with the existing security systems, machine learning can boost their accuracy as it learns to recognize threats better and discover vulnerabilities. ### How can businesses use ML? Machine learning has nearly unlimited applications, and new ones are constantly discovered. Here are some that are already having an impact across industries. - Computer vision — Visual formats such as photos or videos have always been problematic for machines. ML allows computers to extract meaningful information from these media and use it in radiology imaging, face recognition, self-driving cars, or IoT devices. - Speech recognition — Machine Learning enables speech-to-text tools to understand human speech better and translate it into a written format. This technology is already used for voice search, accessible texting, transcription, or in voice assistants like Google Assistant or Siri. - Fraud prevention — ML models can be taught to identify deviations from standard procedures such as financial transactions. Once an anomaly is detected, it’s automatically flagged as a suspicious activity that requires further investigation. The model will use this data to spot fraudulent activity with greater accuracy. Similarly, ML is used in cybersecurity, e.g., to detect data breaches or malware attacks. - Suggestion engines — Machine Learning can discover preference trends in past customer choices. Based on this data, the algorithm automatically picks suggestions that correlate with customers’ interests. Businesses can also use this information to develop more effective cross-selling strategies, e.g., by recommending relevant products during checkout. - Customer service — ML-powered chatbots and virtual assistants can go beyond relying on predefined interaction scripts. In addition to answering common questions about shipping or availability, they can provide personalized recommendations or cross-sell additional products. Machine learning can also analyze support ticket data and suggest customer help processes and content improvements. Similarly to RPA, machine learning also has more industry-specific applications. One of the most prominent examples is healthcare and diagnostics. For instance, [Google’s Deep Learning ML program](https://learn.g2.com/machine-learning-statistics) detected breast cancer with an 89% accuracy rate. In another test, a [machine learning algorithm](https://www.nature.com/articles/s41598-020-75767-2) achieved 92% accuracy in predicting the mortality of COVID-19 patients. Fig. 02 · Machine learning By industry Machine learning use cases across industries - Banking and financeFraud prevention, risk management, credit approval, trading - HealthcareMedical imaging, diagnostics, drug research - E-commerceSupply chain, recommendations, customer analysis - EnergyUsage patterns, grid optimization, weather prediction, transition planning - Manufacturing and logisticsSupply chain, avoiding shortages and deadstock, product design, quality control ## Robotic process automation vs. machine learning: a comparison As you can see, the two technologies share the same overarching goal: imitating humans to streamline business operations. However, they aim to do that from a different angle. While RPA focuses on replicating human behavior, ML solutions imitate how we think and learn. An important factor to consider when comparing robotic process automation vs. machine learning is how they work. RPA uses rules created by business experts and [RPA consultants](https://www.flobotics.io/about-us) to perform specific workflows. Once these rules are defined, RPA runs the sequence repeatedly. Thus, any improvements require constant performance monitoring and reprogramming. As for ML, only the initial, generic algorithm is built by developers. After that, the algorithm develops logical models and self-learns using the training data it receives. Over time, ML models become more precise and efficient on their own. The tricky part is getting there—before the ML model becomes near-autonomous, it requires supervision and tweaks during training. ### Robotic Process Automation vs Machine Learning: what are they best at? These characteristics affect the type of data RPA and ML can use. On its own, RPA works best with standardized, structured records like spreadsheets and relational databases. On the other hand, machine learning can use any data as long as it’s provided with high-quality training material. That’s why cleaning and preparing the initial data is key when implementing ML. The capabilities of each solution dictate the tasks they are best at. RPA excels at manual, low-value, repeatable tasks that follow clear conditions and use structured data. Increased efficiency eventually brings an ROI and starts generating savings. On the other hand, ML is used to analyze datasets in search of patterns that can be turned into valuable insights or improvements to existing processes. If there’s one similarity between RPA and ML, it’s their usefulness. Although both work differently and serve different purposes, they can be used by businesses from any industry. Fig. 03 · RPA vs ML Comparison RPA vs machine learning | RPA | ML | Preferred data | Structured | Structured, semi-structured and unstructured (once trained) | Main tasks | Repetitive, manual processes | Data analysis | Main goal | Saving time and money | Finding improvements and opportunities | Imitates | Human actions | Human thinking and learning | Relies on | Preset rules | Data | Industries | Any | Any | ## Robotic Process Automation vs. Machine Learning: the synergy ML and RPA are quite different, each with strengths and limitations. What if we combined them to complement each other and form an even better, [diverse automation strategy](https://www.flobotics.io/blog/bpm-vs-rpa-the-difference-and-what-it-means-for-your-business)? Solutions that use RPA and AI (including ML) are known as intelligent or [smart automation](https://www.flobotics.io/blog/smart-process-automation) tools. Smart automation systems combine the best of both worlds: RPA’s efficiency and ML’s learning abilities. Fig. 04 · RPA + ML Together How RPA and ML work together - Unstructured dataML lets RPA process all kinds of data. - Automation insightsML shows which processes gain most from RPA. - Faster learningRPA prepares training datasets for ML. - Better performanceWith ML, RPA becomes more accurate and efficient. When paired with ML, RPA can learn from exceptions and its own mistakes to self-improve without reprogramming. Intelligent automation systems can dynamically find and develop solutions to their problems. By analyzing existing processes, ML can help businesses find workflows where RPA would have the most impact. Another benefit of intelligent automation lies in the ability to work with unstructured information. Normally, RPA is limited to standardized data formats. With the aid of ML, it can be taught to recognize and extract data contained in images, videos, emails, and other unstructured data sources. This relationship isn’t one-sided, though. Machine learning relies on large volumes of well-prepared data to learn how to make correct conclusions and identify patterns. RPA can quickly capture, clean, and update these training datasets so that ML can achieve higher accuracy in a shorter time. We’ve discussed how ML and RPA can be used in any industry. Smart automation is no different. Fig. 05 · RPA + ML By industry How industries use RPA and ML - Banking and financeReconciliation, payables and receivables, validation, onboarding - InsuranceClaims, underwriting, compliance, fraud prevention - Customer serviceSentiment analysis, self-learning chatbots and assistants - HealthcareMedical billing, claims, scheduling, referrals - LogisticsSupply and demand planning, inventory, freight matching - SalesPrice optimization, lead nurturing, segmentation ## ML vs. RPA: make the right choice with Flobotics Should you choose RPA, ML, or implement both jointly? All have their benefits, but ultimately, finding the best solution for your company depends on your processes, goals, employees, and other features that form its unique character. Luckily, you don’t have to make this decision on your own. At Flobotics, we’re happy to share our automation expertise and help our clients through [innovative solutions](https://www.flobotics.io/). Get in touch to discuss all available options and receive [a free proof of concept](https://www.flobotics.io/) to see how automation can transform your business. #### Like the article? Spread the word Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RCMRPAAI ### AI vs. RPA vs. ML in Healthcare RCM: A Deep Dive AI vs. RPA vs. ML in healthcare RCM: how each technology improves efficiency, accuracy, and compliance, and which to adopt first. Krzysztof SzwedFebruary 22, 2025 ](https://www.flobotics.io/blog/ai-rpa-ml-rcm)[ RPAAI ### Agentic AI vs RPA: The Next Frontier of Intelligent Automation Agentic AI vs. RPA: how autonomous agents and traditional bots differ, where each fits, and why a hybrid approach is the 2026 strategy for CTOs. Bart TeodorczukJuly 14, 2025 ](https://www.flobotics.io/blog/agentic-ai-vs-rpa)[ RPA ### BPM vs. RPA: The Difference and What It Means for Your Business RPA and BPM integration: the key differences between the two, and how combining them strengthens your automation strategy. Filip NasiadkoMay 19, 2021 ](https://www.flobotics.io/blog/bpm-vs-rpa-the-difference-and-what-it-means-for-your-business) [All articles →](https://www.flobotics.io/blog) --- # From Warehouse to Delivery: 12 Best RPA Use Cases in the Retail Industry Canonical: https://www.flobotics.io/blog/rpa-use-cases-retail Author: Michał Rejman Published: 2023-06-15 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/From Warehouse to Delivery: 12 Best RPA Use Cases in the… [RPA](https://www.flobotics.io/blog?category=rpa) # From Warehouse to Delivery: 12 Best RPA Use Cases in the Retail Industry [Michał RejmanChief Marketing Officer at Flobotics](https://www.flobotics.io/our-editorial-team#rejman) Published June 15, 2023Updated September 1, 2026 Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byMichał Rejman Chief Marketing Officer at Flobotics. [More from Michał](https://www.flobotics.io/our-editorial-team#rejman) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### RPA in Supply Chain Management: Pros, Cons and The Best Use Examples RPA supply chain use cases: pros, cons, and real examples of how automation cuts costs across the logistics industry. Michał RejmanMay 07, 2021 ](https://www.flobotics.io/blog/rpa-in-supply-chain-management-use-examples)[ RPA ### RPA Reloaded: 50+ Robotic Process Automation Statistics to Know in 2026 RPA statistics 2026: 50+ data points on robotic process automation adoption, ROI, and where the technology is headed next. Yana PokoraApril 15, 2025 ](https://www.flobotics.io/blog/rpa-statistics)[ RPA ### RPA in Manufacturing - What Operational Processes Should You Automate Today? RPA in manufacturing: which back-office processes to automate first, from supply chain to order processing and customer service, in 2026. Yana PokoraNovember 29, 2022 ](https://www.flobotics.io/blog/rpa-in-manufacturing) [All articles →](https://www.flobotics.io/blog) --- # UiPath vs. GCP (Google Cloud Platform): Which to Choose for Your Next Automation Project? Canonical: https://www.flobotics.io/blog/uipath-vs-gcp Author: Krzysztof Szwed Published: 2023-05-30 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/UiPath vs. GCP (Google Cloud Platform): Which to Choose… [RPA](https://www.flobotics.io/blog?category=rpa) # UiPath vs. GCP (Google Cloud Platform): Which to Choose for Your Next Automation Project? [Krzysztof SzwedHead of Delivery at Flobotics](https://www.flobotics.io/our-editorial-team#szwed) Published May 30, 2023Updated September 1, 2026 On this page - [Robotic Process Automation — massive time savings and productivity boost](#robotic-process-automation-massive-time-savings-and-productivity-boost) - [UiPath as an automation tool](#uipath-as-an-automation-tool) - [Step 1. UiPath Studio — build your automations](#step-1-uipath-studio-build-your-automations) - [Step 2. UiPath Robots — assign a bot for the job](#step-2-uipath-robots-assign-a-bot-for-the-job) - [Step 3. UiPath Orchestrator — stay on top of things](#step-3-uipath-orchestrator-stay-on-top-of-things) - [Where UiPath shines: automation in action](#where-uipath-shines-automation-in-action) - [A note on sophisticated UiPath scenarios](#a-note-on-sophisticated-uipath-scenarios) - [What’s Google Cloud Platform automation?](#whats-google-cloud-platform-automation) - [Key business benefits of Google Cloud AI Platform](#key-business-benefits-of-google-cloud-ai-platform) - [GCP automation use cases](#gcp-automation-use-cases) - [UiPath vs GCP one-on-one](#uipath-vs-gcp-one-on-one) - [User interface and ease of use](#user-interface-and-ease-of-use) - [Capabilities and scalability](#capabilities-and-scalability) - [UiPath vs GCP: Pricing and licensing](#uipath-vs-gcp-pricing-and-licensing) - [UiPath vs GCP: Integration with other tools and systems](#uipath-vs-gcp-integration-with-other-tools-and-systems) - [UiPath vs GCP: Advantages and limitations of UiPath and Google Cloud Platform automations](#uipath-vs-gcp-advantages-and-limitations-of-uipath-and-google-cloud-platform-automations) - [Why choose UiPath?](#why-choose-uipath) - [Why choose GCP?](#why-choose-gcp) - [UiPath vs GCP: Final remarks](#uipath-vs-gcp-final-remarks) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Imagine you’re a financial officer responsible for employees getting paid on time. However, you don’t use payroll software and run all processes by hand. This means going through timesheets and vacation times, calculating payroll hours, filling out forms, and sorting out tax deductions and contributions—person by person, file by file. And once you’re through with calculations, you still need to print and distribute checks, make money transfers, and update payroll records, usually kept as spreadsheets. That sounds like a lot to handle, right? Let’s discover together what processes can automation handle and see the fight of two automation tools: UiPath vs GCP (Google Cloud Platform). ## Robotic Process Automation — massive time savings and productivity boost Now, contrast that with [Robotic Process Automation Payroll Processing.](https://www.flobotics.io/blog/payroll-process-rpa) RPA works 24/7, automatically collecting and standardizing data from different sources and formats. In addition, it can quickly complete complex calculations and update all documents and databases to keep them current. All that and more results in time-savings from 60-95%, depending on the task. This translates into hours that can be spent on more advanced jobs. Such a productivity boost also saves thousands of dollars monthly. Taking advantage of RPA is a true win-win, so the question shouldn’t be whether to use it for process automation but which solution to choose. And we’ll get to that in a minute, setting side by side two technologies you may consider for your next automation project—get ready to delve into the details of UiPath vs GCP (Google Cloud Platform). But first, let’s get a little refresher on RPA. If you don’t need it, you can skip immediately to section UiPath as an automation tool. ## UiPath as an automation tool [UiPath](https://www.uipath.com/) is one of the pioneers of Robotic Process Automation and the current market leader. The end-to-end platform provides comprehensive features essential to create automations, execute them by bots, and keep them under control. ### Step 1. UiPath Studio — build your automations The first core component of UiPath’s RPA platform is [UiPath Studio](https://www.uipath.com/product/studio). Your robotic automation development starts here. An advanced but intuitive tool, Studio offers a powerful automation canvas for developers and business users. They can build automations based on a rich collection of pre-built activities and templates. All work is done by dragging and dropping visual components and diagrams, so many projects don’t require software programming knowledge. Of course, professionals can take advantage of more advanced features to supercharge their automations, for instance, by adding custom code integration. ### Step 2. UiPath Robots — assign a bot for the job Once you’re done designing automation, you must execute them. For that, you’ll need [UiPath Robots](https://www.uipath.com/product/robots). Instead of reinventing the wheel, you may use UiPath’s existing smart bots. They can execute various tasks, such as reading text or image input, interacting with third-party apps and databases, or making decisions to move the workflow forward. Depending on the level of assistance from a human agent, they fall into two categories: - Attended UiPath robots – bots that cooperate with humans, operating in the background - Unattended UiPath robots – bots that can work independently, taking charge of more complex, long-running workflows ### Step 3. UiPath Orchestrator — stay on top of things Finally, another core element of UiPath automation is the orchestrator. This user-friendly interface lets you keep track of your robots and manage their performance. Using [UiPath Orchestrator](https://www.uipath.com/product/orchestrator), you can deploy and provision bots, distribute, schedule, and monitor workflows, and manage integrations with external solutions. Fig. 01 · UiPath Components UiPath platform components - 01UiPath StudioWhere bots are built - 02UiPath RobotRuns the automation - 03UiPath OrchestratorDeploys, schedules and monitors bots ### Where UiPath shines: automation in action And how about practical applications of UiPath? Those are unlimited. The solution’s scalability and versatility allow virtually any industry to enjoy its benefits. Let’s consider a few amazing examples. #### UiPath and public sector Out of numerous use cases featured on UiPath’s website, those within the public sector industry particularly stand out. Just look at this success story of [the West Midlands Police Department](https://www.uipath.com/resources/automation-case-studies/west-midlands-police-improves-policing-operations-through-automation), which used RPA by UiPath to automate back-end processes and serve the public more effectively. One of the key areas where bots provided immense value was uploading witness statements—thanks to automation, police officers can fill out a digital statement on the spot without having to make a trip back to the base. Another important area where bots help the police preserve their professionalism is recruitment, ensuring candidates from underrepresented ethnicities aren’t falling victim to cognitive bias. → See more [RPA use cases for the public sector](https://www.uipath.com/resources/automation-case-studies?filterResources=&Industries=Public-Sector). #### UiPath and energy and utilities UiPath automations also immensely contribute to energy and utilities. In the case of Morrison Utility Services, the company’s RPA solution has helped save more than 320 person-hours per month on 27 automated processes. Among other workflows, UiPath’s robots helped optimize the risk assessment process, gathering relevant data, generating reports, and distributing them among key decision-makers. The bots have also helped eliminate typos and errors from data inputs, improving service quality and speeding up delivery. → See more examples of how [UiPath helps energy and utility services](https://www.uipath.com/resources/automation-case-studies?filterResources=&Industries=Energy-and-Utilities) #### UiPath and entertainment The UiPath platform is also a great match for the media and entertainment industry, as demonstrated by RedPeg, a marketing company providing digital services. In its case, robot automation has [shortened the time needed to kick off online poker games](https://www.flobotics.io/case-studies) and assign players to tables by 15 times! Another notable example comes from Spotify. The company has [launched a business-wide citizen developers program](https://www.uipath.com/resources/automation-case-studies/spotify-expands-commitment-automation) to upskill employees and allow them to develop their automations. So far, it has deployed over 100 RPA robots to simplify and improve business processes, saving over 45,500 hours to date. ### A note on sophisticated UiPath scenarios When mentioning all these remarkable examples of UiPath in action, we must, however, flag one important thing. Even though the solution is designed for non-technical users, a person without programming experience is unlikely to deliver highly complex use cases. Sophisticated scenarios require coding skills and automation knowledge, usually involving custom integrations and features. Fortunately, our team of experienced [UiPath developers](https://www.flobotics.io/uipath-services) can provide them to you. For more use cases in media, entertainment, and other industries, [check out UiPath’s resources page](https://www.uipath.com/resources/automation-case-studies/prmg). Fig. 02 · RPA By industry An RPA solution for every industry - Banking and financeUse RPA and RPA + AI for higher returns on automation. - HealthcareDeliver services more efficiently and more personally. - Public sectorResilience, speed and efficiency to serve citizens. - TelecomBetter performance from network operations to retail shops. - ManufacturingBetter quality and efficiency across operations. - RetailImprovements in store operations, workforce and customer relations. - InsuranceProtect customer and employee satisfaction, and your bottom line. Learn more about [SAP automation](https://www.flobotics.io/business-process-automation) with UiPath! Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## What’s Google Cloud Platform automation? Now, on to another useful tool that helps businesses capitalize on automation. [Google Cloud Platform](https://cloud.google.com/) allows professional and citizen developers to quickly build, deploy, and automate business apps, websites, and services running on Google infrastructure. The platform belongs to Google Cloud and provides a catalog of services, including storage, hosting, database, big data analytics, networking, and AI and machine learning. And if you are wondering what it has to do with robotic automation, let us explain. In 2021, Google partnered with a well-established RPA software producer Automation Anywhere, to expand its GCP products like AppSheet or AI Platform with RPA capabilities. As a result, GCP provides access to [numerous AI-based models and services](https://cloud.google.com/solutions/ai) enhanced with automation features. Users can access and deploy them through the Google Cloud Platform. Examples of such solutions include Document AI, used for smart document reading and processing, Product Discovery, which provides personalized product recommendations, or Contact Center AI, a virtual help agent to streamline the customer support experience (jump to [GCP automation use cases](https://docs.google.com/document/d/1CBBN_jfB3-CGt0jvKeFXFfHHACrJ6lyoQzsn3eWbWys/edit#heading=h.4qwmblz0zg0k) to learn more). Moreover, the AI team at Google shares a trove of data with the public through [extensive datasets](https://ai.google/tools/). Using them helps train and improve AI and ML models to tap into bottomless resources stored across the web. ### Key business benefits of Google Cloud AI Platform Regarding the business benefits of GCP’s AI and other services, most align with the key advantages of other Google cloud products. #### Enterprise-level security Getting services from a leading cloud provider in the world by default comes with heightened security. A global mega-enterprise with hundreds of billions of dollars of revenue cannot afford to compromise on data safety and protection. That’s why when choosing automation services from Google, you can rest assured that your data are safeguarded by the most elite security experts and top-class, robust solutions. #### High reliability Google is committed to ensuring high availability and reliability, guaranteeing 99.99% service uptime or above. While downtime and outages may happen, they are rare and shouldn’t affect your automations. Moreover, Google collaborates with various system integration partners providing backup and disaster recovery services. So in case anything happens and you lose access to your service, you’re still safe knowing that your data will be fully recovered. #### Unrelenting innovation Pushing the envelope for cloud innovation, Google regularly updates its platform and services. This not only helps deliver improved protection, but also provides regular service improvements. As you continue using the existing automation services, new ones are coming out frequently, so you can continue to innovate and improve your processes. #### Fast-paced deployment Google’s automations are delivered as ready-to-deploy services in the cloud. Moreover, to install and launch them, you often don’t need to involve your IT department (or their engagement will be peripheral). This translates to immense time savings, meaning you can take advantage of your new automations in minimum time. ### GCP automation use cases Google Cloud Platform services can help automate all sorts of tasks, from more sophisticated and detailed to primary and general. For example, companies can implement speech-to-text and [simple text-to-speech](https://www.adobe.com/products/firefly/features/text-to-speech.html) functions or cloud vision for image recognition. These services can serve various purposes—here are a few examples: - Automated mobile events. One tool we can’t skip when discussing GCP’s automation capabilities is [Cloud Functions](https://cloud.google.com/functions). It’s a serverless environment for building and connecting cloud services. It lets developers run code in the cloud to automate various tasks triggered by Google’s Firebase platform, which is used to develop mobile apps and games quickly. Examples of jobs that Cloud Functions can automate include sending out mobile notifications or email confirmation upon a trigger action (an event, a subscription, etc.) or automatically moderating images in an app. - Task management. Another interesting automation feature from GCP is [AppSheet Automation](https://cloud.google.com/appsheet/automation). This service combines the power of AI with no-code capabilities to let business users automate their tasks efficiently. It helps optimize processes related to project and inventory management, data retrieval, job tracking, team management, and more. You can build automation triggered by SMS messages, calls, emails, file creation, etc. - Document processing. As already mentioned, [Document AI](https://cloud.google.com/document-ai/) is a universal platform that transforms unstructured data into structured, easily readable information. As such, it can be used across a variety of industries, from banking (document verification and pre-assessment) and healthcare (faster processing of patient records) to retail (bill, invoices, purchase orders scanning and input) and travel and logistics (tracking labels and receipts or fast-tracking passport and visa processing). - HR & recruitment. In terms of more specialized solutions, companies can, for instance, accelerate and improve talent acquisition with [Cloud Talent Solution](https://cloud.google.com/solutions/talent-solution/). It is an ML technology that helps match eligible candidates to jobs faster and tweak job descriptions for more accurate searches. - Customer service. Another example of more specialized automation from Google would be [Contact Center AI](https://cloud.google.com/solutions/contact-center), which refers to virtual agents that can enrich and speed up customer experience interactions with contact centers. These are just a few famous examples, but GCP offers other functional automation beyond AI/ML. Some of them, like [Recommendations AI](https://cloud.google.com/recommendations-ai/docs/) or [Cloud Life Sciences](https://cloud.google.com/life-sciences/docs), were created specifically for a given industry (in this case, retail and healthcare). ## UiPath vs GCP one-on-one UiPath is a top RPA product, while Google Cloud Platform is a cloud service suite that includes simple and more advanced automations. Depending on your use case and project, you may consider either to get the most out of automation. With that in mind, let’s see UiPath vs GCP battle. ### User interface and ease of use Thanks to the visual drag-and-drop workflow builder, pre-defined tasks and tools, and clear distinction between the Studio, Robots, and Orchestrator components, UiPath is among the users’ favorites regarding ease of use. Getting a solid grip on the platform’s essential features takes one to two days, and even citizen developers can build fairly complex automation with the tool. Additionally, the platform has a [robust marketplace ](https://marketplace.uipath.com/)where users can get various tools and connectors to upgrade their projects without having to program. While the Google Cloud Platform comes with a familiar interface, it might be difficult to learn because of the multitude of features and options available. There are plenty of training videos and certification paths, including ones for cloud novices, but still, to use GCP cost-effectively requires a more thorough understanding of its services. Because of that, user reviews are mixed, and many voices appear talking about GCP as a complex tool professionals best handle. The winner: UiPath ### Capabilities and scalability UiPath’s extensive capabilities make it the leading RPA solution on the market. The platform provides thousands of automation, covering all stages of their development, from creation and provisioning to testing, monitoring, and managing robots. Moreover, the company constantly innovates its product, expanding beyond traditional RPA capabilities to offer data science and AI automation solutions. Finally, UiPath also offers excellent scalability thanks to modular and reusable components that speed up the development of even the most complex scenarios. Still, putting GCP also provides a scalable infrastructure that quickly adjusts to the current demands. In addition, it comes with auto-scaling features, scaling up and down based on predefined thresholds. GPC is extremely versatile in capabilities, offering nearly 200 services (although only a minority are for automation). Because it’s primarily a cloud computing platform, GCP provides storage, computing, and networking capabilities and enables automated app deployment and scheduling. And products like Cloud Functions or Workflows help developers automate backend processes. They can be used to connect services and manage the underlying infrastructure to address the current service demand. The winner: GCP, due to the better scaling capabilities ### UiPath vs GCP: Pricing and licensing [UiPath offers specific plans](https://www.uipath.com/pricing) that depend on the number of licenses and available features. A free plan is available for individual users building simple automation for personal use, while professional plans start at $420/month and can serve up to three tenants. Enterprises need a custom plan that provides access to all functions and can accommodate unlimited users. With all that in mind, UiPath is considered an expensive tool, especially for small companies and beginners. While comparing UiPath vs GCP, in contrast, Google Cloud Platform offers a [pay-as-you-go pricing model](https://cloud.google.com/pricing) with $300 worth of free credits. When spent, the costs rise progressively, depending on workloads, services, and even location, which may sometimes create confusion. Monitoring tools are available to keep spending under control. Still, as always, with this type of pricing, it’s easy to go overboard when you’re not careful enough. The platform also comes with some free services. The winner: UiPath; despite the steep prices, it makes it easier to control spending ### UiPath vs GCP: Integration with other tools and systems UiPath has been designed to seamlessly integrate with all major enterprise apps like AWS, Salesforce, SAP, Microsoft, and many others. The platform supports over 1,400 automation integrations via API and user interface, in many cases making it possible to connect to other tools even for non-technical users. GCP’s integration service connects automatically to third-party apps, databases, and internal Google Cloud Platform services. The platform also comes with a [range of connectors](https://cloud.google.com/integration-connectors/docs/about-connectors), which enable fast integration with platforms and data sources, including Magento, HubSpot, Salesforce, Jira, various SQL databases, and FTP and HTTP servers. However, users are polarized regarding the ease of GCP’s integration. While some praise vast integration capabilities, many complain that it requires technical support. The winner: a slight win for UiPath ## UiPath vs GCP: Advantages and limitations of UiPath and Google Cloud Platform automations ### Why choose UiPath? UiPath is an excellent choice if you need a fairly accessible tool that will help you automate repetitive tasks in web-based apps easily. The solution’s biggest advantages include: Fig. 03 · UiPath Pros and cons UiPath: advantages and limitations Pros - No-codeDrag-and-drop interface with hundreds of built-in tools - ReliabilityDependable, top-class RPA - ConnectivityIntegrates with most enterprise platforms - ML and AIIntelligent process automation - VersatilityUsed in almost every industry - Advanced automationsSupports even very sophisticated bots Cons - High costFrom $420 a month - Unstructured dataNeeds intelligent automation add-ons, adding cost and complexity - Enterprise focusSmaller companies may pay for more than they need ### Why choose GCP? Suppose you are wondering why choose Google Cloud Platform over UiPath. In that case, these might convince you: Fig. 04 · Google Cloud Pros and cons Google Cloud: advantages and limitations Pros - Big dataMany storage and analysis services for large data volumes - ImplementationWeb-based, out-of-the-box services launch quickly - ExperimentationLow entry cost to test, easy move to production - Right-sizedSuits smaller companies that need simple automations Cons - Unpredictable pricingCosts can add up fast as use cases grow - Not built for automationFirst of all a cloud infrastructure platform - Limited flexibilityCovers a narrow range of RPA use cases ## UiPath vs GCP: Final remarks UiPath vs GCP: tools that come from entirely different worlds, so that we may have just compared apples to oranges. However, considering that the process automation market is expected to reach [a CAGR of 5.1% by 2025](https://www.mordorintelligence.com/industry-reports/process-automation-market), it’s no wonder that technology companies want to partake in it. And such is the story of the Google Cloud Platform, which provides more and more automation and AI/ML-driven services to meet the ever-increasing demand for process optimization. And in some respects, it might be a better choice than traditional RPA solutions like UiPath, especially if you only need to automate individual processes. However, where long-term, large-scale automation is required, UiPath vs GCP, the first one is the way to go as it offers greater flexibility and selection of RPA bots than its Google counterpart. But if you are still unsure which of the two would be a better option for you, we will gladly help. Thus, if you don’t want to get stuck in the nightmare of slow, manual processes, contact us, and we’ll recommend the best software for your scenarios. And in the meantime, if you’re wondering how UiPath ranks against other popular RPA solutions on the market, check out our [Python automation guide](https://www.flobotics.io/blog/automation-python) or comparisons: [UiPath vs. Automation Anywhere, UiPath vs. Blue Prism, and UiPath vs. Power Automate](https://www.flobotics.io/blog/uipath-vs-aa). Hoping to hear from you soon! #### Like the article? Spread the word Written byKrzysztof Szwed Head of Delivery at Flobotics. [More from Krzysztof](https://www.flobotics.io/our-editorial-team#szwed) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### UiPath vs. Power Automate - Which RPA Tool To Choose? UiPath vs. Power Automate: compare features and pricing to decide which RPA tool best fits your 2026 process automation needs. Bart TeodorczukJune 27, 2022 ](https://www.flobotics.io/blog/uipath-vs-powerautomate)[ RPA ### Blue Prism or UiPath? Choosing the Best RPA Tool for Your Business Blue Prism vs. UiPath: compare features, pricing, and support to choose the right RPA platform for your automation project. Bart TeodorczukAugust 22, 2022 ](https://www.flobotics.io/blog/blueprism-vs-uipath)[ RPAAI ### UiPath vs. Celonis vs. Kyp.ai: Comparing Top Task Mining Tools UiPath vs. Celonis vs. Kyp.ai: features and pricing compared to help you pick the right task mining tool for 2026. Bart TeodorczukNovember 20, 2023 ](https://www.flobotics.io/blog/uipath-vs-celonis-vs-kypai) [All articles →](https://www.flobotics.io/blog) --- # ChatGPT for Healthcare: How Intelligent Chatbots Can Transform Medicine Canonical: https://www.flobotics.io/blog/chatgpt-for-healthcare Author: Bart Teodorczuk Published: 2023-05-15 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/ChatGPT for Healthcare: How Intelligent Chatbots Can… [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RPA](https://www.flobotics.io/blog?category=rpa) # ChatGPT for Healthcare: How Intelligent Chatbots Can Transform Medicine [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published May 15, 2023Updated September 1, 2026 On this page - [ChatGPT for healthcare: top use cases](#chatgpt-for-healthcare-top-use-cases) - [Decision support for doctors](#decision-support-for-doctors) - [Self-care tools for patients](#self-care-tools-for-patients) - [Medication trackers](#medication-trackers) - [AI-assisted medical coding](#ai-assisted-medical-coding) - [Administrative tasks](#administrative-tasks) - [Medical translation](#medical-translation) - [Fast triage](#fast-triage) - [ChatGPT in telemedicine](#chatgpt-in-telemedicine) - [Remote patient monitoring](#remote-patient-monitoring) - [Mental health support](#mental-health-support) - [ChatGPT in medical research](#chatgpt-in-medical-research) - [ChatGPT for healthcare: risks and challenges](#chatgpt-for-healthcare-risks-and-challenges) - [Conclusion](#conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Developed by OpenAI, ChatGPT became an instant hit and the fastest consumer app to reach [100 million monthly active users](https://www.reuters.com/technology/chatgpt-sets-record-fastest-growing-user-base-analyst-note-2023-02-01/). The conversational chatbot owes its success not only to its ability to generate detailed, human-like responses to seemingly any question. Its flexibility is just as important. Since its release, people have been using it for everything from writing blog articles, social media posts, and even poetry to coding and planning holidays. The possibilities seem endless, and businesses of all industries want to take advantage. Healthcare is no different. From assisting doctors to expediting [clinical back-office workflows](https://www.flobotics.io/blog/healthcare-workflow-automation), there’s no lack of potential applications for ChatGPT in healthcare. This article will investigate the most promising ones and the challenges providers must consider when implementing ChatGPT for healthcare. ## ChatGPT for healthcare: top use cases To best understand the potential of ChatGPT in healthcare, it’s essential to make one thing clear: ChatGPT is not an automation solution. Rather than handling workflows independently, ChatGPT requires human input—prompts—to generate the requested output. That makes it a perfect tool for retrieving, processing, and creating text-based content. However, automation and ChatGPT share a common general goal: boosting productivity. The benefits of ChatGPT for healthcare are similar, too. Providers and physicians can use it to reduce paperwork and become more available to patients. In addition, the model can help prevent [medical billing ](https://www.flobotics.io/blog/how-to-build-automated-medical-billing-system)errors and enhance patient communication with some supervision. All in all, ChatGPT can save time and money while improving patient outcomes. Fig. 01 · ChatGPT Basics ChatGPT: what you need to know - A large language model (LLM) that recognizes, understands and generates text - Imitates how people understand and use language, using natural language processing (NLP) - Trained on millions of texts, including books, websites and articles - You talk to it: a person writes a prompt and ChatGPT replies - Answers questions and summarizes, translates, paraphrases and writes text - Improves through machine learning (ML) Medical specialists can use [ChatGPT and automation](https://www.automationanywhere.com/company/blog/rpa-thought-leadership/chatgpt-and-rpa-automating-thought-and-action-healthcare) together for an even better effect. That’s why leading RPA companies like [UiPath or Automation Anywhere](https://www.flobotics.io/blog/uipath-vs-aa) are working on integrating OpenAI’s chatbot with their platforms. With that said, how exactly can you use ChatGPT in healthcare? ### Decision support for doctors ChatGPT’s learning abilities are a crucial ingredient of its success. In healthcare, these abilities can be used to train the model with medical data. With that knowledge, ChatGPT can make data-based suggestions regarding diagnosis, treatment, and drug interactions or give insights for specific cases. By working together with AI, physicians can make more informed decisions faster. ### Self-care tools for patients Patients can use ChatGPT-based systems to identify and understand their health issues. Then, based on symptoms, ChatGPT suggests the following steps: further medical assistance, preventive measures, home remedies, or non-prescription drugs. With this guidance and all available information about their condition, patients can make better decisions, leading to more positive outcomes. ### Medication trackers Similarly, ChatGPT can help patients keep track of their medicines. This could be particularly helpful for those who need to take several medications each day. For example, the model could provide detailed information about each medication, such as proper dosage and storage, as well as potential side effects or interactions with other meds. Then, if a drug is unavailable or the patient is intolerant to it, ChatGPT can suggest an alternative. AI medication trackers could also be beneficial for physicians. For example, they could use it as an additional source of information about new medicines, defective drugs, and recalls or to quickly look up specific drugs. Fig. 02 · ChatGPT 6 benefits Benefits of ChatGPT in healthcare - Higher productivitySpeeds up work from diagnosis and treatment to research and paperwork. - Better-informed decisionsDoctors find the data they need quickly. - Personalized medicinePhysicians adjust treatment to each patient faster. - Patient educationPatients learn about treatment, medication and results on their own. - Always availablePatient service around the clock. - Better patient careEasier access to medical data leads to better outcomes. ### AI-assisted medical coding ChatGPT for healthcare isn’t limited to the physician’s office. A good example is [medical coding](https://www.flobotics.io/blog/medical-coding). When performed manually, it’s a slow and repetitive process that requires precision. Any error can lead to [claim denials](https://www.flobotics.io/agents/denials-management-automation) or [compliance](https://www.flobotics.io/rcm-automation) violations. Medical coders can use ChatGPT’s language processing capabilities to generate the most appropriate codes for specific symptoms and patient history. With that, providers will avoid costly [medical coding](https://www.flobotics.io/blog/how-to-build-automated-medical-billing-system) mistakes and process large volumes of patient data in a shorter time. ### Administrative tasks According to [Becker’s Hospital Review](https://www.beckershospitalreview.com/healthcare-information-technology/ehrs/physicians-spending-nearly-2-hours-a-day-on-ehr-tasks-outside-work/), physicians devote almost 2 hours daily on average to [EHR-related processes](https://www.flobotics.io/blog/electronic-health-records-rpa). However, in the same study, 57% of doctors declared that administrative burdens reduce time spent with patients. Many back-office tasks in healthcare involve writing, and ChatGPT is just the tool for that job. For example, the model can assist doctors by drafting letters to insurance companies, appeal denials, clinic notes, imaging reports, or patient instructions. Additionally, ChatGPT can use distinct tones of voice. This allows doctors to easily personalize the content, whether formal correspondence or rhymed medication instruction for younger patients. ### Medical translation Language-processing capabilities of ChatGPT make it excellent for translation, especially when it’s needed quickly. This enables better real-time communication between doctors and patients remotely and during visits. For patients, this also means more accessible access to medical information, such as diagnoses or medical instructions, and a better understanding of complicated medical terms. ### Fast triage Providers can use ChatGPT to determine quickly how urgent each case is. This is done by asking patients to answer questions about their condition, medical history, and symptoms. Based on this data, ChatGPT generates a triage summary that doctors can use to set priorities for treatment more efficiently. ### ChatGPT in telemedicine The need for telemedicine skyrocketed during the pandemic and shows no sign of stopping. McKinsey estimates that by July 2021, the [demand for remote healthcare services](https://www.mckinsey.com/industries/healthcare/our-insights/telehealth-a-quarter-trillion-dollar-post-covid-19-reality) has increased 38 times compared to pre-covid levels. In this context, healthcare providers can significantly benefit from any solution allowing them to grant patients better access to their services. ChatGPT can be one of them and serve as each patient’s virtual assistant. Intelligent chatbots can provide patients with personalized medical advice and answers to questions regarding their treatment options, prescriptions, and condition. This will improve availability and more human-like remote interactions between providers and patients. ### Remote patient monitoring Remote patient monitoring (RPM) is a part of telemedicine that focuses on gathering patient data using monitoring devices such as sensors or wearables. In RPM, the role of ChatGPT is to provide doctors with insights into patient status based on the analysis of the collected data. In the case of high-risk patients, a chatbot-powered RPM solution can also send alerts to physicians when a patient’s condition worsens. This gives physicians more tools to track patients’ health and react quickly without hospitalizing them. Fig. 03 · ChatGPT Who uses it How ChatGPT can be used in healthcare Physicians - Find information quickly - Faster triage - Less admin work - Write letters, notes, instructions and other medical content Patients - Answers about their condition, treatment and self-care - Remote monitoring without a hospital stay - Easier access to mental health support - Medication tracking Providers and businesses - Fast, error-free medical billing - More efficient documentation - AI-assisted research - Clinical trial recruitment ### Mental health support The demand for mental healthcare has soared in the past years, and it’s starting to exceed capacity. For example, 66% of psychologists surveyed by the American Psychology Association have reported increased [demand for depression treatment.](https://www.apa.org/news/press/releases/2022/11/mental-health-care-strains) Although ChatGPT can’t replace the human interaction and expertise of trained therapists, it can complement their services. Given the limited access to mental healthcare, the model can be used as a first line of contact for patients seeking guidance. This is achieved through personalized, conversation-based “talking therapy” that helps relieve stress and anxiety. In addition, ChatGPT can screen patients for mental illnesses and offer advice, resources, and referrals for further mental health services. ### ChatGPT in medical research In addition to its use in patient care and administrative work, ChatGPT has multiple applications in medical research. Here, its strength lies in quickly processing large volumes of data such as articles, reports, and patient records. As the model goes through these sources, it extracts relevant information and turns it into structured insights that can inform further research. ChatGPT can also help researchers learn what they don’t know and generate ideas for future studies. Regarding clinical trials, ChatGPT can analyze patient data for suitable participants. This will expedite recruitment and allow practices to target a more diverse population. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## ChatGPT for healthcare: risks and challenges If you think all that sounds too good to be true, you’re… partially correct. The potential for using ChatGPT in healthcare is very much there, but it raises some concerns. First, there’s accuracy. Unfortunately, the algorithm tends to “hallucinate,” making up non-existing facts or even citations, so take all its suggestions with a grain of salt. Another thing to consider is that ChatGPT doesn’t pull data from the internet. Instead, the model was trained on many texts published before 2021. As a result, it still has limited knowledge of any facts that occurred afterward. Another much more significant issue is [security](https://www.flobotics.io/blog/8-security-practices-for-rpa-implementation) and data privacy. OpenAI admits that [ChatGPT can use conversation data](https://help.openai.com/en/articles/6783457-what-is-chatgpt) to improve, which runs the risk of privacy breaches. Even though the company doesn’t share any user data publicly and [claims](https://www.flobotics.io/agents/claims-management-automation) that all information is protected, it urges users not to share any personal information, including identifiable patient data. Still, these precautions are insufficient for many. Italy has lately famously become the first country to temporarily [ban the advanced use of ChatGPT](https://www.bbc.com/news/technology-65139406) over concerns about data collection and potential misinformation. Due to all that, ChatGPT in its current form shouldn’t be used without oversight—particularly when health or sensitive data is concerned. Still, even now, the model can significantly expedite many tasks provided specialist reviews and verifies the output. Also, it’s important to remember that ChatGPT is still in its infancy, and OpenAI constantly works on advancing the model. For example, a new major update called GPT-4 was released in March 2023. It boasts higher accuracy, better reasoning capabilities, and image input, among other improvements. Similarly, existing regulations will have to be updated to ensure that AI tools like ChatGPT warrant the protection of user data. ## Conclusion All the possible use cases prove that ChatGPT may become a standard healthcare tool in the future. Physicians and medical staff are already starting to investigate this potential and benefit from the powerful bot. Once ChatGPT overcomes all its current challenges, it will transform the industry, enabling faster, more accurate, cost-effective healthcare services and improving patient outcomes. #### Like the article? Spread the word Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RCMHealthcare ### How to Improve Revenue Cycle Management: 8 Strategies for Healthcare Leaders Revenue cycle management strategy: 8 practical steps healthcare leaders can use to boost collections and speed up the revenue cycle. Krzysztof SzwedJune 25, 2025 ](https://www.flobotics.io/blog/revenue-cycle-management-strategy)[ Healthcare ### Top 30 Software Solutions for Healthcare in 2026 Healthcare software solutions: explore 30 essential tools for 2026, organized by function, to strengthen clinical care and streamline admin tasks. Yana PokoraDecember 23, 2024 ](https://www.flobotics.io/blog/healthcare-software)[ RPAHealthcare ### 10 Benefits of Artificial Intelligence in Healthcare Benefits of artificial intelligence in healthcare: 10 ways AI cuts administrative costs, speeds prior authorizations, and improves data accuracy. Bart TeodorczukJuly 22, 2025 ](https://www.flobotics.io/blog/benefits-artificial-intelligence-healthcare) [All articles →](https://www.flobotics.io/blog) --- # The Complete Guide to Sales Process Automation: From Idea to Implementation Canonical: https://www.flobotics.io/blog/sales-process-automation Author: Filip Nasiadko Published: 2023-05-12 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/The Complete Guide to Sales Process Automation: From Idea… CEO Notes [RPA](https://www.flobotics.io/blog?category=rpa) # The Complete Guide to Sales Process Automation: From Idea to Implementation [Filip NasiadkoCEO and Co-founder at Flobotics](https://www.flobotics.io/our-editorial-team#nasiadko) Published May 12, 2023Updated September 1, 2026 On this page - [What is sales automation, and why does it matter?](#what-is-sales-automation-and-why-does-it-matter) - [Eliminate manual data entry](#eliminate-manual-data-entry) - [Score, prioritize, and nurture leads](#score-prioritize-and-nurture-leads) - [Get accurate forecasts and reports](#get-accurate-forecasts-and-reports) - [Improve client communication](#improve-client-communication) - [Increase job satisfaction](#increase-job-satisfaction) - [Sell more in less time](#sell-more-in-less-time) - [Implementing sales process automation in 4 steps](#implementing-sales-process-automation-in-4-steps) - [#1. Quantify automation potential and prioritize opportunities](#1-quantify-automation-potential-and-prioritize-opportunities) - [#2. Test prioritized use cases](#2-test-prioritized-use-cases) - [#3. Choose the right technology](#3-choose-the-right-technology) - [#4. Scale, improve, and plan ahead](#4-scale-improve-and-plan-ahead) - [RPA in sales: the success stories](#rpa-in-sales-the-success-stories) - [Cobmax: 50% less time spent on copy-paste](#cobmax-50-less-time-spent-on-copy-paste) - [Synergy: 99% billing errors out, courtesy of bots](#synergy-99-billing-errors-out-courtesy-of-bots) - [Riyad Capital: 66% faster client onboarding](#riyad-capital-66-faster-client-onboarding) - [Bottom line](#bottom-line) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Have you ever wondered how much time your salespeople spend selling? According to [the sales statistics collected by Salesforce](https://www.salesforce.com/blog/15-sales-statistics/), that’s only 28% of their week. The rest of the sales reps’ work time goes to administrative duties, CRM database updates, or internal calls and meetings. Inevitably, this leads to missed opportunities and lower business results. The proof? Participants of [a poll held by Dooly](https://customerthink.com/why-are-salespeople-spending-so-much-time-working-but-not-selling/) admitted that, on average, they could drive 38% more profit if they didn’t need to focus on non-revenue generating activities (NRGs). The potential for automation is here: [McKinsey’s vendor interviews](https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/sales-automation-the-key-to-boosting-revenue-and-reducing-costs) revealed that over one-third of sales, operations could be enhanced using the currently available automation tools. However, the same report notes that sales and marketing tend to fall behind other departments regarding automation adoption, such as finance or supply chain. This blog post addresses this reluctance by discussing the benefits of automating sales processes, going step-by-step through the implementation, and providing real-life examples of three companies that enhanced their sales operations. ## What is sales automation, and why does it matter? Sales process automation refers to tools and software that streamline manual, repetitive, and time-consuming tasks within the sales workflow. This allows salespeople to save time and focus on building meaningful relationships with clients, closing deals, or improving their skillset. Automation can benefit your sales team in multiple ways. What are the most significant ones? ### Eliminate manual data entry [31% of salespeople spend more than one hour on data entry-related tasks](https://www.hubspot.com/state-of-marketing) daily. It adds up to at least 5 hours a week devoted to mundane, error-prone copying-and-pasting rather than contacting or researching prospects. Sales automation tools can handle most data-related tasks: records migration, major CRM upgrades, or daily customer profile updates. When integrated with email, these tools can extract customer details such as email address, company name, or even industry and enter them into your CRM. You can also use automation to quickly pull existing customer data from your other systems, such as ERP or EHR. Again, the volume doesn’t matter—unlike human workers, automation tools can process data around the clock with a near-zero error margin. Besides simply moving records, sales process automation allows you to enrich your current datasets with additional information. For example, you can sync your automation tool with Google Apps (like Calendar, Tasks, or Contacts) or program them to independently research and enter customer details such as demographics, company size, location, revenue, etc. ### Score, prioritize, and nurture leads With all customer data in place, the next step is to assess the value of every prospect and set sales priorities. Here, sales automation tools compare customer information and actions (e.g., requesting a demo or visiting the pricing page) with pre-determined criteria to evaluate how close each prospect is to your perfect lead. The most significant advantage of automated lead scoring lies in quickly processing thousands of potential leads. Based on the assigned lead score, the system can independently decide which prospects are most worth nurturing and which will waste your time and resources. Speaking of nurturing, sales automation can also prepare and distribute customized proposals that will help you minimize customer churn. All that is to make sure that your efforts target the relevant audience. ### Get accurate forecasts and reports Reliable sales forecasts and reports drive profit and help you make informed business decisions. However, manually drawing up an accurate, extensive analysis takes time and energy. Worst of all, one mistake can bring all that effort to naught. With automation tools, you can build report and forecast templates to generate an up-to-date sales analysis whenever needed. Since your salespeople don’t need to input any data manually, errors won’t be an issue. In addition to time savings and fewer errors, automated reporting and forecasting can enable you to create new opportunities and revenue streams. ### Improve client communication Although customer interaction remains mostly personal, sales process automation can cover specific communication scenarios. This allows you to reach your audience immediately, no matter how many customers and little time you have. Email marketing is the perfect use case. You can set up your automation tool to send a predefined email when a specific event occurs. For example, clients can receive welcome emails upon subscribing, reminders when they leave products in the cart, and cross-selling suggestions for related products when they purchase. You can automate follow-up sequences and lead nurturing using more advanced and customer-specific triggers. Automation will also benefit other communication channels like SMS, messaging apps, or chatbots. ### Increase job satisfaction Maintaining high team morale is always essential. However, it’s even more central to success in customer-oriented jobs like sales since it can directly affect the relationship between your reps and clients. The bad news is nearly half of the salespeople feel lukewarm about their jobs, [rating their job satisfaction as “just good.”](https://salesinsightslab.com/sales-research/) A meager 17.6% call it “outstanding.” On the upside, those who spend at least 4 hours daily on sales-related duties report significantly higher fulfillment levels than those who devote more time to other tasks. And here’s where implementing sales process automation can also help, reducing the time needed to perform mundane work and freeing up sales teams to focus on more fulfilling tasks. Naturally, satisfied employees are also less likely to leave, which brings the added benefit of improved staff retention: all that increases productivity, happier clients, and better sales results. ### Sell more in less time Automating individual stages of the sales workflow already makes an impact, but to see the real difference, you must look at the whole cycle. Over time, you’ll notice that your sales specialists can now focus on contacting leads, selling, and closing deals. At the same time, processes that used to take days are now completed in hours. The combination of boosted productivity and efficiency will eventually accelerate your sales cycles, enabling your business to make more profit in less time. Fig. 01 · Sales 6 changes How automation changes sales - 01Less data entry - 02Accurate reports and forecasts - 03Qualified, prioritized leads - 04Shorter sales cycles - 05Better lead nurturing - 06Happier staff who stay Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Implementing sales process automation in 4 steps All that sounds great, but there’s much work before you reap the benefits of an automated sales cycle. Its implementation can be broken down into four key stages. ### #1. Quantify automation potential and prioritize opportunities The use cases listed above are common in sales, but each business is unique. That’s why there is no single implementation roadmap that works for everyone. For the same reason, the first step is to check what processes you should automate for the best results. Start by determining the complexity of each task in the sales process. Next, consider activities performed within each workflow and how much time they take. Then, factor in the impact of automating each task and how hard it will be to implement. In some cases, starting with lower-priority assignments may be worth it to test how automation will work for your business. Another critical factor is determining whether the task involves structured or unstructured data (or both). This stage is all about understanding your processes and the automation technology. To achieve this, assign a sales team member as an SME. Your SME will collaborate with an [automation consultant](https://www.flobotics.io/contact) to evaluate the feasibility of your implementation, set priorities, and develop metrics to measure the outcome. ### #2. Test prioritized use cases Once you know [which tasks you want to automate](https://www.flobotics.io/blog/what-processes-to-automate), it’s time to experiment. Deploying an automation pilot project will allow you to test and tweak the model before a large-scale launch. Think of the pilot as a trial or beta version of a fully automated process. Fig. 02 · Sales 10 tasks Top sales tasks to automate - Lead scoring - Customer profile creation - Follow-up emails - Scheduling meetings - CRM migration and updates - Data extraction and entry - Reports and forecasts - Simple customer service cases - Syncing data between tools - Lead enrichment The pilot usually doesn’t encompass the entire process but focuses on its critical stages. Its goal is to validate the automation project and prove its worth rather than bring instant results. Another reason is that small-scale deployments cost less and are faster to roll out, minimizing potential disruption. Lastly, the focused scope makes pinpointing and fixing any issues more accessible. Another good practice is measuring the pilot’s performance against the manual workflow to understand how much time automation can save you. Additionally, it’s a great way to dig into the process and spot any flaws before they are reproduced during implementation. ### #3. Choose the right technology One of the fundamental goals of the test phase is to try out various automation solutions in search of the one that will be the best fit for your business. What are the most common technologies used in sales process automation? #### Automation solutions: a quick overview ・Machine Learning (ML) — An AI-based solution capable of learning and improving performance on a task. It uses statistical algorithms and mathematical models to analyze data, discover patterns, and make predictions or decisions. ・Natural Language Processing/Generation (NLP) — A field of AI that focuses on enabling machines to understand and interpret human language to generate naturally-sounding texts. ・Smart Workflows — Automated workflows that use AI and ML to optimize business processes by identifying bottlenecks, optimizing resource allocation, and making real-time adjustments. ・Virtual Agents — Chatbots and voice assistants that use scripted rules and AI to communicate with humans in natural language, helping users find information or answer questions conversationally. ・Robotic Process Automation (RPA) — A technology that automates repetitive, rule-based, and manual tasks. It uses pre-programmed algorithms (“bots”) to perform tasks such as data entry, copying and pasting, and filling out forms, freeing humans to focus on higher-value tasks. While all automation solutions have their uses, RPA has some advantages that make it particularly useful in sales. It excels at handling data-heavy, repetitive tasks such as data entry, generating reports, or common communication scenarios. RPA is a tried and tested tool used in [various industries](https://www.flobotics.io/case-studies), including sales, for a long time. Due to its maturity, most major RPA platforms offer integrations with the most popular CRMs like Salesforce, Marketo, or HubSpot. For the same reason, automation companies already have the experience to manage a smooth [RPA implementation](https://www.flobotics.io/blog/rpa-development-process). Finally, RPA synergizes very well with the other solutions, making it a perfect stepping stone for future, more diverse automation projects. ### #4. Scale, improve, and plan ahead You’ve chosen the processes to automate, validated them, and found the best technology for the job. Now, you can start deploying full-scale automation of the selected tasks. Remember that the work doesn’t end once a process is automated. Continuous performance monitoring will enable you to improve the automated procedure and ensure timely maintenance. With the first automation deployment complete, the process starts anew: pick the following procedure to automate from the backlog and use your newly-gained experience to improve your sales operations further. ## RPA in sales: the success stories If you’re looking for inspiration, here are three real-life examples of [successful RPA implementations](https://www.flobotics.io/blog/rpa-failures) in sales. ### Cobmax: 50% less time spent on copy-paste For [Cobmax](https://www.ibm.com/case-studies/cobmax-sales-center/), a telecom, sales, and [customer service](https://www.flobotics.io/) provider from Sao Paulo, rapid growth meant new opportunities and a big challenge: it had 50 people working overtime, moving records between CRMs, and creating hundreds of new customer profiles. Unfortunately, despite their best effort, the overwhelming influx of clients led to delays and errors. The change for the better began in 2016 when Cobmax set out to deal with the endless copying and pasting with the use of IBM’s RPA platform. As a result, the company reduced back-office tasks by 50%. The success of this first initiative encouraged a wider RPA adoption: today, Cobmax trains its citizen devs and has a dedicated automation team that seeks new improvements. Fig. 03 · Case Cobmax Cobmax Sales Center: no more copy-paste GoalFree staff from overtime, moving records between CRMs and creating hundreds of profilesSolutionAutomated copy-and-paste with IBM's RPA platform 50%fewer back-office tasks ### Synergy: 99% billing errors out, courtesy of bots In the case of [Synergy](https://www.automationanywhere.com/resources/customer-stories/synergy-energy-provider), a leading Australian energy provider, the problem lay in handling transaction processes and excessive documentation spread across SAP ERP and other platforms. Tedious tasks cost the company precious time, while errors generate financial losses. To address these issues, Synergy decided to use Automation Anywhere RPA tools. As a result, over less than 15 months, the company managed to automate sales processes such as quoting, procurement, and reporting, achieving 163% ROI and 99% error reduction. Fig. 04 · Case Synergy Synergy: sales process automation GoalSave time on transactions and documentation across SAP ERP and other platformsSolutionAutomated quoting, procurement and reporting 163%ROI 99%fewer errors $2.3Mannual value ### Riyad Capital: 66% faster client onboarding [Riyad Capital](https://www.uipath.com/resources/automation-case-studies/riyad-capital-uses-rpa-to-save-time), an investment company based in Saudi Arabia, struggled to keep up with requests from new customers. Each client who wanted to open a new account required detailed data and identity verification, sharing documents with external institutions, and then notifying the customer of the outcome. These repeating task sequences were handed over to UiPath’s RPA bots, allowing Riyad Capital to reduce the processing time by 66% and save more than 20,000 working hours annually. While some validation still needs to be done manually, the company can now process twenty times more requests without errors, while its staff is free to spend more time on other tasks. Fig. 05 · Case Riyad Capital Riyad Capital: faster client onboarding GoalFaster delivery and more time for higher-value workSolutionAutomated two account-creation processes for a US broker platform 66%less processing time per item 20,000working hours saved 10×more capacity to grow volume 14×less manual intervention ## Bottom line It’s easy to see why sales and automation are a perfect match: efficient sales are the lifeblood of any business, and automation is all about efficiency. But to make that match work, you will need the help of expert automation developers and consultants who will guide you through all stages of the implementation. At Flobotics, we combine technical prowess with business understanding and experience in developing RPA solutions for sales to help our partners save time and resources. So if you want to join them and automate your sales processes, [contact our Flobotics team](https://www.flobotics.io/contact)! #### Like the article? Spread the word Written byFilip Nasiadko CEO and Co-founder at Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### SAP Automation Tools and You: Which One to Choose (And Why RPA Is Our Pick) SAP automation tools compared: strengths, weaknesses, and why RPA remains our top pick for optimizing SAP functions and workflows. Karl MielnickiJuly 11, 2023 ](https://www.flobotics.io/blog/sap-automation)[ AIEligibility ### Generative AI in Finance and Banking: What’s All the Buzz and Why You Should Care Generative AI in finance and banking: explore practical use cases, from fraud detection to reporting, transforming the sector in 2026. Michał RejmanJanuary 30, 2024 ](https://www.flobotics.io/blog/generative-ai-finance)[ RPAEligibility ### A Day Ahead, Not a Single Dollar Short: A Quick Guide to RPA in Payroll RPA in payroll: how automating manual payroll tasks boosts accuracy, speeds processing, and improves quality of life for HR and finance teams. Michał RejmanJuly 20, 2023 ](https://www.flobotics.io/blog/payroll-process-rpa) [All articles →](https://www.flobotics.io/blog) --- # Process Mining vs RPA: How They Work Together to Improve The Efficiency of Your Business Canonical: https://www.flobotics.io/blog/process-mining-automation Author: Bart Teodorczuk Published: 2023-01-30 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Process Mining vs RPA: How They Work Together to Improve… [RPA](https://www.flobotics.io/blog?category=rpa) # Process Mining vs RPA: How They Work Together to Improve The Efficiency of Your Business [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published January 30, 2023Updated September 1, 2026 On this page - [What’s Process Mining?](#whats-process-mining) - [How does Process Mining work?](#how-does-process-mining-work) - [Case ID](#case-id) - [Timestamp](#timestamp) - [Related activities](#related-activities) - [What are the benefits of Process Mining?](#what-are-the-benefits-of-process-mining) - [Optimized processes](#optimized-processes) - [Higher ROI](#higher-roi) - [Transparency](#transparency) - [Compliance](#compliance) - [Task monitoring](#task-monitoring) - [Automation enabler](#automation-enabler) - [RPA and process mining—what sets them apart?](#rpa-and-process-miningwhat-sets-them-apart) - [How can automation support Process Mining?](#how-can-automation-support-process-mining) - [Bottom line](#bottom-line) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) In our other articles, we’ve talked extensively about the benefits of Robotic Process Automation in [different industries](https://www.flobotics.io/case-studies). We’ve also covered the most popular automation tools to help businesses select the best fit for their needs. However, we’ve also noted that [41% of companies are still reluctant to adopt RPA due to the lack of clarity in their business processes](https://www.flobotics.io/blog/rpa-statistics). Their fears are understandable, as [RPA implementation](https://www.flobotics.io/blog/rpa-development-process) is a significant leap you can’t take without preparation. The same can be said about other major business decisions—you can’t just throw money at the problem and hope it will work. The difficulty lies in identifying the issue and then coming up with a solution. The good news is, the answer to this challenge is already here: it’s process mining. The solution is relatively new, but it’s expected to grow substantially in the years to come with an [almost 50% CAGR until 2029](https://www.fortunebusinessinsights.com/process-mining-software-market-104792). The potential for process mining to streamline discovery and decision-making is very much there. And the even better news is that the capabilities of process mining can be further enhanced with Robotic Process Automation. In this article, we’ll show you how the two can be used together for the best results. But first, let’s get you started with process mining, how it works, and what its benefits are. ## What’s Process Mining? At the basic level, process mining is exactly what it seems: mining for processes. Process mining goes through the event log data generated by the software systems used by your business (more on that later) to discover workflows that could use some improvement. That data is then visualized to facilitate decision-making. Advanced process mining systems can also suggest upgrades on their own. There are three main types (or applications) of process mining: - Discovery — The algorithm scans the available data in search of patterns that can be used to create new, efficient workflows. - Conformance — The aim of this process mining type is to check if the current processes are working as intended and find any deviations. - Enhancement — In this check, additional data (e.g., yielded from conformance analysis) helps identify potential improvements in the existing processes. Typically, all three types are used together to find, audit, and optimize workflows. ## How does Process Mining work? As we’ve mentioned earlier, process mining relies on event log data from other systems. Event logs are the digital footprints left after a piece of software processes data. These traces store information about past activities and their use is normally limited to error tracking. This means that each business that runs data-processing systems such as SAP, Oracle, Salesforce, Microsoft Dynamics, etc, has tons of data that is mostly just lying there, unused… … unless you do process mining. The three record attributes that are crucial for that are: ### Case ID A unique number is assigned to each event for easier identification. This can be an order number, client name, or any other identifier. ### Timestamp The time when the event was finished. With the event timestamps for all activities within a workflow in place, we can see how long each of them realistically took to complete. ### Related activities All activities are connected with the case ID. For an order number that could be the customer placing the order, you responding to it, or an invoice being sent. Based on these three data points (the so-called “data triple”) gathered from a statistically significant data sample, the process mining software creates a process graph. This visualization allows you to examine the workflow step-by-step and find inconsistencies, tasks that take too long or are outright redundant, bottlenecks, and other inefficiencies. Advanced process mining solutions can do even more. Some identify the root cause of the problem or monitor process performance 24/7. Others predict results for the set KPIs or give you instant, automated reports, and insights. ## What are the benefits of Process Mining? Before we go straight into listing the pros of process mining, let’s talk shortly about how businesses traditionally discover inefficiencies and areas for improvement. Gathering information about workflows is a part of [Business Process Management (BPM)](https://www.flobotics.io/blog/bpm-vs-rpa-the-difference-and-what-it-means-for-your-business). This is done mostly manually, through interviews, workshops, and process mapping that spans several days and requires the combined effort of members across different teams. It’s time- and work-intensive, and since so many people are involved, the findings can be a little skewed and not entirely objective. That said, this traditional method has its benefits: it engages various stakeholders and takes a qualitative approach. Process mining, on the other hand, relies on data rather than human effort. Process mining algorithms can crunch numbers and find patterns much faster than any team of experts. The number and size of data sets don’t matter—unlike humans, process mining systems don’t have to focus on a single point. Bias isn’t a factor, either, since the software draws its conclusions based solely on objective data. This comparison should give you a good idea of how useful process mining can be but its benefits go beyond that. Here are the key ones: Fig. 01 · Process mining 6 benefits How process mining helps your business - Better processesFinds inefficiencies and removes them. - Higher ROILower operating costs mean higher returns. - TransparencyA clearer view of how the business really works. - ComplianceChecks processes against industry rules. - Task monitoringTrack workflow performance and improve it when needed. - Automation planningShows what to automate and how. ### Optimized processes Process mining helps you find bottlenecks, errors, redundancies, and other inefficiencies and eliminate them to make your workflows simpler and drive better results. ### Higher ROI Similar to RPA, process mining helps businesses earn more not by increasing sales, but rather by lowering operational costs. ### Transparency Process mining gives you a better understanding of the inner workings of your business so you can act based on hard facts, not guesses and opinions. ### Compliance By gaining insight into your workflows, you can validate their compliance with the regulations specific to your industry. ### Task monitoring With process mining, you can constantly track the performance of your workflows and upgrade them when necessary. ### Automation enabler Automation is often the best answer to workflow inefficiencies. Process discovery allows you not only to find them but also to assess [what and how to automate.](https://www.flobotics.io/blog/what-processes-to-automate) Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## RPA and process mining—what sets them apart? If you’re familiar with [Robotic Process Automation](https://www.flobotics.io/), that last benefit of process mining should really speak to your imagination. Implementing RPA involves lots of planning, [consulting](https://www.flobotics.io/about-us), and brainstorming, and a tool like a process mining is an invaluable tool to facilitate the process. In fact, process mining often precedes automation initiatives—so often that it can lead some to believe that it is an integral element of RPA. But that’s only partially true. Sure, process mining and RPA are commonly used together but they are two independent solutions. Process mining is a discovery tool that can enable automation tools such as RPA. Due to that, it is often one of the first steps in RPA implementation that allows stakeholders to assess the scope of the project as well as determine which processes are worth automating. That said, process mining can also reveal other answers to operational challenges, like updating physical infrastructure, eliminating excessive tasks, or reorganizing supply chains. All in all, process mining is beneficial during RPA implementation but is also an independent tool on its own, and a few factors distinguish the two: Fig. 02 · RPA vs process mining Differences RPA and process mining: what sets them apart | RPA | Process mining | What it is | An automation tool that runs processes | A discovery tool that finds inefficiencies and improvements | How it works | Handles repetitive, labor-heavy, high-volume tasks | Uses event logs to map processes for analysis | Replaces | Manual, inefficient task work | Workshops and other manual discovery methods | How they connect | Often made possible by process mining | Shows which processes to automate | When | Implemented after process mining | Comes before RPA in automation projects | If you face Process Mining as an IT consultant, let us show you more about how you can benefit from [automation in consultancy.](https://www.flobotics.io/contact) Discover [SAP automation](https://www.flobotics.io/business-process-automation) with RPA and UiPath! And learn the differences between [RPA and Machine Learning.](https://www.flobotics.io/blog/robotic-process-automation-vs-machine-learning) ## How can automation support Process Mining? If you’re familiar with [Robotic Process Automation](https://www.flobotics.io/), that last benefit of process mining should really speak to your imagination. Implementing RPA involves lots of planning, [consulting](https://www.flobotics.io/about-us), and brainstorming, and a tool like a process mining is an invaluable tool. However, the relationship between RPA and process mining isn’t one-sided and the former can benefit from automation just as much, and in more than one way. Fig. 03 · Process mining 5 uses How automation is used in process mining - 01Data cleaning - 02Data collection - 03DTO generation - 04On-screen task capture and mapping - 05Analysis and insights - First, to bring the expected results, process mining needs data. Not just any data, though. Event records are often duplicated, incorrect, or incomplete. If the process mining algorithm is fed that low-quality data, there’s a good chance that its findings will be distorted and unreliable. However, scanning databases for errors and then correcting them manually would take too much time and effort. Here, RPA can be used to go through event logs in search of missing or mistaken data, no matter how large the sample is. Then, bots will use their data extraction and entry capabilities to fill the gaps and fix the errors to provide process mining systems with clean and complete records. - With machine vision, RPA can also enhance the three key attributes extracted from event logs. By recording the on-screen activity of workers responsible for particular steps of the workflow, Robotic Process Automation will provide you with additional context, e.g. what systems are used at each stage of that workflow. For instance, solutions such as [UiPath Task Capture](https://www.uipath.com/product/task-capture) can take screenshots for every mouse-click in the workflow and map it directly onto the process diagram. - Another compelling use of process mining automation is creating a [DTO — digital twin of an organization](https://www.gartner.com/en/documents/4004172). It’s an automated virtual model of an organization updated with new data that allows decision-makers to see how their business will react to changes and test potential upgrades before they’re implemented. For some companies, this method has already proven effective. Siemens, for example, used DTOs to evaluate and improve the digitalization potential for its order-to-cash processes. The implementation was validated and led to an [11% reduction in manual rework and a 25% increase in the automation rate](https://www.computerweekly.com/feature/Siemens-success-sets-the-scene-for-growth-in-process-mining) of said processes. - Next is the analysis of the workflow models generated by process mining tools. Typically, it would still be performed by human subject matter experts due to the business and technical knowledge required. However, thanks to natural language processing, machine learning, and sequence modeling, the most tedious parts of the analysis can be assigned to algorithms. Surely, as said technologies will continue to develop, so will their role in the analysis process. Some machine learning-based process mining solutions can already recommend the best course of action to optimize a specific task. One particularly intriguing use case for automation is identifying deviations from a standard process. Currently, more complex, multi-path workflow models still need to be analyzed by human experts who know the off-screen business context of each step. In the near future, however, this process can be expedited with the help of intelligent algorithms to correctly identify actual deviations at a much higher rate. ## Bottom line In today’s fast-paced world, it’s crucial to understand how the technologies businesses have at their disposal can mutually amplify their effect and work together for an even better outcome. Equally essential is the inside-out knowledge of the organization’s functioning, from single processes to sophisticated workflows. The connection between process mining and automation is a testimony to both these principles. If you want to find out if your business is ready to get started with Robotic Process Automation, you’re in the right place. [Reach out](https://www.flobotics.io/) and tell us about your plans, challenges, and processes. We’ll evaluate your workflows and create a [free proof-of-concept](https://www.flobotics.io/contact) so you can test our work before making any commitment. Then, we’ll guide you on your way toward RPA adoption. #### Like the article? Spread the word Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPAAI ### UiPath vs. Celonis vs. Kyp.ai: Comparing Top Task Mining Tools UiPath vs. Celonis vs. Kyp.ai: features and pricing compared to help you pick the right task mining tool for 2026. Bart TeodorczukNovember 20, 2023 ](https://www.flobotics.io/blog/uipath-vs-celonis-vs-kypai)[ RPA ### Unearthing RPA Potential: What You Need to Know About Task Mining & UiPath UiPath task mining, explained: see how its process-discovery tools help you find and prioritize the best tasks to automate. Bart TeodorczukJuly 28, 2023 ](https://www.flobotics.io/blog/task-mining-uipath)[ RPAAI ### Task Mining Tools Explained: Benefits, Use Cases and Leading Options Task mining tools introduced: an overview of UiPath, Celonis, and Kyp.ai to help you pick the right software for automation discovery. Bart TeodorczukNovember 20, 2023 ](https://www.flobotics.io/blog/task-mining-tools) [All articles →](https://www.flobotics.io/blog) --- # What Is Smart Process Automation and How Can Your Business Benefit From It? Canonical: https://www.flobotics.io/blog/smart-process-automation Author: Bart Teodorczuk Published: 2022-12-21 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/What Is Smart Process Automation and How Can Your Business… [RPA](https://www.flobotics.io/blog?category=rpa) # What Is Smart Process Automation and How Can Your Business Benefit From It? [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published December 21, 2022Updated September 1, 2026 On this page - [What is Smart Process Automation?](#what-is-smart-process-automation) - [Smart Process Automation vs Robotic Process Automation](#smart-process-automation-vs-robotic-process-automation) - [What are the benefits of SPA?](#what-are-the-benefits-of-spa) - [SPA: industries, processes, and technologies](#spa-industries-processes-and-technologies) - [UiPath](#uipath) - [Blue Prism](#blue-prism) - [Automation Anywhere](#automation-anywhere) - [WorkFusion](#workfusion) - [Power Automate](#power-automate) - [Bottom line](#bottom-line) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) According to Gartner, [the RPA software market grew 14.5% to reach $3.6 billion in 2024](https://www.gartner.com/en/documents/6842834), and will continue to grow. This impressive metric proves that businesses around the globe have been adopting [Robotic Process Automation (RPA) ](https://www.flobotics.io/blog/robotic-process-automation)to great effect. Reducing time spent on mundane tasks and increasing efficiency, this versatile automation technology has already found its use in [all major industries.](https://www.flobotics.io/blog/rpa-use-cases-across-industries) One of the main reasons why RPA has been so successful is its capability to [cope with routine tasks](https://www.flobotics.io/blog/bpm-vs-rpa-the-difference-and-what-it-means-for-your-business). Thanks to that, RPA allows businesses to push the boundaries of what they can achieve with automation. It is only logical then, that Robotic Process Automation itself would be improved in a similar fashion using new technological advancements, right? Discover more about [SAP automation](https://www.flobotics.io/blog/sap-automation) with RPA and UiPath. Enter SPA—Smart Process Automation (or Intelligent Process Automation), an RPA system taken to the next level. In this article, we’ll discuss what SPA is, how it is different from RPA, which industries can use it, and what’s in it for your business. Let’s get cracking! ## What is Smart Process Automation? Unlike RPA, which already has a well-established position in the market (to prove that, Deloitte reports that 53% of enterprises have already started their RPA journey), SPA is a relatively new concept. Let’s start by comparing it to RPA and listing the benefits it brings to all stakeholders. ## Smart Process Automation vs Robotic Process Automation By this point, you probably know what RPA is about: it’s an automation technology that uses pre-programmed scripts (bots) to handle repetitive, high-volume, and rule-based processes. It’s a highly effective solution, but what if it could be improved even further? That’s exactly what SPA sets out to do, taking RPA to another level by applying sophisticated machine intelligence techniques to task automation. A Smart Process Automation system makes use of cognitive technologies such as AI, ML (machine learning), and NLP (natural language processing) to better deal with semi-structured and unstructured data including document scans, emails, contracts, presentations, images, or even audio recordings. By ‘better’, we mean more innovatively. Where RPA takes a task and automates it, completing it in less time than a human would, SPA can also cooperate with people, make suggestions, and apply enhancements to workflows. The higher level of autonomy is one of the defining features of SPA, and its main advantage over traditional RPA. Robotic Process Automation works wonders when it’s delegated to a task that’s based on an if-then rule: if a condition occurs, a program then executes a pre-defined action. These are mostly simple but labor-intense processes such as data entry, records verification, or numerical operations. However, there are exceptions even in the most rudimental tasks, particularly if unstructured data is concerned. Process automation ROI calculator See what automating a process could save you in a few minutes. [Calculate ROI →](https://www.flobotics.io/roi-calculator) When an RPA bot stumbles upon one of these anomalies, it will usually notify the assigned employee/team (so-called “human in the loop”) to resolve the issue. What sets SPA apart from RPA is the ability to observe and learn how the exception is addressed to be able to handle it on its own in the future. This means that your employees won’t be interrupted by bots asking for assistance every time a specific anomaly issue occurs. Instead, the SPA algorithm will predict how a human would solve the exception and act accordingly. Speaking of predictions, the cognitive abilities of SPA will also come in handy for suggesting additional processes that would benefit from automation. Automation platforms like UiPath already offer AI solutions to [identify areas for improvement.](https://www.uipath.com/product/task-mining) And it’s not just the behavior of your staff that SPA can learn. By combining the customer-faced RPA processes with AI and ML, the bots will be able to predict customer behavior, create personalized offers, and improve interactions with clients. Last but not least, SPA creates a whole new world of possibilities for data analytics. Most processes optimized with RPA require bots to run through thousands of records—why not make use of all that data and have AI analyze it in real-time to generate market intelligence for your company? Fig. 01 · SPA What makes it smart What makes smart process automation smart What makes SPA smart? - 01Processing unstructured data - 02Cognitive abilities - 03Exception handling - 04Analytics - 05Better insights ## What are the benefits of SPA? As the next stage in the evolution of RPA, Smart Process Automation does everything its older sibling excels at, but better. And just like RPA, SPA adds value for everyone involved regardless of their role: - Business — From the perspective of the company as a whole, adopting a smart automation system will increase work effectiveness and accuracy while reducing time-to-action. Automation lowers operational expenses as well, with 61% of businesses reporting that their pre-implementation saving expectations were met or exceeded. Click here to read more about this in our article: [RPA statistics](https://www.flobotics.io/blog/rpa-statistics). - Employees — Manual, repetitive workloads feel more like a waste of time rather than a rewarding job. Launching RPA was the first step toward freeing your staff from these chores. The next one comes with SPA, which will give professionals even more time to focus on creative and fulfilling tasks that stimulate business growth now that bots can handle exceptions by themselves. - Customers — SPA can positively impact customer experience, both directly and indirectly. The immediate effect on CX is the better speed and quality of response thanks to optimized customer service workflows or chat and self-service enabled by automation. The indirect impact comes from the overall improvements to your business operations that will help you deliver your services or products more efficiently. Fig. 02 · SPA Who benefits Who benefits from smart process automation - Business - Money and time saved - Better accuracy and efficiency - Employees - Fewer boring tasks - More time for profitable work - Higher job satisfaction - Customers - Better customer experience - Higher service quality Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## SPA: industries, processes, and technologies Perhaps one of the most important advantages of RPA is its flexibility. Given proper implementation, it can be used to optimize a vast range of processes in virtually any industry. The same can be said about Smart Process Automation solutions. Since SPA is essentially RPA empowered by AI and ML, it too will find application in every sector, from healthcare to retail. Let’s take a look at some of the most popular use cases: - Healthcare — With tons of documentation (medical records, insurance claims, registration forms, etc.), back-office tasks, and human health at stake, healthcare is one of the industries that show the most potential for improvement with SPA. Processes such as medical billing and coding, [claims processing](https://www.flobotics.io/case-studies/70-faster-claim-turnaround-time-ctt-claim-management-automation), scheduling, referral management, or check-in all can be relayed to bots for greater efficiency and accuracy. Another good case for smart automation in healthcare is the fact that much of the data used in the industry comes in the unstructured form—think handwritten doctors’ notes or medical images. - Finance and banking — It shouldn’t be a surprise to anyone that financial services are another industry ripe with automation potential. It’s all about crunching numbers and thoroughly documenting all actions. Here SPA will help in reconciliation, fraud prevention, handling accounts receivable and payable, generating reports, forecasts, and analyses, as well as ensuring compliance. - Insurance — Here’s another sector that involves lots of unstructured data, like phone calls, emails, or handwritten documents that need additional context to make sense of. There isn’t much room for error in insurance either, which makes the robotic accuracy of SPA invaluable. Some of the most common insurance processes to automate include claims management, document processing, fraud detection, underwriting, policy management, and compliance. - Logistics — In logistics and supply chain management, every process in the workflow must be carefully coordinated to avoid delays. SPA can guarantee that everything goes according to the plan by optimizing inventory, scheduling, supply and demand planning, shipment tracking, and freight management. To top it off, predictive models can help businesses get the best deals possible with AI-powered vendor analysis and evaluation. - eCommerce — Online retail is no stranger to automation either. Here, bots will improve delivery and inventory management, support, payment processing, product categorization, and store planning. AI can also tap into large volumes of customer data to suggest loyalty programs and offerings tailored to specific client segments. - All industries — Some tasks are the foundation of any business activity, like invoicing, reporting, data operations (entry, extraction, and import), and customer service. Whatever industry your business is in, smart automation will make operations in these areas much faster and more precise. It’s also worth noting that SPA presents opportunities for process automation for small businesses that need additional workforce but can’t afford extra hires. Thanks to their learning abilities, SPA systems can become more autonomous over time, eliminating the need for recruiting new employees while still allowing companies to scale up. Finally, let’s talk about the availability of SPA. Despite the technology being younger than RPA, all leading automation platforms have been developing their smart solutions. ### UiPath UiPath stands at the forefront of smart automation. In addition to [the combination of AI, ML, and NLP](https://www.uipath.com/rpa/intelligent-process-automation), it offers [Computer Vision](https://www.uipath.com/product/ai-computer-vision-for-rpa), which allows bots to “see” on-screen and process on-screen actions. ### Blue Prism Blue Prism’s Intelligent Automation Platform is built around [six automation skills](https://www.blueprism.com/resources/videos/six-intelligent-automation-skills/): knowledge and insight, learning, visual perception, problem-solving, collaboration, and planning and sequencing. ### Automation Anywhere Automation Anywhere advertises its [smart automation platform](https://www.automationanywhere.com/rpa/intelligent-automation) as a process discovery tool and a bridge between front and back office operations. ### WorkFusion WorkFusion boasts custom and purpose-specific AI-powered [Digital Workers](https://www.workfusion.com/digital-workers/). ### Power Automate [AI Builder](https://powerautomate.microsoft.com/en-us/ai-builder/) puts ease of use first, allowing citizen devs to create their own simple AI models. ## Bottom line Knowing that running a business is a never-ending pursuit of improvement, companies around the world have been investing more and more resources into RPA. By harnessing the powers of cognitive technologies, Smart Process Automation is the next big step on the way to optimization that will allow businesses to save even more time, money, and effort. No matter if you’ve already implemented RPA or are just getting started with automation, you’re in the right place. At Flobotics, we have the knowledge and experience to help you make the transition to [smart process automation](https://www.flobotics.io/business-process-automation). ‍ ‍[Click here to talk with us](https://www.flobotics.io/contact) - we’ll gladly hear about your business and tell you how to bring it into the future. Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # RPA in Manufacturing - What Operational Processes Should You Automate Today? Canonical: https://www.flobotics.io/blog/rpa-in-manufacturing Author: Yana Pokora Published: 2022-11-29 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/RPA in Manufacturing - What Operational Processes Should… [RPA](https://www.flobotics.io/blog?category=rpa) # RPA in Manufacturing - What Operational Processes Should You Automate Today? [Yana PokoraContent Manager at Flobotics](https://www.flobotics.io/our-editorial-team#pokora) Published November 29, 2022Updated September 1, 2026 On this page - [The challenges in modern manufacturing](#the-challenges-in-modern-manufacturing) - [What processes to automate?](#what-processes-to-automate) - [RPA: Benefits for everyone](#rpa-benefits-for-everyone) - [The bottom line](#the-bottom-line) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Here’s a piece of linguistic trivia: did you know that the word “manufacturing” comes from the Latin for “making things by hand”? That’s a far cry from today’s reality — Latin has gone out of use a long time ago, and mass manual production will inevitably become a thing of the past, too. Modern factories are steadily becoming increasingly automated with time- and resource-efficient machines delegated to assembly line duties while human staff oversees the process. The industrial automation market is projected to grow at over 8% each year globally, and the number of industrial robots increases by 14% per year. But there’s more to manufacturing than just factory-floor tasks. Supply chain management, customer engagement, inventory planning, sales and order processing… These non-production workflows are just as critical for the business as the production itself. So, why not apply the same effective, automated approach to them? That’s where [Robotic Process Automation (RPA)](https://www.flobotics.io/blog/robotic-process-automation) steps in. In this blog post, we’ll investigate the main operational challenges in manufacturing, the industry-specific uses of RPA, and the benefits of implementing it for all stakeholders. All that to get you started on the road towards full automation of your manufacturing business. ## The challenges in modern manufacturing Recent years have been tough: supply chain disruptions, pandemic, great resignation, demographic shifts, and inflation have all taken a heavy toll on many industries, including manufacturing. At the same time, there are also the lifelong challenges of day-to-day operations that all businesses have to face. What are they? Staff shortages — 54% of manufacturers named hiring skilled employees as the top post-pandemic recruitment challenge. Still, it’s hardly the only one: other major hurdles include stiff competition for talent with other businesses or the industry’s negative image among younger potential hires. Supply chain inefficiencies — Between congestion issues, container shortages, increasing chain complexity, growing costs, and dependence on a single source for vital materials, global supply lines were already stretched thin before 2020. The system needed very little to collapse, and the pandemic was just the final straw. High operational costs — In the case of some business expenses, the figures have gone through the roof. Shipping costs have increased significantly in recent years, and partners are also affected, which makes them likely to charge more for parts and resources critical to your business. Efficient inventory management — Striking the balance between under and overstocking, shifting demand, tracking inconsistencies, limited visibility, and tons of paperwork—due to these factors, optimal inventory management is a never-ending effort. Supply chain disruptions don’t make it any easier, either. Ensuring customer satisfaction — 81% of industrial customers claim that a positive experience encourages another purchase. That number alone should make manufacturing executives realize that excellent customer service in the sector is no longer a nice bonus but a necessity. Increasing productivity — Manufacturing businesses that strive to remain competitive must make the most out of their potential. A significant part of this challenge lies in identifying improvements beyond pure production output: better planning, higher visibility, or removing siloed data. If all that sounds dire, the good news is that you can address all these difficulties with RPA implementation. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## What processes to automate? First, let’s make one thing clear: RPA is by no means a silver bullet for every single challenge troubling your business because no solution is. However, many problematic processes in manufacturing meet the criteria of a perfect automation candidate. Now, what exactly are the best tasks to automate with RPA in manufacturing? Supply chain management No surprises here — supply chain management involves a lot of smaller, consecutive, and repeating tasks which are easy to automate and can bring a quick ROI. One of the significant advantages of RPA-driven SCM is enhanced visibility. Shipments are tracked in real-time, and status updates are automatically sent across all supply chain links. Bill of materials A bill of materials (BOM) is a go-to reference document in manufacturing that lists all raw materials, assemblies, and parts needed to create the end product. RPA makes BOM generation simpler and more accurate, especially when combined with OCR. Inventory management A well-programmed RPA system can analyze storage data, predict demand, monitor inventory levels 24/7, and automatically trigger resupply. [Order processing](https://www.flobotics.io/case-studies/sugar-producer-automation) RPA assists with vendor selection, order handling, ERP updates, payment tracking, approvals, and invoice processing. Data operations Despite automation growth, engineers still spend a significant portion of their time retrieving data manually. RPA integrates with ERP, WMS, and CRM systems to automate data workflows. Customer service RPA enables self-service, automated responses, and faster issue resolution by pulling relevant data instantly. ## RPA: Benefits for everyone Manufacturers RPA reduces costs, eliminates errors, improves efficiency, and scales without additional hiring. Business partners Faster order processing, fewer errors, and improved reliability. Customers Better tracking, faster service, consistent availability, and improved support experience. ## The bottom line Precision, efficiency, and scalability — these three qualities define a successful manufacturer. RPA delivers all three. Are you still wondering if RPA will work for your manufacturing business? Drop us a line or schedule a call. 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byYana Pokora Content Manager at Flobotics. [More from Yana](https://www.flobotics.io/our-editorial-team#pokora) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### RPA Reloaded: 50+ Robotic Process Automation Statistics to Know in 2026 RPA statistics 2026: 50+ data points on robotic process automation adoption, ROI, and where the technology is headed next. Yana PokoraApril 15, 2025 ](https://www.flobotics.io/blog/rpa-statistics)[ RPA ### What Is RPA? | Robotic Process Automation Robotic Process Automation (RPA), explained: how software bots run a 24/7 digital workforce that cuts costs and human error. Bart TeodorczukSeptember 01, 2025 ](https://www.flobotics.io/blog/robotic-process-automation)[ RPA ### 15 Use Cases of RPA in the Energy Sector RPA in energy and utilities: 15 use cases showing how automation boosts compliance, efficiency, and innovation across the sector. Yana PokoraJune 24, 2024 ](https://www.flobotics.io/blog/use-cases-rpa-in-energy) [All articles →](https://www.flobotics.io/blog) --- # Bots You Can Bank On | What’s RPA for Finance and What’s in It for You? Canonical: https://www.flobotics.io/blog/rpa-for-finance Author: Filip Nasiadko Published: 2022-11-21 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Bots You Can Bank On | What’s RPA for Finance and What’s… CEO Notes [Eligibility](https://www.flobotics.io/blog?category=eligibility)[RPA](https://www.flobotics.io/blog?category=rpa) # Bots You Can Bank On | What’s RPA for Finance and What’s in It for You? [Filip NasiadkoCEO and Co-founder at Flobotics](https://www.flobotics.io/our-editorial-team#nasiadko) Published November 21, 2022Updated September 1, 2026 On this page - [Banking and finance - current challenges](#banking-and-finance-current-challenges) - [Unstructured data](#unstructured-data) - [Multiple application layers and legacy software](#multiple-application-layers-and-legacy-software) - [Implementing automation](#implementing-automation) - [Customer experience](#customer-experience) - [Regulatory compliance](#regulatory-compliance) - [Data security](#data-security) - [Recruitment and staff retention](#recruitment-and-staff-retention) - [Operational inefficiencies](#operational-inefficiencies) - [Best banking processes to automate](#best-banking-processes-to-automate) - [Data extraction and document processing](#data-extraction-and-document-processing) - [Compliance management](#compliance-management) - [Mortgage and loan processing](#mortgage-and-loan-processing) - [Customer-facing processes](#customer-facing-processes) - [Know your customer (KYC)](#know-your-customer-kyc) - [Anti-money laundering](#anti-money-laundering) - [Account closure](#account-closure) - [RPA for banking — the benefits](#rpa-for-banking-the-benefits) - [RPA in finance — use cases](#rpa-in-finance-use-cases) - [Paramount Residential Mortgage Group](#paramount-residential-mortgage-group) - [T-Bank](#t-bank) - [Conclusion](#conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) If there’s one heavily regulated industry, it’s finance and banking. The regulations are here for a good reason: to make sure that the flow of money is safe and effective. However, the need to follow these rules means that laissez-faire is not an option; instead, all tasks must be strictly defined and formulated into clear-cut processes. And where there are processes, there are automation opportunities. The banking industry is starting to recognize the potential automation holds: according to [Gartner](https://www.gartner.com/en/finance/insights/robotics-in-finance), 80% of finance leaders are planning to implement [RPA (Robotic Process Automation)](https://www.flobotics.io/blog/robotic-process-automation) or have already done that. Should you do the same? In this article, we’ll help you find the answer. We’ll discuss the most pressing challenges the finance sector is facing, cover the processes you can automate, and see what RPA for banking can give your business. As a bonus, we’ve thrown in a couple of RPA success stories from the banking industry. Learn more about using RPA in other industries, like insurance, logistics, real estate, or automation for consultancy. ## Banking and finance - current challenges The first step to understanding the benefits of [RPA for finance](https://www.flobotics.io/business-process-automation) is to take a look at the main pain points in the industry. Fig. 01 · Banking 8 challenges The main challenges in banking and finance - Large volumes of scattered, unstructured data - Regulatory compliance - Protecting data and assets from cybercrime - High employee turnover - Labor-intensive manual processes - Legacy systems and many application layers - Resistance to change - Demand for better, faster customer service ### Unstructured data Documents and records used in banking workflows are diverse and come both in a digital and paper format. Credit reports, emails, contracts, trade agreements, KYC documentation, forms… Verifying and extracting data from these documents takes a lot of time which could be spent on other tasks. ### Multiple application layers and legacy software ### Implementing automation This one may seem to go against the point of this article but let’s be honest: despite their high adoption rate and unquestionable usefulness of automated solutions, implementing most of them isn’t easy. And it gets even more difficult if you try to deploy a diverse range of attended, unattended, and hybrid models. ### Customer experience [Customer service](https://www.flobotics.io/business-process-automation), onboarding, and advising are crucial but time-consuming. Even though some stages of these workflows are simple and tedious, they are still usually performed by highly trained financial experts. Taking this burden off their shoulders would allow these professionals to put their time and skills to better use. ### Regulatory compliance Failing to comply with regulations such as CECL, SOC2, or SEC carries the risk of severe financial penalties. On average, [organizations lose $4 million in a single non-compliance event](https://www.globalscape.com/resources/whitepapers/data-protection-regulations-study). Even worse, such an event compromises your company’s reputation—and in banking, trust is everything. ### Data security Seeing how customer data is particularly sensitive in banking, its safety shouldn’t rely on human intuition or manual processes. In reality, it often does, which makes breaches and fraud more likely due to simple human errors. ### Recruitment and staff retention With society-wide phenomena such as quiet quitting or great resignation, finding qualified hires becomes a true challenge. It also means that retaining valued employees is even more important than before. ### Operational inefficiencies As we’ve mentioned above, many processes in banking are still performed manually. Tasks such as e-KYC mandate verification or manual loan initiation can take up to weeks and are prone to errors, so even a small improvement can go a long way. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Best banking processes to automate Now that we know the problems, let’s talk about solutions. What processes can you automate to address the challenges raised above? Fig. 02 · Banking 12 processes Which banking processes to automate - Data entry and extraction - Structured and unstructured data and documents - Customer screening - Loan processing - KYC (know your customer) - Customer onboarding and offboarding - Customer service - AML (anti-money laundering) - Customer and internal correspondence - Compliance monitoring - SAR generation - Reconciliation and reporting ### Data extraction and document processing In a perfect world, all documents required for banking processes would be standardized. In reality, only some of them, like customer IDs, spreadsheets, or user details are. Emails, invoices, transcripts, salary statements, registration certificates, and many more documents are semi-structured at best, which makes working with them much harder both for humans and machines. Technologies such as OCR (optical character recognition) or [UiPath’s Document Understanding](https://www.uipath.com/product/document-understanding) allow RPA bots to efficiently scan financial records regardless of the format. Then, the bots extract and validate the details relevant to a particular process, fast and without errors. ### Compliance management To ensure compliance, banks make use of internal and external data stored in various sources. With RPA, gathering this data becomes much faster and more cost-effective. RPA bots can also boost the safety of vulnerable data such as clients’ personal details with automated authorization and access permission granting. Any operations on this data are monitored and reported to prevent privacy policy violations. A major challenge in compliance management is following and adapting to the ever-changing regulations. Here RPA also provides a solution with regulatory monitoring and alerts sent when an update is announced. ### Mortgage and loan processing Loan processing is a long, multi-step process that includes employment verification, credit checks, or underwriting. No wonder [closing the process takes 45 to 60 days on average](https://themortgagereports.com/19487/how-long-does-it-take-to-close-a-mortgage-gina-pogol). RPA can dramatically reduce that time by automatically extracting client info from documents, preparing due diligence, assessing credit scores based on pre-established rules, or entering data. Thanks to that, your agents can process applications faster and with fewer errors. Some companies that implemented UiPath RPA report [agent productivity increases of even 70%](https://start.uipath.com/rs/995-XLT-886/images/Automate-Banking-white-paper.pdf). ### Customer-facing processes Customer-focused workflows involve huge volumes of data that need to be collected, verified, and entered. Couple that with account setup, customer service, and analytics, and you get hundreds of hours dedicated to repeatable, mundane tasks. RPA frees up your staff to work on tasks that are more interesting, develop their skills, or seek improvements and opportunities for their organization. When Blue Prism asked finance workers [what activities they could focus on if 50% of their current work was automated](https://cdn2.assets-servd.host/lively-jackal/production/uploads/resources/white-papers/Blue-Prism-Power-of-Three-report-0521-Exec-Series-1.pdf), 51% answered “use data analytics to uncover problems in processes.” 28% would try to “identify the next products and services customers will want to buy.” At the same time, customers enjoy faster and more accurate case resolutions. Lastly, RPA allows you to tap into your data and get clearer client insights. ### Know your customer (KYC) Since [banks spend over $384 million each year on KYC compliance](https://medium.com/@stenalferd/robotic-process-automation-in-banking-transformation-unseen-bf80232ec4e3), it makes sense that they would seek ways to increase efficiency and decrease spending. Automation is one such way. Faster data extraction, error-free verification, automated alerts, and case forwarding — all that allow banks to cut costs while improving security. To top it off, KYC automation solutions are relatively simple to implement and shouldn’t disrupt the existing systems, making them one of the best implementation candidates. ### Anti-money laundering RPA can assist your employees at multiple stages of the AML workflow. During onboarding, bots will automatically compile customer data, collect watchlists from third parties, and compare them to identify fraudsters. RPA will also monitor all transactions in real-time and alerts you when it detects any anomalies. All ambiguous tasks are relayed to your specialists for review. Another data-intensive task in AML is Suspicious Activity Reports (SAR) generation. RPA records all activity data and creates safety reports on demand. These can then be used for further risk assessment. Overall, the usage of RPA in AML processes can lead to [a 40% effort reduction](https://start.uipath.com/rs/995-XLT-886/images/Automate-Banking-white-paper.pdf). ### Account closure Inactive and non-compliant client records generate unnecessary costs and negatively impact business efficiency. To prevent that, banks must constantly check their clients’ account statuses and remove redundant records from all their systems. RPA empowers banks’ tracking capabilities, quickly identifying inactive accounts. The script can also be pre-programmed to automatically send notifications to remind clients to submit the documents required for compliance. ## RPA for banking — the benefits When implemented properly, automation has a positive effect on the entire organization. Some of the benefits of RPA in finance are: Fig. 03 · Finance 8 gains What a finance organization gains from RPA - Time and money savedBots do repetitive tasks faster, so fewer FTEs are needed. - Peak workloads handledBots absorb the heavy work at closing time. - Fewer errors, better complianceBots do not get tired or distracted; errors drop to near zero. - More value from dataPut large amounts of legacy data to use. - Happier employeesPeople focus on development and the work they trained for. - Better customer experienceFaster, more accurate service. - Better auditingAutomatic tracking gives more visibility into operations. - Painless implementationEasier to deploy than other automation; works with existing systems. - Time and money savings — RPA performs repetitive tasks faster and more efficiently than humans, reducing costs and FTEs necessary. - Fewer errors and better compliance — Bots don’t get tired or distracted, which brings the margin of error to near zero. - Higher employee satisfaction — With mundane chores taken care of, your employees can focus on self-development and tasks they were trained for. - Improved peak workloads — Robotic workforce helps finance companies navigate heavy closure-time workloads. - Better customer experience — Faster and more accurate service means satisfied customers. - Painless implementation — RPA systems are easier to deploy than other automation solutions and integrate smoothly with the existing systems. - Enhanced auditing — Automated tracking grants you a higher degree of visibility and insight into your operations. - Leveraging data — The processing capabilities of RPA give you the opportunity to grow and take advantage of bulks of legacy data. ## RPA in finance — use cases Many companies in the finance sector are already reaping the benefits of automation. Here are two of them that lead the way. ### Paramount Residential Mortgage Group For [PRMG](https://www.flobotics.io/case-studies), a mortgage bank from California, the challenge was to find a solution that would allow them to scale up the throughput and meet the sudden spike in demand. Using [UiPath’s RPA](https://www.uipath.com/resources/automation-case-studies/prmg) platform, automation experts from [Flobotics](https://www.flobotics.io/) facilitated the distribution of disclosure and closing packages, as well as the interoperability of PRMG’s systems. The results? 50% more underwrites per specialist each day, about 40 working hours saved daily, and $2 million saved each year. ### T-Bank Based in Texas, [T-Bank](https://www.flobotics.io/case-studies/t-bank-automation) needed a way to allow business owners to quickly apply for a COVID-19 relief funding program. Despite the application, and website being available only shortly, and even then constantly crashing, Flobotics’ RPA algorithm managed to make the signup process significantly faster by pulling data from a file and pasting it into loan forms. How much faster? Before the RPA was implemented, the whole process took 10-15 minutes. After that, it went down to just 6 seconds! ## Conclusion To overcome old and new challenges in a sector as dynamic as finance, adopting new solutions is a must. Banks and institutions are already doing that. Now it’s your turn to join them. To do so, you’ll need a [reliable partner](https://www.flobotics.io/about-us). You know all about banking, and we know all about automation — [reach out to us](https://www.flobotics.io/contact), and let’s team up to get your finance business started on its road to innovation through RPA. #### Like the article? Spread the word Written byFilip Nasiadko CEO and Co-founder at Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ Eligibility ### How Is Robotic Process Automation Disrupting the Banking and Finance Industry? RPA in banking and finance: top reasons automation and financial institutions work well together, with real use cases inside. Filip NasiadkoJanuary 15, 2021 ](https://www.flobotics.io/blog/rpa-in-finance-and-banking)[ AIEligibility ### Generative AI in Finance and Banking: What’s All the Buzz and Why You Should Care Generative AI in finance and banking: explore practical use cases, from fraud detection to reporting, transforming the sector in 2026. Michał RejmanJanuary 30, 2024 ](https://www.flobotics.io/blog/generative-ai-finance)[ Eligibility ### Payroll Process Improvement Ideas You Can Implement RPA in payroll: proven process-improvement ideas to cut manual work, reduce errors, and speed up your payroll cycle. Michał RejmanFebruary 07, 2022 ](https://www.flobotics.io/blog/rpa-payroll-process) [All articles →](https://www.flobotics.io/blog) --- # eCommerce Automation: How Is RPA Disrupting Online Retail? Canonical: https://www.flobotics.io/blog/ecommerce-automation Author: Filip Nasiadko Published: 2022-11-07 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/eCommerce Automation: How Is RPA Disrupting Online Retail? CEO Notes [RPA](https://www.flobotics.io/blog?category=rpa) # eCommerce Automation: How Is RPA Disrupting Online Retail? [Filip NasiadkoCEO and Co-founder at Flobotics](https://www.flobotics.io/our-editorial-team#nasiadko) Published November 07, 2022Updated September 1, 2026 On this page - [Why is eCommerce automation essential?](#why-is-ecommerce-automation-essential) - [Boosting efficiency and reducing costs](#boosting-efficiency-and-reducing-costs) - [Enhancing customer experience](#enhancing-customer-experience) - [Unlocking the power of data](#unlocking-the-power-of-data) - [What are the benefits of eCommerce automation with RPA?](#what-are-the-benefits-of-ecommerce-automation-with-rpa) - [For customers](#for-customers) - [For businesses](#for-businesses) - [RPA eCommerce automation — real-life examples](#rpa-ecommerce-automation-real-life-examples) - [Lotte — round-the-clock product monitoring](#lotte-round-the-clock-product-monitoring) - [E. & J. Gallo Winery — start small, go big with RPA](#e-j-gallo-winery-start-small-go-big-with-rpa) - [DCH — back-office on the front burner](#dch-back-office-on-the-front-burner) - [Ready for RPA in your eCommerce business?](#ready-for-rpa-in-your-ecommerce-business) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) More and more online retailers are turning to eCommerce automation, including Robotic Process Automation (RPA). Read on to learn what challenges RPA helps address, how to use it, and why embracing it will help your eCommerce business flourish. Learn more about using Robotic Process Automation in other industries, like RPA in insurance, logistics, real estate, retail, manufacturing or automation for consultancy. ## Why is eCommerce automation essential? There are [12-24 million eCommerce websites worldwide](https://www.similarweb.com/corp/blog/ecommerce/retail-insights/ecommerce-statistics/) in thousands of niches. But no matter what your company’s selling or where it’s based, some challenges are universal for all online businesses. The good news is that eCommerce automation can deal with some of the most challenging difficulties. ### Boosting efficiency and reducing costs With millions of eCommerce businesses, saying that the sector is competitive would be an understatement. High saturation means that all improvements are priceless since they can give you the leverage necessary to outdo other retailers in your niche. Another reason you may seek efficiency is to dampen the impact of growing production and distribution costs. When it comes to doing more for less, automation solutions like RPA are second to none. Here, the advantages of automation are threefold: - They increase the output, - eliminate workflow inefficiencies and errors, - and free up your staff. If all that sounds vague, that’s because automation can apply to various processes, from finance to stock management—don’t worry, we’ll talk about them in a bit! ### [Enhancing customer experience](https://www.flobotics.io/business-process-automation) According to a [report by Gorgias](https://www.gorgias.com/guides/cx-growth-playbook), shoppers who make multiple orders from one store constitute just 21% of a brand’s customer base on average. Yet, at the same time, these loyal customers account for a whopping 44% of the total revenue, showing how crucial it is to care for your clients. That’s easier said than done, but luckily, many customer-facing tasks can be optimized using automation. What’s more, automation may have an additional, indirect impact on your clients since it contributes to the overall better quality of your services. Double score! ### Unlocking the power of data Cart abandonment rate, bounce rate, conversion, customer lifetime value, average order value—modern eCommerce uses these and many other metrics to predict client behavior, evaluate current operations, and find improvements. But as your company scales up, so does the volume of data you need to consider. That’s where automation steps in. Crunching numbers is one of its major strengths, no matter how many spreadsheets and databases you throw at it. And, unlike human analysts, automated systems make no mistakes. Fig. 01 · eCommerce 3 gains How automation helps an online business - 01Higher efficiencyRPA bots take work off employees in every department, so they get more done. - 02Better customer experienceFaster operations mean better outcomes and happier customers. - 03Full use of your dataAutomation makes the most of large, complex data sets. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## What are the benefits of eCommerce automation with RPA? Now, “automation” is a broad term encompassing various solutions, including RPA. But what is RPA exactly? The name—Robotic Process Automation—says it all: it’s a bot-based automation solution customized to perform individual workflows. Pre-programmed RPA algorithms are perfect for repetitive, time-consuming, and data-heavy processes. Once implemented, they can run these tedious tasks precisely and without stops, allowing human employees to focus on tasks requiring creativity or expertise. RPA is especially fitting for eCommerce because its versatility allows use in [diverse processes.](https://www.flobotics.io/blog/what-processes-to-automate) Let’s discuss those that show the most potential for [RPA automation](https://www.flobotics.io/blog/rpa-development-process), both from the customer and business perspectives. Fig. 02 · eCommerce What to automate Which e-commerce processes to automate Customer-facing processes - Order tracking and status updatesDelivery updates shared with customers in real time - ReturnsRefunds and internal system updates handled by bots - Automated supportA chat or voice bot answers simple questions - Review managementReply to reviews, alert the team or save feedback for analysis - Loyalty programsSegment customers and send personalized loyalty messages Business processes - Stock tracking and reportingBots monitor inventory constantly - Payments and invoicesData extraction and entry automated - Product categorization and store planningAnalyze user data and build product mapping rules - Content updatesKeep thousands of product listings up to date - Day-to-day marketingRoutine emails, competitor research, SEO upkeep, reporting ### For customers Customers are now more conscious and demanding than ever, so ensuring exceptional shopping experience and support should be one of your top priorities. RPA makes it possible by optimizing a range of customer-oriented processes: - Order tracking and status updates — Following the order at every stage of its journey from your warehouse to the customer’s threshold have become the standard. On a larger scale, giving every customer this degree of visibility can become difficult or impossible if you manually do that. Bots can handle delivery status updates, sharing the current progress with your customers in near real-time. - Automated support — Nothing can replace the human touch in customer service, right? If the query’s answer is short and easy, an RPA chat or voice bot can do the job just fine. In addition, handling common, simple support cases such as questions about refund policy or delivery methods over to bots will spare your customers the wait and your human agents the hassle. - Review management — On average, [32% of shoppers read online reviews before](https://www.statista.com/statistics/1322099/online-reviews-use-household-products-shopping-by-country/) purchasing, making managing customer feedback a crucial part of an eCommerce business. RPA bots can distinguish positive and negative reviews using natural language processing (NLP) and react accordingly: send an automated response, notify your customer relations team, or save feedback for later analysis. - Returns processing — If there’s one thing worse than being disappointed with a purchase, it has to struggle with an inefficient return process afterward. RPA removes the friction, automatically informing the customer on the progress, updating the inventory, adjusting the money return, and then updating your internal systems. - Loyalty management — You may have attracted customers once, but the true challenge lies in making their return. Automation will break up your customer base into subgroups based on their order value or volume and then target them with personalized loyalty campaign messages. If you offer a loyalty points program, RPA can record all earned, reclaimed, or traded points and manage customer profile details. Process automation ROI calculator Answer a few questions and see what return you can expect from automating your process. [Start →](https://www.flobotics.io/roi-calculator) ### For businesses On the business side of things, RPA can assist all your departments. Here are some examples: - Stock tracking and reporting — As with order tracking on the customer side, you can program bots to monitor your inventory constantly. For example, they can immediately send automatic notifications when a supply runs low or even issue a purchase order to your vendor, so you will never run dry. - Payment and invoice processing — Invoicing and accounting tasks are largely based on data extraction and entry, which makes them one of the best processes to automate with RPA, [regardless of the industry](https://www.flobotics.io/blog/rpa-use-cases-across-industries). Collecting, compiling, and sending invoices, accounts payable, accounts receivable, and reconciliation—RPA can do that. - Product categorization and store planning — Sensible, well-structured product categories make your store faster to browse and your products easier to buy. RPA enhances product categorization by analyzing user-related data, assigning attributes, creating custom product mapping rules (based on, e.g., product name or image), and placing items exactly where your customers expect to find them. - Content creation — Your online store can offer thousands of products, each with a listing that must be regularly updated. Doing that manually means hiring dedicated full-time content managers and tons of mundane data entry. Or, you could let RPA handle that and have your specialists work on improving your SEO or social media content instead. - Day-to-day marketing tasks — The average day of a marketer is filled with dull-but-necessary chores that take their focus away from inventing new ways to attract and engage clients. Sending generic emails, competitive research, SEO maintenance, updating customer data, reporting… All these tasks can be automated to release the potential of your marketing specialists. ## RPA eCommerce automation — real-life examples 53% of companies that participated in an [RPA market report by Gartner](https://www.flobotics.io/blog/rpa-statistics) have already started their RPA implementation. It’s no different in eCommerce, where many retailers already leverage automation’s power. Let’s have a look at three online retail RPA success stories. ### Lotte — round-the-clock product monitoring For years, the eCommerce department of the South Korean conglomerate Lotte used to review thousands of its product listings manually. After the company switched to an [optical character recognition-based RPA system](https://www.uipath.com/resources/automation-case-studies/lotte-ecommerce-automation) developed by UiPath, the monitoring capacity has more than doubled. Bots run 24/7, allowing the review team to spend up to three hours each on higher-value tasks. ### E. & J. Gallo Winery — start small, go big with RPA A family business dating back to the 1930s, E. & J. Gallo Winery initially sought to apply RPA in the most standard way possible: [finance and accounting optimization](https://www.uipath.com/resources/automation-case-studies/ej-gallo-arep). Once the proof of concept passed the tests, the automation got underway in other departments. The wine producer and distributor currently boasts $500,000 saved thanks to RPA and a dedicated automation evangelist in 12 business departments. ### DCH — back-office on the front burner For Dah Chong Hong Holdings (DCH), a Hong Kong-based motor and consumer distributor, the top priority was to reduce the extra time its back-office staff spent on low-impact tasks. These included responding to customer emails, matching invoice data, or collecting and entering payment information. [With the help of RPA](https://www.automationanywhere.com/resources/customer-stories/dch-digital-transformation-with-rpa), the company saved over 10,000 working hours annually and is now planning further automation deployment. ## Ready for RPA in your eCommerce business? Lower operational costs, higher employee satisfaction, improved efficiency, greater precision, and, first and foremost, better customer outcome. We’ve shown you the benefits of RPA in eCommerce—now it’s your turn. Flobotics’ RPA developers and [consultants](https://www.flobotics.io/about-us) can help you make that first move toward automation with a free proof-of-concept project. It’ll give you a risk-free opportunity to see the benefits of Robotic Process [Automation in e-commerce](https://www.flobotics.io/business-process-automation). [Reach out to us](https://www.flobotics.io/contact), and let’s talk about your online business and how we can improve it through automation. #### Like the article? Spread the word Written byFilip Nasiadko CEO and Co-founder at Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # How RPA Is Changing the Logistics Industry and Supply Chain Management Canonical: https://www.flobotics.io/blog/rpa-logistics-supply-chain-management Author: Michał Rejman Published: 2022-10-18 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/How RPA Is Changing the Logistics Industry and Supply… [RPA](https://www.flobotics.io/blog?category=rpa) # How RPA Is Changing the Logistics Industry and Supply Chain Management [Michał RejmanChief Marketing Officer at Flobotics](https://www.flobotics.io/our-editorial-team#rejman) Published October 18, 2022Updated September 1, 2026 On this page - [What’s RPA, and how can it boost SCM operations?](#whats-rpa-and-how-can-it-boost-scm-operations) - [Supply chain management and logistics: automation candidates](#supply-chain-management-and-logistics-automation-candidates) - [RPA & supply chain — what are the benefits?](#rpa-supply-chain-what-are-the-benefits) - [Savings](#savings) - [Fewer errors](#fewer-errors) - [Happier employees](#happier-employees) - [Higher customer satisfaction](#higher-customer-satisfaction) - [RPA in logistics and SCM — examples](#rpa-in-logistics-and-scm-examples) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) What do semiconductors, building materials, aluminum, and plastics have in common? They all power the functioning of a whole gamut of sectors, from tech and construction to manufacturing and the food industry. But more significantly, they all continue to experience [a surge in demand, increasing prices.](https://www.supplychaindive.com/news/shortages-2022-outlook-supply-semiconductors-aluminum-food/617537/) Shortages are nothing new, and neither are the culprits: COVID-19 and the supply chain crisis (94% of Fortune 1000 companies are affected by supply chain disruptions). The two were a rude awakening for consumers worldwide as prices and shipping times started to soar and inventories—dwindle. At the same time, the demand for certain products and materials shows no signs of stopping, and the logistics industry has no choice but to adapt, optimizing its processes and cutting costs without cutting corners. One way to achieve that is by applying [Robotic Process Automation](https://www.flobotics.io/blog/robotic-process-automation) (RPA). Let’s see how it can be used in logistics and [SCM](https://www.flobotics.io/blog/rpa-use-cases-retail) to minimize disruptions, streamline operations, and decrease inventory costs. ## What’s RPA, and how can it boost SCM operations? Robotic Process Automation may sound daunting for those unfamiliar with AI-driven technologies. However, technical intricacies aside, its basic concept is easy to grasp. Regardless of the industry, most businesses involve repetitive processes based on rules, performed periodically, and involve large volumes of data. Due to their monotonous nature, they get time-consuming and tiresome if done by hand, making costly slips more likely. RPA enables optimizing these tasks by handing them over to pre-programmed algorithms (bots). They can work around the clock, don’t get tired or sick, and process bulk data in large volumes with speed, ease, and without errors. ### Supply chain management and logistics: automation candidates Since logistics involves many sequences of repeatable processes, it presents many opportunities for RPA optimization. Here are some of the best automation candidates in supply chain management: - Invoice processing — Invoice-related tasks are as essential as they are tedious. Finding, updating, entering vendor and customer details, attaching scans, requesting documents, processing payments, and submitting invoices can cost your company tons of time and frustration. Fortunately, all these phases of invoice processing can be easily automated, making it one of the best RPA use cases. - Vendor analysis and evaluation — Choosing vendors is a multi-stage process usually handled manually. RPA systems can assist you at each selection step—preparing quotation requests, scanning documents, and verifying supplier credit—and give you more time to focus on sealing the deal. - Inventory management — Keeping track of what’s in stock gets increasingly difficult as your company scales up and inventory becomes more diverse. RPA can streamline warehouse management by monitoring specific items’ condition, location, and quantity and notifying you when a product gets damaged, or its stock runs low. - Supply and demand planning — The ability to precisely predict shifts in supply and demand is one of the most fundamental factors in efficient supply chain management. However, achieving that depends on analyzing large data sets, often making the process overwhelming and prone to mistakes. With RPA, all records are automatically collected, compiled, and then analyzed based on preset rules—quickly and accurately. - Coordinating and scheduling — Even when shipping, resupplying, billing, maintenance, and other critical tasks are run flawlessly, they still need to be conformed to make the entire supply chain effective. RPA can serve as an intermediary between all your systems and partners, retrieving information from emails, replying to messages, filling in forms, or sending alerts to relevant stakeholders when a delay occurs to guarantee complete transparency. - Order management — Knowing your inventory is one thing; knowing and resupplying it is another. An RPA system can use the inventory data to initiate purchase orders based on predetermined criteria: the bot compares available vendors and prices, generates order documentation, submits the order for approval, and requests the necessary products—all that to minimize supply chain disruptions and sales lost due to missing goods. - Freight management — Once the stock is full, the next step is moving your shipments. RPA will help you match loads, handle freight claims and charges, and pick optimal routes. After the delivery is complete, analytics bots can assess the health of your supply chain and find potential improvements. - Shipment tracking and status updates — With so many moving parts involved in the SCM process, visibility is key. RPA will monitor the cargo at each stage of its journey and upload current data to your warehouse management system. - ERP integration — An ERP system is an indispensable tool in supply chain management, and RPA can take its capabilities even further. Automating data entry, migration, and validation reduces the risk of error virtually to zero, making the records your ERP relies on much more accurate. In addition, information is uploaded and moved significantly faster, with no manual typing (and typos) involved. - Customer service — Handling shipment status inquiries alone can be a busy job. With the help of RPA, you can keep your customers in the know thanks to up-to-date delivery statuses and automated troubleshooting. Regarding returns and after-sales services, many tasks that don’t require human intervention (such as ticket processing, data entry, or claim verification) can be relayed to bots, too. This list is incomplete, but RPA is not just about making single processes more effective but also about bigger-scale business impact. So let’s see why. If you’re looking for opportunities in logistics as a new industry for your IT consulting firm, find out more about [automation for consultancy.](https://www.flobotics.io/contact) We have also materials about RPA in manufacturing, [e-commerce](https://www.flobotics.io/blog/ecommerce-automation), [sales](https://www.flobotics.io/blog/sales-process-automation), [real estate](https://www.flobotics.io/blog/rpa-in-real-estate), and [insurance](https://www.flobotics.io/blog/rpa-in-insurance-use-cases). Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## RPA & supply chain — what are the benefits? The word ”chain” in logistics and SCM is used simply because its many processes resemble connected and interdependent links. That means that SCM thrives on economies of scale and that even small efficiency improvements can lead to massive increases in output across the board. So let’s zoom out and look at how optimizing individual SCM-related tasks can affect your business. Fig. 01 · Logistics 5 benefits Benefits of RPA in logistics - 01Better efficiency - 02Happier employees - 03Fewer errors - 04Lower operating costs - 05Happier customers Improved efficiency Efficiency is the backbone of all business. That’s particularly true in logistics, where even a small improvement can ripple effect on all subsequent processes. We’ve already come up with an extensive list of labor-intensive SCM tasks. Meanwhile, studies show that RPA systems can help reduce [effortful jobs by 80%.](https://www.flobotics.io/blog/rpa-statistics) Can you see the connection? Whether it’s load capturing, stock monitoring, reporting, or handling customer support, RPA can make the process faster, saving you hundreds of hours. ### Savings Higher productivity translates directly into lower operational costs. Although RPA implementation involves an investment, it usually brings a full ROI within months. After that, savings kick off since tasks are handled faster, current staff can be relegated to other duties, and you don’t need to make new hires. Automation can also drive lower costs by providing the information you need to make the right choice. For example, picking the best shipping rates, material prices, vendors, and third-party carriers generates savings, but the selection can be hard when data is scattered in various places. RPA can not only pull that data and present it as a digestible report but also suggest improvements by automatically analyzing the cost efficiency of your supply chain in real-time. ### Fewer errors The smooth functioning of a supply chain relies on data stored and moved between multiple systems: TMS, WMS, ERP, and CRM, not to mention spreadsheets and paper documents. If records from all these sources are processed manually, you have a recipe for errors. And in logistics, one mistake usually affects all other processes down the line, leading to delays and losses. This is where RPA comes to the rescue. You can easily integrate automation software into your existing systems to handle tedious work centered around endless entering, copying, and pasting. With properly set rules, bots will make virtually no mistakes and free up your staff to focus on more meaningful tasks… ### Happier employees … which will also positively affect their morale and job satisfaction. Skilled and experienced employees are the most valuable asset of any business. Why waste their time on tiresome chores rather than let them work where they can put their talents to the best use? RPA frees your workforce to contribute their potential to decision-making, innovation, negotiations, and expansion—tasks that drive growth for your organization and a sense of accomplishment for your employees. ### Higher customer satisfaction This comes naturally due to all other benefits: An efficient, error-free supply chain and satisfied employees contribute to an enhanced [customer experience](https://www.flobotics.io/blog/rpa-customerexperience). However, there’s a lot more you can do to cater to your clients with RPA. Think automated communication, delivery tracking, onboarding, or returns and refunds. To top that off, RPA-enabled analytics will help you leverage data to understand your customers better. RPA for supply chain becomes a necessity while thinking of [automation in e-commerce](https://www.flobotics.io/business-process-automation). ## RPA in logistics and SCM — examples Considering the wide range of benefits RPA systems bring, they have found uses in [companies from various industries](https://www.flobotics.io/blog/rpa-use-cases-across-industries), including supply chain and logistics. Numerous success stories reflect this. Let’s review some of them. DHL—optimized internal services with RPA DHL Global Forwarding, Freight (DGFF) is a leader in the freight-forwarding services industry, hiring over 4,500 employees across its five Global Service Centers. Seeking improvements to its internal processes, the company turned to UiPath, a leading RPA platform, to test the waters with a [pilot automation program](https://www.uipath.com/resources/automation-case-studies/dhl-global-forwarding-freight). The results were far better than expected: bots helped reassign the employees necessary for conducting the test process to more significant tasks, reducing the staffing in this area from 30 to 15 people, providing the workload of 300 FTEs, and bringing full ROI within just one month. Most importantly, the success of the pilot implementation convinced DHL executives to pursue broader RPA adoption. Fig. 02 · Case DHL DHL: a virtual delivery center GoalStreamline key internal processesSolutionA classic human delivery center complemented by a virtual one 50%less staffing needed 300 FTEsof work done by the bot network 100%ROI in month one 80UiPath robots deployed SF Supply Chain—10k automated orders per month SF Supply Chain offers SCM services to consumer goods enterprises based in mainland China, Macao, and Hong Kong. SF Supply Chain embraced RPA and streamlined [its data processing workflows](https://www.uipath.com/resources/automation-case-studies/rpa-improves-warehouse-efficiency-at-sf-supply-chain) to meet diverse customer requirements. The initial deployment was a success, with RPA bots managing over 10,000 orders monthly on a single site. As a result, the solution has been adopted on other sites, and the company now plans further RPA implementation in order printing, parcel collection, and scheduling. Fig. 03 · Case SF Supply Chain SF Supply Chain: courier data entry GoalBetter customer experience and keeping up with varied customer needsSolutionAn "innovative funnel model" where bots handle courier data entry 10,000orders a month handled by a bot 2 FTEsfreed from manual, repetitive tasks Posti Group—RPA-based digital transformation When Posti Group, a Finnish mail, parcel, and freight delivery provider, decided to [overhaul its internal legacy systems](https://www.uipath.com/resources/automation-case-studies/posti-group-logistics-rpa), implementing RPA was the first choice. With the help of UiPath, Posti first automated its voucher-posting process to get executives on board with a wider RPA automation. And it worked: RPA now aids multiple departments in the company, from finance and sales to HR and customer service. More successes followed, such as streamlining invoice verification or reducing invoice leakage. But perhaps the most significant one was radically improving employee experience, who now have more time for specialized tasks. Fig. 04 · Case Posti Group Posti Group: voucher posting GoalLead the marketSolutionAutomated voucher posting to win executive support for wider RPA 3×first-year target for streamlined invoice checks 5+departments now using RPA Ready to get started with RPA logistics today? You now know what SCM processes to automate with RPA, what’s in it for your business, and how other (prominent) companies use it to streamline their logistics operations. All you need now is one more thing: a reliable partner that will guide you through the [RPA in logistics and transport](https://www.flobotics.io/business-process-automation). We’re a team of experienced RPA developers and consultants with [dozens of successful automation launches](https://www.flobotics.io/case-studies) under our belt — and we’re ready for more. So get in touch and tell us about your SCM processes. We’ll prepare a free, custom automation Proof of Concept to show you how RPA can power up the logistics in your business! #### Like the article? Spread the word At Flobotics we specialize in U.S. healthcare revenue cycle management process automation – no generic bots here. Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byMichał Rejman Chief Marketing Officer at Flobotics. [More from Michał](https://www.flobotics.io/our-editorial-team#rejman) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### RPA Reloaded: 50+ Robotic Process Automation Statistics to Know in 2026 RPA statistics 2026: 50+ data points on robotic process automation adoption, ROI, and where the technology is headed next. Yana PokoraApril 15, 2025 ](https://www.flobotics.io/blog/rpa-statistics)[ RPA ### What Is RPA? | Robotic Process Automation Robotic Process Automation (RPA), explained: how software bots run a 24/7 digital workforce that cuts costs and human error. Bart TeodorczukSeptember 01, 2025 ](https://www.flobotics.io/blog/robotic-process-automation)[ RPAEligibility ### Top RPA Use Cases in the Insurance Industry RPA use cases in insurance: see how robotic process automation streamlines claims, underwriting, and other core workflows. Yana PokoraAugust 10, 2021 ](https://www.flobotics.io/blog/rpa-in-insurance-use-cases) [All articles →](https://www.flobotics.io/blog) --- # Keep Bookkeeping Easy – Why Should You Consider Automating Your Accounting Processes? Canonical: https://www.flobotics.io/blog/automating-accounting-processes Author: Filip Nasiadko Published: 2022-10-14 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Keep Bookkeeping Easy – Why Should You Consider Automating… CEO Notes [AI](https://www.flobotics.io/blog?category=ai)[RPA](https://www.flobotics.io/blog?category=rpa) # Keep Bookkeeping Easy – Why Should You Consider Automating Your Accounting Processes? [Filip NasiadkoCEO and Co-founder at Flobotics](https://www.flobotics.io/our-editorial-team#nasiadko) Published October 14, 2022Updated September 1, 2026 On this page - [The key challenges of accounting (RPA can solve)](#the-key-challenges-of-accounting-rpa-can-solve) - [What (and why) to automate?](#what-and-why-to-automate) - [Efficiency boost](#efficiency-boost) - [Error reduction](#error-reduction) - [Cost savings](#cost-savings) - [Smooth accounting with RPA](#smooth-accounting-with-rpa) - [RPA — use cases in accounting](#rpa-use-cases-in-accounting) - [Cohen & Company — faster and hands-free data processing](#cohen-company-faster-and-hands-free-data-processing) - [Xerox — invoicing made easy](#xerox-invoicing-made-easy) - [Automated accounting processes — your turn](#automated-accounting-processes-your-turn) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) It’s just another business day in your accounting office. You grab coffee, chit-chat in the kitchen, and get to business. The rest of the day flies by on repetitive tasks. Payments, invoices, bank statements, reports, and spreadsheets. A lot of spreadsheets. You trudge through that red tape, but what can you do? Statement by statement, digit by digit, you go through each file twice to make sure no error has crept into your books. Unless… Unless you use Robotic Process Automation (RPA) to make your accounting life easier, more pleasant, and more satisfying. As we will prove in this article, accounting, and finance processes are the [perfect candidates for RPA optimization](https://www.flobotics.io/blog/rpa-for-finance). So, if no other phrase makes you as excited as “automated accounting processes,” read on; otherwise, read anyway and learn why it should. ## The key challenges of accounting (RPA can solve) Many [accounting tasks](https://www.flobotics.io/business-process-automation) are considered tedious and straightforward. However, this simplicity can be misleading. Successfully managing all financial operations requires coordinating multiple jobs, including those listed below. Traditionally, they are performed manually or in a semi-automated fashion. RPA solutions remove many risks involved in their execution and improve their performance accuracy, efficiency, and speed. Fig. 01 · Accounting 9 challenges The biggest challenges in modern accounting - Keeping up with regulatory changes - Forecasts and financial predictions - Manual data entry - Paying suppliers - Reconciling bank statements - Writing useful reports - Tracking and requesting missing documents - Order and invoice processing - Risk assessment - Keeping up with regulatory changes — Ensuring compliance can be taxing between updates and revisions. - Developing forecast analyses — Predicting financial outcomes is essential in accounting, but it can involve massive data volumes that are difficult to process efficiently. - Manual data entry — Typing financial data manually seems unavoidable but increases the risk of errors and requires time. - Paying suppliers — Handling payments individually may be accurate, but it also slows you down, especially when suppliers need to be chased after. - Reporting — Compiling high-quality, insightful reports is another tedious-but-necessary job that is becoming increasingly difficult as requirements for speed, transparency, and insightful data grow. - Document retrieval — Tracking and requesting missing documents is a bottleneck that often hampers the progress of other processes. - Order and invoice processing — This is the bread and butter of accounting that sometimes may taste sour, especially when using an excess of accounting systems in standalone silos or trying to identify the missing details. - Risk assessment — No matter how strong your audit system is, some inconsistencies will always slip through the cracks, such as the lack of contextual understanding of the organization or function or missing ground rules for conducting the assessment. - Reconciling bank statements — Every accountant’s favorite jigsaw puzzle; is a regular chore that can take ages (and a lot of focus) if done manually and is extremely error-prone. ## What (and why) to automate? When asked about the [main benefits of manual process automation in the accounting industry](https://www.accountingtoday.com/news/rpa-on-the-rise-in-accounting), most of 2021’s Corporate Financial Reporting Insights conference participants answered: increased efficiency. And it’s easy to see why: when it comes to easy, repetitive tasks, a well-programmed algorithm will be capable of processing data faster and more accurately than a human accountant. ### Efficiency boost Here are some of the easily-automated accounting processes: - Extracting accounts payable and receivable data from sources in various formats, such as Excel, using optical character recognition (OCR). - By automatically assigning purchase orders to their respective invoices, the algorithm helps accountants save countless hours they would otherwise spend tracing charges. - As a sequence of repetitive tasks such as data input, calculating individual paychecks, or disbursement, payroll management is another easy pick for automation. ### Error reduction Accounting mostly deals with numbers, which has pros and cons: on the one hand, it’s logical, but on the other, any mistake will affect all other tasks down the pipeline. For this reason, error prevention was another advantage of automated accounting processes listed in the survey. - Manual data entry and sharing? Forget it—automated scripts will ensure that your financial records end up in the right place, error-free. In the meantime, you can focus on more sophisticated tasks. - Whether you need to validate checks or compare invoice data with account balance, automation turns reconciliation a breeze. - If you can’t help sweating about the looming tax season year by year, automation may take your worries away by taking care of tax updates, financial statements, or preparing tax returns. ### Cost savings Optimizing accounting processes wouldn’t feel right without generating some sweet cost savings, right? No worries - [a report by SSON](https://www.ssonetwork.com/finance-accounting/reports/how-to-turn-ap-into-a-value-and-profit-engine) shows that automation of accounting processes (accounts payable, to be more specific) can reduce the per-invoice cost by over 40% across various industries, from banking to tech. And that’s not the only way automation can be used to help spend less on bookkeeping: - Automating all error-susceptible processes like manual invoice processing will lead to lower spending. It’s simple: fewer costly errors and less money spent on corrections. - Financial forecasts depend on data—the more you can process, the more informed decisions you’ll make. So automate research and analysis-related tasks to drive results. Figuring out how to do more with less time and fewer resources usually isn’t easy, especially in mature organizations. Advanced automation solutions can independently audit your accounting processes and identify areas for improvement. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Smooth accounting with RPA Fig. 02 · Accounting 5 benefits Benefits of RPA in accounting - Fewer people neededHire fewer accountants and let bots handle the manual tasks. - Better securityAutomatic control over who can access sensitive data. - ComplianceFinancial records stay up to date with terms and regulations. - Faster serviceDeliver services faster with streamlined accounting. - Data governanceStore, share and manage data efficiently. Among all the different automation solutions, RPA stands out as the one that’s best suited for bookkeeping processes. About [80% of finance industry leaders](https://www.gartner.com/en/finance/insights/robotics-in-finance) either use or plan to implement it. Why is that? - Labor shortages — Experienced accountants are few and far between; new specialists take time and money to break in. So the answer may be to make more effective use of your workforce rather than recruit new bookkeepers. By implementing RPA, you allow your accountants to delegate mundane tasks to attended or unattended bots. As a result, they can run ceaselessly for as long as needed while your experts take care of the job that requires human input and expertise. - Compliance — According to a [NICE study on RPA benefits](https://www.flobotics.io/blog/rpa-statistics), 38% of managers name compliance as the main advantage of RPA. This shows how crucial adhering to the current regulations and contract terms is in finance. RPA bots are equipped with technologies such as NLP, allowing them to “read” documents such as agreements and purchase orders. Then, the algorithm extracts all details necessary to confirm (or invalidate) the compliance by comparing it with the organization’s base of financial records. - Data governance — From invoices to reports, accounting is all about data. Managing the flow and access to this data efficiently is crucial, but it’s estimated that [89% of companies struggle to achieve that](https://www.edq.com/resources/data-management-whitepapers/2019-global-data-management-research/). RPA platforms offer multiple ways to streamline data management: OCR, compatibility with external data sources and services, fast data updates, or schedules. However, remember that automation may require some governance (particularly at the implementation stage). Acknowledging that and setting the right goals and expectations is key to avoiding an [RPA failure](https://www.flobotics.io/blog/rpa-failures). - Security — An important part of data governance is ensuring its protection. Customer and partner details must be stored and entered securely and shared only with approved stakeholders. By preventing entry mistakes and automating authorization, RPA can greatly boost the data protection standards within your organization. As with all security systems, RPA is effective if you follow set [guidelines](https://www.flobotics.io/blog/8-security-practices-for-rpa-implementation). Safety first! - Service delivery — Growing your business isn’t just about making your internal processes more efficient and improving the quality of your services. It’s no secret that a happy customer will always return for more. Fewer delays and errors, higher turnover, [better customer service](https://www.flobotics.io/business-process-automation) - RPA gives you all that, resulting in a superior customer experience. In addition, the time you’d otherwise spend on menial accounting tasks can be devoted to research, strategy, and advancement, further increasing the quality of your services. ## RPA — use cases in accounting If you’re somehow not convinced yet, here are some real-life examples of businesses that stepped up their bookkeeping game thanks to automated accounting processes. ### Cohen & Company — faster and hands-free data processing Developing RPA for accounting firms is no mean feat. That’s why when a renowned accounting company asks you to help with its [bookkeeping workflow automation](https://www.flobotics.io/case-studies), you can be sure that the bar is pretty high. Luckily, the RPA system implemented by Flobotics’ [experienced developers](https://www.flobotics.io/blog/rpa-non-technical-developer) rose to the challenge. As a result, data creation, extraction, and input were automated, saving Cohen’s consultants hundreds of hours each month. ### Xerox — invoicing made easy When the printing industry giant set out to [reinvent its finance processes](https://www.uipath.com/resources/automation-case-studies/xerox-created-new-business-model-with-automation), RPA accounting was one of the first bets. With the help of UiPath, the adoption of automation among Xerox’s employees has increased. The company has also developed accounting-oriented applications for claims processing and deals automation, reducing the time spent on or replacing manual tasks. Check what more RPA can do for the [finance industry](https://www.flobotics.io/blog/rpa-for-finance) or [automation for consulting](https://www.flobotics.io/contact) firms. ## Automated accounting processes — your turn As we’ve found out, [RPA can streamline your finance and bookkeeping tasks,](https://www.flobotics.io/business-process-automation) ensure compliance and safety, improve data governance, and generate significant savings. But you’re not the only one to realize the potential of this technology. Companies from various sectors worldwide have already started adopting automated accounting processes. So it’s time to act. Your first step should be to find a reliable RPA partner with a proven track record in accounting automation. Then, schedule [a call](https://www.flobotics.io/contact) with one of Flobotics’ consultants and ask them about the free automation trial to try RPA for yourself. #### Like the article? Spread the word Written byFilip Nasiadko CEO and Co-founder at Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ AIEligibility ### Generative AI in Finance and Banking: What’s All the Buzz and Why You Should Care Generative AI in finance and banking: explore practical use cases, from fraud detection to reporting, transforming the sector in 2026. Michał RejmanJanuary 30, 2024 ](https://www.flobotics.io/blog/generative-ai-finance)[ Eligibility ### How Is Robotic Process Automation Disrupting the Banking and Finance Industry? RPA in banking and finance: top reasons automation and financial institutions work well together, with real use cases inside. Filip NasiadkoJanuary 15, 2021 ](https://www.flobotics.io/blog/rpa-in-finance-and-banking)[ RPAEligibility ### Bots You Can Bank On | What’s RPA for Finance and What’s in It for You? Finance process automation: how RPA helps banks and financial firms cut manual work in heavily regulated, data-intensive workflows. Filip NasiadkoNovember 21, 2022 ](https://www.flobotics.io/blog/rpa-for-finance) [All articles →](https://www.flobotics.io/blog) --- # RPA in Real Estate and Property Management: Benefits, Applications, and Use Cases Canonical: https://www.flobotics.io/blog/rpa-in-real-estate Author: Michał Rejman Published: 2022-09-26 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/RPA in Real Estate and Property Management: Benefits,… [RPA](https://www.flobotics.io/blog?category=rpa) # RPA in Real Estate and Property Management: Benefits, Applications, and Use Cases [Michał RejmanChief Marketing Officer at Flobotics](https://www.flobotics.io/our-editorial-team#rejman) Published September 26, 2022Updated September 1, 2026 On this page - [What is RPA?](#what-is-rpa) - [RPA in real estate — opportunities](#rpa-in-real-estate-opportunities) - [Bank and account reconciliation](#bank-and-account-reconciliation) - [Payment reminders](#payment-reminders) - [NAV calculations](#nav-calculations) - [Portfolio management](#portfolio-management) - [Maintenance management](#maintenance-management) - [AP/AR](#ap-ar) - [AML/KYC compliance](#aml-kyc-compliance) - [The benefits of RPA in real estate](#the-benefits-of-rpa-in-real-estate) - [Scale smoothly](#scale-smoothly) - [Improve customer experience](#improve-customer-experience) - [Ensure safety](#ensure-safety) - [Increase productivity](#increase-productivity) - [Avison Young — empowered real estate analytics.](#avison-young-empowered-real-estate-analytics) - [Colliers Romania — streamlined invoicing](#colliers-romania-streamlined-invoicing) - [Paramount Residential Mortgage Group — automated loan estimation and granting](#paramount-residential-mortgage-group-automated-loan-estimation-and-granting) - [Bottom line](#bottom-line) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Building a prosperous company in the real estate industry resembles building a house. First, you need solid foundations: people, resources, and funds. Without them, the entire structure slowly cracks and crumbles or completely collapses if things go south. With COVID-19 and current political and economic turbulence, the foundations of many real estate companies have become all but solid. The property industry is marred by issues such as: - inflation and economic slowdown, - supply chain inefficiencies, - political and regulatory uncertainty, - labor shortages, - declining consumer confidence. Despite these hardships, the real estate market growth forecasts project a steady [CAGR of 1.9%](https://www.imarcgroup.com/real-estate-market) in the next five years. This shows that the growth potential is still there for those willing to face these challenges. One way to lessen their impact is by maximizing the output while minimizing costs and effort through [Robotic Process Automation](https://www.flobotics.io/blog/robotic-process-automation) (RPA). If you’re unsure what RPA is and what processes in the real estate industry are good candidates for automation, read on. You will learn how RPA implementation can benefit your real estate business and see two examples of companies successfully launching automation projects. Learn more about using Robotic Process Automation in other industries, like insurance, logistics, e-commerce or consulting. ## What is RPA? Increased productivity is the holy grail for all businesses, regardless of size and industry. No wonder any reasonably priced tool that can lead even to a slight efficiency boost is in high demand. Enter RPA. It’s a scripted [automation](https://www.flobotics.io/rcm-automation) solution that excels at dealing with mundane, rule-based tasks. RPA platforms like UiPath are perfect for data-heavy workflows, and they scale well as more tasks are added to the pipeline. We’re not talking about a “slight efficiency boost” anymore here; if implemented correctly, RPA can handle many repetitive tasks independently and save businesses thousands of hours. It is no surprise then that recently, RPA has been finding use in [increasing sectors. ](https://www.flobotics.io/blog/rpa-use-cases-across-industries)In some, like healthcare and finance, it’s become a staple solution and an excellent driver for growth, with plenty of hard data to back this claim up. In healthcare, for instance, RPA is estimated to [help cut costs by up to half](https://www.forbesindia.com/article/weschool/robotic-automation-in-healthcare-can-help-cut-costs-by-50/68713/1). And in finance, a sector closely intertwined with real estate, Juniper projects a [60% year-to-year growth in automated investment until 2023](https://www.juniperresearch.com/press/robotic-process-automation-revenues-in-banking). At this point, you’re probably asking yourself, “If RPA worked there, would it work in real estate, too”? The short answer is ‘yes,’ but let’s see why that is the case. ## RPA in real estate — opportunities It is estimated that even [50% of RPA opportunities are missed](https://www.flobotics.io/blog/rpa-statistics). That’s because a successful RPA launch requires a clear vision and an inside-out understanding of an organization’s workflows. You can think of the first stage of an RPA implementation as recruitment. Ideally, you’re looking for a candidate that suits all your requirements. In the case of RPA, the perfect “hire” is a manual routine that’s time-consuming, repetitive, performed frequently, and involves heaps of data. Fortunately, in the real estate industry, there’s no lack of [processes](https://www.flobotics.io/blog/what-processes-to-automate) that check all these boxes, like: Fig. 01 · Real estate 8 processes What RPA can automate in real estate RPA in real estate - 01Bank and account reconciliation - 02Portfolio management - 03Tenant onboarding - 04AP/AR processes - 05Maintenance management - 06Payment reminders - 07AML/KYC compliance - 08NAV calculations Tenant onboarding Introducing each new tenant consists of several subtasks: creating an application, verifying the tenant’s income, employment, and criminal history, and finally, accepting or rejecting the applicant. Rules can be easily set for all of them, allowing RPA bots to extract and enter data and run the necessary checks. ### Bank and account reconciliation Reconciliation is another task focused on simple, repetitive activities such as extracting and comparing bank statements with your ledger. Again, why not spare your employees the effort and leave these tasks to pre-programmed scripts? ### Payment reminders In property management, there’s no escaping payment delays. But what you can do to reduce them is to automate reminders rather than tracking and verifying payments (or lack thereof) and then sending notices to tenants all by yourself. You can go even further and let bots handle other standardized communication, such as contract renewals or rent increases. ### NAV calculations The Net Asset Value is an essential indicator of ROI potential in CRE. Calculating NAV involves collecting, verifying, and processing market data—all these tasks are perfect candidates for automation. Bots will handle them faster and more efficiently than humans. Plus, they will leave no room for error. ### Portfolio management As you list more and more properties, following their statuses and values and then updating them on all your sites will quickly become a dull but necessary chore. Since portfolio management lies in data checks and entry, you can easily avoid the frustration by relaying it to an RPA bot. ### Maintenance management Here’s one more task that becomes nasty as the number of properties in your portfolio grows. Once again, RPA comes to the rescue, enabling automatic maintenance scheduling and requesting and utilities reporting. ### AP/AR Handling payments and invoices is tough enough as it is, so your accountants will greatly appreciate any help. And RPA is not just any help: bots can verify data, run forecasts, or pull payment details from invoices and upload them into your system. All that fast, error-free, and regardless of volume and format. ### AML/KYC compliance RPA algorithms are no strangers to compliance validation in other industries and work just as well in real estate. Just have them scan customer information for potential regulation breaches or extract customer information needed for other compliance assurance duties. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## The benefits of RPA in real estate Having all the above processes handled by an RPA bot sounds sweet, but you’re probably curious about what’s in it for you and your business. Here are some tangible benefits of Robotic Process Automation in real estate. Fig. 02 · Real estate 5 benefits Benefits of RPA in real estate - Lower costsTime savings and productivity cut operating costs. - GrowthGrow the portfolio without growing hiring. - AccuracyBots handle tedious tasks and stay sharp. - ProductivityStaff focus on customers, negotiations and high-impact projects. - Customer experienceFaster, better service with fewer errors. Cut operational costs Although automation systems require investment, the initial costs are bleak compared to the potential long-term savings generated by RPA. Property management and real estate involve high operational costs that can be significantly reduced thanks to time savings and a productivity boost. Note that the key to an RPA implementation that brings ROI is thorough planning and hiring the right people. ### Scale smoothly Growing your real estate company means more properties and more micromanagement. So you’ll soon face a tough choice: hire more staff or hold back on the expansion. RPA offers a third way, allowing you to scale up your portfolio without scaling up your recruitment. ### [Improve customer experience](https://www.flobotics.io/business-process-automation) RPA helps your real estate firm deliver its services faster, better, and with fewer errors. That’s why it’s hardly a shocker that RPA implementation makes your customers more satisfied—and more likely to return. It’s really that simple! ### Ensure safety Every time a human employee repeats the same boring sequence of actions, the risk of mistake looms larger and larger. Regulatory noncompliance or payment error can cost you dearly, and we don’t mean money but something much more valuable: the trust of your clients and partners. The answer? Hand over arduous tasks to the algorithm that never sleeps and always stays sharp. ### Increase productivity Even though it takes over some ‘human’ tasks, RPA isn’t here to replace your staff but to support them. With the jobs they hate to have to do now handled by bots, your employees are free to focus on customer outreach, negotiations, and high-impact projects. Process automation ROI calculator Answer a few questions and see what return you can expect from automating your process. [Start →](https://www.flobotics.io/roi-calculator) RPA in real estate — real-life examples With so much to gain, why hasn’t RPA become a standard tool in real estate yet? Well, “yet” is the keyword here. Even though the industry is somewhat slow in transformation, several top-tier organizations have already embraced the technology, showing the way for other businesses. Let’s see a couple of examples. ### Avison Young — empowered real estate analytics. Data-based decisions and predictions are crucial for driving profit and customer satisfaction in real estate. That’s why Avison Young, a Canadian real estate advisory firm, decided to turn to UiPath, a leading RPA provider, to help [boost the company’s analytical capacities](https://www.uipath.com/newsroom/avison-young-and-uipath-partner-to-drive-automation-real-estate-experiences). The partnership allowed Avison Young’s agents to automatically collect and upload minute property details such as transportation, air quality, ceiling height, bike, and walk scores quickly and accurately. Additionally, UiPath’s RPA platform integrated smoothly with the company’s existing systems and was used to automate other back-office jobs. The result? Less time spent working with data, higher value delivered to clients. ### Colliers Romania — streamlined invoicing The Romanian Department of Colliers manages more than half a million square meters of real estate space across the country and its capital, Bucharest. The company also offers property management consulting services. Given its impressive portfolio, Colliers needed to reduce the time spent on repetitive invoice services and digitalize their financial operations. Again, RPA seemed like an obvious choice. With the help of UiPath (which also comes from Romania), Colliers intends to [hand over at least 70% of invoice-related tasks to bots](https://www.colliers.com/en-ro/news/colliers-tests-the-first-real-estate-software-robot-based-on-uipath-technologies). ### Paramount Residential Mortgage Group — automated loan estimation and granting Traditional loan processing is riddled with errors on the borrowers’ and underwriters’ end. And their number increases directly to the volume of loan applications submitted. When you are a market leader licensed in 48 US states, like Paramount Residential Mortgage Group (PRMG), manual data handling becomes unmanageable at some point. Especially when experiencing record volumes of loans. That is why to streamline loan processing, unburden staff, and eliminate delays due to errors; the company expanded its team with five RPA bots built on UiPath. Together, they automated several key tasks, including retrieving and sending disclosure packaging, and data entry, transfer, and organization. And the results? Well, if [$2 million savings on improving daily operations efficiency](https://www.uipath.com/resources/automation-case-studies/prmg) or 40 hours of labor saved EACH DAY don’t convince you, nothing will. ## Bottom line Sure, real estate may lag behind [other industries ](https://www.flobotics.io/case-studies)regarding RPA adoption. Still, with all the manual, data-heavy, and repetitive processes involved, the sector holds huge potential for automation. Industry-leading companies have already noticed this opportunity and started to use it to their advantage. And you’re in the right place to join them. At Flobotics, automation is our second name. From consulting services to RPA development, we have everything to make your processes faster, more efficient, and more accurate. So reach [out to us](https://www.flobotics.io/contact), and let’s talk about how you can strengthen the foundations of your [real estate firm with RPA](https://www.flobotics.io/). #### Like the article? Spread the word Written byMichał Rejman Chief Marketing Officer at Flobotics. [More from Michał](https://www.flobotics.io/our-editorial-team#rejman) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### 15 Use Cases of RPA in the Energy Sector RPA in energy and utilities: 15 use cases showing how automation boosts compliance, efficiency, and innovation across the sector. Yana PokoraJune 24, 2024 ](https://www.flobotics.io/blog/use-cases-rpa-in-energy)[ Eligibility ### How Is Robotic Process Automation Disrupting the Banking and Finance Industry? RPA in banking and finance: top reasons automation and financial institutions work well together, with real use cases inside. Filip NasiadkoJanuary 15, 2021 ](https://www.flobotics.io/blog/rpa-in-finance-and-banking)[ RPAEligibility ### Top RPA Use Cases in the Insurance Industry RPA use cases in insurance: see how robotic process automation streamlines claims, underwriting, and other core workflows. Yana PokoraAugust 10, 2021 ](https://www.flobotics.io/blog/rpa-in-insurance-use-cases) [All articles →](https://www.flobotics.io/blog) --- # UiPath vs. Automation Anywhere: Choose Your Perfect RPA Tool Canonical: https://www.flobotics.io/blog/uipath-vs-aa Author: Bart Teodorczuk Published: 2022-09-07 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/UiPath vs. Automation Anywhere: Choose Your Perfect RPA Tool [RPA](https://www.flobotics.io/blog?category=rpa) # UiPath vs. Automation Anywhere: Choose Your Perfect RPA Tool [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published September 07, 2022Updated September 1, 2026 On this page - [UiPath — flexible and robust](#uipath-flexible-and-robust) - [Developer’s insight](#developers-insight) - [Automation Anywhere — scalable and secure](#automation-anywhere-scalable-and-secure) - [Developer’s insight](#developers-insight-2) - [UiPath vs. AA — head-to-head comparison](#uipath-vs-aa-head-to-head-comparison) - [Capabilities](#capabilities) - [Training and talent pool](#training-and-talent-pool) - [Ease of use](#ease-of-use) - [Pricing](#pricing) - [UiPath vs. AA — the verdict](#uipath-vs-aa-the-verdict) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) The year is 2019. Gartner has just released its first-ever Magic Quadrant for RPA Software to reveal who’s in the RPA industry. Two companies come out on top: UiPath and Automation Anywhere. Fast forward to 2023, and… little has changed. The only major difference for the duo is the widening gap between them and the RPA peloton. As a result, the two tools dominate the industry more than ever, at least according to [the newest edition of Gartner’s report.](https://rpamaster.com/2021-gartner-magic-quadrant-for-rpa-whats-new/) To say that their rule is indivisible would be an overstatement. There’s no shortage of competitors like [Power Automate](https://www.flobotics.io/blog/uipath-vs-powerautomate) who breathe down on their necks in the RPA race. Still, UiPath and Automation Anywhere remain unbeatable, and for some good reasons. So what are they, and which of the two is “better”? These are just the questions we’ll answer in this post. ## UiPath — flexible and robust UiPath is the pizza of the automation world—most people love it, and you can’t go wrong with it. The tool shares [over 25% of the RPA market](https://techcrunch.com/2021/04/02/rpa-market-surges-investors-vendors-capitalize-pandemic-tech-shift/), which makes it the most popular RPA vendor. The platform mainly targets bigger enterprises but is flexible enough to be used by small companies, too. UiPath owes this acclaim to its versatility, security, native integrations with dozens of applications, and ease of use in virtually any industry. All that wouldn’t be possible without powerful features, some of which include: - Orchestrator — Automation is all about coordination, especially as the number of processes increases. As an all-purpose RPA interface, [Orchestrator](https://www.uipath.com/product/orchestrator) is UiPath’s answer to the challenges of provisioning, managing, and monitoring your bots from a single control center. - Toolkit — UiPath has the right tool for all your RPA needs. Process recording? Boot [TaskCapture](https://www.uipath.com/product/task-capture). Automation opportunity discovery? [Automation Hub](https://www.uipath.com/product/automation-hub) is coming up. Issue fixing? [Test Suite](https://www.uipath.com/solutions/department/enterprise-test-suite) got you covered. - AI and cognitive features — UiPath leverages the power of AI and recognition technologies to facilitate everyday tasks. [For example, document Understanding](https://www.uipath.com/product/document-understanding) can interpret and extract text (invoices or hand-written receipts). [AI Computer Vision](https://www.uipath.com/product/ai-computer-vision-for-rpa) enables bots to recognize on-screen elements, which may be useful, for instance, fraud detection in finance or health monitoring and diagnostics enhancement in medicine). And [AI Center](https://www.uipath.com/product/rpa-ai-integration-with-ai-center) allows for a flawless deployment of AI and ML automation solutions. - Task Mining — This autonomous tool identifies and captures tasks fit for automation to streamline project workflows and unleash efficiencies. [Task Mining](https://www.uipath.com/product/task-mining) doesn’t come cheap, but in the longer term, it’s more than just helping you find room for savings. Fig. 01 · UiPath Strengths UiPath: main strengths - 01Easy automation management with Orchestrator - 02A complete, versatile toolkit - 03Proven ability to scale - 04Strong AI and cognitive features - 05Workflow aggregation and automation All that considered, it’s easy to see why UiPath is the best in RPA. And not just in terms of popularity; the Gartner above’s report and other influential studies from Everest Group and [Forrester](https://rpamaster.com/uipath-is-the-absolute-champion-in-the-forrester-wave-rpa-q1-2021-report/) unanimously name UiPath as the RPA leader. Discover [SAP Automation](https://www.flobotics.io/business-process-automation) with UiPath. ### Developer’s insight From the software development perspective, it’s also worth considering the following pros and cons when evaluating UiPath: Pros UiPath is not only based on C#, but it also allows developers to use the language to implement many features. Thus, for programmers familiar with C#, the platform makes their work streamlined, efficient, and much easier. Cons On the other hand, for developers with a background in classical programming only (frontend/backend), UiPath allows only a block-based view, which can sometimes get frustrating (as opposed to the list-based idea that provides more information useful when coding – see the developer’s pros for Automation Anywhere). ## Automation Anywhere — scalable and secure If UiPath is the pizza, Automation Anywhere is also pizza from another joint. So whether you get one or the other is frequently a matter of one’s subjective taste. Like UiPath, Automation Anywhere supports numerous integrations; it is secure and can be successfully used by organizations from [various sectors](https://www.flobotics.io/case-studies). It also comes with its own set of solid, Java-based functionalities. Additionally, modern and legacy systems compatibility allows Automation Anywhere to run on the existing software. Here are some of the other AA’s highlight features: - IQ Bot — This bot is just as intelligent as it sounds. It uses AI technologies to extract unstructured data from documents and process it, a task normally performed by human employees. As a result, IQ Bot can facilitate and speed up working with CVs, invoices, contracts, spreadsheets, emails, purchase orders, and other files. - Strong security standards — Automation Anywhere boasts high-security measures, such as multi-layer control, incident response, centralized credential vault, and stringent identity checks, all topped off with some of the highest security standards. Additionally, all communications are secured in transit via SSL and TLS. - Bot Store — Looking for a digital workforce to perform custom tasks? Bot Store is the right place. It’s an App Store for AA, full of free bots ready-made for working with specific applications and workflows. In addition, each bot comes with documentation and an installation guide for smooth implementation. - AARI digital assistant — AARI (short for Automation Anywhere Robotic Interface) is your digital assistant. Everyone’s assistant—AARI enables front- and back-office employees to discover and adopt established automated processes in their day-to-day workflows. Fig. 02 · Automation Anywhere Strengths Automation Anywhere: main strengths - 01Efficient document processing - 02Robust, certified security - 03Hundreds of ready-made bots - 04Strong AI and cognitive features - 05Easy to start, intuitive UI Thanks to these features, Automation Anywhere is considered a close runner-up for the title of the best RPA vendor. ### Developer’s insight Pros From the development’s standpoint, the list view is one big advantage of Automation Anywhere. It shows activities in a code-like arrangement, one by one, enabling programmers to see more of them at once. This feels more intuitive and organized for most developers, which facilitates work. Cons Even though AA is trying to be an entity of its own and somewhat of a programming language, it still lacks many features essential for developers that would make it so. For example, it doesn’t include an option to sort a list of elements or find the min/max item, which are basic features in object-oriented programming. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## UiPath vs. AA — head-to-head comparison Ratings and rankings look great on paper, but the top-down image is not enough when the competition gets tight. So let’s take UiPath and Automation Anywhere apart to compare them part by part. ### Capabilities Hands down, UiPath and Automation Anywhere have the best offering of all RPA vendors, and the differences between them lie in details. Regarding cognitive functions, UiPath knocks the ball out of the park. It leverages the power of AI, OCR, ML, NLP, and other technologies [throughout the automation cycle](https://www.flobotics.io/blog/rpa-development-process). Scheduling, integrations, debugging, analysis, and discovery—UiPath has it. There’s deployment flexibility, too, with both on-premise and cloud options. Automation Anywhere has counterparts for many of UiPath’s features, but they aren’t as efficient. However, one thing that makes Automation Anywhere shine is its ease of scalability. AA dynamically adjusts bot capacity to the current needs and has excellent script reuse functionalities. Still, remember that Automation Anywhere is not capable of working with on-premise deployments. ### Training and talent pool Automation reduces human effort, but it needs to be implemented by the right people. Thus, one of the crucial factors when choosing the solution vendor is the RPA Developers’ availability. UiPath goes the extra mile to ensure no shortage of experienced devs with its platform. Between free Community Edition, UiPath Academy, and certifications, finding and hiring UiPath developers is easy[.](https://www.flobotics.io/about-us) Automation Anywhere University and instructor-led classes give budding devs an excellent opportunity to become AA-savvy. Still, the platform is bound to have fewer developers available simply due to being only the second-most popular RPA tool. ### Ease of use No matter how powerful the tool is, it won’t succeed if you fail to get your employees on board. And that’s so much easier if the solution is intuitive and easy to use. The number of work non-programmers need to put into getting started with UiPath and AA is comparable. As UiPath is built around a visual, drag-and-drop interface, it may initially seem easier to use—choose a process, put its steps on your visual workspace, hook them up together with pre-defined connectors, et voila - you’ve just [automated your workflow](https://www.flobotics.io/blog/what-processes-to-automate). However, it also relies on C#, and in most cases, it will ultimately require some understanding of the language’s basics. On the other hand, AA is making efforts to improve its accessibility for [non-technical users](https://www.flobotics.io/blog/rpa-non-technical-developer), but it is organized in a more code-like manner. All in all, both platforms require similar effort on the part of citizen developers. ### Pricing Last but not least, let’s talk about money. As the top dogs of the RPA industry that offer the best automation solutions, both vendors can afford to put a high price tag on their services. The most basic UiPath business plan comes at $420 per month. Remember that the price can vary if you opt for additional features like Task Mining. Unfortunately, AA doesn’t openly disclose its price. Some [press releases](https://www.automationanywhere.com/company/press-room/rpa-cloud-packages-for-business-continuity) mention plans starting at $750 with extra payments for other users. This lack of pricing clarity means Automation Anywhere and UiPath draw in this round. In the end, the cost will come down to your needs. The best thing to do is find experienced [RPA consultants](https://www.flobotics.io/about-us) who’ll help you assess the scale and price of the implementation. ## UiPath vs. AA — the verdict So, to wrap up, which one should you go for? UiPath or Automation Anywhere? And the answer is… take the one that better matches your needs. Choose UiPath if: - You’re planning a large-scale, long-term automation adoption. - Your organization is looking for a versatile, multi-purpose RPA tool, regardless of the company size. - You’re interested in using some of UiPath’s advanced features. To sum up, UiPath is regarded as the GOAT of RPA for many reasons, from accessibility and flexibility to powerful capabilities and integrations. Go for Automation Anywhere if: - You’re automating less sophisticated workflows. - Scalability is the top priority of your enterprise. AA comes second, yet it is better than UiPath in some respects. However, you need to consider if these few benefits of Automation Anywhere are worth the overall lower potential for a similar (or higher) price. Fig. 03 · UiPath vs AA Verdict UiPath vs Automation Anywhere | UiPath | Automation Anywhere | Features | Powerful | Solid | Training and talent | Bigger talent pool | Decent developer availability | Pricing | High costs that rise with advanced features | Comparable or possibly higher | Ease of use | Little programming needed | A coding background helps day to day | Deployment | Cloud and on-premises | Cloud only | Scalability | High | Excellent | Bottom line Our UiPath vs. AA showdown is over. It was a close one, but UiPath emerged as the winner in the end. That’s why Flobotics [uses UiPath as our primary RPA tool](https://www.flobotics.io/uipath-services) while still giving the green light to Automation Anywhere and other RPA tools like [Python](https://www.flobotics.io/blog/automation-python) if we deem a project will be better off with them. Selecting the right platform is the key to automating [your processes](https://www.flobotics.io/rcm-automation) in any industry, e.g., [finance ](https://www.flobotics.io/blog/rpa-for-finance)and [banking](https://www.flobotics.io/business-process-automation). Still not sure which one to pick? Tell us about your organization, and we’ll suggest the best tool. #### Like the article? Spread the word At Flobotics we specialize in business process automation – no generic bots here. Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### UiPath vs. Power Automate - Which RPA Tool To Choose? UiPath vs. Power Automate: compare features and pricing to decide which RPA tool best fits your 2026 process automation needs. Bart TeodorczukJune 27, 2022 ](https://www.flobotics.io/blog/uipath-vs-powerautomate)[ RPAAI ### UiPath vs. Celonis vs. Kyp.ai: Comparing Top Task Mining Tools UiPath vs. Celonis vs. Kyp.ai: features and pricing compared to help you pick the right task mining tool for 2026. Bart TeodorczukNovember 20, 2023 ](https://www.flobotics.io/blog/uipath-vs-celonis-vs-kypai)[ RPA ### UiPath vs. Python? Choosing the Right RPA Tool for Your Automation Job UiPath vs. Python: compare strengths, use cases, and when to choose code over low-code for your next automation project. Krzysztof SzwedDecember 11, 2023 ](https://www.flobotics.io/blog/uipath-python) [All articles →](https://www.flobotics.io/blog) --- # Blue Prism or UiPath? Choosing the Best RPA Tool for Your Business Canonical: https://www.flobotics.io/blog/blueprism-vs-uipath Author: Bart Teodorczuk Published: 2022-08-22 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Blue Prism or UiPath? Choosing the Best RPA Tool for Your… [RPA](https://www.flobotics.io/blog?category=rpa) # Blue Prism or UiPath? Choosing the Best RPA Tool for Your Business [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published August 22, 2022Updated September 1, 2026 On this page - [UiPath: overview](#uipath-overview) - [Process Mining](#process-mining) - [Community](#community) - [Task Capture](#task-capture) - [UiPath—disadvantages](#uipathdisadvantages) - [Blue Prism: overview](#blue-prism-overview) - [Enterprise focus](#enterprise-focus) - [All-in-one platform](#all-in-one-platform) - [Debugging tools](#debugging-tools) - [Blue Prism—disadvantages](#blue-prismdisadvantages) - [Blue Prism or UiPath: which one’s better?](#blue-prism-or-uipath-which-ones-better) - [The tech perspective](#the-tech-perspective) - [The business perspective](#the-business-perspective) - [The verdict](#the-verdict) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) The promise of handling [manual and repetitive but essential tasks](https://www.flobotics.io/blog/what-processes-to-automate) speak to the imagination, convincing more and more organizations to hire RPA developers. To no one’s surprise, massive demand has led to the industry’s rapid growth, [projected at over 38% per year](https://www.grandviewresearch.com/industry-analysis/robotic-process-automation-rpa-market), and to the emergence of new tools. Blue Prism, Automation Anywhere, [UiPath,](https://www.flobotics.io/blog/uipath-vs-powerautomate) [Power Automate](https://www.flobotics.io/blog/uipath-vs-powerautomate)… These are just three of dozens of major RPA platforms out there. And that’s a good thing—competition spurs improvement, forcing each RPA provider to go the extra mile with their product. All that sounds great, but there’s one major headache: with so many different RPA vendors, which one should you choose? Today, we’ll investigate UiPath and Blue Prism, two leading RPA solutions. We’ll go through their respective strengths and weaknesses and see how they fare from the perspective of businesspeople and tech folks. The goal is to answer the ultimate question: should you choose Blue Prism or UiPath? ## UiPath: overview [UiPath](https://www.uipath.com/) is an RPA tool from a Romanian company specializing in process automation. The first version of the platform launched in 2013, and since then, the tool has occupied the top position in the RPA market. Designed to automate manual and repetitive back-office tasks, UiPath offers users access to pre-built automation components that can be leveraged and enhanced to streamline routine processes. Agile, modern, and user-oriented, it is especially popular with business users (it ranks #1 in [Gartner’s RPA Peer Insights](https://www.gartner.com/reviews/market/robotic-process-automation-software) ratings). Discover [SAP automation](https://www.flobotics.io/business-process-automation) with UiPath. By now, the platform has expanded into a broad ecosystem of products and services that span low-code application development software, AI orchestration, document management automation, chatbot builder, and many other useful tools. Over the years, UiPath has built a name for itself and garnered a large and active user community. There are a couple of reasons for that: Fig. 01 · UiPath Pros and cons UiPath: pros and cons Pros - Automation HubA panel for planning RPA work and prioritizing automation tasks - Process miningFinds automation opportunities in your processes - CommunitySpecialists learn from each other, and companies find good developers - Task CaptureDocuments your business processes Cons - PriceExtra modules cost more Automation Hub You may have dozens of automation ideas from various people within your organization. That’s a good thing, but it all can start going downhill if you don’t prioritize and control how these ideas are implemented. Designed to serve as a cornerstone of all automation pipelines, [Automation Hub](https://www.uipath.com/product/automation-hub) was created to prevent that. It’s a tracking and management panel that allows you to take the front seat during RPA implementation and prioritize opportunities and [ongoing automation tasks](https://www.flobotics.io/blog/rpa-development-process). ### Process Mining While some companies struggle with catching up with the plethora of automation ideas, others have difficulty identifying them. [Process Mining](https://www.uipath.com/product/process-mining) helps you discover automation opportunities by looking into current processes and turning that knowledge into improvement insights. But it doesn’t stop there—once a process is optimized, Process Mining monitors it to see how impactful the automation was. ### Community Everyone loves good tools, especially when they can handle your most mundane tasks! UiPath has thousands of devoted and involved users thanks to its popularity and quality. As a result, there’s always someone to ask for help, and it’s easier to [hire UiPath developers](https://www.flobotics.io/uipath-services) than specialists proficient with other RPA platforms. The company realizes that its user base is a massive asset and puts a lot of effort into engaging with customers through its [community](https://community.uipath.com/). Hence, the community forum, free, time-limited Community license, regular updates, self-learning resources, and insider previews show that UiPath gets its users. ### Task Capture Process documentation is just as crucial as it is difficult—and boring—to create. It needs to be consistent, understandable, and not too detailed to serve its purpose. [Task Capture](https://www.uipath.com/product/task-capture) allows you to easily create and edit workflow diagrams or record the entire process step-by-step. You can then save documentation in one of many formats available or upload it directly to Automation Hub. Neat!UiPath—disadvantages ### UiPath—disadvantages The perfect RPA tool doesn’t exist, and even though UiPath gets pretty close to it, it has one significant disadvantage: pricing. The initial license price is beautiful but does not include all modules. As a result, the costs can quickly increase if you decide to get them all. To reach ROI, smaller companies may need to be more careful about extra functionalities or [hire RPA consultants](https://www.flobotics.io/contact) to help them choose the most beneficial ones. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Blue Prism: overview Founded in 2001 in Great Britain, [Blue Prism](https://www.blueprism.com/) is the oldest RPA tool on the market and a de facto pioneer in automating large, complex business processes. Coming from a corporate background, it is more enterprise-focused than its contestant and strongly embedded in the concept of supplying the digital workforce to businesses. BluePrism supports any platform, including Java, web, and Windows, and can automate virtually any task and application. With over 20 years in the automation industry, the company constantly leverages its experience to improve its mature and widely used platform. One of its biggest assets is high reliability and scalability, essential for a tool commonly used in an enterprise setting. It is also worth noting that Blue Prism can be deployed in any environment (including staging and testing). Let’s see what else makes it an RPA tool of choice for brands like EY, Accenture, Microsoft, IBM, Google, Jaguar, Siemens, and hundreds more: Fig. 02 · Blue Prism Pros and cons Blue Prism: pros and cons Pros - Enterprise focusUnattended automation for medium and large companies - All-in-one platformCovers intelligent automation, with no limit on the number of processes - Debugging toolsOne of the best debuggers available - Task captureDocuments your business processes Cons - PriceMore expensive than competitors - Less active community ### Enterprise focus For Blue Prism, medium and large enterprises are the main target due to the platform’s scalability and reliability features. Blue Prism is well suited to accommodate a large number of bots running at the same time without any impact on their performance or stability. Process modules can also be easily reused, enabling fast automation adoption within a department. It’s also worth noting that Blue Prism only offers unattended automation. So while it excels at logic-based back-office tasks, it won’t aid individual employees in their everyday work. That is more proof that Blue Prism tries to focus on corporate clients. ### All-in-one platform Designed primarily with enterprises in mind, Blue Prism offers a comprehensive product portfolio to meet every automation goal. It can facilitate and streamline all workforce activities, no matter how complex. The platform covers all intelligent automation capabilities, from data gathering, aggregation, and analysis, through visual analytics and machine learning, to automated collaboration and enhanced problem-solving. The number of processes to be executed by the tool is also unlimited. ### Debugging tools Finding the source of a problem is the first step to fixing it. Therefore, efficient debugging features are extremely useful in RPA, especially in complex, multi-stage workflows. Blue Prism is equipped with one of the best debuggers out there. The main advantage lies in its dynamic capabilities—developers can interact with the process and alter variables while the debugging is executed. It makes testing various scenarios much faster and more convenient, ultimately leading to better overall stability. ### Blue Prism—disadvantages We’ve just told you that UiPath’s biggest flaw is its price, but Blue Prism isn’t a cheaper option. On the contrary, its implementation can be more expensive in the short run, even more so if you don’t plan to use UiPath’s advanced functionalities. Another disadvantage is low engagement with the community. Despite its long-time market presence, Blue Prism acts very slowly when implementing features its users request. ## Blue Prism or UiPath: which one’s better? Now that we know the two tools’ main strengths and weaknesses let’s check how they fare compared to one another, tech- and business-wise. ### The tech perspective First, the tech stuff. - App integration — although both platforms can be integrated with popular desktop apps like Word, Excel, and internet browsers, Blue Prism only supports back-office automation and hence lacks the most crucial front-office apps. - Debugging — while UiPath also has its own debug tools, they lack the dynamic adjustment capabilities of Blue Prism. - Education — we’ve already mentioned how UiPath encourages its users to get involved with the platform. One of the ways it does it is by giving them access to a rich collection of learning resources and certifications through a [dedicated UiPath Academy portal](https://academy.uipath.com/). It is a hub for all skills RPA where anyone can learn how to build automation workflows and dig into the subject. Additionally, UiPath offers a free Community Edition that new learners can use to practice. Unfortunately, the same can’t be said about Blue Prism, which offers certification programs but doesn’t get near the scope of UiPath’s educational efforts. Which also affects… - Talent pool — since UiPath does so much more to teach its users how to use their RPA tool, more certified UiPath developers are available for hire than in Blue Prism’s case. - Task recording — Recording is an optional feature in UiPath Studio that lets the algorithm capture users’ on-screen actions and recreate them into automated sequences. Blue Prism doesn’t offer any similar functionality. - Coding knowledge — Both tools are equally user-friendly for [citizen developers](https://www.flobotics.io/blog/rpa-non-technical-developer) as they don’t require coding knowledge to operate (although familiarity with HTML/CSS helps). Still, professional developers add a whole different dimension to what can be done with the platforms (more complex use cases, faster app delivery, smoother operation of the developed automation). One difference is that UiPath is very transparent about its code and allows professional programmers to use C# expressions everywhere, while Blue Prism uses its own, very accessible, language. ### The business perspective Of course, successful RPA implementation isn’t just about the technicalities. You should definitely understand how [RPA development process](https://www.flobotics.io/blog/rpa-development-process) looks like. Business needs are just as important. - Costs — UiPath requires a lower upfront investment than Blue Prism, making it a preferable option for startups and smaller companies. Additional features can be added as the company grows. - Accessibility — UiPath can be accessed from both a mobile and desktop app, as well as through a browser. Blue Prism is only available as a desktop application. - Tasks — unlike UiPath, Blue Prism is limited to unattended bots. These are great for back-office jobs and reducing operating costs but won’t do much for assisting your specialists on-demand. For instance, accounting can make use of both types of bots. - Enterprises — Blue Prism makes more sense for corporations and large organizations due to its enterprise focus and good scalability features. - Industry — over the years, both vendors have built an impressive track record across different industries. But, in the end, it boils down to the scale. For example, hospitals and clinics may prefer to go for UiPath, but Blue Prism may be a better choice for international healthcare providers ## The verdict As you can see, there’s no clear winner in this contest; and there doesn’t need to be—every company has different needs and requires various tools. At Flobotics, we understand that and always consider the specificities of our clients. Therefore, even though UiPath is our number 1 RPA platform, we believe every solution, including Blue Prism, has advantages for all industries, from finance to healthcare. If you’re looking to [automate your processes](https://www.flobotics.io/) but aren’t sure whether Blue Prism or UiPath will work best for you, you’ve found the right people for the job. [Get in touch](https://www.flobotics.io/contact) and tell us about your organization—we’ll handle the rest. Fig. 03 · RPA platforms Verdict UiPath vs Blue Prism | UiPath | Blue Prism | App integration | Common apps, attended and unattended | Common apps, unattended only | Scalability | From small companies to enterprises | Mainly enterprises | Pricing | Lower upfront cost; grows with the license you choose | High upfront cost | Education | UiPath Academy, free community version, certification | Certification | Community | Large and active: forum, insider previews, blogs | Less active | Recording | Available | None | Debugging | Basic | Dynamic | Access | Mobile and desktop apps, browser | Desktop app | Coding skills | Not required, but coding experience makes development faster and better | Same as UiPath | Talent pool | More developers available | Fewer developers available | #### Like the article? Spread the word Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RCMRPAAI ### AI vs. RPA vs. ML in Healthcare RCM: A Deep Dive AI vs. RPA vs. ML in healthcare RCM: how each technology improves efficiency, accuracy, and compliance, and which to adopt first. Krzysztof SzwedFebruary 22, 2025 ](https://www.flobotics.io/blog/ai-rpa-ml-rcm)[ RPA ### UiPath vs. Python? Choosing the Right RPA Tool for Your Automation Job UiPath vs. Python: compare strengths, use cases, and when to choose code over low-code for your next automation project. Krzysztof SzwedDecember 11, 2023 ](https://www.flobotics.io/blog/uipath-python)[ RPAAI ### UiPath vs. Celonis vs. Kyp.ai: Comparing Top Task Mining Tools UiPath vs. Celonis vs. Kyp.ai: features and pricing compared to help you pick the right task mining tool for 2026. Bart TeodorczukNovember 20, 2023 ](https://www.flobotics.io/blog/uipath-vs-celonis-vs-kypai) [All articles →](https://www.flobotics.io/blog) --- # How (and Why) Should You Build an Automated Medical Billing System? Canonical: https://www.flobotics.io/blog/how-to-build-automated-medical-billing-system Author: Karl Mielnicki Published: 2022-08-15 Updated: 2026-09-08 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/How (and Why) Should You Build an Automated Medical… CTO Notes [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # How (and Why) Should You Build an Automated Medical Billing System? [Karl MielnickiCTO & Co-Founder of Flobotics](https://www.flobotics.io/our-editorial-team#mielnicki) Published August 15, 2022Updated September 8, 2026 On this page - [Medical Billing Process](#medical-billing-process) - [Why Does the Medical Billing System Need Automation?](#why-does-the-medical-billing-system-need-automation) - [Proper Documentation](#proper-documentation) - [Lower Costs](#lower-costs) - [Streamlined Medical Billing](#streamlined-medical-billing) - [More Time for Patients](#more-time-for-patients) - [What Can Be Automated in Medical Billing?](#what-can-be-automated-in-medical-billing) - [Appointment Scheduling and Registration](#appointment-scheduling-and-registration) - [Data Entry](#data-entry) - [Eligibility Checks and Cost Estimates](#eligibility-checks-and-cost-estimates) - [Prior Authorizations](#prior-authorizations) - [Electronic Health Records Automation with RPA](#electronic-health-records-automation-with-rpa) - [Claims Processing](#claims-processing) - [Payment Posting](#payment-posting) - [Denials](#denials) - [Patient Communication](#patient-communication) - [Reporting](#reporting) - [The Medical Billing Process in 8 Steps](#the-medical-billing-process-in-8-steps) - [Registration](#registration) - [Financial Responsibility Check](#financial-responsibility-check) - [Check-in and the Superbill](#bookings) - [Coding and Billing Compliance Checks](#coding-and-billing-compliance-checks) - [Transmitting Claims](#transmitting-claims) - [Adjudication Process](#adjudication-process) - [Generate Patient Statements](#generate-patient-statements) - [Follow Up On Patient Payments](#follow-up-on-patient-payments) - [The Steps for Implementing an Automated Billing System with RPA](#the-steps-for-implementing-automated-billing-system-with-rpa) - [RPA in Medical Billing: What to Keep in Mind](#rpa-in-medical-billing-what-to-keep-in-mind) - [Choose the Right RPA Technology](#choose-the-right-rpa-technology) - [Work with the Right Developers](#work-with-the-right-developers) - [Stay HIPAA Compliant](#hipaa-compliance) - [Automate the Right Process](#automate-the-right-process) - [Track the Right KPIs](#track-the-right-kpis) - [Automated Medical Billing – Conclusion](#automated-medical-billing-conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Billing is the lifeblood of any [healthcare practice](https://www.flobotics.io/blog/chatgpt-for-healthcare). For the most part, [medical billing](https://www.flobotics.io/rcm-automation) can be a very complicated and work-heavy procedure with many repetitive processes, but what about implementing an automated medical billing system? ### Medical Billing Process Fig. 01 · Medical billing 10 steps The medical billing process - 01Insurance validation - 02Charge capture - 03Medical coding - 04Claim submission - 05A/R follow-up - 06Denial management - 07Remittance processing - 08Third-party follow-up - 09Patient collections - 10Reporting and analysis This repetitive nature of medical billing makes it a great candidate for automation and coupled with the fact that several organizations are under pressure to keep the medical billing process as efficient and reliable as possible. In this article, we cover why medical billing needs automation, which tasks bots can take over, how the billing process works step by step, and how to implement RPA without wasting time or money. ## Why Does the Medical Billing System Need Automation? Automation takes care of every important aspect of medical billing that might seem tedious to a human. Billing errors get identified before a claim is submitted, which results in claims getting paid faster by payers. Similarly, RPA payment solutions can enhance collections by automatically sending patient bill notifications through text or email. In the United States alone, much money is being spent yearly on healthcare expenses that can be avoided. The following are some reasons why automated medical billing is critical. ### Proper Documentation In an industry where Paper document filings cost $20 per filing process. Healthcare providers fill out an average of 20,000 forms yearly. In medical billing, where lots of administrative paperwork like patient profile creation and registration, eligibility checks, and other billing information validation are being filled daily, error-free documentation should be the goal of every healthcare provider. Similarly, automation enables providers to comply with HIPAA and other regulations and reduces the number of staff members dedicated to a process while increasing productivity. ### Lower Costs Take RCM, which is the financial process of collecting payments for medical bills to generate revenue for a healthcare organization. Revenue cycle management can be time-consuming and expensive because it combines administrative data such as a patient’s personal information, treatment codes, and the insurer’s name with financial billing information. The recommended amount of receivables older than 120 days should be between 12-25 percent, but automating RCM tasks aid in lowering it to less than 12 percent. ### Streamlined Medical Billing All healthcare providers that have jumped on the RPA train in [Medical billing automation ](https://www.flobotics.io/rcm-automation)can attest that using an outdated billing system risks a high level of unorganized claims processes and unnecessary errors. In 2021, $28.91 billion in payment errors were made as a result of coding errors, according to the Centers for Medicare & Medicaid Services (CMS). ### More Time for Patients When bots take over data entry, claim follow-up and status checks, staff spend that time on patients and on the cases that need judgment. People who no longer repeat the same steps all day also tend to be happier in their jobs, and that shows in the care patients get. ## What Can Be Automated in Medical Billing? A lot of tedious and repetitive processes can be automated in medical billing. Billers have to pull data from separate systems, such as patient history, diagnosis and procedure codes and insurance eligibility, and payment depends on getting those codes right. Here are the tasks bots take over most often. Fig. 02 · Medical billing What to automate Which medical billing processes can be automated Medical billing - 01Invoice processing - 02HIPAA-related processes - 03Insurance payment processing - 04Scheduling appointments - 05Tracking and processing claims - 06Preventing underpayments ### Appointment Scheduling and Registration Bots can create patient profiles, register patients and book appointments, and keep the record up to date from the first call until the visit is complete. ### Data Entry Data entry is one of the most time-consuming parts of medical billing and coding, and where most errors start: demographics, codes and insurance details typed by hand. Bots take that information from your EHR or EMR and enter it into the billing system. With OCR, they also read data from scanned images and PDFs, so nobody has to retype them. ### Eligibility Checks and Cost Estimates Bots check a patient’s coverage and benefits before the visit, then link the patient’s profile to the planned services and calculate the cost from the price list you already have. See how this works in our [eligibility verification automation](https://www.flobotics.io/agents/eligibility-check-automation). ### Prior Authorizations Bots collect the data a prior authorization needs from payer websites and your other systems and enter it where your team works, such as the hospital information system. More on this in [prior authorization automation](https://www.flobotics.io/agents/prior-authorization-automation). ### Electronic Health Records Automation with RPA Regardless of the EHR your company uses, there is always room for automation. Bots fill in EHR forms and copy data between systems, for example from one EHR to another or from your EHR to your CRM, which cuts errors and gives doctors more time with patients. ### Claims Processing Human error is a common cause of first-time claim denials. Bots handle charge entry, payer rule checks and submission, and keep fee schedules up to date, so no claim goes out unpaid or underpaid. Our SuperBill client cut claim turnaround time by about 70% this way ([case study](https://www.flobotics.io/case-studies/70-faster-claim-turnaround-time-ctt-claim-management-automation)), and Gentem reduced manual claim prep by 98% ([case study](https://www.flobotics.io/case-studies/98-reduction-in-manual-claim-prep-claims-management-automation)). [Learn more about automated claims processing.](https://www.flobotics.io/agents/claims-management-automation) ### Payment Posting A payment posting bot follows the rules you give it, the same way you would train a new employee. It posts insurance payments, flags unpaid claims for follow-up, and handles refunds and takebacks. ### Denials Bots fix simple errors and resubmit the claim on their own. Complex denials go to a person, with the patient and denial details already gathered, so the rework is faster. See [denials management automation](https://www.flobotics.io/agents/denials-management-automation) and the [case study of an AI agent for denials](https://www.flobotics.io/case-studies/50k-saved-in-1-month-ai-agent-for-denials-management). ### Patient Communication Bots can write an email that sums up the price of a service or other questions from a phone call, and send reminders by email or text. ### Reporting Bots can run around the clock, and everything that passes through them can feed accurate reports, which makes billing decisions easier. Thinking of automating your medical billing management? Find out more [here](https://www.flobotics.io/blog/medical-billing-management). Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## The Medical Billing Process in 8 Steps Medical billing might seem complicated, but it comes down to the following eight steps. Bots can help at almost every one of them. Fig. 03 · Medical billing 8 steps RPA in medical billing: 8 steps to full automation - 01Patient registration - 02Financial responsibility check - 03Appointment booking - 04Coding and billing compliance checks - 05Claim transmission - 06Adjudication - 07Patient statements - 08Patient payment follow-up ### Registration This is the first step of the medical billing process, where a patient calls to schedule an appointment with a healthcare provider. For a doctor’s visit, a patient has to pre-register effectively by providing insurance details. Information on old works will be saved, and a patient only has to explain the reason for their visit on subsequent visits. Registration enables medical billers the opportunity to verify details provided before claim submission. ### Financial Responsibility Check Financial responsibility checks are carried out to verify a patient’s insurance to know who owes what for a doctor’s visit. Before a biller can determine if a patient’s insurance plan covers the services the patient needs, the biller has to gather vital information that can only be carried out by carrying out financial responsibility checks. Individuals and companies all have different insurance plans. Hence, a biller has to check a patient’s coverage to ensure certain bills are assigned appropriately and prescriptions are covered for the entirety of the bill. In this case, RPA bots carry out these kinds of checks. ### Check-in and the Superbill Patients are asked to fill out forms as they arrive to separate registered patients from first-timers. The necessary official identification, such as a valid insurance card along with a passport or driver’s license, is used in determining whether copayments are received before or after the enrollment is done by the providing office. In most cases, Copayments are collected at the point of service, and once the patient has been verified, a report is sent to the medical coder. Upon receiving the medical news, the medical coder analyses it and translates its information into usable medical code. This medical coding process results in what’s called the “superbill.” The superbill includes demographic information about the patient’s medical history, the physician’s name, the provider’s name, the codes for the diagnosis and procedure, the procedures performed, and other relevant medical information. The superbill is then transferred via a software program to the medical biller. ### Coding and Billing Compliance Checks After receiving the superbill, the medical biller transfers it into billing software or a paper claim form. It ensures that the procedures coded are billable, even though the billability of a system depends largely on the regulations laid out by the payer and the patient’s insurance plan. Billers must also ensure that compliance standards are met. Typically the code must follow guidelines laid out by the [Office of the Inspector General](https://oig.justice.gov/) (OIG) compliance standards and the [Health Insurance Portability and Accountability Act](https://www.hhs.gov/hipaa/for-professionals/privacy/laws-regulations/index.html) (HIPAA). ### Transmitting Claims Transmission of claims is done electronically and with coding through the use of EDI (Electronic Data Interchange). The Health Insurance Portability and Accountability Act of 1996 (HIPAA) mandates all health entities covered by HIPAA to submit their claims through electronic means. However, claims will only be transmitted through EDI if they are error-free. Learn how you can improve your claims management by providing [RPA for claims processing.](https://www.flobotics.io/agents/claims-management-automation) ### Adjudication Process This is the stage where a claim is denied, rejected, or accepted. A payer evaluates the medical claim to decide whether it is compliant or valid and how much will be reimbursed to the provider. During the adjudication process, the details of the claims are sent to the biller or provider to know how much they are willing to pay and why. For patients with secondary insurance, the remainder of the claim is sent to their secondary insurer after approval by the primary insurer. An appeal process can be filled with the payer if any problem arises. ### Generate Patient Statements Patient statements detail all the patient’s care from their healthcare provider. It is the procedure bill, and once the payer sorts the agreed amount, the patient handles the rest. Some payers might include an Explanation of Benefits (EOB) to explain why some procedures were covered and others were not. ### Follow Up On Patient Payments Bills must be paid on time to ensure a system functions without issues. Billers are charged with mailing out timely, accurate medical bills to ensure bills get paid on time. Each provider has its own set of guidelines and timelines when it comes to bill payments, notifications, and collections. The biller’s responsible for ensuring that the provider is properly reimbursed for their services if the patient does not pay the full amount or is delinquent in their payment. Learn more about [five processes for the healthcare industry you didn’t know could be automated](https://www.flobotics.io/blog/healthcare-workflow-automation). ## The Steps for Implementing an Automated Billing System with RPA - Audit your processes and confirm the requirements. Pick the processes to automate and rank them by complexity and return on investment. Decide what each automation should achieve and how it fits into your operations. RPA consultants or an [RPA services company](https://www.flobotics.io/uipath-services) can map your processes and compare your current tools with your goals. - Check feasibility. For each process, check how much of it can be automated and whether that is technically possible. The person who runs the process, a subject matter expert and an RPA expert should do this together, including a check of legal compliance. - Fix the process first. If the check shows a process isn’t organized, standardized or documented, fix that before automating it. - Write user stories. Describe each step to be automated from the user’s point of view, then turn that into a process description document for the developers. - Set up the environment and build. Developers build the workflows in an RPA platform such as UiPath or Blue Prism. Each tool has different strengths, so choose carefully. - Test with a proof of concept. Test the automation in every situation you can think of before it goes live, and send any problems back to the developers. - Confirm and deploy. Once the issues are fixed, check the results again and deploy the full solution. ## RPA in Medical Billing: What to Keep in Mind ### Choose the Right RPA Technology RPA platforms such as UiPath, Blue Prism, Power Automate and Kofax differ in features and licensing costs. Some will suit your needs better than others, so compare them before development starts. ### Work with the Right Developers Your developers need the skills and experience to set up the environment and build the workflows on their own, with little downtime, and to scale the automation later. [Here’s what to check](https://www.flobotics.io/blog/rpa-non-technical-developer) before you hire. ### Stay HIPAA Compliant Every workflow and bot must comply with the rules of the market it runs in; in the U.S., that means HIPAA. Penalties for HIPAA violations are severe, whether or not the provider caused the problem. Manual document work is where omissions and errors creep in: forms need specific information approved by patients, which means chasing people for approvals and skipping steps. Bots that move patient data between systems take those manual steps out. [Read more about HIPAA compliance automation.](https://www.flobotics.io/blog/hipaa-compliance-rpa) ### Automate the Right Process Choosing what to automate takes experience: what is actually needed, and which tools and testing methods will get you there. Our guide on [which processes to automate](https://www.flobotics.io/blog/what-processes-to-automate) can help. ### Track the Right KPIs Pick KPIs based on the outcome you need, such as productivity, return on investment or less downtime. More in our guide to [measuring RPA success](https://www.flobotics.io/blog/rpa-successs-metrics). ## Automated Medical Billing – Conclusion A streamlined workflow makes for a less hectic workday. An automated billing system helps healthcare providers reduce human mistakes and process claims accurately. Every organization’s needs are different, so start with an assessment of your own processes, requirements and KPIs by people who have done it before. That avoids wasted time and money and leaves room to scale later. Our in-house RPA developers, including [UiPath consultants](https://www.flobotics.io/uipath-services), can help you automate your medical billing by connecting your health data systems. [Get in touch](https://www.flobotics.io/contact) for a free consultation. ## FAQ: Can medical billing be automated? Much of it can. Eligibility checks, claim scrubbing, and routine denial resubmission are high-volume and rule-based, making them well suited to automation, while complex appeals and patient-facing conversations still benefit from human judgment. What are the main steps in the medical billing process? Registration, eligibility verification, the patient encounter, coding, charge entry, claim scrubbing, submission, payer adjudication, payment posting, and denial management or patient billing. What is a clean claim? A claim that's accepted and paid the first time it's submitted, with no missing information, coding errors, or additional documentation requests from the payer. Should a practice outsource its medical billing? It depends on volume and resources. Outsourcing brings dedicated expertise for a percentage of collections (commonly 4 to 10 percent) without fixed headcount costs; in-house billing gives more direct control but carries the full cost of staff, training, and software regardless of volume. Is medical billing the same as medical coding? No. A coder translates clinical documentation into diagnosis and procedure codes. A biller uses those codes to build and submit the claim, then manages everything that happens to it afterward. Written byKarl Mielnicki CTO & Co-Founder of Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RCMHealthcare ### Medical Coding Automation: Why (and How) Should You Start? Medical coding services, automated: how RPA improves claims accuracy and cuts manual coding errors for healthcare providers. Karl MielnickiMay 13, 2022 ](https://www.flobotics.io/blog/medical-coding)[ HealthcareEligibilityClaims ### Implementing Automated Claims Processing in the Medical Industry Medical claims processing automation: see how RPA replaces costly manual workflows with automated claims for practices of every size. Karl MielnickiOctober 01, 2021 ](https://www.flobotics.io/blog/claims-processing-in-medical-industry) [All articles →](https://www.flobotics.io/blog) --- # [WEBINAR FOR MEDICAL BILLING] How to Process 6x More Patients Without Hiring a Single Person Canonical: https://www.flobotics.io/blog/webinar-medical-billing Published: 2022-08-11 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/[WEBINAR FOR MEDICAL BILLING] How to Process 6x More… [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # [WEBINAR FOR MEDICAL BILLING] How to Process 6x More Patients Without Hiring a Single Person Published August 11, 2022Updated September 1, 2026 On this page - [What did we cover?](#what-did-we-cover) - [Who was it for?](#who-was-it-for) - [Watch the recording of the webinar!](#watch-the-recording-of-the-webinar) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Billing is the lifeblood of any healthcare practice. But, for most parts, [medical billing](https://www.flobotics.io/rcm-automation) remains a complex and work-heavy operation with a lot of repetitive processes. Companies and billing providers across the industry are on a constant look for tactics and solutions that can help them streamline these operations, optimize costs and battle the arising challenges. And what are they? Flobotics’ business team has been talking with various representatives of the industry and some challenges have been mentioned significantly often. - Great Resignation. There is a growing shortage of skilled billing workforce, topped up by decreasing retention of existing billing employees; - Losing Business due to billing mistakes claims errors, and never resubmitting claims after denials; - Dangerous lengthening of the Revenue Cycle, which hurts cash flow and the ability to reinvest. All of these challenges stand in the way of effectively scaling the business. But, luckily, they can be easily tackled with automation software. We’ve conducted the automation webinar for the medical billing industry and discovered how automation software can reshape the way you run your billing operation! ## What did we cover? - Discussed the best solutions to increase the effectiveness of medical billing operations, especially [RPA for medical billing](https://www.flobotics.io/rcm-automation) - Analyzed potential costs of bringing automation software to billing and calculating its potential Return on Investment, - Showcased real-life automation use cases from the industry, and analyzed their measurable business impact. ## Who was it for? 1) People Operations – responsible for overseeing operations, optimizing processes, and improving the bottom line. 2) Billing Managers – responsible for managing billing teams and optimizing billing costs. 3) CTOs & IT leads – who are in charge of maintaining IT systems, data security, and implementing new solutions. ## Watch the recording of the webinar! Get first-hand knowledge on how billing tasks can be streamlined with automation: Having an optimized workflow gives room for a less hectic work experience. Automated medical billing processes help healthcare providers significantly reduce human-related mistakes and process claims accurately. Through the use of [Flobotics automation services,](https://www.flobotics.io/) you’ll be able to speed up your operations, decrease operational costs, and unleash your employees’ productivity. #### Like the webinar? Spread the word Flobotics Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # 5 Processes in the Healthcare Industry You Didn’t Know Could Be Automated Canonical: https://www.flobotics.io/blog/healthcare-workflow-automation Author: Michał Rejman Published: 2022-08-01 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/5 Processes in the Healthcare Industry You Didn’t Know… [Healthcare](https://www.flobotics.io/blog?category=healthcare) # 5 Processes in the Healthcare Industry You Didn’t Know Could Be Automated [Michał RejmanChief Marketing Officer at Flobotics](https://www.flobotics.io/our-editorial-team#rejman) Published August 01, 2022Updated September 1, 2026 On this page - [Main challenges facing today’s healthcare industry](#main-challenges-facing-todays-healthcare-industry) - [Staff shortages](#staff-shortages) - [High operational costs](#high-operational-costs) - [Denied and overdue claims](#denied-and-overdue-claims) - [Data deluge](#data-deluge) - [Compliance issues](#compliance-issues) - [Five Unlikely Candidates for Healthcare Workflow Automation](#five-unlikely-candidates-for-healthcare-workflow-automation) - [1. Onboarding, scheduling, and profile creation](#1-onboarding-scheduling-and-profile-creation) - [3. FTP/SFTP/FTPS](#3-ftp-sftp-ftps) - [4. Compliance monitoring](#4-compliance-monitoring) - [5. Dynamic provisioning](#5-dynamic-provisioning) - [Healthcare workflow automation — what are the benefits?](#healthcare-workflow-automation-what-are-the-benefits) - [Conclusion – what’s next?](#conclusion-whats-next) - [Like the article? Spread the word](#like-the-article-spread-the-word) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) From telecom to transport, IT to insurance—transforming one industry after another, automation shows no signs of stopping. The automation market is growing steadily, expected to increase its total size twofold to almost $400 billion in 2029. But how does this remarkable trend impact healthcare services? Due to its human-centered nature, healthcare may not be the obvious target when considering automation candidates. However, umpteen non-medical background processes are behind every medical procedure and patient-doctor interaction, like insurance billing and [coding](https://www.flobotics.io/blog/medical-coding), [pre-authorization](https://www.flobotics.io/agents/prior-authorization-automation), or [claims processing](https://www.flobotics.io/agents/claims-management-automation). All of them are well-suited for automation, and Robotic Process Automation (RPA), in particular, is a great way to start small and take it from there. Are you keen to learn about automation opportunities for medical providers? Read on and discover the most pressing challenges for [healthcare workflow automation](https://www.flobotics.io/rcm-automation) and how your office or practice can address them using RPA. Learn more about using Robotic Process Automation in other industries, like RPA in insurance, retail, manufacturing, e-commerce, sales, logistics, real estate, or automation for consultancy. ## Main challenges facing today’s healthcare industry In addition to some global factors that affect every business sector (think COVID or skyrocketing gas prices), each industry has its pains to face. When it comes to healthcare, the following few are particularly prominent. Fig. 01 · Healthcare 5 challenges The main challenges healthcare faces Healthcare today - 01Staff shortages - 02High operating costs - 03Compliance issues - 04Data overload - 05Denied and overdue claims ### Staff shortages This is a problem that hospital managers and healthcare HR specialists know all too well. The lack of professionals is nothing new (already, in the early 1990s, analysts raised concerns over the imminent nursing and hospital bed shortages). Still, the great resignation, pandemic, and ever-growing hiring expenses have only exacerbated the issue. Unfortunately, things aren’t expected to take a turn for the better anytime soon. For example, the American Association of Medical Colleges projects a [shortage of up to 124,000 physicians by 2033](https://www.kff.org/coronavirus-covid-19/issue-brief/nursing-facility-staffing-shortages-during-the-covid-19-pandemic/). At the same time, 28% of nursing facilities remain understaffed. That trend applies to non-medical personnel as well. Time and resources necessary to train [revenue cycle ](https://www.flobotics.io/rcm-automation)professionals are some of the main reasons why [60% of healthcare finance leaders](https://revcycleintelligence.com/news/healthcare-finance-leaders-facing-revenue-cycle-workforce-shortages) report having at least 100 vacancies. We’re looking at leaders here, meaning shortages may be even more severe for smaller providers. ### High operational costs With all the processes, resources, and specialists involved in each treatment, it’s hardly shocking that healthcare doesn’t come cheap. However, in recent years, operational costs have gone through the roof. [A report by American Hospital Association](https://www.aha.org/costsofcaring) points to four main culprits: - Workforce expenses — at the peak of the Omicron upsurge, per-patient labor expenses were 57% higher than before the pandemic. - Drug prices — expenses on drugs and medical supplies for each patient increased by 36% between 2019 and 2021. - Supplies and PPE costs — some crucial resources, e.g., energy, resins, and cotton- increased by over 30% between 2020 and 2022. - Inflation — higher prices affect costs and discourage patients from seeking treatment. ### Denied and overdue claims Is $25 a lot? That’s how much [reworking a denied insurance claim costs on average](https://www.physicianspractice.com/view/why-getting-claims-right-first-time-cheaper-reworking-them). Even if this amount seems peanuts to you, multiply it by the monthly number of claims denied or overdue in your practice, and the sum of money leaking out may pile up fast. That’s where healthcare workflow automation comes in. Preventing [denied claim](https://www.flobotics.io/agents/denials-management-automation) losses isn’t easy since the exact reason for claims issues may be tricky to pin down. Here are some of the most common ones: - medical coding errors, - improper pre-authorization, - missing information, - duplicate claims, - medical necessity requirements not met, - missed deadlines. ### Data deluge The [transition to EHR](https://www.flobotics.io/blog/electronic-health-records-rpa) has ended many documentation challenges in healthcare. However, some issues have persisted in plaguing the industry still today. Do any of these sound familiar to you? - Missing or incomplete documentation may negatively affect treatment, lead to negligence, legal action, and even result in patient death. - Miscommunication between providers influences the quality and speed of healthcare delivery and damages the providers’ reputation. - Privacy breaches and leaks due to insufficient and amateur protection against cyberattacks. In the USA alone, 2021 brought a record high in cybersecurity issues, resulting in [45 million patients](https://cybersecurity.criticalinsight.com/2021_H2_HealthcareDataBreachReport) compromising their private information. - The mass use of copy-paste when handling medical documentation that may contribute to the dissemination of incorrect and misleading information. As you can see, handling data is one thing. But the sheer volume of data to process is a challenge for healthcare facilities and professionals. Too many tedious back-office tasks are handled manually, leaving room for human error and putting additional strain on your already busy personnel. Take [medical insurance billing and coding](https://www.flobotics.io/blog/medical-coding), for example. These tasks involve working with huge volumes of data and repetitive procedures while putting your practice at risk of denial if done without due diligence. ### Compliance issues Ensuring [compliance with HIPAA](https://www.flobotics.io/blog/hipaa-compliance-rpa) and other regulations is one of the most error-prone areas of healthcare finances. Even the most conscious professionals can blunder between [hundreds of claims to process each day](https://www.flobotics.io/agents/claims-management-automation). And, given that [fees for non-compliance can reach $1.5 million per year](https://www.hipaajournal.com/what-are-the-penalties-for-hipaa-violations-7096/), that mistake can be costly. Meeting audit and regulatory requirements can be particularly challenging for providers running their operations in multiple countries, each with different compliance regulations. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Five Unlikely Candidates for Healthcare Workflow Automation Luckily, RPA solutions for improving healthcare automation workflow, such as medical coding automation tools, can help providers resolve all the above issues—however daunting they seem. There’s no limit to the use cases that can be supported by robotic-enhanced automation. However, as we will see, certain processes are more likely candidates for automation. ### 1. Onboarding, scheduling, and profile creation The back-office work begins right after a new patient enters your practice. The repetitive nature of onboarding tasks makes RPA and other automation methods shine here. While workflows like setting up an account, verifying history, or submitting patient data to the system can be extremely monotonous, scripts can be easily pre-programmed to run these tasks precisely, no matter the volume. By automating data collection and entry, medical and non-medical staff can prevent mistakes they would normally spot further down the road. Once a patient’s data and account are ready, automation tools can assist your staff in scheduling appointments. Pulling the necessary information from various systems, finding the right time, and confirming the visit with the patient has never been easier. 2. Claims processing Preparing and submitting claims to the insurer is notoriously tedious and just as crucial. Fortunately, in many cases, both processes can be completed entirely without the involvement of a human worker. A bot is capable of handling every step of the procedure. After logging in, it searches for claims to process and respective insurers based on pre-existing databases. Next, medical coding automation algorithms assign the ICD codes to each claim, enabling relevant medical procedures and insurance charges. Since the bot checks if all information is in place and pulls it from all available sources, no empty text field goes unnoticed. Lastly, it scans the claim for unnecessary ICD codes and deletes them. With the cleanup done, the suit gets sent to the insurer. All in just about half a minute! Read more about [claims processing automation](https://www.flobotics.io/agents/claims-management-automation) in this case study. ### 3. FTP/SFTP/FTPS The problem with medical data isn’t just that it’s sensitive and comes in huge volumes. It tends to move a lot between clinics, physicians, insurers, laboratories, [research facilities](https://www.flobotics.io/blog/automate-clinical-trials), and other institutions. Keeping all records secure and complete while preventing them from ending up in siloes and ensuring they reach the right recipient can be overwhelming. See how we [connect healthcare systems](https://www.flobotics.io/data-integrations) using APIs where available and UI automation where needed. Just like with medical coding automation, RPA solutions guarantee the safety and accuracy of data transfer. Data is structured automatically, allowing for easier access and file traffic monitoring. Records are only forwarded after the algorithm ensures they are complete and properly encrypted. ### 4. Compliance monitoring Another challenge from massive bulks of [health records ](https://www.flobotics.io/rcm-automation)is staying compliant with HIPAA and other data regulations. Verifying every file transfer is a job that cannot be completed without proper tools. Algorithms act in line with the compliance policies established by your administrators. Based on defined roles and authorization rules, RPA bots automatically transfer and process the data only when the process is verified and free from errors. Script-run workflows limit human interference, too, reducing the likelihood of a breach. ### 5. Dynamic provisioning We’ve already established that resources are pricier than ever. Moreover, these costs grow further as healthcare organizations increasingly rely on virtual and cloud-based systems. The answer to that problem lies in dynamic provisioning. Automated provisioning bots monitor load conditions and adjust throughput to the current needs. By turning off machines, not in use, dynamic provisioning helps healthcare organizations save money and resources. On the other hand, it also scales up computing power when needed, guaranteeing adequate performance. ## Healthcare workflow automation — what are the benefits? Automating all the processes mentioned above aims to mitigate the main pain points in healthcare automation workflow and help your practice deliver even better services. Here’s what’s in it for all stakeholders—including the medical and management professionals: - Less time spent on dull tasks — your personnel can do what they do best: providing excellent treatment and patient experience. Another important benefit is higher work satisfaction. - Lower operational costs — money saved thanks to automation can be invested elsewhere, e.g., in infrastructure or salaries. - Faster revenue cycle — all processes that make up the revenue cycle, from registration to claim submission, are more immediate, leading to no missed deadlines. - Centralized data — automation helps you harness all the data, no matter how massive. - Higher patient satisfaction — the overall efficiency improvements won’t go unnoticed by patients who’ll love to return to your practice. - Fewer errors, full compliance — bots take care of repetitive tasks, preventing mistakes and ensuring data security. You can also try automating your [healthcare processes with ChatGPT](https://www.flobotics.io/blog/chatgpt-for-healthcare), read to find out more. ## Conclusion – what’s next? Virtually no tasks and workflows are unfit for automation in healthcare (including [clinical trials](https://www.flobotics.io/blog/automate-clinical-trials), medical billing, or [coding](https://www.flobotics.io/blog/medical-coding)). Ultimately, their proper implementation and optimization boil down to choosing the right strategy—and an experienced implementation partner. As a UiPath-certified company with ample expertise in the medical coding business, here at Flobotics, we have everything needed to get your practice started with RPA-assisted workflows and staying [HIPAA compliant](https://www.flobotics.io/blog/hipaa-compliance-rpa). Our experienced consultants can’t wait to hear about your vision and see how they can get your healthcare workflow automation efforts underway. [So reach out and tell us more!](https://www.flobotics.io/) ### Like the article? Spread the word Written byMichał Rejman Chief Marketing Officer at Flobotics. [More from Michał](https://www.flobotics.io/our-editorial-team#rejman) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ AIHealthcareRPA ### Compliance Automation in Healthcare Healthcare compliance automation: how Continuous Control Monitoring and Agentic AI cut administrative drag by 20-30% in 2026. February 04, 2026 ](https://www.flobotics.io/blog/compliance-automation-healthcare)[ RCMRPAHealthcare ### How Data Entry Automation Transforms Healthcare Operations Healthcare data entry automation: see how automated workflows sync patient records instantly and stop denied claims before they start. Michał RejmanJune 30, 2025 ](https://www.flobotics.io/blog/data-entry-automation-healthcare)[ RPAHealthcare ### Interoperability in Healthcare: What You Need to Know (And How to Get There with RPA) Healthcare interoperability, explained: how RPA connects clinics, insurers, and EHRs for faster, more reliable patient data flow. Michał RejmanOctober 03, 2023 ](https://www.flobotics.io/blog/interoperability-in-healthcare) [All articles →](https://www.flobotics.io/blog) --- # Mystic River Consulting | $100K saved in a few days Canonical: https://www.flobotics.io/blog/mystique-river Author: Jędrzej Szymula Published: 2022-08-01 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Mystic River Consulting | $100K saved in a few days [RPA](https://www.flobotics.io/blog?category=rpa) # Mystic River Consulting | $100K saved in a few days [Jędrzej SzymulaContent Manager ](https://www.flobotics.io/our-editorial-team#jedrzej) Published August 01, 2022Updated September 1, 2026 On this page - [Client](#client) - [The challenge](#the-challenge) - [The solution](#the-solution) - [The outcome](#the-outcome) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Client Mystic River Consulting acted on behalf of one of the top debt relief programs based in California, supporting large volumes of tax-related operations for end clients. ## The challenge The company needed to automate two highly labor-intensive processes: pulling client data from the IRS website and filing tax returns. Each step took approximately 45 minutes per client when done manually, and access to the IRS portal was limited to a single set of credentials, preventing parallel work. The situation was further complicated by COVID-19, which significantly disrupted IRS operations, increased processing backlogs, and temporarily prevented the client’s employees from working due to lockdowns. An additional technical challenge was automating two-factor authentication required for IRS access. ## The solution We deployed a coordinated network of RPA robots designed to work sequentially and in parallel. One robot handled logging into the IRS website, retrieving tax documents, scraping the required data, and passing it forward for processing. A second robot automatically filed tax returns for clients using Intuit based on the extracted data. To overcome two-factor authentication, the automation securely accessed a mobile device via VPN and captured rotating authentication codes generated every 30 seconds. The solution was built to be agile, reliable, and resilient under highly constrained operating conditions. ## The outcome During a period when manual operations were severely limited, the automation processed over 1,500 IRS data retrieval cases in just over a week. The first robot completed 1,657 cases with an average processing time of 6 minutes and 28 seconds per case, saving approximately 38.5 minutes per case and more than 1,060 hours of manual work. The second robot completed 2,600 tax return filings with an average processing time of 4 minutes and 25 seconds per case, saving an additional 1,755 hours. Combined, the two robots saved 2,818 hours of manual labor in one week, equivalent to more than 70 weeks of full-time work and over $100,000 in estimated labor cost savings based on median California salaries. The automation delivered continuity, speed, and accuracy at a time when traditional operations were not possible. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Written byJędrzej Szymula Content Manager . [More from Jędrzej](https://www.flobotics.io/our-editorial-team#jedrzej) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # UiPath vs. Power Automate - Which RPA Tool To Choose? Canonical: https://www.flobotics.io/blog/uipath-vs-powerautomate Author: Bart Teodorczuk Published: 2022-06-27 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/UiPath vs. Power Automate - Which RPA Tool To Choose? [RPA](https://www.flobotics.io/blog?category=rpa) # UiPath vs. Power Automate - Which RPA Tool To Choose? [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published June 27, 2022Updated September 1, 2026 On this page - [UiPath — flexible and solid industry leader](#uipath-flexible-and-solid-industry-leader) - [Power Automate — contender on the rise](#power-automate-contender-on-the-rise) - [UiPath vs. Power Automate — key differences](#uipath-vs-power-automate-key-differences) - [Pricing](#pricing) - [Maturity](#maturity) - [Community and developer pool](#community-and-developer-pool) - [Complexity](#complexity) - [Training resources](#training-resources) - [UiPath vs. Power Automate — what to choose?](#uipath-vs-power-automate-what-to-choose) - [Go for UiPath if:](#go-for-uipath-if) - [Choose Power Automate when:](#choose-power-automate-when) - [Final Word](#final-word) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Worth USD 3.4 billion as of 2022, [the global Robotic Process Automation (RPA) market](https://www.globenewswire.com/news-release/2022/01/06/2362208/0/en/Robotic-Process-Automation-Market-to-Hit-USD-23-9-Bn-by-2030.html) is expected to be near USD 24 billion by 2030. The speed and scale of this expansion are astonishing but plausible, as the RPA ecosystem presents organizations across all major industries with the tools to optimize tedious-but-crucial processes. This fact has led more executives to hire RPA developers in recent years. The growth in demand for process optimization tools has led to the emergence of RPA solutions that target different business segments, from healthcare to finances. Here, see what can be done in the finance and banking industry with Robotic Process Automation. Dozens of RPA systems exist, covering specific niches or serving as large platforms encompassing several industries. Two solutions stand out: UiPath and Microsoft Power Automate (formerly known as Microsoft Flow). Just one look at the influential reports from Gartner, Everest Group, and [Forrester](https://rpamaster.com/uipath-is-the-absolute-champion-in-the-forrester-wave-rpa-q1-2021-report/) helps understand their current role in the industry: UiPath is an RPA leader, while Power Automate is an aspiring contender. This guide will dive deeply into the UiPath vs. Microsoft Power Automate comparison. With our help, you can make an informed decision and opt for the tool that will work best for your business. ## UiPath — flexible and solid industry leader According to [Gartner’s Magic Quadrant for RPA 2021](https://www.gartner.com/en/documents/4004033), UiPath has solidified its top standing among other RPA providers, ranking #1. The provider has consistently competed head-to-head for the top spot with Automation Anywhere in the industry-guiding ranking since it was [first published in 2019](https://www.information-age.com/gartner-releases-first-ever-magic-quadrant-for-rpa-software-123483955/). UiPath owes its success in large part to its versatility. It’s a general-use, one-size-fits-all RPA tool that can be employed in virtually any industry and integrated easily into [various processes](https://www.flobotics.io/blog/what-processes-to-automate) and solutions. UiPath is fully scalable and can be successfully used by small and large organizations. Discover [SAP automation](https://www.flobotics.io/business-process-automation) with UiPath. Here are some of UiPath’s main strengths: - Industry leader — UiPath is widely recognized as the best RPA tool currently on the market. - Orchestrator — The platform is an intuitive, all-in-one RPA orchestration tool that allows users to provision, manage, and track bots from a single interface available in the cloud or on-premise. - Robust ecosystem — With add-ons such as TaskCapture, Automation Hub, or Test Suite, UiPath facilitates daily operations such as process documentation, pipeline management, or testing. - Embedded cognitive features — the use of AI-based tools allows UiPath to automate text processing (Document Understanding), build ML-powered workflows (AI Center), and deploy visual recognition bots (AI Computer Vision). - Task mining — this powerful tool is worth its price: it operates independently to identify the best automation candidates and provides extensive discovery reports. Fig. 01 · UiPath Key features UiPath: key features - Industry leaderOne of the best RPA tools on the market. - OrchestratorProvision, manage and track bots from one interface, in the cloud or on-premises. - Strong ecosystemTask Capture, Automation Hub and Test Suite support documentation, pipelines and testing. - Task miningFinds the best automation candidates and reports on them. - Built-in AIText processing, ML workflows and visual recognition bots. ## Power Automate — contender on the rise Power Automate’s case is a little different from UiPath’s. Rather than a dedicated RPA solution, Power Automate is a general automation component within the Microsoft Power Platform, including PowerBI, PowerApps, and Power Virtual Agents. In addition, it comes with a robust set of turnkey connectors that enable easy integration with other Microsoft tools such as SharePoint, Teams, or Outlook. Power Automate’s key features are: - Microsoft stack integration — Integration templates and full Microsoft environment support make Power Automate a good choice for companies that rely mostly on Microsoft tools. - Ease of use — Thanks to its simplicity, all employers can use Power Automate to automate small, everyday tasks. - Power Apps — This compact tool streamlines quick non-code automation of Microsoft 365-based processes, allowing non-technical users to bring up business tools they need for work quickly and without involving the IT team. - Multi-platform support — Power Automate is available on the web, desktops, and mobile devices, allowing users to create, trigger, and manage automation flows anywhere. - Built-in AI features — The platform has several pre-programmed and customizable AI modules that can handle text recognition, translation, category classification, and other tasks. Fig. 02 · Power Automate Key features Power Automate: key features - Microsoft integrationTemplates and full support for the Microsoft environment. - Easy to useAnyone can automate small everyday tasks. - Power AppsNo-code automation of Microsoft 365 processes without IT. - Built-in AIReady-made modules for text recognition, translation and classification. - Multi-platformCreate and run flows on web, desktop and mobile. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## UiPath vs. Power Automate — key differences You must consider many criteria when comparing two RPA platforms as different as UiPath and Power Automate. Here are eight factors we think are most crucial. Fig. 03 · UiPath vs Power Automate Differences UiPath vs Power Automate | UiPath | Power Automate | Type of process | Sophisticated processes | Simpler, everyday tasks | Tools and integrations | Advanced tools: Orchestrator, Task Mining, Test Suite, Task Capture, Automation Hub, Document Understanding, AI Center, AI Computer Vision | Microsoft integrations | Documentation | Large library of resources and training | Limited resources | Architecture | Flexible | Templates | Scalability | Scalable | May not be enough for bigger companies | Pricing | Depends on the licenses | Affordable | Target customer | From SMBs to enterprises | Mostly smaller businesses | Maturity | Mature industry leader | Relatively new contender | Capabilities UiPath is one of the most powerful RPA platforms, and its open-code nature makes it even more capable. The platform can automate even the most intricate, company-wide processes, and with support from experienced developers, you can adjust it to any purpose. With these features, it’s easy to understand why UiPath is the preferable RPA tool for mature enterprises. In contrast, Power Automate is all about everyday tasks. Its architecture isn’t as open as UiPath’s, which hinders customizability but makes the tool more approachable for citizen developers. In addition, its ease of use and robust templates library match the needs of smaller companies that seek to streamline simple workflows. But there is one scenario when Power Automate should be your pick – if your whole organization is based on Microsoft’s stack (Office 365, Azure, MS SQL, etc). It’s worth noting that just because UiPath and Power Automate target businesses of different scopes, it doesn’t mean they are limited to them. With some tweaking, you can use both platforms regardless of how big—or small—your organization is. ### Pricing Power Automate has several plans billed monthly that start as low as $15 per month, making it an affordable automation platform. However, note that the price depends on the number of users or flows, so the total cost can grow significantly as you scale up your automation scope. The power of UiPath comes at a cost. Sure, the monthly license price will vary depending on the project, but by choosing UiPath, you need to be ready to pay more. Remember, though, that automation is an investment; therefore, one should always weigh the price against the long-term gains of [RPA implementation](https://www.flobotics.io/blog/rpa-development-process). ### Maturity UiPath was founded in 2005 and has steadily built since. Over the years, UiPath has proven to be effective regardless of industry and organization size. Time and accumulated experience have allowed the UiPath team to develop a coherent vision for the platform’s future—and RPA. Being relatively new, Power Automate lacks that maturity. What it has instead is the backing of Microsoft and its worldwide presence. These two factors will stimulate Power Automate’s growth in the future. ### Community and developer pool As a more mature tool, UiPath has gathered a staunch base of users over the years. Publicity aside, this popularity has very tangible benefits. Thanks to the large community, new user-made UiPath flows roll out daily. This also means that it’s easier to [hire UiPath developers](https://www.flobotics.io/uipath-services) simply because there are more of them out there. Although Power Automate has been catching up to its competitors in many fields, it doesn’t have the same user base as UiPath. Due to that, there aren’t nearly as many Power Automate developers for hire and user-made flows available, although it is getting traction, especially for internal citizen developers. ### Complexity UiPath is a sophisticated tool requiring RPA expertise to fully leverage its versatility and capabilities. Studio X—UiPath’s no-code automation platform—addresses this issue to a certain extent, with no development skills needed. In more complex cases, business users will most likely rely on developers – working with skilled programmers gives broader control, facilitating customization and troubleshooting. Conversely, the ease of use for citizen developers is among the biggest advantages of Power Automate. Same as with UiPath, no programming skills are required to automate simple daily tasks due to pre-built code blocks, native integration with Microsoft 365, and a drag-and-drop interface. However, relying on templates shows Power Automate’s limits when building more complex flows. ### Training resources Education is one of the cornerstones of UiPath’s efforts to build an image of experts on everything RPA. Its UiPath Academy is full of resources covering both the tool and the basics of RPA. It’s the perfect place to get started with the topic from complete zero—and completely free. Although you can find Power Automate documentation on Microsoft’s Docs website, it’s limited to manual-like instructions for the platform without getting into too much detail about RPA. There are also third-party courses available on e-learning portals. ## UiPath vs. Power Automate — what to choose? Now, the time has come to give you the answer you’re here for. And the verdict is… it depends, as both tools are used in different scenarios and projects. That being said, there are some general rules of thumb. ### Go for UiPath if: - It would be best if you automated complicated processes that encompass the entire company. UiPath’s adaptable architecture can help your company streamline tasks many other tools can’t. - You plan to scale up the automation of your workflows. Even if you start small, UiPath is a great Power Automate alternative since the latter may not be enough for long-term RPA expansion. - You’re going to use any of its advanced features. Orchestrator and Task Mining make UiPath stand out, and they’re just two modules in their arsenal. ### Choose Power Automate when: - Your tech stack is built mostly on Microsoft applications. Integrations with the MS ecosystem are one of Power Automate’s main strengths, so not using them would be a huge waste. - You’re looking for an affordable but solid RPA tool. Power Automate brings a lot of value for its cost—given that you’re using Microsoft apps. - You want to focus on citizen developers and simple tasks. Automation of everyday flows is the main purpose of Power Automate, and it’s just the tool for that. ## Final Word Our UiPath vs. Power Automate comparison shows that no two RPA tools are the same. That’s a good thing—these differences allow every business to find a solution that’s perfectly cut for its needs. That’s why, even though UiPath is the tool of choice at Flobotics, we can’t deny the potential of Power Automate. No matter if you want to hire RPA consultants or need professional assistance to decide what and how to automate, let’s get in touch. We’re sure that together we’ll come up with an RPA solution that saves you time, money, and effort. #### Like the article? Spread the word At Flobotics we specialize in automating processes that mattersmost in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### RPA Reloaded: 50+ Robotic Process Automation Statistics to Know in 2026 RPA statistics 2026: 50+ data points on robotic process automation adoption, ROI, and where the technology is headed next. Yana PokoraApril 15, 2025 ](https://www.flobotics.io/blog/rpa-statistics)[ RPA ### How to Measure RPA Success: A Guide to Robotic Process Automation Metrics How to measure RPA success: the key business and technical metrics to track ROI and prove your automation program is profitable. Bart TeodorczukDecember 23, 2021 ](https://www.flobotics.io/blog/rpa-successs-metrics)[ RPA ### Automation’s for Everyone: 100 Real-World RPA Use Cases Across Industries | 2026 RPA use cases across industries: see 100 real-world examples of process automation in action, from healthcare to manufacturing. Michał RejmanFebruary 23, 2024 ](https://www.flobotics.io/blog/rpa-use-cases-across-industries) [All articles →](https://www.flobotics.io/blog) --- # Revenue Cycle Management Automation in Healthcare – Everything You Need to Know Canonical: https://www.flobotics.io/blog/what-is-revenue-cycle-management Author: Bart Teodorczuk Published: 2022-06-08 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Revenue Cycle Management Automation in Healthcare –… [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Revenue Cycle Management Automation in Healthcare – Everything You Need to Know [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published June 08, 2022Updated September 1, 2026 On this page - [Revenue Cycle Management in healthcare & medical billing](#revenue-cycle-management-in-healthcare-medical-billing) - [Revenue Cycle Management systems — what they are and how they can help?](#revenue-cycle-management-systems-what-they-are-and-how-they-can-help) - [Choosing the right RCM automation tool](#choosing-the-right-rcm-automation-tool) - [Robotic Process Automation](#robotic-process-automation) - [Machine Learning](#machine-learning) - [Optical Character Recognition](#optical-character-recognition) - [Natural Language Processing](#natural-language-processing) - [Intelligent Automation](#intelligent-automation) - [The benefits of RPA in Revenue Cycle Management](#the-benefits-of-rpa-in-revenue-cycle-management) - [How to use RPA in Revenue Cycle Management?](#how-to-use-rpa-in-revenue-cycle-management) - [Conclusion](#conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Healthcare is, and should always be, primarily about health. But the inescapable truth is that all medical services cost money. This obvious fact has led to the developing of a robust IT infrastructure that manages the healthcare revenue cycle, from handling insurance claims to collecting payments. The whole process is a sequence of numerous tightly interdependent steps. Its complexity leaves room for optimization and very little room for error. Smooth Revenue Cycle Management (RCM) is critical for effective healthcare and reducing revenue leakage, but surprisingly few industry leaders perceive its importance. For example, a 2020 report showed that [87% of providers still used manual and paper-based processes for collections.](https://revcycleintelligence.com/news/patient-collections-takes-over-a-month-for-most-providers) The consequences? 78% claimed they failed to collect payments over $1,000 within 30 days. Add [fluctuations in healthcare spending](https://www.healthcarefinancenews.com/news/health-spending-grew-34-2021-altarum-report-finds), and you have a recipe for an unstable and inefficient system from the perspective of patients and providers alike. Even though the pandemic has undoubtedly increased the level of digitization in healthcare organizations, many still rely on manual revenue management operations. Luckily, solutions exist that can be easily adopted and don’t require a massive investment in complex IT infrastructure setup or maintenance. This article will explore some of them, discussing RCM systems for medical services and suggesting how your medical organization can benefit from [Revenue Cycle Management automation](https://www.flobotics.io/rcm-automation). Learn more about using Robotic Process Automation in other industries, like RPA in insurance, RPA in logistics, or automation for consultancy. ## Revenue Cycle Management in healthcare & medical billing Revenue cycle management refers to all the administrative tasks devoted to financial transactions between patients and their providers and how they are handled. The key processes in RCM are: Pre-authorization — the process starts when a patient makes an appointment. To set up a patient account, the provider must gather and register all the necessary data, such as personal info and medical records, and assess the patient’s insurance eligibility. Medical coding — next, medical data like test results, diagnoses, or procedures are translated into a unified code. This standardized system facilitates communication between physicians, office staff, insurance companies, and various healthcare providers involved in the treatment. Claims submission — a coded record of the patient’s treatment is submitted to their insurer, who then reviews and approves or denies the claim. Payment collection — if the insurer reviews the claim positively, the provider receives reimbursement. The amount depends on the patient’s eligibility, as insurance doesn’t always cover the amount due. If so, the provider must follow up with the patient and collect the rest of the payment. Service review and reporting — once the payment is complete, the data used in the revenue cycle and clinical treatment is analyzed. This process ensures insight into possible issues and methods of overcoming them to streamline the entire process. At this stage, it’s important to note that even though the term revenue cycle management is often used interchangeably with medical billing, the two aren’t synonymous. Fig. 01 · RCM Cycle The revenue cycle in healthcare - 01Pre-registrationCollect information before the patient arrives - 02RegistrationCollect the rest at registration - 03Utilization reviewCheck medical necessity - 04Charge captureTurn services into billable charges - 05CodingCode diagnoses and procedures - 06Claim submissionSend claims to insurers - 07Remittance processingApply or reject payments - 08Third-party follow-upCollect from third-party insurers - 09Patient collectionsWork out balances and collect - 10ReportingTrack and improve the cycle Then the cycle starts again with the next patient RCM encompasses all the processes mentioned above, while medical billing refers only to those concerned directly with claims, i.e., coding, submission, and payment collection. In that view, RCM is a broader, end-to-end workflow that includes billing as an important part. The revenue cycle is affected by many unpredictable, shifting factors that can be internal or external. These moving parts often complicate revenue cycle management, making many cases wholly unique. Fig. 02 · RCM Internal and external Factors that affect RCM Internal - Provider's productivityBack-office efficiency sets how many claims you can process - Patient volumeMore patients can strain billing staff - Fees and expensesBilling costs grow as RCM scales External - Patient paymentsMissing patient information and other issues hurt collection - ClaimsUp-to-date information is key to clean claims - ReviewsSlow, and slower without accurate data - Insurance companiesProcedures differ between insurers - Taxes and extra feesPayments outside your control add up ## Revenue Cycle Management systems — what they are and how they can help? Revenue Cycle Management software aims to digitize and replace paper-based procedures and documentation in the revenue cycle workflows. Think of it as the [EHR](https://www.flobotics.io/rcm-automation) of medical billing and claim management. According to a [2021 forecast](https://newsroom.technavio.com/news/healthcare-revenue-cycle-management-rcm-software-market), the Revenue Cycle Management software industry is expected to grow by 10% annually through 2021 and 2025. This and other research prove that the demand for RCM solutions is rising. And for a good reason. Revenue Cycle Management systems assist the back-office staff in many essential tasks within the revenue cycle management, such as: - checking eligibility, - claim correction and tracking, - KPI reporting, - data entry, - medical coding, - denial management and alerts, - contacting patients and insurers, - cost estimation. … and more. They achieve all that by leveraging innovative technologies — including Revenue Cycle Management automation. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Choosing the right RCM automation tool Many RCM processes —[medical billing in particular](https://www.flobotics.io/blog/how-to-build-automated-medical-billing-system)— can be optimized with the help of intelligent software. What’s more, algorithms can entirely take over the execution of some simpler tasks. Here are the most popular solutions used for revenue cycle management automation. ### Robotic Process Automation The name says it all— [Robotic Process Automation](https://www.flobotics.io/blog/robotic-process-automation) (RPA) systems use pre-programmed scripts to handle repetitive, rule-based, high-volume tasks. Many stages in the healthcare revenue cycle are the perfect fit for RPA: scheduling, claims tracking, invoice processing, and most [medical billing](https://www.flobotics.io/blog/how-to-build-automated-medical-billing-system) functions. Read more about [medical coding automation](https://www.flobotics.io/rcm-automation) to know how RPA can help and the RPA development process. ### Machine Learning Machine learning (ML) algorithms thrive on large amounts of data that hospitals, clinics, doctor’s facilities, and medical research centers can use to boost decision-making capabilities. In RCM, machine learning can help recognize claims likely to be denied before they are submitted and recommend corrections. Another example is predicting patient outcomes to help providers make informed decisions when handling risk-based cases. ### Optical Character Recognition Optical character recognition (OCR) is a technology that scans documents and images to extract text and convert it into a digital format. OCR programs are commonly used in healthcare to quickly fill prescriptions, medical records, or other documentation. Faster data entry allows for massive time savings in many RCM-related tasks, such as pre-registration, claims submission, or coding. ### Natural Language Processing Like OCR, natural language processing (NLP) enables faster data extraction. However, rather than scanning the entire text, NLP-based tools focus on identifying key terms in unstructured data, such as doctor’s notes. Unstructured data is great when dealing with complex, unique cases, but it usually takes longer. Capable of capturing more sophisticated texts, NLP allows medical staff to communicate naturally without compromising billing and coding efficiency. ### Intelligent Automation Last but not least, intelligent automation (IA) is the ultimate combination of other automation solutions. They are deployed as a single high-synergy system that is efficient, smart, self-learning, and can deal with any data. When used in RCM, IA combines the best of all worlds. For example, AI can go through patient data extracted and formatted by OCR/NLP in search of repeating patterns. The AI then identifies standard procedures that can be delegated to efficient, pre-programmed RPA bots. ## The benefits of RPA in Revenue Cycle Management While the above solutions find use in revenue cycle management automation, they vary in deployment complexity and day-to-day operations. RPA usually requires the least effort and investment of all five while promising relatively fast ROI. That’s not to say that RPA implementation is easy. On the contrary, a recent survey by [Becker’s Hospital Review](https://go.beckershospitalreview.com/rpa-in-the-revenue-cycle:-what-u.s.-health-system-leaders-shared-about-automation?hs_preview=PrOFYIDn-65855602779) reveals that although 51% of providers incorporate some form of RPA in their systems, just 7% would classify the adoption as “mature” and 33% as “robust.” Still, when you are supported by a trusted team of automation experts, deploying the robotic process automation revenue cycle is a great first step toward further automating your financial operations. That’s because revenue cycle management, by its nature, is: 1. Repetitive — sending invoices, receipts, payment reminders, verifying patient data, and checking regulation compliance — are some tedious daily billing operations that RPA bots excel at. 2. Stage-based — as a whole, the revenue cycle is complex but consists of numerous simpler steps. Many of these stages can be managed by bots, allowing your staff to focus on other, more demanding tasks. 3. Prone to error — since scripts don’t get tired and don’t lose focus, they’re less likely to make typos or leave form fields unfilled. They can assist human billers in complicated cases, suggesting corrections and insights. 4. Costly — MGMA estimates that 2020 the US healthcare industry lost over $16 billion due to revenue cycle inefficiencies. Many of them could have been resolved with [automated revenue cycle management](https://www.mgma.com/resources/revenue-cycle/how-much-revenue-is-your-healthcare-practice-losin). ## How to use RPA in Revenue Cycle Management? Using RPA opens up new opportunities to optimize the processes within the revenue cycle. Here are some of them: Faster cost estimates — automating the benefits retrieval process will expedite cost estimate turnover. Pre-authorization assistance — RPA bots pull patient data from other systems and upload them directly into your Hospital Information System (HIS), reducing delays. Enhanced patient communication — RPA will automatically schedule meetings and send patients reminders or recaps of the information shared on a phone call. Automated data entry — RPA can integrate the data from various sources into your system faster and more precisely, preventing simple errors and resulting denials. Compliance — by reducing manual processes, RPA helps providers avoid errors and assure compliance with HIPAA and other regulations. Handling orders and referrals — manually reviewing referrals and orders creates further delays in the revenue cycle. In contrast, RPA handles order scheduling and confirmation, enabling a smoother RCM. Claim denials management — simple cases of claim denials can be handled entirely by RPA bots while your staff works on the more complicated ones. [RPA for claims processing](https://www.flobotics.io/agents/claims-management-automation) is also a great decision that will boost your company’s productivity Third-party integrations — efficient RCM often requires multiple tools from different providers. RPA ensures that all of them work together seamlessly. Improved patient experience — RPA revenue cycle ensures faster claim processing, improved communication, and higher efficiency, encouraging patients to choose you over other healthcare providers. Discover [SAP Automation](https://www.flobotics.io/business-process-automation) with UiPath and Flobotics. ## Conclusion With constant regulation changes, cost fluctuations, and unforeseeable challenges like COVID-19, delivering high-quality medical services isn’t possible without a stable financial infrastructure. For this reason, healthcare leaders are adopting automated solutions that allow for efficient and secure revenue cycle management. Suppose you’re looking for a trusted partner to automate your organization’s RCM systems; contact us at Flobotics. We have vast experience working with medical companies and believe in the ROI-first approach — we always consider the costs and potential gains to help our clients save and earn as much as possible. #### Like the article? Spread the word Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RCMHealthcare ### Revenue Cycle Management (RCM) in Healthcare Revenue cycle management, explained: how US hospitals and practices stay compliant with payer policy and keep cash flow steady in 2026. Bart TeodorczukSeptember 30, 2024 ](https://www.flobotics.io/blog/revenue-cycle-management)[ RCMHealthcare ### Key Revenue Cycle Management Metrics | 2026 Revenue cycle management metrics: the 25 KPIs healthcare leaders track in 2026, from denial rate to days in A/R and collections. Karl MielnickiAugust 26, 2025 ](https://www.flobotics.io/blog/revenue-cycle-management-metrics)[ RCMHealthcare ### How to Improve Revenue Cycle Management: 8 Strategies for Healthcare Leaders Revenue cycle management strategy: 8 practical steps healthcare leaders can use to boost collections and speed up the revenue cycle. Krzysztof SzwedJune 25, 2025 ](https://www.flobotics.io/blog/revenue-cycle-management-strategy) [All articles →](https://www.flobotics.io/blog) --- # How to Find and Hire a Great RPA Consultant Canonical: https://www.flobotics.io/blog/how-to-find-and-hire-a-great-rpa-consultant Author: Karl Mielnicki Published: 2022-05-19 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/How to Find and Hire a Great RPA Consultant CTO Notes [RPA](https://www.flobotics.io/blog?category=rpa) # How to Find and Hire a Great RPA Consultant [Karl MielnickiCTO & Co-Founder of Flobotics](https://www.flobotics.io/our-editorial-team#mielnicki) Published May 19, 2022Updated September 1, 2026 On this page - [What is an RPA consultancy all about?](#what-is-an-rpa-consultancy-all-about) - [What RPA services do RPA consultants provide?](#what-rpa-services-do-rpa-consultants-provide) - [How to choose the right RPA consultant (RPA consultancy’s criteria)?](#how-to-choose-the-right-rpa-consultant-rpa-consultancys-criteria) - [Where to find the RPA Consultancy’s best fit?](#where-to-find-the-rpa-consultancys-best-fit) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What is an RPA consultancy all about? Like most companies, yours as well relies on certain tasks and processes that don’t always require a specialist’s attention. Some of these can probably easily be automated, making them faster, cheaper, and less prone to making mistakes. Robotic Process Automation is one of the technologies that can help you with just that. RPA can bring the maximum value to the finance and banking, healthcare, manufacturing, insurance and many others. If you have a strong team of developers (preferably: automation developers) in your company – that’s great. You have probably conducted some process audits, built your first automation, and maybe even set up a Center of Excellence. However, if you are just at the beginning of the process automation road, you probably feel a bit lost and confused about what should you automate, how to start, and if this type of technical solution is even suitable for your company. If that’s the case, RPA consultancy is a great way to begin! ## What RPA services do RPA consultants provide? Who are RPA consultants? These are seasoned RPA development experts, who combine technical knowledge (coding, tools) with business expertise. They are able to look at your company as a whole, map processes, analyze them and identify the biggest automation opportunities: ones that will bring you the biggest ROI, unlock the fastest growth potential or remove the most painful bottlenecks in your process. RPA consultants provide a wide range of services to fill the role and carry out the responsibilities which include but are not limited to: Using RPA software, assisting in the resolution of challenges that emerge in day-to-day activities keeping in mind that automation is not done for the sake of automation. Automation is done to make our lives easier. Hence, if automating a task will somehow introduce more complexity or workload, then the conventional way of doing it is the optimum setup for now. ・Understanding, analyzing, and documenting all current business processes that are business-as-usual at the client’s side. ・Establishing an overall automation strategy for the client by creating several operational models for assessment. ・Determining the technical infrastructure needed for the implementation of the agreed-upon automation solutions. ・Providing training for the personnel and assisting in the creation of an “RPA-friendly” workplace in which each team member seeks out more automation possibilities to contribute to the company’s transition & overall continuous growth and development. ・Creating and documenting test scenarios and processes to achieve the optimum setup. Leading PoCs (Proof of Concepts) whenever a new solution is assessed to make sure it’s technically feasible and would provide the benefits needed. ・Educating our clients on how to design, operate, and maintain automation systems to enable the success of the RPA adoption strategy. ・Auditing your current automation RPA setup (bots, licenses, etc.) and proposing improvements. Ensuring legal and regulatory compliance before deploying to the production environment to avoid any complications down the road. ・Further corporate support for the deployment of any form of automation technology. Assisting in the planning and establishment of Centers of Excellence or Process Mining Hubs to aid in the automation of processes. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## How to choose the right RPA consultant (RPA consultancy’s criteria)? It’s not optimal to just hire the first RPA consultant that comes your way! Consultants need to be qualified to lead such roles, that’s why we’re showing here the best-in-class criteria needed in an RPA Consultant. Your future RPA consultants should have a track record of successful project implementation with real tangible deliverables. Make sure to check their current/previous places of work. For example, there are several consulting companies hiring and training RPA developers that have a rigid reputation, such as the “Big Four” club members: PwC, EY, Deloitte & Accenture. If you consider hiring a consultant who has experience working for one of these companies, this is a strong indicator of her/his expertise. Let’s take a look at other must-haves while choosing the right RPA consultant: 1. Project delivered/success stories A track record that is tangible and measurable to actually assess the outcome of previously delivered projects is necessary before hiring a consultant to make sure they’re a good fit for the role and have successful cases in their portfolio. 2. Opinions, testimonials Having feedback & reviews from former clients is really useful in such a case. There are several platforms that have this capability like Clutch and Upwork. 3. Knowledge - Technologies they know about and tools they used in previous projects are ordered according to skill level from expert to beginner. - Education and technical background are necessary for filling such a critical role. 4. Business background and business-first principle: Technical skills are crucial for the role but you can’t only rely on them. A business sense and/or experience are also needed to make sure that the delivered project achieves its business outcome. 5. Hiring cost: Hiring consultants can have various costs depending on the region (i.e., consultants from Central-East Europe charge less than their counterparts from the US and/or Western Europe while providing top-quality as the CEE region is famous for its amazing developers, after all) 6. Company culture fit: Consultants should be comfortable working in such an environment & atmosphere without feeling like outliers. 7. Working within the right time zones: i.e., Middle East time zones are much more convenient to be working with European time zones, etc. 8. Partnerships, certifications: Consultants are preferably certified from well-known institutions (i.e., RPA Consultant UiPath who is a UiPath silver partner/UiPath certified) 9. Industry Knowledge: Consultants shall have an overall good level of knowledge of your industry (i.e., telecom, banking, healthcare, etc.) as well as its challenges and its most popular solutions. 10. Legal landscape knowledge: This is necessary to avoid any legal complications down the road. ## Where to find the RPA Consultancy’s best fit? There are several ways to find the best-in-class consultants in your area which include: Online Freelancers’ platforms (Upwork, Fiverr, Freelancer):Consultants shall have an overall good level of knowledge of your industry (i.e., telecom, banking, healthcare, etc.) as well as its challenges and its most popular solutions. Big Consulting Firms (EY, Deloitte, etc.): Almost guaranteed quality but it’s also very expensive for SMEs and rather targeted at bigger companies/corporates. Classic software development agencies: Sometimes software development agencies have RPA in their offer where they can outsource the RPA-related projects to an external consultant due to their missing expertise in the domain while trying to keep up with the competition providing such services. RPA consulting companies and agencies: Considered to be the best pick since they are specialized in RPA and can provide an individual consulting approach to small and big players. They are usually equipped with experience and the business knowledge needed to achieve such an outcome. (Yes, these are the kind of experts we hire at Flobotics). Let's start with automation! The RPA is disrupting industries all over the spectrum. Are you ready to join the race? At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byKarl Mielnicki CTO & Co-Founder of Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### RPA Failures: 10 Most Common Reasons and How to Avoid Them RPA failures: Flobotics' CTO breaks down the 10 most common reasons automation projects fail and how to avoid them. Karl MielnickiJuly 06, 2021 ](https://www.flobotics.io/blog/rpa-failures)[ RPA ### RPA in Supply Chain Management: Pros, Cons and The Best Use Examples RPA supply chain use cases: pros, cons, and real examples of how automation cuts costs across the logistics industry. Michał RejmanMay 07, 2021 ](https://www.flobotics.io/blog/rpa-in-supply-chain-management-use-examples)[ RPA ### RPA in Real Estate and Property Management: Benefits, Applications, and Use Cases RPA in real estate and property management: explore real automation use cases and see how firms cut manual work across leasing and maintenance tasks. Michał RejmanSeptember 26, 2022 ](https://www.flobotics.io/blog/rpa-in-real-estate) [All articles →](https://www.flobotics.io/blog) --- # Medical Coding Automation: Why (and How) Should You Start? Canonical: https://www.flobotics.io/blog/medical-coding Author: Karl Mielnicki Published: 2022-05-13 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Medical Coding Automation: Why (and How) Should You Start? CTO Notes [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # Medical Coding Automation: Why (and How) Should You Start? [Karl MielnickiCTO & Co-Founder of Flobotics](https://www.flobotics.io/our-editorial-team#mielnicki) Published May 13, 2022Updated September 1, 2026 On this page - [Medical coding — what can you automate?](#medical-coding-what-can-you-automate) - [Medical coding automation tools](#medical-coding-automation-tools) - [1. Computer-assisted coding (CAC)](#1-computer-assisted-coding-cac) - [2. Artificial intelligence](#2-artificial-intelligence) - [3. Robotic Process Automation](#3-robotic-process-automation) - [The benefits of RPA in medical coding](#the-benefits-of-rpa-in-medical-coding) - [Compliance and correctness](#compliance-and-correctness) - [Increased efficiency](#increased-efficiency) - [Cost savings and revenue optimization](#cost-savings-and-revenue-optimization) - [Improved patient experience](#improved-patient-experience) - [Medical coding automation step by step](#medical-coding-automation-step-by-step) - [2. Automation roadmap](#2-automation-roadmap) - [3. Test automation](#3-test-automation) - [4. Deployment](#4-deployment) - [5. Maintenance and improvement](#5-maintenance-and-improvement) - [Conclusion](#conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Healthcare and automation? For many, the two remain an unlikely couple. The knee-jerk reaction to “automation” is to think of industries like banking, finance, manufacturing, logistics, or retail. A few will associate the medical sector with robotics. On the surface level, it’s easy to see why healthcare is inherently more human-centered compared to other industries. That’s because health is a delicate matter and should be handled with exceptional empathy, care, and expertise that only living and breathing doctors, nurses, technicians, caregivers, and other staff can ensure. However, any healthcare executive knows that no medical procedure could be delivered without dozens of menial back-office tasks. These necessary chores take hours, diverting medical staff from providing care and taking a heavy toll on their efficiency. The good news is that these are precisely the tasks that can be automated. Repetitive, patterned, and prone to errors, insurance billing, and coding are fundamental activities that modern healthcare businesses delegate to [Robotic Process Automation](https://www.flobotics.io/blog/how-to-build-automated-medical-billing-system) (RPA). What is involved in the process, and how do hospitals, practices, and healthcare professionals benefit? Let’s dive into medical coding automation and its implementation, from discovery to continuous development with experienced [RPA consultants](https://www.flobotics.io/about-us). Despite its significant role in the healthcare and insurance industries, medical coding is often put down as another back-office job. While this is a huge generalization, there’s one truth: medical coding is foundational for the efficiency of healthcare-related processes. First, we can’t delve into medical coding without mentioning [medical billing](https://revcycleintelligence.com/features/exploring-the-fundamentals-of-medical-billing-and-coding). The two go hand in hand, and the same person often performs both tasks (especially in smaller practices). However, the scope of the two activities is quite different. The main activities within the [medical coding business](https://www.aapc.com/medical-coding/medical-coding.aspx) are the interpretation of patients’ diagnoses, test results, and procedures and converting them into one of the standardized classification systems, such as the International Classification of Diseases (ICD), Current Procedure Terminology (CPT), or Healthcare Common Procedure Coding System (HCPCS). Next, medical billers use these codes to handle insurance claim submission, reimbursement, and billing patients for medical services. Also, medical billing relies on the data translated by medical coders, facilitating communication between healthcare providers, patients, and insurance companies. On the other hand, [medical billing](https://www.flobotics.io/rcm-automation) is just one of the many applications of codified medical records. Between EHR, insurance claims, administrative data, surveys, and trials, there’s a massive amount of data to process in healthcare daily. In this context, having a set of unified codes instead of thousands of terms for procedures, medications, and conditions is a true lifesaver when managing the information flow. It supports: - Patients receive better and faster care, particularly when several healthcare providers are involved in their treatment. - Physicians can focus on delivering care rather than decoding abbreviations and acronyms in the records transferred from another practice. - Administrative staff, who work more efficiently, benefit from streamlined data entry, billing, and compliance assurance procedures. Medical coding helps ensure that all parties in a healthcare ecosystem stay on the same page and communicate smoothly and efficiently. ## Medical coding — what can you automate? All of that sounds great, but it’s important to remember that such an efficient flow of healthcare data is only possible thanks to the everyday work of medical coders. Unfortunately, similar to medical billers, their job can get very repetitive. The usual workday of a medical coder consists of going through medical records, interpreting them, and assigning them appropriate codes. It is an arduous task and one prone to errors, especially after several hours of mapping lines of text to digits. Thankfully, automated bots are capable of assisting coders with many of these tasks: - Text recognition capabilities allow bots to scan and extract structured medical data from documents. - The bot then analyzes the abstracted information and searches the code base for the one corresponding to the data. - Finally, the bot handles data entry, filling the chart into a billing system. Read more about [claims processing automation](https://www.flobotics.io/agents/claims-management-automation) and find out how it can improve your claims management immediately. Pre-programmed scripts have a proven track record of handling similar duties in related fields, from [medical billing](https://www.flobotics.io/blog/how-to-build-automated-medical-billing-system) to [insurance](https://www.flobotics.io/blog/rpa-in-insurance-use-cases). Fig. 01 · RPA Coding and billing What RPA can automate in medical coding and billing Medical coding - 01Data entry - 02Data extraction - 03Assigning codes - 04Structured data analysis Medical billing - 01Registration - 02Claims processing - 03Appointment scheduling - 04Adjudication - 05Patient statements Before you conclude that medical coders will soon become obsolete, there’s one important caveat. While many records fall into a predefined category, they can get tricky when patients have a long and winding medical history. In such cases, the expertise of a trained, highly-qualified human coder is crucial. For this reason, as medical coding automation progresses, we’ll still see human coders. The US Bureau of Labor Statistics predicts a [9% employment increase for medical tech specialists](https://www.bls.gov/ooh/healthcare/medical-records-and-health-information-technicians.htm#tab-6), including coders. However, rather than being replaced by bots, they will work in tandem with them as auditors. The result? A human-machine dream team that can process code with far greater speed and precision than one person alone. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Medical coding automation tools The word “automation” is an umbrella term that covers multiple solutions. The three most relevant to the [medical coding automation](https://www.flobotics.io/rcm-automation) business are computer-assisted coding (CAC), AI, and RPA. These technologies are poised to define the [future of back-end healthcare automation](https://www.forbes.com/sites/tomdavenport/2020/01/03/the-future-of-work-now-medical-coding-with-ai/?sh=be36fc5282cb). ### 1. Computer-assisted coding (CAC) First off, there’s [computer-assisted coding, or CAC](https://www.foreseemed.com/computer-assisted-coding). It is a solution that uses natural language processing (NLP) to enable faster and easier coding of unstructured data. The tool works like a spell checker for medical records, analyzing documents in search of words and phrases related to the classification and using them to suggest which medical code should be produced. Thanks to NLP, CAC can distinguish between phrases that include the same keywords but have different meanings due to their context. For instance, CAC will suggest a code when it detects the name of a diagnosed condition but not when it appears in the patient’s family history. ### 2. Artificial intelligence AI attempts to take the improvements of CAC one step further by adding machine learning to the mix. AI leverages learning capabilities to remember corrections made by human coders and apply them in similar cases in the future. It can also analyze legacy documentation to identify patterns and make predictions, e.g., evaluating the likelihood of readmission. Applying AI to data processing solutions results in much faster, more accurate, and autonomous software when dealing with unstructured (often highly illegible) data such as doctor’s notes. Though AI-powered medical coding solutions have yet to achieve total autonomy, it’s only a matter of time before they become an essential tool in medical coding. All that power, however, comes at a cost. As a complex solution, AI requires much more computing power, high-quality data, and data science experts throughout its lifecycle. Therefore, for the moment, complex machine learning systems are only available to large, well-founded healthcare institutions that lead the way in innovation. Fortunately, another solution is much more affordable and easier to implement in healthcare facilities that operate on tight budgets and cannot dream of hiring medical data analysis experts. ### 3. Robotic Process Automation The specific features of medical coding make it the perfect candidate for [RPA-driven optimization](https://www.flobotics.io/blog/robotic-process-automation): - It’s repeatable — medical coding is a recurring data extraction, analysis, and entry cycle. These smaller processes can be successfully delegated to RPA systems. - It’s rules-based — when programmed to follow simple logic and custom, predefined rules, RPA bots can easily manage the medical coding workload. - It uses high volumes of data — medical coding involves lots of structured data that constitutes the bulk of medical documentation and can be quickly processed by RPA scripts. Even though RPA lacks AI’s decision-making and learning skills, it more than makes up for it with efficiency when handling simple workflows and heavy amounts of textual data. RPA is also a comparatively affordable solution requiring qualified personnel only for deployment and maintenance. Once deployed, non-technical personnel can easily operate Robotic Process Automation systems. Learn more about [5 processes for the healthcare industry you didn’t know could be automated](https://www.flobotics.io/blog/healthcare-workflow-automation). ## The benefits of RPA in medical coding Since medical coding affects many healthcare activities, optimizing it via RPA will have positive consequences for the entire organization. Let’s review the top benefits that RPA can bring to medical organizations. ### Compliance and correctness Even though medical coding is the driving force behind simplifying other medical processes, the code systems have grown in size and sophistication. For instance, [the most recent version of ICD](https://www.who.int/news/item/11-02-2022-icd-11-2022-release) contains around 17,000 unique codes and a staggering 120,000 codable terms. With numbers, these vast errors will eventually sneak in, even when working with seasoned coders. Immune to routine and distraction, RPA eliminates human error from the equation. That’s extremely important in an industry where finance, health, and regulations are all involved. ### Increased efficiency With RPA scripts, medical coders can process more charts per day. As a result, they don’t need to pay much attention to simple, common cases and are more focused on complex ones. The additional benefits are better working comfort and lower fatigue, invaluable gains in the working environment where professionals [experience severe burnout and exhaustion](https://www.beckershospitalreview.com/hospital-physician-relationships/29-physician-specialties-ranked-by-2021-burnout-rates.html). RPA deployment will have an even greater effect on small practices that don’t always have a dedicated coder. Medical coding automation tools will free up their administrative, billing, and medical staff, giving them more time for other tasks. Having feedback & reviews from former clients is useful in such a case. Several platforms have this capability, like Clutch and Upwork. ### Cost savings and revenue optimization Repetitive tasks cost time and resources, so optimizing them for higher efficiency will translate into savings. At the same time, faster records processing allows healthcare organizations to handle more patients. But these aren’t the only ways to deploy RPA solutions in the context of medical coding that can help medical providers reduce costs and shorten the [revenue cycles](https://www.flobotics.io/rcm-automation). Think about claims management, for example. Inaccurate or wrongly coded claims delay revenue collection. By closing the door to potential errors and inaccuracies, RPA solutions streamline and speed up the process, enhancing the cash flow for providers. ### Improved patient experience Reducing the margin of error in coding and billing also helps patients focus on recovery rather than worrying about their insurance. In addition, faster record turnover and flow of information between providers lead to better care, especially when urgency is essential. Medical facilities can achieve these benefits by deploying RPA-based medical coding to enhance patient experience. ## Medical coding automation step by step Despite a relatively low technological barrier to entry of robotic process automation solutions, they are still sophisticated technology. RPA implementation is a complex process that’s best done one step at a time. Fig. 02 · Medical coding 5 steps Medical coding automation, step by step - 01AuditDiscover and evaluate - 02RoadmapSet goals and draw up a plan - 03TestingFind and fix automation errors - 04DeploymentLaunch the tested RPA - 05ImprovementKeep improving the process - Audit and discovery No two organizations are ever the same. That’s why research always precedes the implementation of RPA solutions. At this stage, the implementation partners like Flobotics audit and analyze currently used systems, evaluate existing workflows and data structure, define KPIs, and [identify high-impact automation candidates](https://www.flobotics.io/blog/what-processes-to-automate). ### 2. Automation roadmap We set objectives for each process and plan a schedule at this stage. Usually, we start from relatively easy tasks to automate; this way, any blockers are discovered and can be managed faster, so they don’t stand in the form of more complicated processes later on. ### 3. Test automation Before the actual deployment, RPA is tested for use in the organization-specific context. This step allows us to identify potential problems when they are easier to fix. ### 4. Deployment Following automation production, a Proof of Concept (PoC) build is deployed as the final trial before the solution goes live. Then, with the last tweaks done, the automation engine is ready. ### 5. Maintenance and improvement The de facto implementation is now complete. But as new challenges arise, RPA is adjusted and maintained to help you face them efficiently in the future. Additionally, updates can be made to support emerging use cases, optimize workflows, unburden staff, and increase revenue potential. ## Conclusion Medical coding is one of many repetitive but essential administrative tasks in healthcare that can benefit from robotic process automation. This shows that the potential for RPA to become an industry-defining tool is surely there. Affordable and effective, RPA is also the perfect stepping stone into the world of automation. So if you’re looking to optimize your medical insurance billing and coding workflows, you’ve found the right people for the job. [Send us a message](https://www.flobotics.io/contact) and discuss how we can make your organization more efficient by providing RPA consulting services. #### Like the article? Spread the word Written byKarl Mielnicki CTO & Co-Founder of Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RCMAIHealthcare ### Fixing Denial Codes | Agentic AI in Revenue Cycle Management Denial codes in healthcare billing: how AI automation fixes, resubmits, and prevents claim denials before they hit your revenue. Jędrzej SzymulaOctober 11, 2025 ](https://www.flobotics.io/blog/fixing-denial-codes-rcm-automation)[ RCMRPAHealthcare ### Medical Billing Management: Best Practices, Key Metrics and Automation Medical billing management: the 8-stage billing cycle, the metrics and reports that show revenue leakage, and 8 best practices to fix it. Yana PokoraJuly 25, 2023 ](https://www.flobotics.io/blog/medical-billing-management) [All articles →](https://www.flobotics.io/blog) --- # Payroll Process Improvement Ideas You Can Implement Canonical: https://www.flobotics.io/blog/rpa-payroll-process Author: Michał Rejman Published: 2022-02-07 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Payroll Process Improvement Ideas You Can Implement [Eligibility](https://www.flobotics.io/blog?category=eligibility) # Payroll Process Improvement Ideas You Can Implement [Michał RejmanChief Marketing Officer at Flobotics](https://www.flobotics.io/our-editorial-team#rejman) Published February 07, 2022Updated September 1, 2026 On this page - [What are the problems that companies face with the payroll?](#what-are-the-problems-that-companies-face-with-the-payroll) - [When is the right time to implement one of the payroll process improvement ideas?](#when-is-the-right-time-to-implement-one-of-the-payroll-process-improvement-ideas) - [How long ago was your payroll implemented?](#how-long-ago-was-your-payroll-implemented) - [Have you evaluated whether your payroll software matches your requirements?](#have-you-evaluated-whether-your-payroll-software-matches-your-requirements) - [Do your employees have easy access to the payroll system?](#do-your-employees-have-easy-access-to-the-payroll-system) - [Do all employees receive their salaries on the same day?](#do-all-employees-receive-their-salaries-on-the-same-day) - [Where is payroll automation within your current system?](#where-is-payroll-automation-within-your-current-system) - [Which payroll process improvement ideas should you consider?](#which-payroll-process-improvement-ideas-should-you-consider-in-2023) - [1. Automate repetitive payroll tasks with RPA](#1-automate-repetitive-payroll-tasks-with-rpa) - [2. Payroll Integration with external Systems](#2-payroll-integration-with-external-systems) - [3. Stay up-to-date](#3-stay-up-to-date) - [4. 24/7Access For Workers](#4-24-7access-for-workers) - [5. Provide a Great User Experience](#5-provide-a-great-user-experience) - [6. Make Your System Transparent](#6-make-your-system-transparent) - [7. Constant Review](#7-constant-review) - [Conclusion](#conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) No doubt that following the financially challenging years, we’re all feeling the pinch. Rather than crying over spilled milk, one way your company can save money is to improve, optimize and automate your payroll processes. If there’s anything you can do now, streamlining internal procedures to guarantee your organization is receiving the most value for money should be at the top of your list. Continue reading for a list of payroll process optimization suggestions to help you handle this aspect of your organization while saving you time and money. ## What are the problems that companies face with the payroll? [Payroll](https://www.investopedia.com/terms/p/payroll.asp) generally refers to the procedure for ensuring that your employees are paid on time. But why is it necessary to optimize it? Fig. 01 · Payroll 5 issues Common payroll issues Common payroll issues - 01Miscalculated overtime - 02Misclassified exempt workers - 03Wrong tax rates - 04Inaccurate worker classification - 05Late payroll Poor payroll systems and badly-design processes might cost your company a lot of money. While manually processing payroll may appear less expensive, coordinating data gathering, such as timesheets, takes time and requires experienced human resources. “Time is money,” as the saying goes. Manual payroll processing exposes your company to the danger of human mistakes, which may result in many issues. Consider the case where one of your employees, contractors, or business partners isn’t paid on time or receives an inaccurate paycheck. This might breed distrust and lead to losing faith in your company. In addition, this might lead to legal complications, which are always best to avoid in the first place. That’s why we are writing to you from our experience with all the Payroll Process Improvement Ideas we can propose for your system and business to thrive. ## When is the right time to implement one of the payroll process improvement ideas? You might need to assess several factors to have a solid answer. Here is a bunch of them: ### How long ago was your payroll implemented? With the huge technological developments and the rapid economic changes, you need to consider being up to date with all your systems, especially the payroll one. 3-5 years are more than enough to have a major upgrade in your approach to cope with the internal changes in the company like personnel expansion & regulatory changes. Also, the payroll system should abide by the tax regulations that change every few years. ### Have you evaluated whether your payroll software matches your requirements? We certainly hope you did! Requirements are pretty dynamic and in constant change. That’s why it’s necessary to assess your legal status, personnel number, expansion plans, updated tax regulations, and any changes in the company’s organizational structure and hierarchy that might trigger some changes in the payroll system. ### Do your employees have easy access to the payroll system? Easier said than done! Employees have the right to look at their status within the company at any point in time and have full access to their benefits, salaries, compensations, reimbursements, rewards, etc.… That must be done securely as it’s susceptible and confidential data, so no one should be granted access to such info except for their data only. ### Do all employees receive their salaries on the same day? Some companies have different pay schedules for employees. For example, part-time employees might receive paychecks once a month, whereas full-time workers get paid bi-weekly. Several pay cycles create more administrative work for payroll staff and exposure to possible human error. By synchronizing all pay schedules, the team can spend less time processing paystubs and sending out checks. ### Where is payroll automation within your current system? Automating your current payroll setup, your employees’ salaries will be processed automatically, and any raises or bonuses will automatically be added to monthly wages as soon as a member of management has registered them in the system. An automated & digital system has an additional benefit that we can’t ignore. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Which payroll process improvement ideas should you consider? ### 1. Automate repetitive payroll tasks with RPA RPA bots do the rule-based steps a person does on screen: updating payroll records after a raise or a reimbursement, checking time entries, loading earning and deduction batches, and year-end reconciliation. RPA doesn’t replace your payroll engine; it takes over the manual work around it. We cover this idea in detail, with the payroll tasks worth automating first and examples from Lenovo, BAE Systems and Global Upside, in our [guide to RPA in payroll](https://www.flobotics.io/blog/payroll-process-rpa). ### 2. Payroll Integration with external Systems Integrating your payroll processing system with time and attendance monitoring software is another way to improve its efficacy if you automate your complete payroll processing system. [Employee time and attendance monitoring](https://www.flobotics.io/blog/rpa-in-hr-and-recruitment) software, if you don’t already have it, helps you save money on labor by recording the amount of time your employees spend doing their jobs so you don’t have to. This software can replace manual data input with data collecting via devices like geofencing-enabled mobile applications, real-time reporting that syncs employee data in real-time, biometric authentication, and contactless punches. You can process monthly salaries faster and more precisely if you integrate your payroll system with this software and bring the two together in one platform. You’ll also be able to utilize data analytics to evaluate staff productivity and determine exactly what tasks your employees are working on. ### 3. Stay up-to-date Another way to improve payroll services and automation once you’ve automated your payroll process is to ensure you’re using the most recent version of the software. When programs need an update, they might start to operate slowly, so be sure you’re not wasting any time (and hence money) by doing so. If your payroll operations were previously automated, now is the time to upgrade to the most recent version of your program. Updates can also guarantee that applications work as efficiently as possible. ### 4. 24/7Access For Workers One of the most significant things your software may have when it comes to payroll process optimization ideas is the ability for employees to access and update the system at any time of day. For entering information regarding sick days, vacation days, and — if your payroll software is linked to time and attendance monitoring — when workers are clocking in and out — a cloud-based payroll system that anyone can access is critical. Your employees will notice more openness, which helps develop a sense of trust between management and employees. ### 5. Provide a Great User Experience With the above in mind, your employees must have a simple time navigating the payroll software. Nothing is more frustrating than a complicated system that is difficult to navigate for staff unfamiliar with the program. This will waste time for your HR department, which controls the software, and your employees, who have more vital responsibilities. If the payroll technology is going to be challenging for employees who aren’t as tech-savvy, be sure to draw up instructions on how to use the step-by-step payroll process and share them internally via communication channels. You might even arrange payroll software training classes, which you could refresh every few months or so as technology advances. ### 6. Make Your System Transparent Is your system simple enough for all staff to use? Transparency is at the heart of the finest payroll improvement solutions. Make a concerted effort to arrange regular meetings to inform employees about all corporate regulations influencing payroll. Develop written resources detailing the knowledge for simple reference in addition to training. It’s also a good idea to put the documents on display around the office. ### 7. Constant Review Last on our list of payroll process improvement ideas is to evaluate your payroll software regularly to ensure that it is compliant with state and federal tax laws. While keeping up with regulatory changes is a best practice in payroll processing, items can easily slide between the cracks. And, because laws are continually changing, your company might face legal action if it fails to comply with payroll tax obligations before you know it. Some payroll software will automatically update to reflect any legal changes, but if yours does not, be sure the team in charge of keeping it up to date is. Failure to comply might be a costly blunder for your company. Fig. 02 · Payroll 7 steps Payroll processing, step by step, and how to improve it - 01Collect employee tax informationImprove: automate data entry with RPA. - 02Manage recordsContracts, tax forms, handbooks, training. Improve: automate data entry with RPA. - 03Set pay schedulesImprove: connect time monitoring software. - 04Track time and attendanceImprove: connect time and attendance software. - 05Calculate deductionsImprove: automate the calculation with RPA. - 06Pay employeesImprove: connect payroll providers. - 07Submit payroll tax paymentsImprove: automate tax calculations with RPA. Also: keep software up to date, give 24/7 access, write playbooks and review compliance regularly. Looking for RPA opportunities in other industries? See what benefits can [automation in e-commerce](https://www.flobotics.io/business-process-automation) bring to your company. ## Conclusion Payroll’s job is going to become more ‘human’ than it has ever been. Teams from payroll will be on hand to share insight, engage, and enlighten coworkers. At the same time, technology such as RPA will handle the monotonous and administrative duties that currently consume their time. From our perspective, payroll has had to be one of the most adaptable departments for change. As a professional, you’re always forced to comprehend and apply new laws under tight timelines and communicate them to workers and business stakeholders in relevant ways. In a world of rising automation and robotics, the analytical and communication skills required in this process are – and will continue to be – vital, offering a ‘human’ touch. As more payroll teams see the [importance of RPA](https://www.cio.com/article/3236451/what-is-rpa-robotic-process-automation-explained.html), I believe we’ll see a movement in the role payroll plays within an organization and a shift in views regarding payroll as a critical function that may provide strategic information. You can also learn about [SAP automation opportunities](https://www.flobotics.io/blog/sap-automation) for your company. Thinking about improving your payroll processes with automation? Feel free to [reach out to us](https://www.flobotics.io/contact) for any support needed! Build simple trial automation with our RPA consultants to try the RPA out. Written byMichał Rejman Chief Marketing Officer at Flobotics. [More from Michał](https://www.flobotics.io/our-editorial-team#rejman) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### RPA Reloaded: 50+ Robotic Process Automation Statistics to Know in 2026 RPA statistics 2026: 50+ data points on robotic process automation adoption, ROI, and where the technology is headed next. Yana PokoraApril 15, 2025 ](https://www.flobotics.io/blog/rpa-statistics)[ RPAAI ### Pay on Time, Every Time: Streamlining Invoice Workflows with Invoice Automation Invoice automation, explained: how RPA, OCR, and IA streamline accounts payable and speed up every invoice workflow. Karl MielnickiApril 04, 2024 ](https://www.flobotics.io/blog/invoice-automation)[ RPAEligibility ### A Day Ahead, Not a Single Dollar Short: A Quick Guide to RPA in Payroll RPA in payroll: how automating manual payroll tasks boosts accuracy, speeds processing, and improves quality of life for HR and finance teams. Michał RejmanJuly 20, 2023 ](https://www.flobotics.io/blog/payroll-process-rpa) [All articles →](https://www.flobotics.io/blog) --- # What Should the Model RPA Development and Implementation Process Look Like? Canonical: https://www.flobotics.io/blog/rpa-development-process Author: Radek Moczydlowski Published: 2022-01-25 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/What Should the Model RPA Development and Implementation… [RPA](https://www.flobotics.io/blog?category=rpa) # What Should the Model RPA Development and Implementation Process Look Like? [Radek MoczydlowskiTech Lead at Flobotics](https://www.flobotics.io/our-editorial-team#moczydlowski) Published January 25, 2022Updated September 1, 2026 On this page - [What is RPA and why should you consider implementing it?](#what-is-rpa-and-why-should-you-consider-implementing-it) - [RPA is taking industries by storm.](#rpa-is-taking-industries-by-storm) - [Implementation of RPA: Step-by-step](#implementation-of-rpa-step-by-step) - [Step 1: Intro call](#step-1-intro-call) - [Step 2: Process discovery & audit. Legal compliance check.](#step-2-process-discovery-audit-legal-compliance-check) - [Step 3: Selecting processes for automation PoC](#step-3-selecting-processes-for-automation-poc) - [Step 4: Technology selection and setting up the automation environment](#step-4-technology-selection-and-setting-up-the-automation-environment) - [Step 5: RPA development](#step-5-rpa-development) - [Step 6: Review & User Acceptance Testing](#step-6-review-user-acceptance-testing) - [Step 7: RPA Deployment](#step-7-rpa-deployment) - [Step 8: RPA Scaling and Automation of the Next Processes](#step-8-rpa-scaling-and-automation-of-the-next-processes) - [Step 9: Ongoing Maintenance or Training and Knowledge Transfer](#step-9-ongoing-maintenance-or-training-and-knowledge-transfer) - [Conclusion? Start with Robotic Process Automation today!](#conclusion-start-with-robotic-process-automation-today) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## What is RPA and why should you consider implementing it? ### RPA is taking industries by storm. From healthcare, finance, insurance, real estate, and logistics to national defense and smart cities, companies are looking for ways to automate data-heavy, repetitive tasks, cut costs, and increase efficiency. And with the rising costs of resources and employment, broken supply chain, and growing competitiveness, the need for process optimization is greater than ever. Top solutions for the finance and banking industry or [automation for consultancy.](https://www.flobotics.io/contact) RPA, or [Robotic Process Automation](https://www.uipath.com/rpa/robotic-process-automation), can fully automate complex, data-heavy, time-consuming tasks and complete them in a split second. With the 0% margin of error and being able to run 24/7, this technology can unlock your team’s productivity, letting them focus on tasks that matter. And what can RPA take care of? Among many things, it’s perfect for data entry on a scale, document processing, account registration, eligibility checks, transferring huge amounts of information between various systems and CRMs (sometimes from the public domain), or integrating whole departments. (You can read about [more examples of Robotic Process Automation implementation](https://www.flobotics.io/blog/rpa-use-cases-across-industries) here). But for RPA to truly shine and bring value to your business, it must be done right. That’s why a correctly mapped process of implementation of RPA is so important. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Implementation of RPA: Step-by-step Here is a model RPA development and implementation process in 9 steps. This is what an organization looking for an automation development partner should expect from collaboration every step of the way. Of course, in some cases, the process will be different: you may already have precise automation for implementation in mind, or maybe you already have some automation (or even RPA) setup in place. But usually, the whole journey looks like this. Fig. 01 · RPA 10 steps A model RPA implementation and development process Delivery - 01Intro callUnderstand business needs and vision. Outcome: an automation brief. - 02Process discovery and auditMap processes and calculate ROI for each automation. Outcome: a map of automation potential. - 03Choose processes for a proof of conceptPick the first process by feasibility and ROI. Outcome: a roadmap and backlog. - 04Technology and environment setupChoose the RPA platform, buy licenses, set up the environment. - 05DevelopmentThe team builds the bots. Outcome: bot written. - 06Review and user acceptance testingTest safely, then prepare for deployment. Outcome: bot tested. - 07DeploymentThe bots go live and do the work. - 08Scale to the next processesBack to the backlog. Steps 5–8 repeat until every automation is built. After delivery: your choice - Option 1 Ongoing maintenanceThe RPA agency keeps maintaining and updating your bots. - Option 2 Training and knowledge transferYour team learns to run the RPA system itself. ### Step 1: Intro call This is more of a step zero in the RPA development process, but it is important to mention. As every collaboration starts with a conversation, the RPA development process begins during the intro call between the client and the agency. Talking to a business advisor or RPA consultant during the first call would be best. They should ask you about your company, business challenges, and processes. The goal here is to understand your needs and vision. At this point, you will be asked if you have a specific process for automation in mind or if you are interested in implementing RPA more broadly within your company and need help selecting the right processes. Depending on the answer, you will either be asked to participate in a process discovery workshop or analyze the process you want to automate, ensuring it is eligible for automation. #### What is needed from you at this point? A decisive person (preferably: upper management) to take part in a 30-60 min discovery call. #### What is the outcome of the step? The RPA team has collected the requirements and understands your needs. ### Step 2: Process discovery & audit. Legal compliance check. In most cases, this will be the first step of the collaboration that adds value to the process. Suppose you are unsure which processes in your company should be automated. In that case, RPA consultants and business process advisors will enter your organization and talk to your team to discover all the processes. The goals are to identify bottlenecks and suboptimal flows and map your actions, tools, and stakeholders. The RPA team should also analyze all the legal implications and aspects of automation to ensure compliance with relevant juridical systems, such as [HIPAA compliance](https://www.flobotics.io/blog/hipaa-compliance-rpa) for the [medical billing industry](https://www.flobotics.io/rcm-automation) in the US. Next, the processes should be audited, and their automation potential should be analyzed based on the expected ROI and Expected Business Value. These are just some metrics you can focus on. You can read more about the [key RPA metrics](https://www.flobotics.io/blog/rpa-successs-metrics) and how we calculate them here. Afterward, the technical Architect, in collaboration with the process Architect, will put together a Process Definition Document (PDD), which contains information about every process/step depth. This step is also a great opportunity to look at your company from the outside and learn how you operate daily. #### What is needed from you at this point? Selecting a Single Person of Contact for communication. Selecting people to participate in process discovery workshops (usually: management, people operations, tech leads) #### What is the outcome of the step? A map of processes within your organization and automation roadmap ### Step 3: Selecting processes for automation PoC Based on your business needs and the estimated ROI that can be delivered from every automation, you and your RPA development partner will together select a key process that should be automated in the first place. The model RPA development process should start with automating one, a key process in the form of a Proof of Concept. The rest of the processes should be moved to the backlog for future automation after the PoC is validated successfully. Learn more about [selecting your first process for automation.](https://www.flobotics.io/blog/what-processes-to-automate) #### What is needed from you at this point? Your involvement in selecting the process #### What is the outcome of the step? First automation [Proof of Concept plan ](https://www.techtarget.com/searchcio/definition/proof-of-concept-POC) Process backlog for future automation ### Step 4: Technology selection and setting up the automation environment With your processes mapped and selected for automation, your RPA team should now recommend an RPA technology the best suited for your needs. The tool could be any of the enormous amounts of devices in the market, but the top 3 tools in today’s market are [UiPath](https://www.flobotics.io/uipath-services), Blue Prism & Automation Anywhere. After the automation tool is chosen, the team will select the right licenses and set up the RPA environment. #### What is needed from you at this point? We are approving the technology. You are purchasing licenses if needed. #### What is the outcome of the step? Technology selected. Licenses purchased. RPA environment setup ### Step 5: RPA development After implementing the chosen RPA platform, it’s finally time for the good stuff – bot development! Your dedicated RPA developers will write bots along with the reference of the Process Definition Document. Depending on the task to be automated or the kind of automation required, additional coding may be needed. Sometimes, the development may be speeded up using reusable plugins or pre-existing bots. But every case is different! #### What is needed from you at this point? A Single Person of Contact for further questions about the process and IT assistance (if needed) #### What is the outcome of the step? An RPA bot ready to be tested ### Step 6: Review & User Acceptance Testing Once your bot has been developed, the next stage is to test it. RPA bots are tested either by the dedicated testing team or the development team itself. It’s being done in a safe, pre-production environment to check how the users can utilize this bot to automate a specific task. If the testing is successful, bots are set for deployment. If there are any issues upon diagnosis, the bot returns to the development and testing teams for resolution. #### What is needed from the client at this point? A Single Person of Contact for further questions about the process and IT assistance (if needed) Final bot sign-off #### What is the outcome of the step? A bot is tested and approved for deployment or sent back to development. ### Step 7: RPA Deployment After developing and successfully testing a bot, it is deployed into the production environment – your first RPA implementation is finished. Now your team can work alongside the bot, and your process will be automated from now on! #### What is needed from the client at this point? Nothing. Just relax and have the job done for you! #### What is the outcome of the step? Process Automation Process automation ROI calculator See what automating a process could save you in a few minutes. [Calculate ROI →](https://www.flobotics.io/roi-calculator) ### Step 8: RPA Scaling and Automation of the Next Processes After successfully deploying the first bot and validating your PoC, the next processes can be taken care of. Developers will return to the backlog and select the next one for automation, considering the potential ROI you can achieve. This step can be repeated until all the processes eligible for RPA are automated. #### What is needed from the client at this point? Your involvement in selecting the process A Single Person of Contact for further questions about the process and IT assistance #### What is the outcome of the step? Further automation ### Step 9: Ongoing Maintenance or Training and Knowledge Transfer Once all the bots are online and running, the RPA development process is finished. But, of course, there is still a question of maintenance and keeping the bots healthy and updated. Systems get updated, and databases and CRMs change, sometimes affecting the RPA bots’ performance. RPA may be doing all your work, but you need to put some effort into keeping the system alive and well. At this point, you should be able to decide if you would like to keep the hired team as ongoing support and maintenance or get your team to take over. If you bring this know-how to your company, a model RPA development partner should provide relevant training and workshops for your team. #### What is needed from the client at this point? Your decision Selecting team members to be trained #### What is the outcome of the step? Either way – your RPA system is in good hands:) ## Conclusion? Start with Robotic Process Automation today! The model RPA development process and its implementation should look like this. We hope we managed to clarify what you expect from working with separate RPA developers or an RPA development agency like ours. If you’d like to start with RPA or check if your processes are eligible for automation, [contact Flobotics](https://www.flobotics.io/contact)! Our RPA developers, RPA consulting experts, and business consultants will analyze your process, calculate the potential ROI and automate the right processes that will impact your business most. Let’s automate your company together! #### Like the article? Spread the word Written byRadek Moczydlowski Tech Lead at Flobotics. [More from Radek](https://www.flobotics.io/our-editorial-team#moczydlowski) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # How to Measure RPA Success: A Guide to Robotic Process Automation Metrics Canonical: https://www.flobotics.io/blog/rpa-successs-metrics Author: Bart Teodorczuk Published: 2021-12-23 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/How to Measure RPA Success: A Guide to Robotic Process… [RPA](https://www.flobotics.io/blog?category=rpa) # How to Measure RPA Success: A Guide to Robotic Process Automation Metrics [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published December 23, 2021Updated September 1, 2026 On this page - [Why Should You Measure Your RPA Project Success?](#why-should-you-measure-your-rpa-project-success) - [What Types of RPA Metrics Should You Consider for Tracking?](#what-types-of-rpa-metrics-should-you-consider-for-tracking) - [How to Measure RPA Success: Business Metrics](#how-to-measure-rpa-success-business-metrics) - [1. Value of Time Gains (VTG)](#1-value-of-time-gains-vtg) - [2. RPA Return on Investment (ROI)](#2-rpa-return-on-investment-roi) - [3. Expected Business Value](#3-expected-business-value) - [4. Gained Productivity](#4-gained-productivity) - [5. Business Value Lost in Downtime](#5-business-value-lost-in-downtime) - [6. Cost per Error](#6-cost-per-error) - [7. Budget Estimation Accuracy](#7-budget-estimation-accuracy) - [8. License Utilization](#8-license-utilization) - [How to Measure RPA Success: Technical and PM Metrics](#how-to-measure-rpa-success-technical-and-pm-metrics) - [9. Process Automation Velocity](#9-process-automation-velocity) - [10. Average Automation Development Time](#10-average-automation-development-time) - [11. RPA Automation Uptime](#11-rpa-automation-uptime) - [12. Downtime Rate](#12-downtime-rate) - [13. Bot Success Rate/ Bot Accuracy Rate](#13-bot-success-rate-bot-accuracy-rate) - [14. Exception Rate/ Margin of Error](#14-exception-rate-margin-of-error) - [15. Break-Fix Person Hours](#15-break-fix-person-hours) - [16. Process Automation Utilization Rate](#16-process-automation-utilization-rate) - [17. Automation Scalability](#17-automation-scalability) - [18. Development Scalability](#18-development-scalability) - [What’s Next? Select Your Own RPA Metrics for Tracking!](#whats-next-select-your-own-rpa-metrics-for-tracking) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Why Should You Measure Your RPA Project Success? One of the coolest things I find about [Robotic Process Automation development and implementation](https://www.flobotics.io/) is that you can measure virtually everything. I am not talking about the performance of bots or other highly technical metrics that can be understood only by RPA developers. I have in mind actual business- and money-related metrics that can help you [measure your ROI](https://www.flobotics.io/roi-calculator), calculate business gains, and get a clear answer to how much (or: if) RPA automation is profitable for your company. That’s the true beauty of RPA: being able to generate a data-based report showcasing the exact effects of automation implementation (be that saving $$$, shortening the payment cycle, or decreasing the time needed to perform processes) ready to share with your CEO, board or other stakeholders. ## What Types of RPA Metrics Should You Consider for Tracking? Below you will find the collection of RPA metrics worth considering following from the business project management and [technical perspective](https://www.flobotics.io/blog/rpa-non-technical-developer). Should you know all of them? Yes. You should get familiar with all the metrics below to get a better understanding of what and how can you measure in regard to RPA projects. Should you use all of them? No. Over-measurement can be worse than no measurement at all. When you track too many metrics, you lose focus on what is essential and suffer from information overload. You should select a handful of metrics and stick to them over a more extended period of time. It can also depend on the type of RPA project you are managing, e.g., for some projects, time-related metrics are entirely irrelevant (because the process can be executed overnight or there is no set deadline). For others, timing may be super important (e.g., due to the tight SLAs.) ## How to Measure RPA Success: Business Metrics Fig. 01 · RPA metrics Business Measuring RPA success: business metrics - Value of time gainsCost of a process done by people vs by bots. - ROIMoney gained from RPA minus the cost of implementation. - Budget accuracyDifference between the estimated and final budget. - Productivity gainedFTEs freed by automating one or more processes. - Value lost in downtimeBusiness value lost to errors and downtime. - Cost per errorAverage cost of an error in an automation. - Expected business valueThe sum of all cost savings. - License utilizationHow fully the business uses its RPA license. ### 1. Value of Time Gains (VTG) Value of Time Gains (VTG) tells the difference between the cost of the process carried out by human employees versus the cost of the process carried out by RPA bots. It can be calculated with the following equation: ##### VTG = (EC – AC)/AC x 100% Where: EC = costs of the processes delivered by employees: payrolls (with leaves and holidays), taxes, costs of office and workplace (rent, utilities, etc). AC = costs of the processes delivered by bots: license fees, cost of development, virtual machine/hosting, and maintenance. VTG is your base metric for calculating RPA ROI. ### 2. RPA Return on Investment (ROI) Robotic Process Automation Return on Investment is a key business metric that should tell you how much money you saved (in other words, earn) by implementing RPA in your business. RPA ROI is calculated using the Value of Time Gains (above). To build a complete picture of RPA ROI, you need to take two factors into account: Value of process acceleration The value of process acceleration tells you how much money was gained by implementing the automation. For example, this can be represented by the effects of shortening the client onboarding cycle: a difference between the number of clients processed before and after the automation multiplied by the average gain on one client. Value of error reduction: “Value of error reduction” shows how much money was saved on eliminating mistakes. It should be aligned with what’s essential in your organization. For example, it can represent the total cost of deals lost due to errors or lengthy processing or the cost of fixing the errors manually (represented by payroll costs, e.g., 30% of 1FTE), the improved percentage of cases under SLA, improved quality of data, or anything necessary for a given process/organization. After calculating VoPA, VoER, and VTG, we can calculate the RPA ROI as follows: ##### RPA ROI = [(VTG*AC + Value of process acceleration + Value of error reduction) – AC]/AC x 100% Want to see an example? Read how our client from the finance sector [achieved the 300,000% ROI](https://www.flobotics.io/case-studies/t-bank-automation) (yes, you got the zeroes right!) with one RPA implementation. ### 3. Expected Business Value Expected Business Value is an RPA metric that combines all other RPA business-related KPIs. It represents the sum of all the cost savings (from increased performance, resource utilization, and error reduction) multiplied by the average FTE costs over a given period of time. ### 4. Gained Productivity “Gained Productivity” is one of the most common metrics companies use to measure RPA gains. It tells you how many FTEs were gained by automating a given process (or multiple processes). For example, if automation has replaced the manual work of 4 people, who would spend 2 hours of their time each day carrying out the process, the gained productivity here would be 1 FTE/month. ### 5. Business Value Lost in Downtime Business Value lost in Downtime tells you how downtime hurts your Expected Business Value. You can calculate the Business Value lost in Downtime by subtracting the quantified downtime from your Expected Business Value over a given period of time. ### 6. Cost per Error This metric tells about the average cost of an error in a given automation. It should be the sum of the value lost due to downtime and the cost of working hours needed to fix the error (Break-Fix Person Hours). ### 7. Budget Estimation Accuracy It shows the difference between the estimated budget before starting to work on the project and the final budget. In RPA development (as in other types of software development), estimations usually vary from reality due to the unpredicted software issues or changes in the project during the development phase. Everything over 70% accuracy is considered acceptable. ### 8. License Utilization License utilization represents to what extent the business is utilizing its RPA provider license (e.g., UiPath license). For example, if your UiPath-based bots are maximizing the license capacity but, due to downtime or maintenance, are not working for 10% of the time over a given period, your license utilization will be at 90%. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## How to Measure RPA Success: Technical and PM Metrics Fig. 02 · RPA metrics Technical and PM Measuring RPA success: technical and project metrics Metric | What it measures | Process automation velocity | Average time the automated process takes to run | Average development time | Time to build and implement one bot for one process | Automation utilization rate | How much a process is actually used in operations | Downtime rate | % of time a bot could run but is down (errors, maintenance) | Automation uptime | % of time automated processes are available | Bot success rate | % of cases the bot covers in a process | Development scalability | % of existing code reused in new automations | Break-fix person hours | Time it takes to fix an error | Exception rate | % of cases that failed | Automation scalability | How easily a process can be scaled | ### 9. Process Automation Velocity Process velocity tells you the average time needed for a single case/task of the automated process to be executed. ### 10. Average Automation Development Time These metrics tell you about the average time (expressed in FTEs or the number of working hours of [RPA developers](https://www.flobotics.io/contact)) that is needed for the development and implementation of one RPA bot to execute one process. ### 11. RPA Automation Uptime Automation uptime is the percentage of time your automated processes can be executed. It is the difference between total bot availability and automation downtimes (times when bots were broken or unavailable). ### 12. Downtime Rate The downtime rate represents the percentage of time your bot could be running a process that is not due to errors or bot maintenance. ### 13. Bot Success Rate/ Bot Accuracy Rate This metric shows the % of cases that have been covered by the bot on a given process. The good success metric for RPA is 80% and above. Of course, building an RPA bot with a 99% accuracy rate is entirely possible. But you need to weigh the longer cost of the development and actual business gains coming from the increased success rate. ### 14. Exception Rate/ Margin of Error This is a very important metric from the business and technical perspectives. The exception rate tells you what is the % of cases that have failed. There are two subcategories of errors here: Business exceptions, such as missing data, case-specific problems, but also out-of-scope items) System exceptions (all the things robots should do but couldn’t for any reason, like., timeouts, login errors, changing webpage layout) For the RPA automation to be considered good, the exception rate shouldn’t go over 20%. ### 15. Break-Fix Person Hours Break-Fix Person Hours metric details how long it takes to fix a given error. It should be expressed in FTEs or in man-hours needed to repair the automation and get it back on track. ### 16. Process Automation Utilization Rate Process utilization represents to what extent a given process is utilized in a company’s operations. If a bot in a given process is used 50% of the time, the utilization rate is 50%. This metric can help you validate which automation is critical to your business and which is playing more of a supportive role, as well as decide which you should scale up and which you can resign from in the future. It can also be a great indicator of process implementation: consider the situation when 30% of employees are scared of using brand-new automation and are still doing the job manually. This creates a great space to improve bot efficiency. ### 17. Automation Scalability This metric shows how easy to scale a given process is. It should represent the cost and time needed to add a new machine/duplicate the bot to perform the given task vs. the time and cost needed for recruitment and onboarding the human processor to perform the same tasks + the payroll costs (e.g., 30% FTE). As a rule of thumb, if the RPA bots are written with all other good practices in mind, they should be bound to scale almost instantly. ### 18. Development Scalability It tells you what % of the existing automation code can be reused in the new automation. In most cases, as the amount of automation developed for one organization grows, adding a new bot gets easier and takes less time, as it can be built by rebuilding the existing ones. How does it work in practice? In most cases, organizations already have some tool stack in place and use their tools, such as SAP. Building the first bot will require building SAP logic from scratch, but a significant amount of the job will already be done with the next ones. Check RPA workshops and practical training while implementing RPA in your company. ## What’s Next? Select Your Own RPA Metrics for Tracking! The above metrics on measuring RPA success will help you understand your RPA setup better and provide a deeper perspective on what and how you should measure to have complete control over your Robotic Process Automation bot network. You can quickly implement RPA in your [finance,](https://www.flobotics.io/blog/rpa-for-finance) banking, real estate, or any other industry. They can also come in handy while collaborating with the [RPA development agency](https://www.flobotics.io/rcm-automation) (such as Flobotics) to better understand what is going on and if your business is actually profiting from [RPA implementation](https://www.flobotics.io/blog/rpa-challenges). And if you still feel a bit lost and unsure how to measure RPA success, which metrics should you choose – as I mentioned before, you better avoid measuring EVERYTHING so you don’t get overwhelmed with the data – [reach out to us](https://www.flobotics.io/contact). Our team, sourced only from the “Big Four” of accounting, will analyze your processes and current RPA setup and recommend the metrics and KPIs to measure best suited for your business goals and needs. Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Which Processes Should You Automate to Maximize Your Business Efficiency? Canonical: https://www.flobotics.io/blog/what-processes-to-automate Author: Krzysztof Szwed Published: 2021-12-22 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Which Processes Should You Automate to Maximize Your… [RPA](https://www.flobotics.io/blog?category=rpa) # Which Processes Should You Automate to Maximize Your Business Efficiency? [Krzysztof SzwedHead of Delivery at Flobotics](https://www.flobotics.io/our-editorial-team#szwed) Published December 22, 2021Updated September 1, 2026 On this page - [What Types of Automation are Out There for your Business?](#what-types-of-automation-are-out-there-for-your-business) - [Tool-dedicated scripting](#tool-dedicated-scripting) - [Automation scripts](#automation-scripts) - [Robotic Process Automation (RPA)](#robotic-process-automation-rpa) - [Dedicated Systems/Applications](#dedicated-systems-applications) - [How to Identify What Processes Should I Automate?](#how-to-identify-what-processes-should-i-automate) - [Business Value](#business-value) - [Ease of implementation](#ease-of-implementation) - [Additional factors to consider:](#additional-factors-to-consider) - [Automation Processes: Mistakes You Should Avoid](#automation-processes-mistakes-you-should-avoid) - [Starting with a high value, high complexity process](#starting-with-a-high-value-high-complexity-process) - [Ignoring synergies and reusability between automated processes](#ignoring-synergies-and-reusability-between-automated-processes) - [Automating processes for the sake of automation, ignoring business case calculation](#automating-processes-for-the-sake-of-automation-ignoring-business-case-calculation) - [What Processes Should I Automate With RPA?](#what-processes-should-i-automate-with-rpa) - [Overdue Payments Monitoring and Reminders](#overdue-payments-monitoring-and-reminders) - [Incoming Invoices Upload](#incoming-invoices-upload) - [Cashflow reporting](#cashflow-reporting) - [Products delivery automation](#products-delivery-automation) - [Insurance claims handling](#insurance-claims-handling) - [Summary – what’s next?](#summary-whats-next) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) We live in the era of automation. There is no doubt about it. From simple Excel macros to supercomplex algorithms used in Tesla GigaFactory or Google X lab: different types of scripts, software bots, and actual machines are being created every day to help people work faster, better, and more efficiently. On the other hand, automation is often nothing more than just a buzzword. It is being put in every pitch deck by startups seeking funding, and it’s part of every second strategy plan built by operation executives. In many instances, there is nothing behind these proposals – just empty words without a deeper exploration of the topic. But you can achieve so much with properly planned and executed automation! Increasing ROI, shortening payment cycles, freeing your employees from mundane tasks, reducing operational errors… The list is endless. Automating your accounting, finance or real estate processes with RPA. How to go about [automating your business?](https://www.flobotics.io/business-process-automation) What processes should I automate, how to start, and what pitfalls to avoid to ensure the success of the implementation? You will find the answers in this article. Read on! ## What Types of Automation are Out There for your Business? First, you need to decide what type of automation will be the most suitable for your business. Depending on the complexity of the task that is selected for automation, there are a few options you have: ### Tool-dedicated scripting Tool-dedicated scripting can be used for automating simple tasks inside a specified application. Deployment usually takes a few days and is limited to a single application. Examples? Excel macros, Outlook rules, SAP scripting. ### Automation scripts These are scripts written using a specific programming language, i.e., PowerShell or Python. They can be used to automate a bit more complex tasks. This automation will still have a limited application interaction. The development and deployment of these usually take a few weeks. ### Robotic Process Automation (RPA) [Robotic Process Automation](https://www.flobotics.io/blog/robotic-process-automation) allows the building of more complex automation. It enables the connection of various tools (CRMs, SAPs, databases, etc.) and automates the processing of data and documents between them. Thanks to automation platforms, such as UiPath or Blue Prism, the development and deployment usually take a few weeks and are relatively low cost. These platforms are also built with the low-code principle, so the developers can focus more on tasks than the tool they use. There is also a matter of user interface – RPA can automate any application by interacting with it using UI „just like a human.” ### Dedicated Systems/Applications 100% custom-made applications, allowing for automating multiple processes and tasks of the highest complexity, all in one box, written from scratch. There is no limit to what can be achieved here, but the same goes for the potential cost. The full deployment time can be counted in months, or even years. Fig. 01 · Automation Effort vs complexity Which type of automation fits your needs The more complex the task, the longer automation takes to deploy. - 01Tool-dedicated scriptingSimple tasks and macros. Days. - 02Automation scriptsSingle-application automations. Weeks. - 03Robotic process automationComplex, multi-system automations. Months. - 04Dedicated automation systemsFully custom environments. Years. Automating your business processes with [Intelligent Automation is always a great idea.](https://www.flobotics.io/rcm-automation) ## How to Identify What Processes Should I Automate? Moving to the question, “What processes should I automate?” you must understand how to pick the right ones. From my experience, most processes in a given organization can be automated. Although the most important question at this point should be: is it worth it? For example, if the manual execution of a process takes a few hours a month, while development would take half a year, can this process be automated? Yes. But should it be automated? No. The following part of the article will help you in the initial process selection, after which a [detailed assessment](https://www.flobotics.io/contact) should be conducted. You can also read our article about [RPA metrics ](https://www.flobotics.io/blog/rpa-successs-metrics)to give you more insights on what you should focus on. Here are the most important factors you should consider before choosing what processes you should automate: ### Business Value - Process Execution Cost: cost and time needed for the manual execution of the process - Process Errors Cost: how many errors are made during the manual processing, how important is it to limit the mistakes (i.e., compliance violations), and what is your company’s business loss due to these errors? - Execution Time Cost: Does your company lose opportunities due to delays in process execution, is the process a bottleneck wasting the time of employees and other processes? - Other value factors: limited workforce availability, dynamic process growth, [SLAs](https://www.atlassian.com/itsm/service-request-management/slas), specific times of execution (at night), other business KPIs ### Ease of implementation - Complexity: the number of different paths of execution and logic rules - Stability: how long will the process be executed in its current shape? How big can the modifications be? (For example, we know about tax changes incoming next year, so there is no sense in automating existing business logic as it will have to be redesigned in January) - Standardization: is the process executed according to defined rules or based on human judgment? - Data accessibility: whether required data is: - structured (data tables vs. pure text) - digital (digital invoice vs. invoice scan vs paper invoice) Fig. 02 · Automation 8 factors What to consider before choosing processes to automate Before you choose - 01Data volume - 02Error rate impact - 03Limited workforce - 04Data accessibility - 05Process complexity - 06Stability - 07Standardization - 08Process growth Based on the above factors, we can calculate two dimensions: Automation Potential = Process Execution Cost + Process Errors Cost + Execution Time Cost + Other value factors Ease of implementation = Stability + Standardization + Data accessibility – Complexity With these two dimensions, we can create a simple matrix that will help you assess the automation potential of your processes: Fig. 03 · Automation Priority Which processes to automate first Process value (manual effort) 02 · Automate secondHigh effort, hard to build 01 · Automate nowHigh effort, easy to build 04 · Don't automateLow effort, hard to build 03 · Build a proof of conceptLow effort, easy to build; optimize licenses Ease of development → QUART 1: High value, low (development) effort. The first choice – automate now! QUART 2: High value, high effort. Processes that should be automated in a second order after the organization gets familiar with the RPA technology QUART 3: Low value, low effort – consider building Proof of Concepts, utilizing empty licenses, QUART 4: Low value, high effort. These processes do not necessarily have to be automated; each case should be analyzed separately. Processes from the 2nd and 3rd quart can be automated simultaneously depending on organization needs and available assets. ### Additional factors to consider: - Packages/bundles: in other words: the economy of scale. With multiple processes that are using the same application/logic, specific parts of automated processes can be reused, making other automation easier to develop (the dots on the chart move to the right) - Enablers: automating one process might generate data required by another. i.e., uploading scanned invoices data to the database (the dots on the chart move to the right) - Ice breakers: first few processes automated in the organization shouldn’t be overly complicated and optimally should be inspired by employees, not by management. Process simplicity lets us avoid deadline violations, conflicts, and other problems, thus allowing easier change management. - Optimizers: developing automation is a great opportunity to standardize the existing process, create process documentation and even optimize it. What’s important: as more processes are automated, we might discover that methods initially located in the 4th quart have moved to the 2nd (by enabling another process) or 3rd (by common application/logic synergies or being helped by another method). Shortly speaking: order matters! Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Automation Processes: Mistakes You Should Avoid Here are three pitfalls I would suggest looking out for while selecting what processes I should automate and planning this automation: ### Starting with a high value, high complexity process New, wonderful technology is announced, and great effects come quickly. Meanwhile, due to lack of experience, we discover that the process is even more complex than expected (employees rarely are fully aware of all rules and throw in new ones as development progresses), some functionalities can’t be added, and the project takes twice as much time as planned. Where there’s a possibility, always start with a more straightforward task. ### Ignoring synergies and reusability between automated processes Some processes use the same applications or the same logic. Therefore, parts developed for the first process can be used in the second process, effectively easing and shortening its development. So, we may have four processes, each not worth automating. Still, all use the same application and similar logic, so developing them together reduces the costs by 40%, and now the business case is valid. ### Automating processes for the sake of automation, ignoring business case calculation Sometimes automation is developed because someone is annoyed by a task or a manager has to achieve his KPI, “automate 10 processes in the following year”, even though the automated processes do not bring enough business value compared to development costs and upkeep. Following this path will effectively hurt your RPA-related KPIs and create a negative perception of automation within your organization. If you want to read more about this topic, read our article on [common RPA failures](https://www.flobotics.io/blog/rpa-failures) and why you should remember to work only with [technical RPA developers.](https://www.flobotics.io/blog/rpa-non-technical-developer) ## What Processes Should I Automate With RPA? The answer to this question is always tricky, as plenty depends on your unique business needs and the specifics of your industry. Nevertheless, here are some actionable ideas of which processes can be automated using RPA. Learn about [SAP Automation](https://www.flobotics.io/business-process-automation) with RPA and UiPath. ### Overdue Payments Monitoring and Reminders Description: The bot monitors sales’ invoice payment status. A reminder is sent to the contractor if the payment deadline is exceeded. Multiple escalation levels are defined. Why? Besides limiting employee engagement, the automation enables higher process execution frequency leading to a higher collection rate. At the same time, all required data is digitally accessible, helping entirely rule-based business logic, with limited paths (escalation levels) allowing for easy implementation. Medium value and low development effort make it a perfect “ice breaker” process. ### Incoming Invoices Upload Description: Contractor invoices are coming to the dedicated mailbox, bot extracts the client’s Tax identification number, based on which the Contractor ID is queried from the database. Then the invoice is uploaded to specified contractor files in the [ERP](https://dynamics.microsoft.com/en-us/erp/what-is-erp/) system. Why? Thanks to higher execution frequency sales invoices are being uploaded immediately after receiving them shortening total receive-to-pay time. Reduced mistakes limit the risk of unpaid or delayed invoices. Semi-structured, digital, input data (tax number has defined format allowing its extraction even from scan OCR) and a single execution path make it easy to implement the process. ### Cashflow reporting Description: Daily bank statements are downloaded directly from the bank website. Scheduled payments are extracted from the ERP system. Data from both sources are merged to create a cash flow report. Expected account balance limit violations are reported to the accounting department. Why? Cashflow reports have to be ready by the workday beginning, making the processing time crucial, which, paired with a high risk of miscalculation leading to insufficient funds for defined payment, puts increased pressure on employees. Many bank accounts (in multiple banks) and fees generate a significant process execution cost. Automation development for this process is not straightforward due to multiple input sources (multiple banks) and a few process paths. However, business logic is rule-based, making it a good process in the second automation wave – high value and medium development effort. ### Products delivery automation Description: Based on registered product orders and stock, delivery orders are created in cooperating delivery companies. Why? The process is time crucial as order handling time directly affects both costs and customer satisfaction, high process volume generates high execution costs with several employees engaged daily. Time pressure causes mistake-related risk of invalid delivery parameters. Process automation is feasible thanks to fully digital source data and target systems. Multiple target systems and execution paths increase development costs; however, it’s compensated by process volume. ### Insurance claims handling Description: Insurance claims are registered in a web application by clients. The web application is not integrated with the claims handling system, so all claims must be copied to the target system. Why? Large volume in connection with high error vulnerability generates hefty process execution costs. Although business rules are clearly defined there are multiple execution paths (i.e., claims types) and defined exceptions, making it a very high value, high development effort process. Want to read more examples of processes that can be automated by using RPA? Here is our list of [40 real-world use cases of RPA](https://www.flobotics.io/blog/rpa-use-cases-across-industries) across industries. Thinking of choosing the technology to automate your processes discover the article [Robotic Process Automation vs Machine Learning](https://www.flobotics.io/blog/robotic-process-automation-vs-machine-learning). ## Summary – what’s next? As you can see, there are plenty of factors to be considered before proceeding with your first RPA implementation. I hope this guide sheds some light on how to go about it! But if you are still unsure about what processes should I automate, where to move next – [get in touch with us](https://www.flobotics.io/contact). Hire RPA consultants and we will audit your existing processes and help you select and automate the ones with the highest potential of increasing your ROI. #### Like the article? Spread the word At Flobotics we specialize in U.S. healthcare revenue cycle management process automation – no generic bots here. Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byKrzysztof Szwed Head of Delivery at Flobotics. [More from Krzysztof](https://www.flobotics.io/our-editorial-team#szwed) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ Eligibility ### Payroll Process Improvement Ideas You Can Implement RPA in payroll: proven process-improvement ideas to cut manual work, reduce errors, and speed up your payroll cycle. Michał RejmanFebruary 07, 2022 ](https://www.flobotics.io/blog/rpa-payroll-process)[ RCMHealthcare ### How to Improve Electronic Health Records Processing with Automation EHR automation with RPA: fix electronic health record imperfections without a system overhaul - pros, cons, and real use cases. Bart TeodorczukAugust 09, 2021 ](https://www.flobotics.io/blog/electronic-health-records-rpa)[ RPA ### What Is RPA? | Robotic Process Automation Robotic Process Automation (RPA), explained: how software bots run a 24/7 digital workforce that cuts costs and human error. Bart TeodorczukSeptember 01, 2025 ](https://www.flobotics.io/blog/robotic-process-automation) [All articles →](https://www.flobotics.io/blog) --- # What Does The "UiPath Certified Developer" Title Actually Mean? Canonical: https://www.flobotics.io/blog/uipath-certified-developer-title-meaning Author: Karl Mielnicki Published: 2021-11-26 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/What Does The "UiPath Certified Developer" Title Actually… CTO Notes [RPA](https://www.flobotics.io/blog?category=rpa) # What Does The "UiPath Certified Developer" Title Actually Mean? [Karl MielnickiCTO & Co-Founder of Flobotics](https://www.flobotics.io/our-editorial-team#mielnicki) Published November 26, 2021Updated September 1, 2026 On this page - [Who are Certified Senior UiPath developers?](#who-are-certified-senior-uipath-developers) - [! VERY IMPORTANT DISCLAIMER!](#very-important-disclaimer) - [Certified Senior UiPath developer – a real-life example](#certified-senior-uipath-developer-a-real-life-example) - [Conclusion – what REALLY matters?](#conclusion-what-really-matters) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Have you ever wondered if the “Certified UiPath Developer” title guarantees knowledge and professional expertise (especially when you are on the hiring side?)? In many instances – yes, it is. But in this article, I want to focus on the “certified” part to understand better what meaning lies behind it… ## Who are Certified Senior UiPath developers? First, some broader context: in my opinion, UiPath has [the best learning resources ](https://academy.uipath.com/resources)out of any RPA platform. They have enough material to keep anyone busy for weeks if not months. The courses are well structured and bring much value and knowledge, especially if you are a fresh RPA dev. [Academy.UiPath](https://academy.uipath.com/) is a great place for learning all the features of UiPath if you aren’t familiar with them, but… that’s it. The hard truth is that it is neither practical nor gives you any real coding experience. After completing even one of the learning paths, a diploma of completion is issued. And here is where the problems start. The classes are super easy to finish (not to master the material! to complete an actual course). It is just clicking through information to go further with short multiple-choice tests at the end of sections that can be taken an infinite number of times. I can easily imagine a situation where someone clicks through, does not learn anything, and has a diploma. And that’s the issue’s core with “certified UiPath developers.” These documents aren’t certificates; they are diplomas of completion. They don’t show the actual expertise; they only show that a person has finished a given course. Regardless, plenty of devs will put “UiPath Certified” on their resumes and LinkedIn anyway and, in some instances, create a false impression about their actual skills. At this point, someone looking for an RPA developer who doesn’t know anything about the subject matter will be impressed with their resume (consider the example from the next chapter). ### ! VERY IMPORTANT DISCLAIMER! There are some exceptions to this. A group of UiPath developers have completed the actual, [paid certification courses from UiPath](https://www.uipath.com/learning/certification): UiPath Certified RPA Associate (UiRPA) and UiPath Certified Advanced RPA Developer (UiARD). These certifications are more reliable and can be perceived as indicators of the dev’s skillset. But, as you can see in the example below, they are often being replaced by less valuable “certificates.” Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Certified Senior UiPath developer – a real-life example Consider this excerpt from a real-life “Certified Senior UiPath developer” resume we received not long ago. Certificates Completed: - RPA Developer Foundation - RPA Developer Continuous Learning - RPA solution Architect Foundation - RPA Infrastructure Engineer Foundation - RPA Business Analyst Foundation - RPA Implementation Manager Foundation First reaction? “Holy shit… This guy must be a pro! He also has one year of being a senior RPA developer on his resume… Let’s hire him!” What is the reality? This person with no technical know-how was sick of doing manual reports all day, so he automated some of his tasks using UiPath. Once this person’s manager found out, he was promoted and received the title of senior UiPath developer on the spot. One year later, he wants to ride the wave and make a developer’s salary, so he is looking for a new job. Now as a Senior UiPath Developer with a resume to back it. But, in reality, he was still junior level, without almost any proper knowledge of software development, ready to be defeated by the first, more complex problem (that will arise sooner or later). ## Conclusion – what REALLY matters? Courses and certifications don’t mean anything if you don’t have experience and a technical mindset. In my opinion, four things are needed if you want to be a PROPER [Robotic Process Automation (RPA) developer: ](https://www.flobotics.io/contact) - Technical mindset: to understand how automation works in the first place and be able to analyze the technical environment that will be automated; - RPA platform knowledge: to correctly implement the automation (check our new program of RPA workshops and training); - Project experience: to know how automation corresponds with real businesses and real products; - Passion for automation: to always pursue the best solution available. Fig. 01 · RPA developers What it takes What a good RPA developer needs A good RPA developer needs - 01A technical mindset - 02Project experience - 03Passion for automation - 04Knowledge of RPA platforms (UiPath, Automation Anywhere, Blue Prism, Power Automate) If a developer’s eyes don’t light up while talking about automation, they probably aren’t your perfect pick. If they mostly were in charge of manual reports and right after becoming a senior RPA developers within the same company, probably something is not quite right. Certification only makes sense if it supplements one’s existing knowledge and expertise. It’s a great indicator of one’s professional attitude and a good summary of potential areas where your future dev can support your business and improve your processes. But it cannot replace the good ol’ coding experience. We provide a wide range of [RPA consulting services](https://www.flobotics.io/contact). Build your Robotic Process Automation with our [battle-tested UiPath developers](https://www.flobotics.io/uipath-services) sourced only from “Big Four” consulting firms. #### Like the article? Spread the word Written byKarl Mielnicki CTO & Co-Founder of Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### UiPath Licensing Simplified: How BPO Makes Automation More Affordable Business process outsourcing for UiPath licensing: cut costs, avoid confusing tiers, and scale automation without overhiring. Karl MielnickiMay 16, 2025 ](https://www.flobotics.io/blog/business-process-outsourcing)[ RPA ### Effective Naming Conventions in UiPath: A Comparative Analysis UiPath naming conventions: a practical guide to consistent naming and folder structure for Object Repository automation projects. Maciek MatuszczakDecember 03, 2023 ](https://www.flobotics.io/blog/naming-conventions-uipath)[ RPA ### Specific Content Limitations in UiPath [RPA Developer’s Investigation] UiPath content limitations: Specific Content was removed from Get Queue Items in 2024 - see what fields disappeared and how to retrieve queue data now. Dominik PutMay 21, 2024 ](https://www.flobotics.io/blog/specific-content-limitations-in-uipath) [All articles →](https://www.flobotics.io/blog) --- # RPA in Clinical Trials: 5 Ways Robotic Process Automation Innovates Medical Research Canonical: https://www.flobotics.io/blog/automate-clinical-trials Author: Michał Rejman Published: 2021-10-08 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/RPA in Clinical Trials: 5 Ways Robotic Process Automation… [Healthcare](https://www.flobotics.io/blog?category=healthcare) # RPA in Clinical Trials: 5 Ways Robotic Process Automation Innovates Medical Research [Michał RejmanChief Marketing Officer at Flobotics](https://www.flobotics.io/our-editorial-team#rejman) Published October 08, 2021Updated September 1, 2026 On this page - [Clinical trials – how the processes look like?](#clinical-trials-how-the-processes-look-like) - [How automation and RPA help to improve the efficiency of clinical trials](#how-automation-and-rpa-help-to-improve-the-efficiency-of-clinical-trials) - [The benefits of RPA to clinical trials](#the-benefits-of-rpa-to-clinical-trials) - [Eliminate Monotonous Manual Data Collection](#eliminate-monotonous-manual-data-collection) - [Automate Analysis To Show Extensive Effect Overview](#automate-analysis-to-show-extensive-effect-overview) - [Assist In Validation Processes](#assist-in-validation-processes) - [RPA Clinical Trials Use-cases](#rpa-clinical-trials-use-cases) - [Patient Matching](#patient-matching) - [Processing Pharma Co-vigilance Cases](#processing-pharma-co-vigilance-cases) - [Trial Master Process Management](#trial-master-process-management) - [Regulatory Submission Process](#regulatory-submission-process) - [Conclusion](#conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Data, they say, is the new gold. All sectors of the economy continue to collect huge amounts of data to serve humanity better. And the healthcare sector, among other sectors, arguably tops the list regarding data collection. Many data collected in the healthcare sector come from various sources, including radiology information, insurance portals, lab information systems, ERPs, and clinical trial applications. With so much data to be processed, integrating this information across all channels in the health sector has become labor-intensive and complicated. This ultimately has increased the consumption of resources, hence, reducing efficiency. To tackle these challenges, many healthcare companies are now bringing Robotic Process Automation (RPA) into the picture to automate repetitive and redundant procedures vital to their system’s smooth functioning. One of those processes is Clinical Trials. In this article, we look at ways in which RPA can help provide credible data and reduce cost, workforce utility, enhance operational efficiency, and restrict the likelihood of errors. Learn more about using Robotic Process Automation in other industries, like RPA in insurance or RPA in logistics. ## Clinical trials – how the processes look like? Clinical trials are research studies that aim to deduce if a treatment, device, or medical strategy is safe for human consumption and use. In general, clinical studies provide credible data and medical knowledge, which assist in making healthcare guidelines and decisions. The main objective of clinical trials is research. Trials are modeled to add to medical data and knowledge pertaining to diagnosing, preventing, and treating disease conditions. When it comes to healthcare research, a successful clinical trial needs a lot of accurate and precise data computations. No study or research is better than the quality of data used. The quality of data used in the stages of clinical trials is the most crucial factor to its success. To this end, many healthcare companies continue looking for ways to achieve and use high-quality data in every clinical trial stage. There’s been a continuous increase in clinical data management efforts, which are reflected in related healthcare guidelines, books, and publications. However, as much as new measures are being made, there are still several sources of errors in clinical trials regarding data entry, collection, and processing. Fig. 01 · Clinical trials 4 phases Phases of a clinical trial - IPhase I - Evaluate safety - Find a safe dose - Identify side effects - IIPhase II - Test effectiveness - Further evaluate safety - IIIPhase III - Confirm effectiveness - Monitor side effects - Compare with other treatments - Collect information - IVPhase IV - After approval: more information on risks, benefits and use ## How automation and RPA help to improve the efficiency of clinical trials [Robotic Process Automation (RPA)](https://www.flobotics.io/blog/robotic-process-automation) continues to be an innovative and effective technology across many industries within the economy, automating repetitive and manual processes. Given that RPA focuses on integrating several IT systems, improving employee productivity, and eliminating human error, RPA has become a useful technology in the Life Sciences industry, especially in clinical trials. As explained earlier, Randomized Clinical Trials (RCT) are the standards for evaluating new therapeutics in terms of safety when used in human subjects. Presently at a success rate between 40% to 80% across various phases, clinical trials are still considered to have significant failures due to patient recruitment. Furthermore, with many challenges to overcome when conducting RCTs, the cost of trials is still very high. Some challenges that affect RCT include study design, trial sites, patient retention, availability of the patient, and principal investigators. However, with the integration of RPA, these challenges can be checked, thereby increasing the efficiency and success rate of clinical trials. Robotic Process Automation can improve rule-based processes and workflows in clinical trials. This is because the bots can manipulate data, transaction processes, and system calibration facilities while improving storage. ## The benefits of RPA to clinical trials ### Eliminate Monotonous Manual Data Collection Robotic Process Automation (RPA) brings about infinite possibilities. Through the integration of RPA, Life Sciences companies can effectively speed up the duration of the vaccine market while enhancing regulatory measures and safety. Through the integration of RP, valuable time is saved during clinical trials, freeing healthcare professionals to perform other tasks. RPA effectively promotes efficiency by providing a continuous, error-restructured data collection technique. ### Automate Analysis To Show Extensive Effect Overview With RPA, the Life Science industry can adequately integrate quick data to analyze and detect the overall effect of formulated drugs and vaccines. The patients will be able to notify RPA bots of all side effects. These robots, in turn, then combine this data with medical historical data and external sources such as location-based data or weather to provide a general overview for additional analysis. After introducing such a vaccine or drug into the market, the same RPA bots also assist in analyzing the side effects of such drugs that were not predetermined. These side effects, including market sentiments, are collected daily and integrated with previous analyses. This is to continuously manage and monitor the vaccine’s impact on the market. At the end of it all, integrating RPA bots enhances operational efficiency and improves the management of clinical trial audit logs and compliance with pharmacovigilance regulations. ### Assist In Validation Processes RPA bots can be integrated to be involved in validation processes. However, the process of integration is not that simple. To program bots to validate various clinical methods, stringent regulations are required for each separate system that supports the development of medicine or vaccines. Therefore, a well-structured robot configuration framework, change management, and validation are required to prevent confirmation errors. This is very crucial to the process of integrating RPA solutions. Other benefits include: - Facilitates quick response to patience, which helps to improve the progress of both the doctor and the patient. - Provides patients with one-point access to their data profile - Assist in scheduling appointments and make immediate reminders for the patient and the doctor. - Facilitates healthcare professional cross-platform access to information Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## RPA Clinical Trials Use-cases Fig. 02 · Clinical trials RPA use cases What RPA can automate in clinical trials - 01Patient matching - 02Trial master file management - 03Pharmacovigilance case processing - 04Regulatory submissions Business endpoints that can be optimized using RPA are: ### Patient Matching Creating a patient population using dynamic exclusion and inclusion to evaluate the effect of a trial is usually overwhelming. However, the integration and use of RPA effectively perform this task. As a result, the eligible patient population can be easily enlarged by the study designer if there’s a need for modification. Automating patient matching with RPA makes the entire process better and faster. RPA effortlessly increases recruitment speed by carrying out initial execution with potential patients before the decisive interaction with associates of the clinic. RPA assists in lessening the effort put into repetitive tasks at the patient recruitment stage for a clinical study. ### Processing Pharma Co-vigilance Cases Based on a study by ClinicalResearchNewsOnline.com, it is estimated that big pharmaceutical companies, on average, process about 700,000 adverse incident cases annually. With this kind of pressure on big Pharma companies, a lot of these companies plan to go lean to reduce costs while increasing the caseload and not jeopardizing the base cost. Today, about 50% of the PV resources are utilized to manage cases needing data integration. However, according to [RoboticsandAutomationNews.com](https://roboticsandautomationnews.com/), automation of these manual steps can reduce the time spent on PV by 45%, saving big Parma companies a lot of money yearly. ### Trial Master Process Management Sponsors of clinical trials are known to record every activity carried out in a clinical study. This includes various sites in a master data repository called Trial Master File (TMF). Presently, these data are still manually inputted into the TMF structures. As a result, sponsors with many CROs have to create multiple TMFs, which are often not efficiently integrated. Errors during this integration are known to limit the level of insights drawn from the TMF. That’s not all; additional resources must be trained and equipped to verify and maintain each system. However, with more healthcare companies integrating RPA, the trial controller process management is carried out quickly and efficiently. This is because uploading data and documents into the TMF becomes automatic. The integration of RPA has proven to lessen the time spent on data entry by a whopping 90%, saving millions of dollars on each clinical trial every year. ### Regulatory Submission Process The process of submission for regulatory activities is usually slow. It involves pharmaceutical companies participating in activities like compiling [health records](https://www.flobotics.io/blog/electronic-health-records-rpa) and monitoring the status of documents. Automating this process via RPA has been observed to reduce the time to market a product significantly. ## Conclusion It has become obvious that RPA is the answer to increasing the efficiency of repetitive but vital administrative tasks in clinical processes. RPA is gradually enhancing the efficiency of pharmaceutical firms in focusing on producing effective and safe drugs at a meager cost to the market. Learn more about [the processes in the healthcare industry that can be automated](https://www.flobotics.io/blog/healthcare-workflow-automation). RPA now effortlessly assists in preventing delays in the introduction of drugs into the market. It also helps to redistribute tasks of higher values, such as core research and development, to employees. At [Flobotics](https://www.flobotics.io/), we give a wide range of RPA consulting services; help recognize automation opportunities, analyze these healthcare processes, establish essential infrastructures, and develop sustainable and stable bots. #### Like the article? Spread the word Written byMichał Rejman Chief Marketing Officer at Flobotics. [More from Michał](https://www.flobotics.io/our-editorial-team#rejman) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ Healthcare ### Laboratory Automation Solutions: Enhancing Efficiency and Compliance in Healthcare Laboratory automation solutions: streamline sample processing and test result interpretation to future-proof your lab operations. Bart TeodorczukSeptember 24, 2024 ](https://www.flobotics.io/blog/laboratory-automation-solutions)[ RCMHealthcare ### Medical Coding Automation: Why (and How) Should You Start? Medical coding services, automated: how RPA improves claims accuracy and cuts manual coding errors for healthcare providers. Karl MielnickiMay 13, 2022 ](https://www.flobotics.io/blog/medical-coding)[ HealthcareEligibilityClaims ### Implementing Automated Claims Processing in the Medical Industry Medical claims processing automation: see how RPA replaces costly manual workflows with automated claims for practices of every size. Karl MielnickiOctober 01, 2021 ](https://www.flobotics.io/blog/claims-processing-in-medical-industry) [All articles →](https://www.flobotics.io/blog) --- # Implementing Automated Claims Processing in the Medical Industry Canonical: https://www.flobotics.io/blog/claims-processing-in-medical-industry Author: Karl Mielnicki Published: 2021-10-01 Updated: 2026-09-12 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Implementing Automated Claims Processing in the Medical… CTO Notes [Claims](https://www.flobotics.io/blog?category=claims)[Eligibility](https://www.flobotics.io/blog?category=eligibility)[Healthcare](https://www.flobotics.io/blog?category=healthcare) # Implementing Automated Claims Processing in the Medical Industry [Karl MielnickiCTO & Co-Founder of Flobotics](https://www.flobotics.io/our-editorial-team#mielnicki) Published October 01, 2021Updated September 12, 2026 On this page - [Manual Claims Processing VS Automated Claims Processing](#manual-claims-processing-vs-automated-claims-processing) - [Ensure Your Business Processes Are Efficient](#ensure-your-business-processes-are-efficient) - [How to implement RPA into claims processing](#how-to-implement-rpa-into-claims-processing) - [Use cases of RPA in healthcare](#use-cases-of-rpa-in-healthcare) - [Conclusion](#conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) No matter the country, the healthcare sector is a complex but vital system to its citizens’ general well-being. Due to the complex nature of the healthcare system, managing data that relates to scheduling applications, clinical applications, enterprise resource planning (ERP), HR, radiography information systems, and third-party portals is usually an overwhelming task. And that’s not all, the integration of these processes across the healthcare system is also very labor-intensive and challenging. The healthcare system is so complex that, to guarantee seamless patient care delivery, there’s a need for stakeholders, insurance companies, doctors, including the patient to fully cooperate and work together. However, that has proven difficult due to the level of paperwork that continues to increase with the increase in healthcare patients. According to the [AMA's 2025 survey on the administrative burden of prior authorization](https://www.ama-assn.org/press-center/ama-press-releases/ama-survey-prior-authorization-reform-pledge-falls-short-physicians), physicians and their staff spend an average of 13 hours a week just on prior authorization tasks. To this end, a good percentage of healthcare companies are beginning to adopt [Robotic Process Automation (RPA)](https://www.flobotics.io/blog/robotic-process-automation) as an effective solution to the paperwork involved in hospital processes. When integrated into a healthcare system RPA effectively processes data in record time and addresses the challenges that result from human error. As a result, healthcare companies can increase operational efficiency, reduce cost, and rid their systems of human errors as regards data processing. ## Manual Claims Processing VS Automated Claims Processing [Insurance claims processing](https://www.flobotics.io/agents/claims-management-automation) is a detailed workflow involving lots of checkpoints that every claim must pass through before getting approved. When claims make it through all these checkpoints without issues, the insurer approves and processes it for any insurance payments. If it doesn’t, the claim is rejected and sent back for proper vetting and analysis. Processing claims has mostly been done manually for years. The automation solutions that existed on the market were usually expensive and available only for large practices and billing providers. RPA is changing the game - thanks to Robotic Process Automation we can build small and effective automation on a budget, even for the smallest companies. Some of the benefits offered by automated claims processing over manual include: #### Improved Processing Speed Manual claims processing takes a lot of time because humans can only carry out a single claim at a time. With automation, you gain speed through computational power and multithreading. Additionally, automation allows healthcare workers to focus on other tasks and develop new skills, increasing productivity over time. #### Improves Reliability Automated claims processing ensures that tasks are carried out on time and in the correct sequence. Reliability is not affected by staff absence. In contrast, human fatigue impacts performance. According to a [national study on physician counseling for stress published in JAMA Internal Medicine](https://pmc.ncbi.nlm.nih.gov/articles/PMC4286362/), 60–80% of primary care visits may have a stress-related component. With RPA, doctors have more time to rest, and reliability increases. #### Cost Savings Not having to manually process every claim allows healthcare companies to reduce staffing needs. Fewer employees mean lower payroll costs and reduced recruitment expenses. Additionally, automation reduces overhead costs, as fewer supplies and resources are needed. Flobotics's own [eligibility checks automation case study](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) shows this play out in practice, with a 100% ROI in just 23 days and roughly $180,000 in projected first-year savings. #### Customer Satisfaction Automation reduces patient wait times and increases efficiency. Faster service leads to higher satisfaction. Customer loyalty and trust often begin with satisfaction, and satisfied patients are more likely to recommend your services. The Checklist Before Implementing Automated Claims Processing Automating claims processing improves efficiency and reliability, but certain conditions must be met before implementation. ### Ensure Your Business Processes Are Efficient Claims processing can be automated because it follows predefined rules. Before automation, processes should be clearly mapped and optimized. Automating inefficient workflows only scales problems. If your process has 10 steps, refine it before automating. #### Consider Organizational Readiness Automation introduces change. Ask: - Will automation support your employees? - Will it improve collaboration between staff and systems? - Is it user-friendly for customers? - Can it support continuous improvement? #### Avoid Over-Automation at Once Trying to automate everything at once increases complexity and risk. Start small and scale gradually. #### Automate Workflows Thoughtfully RPA enhances business process automation and workflow efficiency. Modern RPA tools are now accessible beyond large enterprises. Ensure the solution is user-friendly, scalable, and integrates with your EHR. There is also an opportunity to provide holistic automation of key business processes using Intelligent Automation. Flobotics's [overview of agentic AI tools and platforms](https://www.flobotics.io/blog/agentic-ai-tools-platforms-overview) covers how these systems build on RPA foundations. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## How to implement RPA into claims processing [Claims processing automation ](https://www.flobotics.io/agents/claims-management-automation) begins by mapping front-line insurance workflows. These processes are then translated into automation scripts that move data across systems. RPA is typically implemented by internal teams or consultants. Before purchasing any software, define your use cases, as Flobotics's [100 real-world RPA use cases across industries](https://www.flobotics.io/blog/rpa-use-cases-across-industries) illustrates. Implementing RPA may seem complex, but it can be broken down into simple steps: Step 1: Identify subprocesses suitable for automation Step 2: Prioritize use cases based on impact Step 3: Define rules and requirements for automation bots ## Use cases of RPA in healthcare #### Patient Scheduling RPA allows patients to book appointments automatically, reducing administrative workload and improving experience. #### Claim Management RPA automates repetitive tasks such as data input and processing, reducing errors and speeding up workflows. Flobotics's own [claims management automation case study](https://www.flobotics.io/case-studies/98-reduction-in-manual-claim-prep-claims-management-automation) shows this in practice, with a 98% reduction in manual claim prep and roughly six FTEs redirected to higher-value work. #### Regulatory Compliance RPA logs every action, ensuring audit readiness and compliance. #### Data Entry / Migration / Extraction RPA extracts and transfers data from legacy systems into modern digital systems. It also supports data migration for analytics and research. #### Industry-Agnostic Use Cases Processes like accounting and expense management can also be automated using RPA. ## Conclusion Robotic Process Automation is an effective solution for streamlining healthcare claims management. From data validation to automated workflows, the benefits are significant. At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) ## FAQ: Can medical billing be automated? Much of it can. Eligibility checks, claim scrubbing, and routine denial resubmission are high-volume and rule-based, making them well suited to automation, while complex appeals and patient-facing conversations still benefit from human judgment. What are the main steps in the medical billing process? Registration, eligibility verification, the patient encounter, coding, charge entry, claim scrubbing, submission, payer adjudication, payment posting, and denial management or patient billing. Written byKarl Mielnicki CTO & Co-Founder of Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### RPA Failures: 10 Most Common Reasons and How to Avoid Them RPA failures: Flobotics' CTO breaks down the 10 most common reasons automation projects fail and how to avoid them. Karl MielnickiJuly 06, 2021 ](https://www.flobotics.io/blog/rpa-failures)[ RPA ### RPA Reloaded: 50+ Robotic Process Automation Statistics to Know in 2026 RPA statistics 2026: 50+ data points on robotic process automation adoption, ROI, and where the technology is headed next. Yana PokoraApril 15, 2025 ](https://www.flobotics.io/blog/rpa-statistics)[ RPA ### Why Your Non-Technical RPA Developer Sucks RPA for non-technical developers: why coding skills still matter and where non-technical RPA developers fall short. Karl MielnickiJune 15, 2021 ](https://www.flobotics.io/blog/rpa-non-technical-developer) [All articles →](https://www.flobotics.io/blog) --- # 8 Best Security Practices for RPA Implementation Canonical: https://www.flobotics.io/blog/8-security-practices-for-rpa-implementation Author: Krzysztof Szwed Published: 2021-09-20 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/8 Best Security Practices for RPA Implementation [RPA](https://www.flobotics.io/blog?category=rpa) # 8 Best Security Practices for RPA Implementation [Krzysztof SzwedHead of Delivery at Flobotics](https://www.flobotics.io/our-editorial-team#szwed) Published September 20, 2021Updated September 1, 2026 On this page - [What is RPA?](#what-is-rpa) - [Risks associated with RPA](#risks-associated-with-rpa) - [1. Compliance Risks](#1-compliance-risks) - [2. Operational Risks](#2-operational-risks) - [Source of risks associated with RPA](#source-of-risks-associated-with-rpa) - [8 Best practices for Robotic Process Automation security](#8-best-practices-for-robotic-process-automation-security) - [2. Minimize the attack surface area​](#2-minimize-the-attack-surface-area) - [3. Don't trust services](#3-don-t-trust-services) - [4. Apply the principle of least privilege](#4-apply-the-principle-of-least-privilege) - [5. Protect log integrity](#5-protect-log-integrity) - [6. Ensure secure RPA development](#6-ensure-secure-rpa-development) - [7. Apply the principle of defense in depth](#7-apply-the-principle-of-defense-in-depth) - [8. Keep security simple](#8-keep-security-simple) - [Conclusion](#conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Robotic Process Automation (RPA) is rapidly gaining traction around the globe, and it is now regarded as an essential element of digital transformation actions. Over 78% of those who have already implemented RPA expect to significantly increase their investment in RPA over the next three years. Like any program within a network, there's always the risk of an attack, especially if key security principles were not considered during its implementation. Designing an RPA solution poorly can cause a serious breach of security controls and result in sensitive data being revealed to untrusted parties. Besides, automating a process within an organization does not translate to you adequately securing the process. So, if you consider implementing RPA as part of your digital transformation, we've put together the best security practices for your organization's benefit. Remember that choosing the right RPA developer is one of the essential parts of implementing Robotic Process Automation for your business. ## What is RPA? [Robotic Process Automation](https://www.flobotics.io/blog/robotic-process-automation) is the use of scripts and software algorithms to effectively and securely automate the repetitive and mundane tasks that human resources in a company would usually perform. If applied and implemented in the right manner, RPA software algorithms can considerably improve productivity, accuracy, and quality of data and adherence. You can easily Implement RPA in [finance](https://www.flobotics.io/blog/rpa-for-finance) and banking, real estate, or any other industry. Not just that, RPA is known to empower human resources to concentrate and focus on tasks that involve more human interaction and fulfilling work. Make sure that RPA is what you need on a call with our battle-proven RPA consultants. Fig. 01 · RPA 7 benefits Main benefits of RPA implementation - 01Enhanced control - 02Faster processes - 03Lower costs - 0424/7 operation - 05Data accuracy - 06More transactions handled - 07Better visibility of process performance ## Risks associated with RPA One of the alluring features of RPA is its ease of implementation. As a result, many organizations' departments and sectors can set up an RPA bot with IT or sometimes without letting IT know what they are up to. While this seems like an advantage since most IT departments are stretched to the limit, it comes with many security risks. Many individuals or teams who implement RPA without partnering with a competent IT consultant most times have no idea about such security risks. Hence, the danger to the whole security system. The primary risks associated with the integration of Robotic Process Automation can be viewed in two parts: - Compliance risk - Operational risk ### 1. Compliance Risks Compliance risks stem from poor RPA governance, created by various implementation methods that bypass established software development lifecycles and ideal practices that meet data privacy, enterprise architecture, and network security. ### 2. Operational Risks Operational risks include regulatory preparedness towards establishing barriers and everyday controls supporting business continuity and scalability. The fundamental factor responsible for operational and compliance risk is the fragmented approach many organizations employ when establishing many of these automation programs. To curb these risks, business and IT leaders must come together to choose the ideal RPA solution. Not just that, IT leaders must properly operate and design a Center of Excellence that can support a standard where IT tackles regulatory concerns, networks, and data. On the other hand, business leaders need to concentrate more on identifying areas and best [use cases of RPA](https://www.flobotics.io/blog/rpa-use-cases-across-industries) within the organization. Therefore, RPA can effectively contribute to maintaining daily operations while developing programmers' skills and implementing RPA bots. ## Source of risks associated with RPA It is important to have a vast understanding of Robotic Process Automation before integrating the software. And one of the comprehensive things to remember about RPA security is that many of the risks associated with RPA arise from poor care and lack of oversight. Lack of proper planning and oversight of integrating RPA robots into an organizational system can cause more havoc than a strategic procedure. And for many IT leaders who don't know, integrating RPA is not a solution to a firm's lack of security hygiene. It is more likely to exacerbate security issues if they are not rectified first. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## 8 Best practices for Robotic Process Automation security Proper security measures are crucial to implement Robotic Process Automation within an organization successfully. Sensitive data such as customer data and RPA credentials that the RPA software handles need to be protected as they can be exposed to attackers. Proper security frameworks and governance are important to mitigate these risks. There are about eight security practices IT leaders and professionals can carry out to address these security failures and risks in RPA projects. Fig. 02 · RPA security 8 steps Steps to keep RPA secure - 01 Keep security simple - The simpler a bot is, the easier it is to protect from attacks - 02 Prevent abuse and fraud - Lock down bot behavior - Use privileged session management - 03 Protect log integrity - Make sure the RPA tool has full audit capabilities - 04 Develop RPA securely - Use review and change control for RPA scripts - 05 Don't trust services blindly - Check that the service your bot uses handles and processes data securely - 06 Defense in depth - Input verification and data validation - Limited file permissions - Output encoding - 07 Minimize the attack surface - Limit remote data - Limit excessive data input - Load files from a central configuration - 08 Make bot actions accountable - Give each bot and process its own identity - Rotate bot credentials often 1. Ensure accountability for bot actions Many firms and organizations during the Covid pandemic rushed to implement RPA software and algorithms. Most of these implementations were done to reduce the cost of performing repetitive and menial tasks while also reducing cost. However, most firms failed to differentiate between bot identities and bot operators. Hence no accountability was set for bot actions. You must ensure accountability for bot actions to keep the RPA project security tight and secured. This is done by assigning a special identity to every RPA bot and process. Furthermore, implementing password and username authentication along with a two-factor human-to-system will also go a long way in securing your RPA project. ### 2. Minimize the attack surface area​ Attackers look for the weakest avenue in a system to attack and exploit a security system hence the need to defend your avenues from all forms of attack. The fewer weak avenues of attack found in a security system, the harder it is to hack by attackers. To ensure you have a reduced surface area attack, you must limit; - the amount of remote data - excessive data input - the services and connections they both utilize - inputting files and formats to a centralized, single, standard configuration. Implementing these approaches will go far in minimizing attack surface area while reducing the RPA bot's complexity. ### 3. Don't trust services One of the important features of the RPA bot is its ability to work with various services from a wide range of sources. While this is an advantage, it can also be a disadvantage, as not all these sources can be trusted to contain safe data. Therefore, as an IT professional, you should not consider all services or process data they gather as containing safe data. By assuming that all service data or API is untrusted, you naturally establish extra data validation and security controls to ensure the bot can adequately and securely process data. ### 4. Apply the principle of least privilege Applying the principle of least privilege entails programming your bot only to have access to the exact resources and files it requires to carry out its tasks. To adequately secure your RPA project, ensure all elevated permission actions and executive rights are only utilized when needed. Furthermore, any account your bot uses to connect to remote sources should be supplied with just the next trial permissions required by the bot to carry out its task. By doing this, sensitive and crucial data are not exposed in a cyber-attack as the RPA bot can't execute any action outside the permission. ### 5. Protect log integrity In the case where RPA security fails, the IT and security team will need to look at and review your logs. Organizations and firms usually store RPA loggings to a different system to ensure its safety and vouch for its forensic integrity. As an IT and security leader, you must ensure that the RPA tool offers a comprehensive system-generated log without any voids that might impede the investigation. ### 6. Ensure secure RPA development RPA development is always a continuous process as it needs to evolve and develop to tackle various threats and vulnerabilities. However, to speed up the rate of development, firms usually suspend security considerations till RPA algorithms are prepared to run. To ensure secure RPA development, you must create visionary conversations and standard measures between the line of business and security teams. This can be done by establishing a risk structure that assesses RPA implementation. Not just that, testing RPA scripts with a unique emphasis on business log vulnerabilities will also go a long way in securing RPA development. ### 7. Apply the principle of defense in depth Adequate software security requires a layered technique called defense in depth. This implies establishing numerous strategies to protect and secure RPA projects against attacks. For a procedure such as inputting file assets, it might require numerous approaches such as; - input verification and data validation - limit on the permissions of the file and - data output encoding After these procedures, the data output is displayed on the screen or passed to any output console. ### 8. Keep security simple The simpler a bot is, the easier it is to protect from attacks. Like reducing the surface area of attack, keeping your bot security management as simple as possible will enhance its entire defense. ## Conclusion The digital world has exposed all sectors to various kinds of cyber-attacks and hacks, so security must be treated as serious business. To this end, IT consultants and developers who are experts in RPA must be employed to secure and protect the project adequately. [Flobotics](https://www.flobotics.io/) is one of the top IT consulting companies (with experienced UiPath developers) that can adequately implement RPA software within your organization and protect your RPA from all security risks. We are just [one call or message away](https://www.flobotics.io/contact) if you need the best experts on RPA technology to book your free RPA consulting session. #### Like the article? Spread the word Written byKrzysztof Szwed Head of Delivery at Flobotics. [More from Krzysztof](https://www.flobotics.io/our-editorial-team#szwed) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### RPA Reloaded: 50+ Robotic Process Automation Statistics to Know in 2026 RPA statistics 2026: 50+ data points on robotic process automation adoption, ROI, and where the technology is headed next. Yana PokoraApril 15, 2025 ](https://www.flobotics.io/blog/rpa-statistics)[ RPA ### RPA Failures: 10 Most Common Reasons and How to Avoid Them RPA failures: Flobotics' CTO breaks down the 10 most common reasons automation projects fail and how to avoid them. Karl MielnickiJuly 06, 2021 ](https://www.flobotics.io/blog/rpa-failures)[ Healthcare ### Building Automated HIPAA Compliance Workflows with RPA: What Do You Need to Know? HIPAA-compliant automation: how to build RPA workflows that keep healthcare data secure and satisfy HIPAA requirements fully. Michał RejmanAugust 23, 2021 ](https://www.flobotics.io/blog/hipaa-compliance-rpa) [All articles →](https://www.flobotics.io/blog) --- # Building Automated HIPAA Compliance Workflows with RPA: What Do You Need to Know? Canonical: https://www.flobotics.io/blog/hipaa-compliance-rpa Author: Michał Rejman Published: 2021-08-23 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Building Automated HIPAA Compliance Workflows with RPA:… [Healthcare](https://www.flobotics.io/blog?category=healthcare) # Building Automated HIPAA Compliance Workflows with RPA: What Do You Need to Know? [Michał RejmanChief Marketing Officer at Flobotics](https://www.flobotics.io/our-editorial-team#rejman) Published August 23, 2021Updated September 1, 2026 On this page - [HIPAA compliance and what does it mean](#hipaa-compliance-and-what-does-it-mean) - [What is Protected Health Information?](#what-is-protected-health-information) - [What are the primary HIPAA compliance rules?](#what-are-the-primary-hipaa-compliance-rules) - [What are the most common HIPAA compliance violations?](#what-are-the-most-common-hipaa-compliance-violations) - [The need to automate healthcare workflow](#the-need-to-automate-healthcare-workflow) - [1. Preventing HIPAA violations with automation and RPA](#1-preventing-hipaa-violations-with-automation-and-rpa) - [2. Poorly-managed patient flow](#2-poorly-managed-patient-flow) - [3. Burnouts](#3-burnouts) - [4. High risk to medical personnel](#4-high-risk-to-medical-personnel) - [HIPAA compliance with RPA – conclusion](#hipaa-compliance-with-rpa-conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Advancement in technology has fostered dramatic changes in all sectors of the economy, and the healthcare sector is not an exception. Thanks to AI and automation, the healthcare sector can now say goodbye to repetitive, time-consuming, and mundane tasks. Hence, patients’ care and quality medical services become a top priority and importance. However, the integration of AI and automation of the healthcare sector isn’t limited to just performing repetitive tasks and streamlining tedious routines. In most cases, automation becomes the [medical staff’s helping hand](https://www.flobotics.io/) in organizing patients’ data and transmitting information remotely and instantly. Nevertheless, healthcare companies mustn’t get carried away by the vast potential of automation in the healthcare industry. It is important to remain compliant with essential data regulations and restrictions. The reason for these regulations? Healthcare data are susceptible and delicate; hence, the reason to protect them against hackers and cyberpunks. Therefore, there are severe consequences for not following up on these regulations and doing things wrong with the data. Today, one of the vital regulations every healthcare company must stay compliant with is HIPAA. And lucky enough, a perfectly integrated robotic process automation can help protect health data and [create HIPAA-compliant workflows](https://www.flobotics.io/rcm-automation) within the healthcare sector. ## HIPAA compliance and what does it mean [The Health Insurance Portability and Accountability Act](https://www.cdc.gov/phlp/php/resources/health-insurance-portability-and-accountability-act-of-1996-hipaa.html) of 1996 otherwise known as HIPAA is a United States legislation that provides regulations for how healthcare companies secure and manages Protected Health Information (PHI) and patient data. It is a sequence of standards that oversee the disclosure and use of Protected Health Information. Healthcare organizations and vendors like medical device companies, SaaS solutions, and health tech companies must implement all HIPAA measures to be certified HIPAA compliant and work with patient information and data. Fig. 01 · HIPAA Who must comply Who has to comply with HIPAA - 01Healthcare providers - 02Health plans - 03Healthcare clearinghouses - 04Business associates ### What is Protected Health Information? [Protected Health Information (PHI)](https://www.hhs.gov/answers/hipaa/what-is-phi/index.html) is demographic health data established, collected, stored, or delivered by HIPAA-covered organizations and their business associates concerning the outlay of patient care, healthcare policies, and expenses for healthcare services. PHI consists of previous, present, and even prospective health information about a patient’s medical conditions (both physical and mental health). This health information can be delivered in electronic, spoken, and material forms. The PHI also includes health histories, [health records](https://www.flobotics.io/rcm-automation), medical bills, lab test results, and demographic information like patients’ names, phone numbers, addresses, phone numbers, financial information, Social Security number, photos of the face, medical records, and so on. Ensuring the confidentiality of this Protected health information is key, and to do that, HIPAA-covered organizations will have to put in place administrative, technical, and physical measures as stipulated by the HIPAA Security Rule. ### What are the primary HIPAA compliance rules? The HIPAA regulation consists of various types of HIPAA rules, and these include; Fig. 02 · HIPAA 4 rules The main HIPAA rules - 01Privacy RulePatients' rights over their protected health information - 02Breach Notification RuleWhat covered organizations and business associates must do after a data breach - 03Security RuleSafe handling, transmission and storage of electronic PHI - 04Omnibus RuleBusiness associates must comply too; sets out BAA procedures #### The HIPAA Compliance Privacy Rule The privacy rule outlines the criteria for patients’ rights to Protected Health Information. Some privacy rule criteria include healthcare providers’ rights to deny access to PHI, patients’ right to access PHI, the contents of Notices of Privacy Practices, and so on. Every one of these criteria ideally should be documented and stored in the company’s HIPAA procedures and policies, and the company’s employees should be educated on these criteria every year. #### The HIPAA Compliance Security Rule The security rule outlines the criteria for the safe handling, transmitting, and maintaining electronic PHI. The security rule applies to both covered organizations and business associates. Like the privacy rule, ideally, these criteria should be documented and stored in the company’s HIPAA procedures and policies. The company’s employees should be educated on these criteria every year. #### The HIPAA Breach Notification Rule The breach notification rule outlines the criteria that apply to covered organizations and business associates in case of a data breach where ePHI and PHI are concerned. Healthcare companies are mandated to report and document both types of violations. #### The HIPAA Omnibus Rule In 2013, the Omnibus rule established the most important modifications to the criteria affecting both the HIPAA Security and Privacy rules. This new rule enhanced the power of the Office for Civil Rights to execute the regulations and to charge fines if violated. The HIPAA Omnibus Rule states that business associates must remain compliant with HIPAA regulations while outlining the procedures of Business Associate Agreements (BAAs). Business Associate Agreements (BAAs) are contracts that must be finalized between a covered entity and a business associate before ePHI and PHI are shared or transferred. ## What are the most common HIPAA compliance violations? Many healthcare companies have been found guilty of violating HIPAA violations. Some are due to ignorance, honest mistakes, or a breach in their security system. Fig. 03 · HIPAA 9 causes The most common causes of HIPAA violations - Sending PHI to the wrong contact or patient - Discussing PHI outside the office - Ransomware attack - Hacking and cyberattacks - Lost or stolen phone, USB drive or laptop - Office break-in - Business associate breach - Malware incident - Sharing sensitive information on social media Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## The need to automate healthcare workflow To help remain HIPAA compliant and minimize security risks while also facilitating a successful doctor-patient relationship, many healthcare companies are beginning to embrace automation and integrate RPA within their system. According to reports, approximately 50% of a healthcare company’s budget is squandered on inefficient processes, while the financial benefits of implementing automated workflow are venomous. Across the United States, healthcare companies have saved between $37M and $59M in five years. Fig. 04 · RPA in healthcare Why Why use RPA in healthcare - 01Prevents direct HIPAA violations - 02Automates document processing - 03Cuts the paperwork workload - 04Improves the patient experience Some of the primary reasons why healthcare workflow needs to be automated include; ### 1. Preventing HIPAA violations with [automation and RPA](https://www.flobotics.io/) Penalties for HIPAA violations are quite severe, be it the healthcare company’s fault or not. For example, the penalty for violating HIPAA by sending PHI to the wrong contact or patient is [a fine of $50,000. ](https://www.truevault.com/resources/compliance/how-much-do-hipaa-violations-cost#:~:text=HIPAA%20violations%20are%20expensive.,violations%20of%20an%20identical%20provision.) The common tone of hospitals and clinics is not calm and of pleasant attitudes; hence, omissions and errors regarding document-related issues aren’t far-fetched. The steps and procedures required to fill and enter specific information approved by patients are usually long and involve chasing people down to get approvals. All these typically lead to skipping some procedures and making the simplest errors. However, by perfectly implementing RPA and automating healthcare workflow, patients’ data are automatically transferred and processed. This reduces the risk of violating HIPAA regulations while also erasing the need for administrators to perform repetitive and mundane tasks. About 80% of medical professionals claim that automation and electronic prescriptions have significantly reduced human interaction and the time to finalize the paperwork. ### 2. Poorly-managed patient flow A continuous and steady patient flow prevents delays in patient care deliveries and overcrowding. However, that’s usually not the case when it comes to reality. Hospitals, especially the emergency department, are often overcrowded, with patients having to hang around due to lengthy wait times. This reality reflects one of the hospitals’ most time-consuming workflows: getting approvals. All documents dealing with PHI must be approved and signed by healthcare professionals or administrators, which usually takes so much time. This is the space that RPA and automation need to fill. With automated workflow, doctors, administrators, patients, and so on can sign, finalize and exchange paperwork in real-time without physical interactions. The bot(s) automatically informs parties involved to sign, review and fill out documents depending on the conditions set by the healthcare company. ### 3. Burnouts One of the major complaints from medical professionals is burnout. Today, we can better understand medical professionals burning out due to the Covid pandemic. Even during periods of less severe health dilemmas, 50% of healthcare professionals still suffer from burnout. What is the most common reason for burnout? The additional workload of administrative paperwork such as billing, overseeing, and reporting documentation. However, with automation, burnout of healthcare professionals is considerably minimized since robots take care of the administrative paperwork. There’s been a report that healthcare companies that fully automate their processes audit patients’ records in approximately 1.4 hours compared to 4 hours using[ human resources. ](https://www.flobotics.io/blog/rpa-in-hr-and-recruitment) ### 4. High risk to medical personnel The risk to medical personnel has also been considerably reduced courtesy of many healthcare companies integrating RPA within their system. The risk medical professionals subjected to moving very close to sick patients and stake contracting diseases has been minimized via automation. Frankly, that’s the reality of every doctor, and they can’t avoid patients. However, healthcare companies now look for ways to preserve the health and energy of medical practitioners through automated workflows. Designing and developing a good robotics implementation requires a deep level of technicality. While it is true that anyone can learn to code robots, not everyone will be good at it. [Read why non-technical RPA developers can be a reason for RPA project failure](https://www.flobotics.io/blog/rpa-non-technical-developer). So you’ll be able to implement the automation properly. By integrating RPA, there’s no need to reschedule meetings with patients to clarify details and complete necessary paperwork. Healthcare professionals can access, authorize and send patients’ data and information from the comfort of their offices or homes from any device. ## HIPAA compliance with RPA – conclusion With all being said, it is evident that integrating RPA and the automation of healthcare workflows is the better thing to do. At [Flobotics](https://www.flobotics.io/), we are a group of experts who are vast in analyzing healthcare processes, recognizing automation opportunities, establishing necessary infrastructures, and developing sustainable and stable robots. Learn more about [processes in the healthcare industry](https://www.flobotics.io/blog/healthcare-workflow-automation) you didn’t know can be automated and will be HIPAA-compliant. Recognizing how important being HIPAA compliant is for healthcare companies, by providing [RPA consulting services](https://www.flobotics.io/about-us), Flobotics centralizes healthcare data and processes while offering the flexibility to scale up or down whenever necessary. With RPA, healthcare companies can control and oversee the entire ecosystem better and much closer. #### Like the article? Spread the word Written byMichał Rejman Chief Marketing Officer at Flobotics. [More from Michał](https://www.flobotics.io/our-editorial-team#rejman) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ Healthcare ### Healthcare Compliance Automation: Laws, Benefits and Examples Compliance automation software for healthcare: how RPA helps organizations meet evolving regulations without adding manual review work. Filip NasiadkoOctober 09, 2023 ](https://www.flobotics.io/blog/compliance-automation)[ RPA ### 8 Best Security Practices for RPA Implementation RPA security best practices: 8 steps to manage the security risks of your organization's automation implementation. Krzysztof SzwedSeptember 20, 2021 ](https://www.flobotics.io/blog/8-security-practices-for-rpa-implementation)[ RCMAIHealthcare ### Agentic AI in Healthcare: From Hype to Real-World Impact Agentic AI in healthcare: how it differs from generative AI like ChatGPT and where it's already driving real clinical impact. Jędrzej SzymulaSeptember 22, 2025 ](https://www.flobotics.io/blog/agentic-ai-in-healthcare) [All articles →](https://www.flobotics.io/blog) --- # Top RPA Use Cases in the Insurance Industry Canonical: https://www.flobotics.io/blog/rpa-in-insurance-use-cases Author: Yana Pokora Published: 2021-08-10 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Top RPA Use Cases in the Insurance Industry [Eligibility](https://www.flobotics.io/blog?category=eligibility)[RPA](https://www.flobotics.io/blog?category=rpa) # Top RPA Use Cases in the Insurance Industry [Yana PokoraContent Manager at Flobotics](https://www.flobotics.io/our-editorial-team#pokora) Published August 10, 2021Updated September 1, 2026 On this page - [What is Robotic Process Automation (RPA)](#what-is-robotic-process-automation-rpa) - [The use of RPA to solve various challenges in the insurance sector](#the-use-of-rpa-to-solve-various-challenges-in-the-insurance-sector) - [How RPA Solves Problems In The Insurance Sector](#how-rpa-solves-problems-in-the-insurance-sector) - [Simplifying Claims Processing](#simplifying-claims-processing) - [Scalability](#scalability) - [Non-intrusive Compatibility](#non-intrusive-compatibility) - [Legislation Compliant](#legislation-compliant) - [RPA Use-cases In The Insurance Industry](#rpa-use-cases-in-the-insurance-industry) - [Underwriting](#underwriting) - [Process and Business Analytics](#process-and-business-analytics) - [Policy Admin and Servicing](#policy-admin-and-servicing) - [Sales and Distribution](#sales-and-distribution) - [Finance and Accounts](#finance-and-accounts) - [Integration with Legacy Applications](#integration-with-legacy-applications) - [RPA Success Stories](#rpa-success-stories) - [Benefits Of RPA In The Insurance Sector](#benefits-of-rpa-in-the-insurance-sector) - [Conclusion](#conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) It has been established that the workforce in the insurance industry is, to a great extent, burdened with mundane and repetitive tasks. Most of the time, the skills and time of this workforce are hardly invested in more productive and efficient capacities. Daily undertakings such as claims processing, personal and insurance onboarding, and policyholder services are some of the many important but repetitive tasks influencing the insurance industry. These tasks have had an overall influence on the industry’s efficiency affecting business conversion, profitability, and customer satisfaction. However, the solution to solving these repetitive tasks handled by the human workforce is the introduction of Robotic Process Automation (RPA) in the insurance sector. RPA can help perform repetitive tasks more efficiently, accurately, and tirelessly than humans. This results in the human workforce having enough time to focus on tasks that need human interventions, such as emotional intelligence, reasoning, and judgment. The RPA can assist insurers in the insurance space to build a high-growth responsive business at a cost-effective rate. Thus, more value is created in the insurance industry. Discover more RPA opportunities for other industries, e.g., [automation in e-commerce](https://www.flobotics.io/business-process-automation). ## What is Robotic Process Automation (RPA) [Robotic process automation](https://www.flobotics.io/blog/robotic-process-automation) (RPA) is a software algorithm program set up to design, deploy, and oversee software robots or bots that can mimic, learn and perform rules-based business functions. ### The use of RPA to solve various challenges in the insurance sector Insurance companies all over the world, irrespective of their size, face various challenges in the course of managing their businesses. However, insurance companies heavily dependent on back-office operations mostly suffer the impact of these challenges. Challenges faced by these insurance companies include; Fig. 01 · Insurance 3 challenges The challenges insurance companies face - 01Slow, expensive manual data entry - 02Changing regulations that add operating costs - 03Hard to fit new BPM and ERP tools into existing systems - Manual data entry processes are time-consuming and expensive. Manual processes are also liable to human errors leading to a major record discrepancy. - The need to constantly realign with ever-changing regulations which are usually difficult. Non-compliance often leads to severe operational and financial outcomes. - Difficult in incorporating systems with existing ones when implementing new BPM and ERP solutions. Even with complete integration, the legal system available to insurance companies can no longer support growth. ## How RPA Solves Problems In The Insurance Sector Robotic process automation (RPA) in the insurance sector can be of help in so many areas, and these include; ### Simplifying Claims Processing The processing of claims is vital to the profitability of insurance companies. But, many of these insurance providers manually process insurance claims which are usually time-consuming and error-prone. However, by integrating RPA into the insurance sector, [claims and document processing](https://www.flobotics.io/case-studies) are accurate and efficient, eliminating human errors to the barest minimum. ### Scalability Integrating RPA in the insurance sector makes scalability simple, as it is feasible to decrease or increase the number of active RPA robots. Depending on the workload of an insurance firm, RPA robots can be scaled up or down. This scaling, whether temporal or permanent, is essential to meet insurance companies’ long-term goals and objectives, fostering growth in the process. ### Non-intrusive Compatibility A lot of insurance companies still depend on disparate applications or legacy systems. But with the non-intrusive disposition of the RPA, business operations can be streamlined. RPA is known to emulate human mouse clicks and keystrokes, communicating with the exhibition layer of computer applications and programs. To this end, RPA can be implemented to synchronize with existing programs without requiring insurance companies to replace the present IT setup. This implementation also can be done with little or no support from the IT department since no programming knowledge is needed to carry out the task. ### Legislation Compliant Compliance with standard regulations is vital to the success of insurance providers. RPA ensures that all data logins are valid and precise while maintaining running logs of all activities. Hence, insurance providers can monitor their compliance with various regulations based on their internal reviews. RPA allows insurance providers to get prepaid for internal and external audits in the face of ever-changing regulatory compliance. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## RPA Use-cases In The Insurance Industry There are several real-life [use cases of RPA in the insurance sector](https://www.flobotics.io/blog/rpa-use-cases-across-industries). RPA can computerize end-to-end processes by incorporating new front-end technologies with back-office settings, making it a perfect fit in the insurance industry. Let’s look at RPA in insurance, use cases, and implementation. ### Underwriting Underwriting entails assessing clients’ exposures and risks; it involves gathering information from several sources and evaluating the risks that come with the policy. Data analysis, scrambling, and assessing the risk involved before concluding takes 2-3 weeks. [Robotic Process Automation (RPA)](https://www.chetu.com/blogs/insurance/rpa-in-insurance-what-are-the-benefits-of-using-robotics-process-automation-in-the-insurance-sector.php) computerizes the entire data collection process from internal and external sources. Hence, significantly reducing the time consumed for underwriting. RPA also increases multiple fields in the internal systems using applicable data to give reports or recommendations. This is usually the basis for the pricing of products and underwriting. ### Process and Business Analytics Insurance providers can only satisfy and improve customer services if they can measure their overall operations. The huge amount of paperwork and operational processes makes it nearly impossible to measure and trail operational efficiency or point out areas that need improvement. With computerization processes being established, the tasks carried out by RPA can be monitored easily with little or no manual effort. Also, exceptions met during several transaction processes can be easily measured using RPA. The audit pathway constructed by RPA assists with regulatory compliance, leading to enhanced processes. To this end, customer service response time and claims processing are improved, seeing many clients benefit from the streamlined processes. ### Policy Admin and Servicing Policy administration connects an insurance provider’s processes, from quoting, underwriting, and rating to distributing customer services. However, the present policy administration in the insurance sector is archaic, expensive, and of high maintenance. As such, the policy admin cannot scale fast enough to cater to the demands of clients and support growth. This RPA in the insurance use case enables all vital players in every process to achieve an abundance of processes effortlessly without having to involve huge navigation across the systems. It automates administrative and transactional functions such as settlements, accounting, risk capture, tax, regulatory compliance, and credit control. With RPA in charge of repetitive and mundane tasks, back-office personnel can then focus more on front-office functions where they can attend to complex human demands and facilitate all-around growth. ### Sales and Distribution Another RPA in insurance use cases is the ease it brings to the daunting and challenging sales and distribution tasks. Robotic Process Automation (RPA) helps to create sales scorecards to help push notifications to insurance agents and help supervise compliance. ### Finance and Accounts Robotic Process Automation (RPA) is built to carry out keystrokes, clicks, copy-pasting information, temple auto-fill, field entries, pressing buttons, and lots more. As a result, a larger percentage of daily bank reconciliations are automated, and transactional expenses are reduced, including policy-cost footprint. ### Integration with Legacy Applications An important RPA in insurance use cases is its integration with legacy applications. Many insurance companies will make use of legacy applications for their business operations. Implementing and handling BPM and ERP systems are quite difficult and need integration with these Legacy applications. RPA can fit perfectly into the prevailing workflow of insurance providers, adapting to any system made available for use. ## RPA Success Stories Many insurance companies have had quite a success story by implementing RPA in their system. A global insurance company reduced the reporting process from 180 minutes to 3 seconds after implementing RPA. Another international consultancy firm was also able to save 54,000 hours of work yearly while also getting an 85% improvement in accuracy with RPA. Capgemini also reported an increase in productivity of 50% on average in business units where insurance providers implement RPA. Furthermore, companies in highly regulated sectors such as insurance and banking are learning that automation is an inexpensive and rapid way of employing superior skills to address the problems of compliance documentation and checks. However, designing and developing a good robotics implementation requires a deep level of technicality. While it is true that anyone can learn to code robots, not everyone will be good at it. Read [why your non-technical RPA developer sucks](https://www.flobotics.io/blog/rpa-non-technical-developer) to prevent the failure of your project. ## Benefits Of RPA In The Insurance Sector Integrating RPA in the insurance sector comes with a lot of [benefits](https://marutitech.com/benefits-of-rpa-in-business/). Some of the benefits include; Fig. 02 · Insurance 6 benefits The benefits of RPA for insurers RPA - 01Faster claims processing - 02Fewer human errors - 03Easier to scale - 04New data synced with existing systems - 05Legal compliance - 06Happier customers - Consistency of Process Insurance providers get to enjoy the advantages of consistency of process with RPA. RPA entertains repetitive processes governed by rules and accuracy that even bright minds cannot possibly maintain. - Increased data accuracy Making use of RPA increases data validity. This is because, unlike humans, robots are less likely to input wrong data into records. - Standardized processes Integrating RPA requires insurance companies to make use of standardized processes. Through standardization, companies increase staff efficiency while increasing the accuracy and speed at which robots carry out tasks. ## Conclusion Many organizations now look to embrace RPA within their system. However, the overall efficiency depends on a thoughtful implementation of RPA. It is best that at the first trial, RPA should be implemented for a set of operations that require little to no human judgment. After a successful implementation, RPA can have more [use cases](https://www.flobotics.io/case-studies) within the organization. [Flobotics](https://www.flobotics.io/) offers RPA implementation services distinct to your firm’s goals and use cases. We use RPA as an extensive tactical tool to assist you in getting more out of your business. We carefully assess the practicality of a proposal for a business unit and then develop a scalable strategy to implement the solution across your business smoothly. We are ready to walk the extra mile with you. Find out what we can be achieved for your business by implementing RPA in insurance processes. #### Like the article? Spread the word Written byYana Pokora Content Manager at Flobotics. [More from Yana](https://www.flobotics.io/our-editorial-team#pokora) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ EligibilityClaims ### Insurance Claims Processing Automation With RPA: Reasons for Implementation and Use Cases Insurance claims processing automation: how RPA speeds up claims handling, with reasons to implement it and real case studies. Michał RejmanJuly 21, 2021 ](https://www.flobotics.io/blog/insurance-claims-processing-rpa-automation-use-cases)[ RPA ### Automation’s for Everyone: 100 Real-World RPA Use Cases Across Industries | 2026 RPA use cases across industries: see 100 real-world examples of process automation in action, from healthcare to manufacturing. Michał RejmanFebruary 23, 2024 ](https://www.flobotics.io/blog/rpa-use-cases-across-industries)[ RPA ### RPA Reloaded: 50+ Robotic Process Automation Statistics to Know in 2026 RPA statistics 2026: 50+ data points on robotic process automation adoption, ROI, and where the technology is headed next. Yana PokoraApril 15, 2025 ](https://www.flobotics.io/blog/rpa-statistics) [All articles →](https://www.flobotics.io/blog) --- # How to Improve Electronic Health Records Processing with Automation Canonical: https://www.flobotics.io/blog/electronic-health-records-rpa Author: Bart Teodorczuk Published: 2021-08-09 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/How to Improve Electronic Health Records Processing with… [Healthcare](https://www.flobotics.io/blog?category=healthcare)[RCM](https://www.flobotics.io/blog?category=rcm) # How to Improve Electronic Health Records Processing with Automation [Bart TeodorczukHead of AI at Flobotics](https://www.flobotics.io/our-editorial-team#teodorczuk) Published August 09, 2021Updated September 1, 2026 On this page - [What is EHR (Electronic Health Records) Processing?](#what-is-ehr-electronic-health-records-processing) - [How Can Electronic Health Records Be Improved?](#how-can-electronic-health-records-be-improved) - [What Processes in EHR Can Be Automated with RPA](#what-processes-in-ehr-can-be-automated-with-rpa) - [Patient And Appointment Registration](#patient-and-appointment-registration) - [Report Management](#report-management) - [Regulatory Compliance](#regulatory-compliance) - [Pros of Using RPA for EHR](#pros-of-using-rpa-for-ehr) - [Assisting Pre-authorizations](#assisting-pre-authorizations) - [Improving Patient Communication Opportunities](#improving-patient-communication-opportunities) - [Reducing Manual Data Entry](#reducing-manual-data-entry) - [Reduction in Cost](#reduction-in-cost) - [Increasing Efficiency by Utilizing Third-party Tools](#increasing-efficiency-by-utilizing-third-party-tools) - [Cons of Using RPA for EHR](#cons-of-using-rpa-for-ehr) - [Added Complexity](#added-complexity) - [Maintenance](#maintenance) - [Use-cases of Automating EHR Processing with RPA](#use-cases-of-automating-ehr-processing-with-rpa) - [Automating Revenue Cycle Management](#automating-revenue-cycle-management) - [Scheduling Optimization](#scheduling-optimization) - [Effective Management of Human Resources](#effective-management-of-human-resources) - [Conclusion](#conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) The Healthcare sector is one of the economy’s most regulated and demanding industries. As a result, healthcare professionals continuously face increasing administrative work, which seems to have driven down operational efficiency and patient care services. Given the ever-increasing health crisis and predicaments, the healthcare sector is evolving to meet these health crises while finding answers to the pile of administrative work. To this end, Robotic Process Automation is being used to better the Electronic Health Records (EHR) system. ## What is EHR (Electronic Health Records) Processing? Electronic Health Records (EHRs) are real-time, electronic, patient-centered records maintained by the patient’s provider over time and made available to anyone authorized to see them. These electronic health records (EHRs) include a broad spectrum of medical information, such as the patients - Medical histories - Medications - Diagnoses - Treatment plans - Laboratory test results - Allergies - Immunization dates - Radiology images [Electronic Health Records (EHRs)](https://www.healthit.gov/faq/what-electronic-health-record-ehr) allow for intelligent, evidence-based tools to assist healthcare professionals in making better, informed judgments and conclusions on the best way to treat patients. When employed adequately, EHRs help automate clinician workflows, significantly improving patient care quality. However, [integrating Electronic Health Record](https://www.flobotics.io/rcm-automation) systems in vast, integrated healthcare delivery networks has not panned out exactly as envisioned. Today, EHRs are considered monolithic, difficult to use, costly to configure, and inflexible. This is usually a result of many of the popular EHRs systems being built on older technologies which often reflect on their ease of use. Many healthcare professionals, including surgeons, find these older technologies difficult to use and complex, making the EHR system perform way below expectations in delivering their preferred healthcare processes. ## How Can Electronic Health Records Be Improved? Rather than changing an entire EHRs root and system, the imperfections can be corrected using [Robotic Process Automation (RPA).](https://www.flobotics.io/blog/robotic-process-automation) RPA primarily allows digital labor to keep what works while fixing underlying issues. Robotic process automation, or RPA, uses software algorithms and scripts to securely and efficiently automate the tasks the [human resources](https://www.flobotics.io/blog/rpa-in-hr-and-recruitment) in an organization would otherwise perform. RPA often means uncovering error-prone and repetitive tasks by human resources and integrating robots to accomplish such tasks. The benefits? RPA offers many benefits across different sectors and, most importantly, in the healthcare sector, which will be discussed as we move forward. ## What Processes in EHR Can Be Automated with RPA ### Patient And Appointment Registration Robotic process automation (RPA) can effectively automate all [patient data](https://healthtechmagazine.net/article/2019/10/what-happens-stolen-healthcare-data-perfcon) entry, transfer of registered information to patient records, and add relevant appointments to the EHR’s schedule. As mentioned, RPA uses bots to perform all the clicking, copying, pasting, and pointing, saving precious hours and human efforts and allowing staff and healthcare professionals to focus more on higher-value operations. ### Report Management Robotic process automation (RPA) can also assist healthcare professionals in running reports of billing payments and submissions through automation. By compiling these reports, healthcare staff can access charges based on individual providers, insurance carriers, and individualized patients. Asides from running reports, RPA also helped to oversee payments and bills earned every calendar month and analyzed to determine the industry’s trajectory. ### Regulatory Compliance With Robotic Process Automation (RPA), all regulatory processes in a healthcare company are automatically tracked, traced, recorded, and categorized in a structured pattern. This helps healthcare companies always be prepared for impromptu and external audits whenever requested. Here is a preview of automating patients’ profiles and appointments creation in DrChrono EHR with RPA (the data input is a simple Google Spreadsheet with raw data): Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Pros of Using RPA for EHR There are lots of advantages that come with using RPA for EHR. Some of the many benefits RPA offers include the following; ### Assisting Pre-authorizations RPA collects data and information from disparate systems and websites and incorporates them directly into the EHR. In some situations, RPA also helps to submit necessary data for pre-authorization. ### Improving Patient Communication Opportunities RPA helps to improve communication with patients by automatically generating emails that recap all information discussed on the phone with a healthcare professional. ### Reducing Manual Data Entry Through the integration of RPA bots, all information is cataloged across multiple systems, automatically aggregated, and entered into a central patient recording system where healthcare staff can easily access it. ### Reduction in Cost One of the biggest advantages of RPA is reduced cost. For repetitive, rule-based work, such as copying patient data from one system to another, a bot costs less than having people do the same work by hand. It can run at any hour without getting tired or making typing mistakes, and your staff can spend their time on work that needs a person. ### Increasing Efficiency by Utilizing Third-party Tools RPA efficiently operates as a middleman between third-party tools that don’t communicate with each other. This enables the processing and sharing of data between various devices without human intervention. Fig. 01 · RPA in EHR Pros and cons Pros and cons of RPA in the EHR Pros - Helps with prior authorizations - Better patient communication - Less manual data entry - Lower long-term cost - More efficient use of third-party tools Cons - Added complexity - Needs maintenance - High initial investment Learn more about the [processes in the healthcare industry you didn’t know can be automated](https://www.flobotics.io/blog/healthcare-workflow-automation) and what the benefits are. ## Cons of Using RPA for EHR As alluring as these RPA benefits are, this technology has some drawbacks. Some of the Cons include the following; ### Added Complexity Even though RPA is praised for simplifying workload, it can also create complexity in the operation. When the RPA software is not effectively managed and governed, it can create several software layers, complicating healthcare administrative work and making business improvement difficult. ### Maintenance Even though RPA is praised, Generally, RPAs are customized to fit a business model and solve corresponding problems. However, maintenance is usually the problem, especially for ever-changing tasks. A minor change in RPA setup can significantly disrupt RPA robots making maintenance difficult. Hence, integration of [RPA is best for long-term business models](https://www.flobotics.io/blog/what-processes-to-automate). ## Use-cases of Automating EHR Processing with RPA The possibilities for automating EHR processing and integrating robotic process automation in the healthcare industry are endless. Even though the potential and [use cases of RPA](https://www.flobotics.io/blog/rpa-use-cases-across-industries) have not been fully explored, it has various use cases in the healthcare industry ranging from clinical documentation to data transfer. When integrated perfectly, RPA can automate query tasks of Electronic Health Record data, payment personnel letters, accounting and financial systems, and partner ecosystems. Hence, reducing the workload on healthcare professionals. Some of the use cases of RPA in the health sector are; ### Automating Revenue Cycle Management The [revenue cycle](https://www.flobotics.io/rcm-automation) is a complicated system in the healthcare industry. For this cycle to run smoothly, many things must be correctly implemented for claims to be authorized. If not, chances for claim denial increase as a single error can sever the cycle of a successful claim. However, with the integration of RPA, the revenue cycle is effectively automated, and the littlest error is corrected, particularly around; - Intake - Prior Authorization - Bill Scrubbing - RPA for Medical Billing and Invoicing - Claims Status - Collections - Payment Posting ### Scheduling Optimization Optimizing Schedules is one of the popular struggles among healthcare companies, especially when considering many factors. This often results in employee frustration, poor customer service, revenue leakage, and lots more. The factors schedulers need to consider usually include the following: - The client’s preferences and schedules - Location and availability of providers, - Billing capacity and prior authorization - State employment law compliance - Finger regulations And lots more, causing a lot of trouble for schedulers. However, these struggles and tasks are where RPA flourishes the most – carrying out and performing repetitive duties. By integrating RPA, schedules are efficiently optimized, error-prone, and faster while avoiding revenue leakage and, most importantly, sparing medical staff from the tedious work. ### Effective Management of Human Resources Funny enough, it requires a lot of robotic responsibilities to manage and organize [human resources](https://www.helpsystems.com/blog/six-reasons-automate-hr-document-management). With human resources, several operations such as credentialing, scheduling, offboarding, onboarding, and so on involve manual data entry between multiple systems. And these overwhelming audits via human efforts are known to be filled with costly errors and mistakes. You can avoid them and speed up your processes by implementing RPA solutions. ## Conclusion The benefits of EHR automation and the integration of RPA within the healthcare sector cannot be overemphasized. By integrating RPA within healthcare companies, time, human resources, and money are saved in the long run. Above all, and most importantly, patient care is improved. At [Flobotics](https://www.flobotics.io/contact), when it comes to automating Electronic Health Records and medical billing, we are [HIPAA compliant](https://www.flobotics.io/rcm-automation) and pride ourselves on our ability to implement successful RPA solutions in the medical industry. #### Like the article? Spread the word Written byBart Teodorczuk Head of AI at Flobotics. [More from Bart](https://www.flobotics.io/our-editorial-team#teodorczuk) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### How Is Robotic Process Automation Changing HR and Recruitment? RPA in HR and recruitment: how automation takes over routine tasks so HR managers can focus on strategic, people-first work. Michał RejmanJanuary 20, 2021 ](https://www.flobotics.io/blog/rpa-in-hr-and-recruitment)[ RPA ### RPA Reloaded: 50+ Robotic Process Automation Statistics to Know in 2026 RPA statistics 2026: 50+ data points on robotic process automation adoption, ROI, and where the technology is headed next. Yana PokoraApril 15, 2025 ](https://www.flobotics.io/blog/rpa-statistics) [All articles →](https://www.flobotics.io/blog) --- # Insurance Claims Processing Automation With RPA: Reasons for Implementation and Use Cases Canonical: https://www.flobotics.io/blog/insurance-claims-processing-rpa-automation-use-cases Author: Michał Rejman Published: 2021-07-21 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Insurance Claims Processing Automation With RPA: Reasons… [Claims](https://www.flobotics.io/blog?category=claims)[Eligibility](https://www.flobotics.io/blog?category=eligibility) # Insurance Claims Processing Automation With RPA: Reasons for Implementation and Use Cases [Michał RejmanChief Marketing Officer at Flobotics](https://www.flobotics.io/our-editorial-team#rejman) Published July 21, 2021Updated September 1, 2026 On this page - [Robotic Process Automation in Insurance](#robotic-process-automation-in-insurance) - [Reasons for Implementing RPA in the Insurance Industry](#reasons-for-implementing-rpa-in-the-insurance-industry) - [Top 10 benefits of using RPA in the insurance industry](#top-10-benefits-of-using-rpa-in-the-insurance-industry) - [2 – Speed ​​up claims processing](#2-speed-up-claims-processing) - [3 – Higher quality and accuracy](#3-higher-quality-and-accuracy) - [4 – Higher compliance](#4-higher-compliance) - [5 – Scalability](#5-scalability) - [6 – Reduced data entry](#6-reduced-data-entry) - [7 – Completeness of the application](#7-completeness-of-the-application) - [8 – Eliminates the need for storage](#8-eliminates-the-need-for-storage) - [9 – Audit log](#9-audit-log) - [10 – Visibility to the client](#10-visibility-to-the-client) - [Bonus benefit – Identifying fraudulent claims](#bonus-benefit-identifying-fraudulent-claims) - [Real-life use cases from the market](#real-life-use-cases-from-the-market) - [Use Case 1: Prudential Financial](#use-case-1-prudential-financial) - [Use Case 2: Safe-Guard](#use-case-2-safe-guard) - [Use Case 3: Farmers Insurance Group](#use-case-3-farmers-insurance-group) - [Use Case 4: New York Life](#use-case-4-new-york-life) - [Use Case 5: Zurich Insurance](#use-case-5-zurich-insurance) - [Use Case 6: Aegon Life Insurance](#use-case-6-aegon-life-insurance) - [Conclusion](#conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) The insurance industry is notoriously bad at serving customers. But not in China. In the past few years, Chinese tech giants have made tremendous strides to become insurance innovation hubs. Take a look at just one example: WeSure, an insurance platform powered by the WeChat messaging app, celebrated its second anniversary with over [55 million users](https://www.prnewswire.com/news-releases/tencents-insurance-platform-wesure-celebrates-its-2nd-anniversary-55-million-users-within-wechat-ecosystem-300973842.html). This means that the biggest challenge for Chinese insurers today is not just to digitize businesses but to go beyond traditional offerings and even combine insurance with other financial services. To compete, insurance companies are revolutionizing the industry using Robotic Process Automation. The Customer Satisfaction Score (CSAT) and Net Promoter Score (NPS) are the most important metrics for any insurance company. However, they lag far behind in the US as insurers fall short of expectations due to growth in other industries. Since the grievance process greatly impacts[ customer satisfaction](https://www.ttec.com/articles/what-drives-customer-satisfaction-during-insurance-claims-process), let’s look at how RPA insurance bots can revolutionize costs, operations, and customer experience. ## Robotic Process Automation in Insurance [Robotics Process Automation, or RPA](https://www.flobotics.io/blog/robotic-process-automation) – using desktop-level front-end software bots that do not require programming to handle routine processes at the keystroke level – is revolutionizing insurance. From underwriting and onboarding personal and commercial insurance companies to serving insurers and [handling claims](https://www.flobotics.io/agents/claims-management-automation), RPA is already revolutionizing how insurers work, improving customer service and reducing [cycle](https://www.flobotics.io/rcm-automation) times while cutting overhead costs. Are you faced with reducing and minimizing the time for processing insurance documents? Find out how to accelerate these efforts here: [How To Process Over Half a Million Insurance Documents In 8 Weeks](https://www.flobotics.io/case-studies). RPA is also the fastest-growing technology in the field to date, with [current trends](https://www.grandviewresearch.com/industry-analysis/robotic-process-automation-rpa-market) showing that the RPA market, valued at $ 199.1 million in 2016, will grow at a compound annual growth rate (CAGR) of 60.5% through 2024. As per P&S Market Research, the global Robotic Process Automation market will reach unimaginable heights. Simultaneously, it is predicted that the demand for software robots in the field of intellectual work will continue to grow. RPA affects all industries: new jobs will be created as large-scale RPA software is introduced. Companies will need to find the right balance between robotics and up-skilling existing employees. Nevertheless, what about the insurance industry in particular? In insurance, RPA is defined as the implementation of software robots that can be configured for each computer without the need for code. These software robots help their real-life technicians perform monotonous and repetitive insurance routines such as data entry. In insurance operations, RPA effectively engages a workforce with artificial intelligence (AI), that is, robotic assistants who can execute basic computer commands of employees, performing various low-value-added tasks that currently consume these employees’ efforts, energy, and moral spirit. Insurance robots work similarly to Excel macros. But unlike Excel macros (which only work in Excel), RPA insurance bots can run on multiple systems rather than being limited to one. Thus, these robots can work at the level of individual data fields in all insurance systems. RPA platforms like UiPath, and Blue Prism can handle actions down to the mouse and keyboard levels. Once set up properly (more on that in a minute), they can do everything from opening apps to tapping, copying, and pasting information from one app to another, sending emails, and more. For established insurance companies, operations have traditionally (and largely) relied on outdated legacy systems (with complex moving parts) that do not interact well with each other. This has led to the need for highly paid IT professionals to bridge these disparate systems effectively – which amounts to grueling days spent decrypting and arranging data: - opening emails, - copying and pasting data between legacy systems, - creating PDF files, - etc. Thus, the Tower of Babel problem — the inability of legacy systems to “talk to each other” without manual human intervention at the keystroke level — created an insurmountable obstacle to optimizing existing technologies without a wholesale (and costly) rethinking of the company’s entire IT infrastructure. So it never happened. The bar is lower for new insurance companies. They face fewer difficulties given their ability to use primarily cloud infrastructure from the get-go. Compare their situation to that of well-established insurance companies, and you will see that it is costly to invent basic systems that usually fall short of the automation promises. This is why insurance companies – perhaps especially the big ones – are so excited about RPA. Finally, it allows them to use robotics in the insurance industry to “bridge the last mile” of their legacy insurance systems in ways that improve customer service and back-office efficiency. Unsurprisingly, RPA is changing the way insurance companies do business. As you probably know, insurance operations require complex processes and system connections to run a business, including underwriting, claims management, and risk analysis. Nonetheless, insurance companies using RPA can make these processes more efficient – sometimes a staggering 50 percent – by reducing the cumbersome and time-consuming data entry and transcription tasks in legacy systems. ## Reasons for Implementing RPA in the Insurance Industry Insurance companies face many challenges: - Customer expectations for lead times and multi-channel access continue to rise - Intensive operations such as claim processing continue to hinder profitability. - Complaints handling includes several management, administrative and customer service functions that manually perform resource-intensive tasks to protect the company from fraud or error. Despite all this, in the US alone, the insurance industry loses $ 80 billion annually due to fraud ([Coalition Against Insurance Fraud](https://insurancefraud.org/fraud-stats/)). It’s no surprise that RPA claims processing is emerging as a new trend in the insurance industry. Because the company’s service standards and customer commitment are at stake, there is little room for error, and the cost of accurate claims handling should not be underestimated. This is why more and more companies are turning to robotic process automation (RPA) to solve these problems. Fig. 01 · Insurance Why RPA fits Why insurance is a good fit for RPA Why insurance suits RPA - 01Lots of manual data handlingClaims rely on manual entry, so work is slow and error-prone - 02Legacy systemsOld and new systems are not connected, so data is handled poorly - 03Regulation and complianceRules change often and differ between states and countries - 04Many different formatsImages, emails and documents make data hard to own and track - 05Constant data extractionData has to be pulled from many programs and systems Some of the challenges associated with handling claims efficiently and error-free include: - Manual data entry: Traditional claims processing relies heavily on manual data entry, making the process inconsistent and error-prone. - Incomparable means: Disparate mediums by which information is processed and collected (e.g., images, emails, documents) create a shortage of accountability and ownership. - Legacy systems: Lack of integration of these systems with new solutions reduces performance. - Data Extraction: Data extraction is a huge challenge when multiple programs, processes, systems, and applications are used. - Regulation and Compliance: Changes in laws and regulations can seriously affect claims handling, posing a major challenge for companies to stay compliant when operating in different states and countries. These challenges impede insurance companies’ efforts to improve operational efficiency, reduce costs and improve customer service. The decision to automate insurance duties can help here. Claims handling with RPA ensures error-free tasks, simplifies data entry, and streamlines processes, resulting in lower operating costs, faster processing times, and greater compliance. The productive impact of insurance claims processing automation is manifested in many aspects. We present and briefly discuss 10 of the most important ones. ## Top 10 benefits of using RPA in the insurance industry Fig. 02 · Insurance 10 benefits Benefits of RPA in insurance - Optimizes the whole process - Faster claims processing - Higher quality and accuracy - Better compliance - Easy to scale - Less data entry time - Documents circulate faster - Less paper in circulation - Easier document and data audits - Happier customers 1 – Optimization of the whole process RPA helps insurers simplify claims processing by streamlining multiple processes, including entering data into the system from various channels such as email, telephone, or online forms, checking coverage, and issuing settlement notices. A claims proofreader bot like the IQ Bot can eliminate the tedious manual processes of reviewing policy claims and checking for fraud. A bot can speed up processes – from organizing data, retrieving to transferring – without human intervention. ### 2 – Speed ​​up claims processing Following the previous point, an automated bot allows employees to focus better on interacting with customers than dragging and dropping documents from one department to another. This improves efficiency by structuring the vast amounts of claims data flowing through the department and increasing customer satisfaction by speeding up the claims handling process. This frees the claims processor from manual validation and data execution to focus on other steps that require human intervention to make decisions. Read more about how we can help you with [claims processing automation](https://www.flobotics.io/agents/claims-management-automation) and the benefits. ### 3 – Higher quality and accuracy RPA not only reduces the backlog but also reduces the inevitable human error. For example, property and accident insurers need to assess damage estimates accurately. But since this information comes from various paper or PDF forms, it cannot be easy to maintain perfect accuracy whenever done manually. Having a bot to manage repetitive tasks such as data entry, validation, and cross-validation of coverage requirements can lead to a fast, efficient, and accurate claims process. In case of inaccuracies or deviations, the bot may require human intervention for further investigation. ### 4 – Higher compliance Insurance companies are strictly regulated and must comply with laws set by various local and global regulatory bodies. Enforce these rules more closely by letting the bot document each step of the claim processing. This will dramatically improve insurance compliance and governance as companies can track and validate records continuously without depressing about errors or missing data. ### 5 – Scalability One of the biggest pros of RPA is the creation of a virtual digital workforce that can be easily scaled up or down based on seasonality. With increased workload during peak periods, RPA can be a lifesaver for those handling claims. These bots ensure that work continues without delays and policyholders are not hurt by the spike in claims processing while still being 100% accurate. ### 6 – Reduced data entry Clients are required to complete numerous forms as part of the claims handling process. The information obtained from these forms must be entered into a centralized system. Processing is not possible if this information is not available in electronic format. Before automation was widely adopted in the claims industry, entering this data into the system was manual, time-consuming, and costly. However, modern technology has allowed software to directly read information from forms and enter it into the system. Consequently, converting data from paper forms to electronic records can be done with minimal manual intervention. Since data handling is one of the biggest costs incurred by any insurance company, reducing the volume of data entry goes a long way toward saving costs. ### 7 – Completeness of the application The lack of complete data is a serious obstacle to the fast processing of insurance claims. The reality is that different types of documents must be provided to obtain insurance. The list of these documents varies from case to case. Therefore, creating a simple checklist that can be verified is impossible. Because the requirements are complex, most insurance consumers miss the opportunity to provide certain information from the outset. Consequently, their application is sent back, and they are asked to provide additional documents. The process is usually repeated several times before the claim is processed. The repetitive nature of this process is a problem for insurance companies and consumers. This is because consumers must wait longer before receiving their money. From the insurer’s perspective, the continuous back-and-forth movement means that the efficiency of the back office, as well as the front office staff, decreases, leading to increased costs. ### 8 – Eliminates the need for storage As mentioned above, the claims handling process requires a lot of paperwork. Insurance companies must keep these documents for future reference. This becomes a problem because it is tough to maintain a physical archive. With the growth of automation in the claims processing industry, physical archives are outdated. Now they are being replaced by electronic archives. Electronic archives are easier to maintain. This is because the archiving process, as well as the receipt of documents, can be automated. This means that significantly fewer people and money must be spent on maintaining the archive. In addition, since the electronic archive does not take up much space in the real world, real estate costs are also saved. ### 9 – Audit log The best thing about automating the complaints-handling process is that auditing becomes extremely simple. Suppose any insurance company manager has access to a specific file of the claim or performed any action related to the claim. In that case, this information is automatically recorded by the system. This way, the software creates a footprint that can be easily verified during an audit. This feature is essential for insurance companies that have lost funds in the past due to the connivance of their service personnel by outsiders. ### 10 – Visibility to the client The entire claims handling process is a black box from a consumer perspective. This means the consumer does not know what is happening with their application until he receives the money. This creates a sense of ambiguity and uncertainty. Consumers do not mind waiting a little longer while they know what is happening with their requirements. New and modern software for the automated processing of claims allows the timely provision of this information to customers. Clients are often presented with a flowchart explaining the different stages that their claim must go through. The dashboard provides customers with real-time updates when they log in. Thus, automated claims handling software not only lowers costs but also improves customer service. ### Bonus benefit – Identifying fraudulent claims Automated claims processing software can also detect patterns in data. Hence, whenever auditors discover a fraudulent claim, they must flag it in the system. Over time, the program developed its database of fraudulent claims. The system can then perform analytic operations on that data to uncover patterns typical of these fraudulent claims. The software can then use this information to flag new claims that follow the same way and, therefore, may be fraudulent. Most claims processing programs can learn continuously as more and more data points are attached to their database over an extended period. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Real-life use cases from the market The insurance industry’s robotic automation use case is defined as documenting a list of insurance transactions/steps performed at the employee level. These actions and measures, performed on computers or other electronic devices, are then used to automate the movement of information in insurance applications. IT consultants or your staff uses the insurance RPA use cases as drafts to implement automated scenarios that run across multiple systems to process data. To help you learn, appreciate, and draw inspiration from how the insurance industry is deploying RPA, here are six examples of how insurance companies are adopting the technology in the United States, Europe, and Asia. Also, see [40 Real World Use Cases of Robotic Process Automation Across Industries](https://www.flobotics.io/blog/rpa-use-cases-across-industries). ### Use Case 1: Prudential Financial Goal: Achieve precision, efficiency, and cost control Company info: - The company is headquartered in Newark, New Jersey. - In business for almost 145 years - Services to institutional and individual clients from over 40 countries - The 2017 [annual report](http://www3.prudential.com/annualreport/report2018/annual/HTML1/prudential-ar2017_0008.htm) shows the total revenue is $ 53.6 billion. Prudential’s VP of Robotics Process Automation, Anne Delmedico, leads the Robotics Process Automation Center of Excellence. In September 2017, she presented how her company deployed a global RPA solution. RPA was part of a larger, corporate-wide “transformation program” to drive strategic growth, improve customer service, and manage costs. Prudential picked Blue Prism as its RPA software solution. Delmedico highlighted in her keynote that the company approached its decision to implement RPA with a value proposition rather than industry trends. The insurer intended to reach three main goals: - accuracy, - efficiency, - cost management. The first application of RPA at Prudential was to help handle payment discrepancies. Potential solutions were identified using automation to determine if there were two policies for the same person, look for the inversion of the policy number, and check if the policy was loaned. The company will contact the bank if no positive matches can be found in these categories. Result: The infrastructure to start the process was created in July 2016; the first implementation was rolled out in October – just three months later! By the end of 2016, Delmedico notified that ten automation processes were in production, resulting in savings of $ 500,000. ### Use Case 2: Safe-Guard Goal: Faster document processing, higher customer satisfaction scores Company info: - Based in Atlanta, Georgia. - In business for 25 years - Handles nearly four million contracts a year - Serves over 11 million consumers [Safe-Guard](http://www.safe-guardproducts.com/) offers products and solutions for the automotive industry and partners with Ford, Harley-Davidson, and BMW. Irvine, California-based Kofax, a global RPA software provider, has published a case study describing how it helped Safe-Guard move from paper-intensive claims processing to a more efficient and automated process. According to Tim Dewey, former Safe-Guard VP of Operations Technology: “We sell many financial and insurance products through car dealerships, which typically rely on pen and paper. Claims processing was an equally time-consuming process. In each of these areas, we need to collect significant documentation from external stakeholders and clients. Our administration teams have spent much time and effort scanning and processing paper documents and viewing and sorting email attachments into folders.” Using the Kofax suite of products, the company has implemented several automated solutions. One of the first steps was to automate the process of drawing up a contract and filing claims. Paper documents are primarily scanned and uploaded to a centralized portal. After that, documents can be received by mail, email, or fax. They are identified by document type and then sent to the work queue for further processing. An automated document extraction process then extracts the categories of information that Safe-Guard deems relevant and stores it in the system. Each step is monitored and analyzed to identify high-performance points and opportunities for improvement. Result: As a consequence, Kofax reports that document processing time has been reduced from two hours to 10-15 minutes. Processing of documents has been reduced from five times to one, that is, by about 80 percent. Overall productivity increased by 30 percent, resulting in a 15 percent increase in customer satisfaction. ### Use Case 3: Farmers Insurance Group Goal: Increased satisfaction of both agents and customers Company info: - In business for over nine decades - Serves over 10 million households - Processes over 19 million individual policies - It covers all 50 states Farmers Insurance, based in Woodland Hills, California, prepares policies for vehicles, homes, and small businesses. Besides, it offers a wide range of other insurance and financial services. Evidence of farmers’ RPA efforts can be seen in a [case study published by Pegasystems](https://www.pega.com/customers). Pegasystems (“Pega”), founded in 1983 and based in Cambridge, Massachusetts, develops software for operational solutions and customer interaction solutions. Farmers partnered with Pega to develop an automated software solution to provide agents serving small business customers with real-time support and a more intuitive interface. The goal was to enhance the agents’ ability to respond to Famers’ small business customers’ unique needs. A year after the rollout, Pega says its business process management (BPM) technology has enabled the insurance company to double its market share. However, the exact number was not specified in the study. Main results: - The time it takes to form quotes has been reduced from 14 days to 14 minutes. - Umbrella policy sales were up 70 percent. - The new policy system was rolled out in less than five months. - The satisfaction of agents and customers has increased. Additional results: Other efficiency and time-saving tools built into the automation protocol, such as the ability to pre-fill applications for agents serving new customers, are discussed by Mhais Samalya, President of Commercial Business Insurance, in the 3-minute video (in the top right corner of the page). In June 2018, additional evidence of RPA adoption at Farmers was cited in a [Wall Street Journal article](https://www.wsj.com/articles/farmers-insurance-tests-ai-automations-potential-for-speeding-up-claims-process-1530222890?tesla=y) about the company. According to this feature, RPA is being used in a pilot program specifically to “automate a complex and routine process for claims adjusters.” [Rehan Ashroff](https://www.linkedin.com/in/rehan-ashroff-5bb79a/), director of the innovation lab and new ventures at Farmers Insurance, explains that the pilot aims to reduce turnaround times, improve efficiency, and shorten the payout period from weeks to days – or hours. ### Use Case 4: New York Life Goal: Automation at the hands of business administrators, not IT professionals Company info: - Almost 175 years in business - Strengths in Mutual and Life Insurance - National and Global - Operating income of $ 2.06 billion, according to the 2017 [operating earnings reconciliation.](https://www.newyorklife.com/assets/docs/pdfs/financial-info/2017/2017-Reconciliation-of-GAAP-Net-Income-to-Operating-Earnings.pdf) - Its 2017 operating profit was the largest in the insurer’s history to date When New York Life realized it was handling over a million back-office transactions a year, it was looking for smarter ways to improve its processes and increase efficiency. So New York Life dealt with Pega to develop an automated back-office application called Processflow. With Process flow, business administrators can quickly change processes, change steps, or reorder steps. In this three-minute [video](https://www.pega.com/insights/resources/new-york-life-improving-customer-satisfaction-pega), Miguel Suarez, VP of New York Life Direct, and Jason O’Brien, TBC, New York Life Direct, give a presentation discussing the case study. Result: At the time of the presentation, 84 of the 128 tasks in this workflow were either renewed or added to the system by a business administrator, not an IT professional. ### Use Case 5: Zurich Insurance Goal: Save effort, speed up processes Company info: - Almost 150 years in business - Serves over 210 countries - The 2017 annual report shows the total revenue is $ 64 billion. - Investment portfolio $ 207 billion - According to the Insurance Information Institute, it is ranked fourth among the top 10 commercial auto insurance authors in terms of direct premiums in 2016[.](https://www.iii.org/table-archive/20345) [Zurich Insurance](https://www.zurich.com/), a global diversified insurance company based in Switzerland, offers products and services for property, casualty, and life insurance. It is also the parent company of the Farmers Insurance Group. The company reportedly decided to implement RPA by hiring London-based RPA software developer Blue Prism. In September 2017, Blue Prism published a case study describing how it helped a global insurer improve the management of international insurance contracts. Before RPA, the execution and closure of international contracts in Zurich required a significant investment of staff time – particularly, four to five hours of transaction time per policy – and more than 1,000 steps and substages from start to finish. Property and liability insurance are particularly ripe for RPA adoption due to their high volume and overlap with other lines of business. Zurich was planning an initial deployment of the automation process in five countries, including the UK and Germany. At the time of the case study, Blue Prism robots were produced in these two countries. Results: The results are remarkable. RPA implementation has lessened policy transaction times from nearly five hours to 40 minutes to 1.5 hours. In addition, Blue Prism claims that “exceptional” processes reduced effort by 20 to 30 percent, while [straight-through processing](https://www.investopedia.com/terms/s/straightthroughprocessing.asp) reduced the effort required by 70 percent. ### Use Case 6: Aegon Life Insurance Goal: Automation of 120 basic tasks Company info: - Founded in 2007 - Headquarters in Mumbai, India - Serves an international clientele with tools for asset management, life insurance, and retirement benefits. A [case study](https://www.pega.com/customers/aegon) posted by Pega illustrates how Aegon Life Insurance implemented RPA. The insurer first identified opportunities to improve customer service management. For instance, manual legacy business processes often required “multiple steps to validate information regarding user IDs, compliance, policies, and checklist requirements, according to the case study. These time-consuming tasks were mature goals for moving to an automated framework. At the time of this writing, Pega worked with Aegon to manage and automate approximately 120 core business tasks. Reported results: - Expedited Claims Resolution – processing time reduced by 60 percent - A 20% increase in the Net Promoter Score (NPS), an important metric of customer and employee satisfaction - Total savings 84% By using RPA, Aegon has saved time previously spent on staff training or manual completion of tasks. The time savings also contributed to better customer service. The insurer’s contact center increased the first call resolution rate from 50 percent to 80 percent. ## Conclusion Insurers continue to face challenges with rapidly changing customer needs and heightened competition. As the insurance industry relies heavily on efficient back-office processes, insurers have begun implementing RPA to automate transactional, routine, rule-based operations so capital and talent can be repurposed to address more complex and strategic challenges. Robotic process automation is used to promote long-term success and productive market opportunities. RPA in insurance can help achieve higher margins, greater compliance, sustainable company growth, and superior customer service while lowering costs and minimizing customer abandonment. Repeating the versatility and advantages that automation can bring, its adoption in the insurance sector is expected to be inevitable. We at Flobotics, with our UiPath developers, provide end-to-end RPA solutions tailored to your organization. We use RPA as a deeper strategic tool to help you get the most out of it. From assessing the feasibility of a business unit proposal and developing a scalable program to implementing a solution across your business, we do our best for you. We fully back you in analyzing the best automation capabilities that deliver fast results and take your business to the next level. Choose the right people to take advantage of RPA’s vast insurance benefits. Drop us a note via [this link](https://www.flobotics.io/contact), and we will answer soon. #### Like the article? Spread the word Written byMichał Rejman Chief Marketing Officer at Flobotics. [More from Michał](https://www.flobotics.io/our-editorial-team#rejman) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPAEligibility ### Top RPA Use Cases in the Insurance Industry RPA use cases in insurance: see how robotic process automation streamlines claims, underwriting, and other core workflows. Yana PokoraAugust 10, 2021 ](https://www.flobotics.io/blog/rpa-in-insurance-use-cases)[ RPA ### RPA Reloaded: 50+ Robotic Process Automation Statistics to Know in 2026 RPA statistics 2026: 50+ data points on robotic process automation adoption, ROI, and where the technology is headed next. Yana PokoraApril 15, 2025 ](https://www.flobotics.io/blog/rpa-statistics)[ RPA ### What Is RPA? | Robotic Process Automation Robotic Process Automation (RPA), explained: how software bots run a 24/7 digital workforce that cuts costs and human error. Bart TeodorczukSeptember 01, 2025 ](https://www.flobotics.io/blog/robotic-process-automation) [All articles →](https://www.flobotics.io/blog) --- # RPA Failures: 10 Most Common Reasons and How to Avoid Them Canonical: https://www.flobotics.io/blog/rpa-failures Author: Karl Mielnicki Published: 2021-07-06 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/RPA Failures: 10 Most Common Reasons and How to Avoid Them CTO Notes [RPA](https://www.flobotics.io/blog?category=rpa) # RPA Failures: 10 Most Common Reasons and How to Avoid Them [Karl MielnickiCTO & Co-Founder of Flobotics](https://www.flobotics.io/our-editorial-team#mielnicki) Published July 06, 2021Updated September 1, 2026 On this page - [Why Do RPA Projects Fail?](#why-do-rpa-projects-fail) - [10 Most Common Reasons for RPA Failures](#10-most-common-reasons-for-rpa-failures) - [#1 The Process Is More Dynamic than You Think](#1-the-process-is-more-dynamic-than-you-think) - [#2 The Target Interface Changes, but Your RPA Bot Does Not Receive a Reminder](#2-the-target-interface-changes-but-your-rpa-bot-does-not-receive-a-reminder) - [#3 You Underestimate the Political Implications](#3-you-underestimate-the-political-implications) - [#4 You Have Unrealistic Expectations](#4-you-have-unrealistic-expectations) - [#5 Lack of a Coherent Platform](#5-lack-of-a-coherent-platform) - [#6 Lack of Consistency with Stakeholders](#6-lack-of-consistency-with-stakeholders) - [#7 Choosing the Wrong Process for Automation](#7-choosing-the-wrong-process-for-automation) - [#8 Too Much Complexity](#8-too-much-complexity) - [#9 Impossibility of Scaling](#9-impossibility-of-scaling) - [#10 Shadow Deployment](#10-shadow-deployment) - [The “Multiplier Effect”](#the-multiplier-effect) - [Case #1](#case-1) - [Case #2](#case-2) - [Case #3](#case-3) - [How to Deliver a Successful RPA Project?](#how-to-deliver-a-successful-rpa-project) - [IT teams](#it-teams) - [Data and Analytics](#data-and-analytics) - [HR](#hr) - [External RPA specialists](#external-rpa-specialists) - [Conclusion](#conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) [Robotic Process Automation (RPA)](https://www.flobotics.io/blog/robotic-process-automation) is the use of software (“robots” or “bots” in this scenario) to collect and interpret data to automate processes, manipulate data, and exchange it between multiple systems. It is used to automate slow, manual tasks that take up your employees’ time and can help you scale the business processes you are already working on without additional time or resources. Done right, RPA can be the fastest and most efficient way for you to acquire, improve, and deliver information, and it can help your business cut costs and save time for key employees. See the improvement ideas for the [finance](https://www.flobotics.io/blog/rpa-for-finance), banking[, ](https://www.flobotics.io/business-process-automation)or real estate industry. However, without the right structure, logic, and customization, RPA projects can go wrong, and many organizations fail to implement RPA at scale. Turning to the RPA failure rate, [as per EY](https://www.cmswire.com/information-management/why-rpa-implementation-projects-fail/), while RPA can change the economics and service levels of ongoing manual operations, the experts have seen 30 to 50% of initial RPA projects fail. ## Why Do RPA Projects Fail? RPA can be great for tedious and repetitive processes, but it won’t fix a process that you don’t fully understand, or that is, oppositely, fundamentally broken. This is an essential and common mistake that usually leads to the RPA project not achieving its goals. People are trying to implement RPA before they know how their processes work. It tends to fail as they constantly discover new exceptions and variations. Indeed, “exceptions and variations” are not harbingers of RPA success. When evaluating candidate RPA processes, most experts recommend looking for predictable, rule-based processes that repeat regularly. On the other hand, methods that change or don’t follow a predictable path tend to be poorly suited for RPA. RPA tends to fail in two scenarios: - either the process being automated is not as robotic as it was initially intended, - or the resulting automation is running in a much more dynamic environment than previously thought. In any case, the tool requires much more maintenance and continuous development. More work on maintenance and continuous development is not the metric you bragged about. This contradicts in some way why you are considering RPA in the first place: RPA aims to improve the efficiency of processes and reduce the likelihood of human error. Let’s take a closer look at the 10 main reasons why RPA projects fail. ## 10 Most Common Reasons for RPA Failures Despite the obvious benefits, companies often face the issue of why RPA projects fail. It is common for companies to be unaware of the challenges associated with automating robotic processes. According to Forbes, 54% of technology disruptions are due to poor management, while technical issues account for only 3%. Fig. 01 · RPA 10 reasons The ten most common reasons RPA projects fail. Each one is covered below. Why do RPA projects fail? - 01[The process is more dynamic than you think](#1-the-process-is-more-dynamic-than-you-think) - 02[The target interface changes, but your bot is never told](#2-the-target-interface-changes-but-your-rpa-bot-does-not-receive-a-reminder) - 03[You underestimate the political implications](#3-you-underestimate-the-political-implications) - 04[You have unrealistic expectations](#4-you-have-unrealistic-expectations) - 05[No coherent platform](#5-lack-of-a-coherent-platform) - 06[Stakeholders are not aligned](#6-lack-of-consistency-with-stakeholders) - 07[The wrong process was chosen for automation](#7-choosing-the-wrong-process-for-automation) - 08[Too much complexity](#8-too-much-complexity) - 09[It cannot scale](#9-impossibility-of-scaling) - 10[Shadow deployment](#10-shadow-deployment) ### #1 The Process Is More Dynamic than You Think This is the biggest mistake I see happening. It essentially means that you have automated the wrong process. If the process requires decisions on a case-by-case basis, you still want people to be actively involved. Suppose the environment in which the automation operates is more dynamic than expected. In that case, [the RPA toolkit](https://www.flobotics.io/blog/automation-technologies) must have additional complexity to ensure it can continue working in an ever-changing environment and deliver the right results. Again, this is hitting the target. If the process requires decisions on a case-by-case basis, you still want people to be actively involved. Tasks that involve creative thinking, brainstorming, or interacting with the physical world (such as pulling papers from a filing cabinet) are better performed by humans. This does not mean you cannot automate any part of these processes – [a workflow automation ](https://www.flobotics.io/blog/workflow-automation)tool can help you deal with repetitive steps in a process that requires decision-making and human skills. Workflow automation tools and RPA can work together. The idea is to leave human work to be done by humans. Nobody likes to work on low-value, thoughtless, or repetitive work. ### #2 The Target Interface Changes, but Your RPA Bot Does Not Receive a Reminder RPA follows instructions well. It cannot learn on its own or react to unexpected events. Some people don’t make that distinction as they combine RPA with AI (RPA is generally dumb as it stands, although we will likely see an increase in [use cases](https://www.flobotics.io/blog/rpa-use-cases-across-industries) when deployed alongside cognitive technology). We’ve seen an RPA bot break down when encountering scenarios it has not been trained or instructed to operate. One of the most common examples is changes to the target user interface. To put this in perspective, if the RPA bot has been configured to go to a web page and click in the upper left corner to go to the registration page, it can do so until the bot can find that specific button in the upper left corner. The problem arises if you move this registration button to the middle of the page – or anywhere other than the top left corner, for that matter. The RPA sequence will stop because the bot will keep looking for it in the upper left corner. From a technical point of view, we are wrong to call it an RPA failure; this is indeed a human error. The bot works exactly as it was told. I didn’t expect such an obstacle. This is generally a more significant issue than some think when first deploying RPA. A common problem with RPA is process rigidity, dependency, and sensitivity of applications or systems that are being automated. This is because RPA typically uses screen-cleaning technologies with obvious problems that arise when changing user interface screens. ### #3 You Underestimate the Political Implications Here, we want to point out another consideration that has nothing to do with the process itself: the political landscape of your organization. As with many technology investments, your chances of success will be higher if senior executives can help you overcome obstacles when they arise. This can be especially important in organizations where “automation” is a dirty word, often because it makes people paranoid about the safety of their jobs. Areas of the business that do not attract the attention of key executives can also be poorly suited for RPA, as RPA requires political capital in the form of management support to establish corporate governance and provide annual financial costs to sustain operations. For those who buy automation and RPA, it doesn’t seem like there is any reason not to, but for some people in the organization, the sale may not be that easy. Without the support of the right people, RPA projects can stop quickly. While participating in these projects, it is recommended that you think well about potential blockers and work with them to overcome any fears or reasons not to use RPA. ### #4 You Have Unrealistic Expectations As with any technology initiative, you need [metrics to measure](https://www.flobotics.io/blog/rpa-successs-metrics) results and ensure RPA meets its intended goals. Ensure these goals are achievable and you are not trying to hammer in a nail with a screwdriver. RPA solutions are not SaaS or [cloud services](https://www.flobotics.io/blog/uipath-vs-gcp) that work immediately. This can be a problem regarding your supplier relationships, especially if you don’t have RPA experience. As a rule, customers expect RPA solutions to work out of the box with limited customization options. RPA solutions are highly recommendatory deployments and require many professional services to deploy, implement, and support in the future. It is very time-consuming and resource-intensive, requiring much manual work. “A lot of manual work” is what RPA is designed to mitigate, so make sure you do your due diligence. It is not uncommon for organizations to set goals and expectations when they first launch an RPA project, but these expectations need to be controlled. RPA can be very powerful and bring significant benefits, but when working alone, it can only be used for automation, and expectations must be aligned with what is possible, not what you would like to do. ### #5 Lack of a Coherent Platform [Research shows](https://www.forrester.com/report/The-Forrester-Wave-Robotic-Process-Automation-Q4-2019/RES147757) that over 50% of RPA projects cannot grow beyond ten bots, and over 70% of RPA projects reach a plateau with fewer than 50 bots. Companies fail to achieve their RPA goals, largely due to the lack of a coherent platform and the ability to scale modules and intelligence. RPA technologies are more likely to be successful when combined with other intelligent automation solutions, such as cognitive capture and process orchestration. ### #6 Lack of Consistency with Stakeholders Many managers fail to think holistically about an organization’s culture that will need to adapt and support change in its work environment before embarking on its RPA journey. Mastering new technologies, especially RPA, is not an easy task because they change the way people do their work and the organization’s behavior as a whole. Consequently, communicating effectively about these changes, listening to employees’ opinions, and ensuring their commitment are essential to success. Training employees in skills and their ability to navigate this new culture of interaction between bots and humans is also essential. Just as we train new drivers before they hit the road, your employees must understand how to work with RPA technology, build bots, and fulfill their new, bot-powered roles. As in point 3, a lack of alignment with key business stakeholders quickly closes the RPA project. This is due not only to underestimation of the political consequences but also to unrealistic expectations. Suppose you can manage the contributors’ expectations and ensure that the RPA goals align with the business goals and objectives. In that case, you are more likely to attract the right people for the project while minimizing the risk of failure! ### #7 Choosing the [Wrong Process for Automation](https://www.flobotics.io/blog/what-processes-to-automate) RPA works best in locations where transactions are repetitive. For example, RPA is changing the retail and CPG industry and does not require human judgment. RPA is not for those methods where human intervention is needed to complete a task, in which case RPA projects fail. RPA implementation will run smoothly and will likely yield good results if the operations have undergone a selection process through the IT, business, and RPA teams. Sometimes, the reason for RPA project failure is that your RPA developer is non-technical. Saying that anyone can develop an RPA code is a big misconception by the public, fuelled by the top RPA software companies claiming that the platform is low-code and anyone can become a citizen developer. So, [choose an RPA expert](https://www.flobotics.io/contact) carefully. ### #8 Too Much Complexity RPA is powerful - to a certain extent. However, at this stage in their development, many tools available do not handle complexity well. This complexity often manifests in too many steps or decision points in the broader process. Forrester analyst Craig Leclair cites the [“Rule of Five,”](https://siliconangle.com/2019/10/13/hot-bots-payoffs-pitfalls-robotic-process-automation/) noting that if you go beyond the five decision points or applications, you probably need another technology, such as digital process automation (DPA). Thus, organizations must evaluate current and planned RPA deployments. If they have reached or passed the five steps of the process, they have reached the complexity limit. This complexity limit can also result from a lack of structure. The “robotic” nature of RPA means that it focuses on well-defined data formats, steps, and results. Throw in unstructured data or process variations, and RPA will crash at best and break at worst. Again, this requires organizations to evaluate the processes being automated carefully. If the data formats and process steps are not rigid and structured, plan to choose a more suitable tool for DPA, spend significant time pre-labeling and preparing data, or set up a process rule. ### #9 Impossibility of Scaling Another inherent limitation of RPA is that it automates certain tasks – in other words, it mimics human behavior at the individual work level. This has a significant impact at this micro-level but leads to personal improvements for the macro-organization. Research firm IDC calls this scenario [“islands of innovation”](https://www.idc.com/research/viewtoc.jsp?containerId=EUR145762919) —it’s not bad in itself and might make sense as the origin of a digital transformation journey. Still, unless you connect the islands, you’re not going anywhere. Organizations should consider stepping back and wondering what they want to achieve regarding process automation (and whether those goals were met). If it was the automation of a particular task, then, by all means, go to RPA. If this were the broader goal of digital transformation, then using RPA in isolation would not achieve it. The word “scale” also has its difficulties with RPA. Vendors use this term to refer to the reliability of their platform – in other words, how many bots it can support. However, from a consumer perspective, this is only half of the equation. The larger business puzzle is whether RPA scales in terms of impact on organizational processes. The short answer is “no.” An example of these spanners in the works (too much complexity (point 8) and scale beyond the level of individual work) can be found in most larger organizational processes. Take, for example, lending in the financial services industry. RPA can ideally automate specific steps, such as retrieving data from an initial loan application. However, loan processing and approval require numerous steps in which the application travels through many different departments and systems, extracting data from various sources. Expecting RPA alone to transform the entire lending process digitally is a recipe for failure. ### #10 Shadow Deployment To avoid RPA crashing, installing fences for bot deployment is essential so that advanced users are less likely to make mistakes. Bots make creating code more effortless for people outside the core development group. This can lead to the shadowy development of organizations and a lack of oversight. As with any technology, bots must be properly managed, monitored, and logged. Building and deploying a bot is deceiving – it seems easy to create a deployment. Still, without the technology and support process, the bot will likely cause more headaches and generate more work than if the task is done manually. IT departments also need to work directly with business users and communicate that RPA is just one tool in their IT toolbox. When determining if a task is suitable for RPA, it is essential to ask questions about the volatility and repeatability of the job before assigning a bot to it. Organizations should [seek assistance](https://www.flobotics.io/rcm-automation) from successful RPA implementation strategies and consulting services. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## The “Multiplier Effect” More than one of the problems described above is often present or related, creating significant multiplier effects. As our list of Top 10 RPA failure examples shows, fixing these problems requires a lot of foresight or outside help. Unfortunately, if more than one of these problems occurs, which is expected, a significant multiplication effect can lead to a loss of faith in RPA or to a project halt. Let’s look at an example of three more straightforward problems encountered in an RPA program. In the scenario below, we want to provide a simple PoC for data cleansing and then quickly deploy it to production to gain tactical benefits: ### Case #1 Issue: Using the wrong delivery methodology. Normal delivery time if problems can be avoided: 2-4 weeks. With skilled resources and an agile RPA-centric approach, simple sub-processes are usually automated and ready to run in two to four weeks. Normal delivery time if the problem affects: 10-15 weeks. If a software delivery method is used, redundant documentation and management gateways can quickly take six to eight weeks to be ready to go. ### Case #2 Issue: Assuming the skills required to build a PC are sufficient to automate production. Normal delivery time if problems can be avoided: 2-4 weeks. Knowing that PoC needs to be launched means that proper design, rigorous development, and unit testing are being used. Hence, the PoC delivery portion can take anywhere from one-two week to two-three weeks to prove it is fully scalable, resilient, and auditable. Normal delivery time if the problem affects: 10-15 weeks. If PoC is delivered by insufficiently skilled personnel, then training the robot to process can miss important scaling, error handling, concurrency, or scheduling issues. Consequently, there can be numerous testing cycles and reworking before it is ready to go – adding two-three weeks. ### Case #3 Issue: Too much process automation or failure to optimize for RPA. Normal delivery time if problems can be avoided: 2-4 weeks. Assuming the focus is on the optimal 70% of the process, it can be automated in two to four weeks. Normal delivery time if the problem affects: 10-15 weeks. Continuing to automate the remaining 30% is often associated with convoluted exception handling or multiple happy voyages splits, so delivery times can be doubled by adding two to four weeks. ## How to Deliver a Successful RPA Project? The good news is that most RPA failures result from human error, not the technology itself. The most important lesson here is that companies can learn from past mistakes and generally take a different approach. Companies must develop a roadmap for the entire RPA implementation process. This ensures that all participants fully understand their roles. Companies should check whether all internal and external stakeholders are consulted to rule out outcome assumptions. This is especially important in projects where there is no external implementation partner. Organizational consistency is critical as the organization alone is responsible. All teams and management must be fully involved. Top-level leadership must review each implementation step so that local groups devote significant time to automating processes. Everyone should be convinced in advance to use it. Based on our experience, we recommend that you seek advice from the following departments: Fig. 02 · RPA consulting 6 benefits Benefits of RPA consulting - 01A strategy built with experts - 02A better chance of success - 03Better research and process mapping - 04Faster deployment and optimization - 05Employees involved in the process - 06Professional KPI and ROI checks ### IT teams The IT teams should be consulted before building a roadmap for an RPA solution. The IT department will act as a focal point between internal and external groups, as needed. IT will also know if future integration problems with existing systems will exist. If the company already has an RPA implementation, IT should combine both concepts, learning from the previous RPA implementation. ### Data and Analytics Data and analytics are included in most management programs, and bots can generate significant amounts of data. If analytics is involved from the beginning, then important decisions are made based on valuable data from bots rather than diagnostic information obtained from most bot installations. ### HR HR is critical to alignment. Otherwise, RPA training programs may never be included in the corporate training schedule. RPA training is crucial to cut reliance on RPA consultants and empower employees. ### External RPA specialists External RPA specialists ([UiPath consultants](https://www.flobotics.io/about-us), particularly [RPA developers](https://www.flobotics.io/contact)) like us are already running many processes for large companies. It makes sense for the business to consult with companies like ours since we have accumulated significant experience in the RPA field. Most companies don’t have RPA solutions, so they ask us to design the technology for them, either with our turnkey solutions or expert knowledge if the client wishes to develop an RPA in-house. See the [process in the healthcare industry you didn’t know can be automated](https://www.flobotics.io/blog/healthcare-workflow-automation), the benefits, and how you can predict the failures. ## Conclusion For the reasons listed above, it is clear that RPA should be used for processes that can be automated with a simple and intuitive user interface. Not all RPA project bugs are the same, and most, if not all, are avoidable. RPA was a new technology five years ago. Today, it is rapidly gaining traction, and the experience of developers and owners has expanded. Yes, there are a number of reasons why RPA projects fail, but they are all understandable and manageable. Moreover, the relevance of the introduction of this technology is increasing, not decreasing. Although the list of organizations that have achieved success in large-scale RPA projects is small, it is constantly growing. Businesses that succeed early with this wave of automation will create a structural advantage that their competitors will be hard-pressed to resist. The 5% of companies that do well with RPA today are demonstrating that the technology really works, and these businesses are creating yet another technological arms race that all organizations must join in order to survive, let alone prosper. Yes, [achieving full RPA ROI ](https://www.flobotics.io/roi-calculator)in one quarter may protect your bonus this year, but successful large-scale bot deployments over the next year or two will protect your job and possibly your career. This may sound like the same hyperbolic rhetoric that the RPA industry has been at fault for all this time. But no. Rather, it is the inevitable result of a technology demonstrating that it can work when applied correctly and does indeed produce game-changing results. After all, as with PCs, the Internet, and social media, not using RPA is not an option. You just have to do it right. Moreover, an attempt to automate more and more complex processes within the framework of one task or solution can lead to various errors. Therefore, choosing the right approach is a must. Flobotics understands RPA processes and provides a hassle-free model for outsourcing RPA implementation. Considering bringing RPA to your organization? [Get in touch with us](https://www.flobotics.io/contact). #### Like the article? Spread the word Written byKarl Mielnicki CTO & Co-Founder of Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Why Your Non-Technical RPA Developer Sucks Canonical: https://www.flobotics.io/blog/rpa-non-technical-developer Author: Karl Mielnicki Published: 2021-06-15 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Why Your Non-Technical RPA Developer Sucks CTO Notes [RPA](https://www.flobotics.io/blog?category=rpa) # Why Your Non-Technical RPA Developer Sucks [Karl MielnickiCTO & Co-Founder of Flobotics](https://www.flobotics.io/our-editorial-team#mielnicki) Published June 15, 2021Updated September 1, 2026 On this page - [The Technicalities Of RPA](#the-technicalities-of-rpa) - [Knowledge Of RPA Software](#knowledge-of-rpa-software) - [General Process Automation And Business Skills Knowledge](#general-process-automation-and-business-skills-knowledge) - [Conclusion](#conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) The ability of [Robotic Process Automation (RPA)](https://www.flobotics.io/blog/robotic-process-automation) to modernize business operations and reduce costs has provided organizations the opportunity to automate unexciting business processes, allowing workers to devote more time to other higher-value work. According to [Forrester](https://www.forrester.com/report/The-RPA-Market-Will-Reach-29-Billion-By-2021/RES137229), the RPA market is expected to grow to $2.9 billion before the end of 2023. However, designing and developing a good robotics implementation requires a deep level of technicality. While it is true that anyone can learn to code robots, not everyone will be good at it. Read on to find out why as a technical RPA developer, I’ve come to such a conclusion. ## The Technicalities Of RPA In my undergraduate days, Courses like Unix Fundamentals, Programming, Calculus I, II, III, Discrete Mathematics I, II, Electronic Principles, etc., were part of my curriculum for my Bachelor’s degree in Computer science, which gave me a perfect head start and contributed to my success in the RPA world. Don’t get me wrong, I’m not saying that a Computer Science degree is necessary to be efficient at RPA, but technical people will do much better than people in Arts & Humanities. A non-technical person can be a good developer; pretty much everything can be taught today, but the journey would be much more vigorous in such an instance. The following are the things that were foreign to me when I started: - Object-Oriented vs. Scripting Languages - Object-Oriented Concepts - Regex - Differences between static and non-static - Algorithm optimization - Scalability - Reusability - Clean code - d{1,2}/d{1,2}/d{2,4} Let’s take two people, for example, one technical and the non-technical. Finding the differences between the automation of two Excel files will yield two very different solutions for both of them. So, a non-technical person will probably find no need to think about things like scalability and reusable components involved. And what happens in a situation where we decide to go a lot further by adding more Excel files, increasing the rows to thousands, and instructing them to run the program hundreds of times a month? A solution that wasn’t scalable past two small Excel files won’t be good. And this is where experience comes in! So, the ability to see the bigger picture and foresee the possible future of automation is essential. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Knowledge Of RPA Software The knowledge of the software program is learnable to a certain degree but takes longer. The extent of the digital domination of today’s world has made the automation of varying repetitive tasks and processes prevalent. RPA helps automate these repetitive tasks by identifying and simulating human interactions with legacy systems. Implementing RPA only requires adding existing processes and legacy systems instead of installing new infrastructure. RPA tools like Blue Prism and UiPath are needed to develop processes. So, it will take much longer to grasp these tools if there isn’t a technical knowledge foundation. As a technical RPA developer, I don’t have to think about things too much compared to a person who doesn’t fully understand the basics. Learn more about RPA workshops and training on building and deploying RPA bots and infrastructures in a chosen automation tool and following RPA best practices. Fig. 01 · RPA skills Not the same Knowing RPA is not the same as being good at it ≠ To know RPA - Knowing the tools and features To be good at doing RPA - Building bots that keep working in real processes ## General Process Automation And Business Skills Knowledge Business process automation paves the way for a streamlined workflow unbridled by manual, time-sucking tasks. BPA enables you to automate Analytics, Sales, Planning, and Customer relationships. If you don’t know all the ins and outs of a process, including who is responsible for operating it, you probably won’t be able to automate it effectively. Your technical background and experiences would have shaped you and provided more insight into how well processes function. So this creates a clear path for higher productivity and eliminates wasteful activities. ## Conclusion Saying that anyone can develop an RPA code is a big misconception by the public, fuelled by the top RPA software companies claiming that the platform is low-code and anyone can become a citizen developer. Anyone can learn to play chess in a matter of minutes. There are only a handful of moves and rules to remember, but being great at chess is a different story. But even if that person eventually becomes good at coding, it still doesn’t make them a computer scientist. Hire a technical RPA developer with an excellent understanding of all ins and outs of Robotic Process Automation. #### Like the article? Spread the word Written byKarl Mielnicki CTO & Co-Founder of Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### What Is RPA? | Robotic Process Automation Robotic Process Automation (RPA), explained: how software bots run a 24/7 digital workforce that cuts costs and human error. Bart TeodorczukSeptember 01, 2025 ](https://www.flobotics.io/blog/robotic-process-automation)[ RPA ### 8 Best Security Practices for RPA Implementation RPA security best practices: 8 steps to manage the security risks of your organization's automation implementation. Krzysztof SzwedSeptember 20, 2021 ](https://www.flobotics.io/blog/8-security-practices-for-rpa-implementation)[ RPA ### How to Find and Hire a Great RPA Consultant RPA consultant hiring guide: what to look for and how the right partner turns manual tasks into fast, reliable automated workflows. Karl MielnickiMay 19, 2022 ](https://www.flobotics.io/blog/how-to-find-and-hire-a-great-rpa-consultant) [All articles →](https://www.flobotics.io/blog) --- # 5 Ways RPA Can Take Your Customer Experience To A New Level [With Examples!] Canonical: https://www.flobotics.io/blog/rpa-customerexperience Author: Michał Rejman Published: 2021-06-07 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/5 Ways RPA Can Take Your Customer Experience To A New… [RPA](https://www.flobotics.io/blog?category=rpa) # 5 Ways RPA Can Take Your Customer Experience To A New Level [With Examples!] [Michał RejmanChief Marketing Officer at Flobotics](https://www.flobotics.io/our-editorial-team#rejman) Published June 07, 2021Updated September 1, 2026 On this page - [What is RPA?](#what-is-rpa) - [Why does customer experience management need RPA?](#why-does-customer-experience-management-need-rpa) - [Five ways of implementing RPA in customer experience](#five-ways-of-implementing-rpa-in-customer-experience) - [#1. Focuses on tasks that develop customer relationships](#1-focuses-on-tasks-that-develop-customer-relationships) - [#2. Quickly responds to customer requests](#2-quickly-responds-to-customer-requests) - [#3. Solves a customer problem before they hang up](#3-solves-a-customer-problem-before-they-hang-up) - [#4. Reduces human error](#4-reduces-human-error) - [#5. Boosts your Net Promoter Score](#5-boosts-your-net-promoter-score) - [Case studies](#case-studies) - [Involving employees in automation](#involving-employees-in-automation) - [Using bots to find flaws](#using-bots-to-find-flaws) - [Reconcile 75,000 lines of data in minutes](#reconcile-75-000-lines-of-data-in-minutes) - [Conclusion](#conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) One of the most talked-about, debated, and blogged topics these days revolves around artificial intelligence, Robotic Process Automation, and the myriad ways they will change our lives. Due to the big buzz around, Robotic Process Automation has become the hottest topic of discussion among senior management. One of the main benefits of RPA is that it helps automate routine tasks. This increases employees’ productivity and gives them enough time to complete value-oriented tasks. But first things first. Here in this blog post, we discuss RPA in customer service. ## What is RPA? Initially, automating processes aimed to increase the speed of order fulfillment. By eliminating manual data entry, businesses can improve speed, efficiency, and accuracy – and, of course, profit. Fast forward to the early 2000s and the arrival of Robotics Process Automation (RPA). RPA is a capability (software and services) that allows virtual employees, also known as “bots,” to transact on any of the company’s systems like a human, performing complex rule-based actions. RPA software allows users to create automation and manage workflows with drag-and-drop functionality in a visual way that can be completely independent of coding knowledge. The beauty of RPA is that it allows company employees to easily customize the “robot” for reasoning, gathering and extracting knowledge, recognizing patterns, learning, and adapting to new situations or environments. The global [Robotic Process Automation (RPA) market](https://www.grandviewresearch.com/industry-analysis/robotic-process-automation-rpa-market) volume was estimated at $597.5 million in 2018 and is expected to reach $3.97 billion by 2025. According to a study by Grand View Research, Inc., the industry will grow with an average annual growth rate of 31.1% for the forecast period. RPA dominates the industry today. ## Why does customer experience management need RPA? Many companies use RPA tools to develop software for data management, transaction interpretation, and interaction with other digital systems. You can scale your business growth by leveraging RPA automation best practices anywhere in your project. Recently, a [study](https://www.gartner.com/smarterwithgartner/realize-the-value-of-rpa-in-financial-reporting/) was conducted with financial and accounting professionals on the benefits of using RPA software. The study concluded that automating robotics processes helped eliminate much of the repetitive, time-consuming, manual processes that professionals in these industries perform every day. RPA can help improve workplace efficiency and provide more accurate insights. It can also give real-time access to financial data with analytics and reporting features. Since the big data boom, the volume of financial data has grown exponentially. The only way that finance professionals can keep up is through the use of this type of technology. RPA can add real value not only to the customer experience at the operational level but also to the workplace from a strategic point of view and can help a company to profit. Many companies are starting to pay attention to how RPA is improving their customer experience. This technology allows software robots to learn to mimic human behavior. For example, RPA technology can manage enterprise software systems such as FSM software, ERP systems, and service management tools. This is achieved by using the interface of each application in the same way as a human would. The only exception is that the robot can work much faster and more efficiently without taking breaks or slowing down. However, as with all technologies, there are some limitations to using artificial intelligence, RPA software, and machine learning. However, RPA significantly improves the customer experience and can boost your sales. The RPA approach can optimize a company’s internal processes by combining technology and people. It can also help identify ideas and trends more quickly, allowing businesses to seize opportunities. RPA works better with general rule-based tasks that require manual input. Once configured, the software robot will use different application interfaces. Typically, only a few modifications are needed to implement a robot. In some cases, if configured correctly, no changes will be required from the outset. ## Five ways of implementing RPA in customer experience Fig. 01 · RPA market $ millions Total RPA market, 2016–2022 - 612271341 - 1,114626488 - 1,7151,076639 - 2,3451,553792 - 2,9942,048946 - 3,6532,5521,101 - 4,3083,0531,255 2016201720182019202020212022 - RPA software and services - BPA software and services Year-on-year growth slowed from 131% (2017) to 20% (2022) for RPA, and from 43% to 14% for BPA. | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | RPA software and services | 271 | 626 | 1,076 | 1,553 | 2,048 | 2,552 | 3,053 | BPA software and services | 341 | 488 | 639 | 792 | 946 | 1,101 | 1,255 | Here are some ways RPA improves the customer experience, perhaps in your competing organizations. ### #1. Focuses on tasks that develop customer relationships Once again, robotic process automation helps companies automate routine tasks, which increases efficiency and reduces costs. When machines handle repetitive tasks, workers have more time to invest in value-driven tasks related to creativity, innovation, problem-solving, customer communication, and customer experience development. Moreover, RPA allows customer agents to focus on customer relationship tasks. Let’s see how RPA does it. It helps agents by offloading repetitive tasks so they can focus more on improving their skills and strengthening customer relationships. One of the most popular examples of using RPA was when one bank changed the order processing to use bots to process 1.5 million requests per year. You’d be surprised to know that the total work done by 85 bots was equal to the productivity of 200 full-time employees, but that was equivalent to only 30% of the cost. Thus, using RPA helped the bank increase productivity, allowing it to use the saved time and money to solve value-oriented problems related to building customer relationships. You can also hire RPA developers for your projects to increase the overall business performance. Advantages of this approach: - Takes less time - Increase your productivity - Requires fewer resources - Reduces cost ### #2. Quickly responds to customer requests RPA has completely changed the way companies NOW respond to customer inquiries. Have you heard of Amelia before? It is a chatbot adopted by Allstate to help its employees interact with customers. Contact center operators can use Amelia to access the latest insurance policies and protocols while on the phone with a client. Using this chatbot lets the company achieve the best of both worlds: on the one hand, customers get instant responses to their queries. On the other hand, they also get the speed and efficiency of the chatbot to handle huge volumes of ever-changing insurance information. Gartner predicts that by the end of 2021, 15% of all customer service interactions globally will be handled completely by AI. In the coming days, businesses will likely use RPA-driven chatbots to handle customer requests, showing that understanding RPA (Robotic Process Automation) techniques is NOW more important than ever. Advantages of this approach: - Increase speed and efficiency - Quick response to customer inquiries - Processing multiple requests in less time - More spare time ### #3. Solves a customer problem before they hang up Huge delays in responding to customer inquiries can be a huge hurdle and can seriously damage your reputation in the market. Spending too much time-solving customer requests and keeping customers waiting too long is not good. Let’s look at the aspects that determine how quickly your company responds to customer requests to ensure incredible customer satisfaction. One of them is FCR (First Called Resolution). It is the KPI that has the greatest impact on customer satisfaction. A study of over 150 call centers found that each percent improvement in FCR results in a corresponding one percent increase in customer satisfaction. The key to improving FCR is to immediately provide customer agents with the information they need to address customer inquiries in less time. This is how the RPA customer experience comes into being! Using RPA solutions, the catered robot can display relevant information on top of any program on the agent’s computer, making it easier to access critical information in real time without taking too much time. This way, RPA helps you retain your customers and address their needs before they hang up on your site. This is mainly why understanding RPA in customer support techniques has become a topic for businesses. Advantages of this approach: - Data reassignment - Updating fields - Navigating complex applications - Retrieving customer information ### #4. Reduces human error One of the main benefits of RPA is reducing human error by automating tasks. This is a huge relief for employees as they no longer have to spend hours fixing mistakes. Research has shown that 10% to 20% of a person’s work time is spent on repetitive, low-level computer tasks. The human error only exacerbates the situation and takes much company time and resources. But using RPA as a solution can reduce errors, which allows customer agents to spend time on value-driven tasks. And all thanks to RPA robots! One of the benefits of customer journey automation is that it gives employees enough time to complete advanced functions, which helps them improve their problem-solving and creativity skills. Understanding RPA and using it is also beneficial for organizations, as they can save on the costs spent on correcting work that has a human error. According to an IDC white paper, the human element costs organizations more than $ 62.4 million annually! With RPA, organizations can reduce over 65% of their costs and achieve ROI within six months of implementation. Advantages of this approach: - Increase productivity - Reduces human error - It saves time and money ### #5. Boosts your Net Promoter Score To improve your customer experience, you must be clear about where you are in the market and how to boost your customer experience. This allows you to bring more business users and increases customer retention. Among all the methods that prevail in the market today, the Net Promoter Score (NPS) has proven to be the most effective way to measure customer satisfaction and loyalty. But how do you calculate this? The answer is simple. NPS is calculated based on responses to a simple question: “How likely is it that you recommend us?” Net Promoter Score is the difference between the number of people who will and will not recommend your services/products to others. The Net Promoter Score measures your customers’ willingness to recommend a company’s products or services to others and helps you gauge your market position. First, the assessment measures how well your services satisfy the target customers. RPA customer experience bots automate tasks, allowing employees to devote more time and attention to tasks that help build client relationships. Customer service agents can now focus more on understanding customer needs and spending time-solving their problems. You can improve your Net Promoter Score by using RPA automation anywhere in your business. The process of using RPA is simple but can sometimes be very expensive. “Show your bots what you are doing, then let them do the job. They can even interact with any system or application just like you,” said [Mukund Srigopal](https://www.forbes.com/sites/tomtaulli/2019/02/02/what-you-need-to-know-about-rpa-robotic-process-automation/), director of product marketing at Automation Anywhere. Advantages of this approach: - Allows employees to devote more time to customer-related issues - It lets you spend less time on repetitive tasks - Helps to solve the buyer’s problems quickly - Provides effective communication with experts Fig. 02 · Customer experience 9 benefits What RPA brings to customer experience - Lower costsAutomating time-consuming tasks can save 40–75%; a software robot costs far less than a full-time employee. - Better customer experienceFreed-up time goes back into customer success. - More word of mouthFaster replies mean fewer complaints and better reviews. - Lower operational riskFewer errors from fatigue, confusion or missing knowledge. - Better internal processesFaster reporting, onboarding and internal performance. - More accurate reportsLess bias, more consistent processes, better customer satisfaction reports. - 24/7 responseHigher-quality work at any time of day. - Keeps your IT systemsBots work with existing systems; nothing has to be replaced. - Engaged employees and strong ROIStaff move to meaningful work and face-to-face customer time. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Case studies The Colorado Housing and Finance Authority finances affordable housing and uses robotic process automation to speed up repetitive but necessary work. The quasi-government agency has digitized a mortgage reconciliation process that used to take four employees over three days but is now completed in just a few minutes. Likewise, according to one executive, Equifax’s consumer credit reporting company has turned to Robotic Process Automation (RPA) tools to move faster in a market that punishes those who are slow to complete customer tasks. Read more about using [RPA in the finance industry](https://www.flobotics.io/blog/rpa-for-finance). Fortune 500 insurance company Unum measures the performance of about 40 RPA bots that either help employees or tackle repetitive tasks entirely. Bots help Unum find weaknesses in processes so that the company can eventually rework them using more extensive and persistent RPA software. Unum, Equifax, and the Colorado Housing and Treasury Administration (CHFA) ​​recently shared their views on why they want to bring automation to workflows that humans have long done. For them, RPA does not threaten their jobs but rather relieves them of routine tasks so that they can carry out tasks that require more discretion. Using RPA tools that reduce errors, speed up workflow, and enable employees to tackle large-scale projects, these companies say they are better positioned to serve customers who expect service to be delivered quickly and near perfect. “For us, it’s about ensuring that our services are very good for our clients,” said Jairo Quiros, vice president of general global services at Equifax and site manager for the company in Costa Rica. “RPA is a means to achieve this goal.“ ### Involving employees in automation The London School of Economics found that RPA delivers between 30% and 200% ROI in its first year of use. But in an [interview with McKinsey & Company](https://www.mckinsey.com/industries/financial-services/our-insights/the-value-of-robotic-process-automation), Leslie Wilcox, professor of technology, labor, and globalization at the school’s management department, said companies would be wrong to focus solely on financial gain, particularly those derived from labor savings. As Wilcox and other automation experts have pointed out, RPA tools – when used correctly – can deliver long-term benefits. For example, Equifax first tried RPA in 2016. “Think big but start small,” Quiros said. “We had a lot of questions about RPA: “Is it real? Will it bring the benefits that we expect? ” However, two big questions remain. “Can we do it globally, and can we do it so quickly?” Now, by applying RPA to 65 processes, most of which are paper-based, Equifax can answer these important questions in the affirmative. Indeed, its RPA portfolio is expanding, Quiros said, noting that Equifax uses RPA software to address certain product and service-related challenges, such as speeding up the time it takes to compile mortgage credit reports. And in the customer service department, RPA robots now perform data entry tasks that previously required employees to switch between 20 different windows of computer programs. “The bot will offer a window asking what to do,” Quiros said. “Bots will collect data to solve a complex customer problem.” The customer service agent’s focus is no longer split, he said, but instead focused on communicating with the customer. RPA allows Equifax to check now “thousands of systems and thousands of processes that have not been analyzed for a long time,” Quiros said. Of course, such conversations can make employees worry about the safety of their jobs. But Quiros said that the corporate automation center of excellence had put RPA in the hands of employees, allowing them to see how it works and, in turn, get rid of their fears. As employees decide how best to use RPA, rather than leaving it to the IT department, he said they can recognize the work areas for which automation is best. “The business is responsible for launching the bot,” he said. “This is driving the [growth] of a culture of automation.” That way, employees don’t have to worry about robots taking their jobs, Quiros added. Instead, he said that if employees are promoting ideas for how RPA can make their jobs easier, Equifax will try to automate those repetitive tasks so employees can do more for the client. “They accept it.” ### Using bots to find flaws Insurance company Unum also experimented with RPA software in 2016. Previously, customer service representatives had to log into several different systems to perform simple tasks such as changing a customer’s address and copying and pasting “everywhere,” said Rex Price, Technology Capability Manager, General Services, Center of Excellence for Process Efficiency at Unum. He said it was “a good launching pad for us” as a trial run of Unum with RPA combined customer and policy information. He also took care of the repetitive work of injecting corrected data into various legacy system programs of the company. Fast forward almost two years and Unum has 30 human-maintained desktop bots and ten more automated bots, not only processing customer information in the contact center but also helping the policy administration customer service team with repetitive tasks like changing insurance policies and follow-up work on expired policies. These bots, offered by software company Pega, improve customer experience by reducing lead times and task transfers, Price said. He hopes to have 75 bots implemented by the end of the year. Price said he doesn’t yet know the full measure of the financial gain to be gained from RPA, but Unum’s ultimate goal is to ditch bots and change all the repetitive processes instead of eventually. This is because bot connections can be interrupted when data sources change; the main problem remains even after the bot is repaired. Unum intends to eventually overhaul these processes by identifying flaws and constantly automating repetitive manual tasks with the Pega Platform, the vendor’s flagship product. “Some people who cut and paste [to change customer information] hug us,” Price said. “They can think more about improving quality.” ### Reconcile 75,000 lines of data in minutes Each month, the Colorado Housing and Treasury business unit reconciles accounts, reports, and other data sources to ensure that CHFA customer loan information is consistent with the data provided by the loan service company. It contains 75,000 rows of spreadsheet data and is “an ideal use case for automation,” said Brian Mueller, manager of the integrated records management division of CHFA. Previously, it took four people in a business unit three days to manually transfer data from a series of spreadsheets to a database. Using RPA software, data is automatically retrieved and placed into an SQL table and then compared with information in the data warehouse. Any discrepancies in information are displayed through a user interface for employees who can reconcile the data in minutes. “They can opt out of manual data entry,” Mueller said of the business unit. “They can focus on high-level things more important than moving data.” For example, these employees now have more time to view down payment benefits data. Want to see more RPA use cases? Click here to[ read about RPA use cases ](https://www.flobotics.io/blog/rpa-use-cases-across-industries)> ## Conclusion The nature of automation eliminates any inherent human error or bias from repetitive back-office processes, ensuring a consistent customer experience. It also allows your employees to focus on the most important customer-centric business areas. In this age of digital transformation, it is becoming increasingly clear that the more time your company can spend interacting with a customer, the more positive the customer experience will be and the better the outcome for all parties. This is true both during customer interaction and in the future. As Flobotics customers can attest, [RPA can transform the way businesses do business](https://www.flobotics.io/case-studies) on the server to improve efficiency, productivity, and, ultimately, customer service in any industry. Companies using this technology to improve customer interactions will be able to gain some competitive advantage. On top of that, as more and more processes are automated to free up time with the client, the better the experience will be in the long run. Reach out to our [RPA consultants](https://www.flobotics.io/about-us) to know more about the automation of your specific processes. #### Like the article? Spread the word Written byMichał Rejman Chief Marketing Officer at Flobotics. [More from Michał](https://www.flobotics.io/our-editorial-team#rejman) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### RPA Reloaded: 50+ Robotic Process Automation Statistics to Know in 2026 RPA statistics 2026: 50+ data points on robotic process automation adoption, ROI, and where the technology is headed next. Yana PokoraApril 15, 2025 ](https://www.flobotics.io/blog/rpa-statistics)[ RCMRPAHealthcare ### Medical Billing Management: Best Practices, Key Metrics and Automation Medical billing management: the 8-stage billing cycle, the metrics and reports that show revenue leakage, and 8 best practices to fix it. Yana PokoraJuly 25, 2023 ](https://www.flobotics.io/blog/medical-billing-management)[ RCMHealthcare ### How to Improve Electronic Health Records Processing with Automation EHR automation with RPA: fix electronic health record imperfections without a system overhaul - pros, cons, and real use cases. Bart TeodorczukAugust 09, 2021 ](https://www.flobotics.io/blog/electronic-health-records-rpa) [All articles →](https://www.flobotics.io/blog) --- # BPM vs. RPA: The Difference and What It Means for Your Business Canonical: https://www.flobotics.io/blog/bpm-vs-rpa-the-difference-and-what-it-means-for-your-business Author: Filip Nasiadko Published: 2021-05-19 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/BPM vs. RPA: The Difference and What It Means for Your… CEO Notes [RPA](https://www.flobotics.io/blog?category=rpa) # BPM vs. RPA: The Difference and What It Means for Your Business [Filip NasiadkoCEO and Co-founder at Flobotics](https://www.flobotics.io/our-editorial-team#nasiadko) Published May 19, 2021Updated September 1, 2026 On this page - [What is RPA?](#what-is-rpa) - [What is BPM?](#what-is-bpm) - [BPM vs RPA (comparison)](#bpm-vs-rpa-comparison) - [Definitions and core functions](#definitions-and-core-functions) - [RPA vs BPM: Technology](#rpa-vs-bpm-technology) - [RPA – Software Technology](#rpa-software-technology) - [RPA vs BPM: Automation Focus](#rpa-vs-bpm-automation-focus) - [RPA vs BPM: Deployment Effort of integrations](#rpa-vs-bpm-deployment-effort-of-integrations) - [RPA vs BPM: Business Impact](#rpa-vs-bpm-business-impact) - [BPM vs RPA: what are the differences](#bpm-vs-rpa-what-are-the-differences) - [How is RPA used?](#how-is-rpa-used) - [How is BPM used?](#how-is-bpm-used) - [BPM and RPA combined](#bpm-and-rpa-combined) - [BPM will help determine the preferred processes for automation](#bpm-will-help-determine-the-preferred-processes-for-automation) - [BPM and RPA will help link legacy and modern systems](#bpm-and-rpa-will-help-link-legacy-and-modern-systems) - [BPM can help with exception handling in RPA rules](#bpm-can-help-with-exception-handling-in-rpa-rules) - [RPA can be deployed and managed by people who are not developers](#rpa-can-be-deployed-and-managed-by-people-who-are-not-developers) - [Future predictions about using RPA and BPM](#future-predictions-about-using-rpa-and-bpm) - [Conclusion](#conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Business Process Management (BPM) is a concept that has been on the market for many years and has earned users’ trust. Robotic Process Automation (RPA) is a relatively new technology with great potential. Robotics Process Automation (RPA) is a popular topic today. At the same time, questions often arise, whether Business Process Automation systems (BPMS) are disappearing into oblivion and new technology is coming to replace that. Nevertheless, BPM vs. RPA has something in common. Abbreviations in both of them with “P” stands for “process.” BPM has a longer history, but at its core, both improve the performance of enterprises. Despite this, BPM and RPA are increasingly being used together and are even integrated into some tools. BPM and RPA are not competing for technologies. They help each other solve the same issue from different aspects. So, BPM systems solve the problems of process management automation and RPA – the automation of specific operations. The correct combination of these technologies gives a powerful synergistic effect. You can also learn more about [Robotic Process Automation and Machine Learning](https://www.flobotics.io/blog/robotic-process-automation-vs-machine-learning). RPA vs. BPM confuses – many users do not understand how they combine and where the differences lie between them. But first things first. ## What is RPA? RPA (Robotic Process Automation) technology allows you to shift routine work from a person to a robot. Routine refers to the standard, repetitive operations that office workers perform using the keyboard, screen, and mouse. A robot that does routine work for a person is a program that, just like an employee, needs a keyboard, screen, and mouse. But it only uses them virtually. The robot copes with the routine: - faster than a person; - no mistakes associated with the “human factor”; - no vacations, weekends, or breaks; - with a predictable and easily controllable result. Implementing RPA does not rebuild the existing workflow. Replacing humans with robots does not change the principle of work organization. When the performer is altered – the speed increases, the number of errors decreases. For more info, see our [Robotic Process Automation Guide: All You Need To Know About RPA. ](https://www.flobotics.io/blog/agentic-ai-vs-rpa) To understand how RPA can be useful in different industries, check the article about implementing [RPA in finance,](https://www.flobotics.io/blog/rpa-for-finance) RPA in insurance, or RPA in logistics. ## What is BPM? BPM or Business Process Management combines a management concept that considers a company as a network of interconnected processes. Any business process is a daily purposeful activity of employees, which is completed and leads to a certain result. So, examples of business processes are: - bank account opening process, - sales process, - employee hiring process. BPM breaks down the company’s business process system into a sequence of task steps, describes them in the form of a diagram, and automates them. BPM systems are a special group of software products that implement the concept of process management. Modern BPM platforms provide management of complex, branched, dynamically developing processes. BPM tools allow you to model business processes, support users, and track the progress of tasks. Fig. 01 · Automation Examples Processes you can automate Processes you can automate - 01Creating reports from ready-made templates - 02Analyzing information and checking it for errors - 03Changing and copying data in Excel tables - 04Moving information between systems - 05Filling in clients' screen forms ## BPM vs RPA (comparison) ### Definitions and core functions First, you need to distinguish between them and determine what each is. Most practitioners usually argue that BPM is a specific activity that a company does. So, BPM, in a broader context, is the continuous work of documenting, analyzing, evaluating, and improving the processes that govern the day-to-day activities of an organization. And software tools for Business Process Management eat the product of this people-centered practice. On the other hand, RPA is software. “Robotization” should not conjure up associations with the books of science fiction writers. RPA refers to software bots that automate certain computer tasks, such as extracting or transferring data. People must create and manage these bots to achieve their goals, but ultimately RPA is just software. In a broader sense, we see RPA and BPM as a symbiosis of technologies, especially for use cases in key areas such as HR, insurance claims processing, or order processing. ### RPA vs BPM: Technology ### RPA – Software Technology A subset of Business Process Automation, RPA is a kit of technologies created to support and execute improvements developed with BPM. So, Robotic Process Automation relies on the application of software robots (often abbreviated as “bots”) to automate and optimize large-scale processes. Brief: Software “bots” are configured to perform routine, repetitive tasks that an employee usually has to perform. #### BPM – Holistic Technology BPM is a complex set of technologies and processes designed to integrate and manage disparate business functions into a coherent whole. It is a key component of digital transformation. It bridges legacy systems and new technologies, eliminating unnecessary waste and costs. BPM solutions are strategic, integrating business intelligence, workflow automation, machine learning, and other tools to achieve positive business impact. Brief: Includes a wide range of software technology components, like business intelligence, workflow engine, and more, to optimize business processes with maximum efficiency. ### RPA vs BPM: Automation Focus #### RPA – Manual Tasks Robotic Process Automation is task-oriented. RPA robots excel at automating manual, repetitive tasks and have some ability to handle contingencies. So, rule-based processes (such as approval routing) that do not require advanced decision-making are ideal for RPA technology. Brief: Minimizing manual, repetitive, and rule-based tasks that do not require complex decisions. #### BPM – End-to-End Process Automation Business Process Management is process-oriented. It is used - to plan end-to-end process automation - to chart a course that focuses on reengineering and optimizing complex processes, simplifying collaboration, improving decision-making, and achieving corporate productivity. Brief: Reorganizing process flows to remove bottlenecks, connect systems, and improve productivity across the enterprise. ### RPA vs BPM: Deployment Effort of integrations #### RPA – Low RPA features low effort, speed, and tact. RPA tools can be easily and quickly integrated to work with specific existing applications. They solve specific problems without completely overhauling your entire IT system or corporate culture. So, for instance, you can use RPA: - to create an automated user interface to provide answers to common customer questions through your web page user interface (improve customer experience) - to solve low-value repetitive tasks in your pre-pay purchasing system (P2P) - to free up your employees to work more productively and strategically (workflow management). Standalone RPA solutions are typically less expensive than complex BPM platforms, both in actual cost and in the costs associated with culture change. Brief: Runs non-disruptively within an organization’s existing processes and applications without requiring coding or extensive training. #### BPM – High BPM is a long-term process that requires a lot of effort. An effective BPM requires a big vision and a lot of patience. Its platforms are deeply transforming and, therefore, disruptive. In organizations using legacy systems, a successful digital transformation strategy may require - cultural shifts, - educational initiatives, - support from both management and staff. However, BPM is quickly becoming necessary for any company competing in the global marketplace. Brief: Long-term effort that may require specialized technical resources, depending on the complexity and depth of the process. ### RPA vs BPM: Business Impact #### RPA – Quick & Immediate Bots are gaining traction as they look promising in demo projects. As the use of bots increases, the benefits will multiply. RPA vs. BPM means that bots can be used quickly and independently, automating repetitive tasks and gaining tangible benefits. As bots get smarter, they can solve pinpoint problems (like machine learning) and fuel the already developing artificial intelligence (AI) frenzy. Over the past quite a long time, there have been no problems with managing and updating bots. It’s hard enough to ignore the tactical advantages that RPA provides and focus instead on the big picture, so the proliferation of bots will continue. Brief: Return can be implemented quickly and with minimal cost, but implementation may not always solve the problem of inefficiency in the main process. #### BPM – Significant & Transformational Processes provide insight into the workflow and balance of work. Of course, they cross-organizational and technological boundaries. The main challenges arise when implementing a workflow using multiple technologies and software stacks to solve problems that affect organizational roles and divisions. The starting time costs are more here, and it is not always possible to get the effect immediately. But although the impact of these efforts does not come directly. Without them, improving the client’s quality significantly will not be possible. Also, because the term BPM is no longer in vogue, it turns out that BPM is a long-term game. So, the benefits of business processes will not go anywhere, and the patient will wait. Brief: Significant gains can be made in productivity, agility, cost savings, efficiency, and regulatory compliance. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## BPM vs RPA: what are the differences Fig. 02 · RPA vs BPM Overview RPA vs business process management (BPM) | RPA | BPM | Technology | Software bots set up to do routine, repetitive tasks an employee would otherwise do | A wide range of software that optimizes business processes for efficiency and effectiveness | Focus | Removing manual, repetitive, rule-based tasks that need no complex decisions | Reorganizing processes to remove bottlenecks, connect systems and lift productivity company-wide | Deployment effort | Runs inside existing processes and apps without coding or long training | A long-term effort that may need specialist resources, depending on the process | Business impact | Quick returns at low cost, but may not fix the inefficiency in the core process | Large gains in productivity, agility, cost, efficiency and compliance | ### How is RPA used? There are many processes at a scale where, when automating, you can see the impact on the business in terms of: - savings, - efficiency, - mitigation of risk, - business results can be easily measured. However, the real value of RPA will be revealed when AI is added to these applications. Adding AI to RPA will free it from focusing exclusively on mundane tasks. AI will make up an increasingly large portion of the digital workforce, and, after all, RPA will account for a small fraction of the total spending of the AI ​​cabinet market. However, RPA is mainly used for routine work such as scanning records. ### How is BPM used? In contrast, BPM is used to automate end-to-end processes. This is done in different ways: - It defines and clarifies all administrative responsibilities associated with the process. - It describes people’s work, that is, their work processes. - Then it finds areas where these workflows can be optimized. There are aspects of standardization and documentation here, but BPM is also key to getting people to work together. Ultimately BPM is about mapping a process, tracking its performance, and looking for opportunities to improve it. ## BPM and RPA combined RPA is a tool that can expand and elevate BPM’s basic tasks. While RPA and BPM are different terms, they complement each other and, when deployed together, can contribute to digital transformation. So what is the complementary relationship between RPA and BPM? The ultimate goal of BPM is to improve processes, but by itself, it does not automate them (even if it brings the optimal result). On the other hand, RPA automates certain types of processes, but by itself, it cannot improve or optimize them. By automating an ineffective or faulty process, you are not fixing it — it will simply run faster and increase the repetition rate along with the failure. Fig. 03 · RPA + BPM Combined What you gain by combining BPM and RPA BPM + RPA - 01BPM shows which processes to optimize first - 02Together they link legacy and modern systems - 03BPM helps handle exceptions in RPA rules - 04People who are not developers can deploy and manage RPA ### BPM will help determine the preferred processes for automation The essence of BPM is to understand better and document the wide range of processes that make up the day-to-day activities of an organization. Business Process Management is about managing business processes usually hidden in people’s heads and guidelines, rules, laws, and worksheets. So, they inevitably accumulate in any business and tend to be poorly managed over the long term. Thus, BPM is an excellent foundation for an RPA program because success requires well-understood, well-documented processes and a mindset focused on continuous improvement. Remember – trying to automate processes that you don’t understand is going to be on a path to inherent failure. Also, BPM allows you to identify areas in the organization’s various processes, including the workforce, where automation would bring the most benefit and is the only optimization tool. RPA is a convenient and cost-effective way to automate gaps in areas where organizations have legacy platforms, web applications, or back-end systems that lack enterprise integration functionality. ### BPM and RPA will help link legacy and modern systems BPM links processes to underlying systems to ensure streamlined and efficient operations. Some experts believe that digital transformation can be seen as the heir to BPM. But that doesn’t mean that in pursuit of becoming a digital company, it will be able to get rid of legacy systems overnight or instantly find itself in an ideal environment. In a place where people always work together, automation comes with the wave of a magic wand. Yet, most organizations cannot boast of this. BPM continues to rely on complex and often legacy core systems that perform critical business functions that require human intervention to maintain them. RPA is key in integrating complex systems and automating repetitive and manual tasks. Especially when retrieving, transferring, and processing data, it can significantly save time, reduce errors and improve data quality. For example, banking and financial services companies have deployed robust mobile applications that enable customers to mobile escrow, transfer funds, or apply for mortgages from their smartphones. To do this, they needed to find a way to connect mainstream legacy systems with modern mobile applications. BPM can create digital connections between modern mobile applications and legacy IT systems, while rules-based RPA takes action to move data from one system and enter it into another. ### BPM can help with exception handling in RPA rules RPA operates according to the previously set rules – it does not know how to make exceptions or take “last resort” actions. When faced with them, the bot is practically out of order. RPA and BPM can be very effectively combined in scenarios where RPA relies on BPM to handle certain exceptions to perform automated actions. For example, when a bot encounters a missing document or information shortage while processing an HR process. Conversely, BPM can rely on RPA to automate time-consuming and manual tasks such as transferring employee data to various payroll systems as part of the HR process. The same can be said for other scenarios where BPM and RPA go hand in hand. RPA relies on BPM to handle exceptions that do not match a set of rules and require human intervention or decondensation. Because RPA is rule-driven, a changing environment or process can destroy the bot. So BPM can be a backup to handle all exceptions and keep it running. Business Process Management informs the company about existing exceptions and changes. Without knowing them, enterprises are putting RPA implementation at risk. Even a difference in the configuration of the user interface of a web application turns off a bot. ### RPA can be deployed and managed by people who are not developers BPM increasingly overlaps with IT, responding to organizations’ aspirations to acquire the expertise and skills needed to implement an automation strategy. RPA is a technology that allows you to do this without over-engaging IT professionals. This means the same people who work with BPM, such as business analysts or business units, can also deal with certain process automation. A collaborative approach to RPA is preferred, but this does not mean that CIOs will need to recruit or reallocate additional developers or other IT professionals to support automation. RPA bots can be customized by non-technical employees, which means less work for IT staff who are already overwhelmed by the fact that companies have moved their employees to remote work. These features make RPA ideal for organizations looking to deploy integration and automation solutions in response to change quickly. ### Future predictions about using RPA and BPM At the macro level, automation continues to drive down costs for organizations by allowing them to invest these financial resources in more strategic business areas. The technologies that govern automation are continually evolving, including RPA, workflow mechanisms, and interactions between systems. It helps to improve the BPM experience. In addition, these technologies are moving or expanding into the cloud, making the technology even more accessible to small businesses. ## Conclusion RPA is a living, working technology that is already in use. From the management side, RPA without BPM does not give a complete result. It is patchy automation of some operations. But the coexistence of BPM and RPA technologies has a cumulative effect. RPA automates anything that can be automated without integration, which is not a constant source of change. And BPM makes sense to delegate interactions between people, especially actions that require value judgments. In addition, BPM can integrate with third-party systems. Thus, it is too early to talk about replacing BPM with robotic systems, and the separate use of RPA will not fully improve business processes. BPM vs. RPA leads to the symbiosis that significantly increases the efficiency of performing tasks through automation. In addition, the integrated solution contributes to the overall reduction in operating costs and improves the company’s operations. Want to find the right solution for your business? [Get in touch with us!](https://www.flobotics.io/contact) #### Like the article? Spread the word Written byFilip Nasiadko CEO and Co-founder at Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPAAI ### Agentic AI vs RPA: The Next Frontier of Intelligent Automation Agentic AI vs. RPA: how autonomous agents and traditional bots differ, where each fits, and why a hybrid approach is the 2026 strategy for CTOs. Bart TeodorczukJuly 14, 2025 ](https://www.flobotics.io/blog/agentic-ai-vs-rpa)[ RPAAI ### Agentic AI vs Generative AI: The Next Frontier of Intelligent Automation Generative AI vs. Agentic AI, explained: from ChatGPT's 100 million users in two months to the rise of autonomous automation in 2026. Jędrzej SzymulaSeptember 08, 2025 ](https://www.flobotics.io/blog/agentic-ai-vs-generative-ai)[ RPA ### Process Mining vs RPA: How They Work Together to Improve The Efficiency of Your Business Process mining and RPA: how combining the two turns automation candidates into measurable efficiency gains for your business. Bart TeodorczukJanuary 30, 2023 ](https://www.flobotics.io/blog/process-mining-automation) [All articles →](https://www.flobotics.io/blog) --- # RPA in Supply Chain Management: Pros, Cons and The Best Use Examples Canonical: https://www.flobotics.io/blog/rpa-in-supply-chain-management-use-examples Author: Michał Rejman Published: 2021-05-07 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/RPA in Supply Chain Management: Pros, Cons and The Best… [RPA](https://www.flobotics.io/blog?category=rpa) # RPA in Supply Chain Management: Pros, Cons and The Best Use Examples [Michał RejmanChief Marketing Officer at Flobotics](https://www.flobotics.io/our-editorial-team#rejman) Published May 07, 2021Updated September 1, 2026 On this page - [What is RPA?](#what-is-rpa) - [The main processes in supply chain management](#the-main-processes-in-supply-chain-management) - [Demand forecasting](#demand-forecasting) - [Lack of supplier diversification](#lack-of-supplier-diversification) - [Logistics and delivery](#logistics-and-delivery) - [Obsolete interaction formats and manual data processing](#obsolete-interaction-formats-and-manual-data-processing) - [Robotic Process Automation in supply chain management](#robotic-process-automation-in-supply-chain-management) - [#2 – Planning supply and demand](#2-planning-supply-and-demand) - [#3 – Supplier selection and procurement](#3-supplier-selection-and-procurement) - [#4 – Order processing and payments](#4-order-processing-and-payments) - [#5 – Message about the status of sending](#5-message-about-the-status-of-sending) - [#6 – Robotization of document processing](#6-robotization-of-document-processing) - [Takeaway](#takeaway) - [What technologies can be used in supply chain management](#what-technologies-can-be-used-in-supply-chain-management) - [IoT, 5G, and big data](#iot-5g-and-big-data) - [Cloud Automation](#cloud-automation) - [Working with AI](#working-with-ai) - [Pros and cons of implementing RPA to supply chain management](#pros-and-cons-of-implementing-rpa-to-supply-chain-management) - [RPA supply chain management cons](#rpa-supply-chain-management-cons) - [RPA supply chain use cases](#rpa-supply-chain-use-cases) - [Automation of data entry](#automation-of-data-entry) - [Predictive/preventive maintenance](#predictive-preventive-maintenance) - [Logistics management](#logistics-management) - [After-sales service](#after-sales-service) - [Creating purchase orders](#creating-purchase-orders) - [RPA supply chain management future](#rpa-supply-chain-management-future) - [Conclusion](#conclusion) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Transport companies use modern technologies such as artificial intelligence, the Internet of Things (IoT), and 5G to optimize the supply chain. Despite some anxieties about using AI in warehouses, plants and the fact that autonomous means pose a risk to truck drivers, technology creates several prospects and opportunities for supply chain companies. If we think about economic processes, modern technologies, including robotic machines, will not be ready to completely replace human labor in the industry, but they will significantly simplify it. According to the [McKinsey consulting company](https://www.mckinsey.com/~/media/mckinsey/featured%20insights/Digital%20Disruption/Harnessing%20automation%20for%20a%20future%20that%20works/MGI-A-future-that-works-Executive-summary.ashx), leading manufacturers of warehouse automation equipment have increased their annual revenues by 15-20% since 2014. Analysts believe that companies will choose interesting solutions and integrate them into their projects using a robotic process automation (RPA) system in the short and longer term. ## What is RPA? Today, many people at work do predominantly automatic chores that do not require much mental effort but take a lot of time. Fig. 01 · RPA What it is What is robotic process automation? Manual work that takes timeDone in seconds by software robots - Filling out forms and questionnairesForms filled automatically - Complex calculationsCalculated without errors - Data reconciliationRecords matched automatically - Updating the same data in several systemsUpdated everywhere at once - Difficult, error-prone tasksDone the same way every time For example, I was filling out forms, questionnaires, data reconciliation, updating the same data in different systems, complex calculations, manual tasks associated with a high risk of making a mistake, and much more. A program is a new step in the automation of business processes, including the global supply chain and logistics industry – Robotic Process Automation (RPA). [Robotic Process Automation (RPA)](https://www.flobotics.io/blog/robotic-process-automation) uses artificial intelligence (AI) software with machine learning capabilities to handle repetitive, high-volume tasks that humans previously performed. This technology will allow replacing people with robots, with the subsequent redistribution of human resources to perform more complex tasks. ## The main processes in supply chain management The supply chain consists of four main functions: supplier, manufacturer, distributor, and consumer. Within the supply chain, value is created that the consumer perceives. For society or the economy as a whole, the goal is to maximize the meaning of the value created without spending too many resources on it. Each participant must effectively perform their function to create maximum customer value within the chain. Also, all participants in the chain must communicate effectively with each other. However, the coronavirus pandemic in 2020 has seriously changed supply chain processes. The business faced a new reality: on the one hand, there was a sharp increase in online commerce and delivery, consumer patterns changed, and on the other hand, stable logistic ties between contractors were disrupted. Many companies were painfully aware of the consequences of the cash gap and saw the complexity of manual data processing due to the low level of automation. The pandemic highlighted several key challenges faced by companies: - forecasting demand, - lack of diversification of suppliers, - increased burden on logistics, - outdated formats of interaction with counterparties, - manual data processing. Let’s look at it in order. ### Demand forecasting Manufacturers, distributors, and retailers were not ready for a sharp increase in demand for some categories of goods and a drop in demand for others – supply chains and sales plans were formed without considering the pandemic. This simultaneously led to supply disruptions, unclaimed stocks, and the need to rebuild logistics processes. Predicting demand in such conditions proved to be difficult. ### Lack of supplier diversification Supply chains have not had time to adapt to change. Companies whose supply strategy depended on direct suppliers were forced to reallocate resources. Apple became such an example, being dependent on supplies from Chinese manufacturers. ### Logistics and delivery The growth in demand for certain product groups has increased the burden on logistics. Companies faced the need to reallocate resources and look for additional carriers. The market for online delivery has shown problems with route optimization and long delivery times. For example, retailers noted how, due to missing items, the order collection time increased by 1.5-2 times, and the delivery time also increased. ### Obsolete interaction formats and manual data processing The pre-crisis methods of working with counterparties have shown their ineffectiveness in conditions of isolation. Information systems could provide transparent processes between employees and contractors. Still, the low level of procurement automation does not allow companies to analyze consumer demand and the availability of goods and predict further actions. [DHL experts](https://theloadstar.com/the-next-big-challenge-for-logistics-will-be-future-proofing-the-workforce/) have analyzed the challenges faced by various industries and see the following picture for the near future: - Logistics professionals will be driven by the sustainability of supply, not cost. Keeping the chains intact will be critical. - Consumer behavior changes will require adapting traffic flows and warehouse networks to new realities. Robotization will affect those processes in cargo transportation that have not previously been reached. - The need for effective management of the life cycle of contracts with suppliers will create the need for robotization and automation in this area. - Information systems will have to support the option of remote work of employees with documents and data. Leaders in the supply chain rankings, according to [Gartner](https://www.gartner.com/en/newsroom/press-releases/2020-05-20-gartner-announces-rankings-of-the-2020-supply-chain-top-25), are among the first to adopt RPA supply chain management technologies, and some of them continue to develop supply chains even in difficult economic conditions because they see it as an opportunity for planning and flexible response in real-time to overcome fluctuations in demand. ## Robotic Process Automation in supply chain management Fig. 02 · Supply chain 6 uses RPA in supply chain management - 01Email automation - 02Supply and demand planning - 03Supplier selection and procurement - 04Order processing and payments - 05Shipping status messages - 06Document processing #1 – Email Automation Maintaining a meaningful relationship between customers, suppliers, shipping agencies, and manufacturers is critical for any supply chain. The organization always has open communication during urgent situations, such as delays in delivery or difficulties in fulfilling an order, to build trust and credibility. At the moment, most of this task is done manually. But with RPA supply chain management, companies can easily automate this entire communication process. RPA also helps automate email responses when an order has been requested, shipped, halfway completed, delayed, or received. This ensures that everyone in the supply chain can receive real-time notifications. Also, bots can read emails, recognize the meaning of the content, and perform the necessary actions. This not only frees up human resources but also eliminates human error. ### #2 – Planning supply and demand Before the advent of RPA, supply and demand planning was not a cakewalk for any organization. Employees must gather the information they need from various sources, such as suppliers, customers, market information, and sales, and then present that data in a standardized format. With RPA technology, organizations can automate supply and demand planning. It also helps collect and format the information you need from various sources, analyze data exceptions, perform data cleansing, and convert data to a plan. Once automated, the human role is limited to handling robot exceptions, running simulations, and holding supply and demand meetings to reach a consensus on a plan. ### #3 – Supplier selection and procurement Organizations must follow a laborious manual process when selecting and purchasing suppliers. This included preparing an RFQ (Request for Quotation), communicating with suppliers, performing a preliminary review of supplier documents, evaluating a supplier’s credit check, and completing supplier selection. By implementing RPA for the supply chain, a company can automate sourcing and procurement processes. Human intervention is restricted to the initial phase of work, such as defining a project, creating lists of potential suppliers, and participating in site visits and negotiations. Once automated, supply chain enterprises can reduce cycle times by 25-50% and processing times by 15-45%. ### #4 – Order processing and payments Order processing in any business consists of three stages, which include: - Selecting a specific product/service, - Initiating a payment, - Confirming an order. In this era of automation, businesses still prefer paperwork to process these transactions, but this leads to erroneous and wasted time. With RPA, order processing, and payments can be automated. This is performed so that the transaction data can be directly updated in the company database, payment gateways can handle the amount withholding, and the software solution can send a confirmation notification to the user. ### #5 – Message about the status of sending Logistics service centers regularly receive thousands of customer inquiries about the parcel’s status with their order. The manual process goes like this: - A customer service representative has to open every email, - Open the ERP system to find the shipment record, - Then record the shipment, - Finally, they send customers updated shipping status information. However, once RPA is implemented, the entire process can be automated, from opening emails, processing customer requests, logging into the ERP system, and communicating the exact delivery status to the customer. ### #6 – Robotization of document processing While industry leaders are adopting RPA, companies have not switched from paper to electronic workflow, leading to long-order processing, a lack of transparency in the supply chain, and suboptimal decision-making. The robotization of document processing removes the routine from a person and allows you to establish transparent communication with counterparties. This can be reconciliations, creating invoices, and collecting statistics on inventory balances and sales. As a result, automation: - Reduces personnel costs and labor costs - Provides unattended shipments - Reduces logistics errors and optimizes the supply chain - It allows you to manage your warehouse and predict loads efficiently. ### Takeaway First, these are back office and supply chain operations—automation of order processing and payments. Order processing is accompanied by transactions such as manually entering customer information into the company database, processing payments, issuing confirmations by email, and order updates. Many companies still rely on manual labor and paperwork to complete these steps. It can be used for purchasing, automating order and payment processing, controlling inventory levels, and tracking deliveries. Inventory management is the core of the logistics supply chain. Manufacturers and suppliers must keep track of inventory levels to ensure they have enough products to meet customer needs. Benefits of RPA in the supply chain: - RPA reduces the need for manual work, which gives time to interact with customers in the front office. - RPA automates communication by automatically sending an email when an order is processed, agreed upon, or delayed otherwise. - Software robots monitor inventory levels and provide real-time reports to determine optimal inventory requirements based on past and future trends. Between 2017 and 2022, the global RPA market could grow by 30.14% annually. Robotic Process Automation makes it possible to transform the supply chain and disrupt the way goods are produced, sold, bought, and consumed. RPA is a great opportunity to improve efficiency and reduce costs in the huge logistics industry and supply chain. Learn more about using Robotic Process Automation in other industries, like RPA in insurance or RPA in logistics. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## What technologies can be used in supply chain management In a recent report by [Deloitte](https://www2.deloitte.com/content/dam/Deloitte/at/Documents/technology/at-technology-robots-are-ready.pdf), RPA technology was identified as the best solution for delivering high enterprise productivity at every stage of the supply chain, as well as one of the ways to implement Industry 4.0 technologies throughout the company’s entire life cycle. ### IoT, 5G, and big data With the appearance of 5G and the increasing availability of the Internet of Things, companies have begun collecting data about their goods at every stage of the supply chain. If this info is not organized and sorted for different types of AI platforms in real-time, it will be useless for the company. RPA assists in data flow management in the logistics industry and ensures no human failure in processing data collected by IoT sensors. ### Cloud Automation Data collected through IoT + 5G and sorted through RPA is processed at the edge or sent to the cloud. It is recommended to store information in the cloud to identify the types of data, especially those that can help the company to manage. But often, a problem arises: the platform that collects and stores data cannot integrate with the chosen cloud service. In this situation, the integration is done at the expense of RPA. Using RPA, logistics professionals can connect cloud services to on-premises data platforms and collect and analyze information. ### Working with AI With 5G and the IoT that facilitate data collection and storage, companies are leveraging AI to organize information and deliver it to customers in a usable way. Companies use RPA to build chatbots that answer customer questions about a product, delivery schedule, and more. In this case, RPA is an intelligent intermediary and link between various platforms and modern technologies. ## Pros and cons of implementing RPA to supply chain management Fig. 03 · Supply chain Pros and cons Pros and cons of RPA in supply chain management Pros - Robots make no mistakes and work 24/7 - Robots keep a full record of their actions - Operations follow rules and standards - Hours of manual work done in seconds - Employees freed from dull, repetitive work Cons - Fear of losing jobs - Concern that money goes to technology, not people RPA supply chain management pros - Robots do not need to rest. They will do their job 24 hours a day; - Robots are not wrong. Once correctly configured, the robot will perform its tasks without errors that can periodically occur in humans; - When the scope of work changes and new tasks appear, it is enough for the robot to change the rules of the workflow (modify the script), and employees in this situation must additionally learn; - Robots keep a 100% record of their actions, which can be retrieved if necessary; - Depending on the type of robotic process, one robot replaces 3 to 8 people in performance; - The robot is very compact because it does not take up space; - Ensuring prompt customer service; - Ensuring business operations and processes are following rules and standards; - Speeds up the execution of automatic processes; - Ensuring increased efficiency by digitizing and auditing process data; - Providing freed employees to solve more interesting problems. ### RPA supply chain management cons One of the drawbacks is the impact of robotization on company workers. This is the fear of losing your job and the bewilderment that funds are invested in technology, not employees. However, the practical experience gained over the years and the current socio-economic environment has shown that overcoming the vigilance that arises with RPA is much easier than one might think. The reasons for this are the impending shortage in the labor market and the overload of employees with routine operations. ## RPA supply chain use cases “In most cases, RPA is used in conjunction with other digital levers such as the Internet of Things, intelligent document processing, chatbots, mobile apps, and even blockchain to reimagine workflows to eliminate bottlenecks and other serious business challenges,” said Shirley Hung, vice president of the Everest Group, a Dallas-based consulting and research firm. Companies incorporate RPA into their logistics and supply chain workflows in five ways. The reasons for this are the impending shortage in the labor market and the overload of employees with routine operations. ### Automation of data entry Lack of integration is a crucial issue for almost every shipping business, and RPA software can help close some of these gaps. Take the external logistics provider AM Transport, for example. According to Jason Doris, CTO of AM Transport, the company has built two infrastructures: - one based on Boomi, a division of Dell Technologies, to connect EDI integration between its customers, - and one back-end application infrastructure on Salesforce, Google, and AWS. He said the direct API integration can handle many workflows, but some gaps require manual data entry on an ongoing basis. Doris’s team implemented an RPA service called Boomi Flow to eliminate repetitive data entry and EDI tasks and extend the workflow to other “reas. “If one chain of events happens, we can automatically contact customers, notify accounting and provide [bills],” Doris said. “I used to have to do all these tasks separately and manually.“ ### Predictive/preventive maintenance Equipment maintenance is an important aspect of supply chain management and RPA – working with other technologies – can help by facilitating preventive maintenance efforts. For instance, IoT-based preventative maintenance can detect corrosion and damage to pipelines in an oil and gas plant. These IoT apps then use sensors installed in the channel to obtain data on hydrogen potential and gaseous composition. Apps pull sensor data in real time and transfer it to the cloud for assessment, analysis, and prediction. RPA bots act on this information automating the service scheduling process, notifying affected customers, and updating financial plans. This eliminates delays typically associated with manual labor, shortens response times, reduces employee effort, and improves operational efficiency. ### Logistics management RPA can improve the efficiency of the delivery phase in the supply chain. RPA bots track orders and updates order transfer details across all relevant systems in these cases. They can also work in connection with AI-based intelligent routing systems that coordinate the activities of multiple logistics partners, such as road transport, cargo ships, and air transport. Bots can automatically assign a shipping partner based on the location of the goods. RPA bots can also generate notifications for customers in case of a delay improving customer experience through practice and real-time order updates. Essentially, this technology improves error handling. RPA is especially useful in managing cross-border traffic, which may require various additional customs, storage, and inspection processes to coordinate. ### After-sales service What happens after the sale is becoming increasingly important, and RPA can work with several other technologies to improve this aspect of supply chain management. For example, when a customer submits a service request using a mobile app, an intelligent virtual assistant or chatbot can interact with the customer and then post the requests to the system. Smart document processing apps can read data from various service request document formats and then coordinate with RPA robots to collect and process service ticket data. If a customer needs to return an item, a mobile app for third-party service and reverse logistics partners can improve the visibility of location, arrival time, and turnaround time in the event of a repair. RPA bots can follow orders in real-time and automatically send confirmation emails to customers. Digitally-assisted processes reduce employee effort and time spent on internal processes, freeing time to interact with dissatisfied customers. ### Creating purchase orders An organization’s supply chain departments can use an RPA bot to check inventory levels and initiate a purchase order when the supply falls below a specified threshold. Most firms have a purchase order template or online ordering process customized by their suppliers, and the structured nature of the purchase order information lends itself to automation. “By automating the process with RPA, the team can ensure consistency and reduce the likelihood of delays or failures in the process,” said Kapil Kalohe, senior director of business consulting services at Saggezza, a global IT consulting company based in Chicago. Maintaining an efficient supply chain process reduces the risk of lost sales due to material or inventory shortages, ensuring that organizations can manage optimal inventory levels. Companies need to be able to control their supply during peak and trough times. Manufacturing enterprises generate reports on the level of stocks of raw materials, work in progress, and finished goods. IT pros can set up an RPA bot to sync with a company’s CRM system. Based on the data in the report, the RPA bot can contact the relevant supplier via email or through the ordering portal to place an order. The purchasing manager must only track the notifications and approve the request. This process can occur hundreds of times a day in multi-vendor and high-volume production organizations. “There will be significant time savings by enabling RPA,” Kalohe said. However, using RPA does not mean that human oversight is unnecessary. He said creating an additional approval process for an abnormal activity is also essential to avoid too many orders or misinterpreting rare cases. Find out additional [40 Real World Use Cases of Robotic Process Automation Across Industries.](https://www.flobotics.io/blog/rpa-use-cases-across-industries) ## RPA supply chain management future Many trade and manufacturing companies use the RPA system for logistic purposes, namely in warehouses. Companies like Amazon, Ocado, Alibaba, and others actively use robotics in their distribution centers. RPA, generally speaking, acquires a physical shell and clearly shows its purpose in the actions of a robot, which will perform the same automatic work as in the form of a graphical interface. Business processes in the global logistics and supply chain industry rely heavily on back-office operations, such as updating customer information on web portals with current load status and ETA (Estimated Arrival time), scheduling delivery, or picking up a trailer. Robotic Process Automation (RPA) makes core business processes less tedious and repetitive. This ensures operation and operational efficiency, thereby improving economies of scale. Transport and logistics companies are increasingly under pressure from service companies and freight forwarders demanding higher service prices. Therefore, the only way for these companies to increase profits is to automate existing processes. Unlike expensive and resource-intensive implementations of IT systems, the implementation of RPA pays off in 6-9 months, depending on the volume of operations performed by “virtual robots.” RPA improves the efficiency of supply chains by: - Excluding manual data entry from internal systems to corporate portals; - Collection of structured and unstructured data from various sources and subsequent processing; - Increasing employee satisfaction with their work, free from repetitive operations of the same type. Promotes professional growth and leads to a decrease in staff turnover; - Using software robots to read emails. Robotic process automation contributes to analytics and artificial intelligence by gathering information about business models and internal workings to identify potential disruptions and weaknesses. These ideas can be used to improve and optimize all areas of logistics. The RPA is like an outsourcing company in the field of boring, routine, but obligatory activities. You only need to pay for the installation; the program will work for you. The reach of RPA is so wide that scenes from movies about the uprising of machines may inevitably come to mind. Still, in this situation for AI, the limit of possibilities is to facilitate and reduce the amount of work. What sets RPA apart from traditional IT automation is the ability of RPA software to take into account and adapt to changing circumstances, exceptions, and new situations. This will allow avoid arising errors in calculations in transport, warehouse, and other areas of logistics. The freed staff will be able to concentrate on more serious tasks, which will undoubtedly lead to discoveries and progress in the field of supply chain management. Soon, we should expect the transition of large and medium-sized supply chain management companies from pilot implementations to full-scale projects designed to transfer routine operations to the conduct of hardware robots. ## Conclusion By transforming supply chain processes, we improve efficiency and meet customer expectations. In this matter, one-size-fits-all is no model for digital technology. Organizations need an IT partner who can tailor RPA implementation services to their needs based on the current state of affairs and ultimate goals. Compared to traditional automation, robotic process automation replaces not only the workforce but also changes everything on which the organization was founded. New challenges can arise in the service delivery process, and entire operations can be reworked to improve productivity and efficiency at the end of the day. #### Like the article? Spread the word At Flobotics we specialize in Agentic AI automation – no generic bots here. Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byMichał Rejman Chief Marketing Officer at Flobotics. [More from Michał](https://www.flobotics.io/our-editorial-team#rejman) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### RPA Reloaded: 50+ Robotic Process Automation Statistics to Know in 2026 RPA statistics 2026: 50+ data points on robotic process automation adoption, ROI, and where the technology is headed next. Yana PokoraApril 15, 2025 ](https://www.flobotics.io/blog/rpa-statistics)[ RPA ### What Is RPA? | Robotic Process Automation Robotic Process Automation (RPA), explained: how software bots run a 24/7 digital workforce that cuts costs and human error. Bart TeodorczukSeptember 01, 2025 ](https://www.flobotics.io/blog/robotic-process-automation)[ RPAEligibility ### Top RPA Use Cases in the Insurance Industry RPA use cases in insurance: see how robotic process automation streamlines claims, underwriting, and other core workflows. Yana PokoraAugust 10, 2021 ](https://www.flobotics.io/blog/rpa-in-insurance-use-cases) [All articles →](https://www.flobotics.io/blog) --- # How Is Robotic Process Automation Changing HR and Recruitment? Canonical: https://www.flobotics.io/blog/rpa-in-hr-and-recruitment Author: Michał Rejman Published: 2021-01-20 Updated: 2026-09-03 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/How Is Robotic Process Automation Changing HR and… [RPA](https://www.flobotics.io/blog?category=rpa) # How Is Robotic Process Automation Changing HR and Recruitment? [Michał RejmanChief Marketing Officer at Flobotics](https://www.flobotics.io/our-editorial-team#rejman) Published January 20, 2021Updated September 3, 2026 On this page - [What is RPA?](#what-is-rpa) - [Biggest Challenges HR and Recruitment Face?](#biggest-challenges-hr-and-recruitment-face) - [1. Inability to organize a sufficient flow of applicants](#1-inability-to-organize-a-sufficient-flow-of-applicants) - [2. The work of a recruiter is not automated](#2-the-work-of-a-recruiter-is-not-automated) - [3. Statistics on selection are not collected or analyzed](#3-statistics-on-selection-are-not-collected-or-analyzed) - [4. Recruitment of competing companies is not analyzed](#4-recruitment-of-competing-companies-is-not-analyzed) - [5. Poorly organized work of the HR department as a whole](#5-poorly-organized-work-of-the-hr-department-as-a-whole) - [What processes Can Be Automated With Robotic Process Automation in HR and recruitment?](#what-processes-can-be-automated-with-robotic-process-automation-in-hr-and-recruitment) - [Trouble-free assistants](#trouble-free-assistants) - [Ability to entrust more processes](#ability-to-entrust-more-processes) - [Benefits of Robotic Process Automation in HR and recruitment](#benefits-of-robotic-process-automation-in-hr-and-recruitment) - [Precision and increased productivity](#precision-and-increased-productivity) - [Consistency](#consistency) - [Scalability](#scalability) - [Reliability](#reliability) - [Flexibility](#flexibility) - [Real-World Use Cases of RPA Implementation in HR](#real-world-use-cases-of-rpa-implementation-in-hr) - [Process # 1: Recruiting](#process-1-recruiting) - [Process # 2: Changing the staffing table](#process-2-changing-the-staffing-table) - [Process # 3: Controlling the timing of vacations](#process-3-controlling-the-timing-of-vacations) - [Process #4: Simplified adaptation](#process-4-simplified-adaptation) - [Process #5: Employee data management](#process-5-employee-data-management) - [Process #6: Cost management](#process-6-cost-management) - [Process #7: Employee introduction and training](#process-7-employee-introduction-and-training) - [Companies Using RPA in HR](#companies-using-rpa-in-hr) - [RPA Implementation Case Study #1: SAP’s Economies of Scale](#rpa-implementation-case-study-1-saps-economies-of-scale) - [RPA Implementation Case Study #2: Unilever’s Introduction of RPA in HR](#rpa-implementation-case-study-2-unilevers-introduction-of-rpa-in-hr) - [Summary](#summary) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Robotic Process Automation in HR and recruitment is an urgent business need. Digital tools “take over” routine processes, freeing HR managers’ resources to solve strategic problems—for example, a cool chatbot recruiter tool. Recruiters receive many emails and calls containing similar questions related to job descriptions, key requirements, corporate policies, and salaries. It takes a long time to respond to each candidate or redirect them to the FAQ page on the company’s website. Intrigued? Read on! ## What is RPA? Robotic Process Automation (RPA) is a rapidly developing innovative technology in the automation field. RPA is one of the most powerful business process optimization tools today. This groundbreaking technology fundamentally changes the business operating model, replacing people performing routine tasks with robots. A recently published [Ernst and Young (EY) study](https://www.uipath.com/blog/rpa/why-rpa-deployments-fail) indicated that 30 to 50 percent of new RPA implementation initiatives encountered problems. But the first temporary difficulties give companies invaluable experience in finding the best path in the digital world in a competitive environment where standing still is inevitable to lose. Today the world is concerned about how to develop the economy further. How to get back to sustainable growth? There are two trends on the surface: the first is robotization, and the second is environmental friendliness. The first benefits business, especially at low rates, but not always beneficial to the state. ## Biggest Challenges HR and Recruitment Face? All companies are engaged in selecting personnel—even those with no HR policy, and managers are involved in HRM without regaining consciousness. But everyone has recruitment – from startups and flower stalls to giant companies. They all need people: some of them constantly, some of them occasionally. Most HRs started their careers with recruiting, and many executives conduct interviews from time to time. Therefore, this work does not seem difficult for anyone. But the paradox is that many companies cope very badly with the selection. And even if they more or less manage to do it, they still complain of serious difficulties. When recruiting from year to year, it’s easy to overlook your own mistakes: it’s always easier to refer to demographics, industry specifics, high expectations of job seekers, and so on. But if everything has reached a standstill, there is nowhere to go – you need to change something. Then a look from the outside is useful, and we will gladly share our observations with you. ### 1. Inability to organize a sufficient flow of applicants The recruiter works with the same candidate stream sources and does not restructure their work for different vacancies. This is partly a continuation of the previous problem. What is the problem? Recruiters often follow the stereotype: if suitable candidates came from this site yesterday, they would also come this time. You need to wait. However, time is wasted while they wait, and vacancies are empty. ### 2. The work of a recruiter is not automated At all stages of the selection, the recruiter does everything manually without using auxiliary software. Thus, why not turn to HR process automation? What is the problem? There are many routine and time-consuming processes in recruiting. According to the recruiters themselves, they do it “automatically.” So isn’t it easier to entrust the work to a special robot than to turn a person into it? Many manual workloads a recruiter so tightly that they do not have time for active and proactive recruiting (these problems have already been written about above). Simply put, a recruiter has no time to think about how to do better and what to change. They have no time to master new technologies. At the same time, recruiting becomes more difficult and requires new approaches, and the requirements for an HR manager are increasing. And this only exacerbates the problem. ### 3. Statistics on selection are not collected or analyzed Or it is assembled but not used in practice. What is the problem? Typically, HR departments are limited to the minimum statistics needed to report back to management. But the recruiters themselves are either not interested in delving into statistics, or they have no time. However, recruiting provides a ton of data for analysis. If you learn to work with them, then recruiting can be greatly improved. ### 4. Recruitment of competing companies is not analyzed Competitors can be both companies from your main market segment and completely different industries if your interests overlap in the labor market. For example, sales managers are often ready to be hired from related industries, so companies from different markets can compete for the same candidate. What is the problem? By not analyzing the recruiting of competitors, you are missing out on many useful things. Often the actions of other companies will more clearly indicate your mistakes and suggest great ideas. ### 5. Poorly organized work of the HR department as a whole For example, the department was formed spontaneously, and its place in the company’s structure is unclear. Interaction with other units is not regulated. There are no clear rules for interaction. What is the problem? All defects in the HR department affect recruitment, as well. If there is no clear interaction scheme within the department and with other company divisions, this slows down the selection. For example, candidates sometimes go tHRough all the interview stages in a couple of days or have to visit the company for weeks. As a result, most nimble and promising ones manage to find another job. ## What processes Can Be Automated With Robotic Process Automation in HR and recruitment? Fig. 01 · HR 10 use cases RPA use cases in HR HR department - 01Exit management - 02Time and attendance - 03Introduction and training - 04Survey and review analysis - 05Employee data management - 06CV screening and shortlisting - 07Offer letters - 08New hire setup and onboarding - 09Travel and expenses - 10Monthly payroll Overall, the human resources department in any organization plays a critical role in supporting employees and improving the whole work environment so that employees can do their jobs effectively. But given, the sheer volume of data management — filling out forms, updating and validating records, and the continuous flow of request processing — forces HR managers to perform repetitive administrative tasks. By implementing Robotic Process Automation in HR and recruiting, organizations can dramatically reduce day-to-day processes by automating the most repetitive tasks and allowing HR managers to focus on other productive and more strategic tasks critical to the company’s growth. The main focus of RPA in HR operations is primarily micro-tasks, thus integrating all the processes that large legacy systems could not or could not solve. RPA has tremendous potential to revolutionize the HR industry through greater efficiency and faster return on investment. RPA can run in the background without requiring human attention as a completely non-invasive technology. Read how RPA can be implemented with our top battle-proven Uipath developers. So what RPA in HR can bring to your company? ### Trouble-free assistants The use of software robots is justified in situations where manual data processing operations in a business process are massive. It can be easily algorithmized, take less time to complete, and is characterized by few exceptions. An extensive field for robotization is opening up precisely in the area of HR, where you constantly have to deal with many repetitive processes (regular communication, processing standard requests and responses, generating certificates and documents, searching for information about candidates on external resources with subsequent entry into accounting systems, etc. ). Traditional approaches are either ineffective or too expensive in this case. Familiar macros help increase productivity only when using separate (at best, several “related”) applications. At the junction of various systems, integration can be limited by the lack of open APIs and unreasonably high development costs. In turn, modern Robotic Process Automation in HR platforms makes it possible to quickly and inexpensively solve the issue: to form a set of “skills” for bots, promptly create them in a virtual studio, and test and put them into operation. From this moment, within its “powers,” each software robot will quickly and independently reproduce actions that previously consumed much human energy and time. ### Ability to entrust more processes What processes can you entrust to recruiting automation bots? Here is an incomplete list of possible uses of RPA in HR processes: - Automatic creation of a new employee profile. When hiring a new employee, it is necessary to form their “digital twin” (personal accounts in corporate systems) using data from the HR system and text documents; - Vacation management. When forming a vacation schedule, you can automatically collect employee expectations, check them for compliance with the requirements of legislation and corporate policies, and provide feedback in case of non-compliance. A well-designed bot will not forget to check for claims and re-request them from those who have forgotten about the right to rest; - Absence management. In response to a preliminary notification or upon a signal from the workplace attendance system, the software HR automation robot can automatically send an employee a request to provide the relevant documents, control their receipt and accept them in the HR system; - Preparation of expense reports. When generating an essay on travel expenses, the bot can undertake the technical collection of documents and receipts from the folder, enter them into the accounting system and monitor compliance with corporate policies using various sources (for example, obtain currency rates from the Central Bank website); - Verification of data on new employees. Following the pre-configured checklist, the software robot can request documents from previous employers that characterize a new employee and accumulate them in the required place (on a network drive, in attachments to a profile, etc.); - Monitoring the performance of goals. Suitable work for a bot that, at a given frequency, will request reports from employees on the status of achieving goals, update the summary report, and save the history of correspondence; - VHI management. A software robot can easily cope with such a task as sending formalized letters to employees about the need to choose a program for the subsequent formation of applications for attachment to insurance companies; - Collection of documents on professional development. After the employee completes training outside the walls of the company, the bot can send a request to the educational organization, control the receipt of the necessary documents (certificates, score sheets, invoices, and acts), and save them; - Provide information. In response to an employee’s request for a standard certificate (“from the place of work”), the bot will generate the necessary documents in the HR system and send them to the employee. ## Benefits of Robotic Process Automation in HR and recruitment Robots have already become an HR sensation, especially in the recruiting space. Using such technology as RPA in HR is justified by increasing operational productivity and minimizing risks. At the same time, the key advantages of software robots are as follows: - Robots work 24 hours a day, 7 days a week. - Robots work faster, don’t get tired, and don’t make mistakes. - Robots don’t get sick, don’t come late, and don’t go on vacation. Due to the huge number of repetitive administrative tasks, often performed manually (filling out forms, receiving and processing data, updating and sending many requests and notifications), the HR service is one of the most promising for using and implementing software robots in a company. Let’s see the additional benefits of this implementation! ### Precision and increased productivity RPA uses pre-coding technology to minimize errors. In addition, by allowing employees to focus on more important tasks, technology directly contributes to achieving overall strategic goals and company productivity. ### Consistency By using RPA in the background, HR departments can count on tasks to be completed consistently without any problem. RPA is built for perfect replication and error-free performance, eliminating any variation in output over the product’s life. ### Scalability The cost per task or effort per RPA is significantly lower when working on a large scale and can be easily increased or decreased as required. This results in minimal loss of effort or downtime for the entire system. ### Reliability Without human intervention and any leaves, the efficiency increases dramatically as the bots work 24/7 with constant performance. ### Flexibility RPA solutions are extremely flexible and can follow programmed procedures regardless of the deployment environment. Fig. 02 · HR Onboarding How a bot onboards a new employee HR starts the process; the bot does the rest and the new employee gets everything they need. - 01Create email account - 02Add to mailing list - 03Generate phone extension - 04Update lists - 05Request access card - 06Create accounts - 07Send info and login codes Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## Real-World Use Cases of RPA Implementation in HR ### Process # 1: Recruiting Task: Search for candidates, their analysis, processing, and transfer to the system Decision: The HR specialist fills in a criteria matrix to find targeted candidates. The robot checks the information update in the file and searches for candidates according to the specified criteria. The robot transfers the most suitable vacancies to the information system. Upon completion, the robot sends a notification to the HR specialist about the readiness of the work done. Result: - Reduction of manual labor by up to 80%. - Increasing the speed of the business process. ### Process # 2: Changing the staffing table Task: Keeping accounting and management reports Decision: The robot uploads accounting reports from the accounting system and updates employees’ staffing tables by sending targeted messages to HR curators. Having received the staffing table from the curators, the robot generates analytics on personnel and service notes’ movement for the departments within which staff changes have occurred. The robot generates an order based on the target staffing table, which it sends to HR specialists. Result: - Robotic process automation in HR reduced manual labor by up to 95%. - We are reducing the number of errors to 0%. - Significant performance gains. ### Process # 3: Controlling the timing of vacations Task: Sending notifications to employees about the upcoming vacation Decision: The robot uploads the target report from the accounting system and generates an up-to-date vacation schedule. The robot checks the upcoming vacation dates for each employee, sends email notifications, and records changes. Result: - Achieved 100% automation. - 100% process accuracy. - Faster processing times. - Effective compliance. ### Process #4: Simplified adaptation Task: Achieving agreement between organizational procedures, employee profiles, and preferences requires robust data integration capabilities. Decision: Robotic process automation can streamline the onboarding process by automatically activating a specific template for the user account onboarding workflow. The software robots can then make rule-based decisions, such as which documents to send, which credentials to assign to a new employee and more. In addition, bots dramatically speed up processes such as creating an employee ID and allow new employees to begin their roles smoothly and hassle-free. Result: - Reduce onboarding costs as robots assist HR departments through tedious manual and repetitive processes and automatically transcribe information from multiple sources into multiple systems. - Increase the overall processing speed by automatically validating new hiring data and entering it into different systems. - Reduce errors in onboarding processes by accurately updating personal and account information across multiple systems for faster processing. ### Process #5: Employee data management Task: With a constant influx of employee data from existing employees, new employees, contractors, etc., manually managing it can be a nightmare for HR teams. Decision: For example, RPA in HR can automatically generate important documents that employees need instead of having HR personnel migrate all employee data from HRIS into a document template. Robots can also perform data cleansing tasks regularly to ensure data compatibility across multiple databases. Result: - Automating processes with robots can simplify the tasks associated with managing employees, thereby minimizing the risk of incorrect data entry. - This also means staffing services can be delivered to employees more efficiently and faster. ### Process #6: Cost management Task: HR managers in any organization tend to find it difficult to carry out manual travel and expense management processes due to various factors, such as missing receipts, late submission of expenses, out-of-order expenses, and messy spreadsheets. Decision: RPA software allows actual expenditure to be validated using a rule-based procedure to determine the billing type. The software then processes the expense statement making sure it meets all requirements. Result: - An RPA expense management solution allows companies to automatically extract all important fields from expense receipts, saving time. - It also eliminates the need to carry expense receipts with them, as they can take a photo of their receipts, and all relevant data will be automatically extracted from the receipts. ### Process #7: Employee introduction and training Task: RPA technology can help your organization and HR to fully automate the onboarding process, which means new candidates will have a digital profile as soon as they apply and receive a job offer. Decision: As part of this digital profile, RPA software can trigger an automated recruitment process and ensure that candidates are updated with all business processes, compliance standards, and other regulations. Result: - An automated RPA-based induction process can dramatically improve learning efficiency and adoption when combined with a well-designed eLearning and training support platform. ## Companies Using RPA in HR Several IT companies are introducing RPA algorithms into tools for evaluating resumes, sending letters after interviews, and finding potential candidates. [Beamery](https://beamery.com/) uses machine learning to help companies build productive relationships with candidates. For example, they can search for missing data for a candidate’s profile on social networks and fill in the gaps in a recruiter’s knowledge about a person. In addition, the software monitors candidates’ connections with employers and finds the most suitable candidates. The service can scale up hiring efforts without increasing the recruiting team. [AMS (formerly Alexander Mann Solutions)](https://www.weareams.com/), a recruitment and consulting outsourcing company, was among the first to invest in Artificial Intelligence. The software creates profiles of candidates based on CVs and supplements them with available information from the Internet. The program then analyzes the data and identifies the most promising candidates. Fig. 03 · HR 6 processes HR processes to automate - 01Employee onboarding - 02Employee offboarding - 03Payroll - 04Travel expenses - 05Excel data management - 06Reports The recruiter’s assistant automates up to 75 percent of tasks. A specially designed chatbot communicates with candidates, collecting information in the native environment, or using Facebook Messenger, uses natural language processing, and can instantly respond to requests without waiting for a recruiter to become available. If the application cannot find an answer, it contacts the person. The creators claim that the bot constantly learns in communication and can rank candidates based on several factors, including qualifications and level of engagement in the dialogue. ### RPA Implementation Case Study #1: SAP’s Economies of Scale Here is another real-world example of HR robotization. Preparation and distribution of job offer to applicants is a critical and responsible process for large and even more so international companies. A high proportion of manual operations traditionally accompanies it. For example, [SAP](https://www.sap.com/) annually generates and sends more than 27,000 such letters. Each should consider the peculiarities of labor legislation in a particular country. It was necessary to eliminate this routine, and robotization helped a lot here. Various systems and data sources are used in the business process, the roles of participants (hiring initiators, recruiting specialists, representatives of the head HR department) are clearly defined, and “manual” operations lend themselves to algorithmization. As a result, an intelligent software robot with the necessary skills was developed and implemented in a short time. ### RPA Implementation Case Study #2: Unilever’s Introduction of RPA in HR Tasks were broken down into projects, subprojects, in turn, were detailed to the required level. This discussion was conducted in a workshop format – it lasted 3-5 days, and the result was a specific list of tasks that needed to be solved in a particular project. For two years (2017-2018), the robotization of processes allowed them to reduce the costs of working with data, conducting dismissal processes, and processing payments for VHI – by only 82,000 euros. Given that [Unilever](https://www.unilever.com/) is a global company, ensuring that the work with foreign data complies with local legislation requirements is necessary. An important and challenging task was integrating the systems of the parent company and foreign offices’ systems. Historically, they transferred a significant part of the data manually due to the substantial difference in system interfaces. Robotization helped move away from the manual part. What changed? For example, previously, actions related to the establishment of data on the dismissal of an employee in the local system took an HR department employee 13 minutes. The HR bot does the same operations, but it takes 3 minutes, and the risk of errors is lower. Across the company, this difference in minutes adds up to hours and, ultimately, money that the business saves tHRough automation. Previously, the task of selecting interns was complicated for HR because applicants must meet a large set of diverse criteria. The recruiting process was slow and costly, with the HR department closing only 80% of business requests on time. It was essential to increase this indicator in a short time. What did the bot implementation experiment bring? They collected 4 times as many applications, closed 100% of applications, answered candidates five times faster, and reduced the cost of this task by 35%. At the same time, it took only $ 200 to launch the bots. We must say that they not only robotized the selection process but also made it more interesting for applicants. Those who passed the first selection stage were allowed to record a video presentation. This video message was organized with the support of VCV, whose service they have integrated into their HR processes. ## Summary No less promising areas for the implementation of software robots are finance and accounting (working with suppliers, posting, making payments, paying benefits, ordering certificates), supply chain and procurement (managing inventory, contracts, and invoices), and IT service (monitoring and processing requests, sending notifications and letters, monitoring and managing credentials). RPA technology already has sufficient components for automating business processes, but it is also developing very rapidly. Today, the technology moves from simple RPA to IPA (Intelligent Process Automation). They already use cognitive software robots, which, based on trained machine learning models and neural networks, solve analytical and intellectual problems of increased complexity. Such robots can also work with optical recognition (OCR) technology to automate paperwork and image analysis. Are you still hesitating? Find this info insufficient? Feel free to [contact our talented RPA experts](https://www.flobotics.io/contact). We will analyze your HR processes, identify those with the highest automation potential and develop bots to boost your efficiency and increase your ROI. #### Like the article? Spread the word Written byMichał Rejman Chief Marketing Officer at Flobotics. [More from Michał](https://www.flobotics.io/our-editorial-team#rejman) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### RPA Reloaded: 50+ Robotic Process Automation Statistics to Know in 2026 RPA statistics 2026: 50+ data points on robotic process automation adoption, ROI, and where the technology is headed next. Yana PokoraApril 15, 2025 ](https://www.flobotics.io/blog/rpa-statistics)[ RPA ### RPA Failures: 10 Most Common Reasons and How to Avoid Them RPA failures: Flobotics' CTO breaks down the 10 most common reasons automation projects fail and how to avoid them. Karl MielnickiJuly 06, 2021 ](https://www.flobotics.io/blog/rpa-failures)[ RPA ### Process Mining vs RPA: How They Work Together to Improve The Efficiency of Your Business Process mining and RPA: how combining the two turns automation candidates into measurable efficiency gains for your business. Bart TeodorczukJanuary 30, 2023 ](https://www.flobotics.io/blog/process-mining-automation) [All articles →](https://www.flobotics.io/blog) --- # How Is Robotic Process Automation Disrupting the Banking and Finance Industry? Canonical: https://www.flobotics.io/blog/rpa-in-finance-and-banking Author: Filip Nasiadko Published: 2021-01-15 Updated: 2026-09-01 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/How Is Robotic Process Automation Disrupting the Banking… CEO Notes [Eligibility](https://www.flobotics.io/blog?category=eligibility) # How Is Robotic Process Automation Disrupting the Banking and Finance Industry? [Filip NasiadkoCEO and Co-founder at Flobotics](https://www.flobotics.io/our-editorial-team#nasiadko) Published January 15, 2021Updated September 1, 2026 On this page - [What is RPA?](#what-is-rpa) - [How Does Robotic Process Automation in Banking and Finance Work?](#how-does-robotic-process-automation-in-banking-and-finance-work) - [Top Reasons Why RPA and Banking & Finance Work Together Well](#top-reasons-why-rpa-and-banking-finance-work-together-well) - [Automate Manual and Repetitive Actions and Processes](#automate-manual-and-repetitive-actions-and-processes) - [Speed and Efficiency](#speed-and-efficiency) - [Productivity](#productivity) - [Working Time](#working-time) - [No errors](#no-errors) - [Expand the Boundaries of Tasks](#expand-the-boundaries-of-tasks) - [Changes in the Existing Banking Business Model](#changes-in-the-existing-banking-business-model) - [Where Robotic Process Automation in Banking Can Be Applied?](#where-robotic-process-automation-in-banking-can-be-applied) - [10 Real Use-Cases of Robotic Process Automation in Banking, Fintech, and Finance](#10-real-use-cases-of-robotic-process-automation-in-banking-fintech-and-finance) - [1. Automation Control](#1-automation-control) - [2. Revising Accounts](#2-revising-accounts) - [3. Processing of Accounts](#3-processing-of-accounts) - [4. Processing of Orders](#4-processing-of-orders) - [5. Correction of Inaccuracies](#5-correction-of-inaccuracies) - [6. Work with Cash](#6-work-with-cash) - [7. Make Sure the Contractual Terms Are Compliant](#7-make-sure-the-contractual-terms-are-compliant) - [8. Report of Profits and Losses](#8-report-of-profits-and-losses) - [9. Data Management in Multiple Systems](#9-data-management-in-multiple-systems) - [10. Overall Efficiency](#10-overall-efficiency) - [3 Financial Companies That Successfully Use RPA](#3-financial-companies-that-successfully-use-rpa) - [Kryon Systems – Claim Payment Processing](#kryon-systems-claim-payment-processing) - [Bancolombia – Investment Portfolio Management](#bancolombia-investment-portfolio-management) - [Keybank – Accounts Receivable System](#keybank-accounts-receivable-system) - [Summary](#summary) Book a callWant to talk about it? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) The innovative technology of Robotic Process Automation (RPA) is one of the most powerful tools for optimizing business processes today. The course of all exhausting, routine processes in any business area can be significantly improved thanks to it, and the costs of their maintenance are significantly reduced. However, is the banking sector one of those where it is possible to use robotization technology? After all, Robotic Process Automation in banking sector and automation in general is perhaps one of the most vulnerable in terms of risks, given banking specifics. In addition, the rather restrained attitude of banking IT departments to all kinds of technological innovations that could interfere with the smooth operation of banking systems and already integrated corporate applications is well known. Also, what about security issues? Indeed, in the banking sector, they are relevant, like in no other: it is information security, the security of saving personal data, the security of operations, etc. The slightest mistake can be very expensive here – both in monetary terms and in matters of reputation bank and clients’ confidence in it. Due to such a high degree of financial and non-financial risks, doubts may even creep in whether it is advisable to “let robots into the bank” at all. But, despite the quite fair questions and warnings, the technology of robotization of business processes is not only suitable for implementation in the banking sector – it already has successfully established itself in this field and showed the first results that are encouraging for all skeptics. Such world-famous banks as HSBC, Credit Suisse, Citi, Deutsche Bank, and international groups Raiffeisen Bank International and BNP Paribas are already leveraging RPA and intelligent automation. Many other institutions around the world are already on the verge of implementing Robotic Process Automation in banking and see it as a powerful and truly revolutionary tool for positive changes in the banking business. ## What is RPA? The banking and finance industry has experienced exponential growth over the past few years, thanks to the implementation of technological advances that lead to faster, safer, and more reliable services. To stay competitive in an increasingly crowded market – especially with the increasing adoption of virtual banking – banking firms had to find a way to provide their customers with the best possible user experience. Almost 81% of banking executives are more concerned about the speed of technological change than any other sector in the industry, [according to PwC](https://www.pwc.com/gx/en/financial-services/assets/pdf/technology2020-and-beyond.pdf). Within the company, the challenge has also grown to maximize efficiency and minimize costs while maintaining the highest level of security. To meet these needs, Robotic Process Automation (RPA) has become a powerful and effective tool. RPA has been widely adopted in this sector to make labor-intensive banking transactions more organized and automated. According to [reports](https://www.grandviewresearch.com/industry-analysis/robotic-process-automation-rpa-market), the largest share of revenue in 2019 came from the BFSI segment in terms of RPA application. Robotic Process Automation in banking has also greatly simplified a wide range of back-office processes that once bored bank workers. By shifting much of these tedious manual tasks from person to machine, banks have been able to significantly reduce the need for human participation, which has had a direct impact on everything from productivity and efficiency to personnel issues and costs. Recently, Japan’s largest banks announced the introduction of Robotic Process Automation to reduce labor costs and improve operational efficiency. Large banks such as Axis Bank and Deutsche bank also announced the implementation of RPA to automate business processes. A bank employee deals with voluminous data from customers, and manual processes are prone to error. Banks around the world are considering using RPA to minimize manual processing of this huge data to avoid errors. Handling data manually is also a laborious task. Simple checking of client information from two systems can take seconds instead of minutes with bots. Implementing bots for these manual processes can reduce processing costs by 30% to 70%. Some processes in banks can be automated to free up staff to work on more important tasks. Over the years, companies have tried to find ways to improve these departments through corporate systems, reporting tools, and interim measures to eliminate repetitive manual actions. According to [Jeremy Dean](https://www.linkedin.com/in/jeremy-dean-b314a18/), the head of RPA at the accounting company Mazars in the USA, this phenomenon has a bright future: “Unfortunately, these methods solved many other problems but did not help in any way to eliminate two main ones that exist in finance and accounting. The first is how to load data into the systems, and the second is how to carry out the “closing of the month.” Many people now realize that automation solves these two problems.” ## How Does Robotic Process Automation in Banking and Finance Work? To reduce errors and perform repetitive workloads, RPA also leverages the power of artificial intelligence. The advantage of RPA is that you do not need to automate the entire process, but only certain parts of a multi-step process. [Dennis Gannon](https://www.gartner.com/analyst/67358/Dennis-Gannon), vice president of consulting at Gartner, says rule-based processes are best suited for automation. This is where RPA delivers fast results and acts like digital adhesive tape. “RPA is good at handling bottlenecks that arise in time-consuming processes that require many hours of manual labor,” Gannon revealed. He says RPA is likely to gain widespread acceptance as a means of automating the buy-to-pay process. By starting with these transactions, finance teams can capture early results and get feedback on what is working well, and then move on to other tasks that are also easy to automate. When it comes to fears of being unemployed due to automation, it’s important to involve finance staff on RPA projects to reduce their fears and allow them to discover new perspectives. To begin with, project managers will involve employees in automation processes for a couple of days a month so that they can practice introducing new robots into the production environment. For the remainder of the time, they will observe how the robot is working and identify any limitations and problems in using it. This will open up other areas for them to automate their work. RPA consists of software robots, which are patterns of repetitive actions. The robot mimics normal human functions: reading text in an application, copying information, and transferring it to another application. IT departments use RPA platforms to create, monitor, manage, reuse, and save robots and the actions they perform. The simplest robots capture the mechanical actions of a person and copy them. This is a kind of sample. Based on it, the developer will create a stronger robot that will not break if the application screen is slightly changed. Other artificial intelligence technologies often complement robots. For example, optical character recognition (OCR) is used to transfer text from a paper document, and machine learning is used to match fields in an invoice with fields in an application. This combination is sometimes referred to as intelligent process automation. Robotic Process Automation in banking also complements a number of other technologies. Sometimes IT departments use low-code / no-code frameworks to create lightweight automation that is implemented as code, API management frameworks, or platform-as-a-service, which enables direct communication that is much faster than RPA. However, RPA has access to any application available to humans, and this is its advantage over other technologies. Fig. 01 · RPA market $ millions Global RPA market, 2016–2021 - 27173198 - 443113330 - 629153476 - 822192630 - 1,022232790 - 1,062272790 201620172018201920202021 - RPA software - RPA services Year-on-year growth slowed from 63% (2017) to 20% (2021). | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | RPA software | 73 | 113 | 153 | 192 | 232 | 272 | RPA services | 198 | 330 | 476 | 630 | 790 | 790 | Studying the market of implemented RPA solutions in the international IT segments, we can conclude that the use of RPA does not actually depend on the industry, and this technology works in any market segment. However, this article is devoted primarily to Robotic Process Automation in banking and finance. ## Top Reasons Why RPA and Banking & Finance Work Together Well Here are the most important points. Look through all of them to see the main benefits of using Robotic Process Automation in finance. ### Automate Manual and Repetitive Actions and Processes Experience has shown that robotization works best in those business areas where there are many manual and repetitive actions and processes. From this point of view, the banking sector, in which such processes – carrying out transactions, entering/reconciling data, paying bills, etc., are commonplace – is one of the most suitable for RPA. And suppose we imagine the scale of these processes in the context of an extensive banking network of regional branches. In that case, the need for their robotization over time will become simply imperative. ### Speed and Efficiency Correctly implemented and correctly controlled robotization will significantly improve the speed of processing banking operations, the efficiency of back-office and front-office processes in the bank, reduce the duration of processing client requests, and, consequently, free up front-office employees the time needed to serve customers better. ### Productivity Contrary to concerns about reliability, robotization technology allows not only increases the productivity of business processes significantly but also minimizes the number of purely mechanical errors that a person can make due to the influence of the so-called “human factor” (fatigue, health, etc.). ### Working Time In addition, the working time of software robots is not limited. They are capable of performing specified operations 24/7, which is very important for a modern bank’s operational activities with the same unlimited 24/7 access to a wide range of banking services (in particular, through Internet banking, and payment terminals). In addition, Robotic Process Automation in banking successfully integrates with corporate applications already available in the bank, without changing the IT landscape, which does not threaten banking systems’ smooth operation. On the contrary, it greatly improves their work. ### No errors Although RPA technology is still relatively new on the market, examples of positively implemented business cases on robotics in the banking sector are already making themselves felt. In those banking institutions where robotization has already been successfully implemented, it has significantly increased business processes’ operational efficiency and productivity. Because reducing manual processes minimizes not only costs but also the likelihood of errors. Thus, Robotic Process Automation in banking ensures the highest quality and the highest level of accuracy in business processes. Therefore, perhaps there is nothing surprising in the fact that automated solutions are increasingly becoming the subject of close attention from the banking sector since they allow them to bring it to a qualitatively new level of mastering new opportunities for developing the banking business. ### Expand the Boundaries of Tasks Robotization, enhanced by the capabilities of machine learning and artificial intelligence technologies, will also significantly expand the boundaries of tasks performed by software robots, making it possible for them to process unstructured and semi-structured data sets. ### Changes in the Existing Banking Business Model Undoubtedly, it is also worth remembering that Robotic Process Automation in banking & finance will lead to significant changes in the existing banking business model. This does not literally mean that hundreds and thousands of employees will instantly lose their jobs with its implementation. Although we do not completely exclude the possibility that the least qualified among them, capable of performing only mechanical work, can lose it – it will be difficult for them to compete with robots in speed and efficiency. However, along with the implementation of RPA, one should be ready to redistribute the workload and powers between the employees who were previously engaged in routine processes within the bank itself, since robotization will free up their working time, which would be more expedient to be directed to solving more creative tasks and better work with clients. Therefore, here we are also dealing with an indirect effect of robotization, which will consist of an unobtrusive inducement of employees to improve their qualifications. The human employee will also have to learn how to effectively interact with software robots to ensure banking business processes’ efficiency and continuity. ## Where Robotic Process Automation in Banking Can Be Applied? How and what is automated in finance? According to a poll by [The Economist Intelligence Unit](https://www.automationreadiness.eiu.com/static/download/infographics.pdf), more than half of all financial transactions last year were carried out with robots’ participation. Analysts at [McKinsey](https://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/where-machines-could-replace-humans-and-where-they-cant-yet) say that in the financial sector, automation can, on average, free up 43% of employee time. This figure may vary depending on the specific specialization. For example, a mortgage broker spends 90% of the time processing applications in manual mode, but if it uses more modern methods of determining the authenticity of documents or applications for a loan, then 60%. As a result, they can devote the saved time to communicating with clients – to consult more and delve deeper into their needs. Companies trust robots to solve specific problems in large processes. They can: - get access to applications; - make decisions based on the if / then rule; - navigate through applications; - write and send emails; - read structured data from documents; - open files and attachments; - copy and paste information. As practice shows, a wide variety of banking functions and processes are successfully amenable to robotization: - lending, - servicing accounts and payments, - audit reporting, - mortgage payments, - reconciliation of account balances, - etc. Here are examples of the most common tasks that robots take on in the financial sector. - Collection and processing of data. Finance and insurance workers in the United States spend half of their time on these processes. According to McKinsey, RPA solutions are capable of handling 60% of these tasks. Robots successfully process completed customer forms according to the specified parameters, extract and check data from invoices, confirm payments, send error notifications, monitor duplicate payments, etc. The robot copes with data entry faster than a human. This saves companies the time and money needed to rework the task. The program works around the clock without a break for lunch and sleep, does not get tired and does not make mistakes, and provides reports simultaneously. Thus, customers of banks and insurance companies are less likely to face situations such as delays in payments. - Confirmation of data accuracy. Employees of many financial institutions spend a lot of time on tasks such as determining a credit score. Robots with access to databases are able to verify the authenticity of the information provided by clients by order of magnitude faster. They easily track money transactions and identify suspicious activity. In the long term, this means that a person with a clean credit history will get access to necessary services faster. - Prepare material for analysts. Organizing data for analysts takes a huge amount of time, and this task can also be safely given to a robot. The specialist will work with a ready-made table. Its task is reduced to familiarization with the document and making decisions. - Customer support. Most executives across industries, including finance, believe that customer support automation is essential to a company’s competitiveness. This implies both a more convenient search and storage of user information and the implementation of RPA solutions integrated with chatbots. So, bots are happy to communicate with any client, regardless of the time of day. They are ready to answer basic questions, leaving complex counseling to the people. With such a wide range of potentially robotic processes, one has only to remember about choosing the “correct” ones among them, the effect of which will be the best. The decision on this should be made on an individualized basis – taking into account the specific banking infrastructure and current business processes efficiency. Let alone RPA in the banking industry, the robot can do the following: - opening/closing applications and systems Web clients, Email (including attachments); - navigation within applications (ERP, CRM, etc.); - creating and moving files and folders; - following links and emulating button presses; - automatic switching between applications; - filling out forms, copying; - loading data from external sources into the program interface and directly into the database; - comparison and validation of data, mathematical calculations; - work on complex logic with conditions and cycles; - OCR (PDF / DOC / XLS); - multilevel automated verification of data entered by other employees; - messengers – communication using intelligent chatbots; - using predictive analytics to drive statistics-based robot decisions and data mining. Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) ## 10 Real Use-Cases of Robotic Process Automation in Banking, Fintech, and Finance Below are ten examples of implementing Robotic Process Automation in banking, accounting, and finance. ### 1. Automation Control RPA implementation is difficult to scale. One of the challenges is to allow finance departments to create new robots easily, but the process needs to be limited. “To address this issue, Hewlett Packard Enterprise (HPE) [created a centralized bot infrastructure](https://www.hpe.com/us/en/insights/articles/conversational-ai-and-the-rise-of-the-chatbots-1805.html),” said Sandeep Singh, head of financial control and quality assurance and RPA CoE at a multinational IT company based in San Jose, California. His team has built a bot platform based on WorkFusion, which simplifies the process of deploying automation, building robots, and tracking and reporting bugs. Employees created an internal governance framework so that all stakeholders can access audit, business compliance, IT, and finance data. Singh says: “This is convenient for both the executives and external auditors as it allows you to keep a close eye on what is happening. We are constantly working to ensure that no information passes by us.” ### 2. Revising Accounts Reconciliation of accounts between systems is a necessary but extremely boring exercise. As per Singh, [HPE has benefited most from using RPA](https://www.hpe.com/us/en/insights/articles/robotic-process-automation-is-expanding-outside-the-back-office-1712.html), as it improved logging and subsequent invoice reconciliation. These processes are compliance-driven, time-consuming, and involve excellent operations. For example, different departments within HPE have different process templates and review procedures. Some of these processes may include functions within the ERP system. Others must meet both the audit and compliance requirements for the authenticity of transactions and the business requirements for approval procedures and thresholds. Singh’s team was challenged to find the right balance between specific business requirements and rigorous audit and compliance rules, resulting in an optimal solution that can be automated using RPA. “While business requirements are not as strict and negotiable, and it is possible to improvise here, accounting and compensation must be handled very delicately,” Singh says. ### 3. Processing of Accounts Invoice processing is another notable area for automation. HPE accountants process significant volumes of paper invoices every month. They are also responsible for registering them for subsequent payment processing. Problems arise here due to the different formats of invoices, the quality of the scanned documents, and other languages’ use. The company has combined OCR technology and WorkFusion machine learning modules to smooth out format and image quality issues. Optical Character Recognition (OCR) technology helps convert images to a sequential text format, and then machine learning uses historical rules to determine how information from an invoice is entered into a financial application. HPE also uses automation to feed extracted data into SAP Ariba’s procurement management system. ### 4. Processing of Orders Depending on the source of the order, the document format itself is also different. Jeremy Dean believes that automation speeds up order processing and eliminates human error. The principle of operation here is similar to processing invoices: OCR technology reads data from paper, and machine learning transfers it to the system. For example, Dean was working on a project for a brewery where they wanted to automate the creation of orders in SAP. Their robot received input data in two different formats, checked the entered data’s completeness, then set up a shopping cart in SAP, and sent a request for order confirmation. ### 5. Correction of Inaccuracies Another great point of RPA in finance examples. As soon as erroneous information enters the enterprise data ecosystem, it immediately spreads across all systems and data warehouses. Subsequent cleaning and adjustments will require considerable effort. Dean has already worked on several projects. The bottom line is that automation scans the data in order to quickly and efficiently make corrections and identify errors, then send them to employees for review. Having found the correct data, the robot programmatically changes all other information in the system. For example, Dean was working on a logistics company project where RPA helped identify inaccuracies between the ERP system and reporting tools. To assess the degree of a discrepancy, the robot used different rules to determine whether the problems that have arisen are related to the original data, or have already appeared in ready-made reports. The final decision is flagged for employee review and approval. The robot will make changes to the system as soon as the employee approves them. This approach improves the quality of data across all company systems. ### 6. Work with Cash Cash depositing is an important function during the processing of receivables. For example, many errors arise when money goes to another account or is posted on the wrong invoices and invoices. HPE Finance receives a huge stream of payments from customers in more than 50 countries. It all starts with bank statements, which are provided in the required format. Then they are posted to the appropriate accounts for a particular department or group. Robotic Process Automation in finance helps automate the reading of information from statements and entering data into specific fields in a receivables program. Singh says the different formats, languages, and the lack of specific information on the statements became a problem for HPE, as it made it difficult for analysts on accounts receivable. The solution was implementing RPA in finance and its development, which uses fuzzy logic to improve data recognition, and machine learning to avoid repeating previous mistakes. As a result, the deposit process’s accuracy has increased, and the processing time has been significantly reduced. ### 7. Make Sure the Contractual Terms Are Compliant In compliance, it is especially important that suppliers adhere to previously agreed terms. And this is another great argument for the bright future of RPA in finance. For example, it helps HPE contract employees automate many of the operations associated with fulfilling contractual obligations. Singh defines this work as extremely cumbersome and boring, which is also done by hand. Using natural language processing technology, the robot scans all contracts and purchase orders and extracts the necessary information on discounts, recalculations, and penalties. The robot then compares this data with data from the company’s ERP system to identify gaps and inaccuracies. ### 8. Report of Profits and Losses [Manish Chawla](https://www.blueprism.com/uploads/resources/white-papers/ux_whitepaper_Blue_Prism_Protiviti_2020.pdf), associate director of business performance at international consulting firm Protiviti, says many companies automate the generation of profit and loss statements, especially those that need to submit such reports to management on a daily basis. As with the previous examples, Robotic Process Automation in banking dramatically reduces the number of repetitive, time-consuming, and manual tasks so that finance staff can focus on generating profit and loss statements, which is their top priority. Many companies significantly reduce the time for processing reports and provide early access to them, but at the same time with much more accurate data. ### 9. Data Management in Multiple Systems Oftentimes, finance staff members need to manage data that resides in different systems. Automation improves data management in these systems and allows you to take into account the rules for their movement. Jeremy Dean says that IT departments can set up financial robots to respond to certain events in the systems, or so that they can be launched at a fixed time when it is necessary to complete the process. Dean was involved in developing a solution for a banking and insurance company. The goal was to improve the process of managing master data and maintaining financial accounts. For example, his team has automated three back-office activities related to the seizure of enforcement of clients’ assets. This simplified the launch of an operation, during which access to various databases is opened, and amounts are frozen on different accounts and two different banking systems with minimal involvement of employees. In the meantime, they can focus on more complex tasks such as analyzing and introducing new data. ### 10. Overall Efficiency In 2017, the Polish Eurobank [turned ](https://www.uipath.com/resources/automation-case-studies/eurobank)to the consulting company PricewaterhouseCoopers for their assistance in implementing RPA. At that time, the financial institution served 1.4 million private accounts and had a network of 500 branches. It took several months to check the viability of the project and develop several test robots. The experience turned out to be successful, and the bank created its own RPA competence center, which began studying business processes and preparing them for robotization. UiPath Orchestrator from one of the world leaders in RPA, UiPath, was chosen as the centralized robot control platform. The selection from the list provided by PwC was based on test results in which the UiPath Orchestrator demonstrated the best performance in terms of cost-effectiveness, simplicity, and ease of use. The results of the project exceeded expectations. The robots were able to take over about 20% of the bank’s back-office tasks. This 20% includes almost all compliance-related tasks. The bank noted an improvement in customer service quality, and the resulting robotics savings in working time exceeded 20 FTE. Fig. 02 · Case Banking results Key results 20%of daily work in one department handled by bots ~100%of the backlog processed by UiPath bots 20+FTEs saved a month Bettercustomer service ## 3 Financial Companies That Successfully Use RPA Financial companies planning to automate their processes can learn from the following examples. These companies have pioneered Robotic Process Automation innovations beyond simple operational efficiencies. ### [Kryon Systems](https://www.kryonsystems.com/) – Claim Payment Processing Insurance is one of the main beneficiaries of Robotic Process Automation. Kryon Systems, a provider of RPA solutions, helped a global insurance company reduce payment processing times. RPA has proven to be a game-changer in claims technology. Their client, a global insurance company, had to go through 26 different banking websites and use a smart search to check if payments were made. This happens on 4 different days each month and takes 4 business days each month. Once RPA was implemented, it took only 2 hours to complete. In the past, employees made mistakes and searches were wrong, but robots provided a mechanism that increased accuracy. As a result, thousands of working hours are saved every year, and human error is eliminated. ### [Bancolombia](https://www.grupobancolombia.com/) – Investment Portfolio Management Bancolombia, the largest bank in Colombia, has implemented RPA solutions to help people better manage their investment portfolios. Their RPA tool, Invesbot, is available to anyone with investments over $7,000. It provides real-time market information and portfolio performance and offers advice on making changes in line with current market conditions. Another innovation is a robot advisor who advises Colombian investors on stock marketing and helps them experiment with it. This allowed Bancolombia to teach how to invest in the stock market digitally. “The idea is that the client does not have a higher cost for advisory services. We see this more as a highway for growth rather than something that allows us to cut back on financial advisors.” – Juan Felipe Giraldo, President of Valores Bancolombia The results are clear: Bancolombia has won the Digital Transformation Award at Colombia’s Best Biggest Company from PwC and CINTEL. ### [Keybank](https://www.key.com/personal/index.jsp) – Accounts Receivable System Keybank is the leading commercial bank in the United States to partner with Billtrust and implement RPA technology to improve its efficiency. Bank automated invoice delivery and receivables processing with RPA solution powered by Billtrust. It includes the creation of electronic invoices with Quantum Payment Cycle Management Billtrust. Keybank has optimized accounts receivable through an end-to-end implementation of RPA. “Banks have traditionally focused on payment execution. We think that’s important. But in consulting with our clients, we hear a lot of pain upstream and downstream of payment processing. Partnering with innovators like Billtrust enables us to optimize clients’ processes from beginning to end.” – Matt Miller, Head of KeyBank product and innovation for commercial enterprise payments The bank has automated repetitive manual tasks. They hope that the entire implementation of machine learning will improve processes over time. It expands its RPA capabilities for better digital transformation. ## Summary For now, most industry leaders have no doubt that RPA will increase their companies’ competitiveness over the next two years. The reason for this will be, among other things, an increase in the level of service and greater customer satisfaction. So, let’s say a positive decision on robotization in the bank has been made. It will be equally important to correctly build further steps for its implementation and determine what basic rules should be followed in order to make a banking RPA project successful. Never heard of our services? Take a read of the [Flobotics bank case study](https://www.flobotics.io/case-studies/t-bank-automation) to make sure that we won’t waste your time. Feel that the help of specialists would be useful? Don’t hesitate and [contact](https://www.flobotics.io/contact) Flobotics for RPA consultation and development. #### Like the article? Spread the word Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) Written byFilip Nasiadko CEO and Co-founder at Flobotics. Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart Keep reading ## More insight The latest industry news, interviews, technologies, and resources. [ RPA ### What Is RPA? | Robotic Process Automation Robotic Process Automation (RPA), explained: how software bots run a 24/7 digital workforce that cuts costs and human error. Bart TeodorczukSeptember 01, 2025 ](https://www.flobotics.io/blog/robotic-process-automation)[ RPA ### RPA Reloaded: 50+ Robotic Process Automation Statistics to Know in 2026 RPA statistics 2026: 50+ data points on robotic process automation adoption, ROI, and where the technology is headed next. Yana PokoraApril 15, 2025 ](https://www.flobotics.io/blog/rpa-statistics)[ RPA ### Top 10 RPA Implementation Challenges to Be Aware of Challenges of RPA implementation: the top 10 obstacles slowing projects down and proven strategies to keep your automation on track. Krzysztof SzwedAugust 22, 2023 ](https://www.flobotics.io/blog/rpa-challenges) [All articles →](https://www.flobotics.io/blog) --- # 100% ROI in just 23 days. We Automated Eligibility Checks! Canonical: https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks Published: 2026-03-09 Updated: 2026-04-08 --- [Home](https://www.flobotics.io/)/[Client Results](https://www.flobotics.io/case-studies)/100% ROI in just 23 days. We Automated Eligibility Checks! Eligibility Checks # 100% ROI in just 23 days. We Automated Eligibility Checks! $180,000 worth of savings after year one. Our eligibility automation, together with Denial Hunter for denials, reached a 100% return on investment in 23 days. 100%ROI in just 23 days from eligibility automation together with Denial Hunter, with $180,000 worth of savings after year one. ClientPTCoA WorkflowEligibility Checks Headline result100% On this page - [Project Scope](#project-scope) - [Main Challenge | Eligibility Checks](#main-challenge-eligibility-checks) - [Solutions:](#solutions) - [Eligibility Check Automation](#eligibility-check-automation) - [Results:](#results) Book a callWant results like these? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Project Scope Pain Treatment Centers of America (PTCoA) is one of the largest fully comprehensive pain management practice networks in the U.S.A. They're operating in 13 clinics across Arkansas and Mississippi. They provide cutting-edge interventional pain treatments and advanced surgical services, their RCM team needs to ensure timely reimbursements and smooth administrative workflows. Pain management is a high-volume & low-margin, as well as high-repetition & fast-burnout field. Reputation and Net Promoter Score are crucial here. Initially, PTCoA came to us with a very specific need – they asked us to address their most time-consuming RCM processes through AI-powered automation. So we agreed. ## Main Challenge | Eligibility Checks Most pain management plans consist of multiple procedures. Epidural injections, nerve blocks, follow–up visits, or therapy sessions…each of these requires precise eligibility verification. Even minor errors, like outdated policy data, mid-month plan changes, or incorrect benefit types, meant that a whole chain of claims would later bounce back. In pain management, eligibility checks are straightforward and repetitive, yet absolutely crucial. PTCoA’s billing department was facing hundreds of small, repetitive claims daily. The process was fully manual and required constant human oversight. Their RCM specialists had to: - Cross-check patient insurance details across multiple payer portals by hand, - Confirm coverage and copayment eligibility for every visit or procedure, - And manually transfer verified data between EHR and billing systems, since no integration existed between them. With no technological solution in place, the team was essentially processing patients data by hand – from coverage check to data entry. That meant 5–7 minutes per patient, multiplied by hundreds of daily visits. A growing verification backlog, delayed claims, and a mounting administrative burden… With rising patient volumes and expanding payer requirements, manual verification became a scalability bottleneck – costing PTCoA valuable hours every week. That’s where we stepped in. ## Solutions: Since the main goal was to save FTE hours, we started by mapping the entire eligibility verification workflow. After all, RCM automation doesn’t have to be one big leap – it can be approached in small, targeted steps that deliver fast results. We spent a long time with PTCoA’s team to catch every step. Pain management practices have their own operational rhythm – high visit frequency, small-ticket procedures, and multiple insurers per patient. After several days of workshops, we had a complete picture of their eligibility workflow. It quickly became clear that automated data exchange between PrognoCIS (EHR) and Trizetto (Billing Service) was the cure. ### Eligibility Check Automation Within a month, we deployed a fully automated eligibility verification process. Each time a new appointment is created, the automation triggers instantly – confirming eligibility in real time before the visit. When inactive coverage or missing IDs are detected, records are flagged for staff review, preventing downstream denials. All verification results are timestamped, logged, and archived within a HIPAA-compliant environment, for maximum PHI security and full audit traceability. Moreover, the solution also integrates seamlessly with other PTCoA workflows already in use. What used to be a chain of manual steps now runs silently in the background. Our automation swiftly: - Logs into payer portals, - Retrieves active policy data, - Verifies coverage, copay, and deductible information, - Writes verified data directly back to PrognoCIS. To top that off, our data-exchange pipeline verifies patient coverage and calculates copayments continuously – all without human intervention. It’s worth noting that verified coverage information is instantly synced with TriZetto, ensuring pre-claim data stays consistent across systems. #### How the Eligibility Check Automation Works? Here’s how it works: - Data Trigger: A new appointment is created in the EHR. - Portal Login: The Eligibility Checker logs into the relevant payer portals or API endpoints. - Verification: It extracts key insurance data – coverage, copay, deductible status, and policy dates. - Bad Coverage Flagging: Inactive or mismatched coverage is automatically flagged in the patient record for review. - EHR Update: Verified details are automatically written back into the patient record. - Notification: Staff receive alerts for exceptions or missing data. ## Results: Automating eligibility verification gave PTCoA an instant efficiency boost across the entire RCM chain. Our automation overwatches eligibility checks 24/7, cutting down the processing time to 45 seconds each case – all without human supervision. As a result: - Check–ins were faster, - Net Promoter Scores (NPS) improved, - The volume of checks increased, - RCM team unlocked full-time employee (FTE) capacity. That’s the real power of solid AI automation in healthcare. On top of that, our eligibility automation combined with solutions like Denial Hunter, together achieved a 100% return on investment in 23 days, projecting $180,000 worth of savings after year one. In short: We solved the eligibility checks bottleneck. KPI | Before automation | After automation | Impact | Process Time per Check | 5–7 minutes | ~40 seconds | ~85–90% faster | Monthly Volume | Manual processing | 8,000+ eligibility verifications / month | High-volume scalability | Operational Effort (FTE) | Baseline staffing | Automation-driven | ~3 FTE saved | With the success of the eligibility check automation, PTCoA continues to grow. Their road plan for automations now covers lab orders, price comparison, write–offs, and patient communication. Together, these solutions form a cohesive, HIPAA–compliant automation ecosystem that keeps RCM operations fast, accurate, and scalable. Which brings us to the following point: At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic automations here. Metric | Result | Process Time per Check | 5–7 min → ~40 seconds | Volume | 8,000+ eligibility verifications processed / month | FTE Savings | 3 FTE | Checking eligibility by hand too? 30 minutes with Karl, our CTO, or Bart, our Head of AI. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) More work ## More case studies Real deployments, with the numbers our clients measured. [ Denials Management Up to 80%higher throughput in RCM, with a custom laboratory information system data exchange. ### Up to 80% Higher Throughput in RCM Read the case study → ](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation) [All case studies →](https://www.flobotics.io/case-studies) --- # 98% Reduction in Manual Claim Prep | Claims Management Automation Canonical: https://www.flobotics.io/case-studies/98-reduction-in-manual-claim-prep-claims-management-automation Published: 2026-04-08 Updated: 2026-04-08 --- [Home](https://www.flobotics.io/)/[Client Results](https://www.flobotics.io/case-studies)/98% Reduction in Manual Claim Prep | Claims Management… Claims Management # 98% Reduction in Manual Claim Prep | Claims Management Automation See how an automated EHR-to-claim data pipeline removed up to 250 hours per week of manual RCM work. 98%Reduction in manual claim prep. See how an automated EHR-to-claim data pipeline removed up to 250 hours per week of manual RCM work. ClientGentem Health WorkflowClaims Management Headline result98% On this page - [About Gentem Health](#about-gentem-health) - [Challenge | Manual Claim Preparation](#challenge-manual-claim-preparation) - [Solution | Claims Management Automation](#solution-claims-management-automation) - [Results](#results) - [Summary](#summary) Book a callWant results like these? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## About Gentem Health Gentem Health (now part of a SimplePractice) is a Silicon Valley–based company focused on healthcare providers reimbursement and patient’s financial experience. Their ambition is to deliver highly innovative, near real-time eligibility insights and upfront reimbursement estimates, giving providers and patients financial clarity before care is delivered. Before contacting us, Gentem Health relied on manual extraction and transfer of data from various EHRs of various practices into their internal database. This meant frequent system hopping across EHRs to pull the necessary fields, re-enter information, and correct formatting issues by hand. Their revenue cycle depends on accurate and consistent data flowing from multiple EHR systems into their billing platform. They also provide medical billing processing service on behalf of its clients. ## Challenge | Manual Claim Preparation Gentem’s billing team was spending up to ~250 hours per week just extracting and correcting EHR data. The work was slow, costly, and susceptible to many RCM errors like: - technical denials, - rework loops, - delayed claim submission, - ultimately increased aging in accounts receivable. On top of that, the workload was scaling faster than the team could handle. As volume increased, manual preparation became the gating factor for throughput. Claims that were clinically complete often sat idle in pre-submission queues, waiting on administrative cleanup before they could even enter the claim engine. Gentem needed a way to remove manual pre-submission steps without changing EHR systems, retraining staff, or disrupting downstream billing workflows. The core issue was not payer adjudication speed, but lost time before submission. Once a claim missed its intended submission window, its probability of timely reimbursement dropped sharply - regardless of payer performance. Claims delayed at the document and data-prep stage were far more likely to enter the revenue cycle late, increasing exposure to aging, rework, and write-offs downstream. Gentem’s challenge was therefore to stabilize and compress the document-to-claim-ready window - before claims ever entered the payer system. In short: Claims management automation was inevitable. ## Solution | Claims Management Automation We approached this project by treating the EHR as the source of truth. Our agentic AI based integrations were operating between multiple EHRs and Gentem’s databases. It took relevant data (patients, providers and their location, appointments, services, payments) from the EHRs and inserted it into Gentem’s database so they could process insurance claims based on the information provided. Fig. 01 · Claims How it flows How claims flow from practices to insurers - 01Practices A–DEach on its own EHR - 02Gentem databaseClaims gathered and prepared in one place - 03Insurance companiesClean claims submitted The new system syncs the data from multiple practices using multiple EHRs daily. Our automation provides the extraction of patient demographics, billing information, provider credentials, appointment details, service line structure, and payment data from each connected EHR. On top of that, claims management automation targets one of the most critical RCM metrics: clean claim rate. In this case, “clean claims” did not mean payer leniency or better contracts – it meant eliminating avoidable, human-made errors before submission. Manual data extraction introduced small but costly mistakes: mismatched patient demographics, missing modifiers, incorrect provider identifiers, or formatting inconsistencies. Each of these errors could trigger a denial for purely administrative reasons, even when the clinical service itself was fully reimbursable. Improving clean claim rate therefore meant reducing “stupid denials” – denials caused not by medical necessity or coverage rules, but by preventable input errors at the preparation stage. By standardizing and automating claim-ready data before submission, Gentem reduced the noise in the denial pipeline and protected revenue that was previously lost for non-clinical reasons. By improving the consistency of upstream data, Gentem could reduce the rate of technical denials, decrease back-and-forth document requests, limit claim revision cycles, and shorten the time from encounter to claim submission. Cleaner data also reduces the burden on RCM teams, who often spend a disproportionate amount of time correcting avoidable errors created by workflow fragmentation across EHRs, payer portals, and billing systems. ## Results The impact can be summarized conservatively: Clean Claim Rate (CRR) increased from ~80% to ~95%. The improvement reflects reduction in technical denials driven by incomplete or inconsistent upstream data. Cleaner submissions reduced downstream claim touches, stabilizing claims after submission rather than just at intake. In short: Strong upstream automation paid off. On top of that, preparation time for claim-ready data decreased from ~30 minutes to ~2 minutes, and manual effort equivalent to ~6 FTEs was redirected toward higher-value tasks. Technical denials caused by incomplete or inconsistent data dropped by roughly 30%, contributing to a more predictable reimbursement timeline. Here’s a short metrics summary: KPI | Before Automation | After Automation | Impact | Clean Claim Rate (CCR) | ~80% | ~95% | +15 percentage points | Preparation Time for Claim-Ready Data | ~30 minutes | ~2 minutes | ~93% faster | Manual Effort Required | ~250 hours/week | 0–5 hours/week | ~6.2 FTEs reallocated | ## Summary While Days in A/R and long-tail collections are measured after submission, their root causes often originate much earlier. Gentem’s case demonstrates how an agentic AI automation layer strengthens the entire claims lifecycle without adding headcount or forcing changes to existing EHRs. If your teams are slowed down by manual EHR-to-claim data work or are struggling with clean claim performance, automation of this kind can materially improve accuracy, throughput, and financial reliability–starting at the part of the workflow where claims succeed or fail. This project proves that you don't need to replace your portals to fix your workflow–you just need an Agent to manage them. KPI | Before Automation | After Automation | Impact | Clean Claim Rate (CCR) | ~80% | ~95% | +15 percentage points | Preparation Time for Claim-Ready Data | ~30 minutes | ~2 minutes | ~93% faster | Manual Effort Required | ~250 hours/week | 0–5 hours/week | ~6.2 FTEs reallocated | They were easy to get in contact with and the whole collaboration went smoothly. The automation has saved us a considerable amount of time. Everyone in the team confirmed it works fantastically and that it’s freed them up a lot of time. Manny AkintayoCo-founder & CTO at Gentem Health Preparing claims by hand too? 30 minutes with Karl, our CTO, or Bart, our Head of AI. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) More work ## More case studies Real deployments, with the numbers our clients measured. [ Denials Management Up to 80%higher throughput in RCM, with a custom laboratory information system data exchange. ### Up to 80% Higher Throughput in RCM Read the case study → ](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation)[ Eligibility Checks 100%ROI in 23 days from eligibility automation plus Denial Hunter, with $180,000 in savings after year one. ### 100% ROI in just 23 days. We Automated Eligibility Checks! Read the case study → ](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) [All case studies →](https://www.flobotics.io/case-studies) --- # 85% Faster Submissions, 8+ FTEs Saved | Prior Authorization Automation Canonical: https://www.flobotics.io/case-studies/85-faster-submissions-8-ftes-saved-prior-authorization-automation Published: 2026-03-07 Updated: 2026-08-03 --- [Home](https://www.flobotics.io/)/[Client Results](https://www.flobotics.io/case-studies)/85% Faster Submissions, 8+ FTEs Saved | Prior… Pre-Auths # 85% Faster Submissions, 8+ FTEs Saved | Prior Authorization Automation Agentic AI cut prior authorization submission time 85% and freed 8+ FTEs for a multi-state pain management network, while denials dropped to under 7%. 8+FTEs saved. Learn how agentic AI freed 8+ FTEs for a multi-state pain management network and its RCM team. ClientPTCoA WorkflowPre-Auths Headline result8+ On this page - [Project Scope](#project-scope) - [Challenge | Volume & Timing](#challenge-volume-timing) - [Solution | Prior Authorization Automation](#solution-prior-authorization-automation) - [1. PA Data Intake & Submission Automation](#1-pa-data-intake-submission-automation) - [2. Follow-Up Automation](#2-follow-up-automation) - [3. Built In Enterprise-Grade Compliance](#3-built-in-enterprise-grade-compliance) - [Results](#results) - [Summary](#summary) Book a callWant results like these? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Project Scope Not so long ago, a fully comprehensive pain management practice network contacted us to solve one of their major bottlenecks - prior authorizations. While they operate in over 15 clinics across two states, their RCM team needs to ensure timely reimbursements and smooth administrative workflows. After all, pain management is a high-volume & high-reimbursements, as well as high-repetition & fast-burnout field. That’s why they decided to invest in RCM automation. ## Challenge | Volume & Timing In this case, weekly volumes were rising faster than staffing capacity, and payer rules were shifting month-to-month, creating inconsistent turnaround times and unpredictable AR impact. Each request required navigating multiple portals, reconciling conflicting requirements, and repeating data entry across disconnected systems. Each week, their RCM team was losing hours to thousands of repeatable authorization requests across commercial payers like Medicare Advantage plans, and Medicaid MCOs. This created natural variability in turnaround times and made operational planning increasingly difficult. High volume combined with payer diversity meant that even small inconsistencies slowed the overall cycle and created rising administrative load. On the top of that, our RCM workshop excavated a few additional improvement fields including i.e. denials management automation. As the company continued to scale, manual throughput could no longer keep pace with demand, prompting a shift toward automation to stabilize processing speed and ensure consistent output across all payers. Every missing field meant more delays, more denials, and more rework. Hiring more staff wasn’t a smart solution due to training lag - it would only bloat Cost-To-Collect (CTC). That’s when they turned to us for Agentic AI Automation. ## Solution | Prior Authorization Automation Since every insurer behaved differently our AI automation system had to scale predictably. After mapping their operational flow and system, our team built a fully autonomous AI agent for prior authorization automation. We built a modular structure with: - unified GUI library, - reusable objects for portal navigation, - unified API interactions (AWS, registries, password vaults), - client-specific activity library, - automated logging & exception pipelines. To top that off, our PA automation is capable of managing both submissions and follow-ups across fragmented payer systems. Here are its two major components: ### 1. PA Data Intake & Submission Automation Unlike old-school batch processing, we trained the AI agent to activate the moment a new order hits the EHR. Unlike old-school batch processing, we trained the AI agent to activate the moment a new order hits the EHR. Before contacting any payer, the agent verifies provider identity and active status using the NPI Registry, then proceeds with payer-specific eligibility checks. Once the data is verified, the agent securely logs into the payer portal. It navigates the interface and auto-fills provider details. It also transfers CPT/HCPCS strings, and ICD-10 codes with 100% accuracy. Beyond data entry, the agent handles payer-specific prior authorization questions designed to assess medical necessity and utilization risk. This includes checking defined lookback windows for similar services, verifying prerequisite exams or procedures, and supplying supporting context required by each payer’s PA form. Finally, it downloads the submission PDF and attaches it–along with the audit logs–directly to the client's CRM and EHR. The real engineering challenge was portal instability. Payer websites change constantly. To handle this, we avoided rigid scripts and built a Modular Activity Library instead. By using reusable objects for navigation and API calls, the system breaks less often. This approach also made scaling much faster. In fact, it cut the time required to add a new payer workflow by 70% – saving 8+ FTEs. #### How Does the PA Data Intake and Packet Submission Automation Works? - Validates patient & provider data using NPI Registry. - Logs into the payer portal and auto-fills all required fields. - Transfers CPT/HCPCS & ICD-10 codes. - Submits the PA request. - Saves the submission PDF & attaches it to CRM/EHR. - Updates PA status, timestamps, and audit logs. - Flags only true exceptions for staff review. ### 2. Follow-Up Automation The second AI agent solved the RCM team’s biggest distraction: the endless loop of checking for updates. In a manual workflow, staff waste hours logging into portals just to see a "Pending" status. We automated that entirely. The agent runs a multiple sweeps a day of all open cases. It signs into the insurer portals and scans for changes. It doesn't just look for a status code; it reads the actual approval or denial messages. Then, it writes that outcome directly into the CRM or EHR. If the claim is still processing, the agent notes it and moves on. If it finds a denial or a request for more info, it instantly alerts the staff. This means your team stops chasing statuses and only touches a case when there is an actual problem to solve. How Does the PA Follow-up Automation Works? - Signs into insurer portals. - Retrieves updated statuses. - Reads approval/denial messages. - Records the outcome in CRM/EHR. - Alerts staff only when human review is needed. ### 3. Built In Enterprise-Grade Compliance To top that off, every automated prior authorization request generated a complete, audit-ready record including: timestamps, and source-system logs. All workflow actions are captured automatically. Moreover, payer confirmation receipts are stored in AWS with immutable logging. A PDF of each submission gets downloaded and attached directly to the CRM and EHR and every field change is tracked with full history; and all resubmissions or corrections are versioned automatically. The result is a PA process that is fully transparent, fully traceable, and fully defensible during audits or payer reviews. ## Results Before automation, 9–16% of this clients' denials were directly linked to simple, avoidable mistakes like missing notes, incomplete demographics, coding mismatches, expired auth numbers, and inconsistent payer formatting. These were operational misses, not medical-necessity disputes, and they directly prolonged reimbursement cycles across UHC, BCBS, Aetna, and multiple Medicaid MCOs. The AI agent eliminated these inconsistencies by standardizing every submission across portals. Clinical documents, codes, and eligibility data were validated automatically, and requests were filed on time, in the exact payer-specific structure required. As a result, preventable PA-related denials fell to 4–7%, immediately improving clean-submission rates and shortening the revenue cycle. Fewer avoidable denials meant fewer RFIs, fewer reworks, and a more predictable flow of payments–turning a chronic operational leak into a controlled, measurable process. What once required entire teams now takes a few minutes to compute. One AI agent can handle dozens of PAs simultaneously with no drop in accuracy. Metric | Before Automation | After Automation | Δ Impact | Avg PA packet submission time | 10–15 minutes | 1–2 minutes | ↓ 85% | Follow-up cycle time | 2–5 days | 1h after confirmed by payer | ↓ 48–80 hours | Daily PA backlog | 200–600 cases | 0–30 cases | Cleared | Error rate on submissions | ~11% | <1% | ↓ 90% | Staff capacity | 10–11 FTE | 2–3 FTE | 4–5× throughput | ### Summary In this particular project, shrinking the prior authorization processes from hours to minutes had a direct downstream effect on liquidity. In many specialties, prior authorization routinely adds five or more days to the time it takes to begin treatment or schedule a procedure. With administrative barriers removed, the average time-to-appointment dropped by 1.8 days, creating a tighter alignment between demand and capacity. This operational shift pulled an estimated $40,000 to $60,000 in revenue recognition forward every week, simply because provider schedules were no longer held hostage by pending paperwork. The stability of the schedule improved just as much as the cash flow. Last-minute cancellations and financial holds–often caused by stagnant portal requests–dropped significantly. Patients received care faster, and the clinic stopped losing slots to administrative friction. With an autonomous core submission pipeline, our client is currently pivoting to high-complexity workflows. The next phase involves our Denials Management Automation and a few additional minor automation including payments posting correspondence. PA automation became the foundation of their new RCM operating model. | Before Automation | After Automation | Δ Impact | Avg PA packet submission time | 10–15 minutes | 1–2 minutes | ↓ 85% | Error rate on submissions | ~11% | <1% | ↓ 90% | Staff capacity | 10–11 FTE | 2–3 FTE | 4–5× throughput | Submitting prior authorizations by hand too? 30 minutes with Karl, our CTO, or Bart, our Head of AI. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) More work ## More case studies Real deployments, with the numbers our clients measured. [ Denials Management Up to 80%higher throughput in RCM, with a custom laboratory information system data exchange. ### Up to 80% Higher Throughput in RCM Read the case study → ](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation)[ Eligibility Checks 100%ROI in 23 days from eligibility automation plus Denial Hunter, with $180,000 in savings after year one. ### 100% ROI in just 23 days. We Automated Eligibility Checks! Read the case study → ](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) [All case studies →](https://www.flobotics.io/case-studies) --- # 90% Faster Packet Submissions | Prior Authorization Automation Canonical: https://www.flobotics.io/case-studies/90-faster-packet-submissions-prior-authorization-automation Published: 2026-04-08 Updated: 2026-04-08 --- [Home](https://www.flobotics.io/)/[Client Results](https://www.flobotics.io/case-studies)/90% Faster Packet Submissions | Prior Authorization… Pre-Auths # 90% Faster Packet Submissions | Prior Authorization Automation See how Agentic AI bridged the gap between Laboratory Information Management System (LIMS) and Payer Portals. -90%Faster packet submissions. See how Agentic AI bridged the gap between Laboratory Information Management System (LIMS) and Payer Portals. WorkflowPre-Auths Headline result-90% On this page - [Project Scope](#project-scope) - [Main Challenge | The "Double-entry" Bottleneck](#main-challenge-the-double-entry-bottleneck) - [Solution | Prior Authorization Automation](#solution-prior-authorization-automation) - [How the Prior Authorization Automation Works?](#how-the-prior-authorization-automation-works) - [Results](#results) - [Summary](#summary) Book a callWant results like these? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Project Scope In late 2024, we partnered with a high–volume Genetic Diagnostic Lab in the Midwest. They specialize in hereditary cancer screening and prenatal testing – a sector where reimbursement rules are notoriously complex and Prior Authorizations (PA) are mandatory for almost every sample. While the lab utilized a leading third–party diagnostic management portal to handle the complexity of genetic PAs and patient cost estimates, the process itself was still manually driven. Their Accessioning Team was drowning, spending 40% of their day manually transferring data from their Lab Information Management System (LIMS) into the external portal. The goal was simple: To eliminate the "double–entry" tax and make most of the PA packet submission lifecycle – all without replacing their existing tech stack. (This case has been anonymized for confidentiality.) ## Main Challenge | The "Double-entry" Bottleneck In genetic testing, a sample cannot enter the "Wet Lab" (processing) until the administrative work is clear. This client’s LIMS (where the order lives) and the Third–Party PA Portal didn’t speak to each other. For every single test (CPT 81408, 81211, etc.), a staff member had to open the LIMS, copy the Patient Demographics, Insurance Info, and CPT codes, switch tabs, and paste them into the PA portal. This took 8–12 minutes per case. With volumes exceeding 500 accessions per week, the lab was losing ~80 hours of labor weekly just to data entry. These figures capture only hands-on data entry time and exclude the often longer delay while samples waited in queue for staff availability. Samples were sitting in the refrigerator waiting for administrative clearance. Turnaround Time (TAT), the lab’s most competitive metric, was suffering not because of science, but because of data entry speed. In short: This client needed an automation that was both: - a "Digital Bridge" – which moves data from LIMS to the Prior Authorization portal instantly 24/7, - a “Digital workforce” – that takes the strain off the RCM team members' backs. ## Solution | Prior Authorization Automation We didn't need to rebuild their infrastructure. We just fully automated it. We started with deploying an agentic AI workflow orchestration to act as the middleware between the LIMS and the external PA portal. This was the aforementioned “digital bridge". The solution operates on a strictly event–driven architecture designed to eliminate the latency between sample receipt and administrative clearance. We also made this PA automation bi–directional. Once the submission is logged, the agent waits to capture the "Patient Cost Estimate" generated by the portal, scrapes this specific dollar amount, and writes it directly back into the LIMS. This ensures that the billing team has immediate, real–time visibility into out–of–pocket expectations without ever needing to leave their primary system or log into a third–party site. Instead of manual batches, the agent continuously monitors the LIMS database and triggers the automation sequence the moment a sample is accessed and marked as “Received.” On top of that it immediately extracts the necessary Patient PHI, NPI validation, ICD–10 diagnosis codes, and the required Genetic CPT panels. The agentic AI automation then uses a secure browser to interface directly with the external PA portal, via the "New Case" wizard to input data and select test menus with absolute fidelity to the original requisition. It is worth noting that genetic testing often requires attaching clinical notes (Family History). The Agent was configured to locate the PDF requisition in the LIMS, verify it matches the patient, and upload it directly to the PA portal's documentation tab. ### How the Prior Authorization Automation Works? - Listens: Detects new order in LIMS. - Validates: Checks against NPI Registry - Submits: Logs into the PA portal, auto–fills 100% of fields, and uploads clinical PDFs. - Updates: Scrapes the PA Status (Approved/Pending) and Cost Estimate. - Syncs: Writes the Auth Number and Estimate back into the LIMS. - Alerts: If the portal flags "Prior Auth Not Required" or "Info Missing," the agent tags the case in the LIMS for human review. ## Results The impact was immediate. By removing the manual entry barrier, the "Time to Wet Lab" (the time from sample receipt to testing start) dropped drastically. The backlog of samples waiting for admin clearance dropped to zero. Transcription errors (typos in Member IDs) were eliminated, reducing downstream denials. The automated sync of "Cost Estimates" allowed the lab to collect copays upfront more effectively, improving collections by 15%. In short: Our event-driven agent significantly improved RCM team capacity. Metric | Manual Process | Automated Agent | Impact | Avg Handling Time | 8–12 mins/case | <1 min/case | ↓ 92% | Daily Capacity | ~40 cases/FTE | Unlimited (Scalable) | Uncapped | Error Rate | 6–8% (Typos) | 0.2% | Clean Data | LIMS Sync | Manual / Delayed | Real-time | Instant Visibility | ### Summary What was once a manual chokepoint is now a silent, invisible utility. By deploying Prior Authorization Automation, this diagnostic lab didn't just save money on data entry; they improved their competitive advantage by delivering results to patients faster. This project proves that you don't need to replace your portals to fix your workflow–you just need an Agent to manage them. Metric | Manual Process | Automated Agent | Impact | Avg Handling Time | 8–12 mins/case | <1 min/case | ↓ 92% | Daily Capacity | ~40 cases/FTE | Unlimited (Scalable) | Uncapped | Error Rate | 6–8% (Typos) | 0.2% | Clean Data | Building prior authorization packets by hand too? 30 minutes with Karl, our CTO, or Bart, our Head of AI. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) More work ## More case studies Real deployments, with the numbers our clients measured. [ Denials Management Up to 80%higher throughput in RCM, with a custom laboratory information system data exchange. ### Up to 80% Higher Throughput in RCM Read the case study → ](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation)[ Eligibility Checks 100%ROI in 23 days from eligibility automation plus Denial Hunter, with $180,000 in savings after year one. ### 100% ROI in just 23 days. We Automated Eligibility Checks! Read the case study → ](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) [All case studies →](https://www.flobotics.io/case-studies) --- # Halving Monthly Backlog – Eligibility Automation in Action Canonical: https://www.flobotics.io/case-studies/halving-monthly-backlog---eligibility-automation-in-action Published: 2026-03-08 Updated: 2026-08-03 --- [Home](https://www.flobotics.io/)/[Client Results](https://www.flobotics.io/case-studies)/Halving Monthly Backlog – Eligibility Automation in Action Eligibility Checks # Halving Monthly Backlog – Eligibility Automation in Action Eligibility verification automation cut manual work over 90% and dropped check time from 5 minutes to about 1 minute per patient, at scale. +50%Restored capacity. See how AI automation simplified eligibility checks across multiple systems and halved monthly backlog. WorkflowEligibility Checks Headline result+50% On this page - [Project Scope](#project-scope) - [Main Challenge | Keeping the Pace](#main-challenge-keeping-the-pace) - [Solution | Eligibility Checks Automation to the Rescue!](#solution-eligibility-checks-automation-to-the-rescue) - [How does the eligibility checker work?](#how-does-the-eligibility-checker-work) - [Results](#results) - [Summary](#summary) Book a callWant results like these? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Project Scope In early 2025, we partnered with a fast-growing U.S. health-tech company to automate one of their key RCM processes - eligibility checks. Verifying patient eligibility and active coverage across multiple payer portals consumed hours of manual labor every day. Their RCM team was overwhelmed, spending most of their time verifying thousands of insurance details. As the verification queue grew, eligibility checks became a serious bottleneck. That’s when automation became the natural next step. (This case has been anonymized for confidentiality.) ## Main Challenge | Keeping the Pace Every RCM leader knows that bad data = higher CTC rates. Missing or incorrect PHI – such as patient identifiers, coverage details, or demographic data, always results in one or more of the following: - Decreased process efficiency. - Lowered Net Promoter Score (NPS), - Hours lost to rework and payer follow-ups, In this particular case, the RCM team relied on a batch-style eligibility workflow, which delayed updates and inflated backlogs. On top of that their custom built platform relied on multiple disconnected systems for patient, provider, and payer data. The fragmentation forced constant system-hopping and double entry – a direct driver of rising Cost-to-Collect (CTC). Hiring more people was neither sustainable nor strategic. In short: Pathways between systems weren’t integrated, coverage details were often outdated, and copay amounts were calculated manually. Each verification was taking around five minutes. Multiply that by thousands of patients every week, and you’ll understand the challenge this client was facing. This RCM team needed a scalable, accurate, and compliant way to automate the verification process: - One that would connect payer portals, internal systems, and EHRs seamlessly; - One that would run 24/7 without bloating CTC or blowing the budget; - One that was crafted by our devs team - to put it simply. ## Solution | Eligibility Checks Automation to the Rescue! Our goal was clear: automate insurance verification end-to-end – with full accuracy, auditability, and HIPAA compliance. The board outlined three priorities: - Reduce manual workload and verification time, - Prevent denials linked to incorrect or expired coverage, - Lower the overall CTC without growing headcount. After a series of process discovery workshops, we began to build. The first step was setting up the architecture on Amazon Web Services (AWS) – a comprehensive cloud platform offering storage, databases, and computing power. Then, we followed it with setting up an automation framework platform, which allowed us to automate processes. In a few short weeks, we designed a tailored-to-needs Eligibility Checks Automation System. The automation now works across multiple payer portals and middleware systems – even those without APIs – performing real-time checks on insurance coverage, copays, and deductibles. The process runs fully unattended on virtual machines orchestrated through the automation platform, ensuring continuous eligibility verification with no human intervention. Each transaction is logged and archived via AWS, maintaining a full audit trail in compliance with HIPAA and PHI security standards. The solution operates fully within HIPAA requirements by restricting all processing to the minimum necessary data: payer details, provider information, patient identifiers (ID and date of birth), and the service type with its procedure code. To top that off, we also ensured strict access controls allowing only authorized AI workflows to access and handle PHI. ### How does the eligibility checker work? When a new patient profile is added or updated, our eligibility checker automatically: - Logs into the relevant payer portals such as Availity, - Validates plan status, effective dates, and benefit coverage, - Extracts copay and deductible information, - Flags inactive or mismatched coverage, - Writes the verified data directly back into the EHR, - Sends alerts via Slack or email for exceptions that require review. “The Flobotics team is knowledgeable, easy to work with, and gets things done. They built a solution that scales effortlessly and works exactly as promised.” - CTO, U.S. Healthcare Platform ## Results The project was a major success. With process automation, eligibility bottlenecks disappeared. With a modest investment, our client eliminated one of the most error-prone steps in their revenue cycle and regained lots of capacity. Their RCM team could finally focus on complex, high-value cases – instead of repetitive verification work. With all verification gates and decision loops we introduced, our client’s data was stored securely and consistently across all systems. We’re especially proud that this specific healthcare company could finally rely on real-time, validated payer information. This minor improvement significantly increased their Net Promoter Score (NPS) It was also designed to scale as patients' volume grows. Too good to be true? Wait until you read about the ROI metrics. The results speak for themselves: - Eligibility check duration dropped by 90% - 5x faster eligibility check than manual handling ### Summary What once was a manual, time-consuming workflow is now a silent background process – just as it should be. By replacing repetitive manual verification with an intelligent and scalable automation layer, the client unlocked significant ROI – saving time, money, and staff capacity. This project shows how automating eligibility verification can completely transform RCM performance in the healthcare industry. Which brings us to the following point: At Flobotics, we skip the fluff, speak from the heart, and stay focused on real outcomes - not hype. Ready to scale without growing headcount? Metric | Result | Manual Work Reduction | Over 90% eliminated | Verification Speed | 5 min → ~1 min per case | HIPAA Compliance | 100%, AWS-based audit logging | Falling behind on eligibility checks? 30 minutes with Karl, our CTO, or Bart, our Head of AI. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) More work ## More case studies Real deployments, with the numbers our clients measured. [ Denials Management Up to 80%higher throughput in RCM, with a custom laboratory information system data exchange. ### Up to 80% Higher Throughput in RCM Read the case study → ](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation)[ Eligibility Checks 100%ROI in 23 days from eligibility automation plus Denial Hunter, with $180,000 in savings after year one. ### 100% ROI in just 23 days. We Automated Eligibility Checks! Read the case study → ](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) [All case studies →](https://www.flobotics.io/case-studies) --- # 70% Faster Claim Turnaround Time (CTT) | Claim Management Automation Canonical: https://www.flobotics.io/case-studies/70-faster-claim-turnaround-time-ctt-claim-management-automation Published: 2026-08-06 Updated: 2026-08-03 --- [Home](https://www.flobotics.io/)/[Client Results](https://www.flobotics.io/case-studies)/70% Faster Claim Turnaround Time (CTT) | Claim Management… Claims Management # 70% Faster Claim Turnaround Time (CTT) | Claim Management Automation SuperBill case study: AI document-to-claim automation cut Claim Turnaround Time 70%, from ~24 hours to ~7 hours, without adding headcount. 70%Faster Claim Turnaround Time (CTT). See how document-to-claim automation accelerated out-of-network reimbursement workflows. WorkflowClaims Management Headline result70% On this page - [About SuperBill](#about-superbill) - [Challenge | Document-to-Claim Bottleneck](#challenge-document-to-claim-bottleneck) - [Solution | Claims Management Automation](#solution-claims-management-automation) - [Summary](#summary) Book a callWant results like these? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## About SuperBill SuperBill is a San Francisco-based ​​medtech company helping healthcare providers manage insurance claims, medical billing & process reimbursements. They provide solutions for healthcare providers (clinics, hospitals) and individual clients. If superbill intake delays your submissions by even one day, this case applies directly to your operation. ## Challenge | Document-to-Claim Bottleneck Before our cooperation, their RCM team reviewed each superbill manually. SuperBill’s staff was spending ~120 hours per week converting unstructured documents into claim-ready records. CPT/ICD codes, provider details, patient demographics, modifiers - it all required tedious work. Every day, the team handled ~300–500 uploaded files, and weekly intake regularly exceeded ~2,000 documents, ranging from PDFs and scanned superbills to emailed images and screenshot invoices. Operationally, the consequences were very familiar to other RCM cases: - incorrect data, - lost documentation - delays before submission, - more requests back to patients for missing fields, - inconsistent code capture that required revision, - and rising aging across the reimbursement pipeline. On top of that, the manual workload varied claim by claim. SuperBill quickly realized that if they wanted to scale, they needed to significantly improve turnaround time (TT). Staffing wasn’t sufficient nor sustainable in this case. At peak volume, their RCM team carried a backlog of ~400–700 claims waiting for document review before they could even enter the claim engine. Claims that should have been prepared the same day were often delayed by several days extending the overall reimbursement timeline for providers relying on the platform. Volume increased faster than staff capacity, and manual review became the gating factor for throughput. Out-of-network reimbursement already carried longer A/R cycles compared to in-network claims, and any delay at the document stage compounded that problem. In short: Claim management automation was inevitable. ## Solution | Claims Management Automation The goal wasn’t to read documents faster–it was to remove document reading from the critical path entirely by leveraging AI. We deployed an AI automation layer that took every incoming document and converted it into a claim-ready record. Our AI agent reads PDFs, images, and structures the data so it fits SuperBill’s claim format and each payer’s rules. It’s able to read data like: - patient demographics, - provider identifiers, - service dates and locations, - CPT/ICD codes and modifiers, - units, charges, and payment information. This removed the need for staff to open files, extract codes, or rebuild claim headers by hand. Most of the workload now moves straight through automation. About 95% of documents pass end-to-end without intervention. Only 5% are routed to specialists for missing fields or edge cases. The large manual prep queue is gone. The team works only on exceptions instead of touching every claim. On top of that, the agent runs continuously. New uploads are processed in 2–5 minutes, even on days with 300–500 documents coming in from patients and practices. That keeps claim intake steady, prevents backlogs, and stabilizes daily throughput. The automation also applies payer-specific formatting so claims enter the billing system in a clean, submission-ready state, reducing rework and downstream corrections. Results Earlier submission directly translated into earlier reimbursement – without adding staff. By removing manual claim-prep tasks at the front of the process, SuperBill was able to focus on the KPI that drives reimbursement speed: Claim Turnaround Time (CTT) Our AI automation cut the document-to-claim cycle from ~24 hours to ~7 hours, reducing claim turnaround time by about 70%. The manual intake queue shrank from roughly 500 pending claims waiting on document review to around 150 at any given time. While individual documents are processed in minutes, end-to-end claim readiness reflects batching, validation, and system handoffs across the intake window. That had a direct financial effect: faster prep meant earlier submission, which meant earlier reimbursement. On top of that, standardizing claim inputs reduced variance across payers, lowering audit and resubmission risk. Daily throughput increased from ~250 claims per day to ~425, so the team could keep up with volume spikes without building a backlog. Error rates tied to document reading and formatting dropped by ~35%, which meant fewer claims sent back for fixes or rework. Employees no longer had to interpret every file or rebuild claim data from scratch. Only about 1–5% of documents now need exception review. Once inputs are structured and consistent, the entire claims cycle becomes more stable – all without adding headcount or forcing providers to change how they send documentation. KPI | Before Automation | After Automation | Impact | Claim Turnaround Time (CTT) | ~24 hours | ~7 hours | ~70% faster | Manual Effort Required | ~120 hrs/week | ~0–5 hrs/week | ~3 FTE reallocated | Daily Throughput | ~250 claims/day | ~425 claims/day | +70% capacity | Document-Related Error Rate | Baseline | ~35% lower | Fewer rework loops | Exception Review Load | High (every claim touched) | Targeted-only (1–5%) | Lower queue volume | ### Summary SuperBill’s case shows the power of document-to-claim automation. When agentic AI handles the extraction and structuring of unstructured inputs, RCM staff can process more claims with fewer delays, reducing turnaround time without changing upstream systems or adding resources. If your team is slowed down by converting patient documents, superbills, or PDFs into claim-ready data, document automation can materially accelerate submissions and stabilize reimbursement timelines. You don’t need new portals or new tools. You just need an Agent between the documents and your claim engine. KPI | Before Automation | After Automation | Impact | Claim Turnaround Time (CTT) | ~24 hours | ~7 hours | ~70% faster | Manual Effort Required | ~120 hrs/week | ~0–5 hrs/week | ~3 FTE reallocated | Daily Throughput | ~250 claims/day | ~425 claims/day | +70% capacity | Turning superbills into claims by hand too? 30 minutes with Karl, our CTO, or Bart, our Head of AI. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) More work ## More case studies Real deployments, with the numbers our clients measured. [ Denials Management Up to 80%higher throughput in RCM, with a custom laboratory information system data exchange. ### Up to 80% Higher Throughput in RCM Read the case study → ](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation)[ Eligibility Checks 100%ROI in 23 days from eligibility automation plus Denial Hunter, with $180,000 in savings after year one. ### 100% ROI in just 23 days. We Automated Eligibility Checks! Read the case study → ](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) [All case studies →](https://www.flobotics.io/case-studies) --- # $50K+ Saved in 1 Month | AI Agent For Denials Management Canonical: https://www.flobotics.io/case-studies/50k-saved-in-1-month-ai-agent-for-denials-management Published: 2026-08-06 Updated: 2026-08-03 --- [Home](https://www.flobotics.io/)/[Client Results](https://www.flobotics.io/case-studies)/$50K+ Saved in 1 Month | AI Agent For Denials Management Denials Management # $50K+ Saved in 1 Month | AI Agent For Denials Management AI-driven denials automation cut RCM rework 90%, dropped claim processing from 6 minutes to 30 seconds, and delivered $90K+ in monthly savings. $50K+Saved in 1 Month. Discover AI automations that reduce 90% of manual re-work for RCM teams. WorkflowDenials Management Headline result$50K+ On this page - [Main Challenge | Scaling](#main-challenge-scaling) - [The Bottom Line](#the-bottom-line) - [Solutions | AI Automation to the Rescue!](#solutions-ai-automation-to-the-rescue) - [Denials Handling System](#denials-handling-system) - [Posting Correspondence Automation](#posting-correspondence-automation) - [The Outcomes](#the-outcomes) - [Summary](#summary) Book a callWant results like these? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) Project Scope At the beginning of 2025, a recognizable medtech startup from California contacted us for two things: - Automation opportunities audit - Denials management automation They mainly focus on disease detection improvements and molecular diagnostics, but as it is common in modern times, their growth path leads through technological improvement - in this case process automations. ## Main Challenge | Scaling Scaling Revenue Cycle Management (RCM) operations is quite challenging. Growing denial rates, delayed reimbursements, overextended staff - we bet that sounds familiar. It’s a very common case among medtech startups in the U.S. After all: Higher claims volume = Back-office pressure In this case, the main part of the workload consisted of manual correspondence, data re-entry, and reconciliation across Xifin and payer portals. On top of that, each day, more than tens of new claim denials popped up. They all required handling - entirely by hand. When UnitedHealthcare introduced PIB12 and PI96 denial codes, the claims backlog surged past 3,000 records. Each one required validation, reconciliation, and resubmission. What would your company do in such a situation? Hiring more people wouldn’t change much. After all, the main goal was to scale the operations, not to double the digits on the charts, right? Their team quickly realized that. ### The Bottom Line The MedTech startup we're describing needed a scalable way to process data and accelerate reimbursements. Not only to keep the momentum, but most importantly, to secure & stabilize the revenue stream - all without bloating the CTC metrics. They instantly knew that their situation requires: - Improved operational capacity, - Cost To Collect (CTC) optimization, - Precise end-to-end denial handling. In short: The investment in automation was inevitable. ## Solutions | AI Automation to the Rescue! To scale efficiently, they needed automation that could handle both: - structured processes (like Xifin workflows and payer integrations) - unstructured processes (such as documents processing, correspondence, etc.). The main goal of our task was clear – eliminate the repetitive, time-consuming tasks that were bogging down the RCM team. So far, the cooperation resulted in the following targeted AI automations: Challenge | Automation Solution | Denial Overload | Denials Handling System | Backlog Surge | PIB12 / PI96 Denial Reconsiderations | Manual Re-submissions | UHC Resubmitter | Paper Mailroom | Posting Correspondence Automation | ### Denials Handling System At first, we’ve decided to build an automation system that takes over the repetitive and error-prone parts of claim handling. We aimed to find and classify denial types, pull missing or corrected data, fix claims, and resubmit them to payer portals automatically. Only the complex cases that need human input were meant for the RCM team. We designed the entire flow to move claims forward without manual work. How Denials Handling Automation works: Fig. 01 · Denials UHC resubmitter Automated denials management and UHC resubmission - 01Identifies the denial response - 02Classifies and matches the error type - 03Retrieves missing or corrected data - 04Fixes and resubmits denials - 05Sends the rest to a person for review #### Results: Denials that used to delay payments for days are now resolved in seconds - giving the team more time to focus on the cases that really need their attention. - Manual rework eliminated for 90% of cases - Only the last 10% routed to staff - Small human errors completely removed #### PIB12/PI96 Denial Reconsiderations Remember the piling up PIB12/PI96 denials issue? A backlog of over 3,000 claims created an urgent need for another automation - so we moved fast. Within three weeks, the PIB12/PI96 Denial Reconsiderations automation cleared 80% of the backlog and then became a daily automation. Here’s how it works: The automation retrieves denied accessions from Xifin, extracts key details, and downloads the related medical records. It then matches each record to the correct UnitedHealthcare (UHC) claim, uploads the required documentation, and submits the reconsideration request. Once complete, the system updates the claim status in Xifin and sends execution summaries via Slack and email - keeping the RCM team fully informed. Today, the automation handles around 50 denials per day, covering reason codes M127, N705, PI252, CO252, N393, and OA252. The success of this initiative also led to ongoing collaboration with UHC. #### Results: - Manual denials handling reduced from 6 min → 30 sec per case - ~4 hours saved daily - More RCM FTEs for complex appeals Resubmiton Module Automation During PIB12/PI96 testing, multiple claims required re-submission. The scope was extended to include a resubmission module, developed in just 1 week, combining API efficiency with GUI flexibility. It was also re-usable for future denial types - making it future-proof. #### Results: - ~1,200 failed claims automatically updated - ~120 hours saved for the RCM team - Additional 2 hrs/day saved on PIB12/PI96 reconsiderations ### Posting Correspondence Automation The described startup expanded their automation to mainly handle payer correspondence using UiPath and AI. The goal for our automation was clear: Process all of incoming mail the same day - with no human input. Hand in hand with their internal IT team we’ve created a system that digitizes physical mail, sorts documents into Google Drive, and reads and extracts key data automatically. It was also designed to map reason codes and update claim records in Xifin, keeping everything accurate and up to date without manual effort. How Posting Correspondence Works? Fig. 02 · Posting Correspondence Posting correspondence automation - 01Digitizes each documentOCR - 02Extracts key fieldsAccession, patient, dates, payer, reason code - 03Queues a transaction - 04Posts the documentThrough the user interface #### Results: - 95% less manual post correspondence processing - Accelerated claim adjudication and payment - 24/7 AI mailroom - no extra headcount - Billing team redirected from admin work to core finance activities ## The Outcomes So far, denial management and post correspondence automation has delivered promissing results. Our partner saved above $90,000 to date, while replacing over 2,300 hours of manual work with fully automated processes. Nearly 90% of all manual rework has been eliminated, leaving only the most complex 10% of cases for staff review. Within just three weeks, automation cleared 80% of a 3,000-claim denial backlog, improving operational throughput. Processing time for each claim has dropped by 90%, from six minutes to roughly 20–30 seconds, and reimbursement cycles have been shortened by four days. The transformation has also changed how the team works. Freed from repetitive tasks, team members now focus on higher-value analysis, appeals, and strategic improvements. ## Summary This particular case shows that investing in AI automation and RPA brings multiple profits. With 15 automations operating so far (more underway), the improvement is visible almost across every part of the revenue cycle management field. Current roadmap includes Availity integration, LLM-based automation for HR, and expanding AI to contract management. Which brings us to the following point: At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management - no generic bots here. Metric | Result | Manual Work Reduction | 90% eliminated | Claim Processing Speed | 6 min → 30 sec per case | RCM Backlog Cleared | 80% in 3 weeks (3,000 transactions) | Monthly Time Savings | 500+ hours saved | Monthly Savings | Over $90,000 and growing | Working denials by hand too? 30 minutes with Karl, our CTO, or Bart, our Head of AI. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) More work ## More case studies Real deployments, with the numbers our clients measured. [ Denials Management Up to 80%higher throughput in RCM, with a custom laboratory information system data exchange. ### Up to 80% Higher Throughput in RCM Read the case study → ](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation)[ Eligibility Checks 100%ROI in 23 days from eligibility automation plus Denial Hunter, with $180,000 in savings after year one. ### 100% ROI in just 23 days. We Automated Eligibility Checks! Read the case study → ](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) [All case studies →](https://www.flobotics.io/case-studies) --- # 300,000% ROI for T Bank | Finance & Banking Canonical: https://www.flobotics.io/case-studies/t-bank-automation Published: 2026-08-06 Updated: 2026-08-03 --- [Home](https://www.flobotics.io/)/[Client Results](https://www.flobotics.io/case-studies)/300,000% ROI for T Bank | Finance & Banking Business process automation (Non-healthcare) # 300,000% ROI for T Bank | Finance & Banking T-Bank results: an RPA bot processed SBA loan applications in 6 seconds each, saving 200+ hours of manual work and generating a 300,000% ROI. 300,000% ROILearn how one, simple RPA procedure resulted in 300,000% ROI WorkflowBusiness process automation (Non-healthcare) Headline result300,000% ROI On this page - [Client](#client) - [The Challenge](#the-challenge) - [The Solution](#the-solution) - [Results:](#results) - [The Outcome](#the-outcome) Book a callWant results like these? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Client [T-Bank](https://t.bank/) is a financial institution based in Texas. T-Bank is a partner with an entrepreneurial credit philosophy designed with business and practice needs in mind. Ranked among the Top 200 Healthiest Banks in the US in Lending Tree’s 2021 annual analysis, T-Bank - a Tectonic Financial company - serves clients with dedicated personal attention and cutting-edge technology. It is one of the top SBA loan providers in the nation. ## The Challenge The SBA Paycheck Protection Program is a $699-billion US governmental loan program introduced to address the COVID-19 crisis. The applications for the first round of funding were open for a limited time. Once the loan funds were depleted, the applicants had to wait for another funding pool to open. In the meantime, the application submission website remained unavailable to users. T-Bank wanted to enable business owners to apply for as many loans as possible before the funding ran dry. The institution turned to Flobotics to build a Robotic Process Automation solution to achieve this. The implementation had its specific challenges. First of all, to set up the RPA, the loan submission website had to be available. To that end, the Client asked Flobotics to stay on standby, waiting for the next pool of loans to launch and the website to reopen. Another issue was related to the server side of the website. Due to the overwhelming number of visitors, the web app would often crash or freeze on loading at the end of the application submission process. The issue was forcing the users to input the same information repeatedly, leading to excessive time waste and triggering user frustration. For the above reasons, time was a crucial factor in project implementation. We had to act at full speed, applying changes directly on a live website. ## The Solution We set to work the minute the new pool of loans became available, and the program’s website reopened. To speed up the submission process, we developed an attended robot (working alongside a human operator) to fill out the application form in a flash, replacing the manual process. Our RPA robot worked by extracting batch customer data from a CSV file, navigating to the website, and populating the loan application forms with the applicant information. At the very end, the human operator stepped in, clicking the ‘Submit’ button to confirm sending the application. By streamlining the procedure, RPA cut the entire application submission process down to 6 seconds! Before completing the form by hand used to take 10-15 minutes. The new solution also made it possible to bypass the issue of overloading the servers. In case of a crash, the bot would remain on hold until the website recovered. It would then immediately start filling out the form – saving the users the time and frustration of repeatedly submitting the same information. Our robot can fill out the loan application in just a few seconds. ### Results: Metric | Value | Manual labor saved | 200+ hours | Revenue from submitted applications | $5M | ROI generated | 300,000% | Bot development time | 8 hours | Their availability was impressive. They worked through the middle of the night during a weekend to get it done for us. This project wouldn’t have been possible without that access. David Clifford CSO of Tectonic Financial ## The Outcome Through automation, the Client saved over 200 hours of human labor, allowing business owners all over the USA to apply for over 1,000 loans. This represents about $100,000,000 worth of applications and $5,000,000 in the organization’s revenue. The entire development took about 8 hours, so the Client saw the Return on Investment in the project within seconds after running the robot. Not only did we enable our Client to generate substantial revenue, but we did it on a fraction of the development cost – without engaging employees on the Client’s side in the project. We have a lot of ideas on how to automate your [accounting](https://www.flobotics.io/business-process-automation) or finance processes. Think of implementing RPA in your finance company. At Flobotics we focus exclusively on automating what matters most in U.S. healthcare revenue cycle management – no generic bots here. Ready to scale without growing headcount? Let’s talk! 👉 [Book a 30-minute call](https://www.flobotics.io/book) 300,000% ROI Processing applications by hand against a deadline? 30 minutes with Karl, our CTO, or Bart, our Head of AI. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) More work ## More case studies Real deployments, with the numbers our clients measured. [ Denials Management Up to 80%higher throughput in RCM, with a custom laboratory information system data exchange. ### Up to 80% Higher Throughput in RCM Read the case study → ](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation)[ Eligibility Checks 100%ROI in 23 days from eligibility automation plus Denial Hunter, with $180,000 in savings after year one. ### 100% ROI in just 23 days. We Automated Eligibility Checks! Read the case study → ](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) [All case studies →](https://www.flobotics.io/case-studies) --- # 2 FTEs saved via full invoice processing automation case study | Cohen & Company Canonical: https://www.flobotics.io/case-studies/cohen-rpa-in-accounting-automation-case-study Published: 2026-04-08 Updated: 2026-04-08 --- [Home](https://www.flobotics.io/)/[Client Results](https://www.flobotics.io/case-studies)/2 FTEs saved via full invoice processing automation… Business process automation (Non-healthcare) # 2 FTEs saved via full invoice processing automation case study | Cohen & Company See how our RPA team fully automated invoice processing, streamlined Cohen's accounting and freed up the time of two full-time employees 2 full FTEs2 FTEs ClientCohen & Company WorkflowBusiness process automation (Non-healthcare) Headline result2 full FTEs On this page - [Client](#client) - [The challenge](#the-challenge) - [The solution](#the-solution) - [The outcome](#the-outcome) Book a callWant results like these? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Client Cohen & Company offers a full range of accounting, tax, and consulting services to clients in the United States and internationally, focusing on private companies, the investment industry, real estate, and private equity. ## The challenge Cohen & Company approached us with a clear vision of which processes should be automated using RPA, including invoice creation and upload, invoice data extraction and upload, and purchase order data creation and upload. Despite their importance to the business, all of these processes relied heavily on manual work, creating employee stress and a constant risk of errors. ## The solution We first advised on the appropriate automation technology and selected UiPath as a secure, fast, and industry-standard platform that enables rapid implementation. Because multiple processes were involved, the solution was designed modularly. For invoice processing, two robots were implemented: one responsible for generating PDF invoices according to defined business rules, and another responsible for importing the generated invoices into the target system with the correct parameters. Additionally, the automation extracted invoice data from a designated mailbox and inserted it directly into the appropriate system. The same automation logic was applied to purchase order data creation, resulting in a consistent and scalable solution. ## The outcome The automation delivered measurable operational impact, saving the equivalent of two full-time employees per month, or approximately 320 hours of manual work. Instead of processing invoices manually, operators now review exception reports and handle only the few cases where automation requires intervention. This shift allows teams to focus on higher-value, strategic work while maintaining accuracy and process reliability. According to Cohen & Company, the solution met aggressive timelines, stayed within budget, and fully delivered on the project scope. 2 FTEs Processing invoices by hand too? 30 minutes with Karl, our CTO, or Bart, our Head of AI. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) More work ## More case studies Real deployments, with the numbers our clients measured. [ Denials Management Up to 80%higher throughput in RCM, with a custom laboratory information system data exchange. ### Up to 80% Higher Throughput in RCM Read the case study → ](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation)[ Eligibility Checks 100%ROI in 23 days from eligibility automation plus Denial Hunter, with $180,000 in savings after year one. ### 100% ROI in just 23 days. We Automated Eligibility Checks! Read the case study → ](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) [All case studies →](https://www.flobotics.io/case-studies) --- # Canada Satellite | Hundreds of SIM cards & healthy CRM Canonical: https://www.flobotics.io/case-studies/canada-satelite-automation Published: 2026-04-08 Updated: 2026-04-08 --- [Home](https://www.flobotics.io/)/[Client Results](https://www.flobotics.io/case-studies)/Canada Satellite | Hundreds of SIM cards & healthy CRM Business process automation (Non-healthcare) # Canada Satellite | Hundreds of SIM cards & healthy CRM How to automate the processing of hundreds of SIM cards and create a consistent, accurate CRM system? WorkflowBusiness process automation (Non-healthcare) On this page - [Client](#client) - [The challenge](#the-challenge) - [The solution](#the-solution) - [The outcome](#the-outcome) Book a callWant results like these? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Client Canada Satellite provides satellite services and devices, including satellite phones, satellite TV, and satellite internet. With offshore branches such as Africa Satellite, Asia Satellite, Australia Satellite, Europe Satellite, and American Satellite, the company operates globally and supports customers across multiple regions and markets. ## The challenge Canada Satellite sells prepaid and postpaid satellite SIM cards through its online shop, where customer accounts and services are created automatically. The shop backend, however, was unable to handle critical logic related to prepaid SIM balances, expiration dates, and recharge decisions, as well as postpaid usage limits and overage costs that impact monthly invoicing. While the CRM system could track usage, balances, and invoices, checkout and credit card processing had to be executed in the shop backend, creating a disconnect between systems and introducing operational risk, manual work, and billing inaccuracies. ## The solution We implemented an RPA-based automation layer connecting the CRM and shop backend, leveraging the fact that both prepaid and postpaid processes were rule-based with a shared starting point in the CRM and a shared endpoint in the shop system. Automation began with the auto-recharge process, where bots retrieved data from the CRM database, validated it against business rules, and either triggered notifications in case of missing or invalid data or created customers and processed checkout automatically when validation succeeded. The automation handled payment failures by notifying customers via email and satellite SMS and successfully completed paid transactions by writing order details back into the CRM to trigger vendor top-up processes. Full reporting was implemented at every step, with all exceptions, edge cases, and successes reflected in CRM status updates. Building on this foundation, the postpaid process was automated quickly by reusing and extending the existing logic, adjusting database queries, and adding additional scenarios. ## The outcome The automated auto-recharge and postpaid processes now handle hundreds of SIM cards each month, ensuring uninterrupted satellite services that are often critical in emergency situations. Manual, repetitive work was eliminated, freeing Canada Satellite’s teams from error-prone processing and significantly improving operational reliability. At the same time, data consistency across systems increased, resulting in a more unified and healthier CRM environment for Canada Satellite and its global subsidiaries. Activating SIM cards or updating your CRM by hand? 30 minutes with Karl, our CTO, or Bart, our Head of AI. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) More work ## More case studies Real deployments, with the numbers our clients measured. [ Denials Management Up to 80%higher throughput in RCM, with a custom laboratory information system data exchange. ### Up to 80% Higher Throughput in RCM Read the case study → ](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation)[ Eligibility Checks 100%ROI in 23 days from eligibility automation plus Denial Hunter, with $180,000 in savings after year one. ### 100% ROI in just 23 days. We Automated Eligibility Checks! Read the case study → ](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) [All case studies →](https://www.flobotics.io/case-studies) --- # 10,000+ transactions automated monthly | DocPlanner Case Study Canonical: https://www.flobotics.io/case-studies/docplanner Published: 2026-04-08 Updated: 2026-04-08 --- [Home](https://www.flobotics.io/)/[Client Results](https://www.flobotics.io/case-studies)/10,000+ transactions automated monthly | DocPlanner Case Study EHR Integration # 10,000+ transactions automated monthly | DocPlanner Case Study Our RPA system provides interoperability between 10+ different EHR systems (such as iClinic, mMedica, or Arzamed) in four different markets: Spain, Italy, Brazil, and Poland. 10,000+transactions automated monthly ‍ ClientDocPlanner WorkflowEHR Integration Headline result10,000+ On this page - [Client](#client) - [The Challenge](#the-challenge) - [The Solution](#the-solution) - [The Outcome](#the-outcome) Book a callWant results like these? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Client [DocPlanner ](https://web.archive.org/web/20241005064300/https://www.docplanner.com/about-us)is the world’s biggest healthcare platform (and the market leader in 13 countries), serving 90M patients and 280M healthcare professionals and processing over 22M appointments booked via the DocPlanner app monthly. Their app combines the logic of a healthcare marketplace with EHR (Electronic Health Records) functionalities, allowing patients to schedule appointments and medical facilities to manage the visits easily. ## The Challenge DocPlanner had a very well-defined business vision: to increase the number of people using their app (both patients and medical professionals) and become the booking system of first choice in the markets they operate. The main challenge they face is that many medical clinics still utilize outdated, legacy Electronic Health Records systems and are reluctant to change. Although Docplanner can easily be integrated with many of these tools via API, there are EHRs on the market that are particularly hard to integrate. Even when clinics use the DocPlanner solution, they often keep their existing EHR in place, manually moving the data between systems, which requires a lot of manual labor and is prone to mistakes. Sometimes, they are forced to keep the old system due to the lack of certain local functionalities within the DocPlanner app. These were their main scalability bottlenecks. During the solution research, DocPlanner reached out to UiPath, a leading Robotic Process Automation platform. UiPath created a simple PoC of one automation and recommended Flobotics as a development partner. ## The Solution From day one, we recognized the huge potential of bringing automation to DocPlanner, going beyond the assumptions made initially and DocPlanner and the UiPath team. The automation should be built as universally as possible (when it comes to the clinic networks, various EHRs, and multiple markets), allowing product scalability. The goal was to fully [integrate various types of EHRs/EMRs](https://www.flobotics.io/data-integrations) within the DocPlanner app, automatically moving and processing data. The PoC designed by UiPath integrated only one Electronic Health Records system within one facility. We decided to keep the logic but rewrite the automation from scratch. The RPA bot would now automatically extract data and tasks (such as scheduling new appointments) from the EHR and pass them to the DocPlanner app, performing various automated tasks along the way. What data is being automatically migrated? Whatever is needed!: ‍ - detailed patient data (personal info, Social Security Number, etc.) - Patient’s insurance details - Healthcare provider's data (clinics, clinicians, etc) - detailed appointment info (location, service codes) - Actions and tasks (scheduling, canceling, rescheduling, etc.) After three weeks of development, we were ready to deploy the MVP in the first clinic network. Here is a sneak peek of how the automation works: After the immediate success of the first automation, we began to scale it. We built an automation system that can be easily extended to: - new/legacy EHR software used by the clinics, - new facilities using the already integrated software, - different geographic markets. We have also been successfully adding new features to the system, such as: - Automated patient data migration within all the apps connected to the system - Supporting rescheduled and canceled visits - One, universal dispatcher bot for many performer bots - Support of new markets and language versions - adding support for ad-hoc migration of data - an exception system to notify clinic employees about various edge cases of patients/appointments that require their manual action - Automated or manual launch of the bots - reporting and messaging in the native languages of supported markets (ES, PL, IT, PT-BR) - RPA Supervisor Tool for bot monitoring and data visualization (Business Intelligence Dashboards) - Automated system deployment for every new facility added to the system, so there is no need to engage the developer ## The Outcome As of today, our RPA system provides interoperability between 10+ different EHR systems (such as iClinic, mMedica, or Arzamed) in four different markets: Spain, Italy, Brazil, and Poland. Clinicians and back-office workers need way less time to move patients’ data between systems, as they only handle the edge cases—more than 98% are processed automatically, with no mistakes. From DocPlanner's business perspective, implementing RPA drove more users to the app, which meant more business and strengthening their position in the market. As new clinics, software integrations, and markets are continuously being added to the network, the reach and capabilities of the Doclpanner app increase. Thank you, DocPlanner, for your (ongoing) trust!. 10 EHR systems integrated 10,000+ processes automated monthly 98% of cases processed automatically Need to connect systems that have no API? 30 minutes with Karl, our CTO, or Bart, our Head of AI. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) More work ## More case studies Real deployments, with the numbers our clients measured. [ Denials Management Up to 80%higher throughput in RCM, with a custom laboratory information system data exchange. ### Up to 80% Higher Throughput in RCM Read the case study → ](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation)[ Eligibility Checks 100%ROI in 23 days from eligibility automation plus Denial Hunter, with $180,000 in savings after year one. ### 100% ROI in just 23 days. We Automated Eligibility Checks! Read the case study → ](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) [All case studies →](https://www.flobotics.io/case-studies) --- # $100K+ saved in a few days | Mystic River Consulting Case Study Canonical: https://www.flobotics.io/case-studies/mystic-river-consulting-automation Published: 2026-04-08 Updated: 2026-04-08 --- [Home](https://www.flobotics.io/)/[Client Results](https://www.flobotics.io/case-studies)/$100K+ saved in a few days | Mystic River Consulting… Business process automation (Non-healthcare) # $100K+ saved in a few days | Mystic River Consulting Case Study More than 70 weeks of full-time work and over $100,000 in estimated labor cost savings - based on median California salaries $100,000+$100,000 in estimated labor cost savings WorkflowBusiness process automation (Non-healthcare) Headline result$100,000+ On this page - [Client](#client) - [The challenge](#the-challenge) - [The solution](#the-solution) - [The outcome](#the-outcome) Book a callWant results like these? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Client Mystic River Consulting acted on behalf of one of the top debt relief programs based in California, supporting large volumes of tax-related operations for end clients. ## The challenge The company needed to automate two highly labor-intensive processes: pulling client data from the IRS website and filing tax returns. Each step took approximately 45 minutes per client when done manually, and access to the IRS portal was limited to a single set of credentials, preventing parallel work. The situation was further complicated by COVID-19, which significantly disrupted IRS operations, increased processing backlogs, and temporarily prevented the client’s employees from working due to lockdowns. An additional technical challenge was automating two-factor authentication required for IRS access. ## The solution We deployed a coordinated network of RPA robots designed to work sequentially and in parallel. One robot handled logging into the IRS website, retrieving tax documents, scraping the required data, and passing it forward for processing. A second robot automatically filed tax returns for clients using Intuit based on the extracted data. To overcome two-factor authentication, the automation securely accessed a mobile device via VPN and captured rotating authentication codes generated every 30 seconds. The solution was built to be agile, reliable, and resilient under highly constrained operating conditions. ## The outcome During a period when manual operations were severely limited, the automation processed over 1,500 IRS data retrieval cases in just over a week. The first robot completed 1,657 cases with an average processing time of 6 minutes and 28 seconds per case, saving approximately 38.5 minutes per case and more than 1,060 hours of manual work. The second robot completed 2,600 tax return filings with an average processing time of 4 minutes and 25 seconds per case, saving an additional 1,755 hours. Combined, the two robots saved 2,818 hours of manual labor in one week, equivalent to more than 70 weeks of full-time work and over $100,000 in estimated labor cost savings based on median California salaries. The automation delivered continuity, speed, and accuracy at a time when traditional operations were not possible. Pulling data from government portals by hand? 30 minutes with Karl, our CTO, or Bart, our Head of AI. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) More work ## More case studies Real deployments, with the numbers our clients measured. [ Denials Management Up to 80%higher throughput in RCM, with a custom laboratory information system data exchange. ### Up to 80% Higher Throughput in RCM Read the case study → ](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation)[ Eligibility Checks 100%ROI in 23 days from eligibility automation plus Denial Hunter, with $180,000 in savings after year one. ### 100% ROI in just 23 days. We Automated Eligibility Checks! Read the case study → ](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) [All case studies →](https://www.flobotics.io/case-studies) --- # $186,000 of profit in year one | Axpo RPA Case Study Canonical: https://www.flobotics.io/case-studies/axpo-automation Published: 2026-04-08 Updated: 2026-04-08 --- [Home](https://www.flobotics.io/)/[Client Results](https://www.flobotics.io/case-studies)/$186,000 of profit in year one | Axpo RPA Case Study Business process automation (Non-healthcare) # $186,000 of profit in year one | Axpo RPA Case Study We were recommended to Axpo as a process automation agency by our technology partner UiPath, who were familiar with the scale and complexity of projects we had delivered previously. Axpo was experiencing rapid growth that existing processes could not support, relied on manual workflows in billing and switching departments that were no longer scalable, and operated under strict regulatory requirements across multiple energy markets. To address these challenges, we built a network of RPA bots supporting Axpo’s billing and switching operations. $186,000$186,000 of profit in year one WorkflowBusiness process automation (Non-healthcare) Headline result$186,000 On this page - [Overview](#overview) - [Key metrics](#key-metrics) - [Client](#client) - [The challenge](#the-challenge) - [Solution](#solution) - [The outcome](#the-outcome) Book a callWant results like these? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Overview Client: Axpo. Location: Poland & Switzerland. Industry: Green energy (renewables and gas). The project was delivered by a team consisting of a Tech Coordinator, Senior RPA Developer, Agile Coach, and Project Manager. Technology used: UiPath. Timeframe: one year and ongoing. ## Key metrics The engagement resulted in 6.18 FTEs saved, $186,000 of profit generated in the first year, a 147% return on investment, approximately 54,000 automated actions per month, and an average bot accuracy exceeding 90%. ## Client Axpo is Switzerland’s largest producer of renewable energy and an international leader in energy trading and the marketing of solar, wind, and gas power. ## The challenge We were recommended to Axpo as a process automation agency by our technology partner UiPath, who were familiar with the scale and complexity of projects we had delivered previously. Axpo was experiencing rapid growth that existing processes could not support, relied on manual workflows in billing and switching departments that were no longer scalable, and operated under strict regulatory requirements across multiple energy markets. While both UiPath and Power Automate were initially considered, UiPath was selected due to its superior handling of complex processes and stronger orchestration capabilities. Axpo also brought a backlog of automation ideas, which were validated during workshops before development began. ## Solution To address these challenges, we built a network of RPA bots supporting Axpo’s billing and switching operations. One automation focused on generating and sending annual purchase summaries to approximately 1,500 partners by logging into multiple distribution network operator systems, extracting usage data, calculating costs, generating reports, and sending them for approval, reducing 27 days of manual work to a single day. Another automation targeted invoicing and invoice corrections, where bots queried Power BI to identify invoices ready for processing, logged into the CRM system, generated invoices, and corrected existing ones, resulting in more than 600 transactions automated daily and significantly improved invoicing speed and accuracy. ## The outcome After automating the initial set of processes, Axpo achieved savings equivalent to 6.18 FTEs with projected annual savings of $186,000. The collaboration continues, with ongoing identification of new automation opportunities and expansion of the RPA bot network. Axpo, thank you for your trust. If you are looking to automate processes in your energy company, discover what we can do for you. Have a backlog of processes waiting for automation? 30 minutes with Karl, our CTO, or Bart, our Head of AI. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) More work ## More case studies Real deployments, with the numbers our clients measured. [ Denials Management Up to 80%higher throughput in RCM, with a custom laboratory information system data exchange. ### Up to 80% Higher Throughput in RCM Read the case study → ](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation)[ Eligibility Checks 100%ROI in 23 days from eligibility automation plus Denial Hunter, with $180,000 in savings after year one. ### 100% ROI in just 23 days. We Automated Eligibility Checks! Read the case study → ](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) [All case studies →](https://www.flobotics.io/case-studies) --- # 4,685 hours of manual labor saved per year | Sugar Producer Case Study Canonical: https://www.flobotics.io/case-studies/sugar-producer-automation Published: 2026-04-08 Updated: 2026-04-08 --- [Home](https://www.flobotics.io/)/[Client Results](https://www.flobotics.io/case-studies)/4,685 hours of manual labor saved per year | Sugar… Business process automation (Non-healthcare) # 4,685 hours of manual labor saved per year | Sugar Producer Case Study This RPA case study is about one of the largest sugar producers in the world, with annual production of approximately 4.8 million tonnes and factories across multiple European countries. 4,6854,685 hours of manual labor saved per year WorkflowBusiness process automation (Non-healthcare) Headline result4,685 On this page - [Client](#client) - [The Challenge](#the-challenge) - [Selected Solutions](#selected-solutions) - [The Outcome](#the-outcome) Book a callWant results like these? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Client Due to an NDA,we cannot disclose the client’s name or identifying details. The client is one of the largest sugar producers in the world, with annual production of approximately 4.8 million tonnes and factories across multiple European countries. ## The Challenge The client operates as a large, multinational sugar production corporation, processing vast volumes of documents and data daily using SAP. They began their SAP automation journey with another RPA vendor but were not fully satisfied with the results and sought an alternative partner.SAP provided multiple automation opportunities using UiPath, primarily through UI automation and scripting, allowing rapid delivery despite operating across multiple language versions. ## Selected Solutions The collaboration started with automating critical processes in controlling and finance, then expanded into client service, sales, and logistics. Initially, attended bots were deployed to help employees build trust and familiarity with automation, with a gradual transition toward unattended automation. Automated self-invoicing in SAP: A bot enabling vendors to generate SAP invoices during purchases and send them to a dedicated mailbox, handling around 700 cases annually and saving approximately 175 hours per year. EUR-pallet management automation: An SAP bot supporting pallet tracking and settlement by scanning order documentation and updating SAP records. The process was accelerated tenfold, handling about 200 orders per month and saving roughly 40 hours monthly. Sales-support automation: A bot scanning SAP for blocked client orders and missed payments, several times daily, and notifying sales representatives. This saved approximately 3,640 hours annually, processing around 210 documents weekly with a fifteenfold speed increase. Stock index web scraping: A scraping bot monitoring commodity prices from stock index websites in real time, delivering results comparable to APIs at lower cost and saving about 20 hours per month. Quality assurance automation: A bot collecting laboratory reports, extracting and validating data, and migrating it into SAP fully automatically. This reduced handling time from fifteen minutes to seconds per report while supporting more than fifty reports monthly. ## The Outcome This collaboration became one of Flobotics’ longest and most successful partnerships. Initial automation backlogs were cleared, and ongoing process discovery workshops identified new SAP bottlenecks. The client’s Center of Excellence was optimized by gradually shifting from attended to unattended bots, allowing teams to fully leverage RPA across SAP-driven workflows. Processing documents in SAP by hand? 30 minutes with Karl, our CTO, or Bart, our Head of AI. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) More work ## More case studies Real deployments, with the numbers our clients measured. [ Denials Management Up to 80%higher throughput in RCM, with a custom laboratory information system data exchange. ### Up to 80% Higher Throughput in RCM Read the case study → ](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation)[ Eligibility Checks 100%ROI in 23 days from eligibility automation plus Denial Hunter, with $180,000 in savings after year one. ### 100% ROI in just 23 days. We Automated Eligibility Checks! Read the case study → ](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) [All case studies →](https://www.flobotics.io/case-studies) --- # 4x faster account activation | GPS nVision Case Study Canonical: https://www.flobotics.io/case-studies/gps-nvision-automation Published: 2026-04-08 Updated: 2026-04-08 --- [Home](https://www.flobotics.io/)/[Client Results](https://www.flobotics.io/case-studies)/4x faster account activation | GPS nVision Case Study Business process automation (Non-healthcare) # 4x faster account activation | GPS nVision Case Study We implemented an RPA solution for them using UiPath to automate both activation and deactivation workflows and cut account activation from about 16 minutes to 4. 4xfaster account activation: about 16 minutes down to 4. WorkflowBusiness process automation (Non-healthcare) Headline result4x faster activation On this page - [Client](#client) - [The Challenge](#the-challenge) - [The Solution](#the-solution) - [The Outcome](#the-outcome) Book a callWant results like these? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Client GPS nVISION is a Texas-based company specializing in affordable devices and software for tracking cars, trailers, assets, and people. ## The Challenge GPS nVISION needed to automate two critical processes:device and SIM card activation and deactivation. These processes are essential for efficient tracker management and uninterrupted customer access. For activations, customers submitted details via a website form, triggering email requests. Administrators then manually configured accounts and devices across multiple web applications. For deactivations, administrators monitored unpaid subscriptions and manually deactivated devices and SIM cards across platforms. The manual workflows required frequent application switching, repetitive tasks, and significant time investment, often forcing users to seek administrator support. ## The Solution We implemented an RPA solution using UiPath to automate both activation and deactivation workflows. For activations, the robot scans emails for new requests, extracts customer data, creates device entries, activates SIM cards, sets up user accounts, activates GPS trackers across multiple applications, and sends confirmation emails to users. For deactivations, the robot regularly reviews unpaid subscriptions, verifies deactivation status, deactivates trackers and SIM cards across relevant platforms, updates subscription records, and notifies administrators upon completion. The automation integrates GSuite with five client web applications and runs unattended. The client first reviewed an activation-focused demo, and after approval, the deactivation process was added. ## The Outcome The full implementation, including testing, was completed in under three weeks by a single UiPath developer. Activation time was reduced from approximately sixteen minutes to four minutes per request. The automation removed the need for administrator involvement in routine tasks and introduced robust handling of system and business exceptions, with automated email alerts sent when issues occur. Activating and deactivating devices by hand too? 30 minutes with Karl, our CTO, or Bart, our Head of AI. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) More work ## More case studies Real deployments, with the numbers our clients measured. [ Denials Management Up to 80%higher throughput in RCM, with a custom laboratory information system data exchange. ### Up to 80% Higher Throughput in RCM Read the case study → ](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation)[ Eligibility Checks 100%ROI in 23 days from eligibility automation plus Denial Hunter, with $180,000 in savings after year one. ### 100% ROI in just 23 days. We Automated Eligibility Checks! Read the case study → ](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) [All case studies →](https://www.flobotics.io/case-studies) --- # 600x faster account activation | Global View Case Study Canonical: https://www.flobotics.io/case-studies/global-view-automation Published: 2026-04-08 Updated: 2026-04-08 --- [Home](https://www.flobotics.io/)/[Client Results](https://www.flobotics.io/case-studies)/600x faster account activation | Global View Case Study Business process automation (Non-healthcare) # 600x faster account activation | Global View Case Study Global-View needed to streamline the activation of device accounts and SIM cards. We implemented an RPA solution using UiPath and its low-code automation platform, and automated email notifications sent to administrators when issues occur. 600xfaster account activation: about 10 minutes down to 1 second. WorkflowBusiness process automation (Non-healthcare) Headline result600x faster activation On this page - [Client](#client) - [The Challenge](#the-challenge) - [The Solution](#the-solution) - [The Outcome](#the-outcome) Book a callWant results like these? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Client Global-View is a Texas-based company offering GPS tracking devices and cloud-based software to locate cars, trailers, assets, and people. Their platform supports fleet, vehicle, and agent management. ## The Challenge Global-View needed to streamline the activation of device accounts and SIM cards. The existing process required employees to handle activation requests via email, manually create accounts, and activate devices across multiple applications. Frequent system switching, manual logging, and asset lookups made the process slow, error-prone, and confusing for users, who regularly required administrator assistance. ## The Solution Flobotics implemented an RPA solution using UiPath and its low-code automation platform. An intelligent robot was developed to fully automate the activation workflow. The bot monitors incoming emails for activation requests, verifies payment status, validates submitted data, creates user accounts, activates SIM cards and trackers across multiple platforms, and notifies users upon successful completion. The automation integrated GSuite, email and spreadsheets, the client’s internal SIM management system, and the tracker management platform into one unattended process. After three weeks of development, the MVP was deployed and tested across selected facilities. ## The Outcome The full implementation, including testing, was completed in under three weeks by a single UiPath developer. The activation process was reduced from approximately ten minutes per request to just one second. System administrators no longer need to assist with routine activations and can focus on core responsibilities. Additional error handling was implemented to manage system and business exceptions, with automated email notifications sent to administrators when issues occur. Activating accounts and devices by hand too? 30 minutes with Karl, our CTO, or Bart, our Head of AI. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) More work ## More case studies Real deployments, with the numbers our clients measured. [ Denials Management Up to 80%higher throughput in RCM, with a custom laboratory information system data exchange. ### Up to 80% Higher Throughput in RCM Read the case study → ](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation)[ Eligibility Checks 100%ROI in 23 days from eligibility automation plus Denial Hunter, with $180,000 in savings after year one. ### 100% ROI in just 23 days. We Automated Eligibility Checks! Read the case study → ](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) [All case studies →](https://www.flobotics.io/case-studies) --- # 100% ROI within two months | eSky Case Study Canonical: https://www.flobotics.io/case-studies/esky-luggage-tracking-automation Published: 2026-04-08 Updated: 2026-04-08 --- [Home](https://www.flobotics.io/)/[Client Results](https://www.flobotics.io/case-studies)/100% ROI within two months | eSky Case Study Business process automation (Non-healthcare) # 100% ROI within two months | eSky Case Study We designed an RPA bot to automatically monitor airline websites daily, detect policy changes within seconds, and forward relevant updates to an alert system. After gathering requirements during joint workshops, the first version of the bot was developed in Python to quickly validate feasibility. Core automation logic was written in a human-readable form, with complex components such as site sequencing and data preprocessing handled in Python. 100%100% ROI in two months! ClienteSky.com WorkflowBusiness process automation (Non-healthcare) Headline result100% On this page - [Client](#client) - [The Challenge](#the-challenge) - [The Solution](#the-solution) - [The Outcome](#the-outcome) Book a callWant results like these? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Client eSky is a travel tech marketplace operating in over 50 countries and a market leader in Central and Eastern Europe. It offers flights, accommodation, city breaks, holiday packages, and ancillary services such as insurance, car rental, airport transfers, and attractions. ## The Challenge eSky monitors hundreds of airline websites in real time to track ticket prices and customer policies. While price tracking was straightforward, detecting changes in luggage policies proved difficult. These policies are often hidden, updated unexpectedly, and hard to spot, especially during nighttime updates. Outdated luggage policy information led to poor customer experience, complaints, and compensation for misled clients. Manual monitoring by employees was too time-consuming, monotonous, and prone to human error. ## The Solution We designed an RPA bot to automatically monitor airline websites daily, detect policy changes within seconds, and forward relevant updates to an alert system. After gathering requirements during joint workshops, the first version of the bot was developed in Python to quickly validate feasibility. Core automation logic was written in a human-readable form, with complex components such as site sequencing and data preprocessing handled in Python. The result was a powerful yet easy-to-manage automation that significantly reduced complexity and operating costs compared to cloud-based solutions. ## The Outcome Within eight days, an RPA bot was deployed to monitor airline websites for luggage policy changes in real time.A user-friendly dashboard was created in the Robocorp Control Room, providing historical logs and performance charts. Email alerts notify eSky employees only when actual changes occur. Previously, this task required more than one full-time employee if performed daily. Within 32 hours of work, the automation fully replaced the manual process.eSky achieved a return on investment within two months. Watching websites for changes by hand? 30 minutes with Karl, our CTO, or Bart, our Head of AI. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) More work ## More case studies Real deployments, with the numbers our clients measured. [ Denials Management Up to 80%higher throughput in RCM, with a custom laboratory information system data exchange. ### Up to 80% Higher Throughput in RCM Read the case study → ](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation)[ Eligibility Checks 100%ROI in 23 days from eligibility automation plus Denial Hunter, with $180,000 in savings after year one. ### 100% ROI in just 23 days. We Automated Eligibility Checks! Read the case study → ](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) [All case studies →](https://www.flobotics.io/case-studies) --- # Custom algorithm | ePhi Case Study Canonical: https://www.flobotics.io/case-studies/custom-algorithm-for-ephi Published: 2026-04-08 Updated: 2026-04-08 --- [Home](https://www.flobotics.io/)/[Client Results](https://www.flobotics.io/case-studies)/Custom algorithm | ePhi Case Study Business process automation (Non-healthcare) # Custom algorithm | ePhi Case Study See how we delivered an algorithm capable of capturing, organizing, and sharing satellite images with consistent scale, definition, and predictable costs for ePhi - industrial cleaning services company from France. ClientePhi WorkflowBusiness process automation (Non-healthcare) On this page - [Client](#client) - [The Challenge](#the-challenge) - [The Solution](#the-solution) - [The Outcome](#the-outcome) Book a callWant results like these? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## Client ePhi is an environmental services company based in France, providing industrial cleaning services. ## The Challenge ePhi needed to process satellite imagery covering large industrialized areas across multiple cities. The goal was to analyze every square meter of land and identify buildings that could be classified as commercial development targets. Due to the massive data volumes involved, manual processing was not feasible. Initial plans to build custom AI solutions in-house proved too costly and time-consuming. ## The Solution After gathering project requirements, Flobotics selected tools that balanced cost, quality, and development speed. The map scraping process was based on Google Maps, which provided an optimal ratio of satellite image quality to cost. Scraping entire metropolitan areas typically cost less than $90,depending on size, and the API ensured consistent image resolution and dimensions. Low development complexity further reduced overall project costs. Because Google Maps Static API is not designed for machine learning use, we developed a custom algorithm to refine and enrich the image data in real time. The automation was deployed on Amazon Web Services, due to API rate limits requiring long-running processes.AWS enabled fire-and-forget execution, and images were stored in AWS S3 for seamless integration with machine learning services such as SageMaker. ## The Outcome Flobotics delivered an algorithm capable of capturing, organizing, and sharing satellite images with consistent scale, definition, and predictable costs. The images were automatically transformed into structured, readable data for future analysis. The entire development process took less than two months, meeting the client’s time constraints. ePhi, thank you for your trust. Too much data for your team to process by hand? 30 minutes with Karl, our CTO, or Bart, our Head of AI. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) More work ## More case studies Real deployments, with the numbers our clients measured. [ Denials Management Up to 80%higher throughput in RCM, with a custom laboratory information system data exchange. ### Up to 80% Higher Throughput in RCM Read the case study → ](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation)[ Eligibility Checks 100%ROI in 23 days from eligibility automation plus Denial Hunter, with $180,000 in savings after year one. ### 100% ROI in just 23 days. We Automated Eligibility Checks! Read the case study → ](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) [All case studies →](https://www.flobotics.io/case-studies) --- # Claims Processing Automation | AI Agents | RPA Canonical: https://www.flobotics.io/agents/claims-management-automation Published: 2026-02-26 Updated: 2026-02-26 --- [Home](https://www.flobotics.io/)/[What we do](https://www.flobotics.io/what-we-do)/Claims management Workflows we automate # Claims Management Automation We pull the information needed for claims, check it against your billing rules, and send it through your existing submission process. The automation records responses and flags rejected claims or missing updates. Your team handles the cases that need review. [Book a 30-minute call →](https://www.flobotics.io/book)[See client results](#results) Illustration of a claims run. Three completed encounters enter the claim queue. For two, the automation pulls the patient, provider, service and charge data, checks the required fields, submits the claim and saves the acceptance response. The third is missing a required provider identifier, so it is stopped before submission and sent to staff with the reason. The example ends with 2 accepted for processing and 1 needing information. No payment is shown. Claim preparation and submission - Prepare - Check - Submit - Follow up Claim queue · completed visits - A. Rivera · claim C-1041Office visit · Lakeshore PPOAccepted for processing · response saved - J. Okafor · claim C-1042Follow-up visit · Northfield HMOAccepted for processing · response saved - M. Chen · claim C-1043Office visit · Riverside AdvantageStaff review · provider identifier missing 2 accepted for processing · 1 needs information Current claim · A. Rivera · claim C-1041 ClaimC-1041 PayerLakeshore PPO Claim →Clearinghouse← Acknowledgment Encounter dataPulled Required fieldsComplete Submitted14:05 ResponseAccepted Response saved to the claim record Example with made-up patients and claims. Acceptance for processing does not mean payment. PauseReplay Client result · Gentem Health ## How Gentem Health automated claim preparation Gentem Health's team copied and corrected billing data from several EHRs. We built a daily transfer into its billing database. The automation pulls the fields needed for claim preparation and formats them for the receiving system. [Read the Gentem Health case study →](https://www.flobotics.io/case-studies/98-reduction-in-manual-claim-prep-claims-management-automation) Measured results ~30 min →to ~2 minto prepare claim-ready data ~250 h →to 0–5 hof manual preparation work per week ~80% →to ~95%clean claim rate Results from Gentem Health's data-preparation project. These figures do not measure how quickly a payer pays a claim. SuperBill reduced its document-to-claim cycle from about 24 hours to about 7 hours by turning uploaded documents into claim-ready records. [Read the SuperBill case study →](https://www.flobotics.io/case-studies/70-faster-claim-turnaround-time-ctt-claim-management-automation) What we automate ## The tasks from claim preparation to payer follow-up. A claim needs complete information, a submission, and a record of what happened next. These are the tasks we automate. - 01Prepare Pull the information already recorded for the visit. - Find completed encounters or claims ready for preparation. - Pull patient, provider, insurance, service, and charge details from your systems. - [Read existing billing documents](https://www.flobotics.io/healthcare-document-processing) where information arrives in PDFs or images. - 02Check Check the required fields before submission. - Check that required identifiers, service dates, codes, and charges are present. - Apply the formatting and billing checks agreed with your team. - Flag missing information, conflicting records, or possible duplicates. - 03Submit Send the claim and keep its response. - Transfer claim-ready data into your billing system or clearinghouse. - Submit through the supported process and capture acknowledgments. - Save claim references, submission times, and rejection messages. - 04Follow up Keep the claim record current. - Check available payer statuses on an agreed schedule. - Match responses to the right claim and update your records. - Send rejected claims, missing acknowledgments, and overdue updates to staff. We set up the workflow for your systems, payers, and rules. Your team handles missing information and cases that need billing or coding review. A claim accepted for processing has not necessarily been approved or paid. The payer still reviews it. Is it a good fit? ## Claims automation usually pays off when most of these are true. - Your team prepares or submits many claims each day. - Staff copy encounter details between EHRs, documents, and billing systems. - Someone checks clearinghouse and payer responses by hand. - Most claims follow known steps, and you know which cases need billing or coding review. What affects your savings - How many claims and documents you process each month - How long preparation, submission, and status checks take by hand - Which EHR, clearinghouse, and payer connections are available - How often claims need missing information or specialist review - What it costs to build and maintain The return is different for every organization. Schedule a call and we'll give you a quick, honest estimate of whether it's worth it for yours. [Book a 30-minute call →](https://www.flobotics.io/book) How claims automation works with your systems ## The automation moves claim information between your systems and payers. Your staff keep using the systems they know. We use direct connections and clearinghouses where available, or UiPath and Python for work in portals and desktop apps. AI can read uploaded billing documents. Your team reviews information that is missing, unclear, or needs coding judgment. Example of the automation between three places. It pulls complete claim records from the EHR or billing system, submits them through the clearinghouse and writes the acknowledgments back. The third claim is missing a provider identifier, so it goes to the staff review queue before submission. Later, a claim status response shows the first claim as pending payer review. No payment is shown. Your EHR or billing system · claim queue ClaimPatientLast updateStatus C-1041A. Rivera—Ready C-1042J. Okafor—Ready C-1043M. Chen—Ready Flobotics automation Your rulesCheck required fieldsSave acknowledgmentsMissing information → staff Clearinghouse and payer responses Later payer update ClaimPayerTotal chargeSubmit claim Acknowledgment— Your staff · review queue M. Chen · claim C-1043Provider identifier is missing. Check the encounter record. No exceptions yet Monitored and maintained by us. We check the runs and update the workflow when payer connections or your systems change. Example with made-up patients and claims. Submission, acceptance, and payer review are separate steps. PauseReplay Denial appeals and payment posting are separate workflows. Routine correction of rejected claims can be added where the source data and payer rules are clear. Patient data (PHI) What happens to your patient data Your data is safe. Where it runsOn a machine you own: usually a virtual machine on your side, or your own AWS or Azure account. What we storeWe don't store patient data. The automation reads it, uses it and writes the result back. In the rare case PHI has to be in transaction data, it's encrypted. Who can access itOnly the developer who builds and maintains the automation. On your machine, you decide who else gets access. What we signA BAA before we see any patient data. AI runs on AWS, Azure or Google under BAAs, and your data isn't used to train models. [How we handle patient data →](https://www.flobotics.io/security)[Request our security policies →](https://trust.inc/flobotics) Related workflows ## The billing workflows before and after claim submission. - 01[Eligibility & benefits](https://www.flobotics.io/agents/eligibility-check-automation)Check coverage before the visit and save the result in the patient record.~40 s per checkPTCoA · [Case study](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks)→ - 02[Prior authorization](https://www.flobotics.io/agents/prior-authorization-automation)Prepare and submit authorization requests, then check for updates.85% less submission timePTCoA · [Case study](https://www.flobotics.io/case-studies/85-faster-submissions-8-ftes-saved-prior-authorization-automation)→ - 03Claims managementPrepare, submit, and track claims.You are here - 04[Denials management](https://www.flobotics.io/agents/denials-management-automation)Prepare supported corrections and appeals, then track payer responses.Up to 300 resubmissions a dayPathGroup · [Case study](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation)→ [Explore revenue cycle management automation →](https://www.flobotics.io/rcm-automation) Talk to us ## Is automating your claims work worth it? Book a 30-minute call with Karl, our CTO, or Bart, our Head of AI. If you'd rather write, send us a message. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through how your team prepares, submits, and tracks claims. Within the first 15 minutes, we can usually tell whether automation makes sense. We'll discuss the work involved and what we'd need to estimate the cost. Karl & Bart --- # Denial Management Automation | AI Agents | RPA Canonical: https://www.flobotics.io/agents/denials-management-automation Published: 2026-02-26 Updated: 2026-02-26 --- [Home](https://www.flobotics.io/)/[What we do](https://www.flobotics.io/what-we-do)/Denials management Workflows we automate # Denials Management Automation We find denied claims, capture the payer's reason, and gather the information needed for the next step. The automation handles agreed corrections or prepares reconsideration and appeal documents. Your team reviews cases that need coding or clinical judgment. [Book a 30-minute call →](https://www.flobotics.io/book)[See client results](#results) Illustration of a denial run. Three denied claims enter the queue. For the first, the automation reads the payer message, matches it to the record, gathers the requested document and submits a reconsideration. For the second, it submits a corrected claim through a different, agreed route. The third is a medical-necessity denial, so it goes to staff with the payer message and documents. The example ends with 2 requests submitted and 1 needing clinical review. Both submitted cases stay open. Denial handling - Find - Classify - Prepare - Follow up Denied claims · this week - A. Rivera · claim D-2041Documents requestedReconsideration submitted · receipt saved - J. Okafor · claim D-2042Administrative correctionCorrected claim submitted · reference saved - M. Chen · claim D-2043Medical necessityStaff review · clinical review required 2 requests submitted · 1 needs clinical review Current denial · A. Rivera · claim D-2041 Payer reasonRecords requested RouteReconsideration Request →Payer route← Receipt Record matchFound Supporting infoRecords attached Submitted15:12 ReferenceRC-80314 Receipt saved · case stays open for follow-up Example with made-up patients and claims. The next step depends on the payer's reason and rules. PauseReplay Client result · PathGroup ## How PathGroup automated recurring denial work PathGroup's team cross-checked records between athenahealth and its PathSys lab system. We built a data exchange and automation for recurring denial types. It gathers the available corrections, updates claims, and resubmits supported cases. Complex cases go to staff. [Read the PathGroup case study →](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation) Measured results ~10 min →to ~55 sper case in the automated workflow Up to 300claims checked, corrected, and resubmitted per day Near-zerobacklog in the targeted denial queues Results from the targeted workflows and supporting automations at PathGroup. Resubmission is separate from a payer's decision. A California medtech company cleared 80% of a 3,000-claim denial backlog in three weeks using automated reconsiderations. [Read the medtech case study →](https://www.flobotics.io/case-studies/50k-saved-in-1-month-ai-agent-for-denials-management) What we automate ## The tasks behind a denied claim. A denied claim needs a reason, supporting information, and the right next step. These are the tasks we automate. - 01Find Bring the denied claim and its records together. - Pick up denied claims from your billing queues, remittance files, or payer portals. - Match each claim to the patient, service, and payer record. - Pull the related documents and previous submission details. - 02Classify Record the reason and the work it needs. - Capture the payer's message and reason codes when provided. - Group recurring issues using rules agreed with your team. - Record the required next step and applicable deadline where confirmed. - 03Prepare Prepare the response supported by your records. - Apply agreed administrative corrections using verified source information. - Gather the documents for a reconsideration or appeal. - Send coding questions, clinical disputes, and incomplete cases to staff. - 04Follow up Send supported responses and track what happens next. - Submit supported corrections and reviewed requests through the right payer route. - Save submission references, documents, and timestamps in your system. - Check for updates and send unanswered or unresolved cases to staff. We set up the workflow for the denial types you handle often. Your team reviews unfamiliar cases and decisions that need a person. A corrected claim, reconsideration, and appeal follow different payer processes. Automation does not guarantee that a denial will be overturned or a claim paid. Is it a good fit? ## Denials automation usually pays off when most of these are true. - Your team sees the same denial reasons repeatedly. - Staff gather records and re-enter corrections across several systems. - Open denials wait for document uploads, resubmission, or status checks. - You have clear handling rules for common cases and a review process for the rest. What affects your savings - How many denials you handle each month - How long gathering records and preparing responses take by hand - How many cases follow repeatable, supported correction rules - Which payer routes and filing deadlines apply - What it costs to build and maintain The return is different for every organization. Schedule a call and we'll give you a quick, honest estimate of whether it's worth it for yours. [Book a 30-minute call →](https://www.flobotics.io/book) How denials automation works with your systems ## The automation connects denial queues, supporting records, and payer responses. Your staff keep using the systems they know. We use direct connections where available, or UiPath and Python for billing systems and payer portals. AI can read payer letters and supporting documents. Your team reviews uncertain matches, clinical disputes, and cases outside the agreed rules. Example of the automation between three places. For the first denied claim, it gathers the visit note from the EHR, submits a reconsideration in the payer portal and saves the receipt in the billing system. For the second, it submits a corrected claim through a separate route and saves the reference. The third is a medical-necessity dispute, so it goes to the staff review queue with its documents. Later, a payer update shows the first case under review, and it stays open with a next-check date. Your billing system · denied claims ClaimPatientPayer reasonNext action D-2041A. RiveraRecords requestedOpen D-2042J. OkaforCorrection neededOpen D-2043M. ChenMedical necessityOpen Visit note 10/14 · from EHR Flobotics automation Your rulesMatch claim and documentsUse the agreed payer routeClinical dispute → staff Payer portal · response submission Later payer update ClaimRouteSupporting infoSubmit Receipt— Your staff · review queue M. Chen · claim D-2043Payer disputes medical necessity. Review the denial letter and clinical record. No exceptions yet Monitored and maintained by us. We check the runs and update the workflow when payer processes or your systems change. Example with made-up patients and claims. Correction, reconsideration, and appeal steps differ by payer. PauseReplay Rejected claims that never reached payer review are handled separately from denied claims. Coding decisions and clinical appeal arguments stay with the appropriate staff. Patient data (PHI) What happens to your patient data Your data is safe. Where it runsOn a machine you own: usually a virtual machine on your side, or your own AWS or Azure account. What we storeWe don't store patient data. The automation reads it, uses it and writes the result back. In the rare case PHI has to be in transaction data, it's encrypted. Who can access itOnly the developer who builds and maintains the automation. On your machine, you decide who else gets access. What we signA BAA before we see any patient data. AI runs on AWS, Azure or Google under BAAs, and your data isn't used to train models. [How we handle patient data →](https://www.flobotics.io/security)[Request our security policies →](https://trust.inc/flobotics) Related workflows ## The billing workflows before a claim is denied. - 01[Eligibility & benefits](https://www.flobotics.io/agents/eligibility-check-automation)Check coverage before the visit and save the result in the patient record.~40 s per checkPTCoA · [Case study](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks)→ - 02[Prior authorization](https://www.flobotics.io/agents/prior-authorization-automation)Prepare and submit authorization requests, then check for updates.85% less submission timePTCoA · [Case study](https://www.flobotics.io/case-studies/85-faster-submissions-8-ftes-saved-prior-authorization-automation)→ - 03[Claims management](https://www.flobotics.io/agents/claims-management-automation)Prepare, submit, and track claims.98% less manual claim preparationGentem Health · [Case study](https://www.flobotics.io/case-studies/98-reduction-in-manual-claim-prep-claims-management-automation)→ - 04Denials managementPrepare supported corrections and appeals, then track payer responses.You are here [Explore revenue cycle management automation →](https://www.flobotics.io/rcm-automation) Talk to us ## Is automating your denial work worth it? Book a 30-minute call with Karl, our CTO, or Bart, our Head of AI. If you'd rather write, send us a message. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the denials your team handles most often. Within the first 15 minutes, we can usually tell whether automation makes sense. We'll discuss the work involved and what we'd need to estimate the cost. Karl & Bart --- # Insurance Eligibility and Benefits Verification Automation Canonical: https://www.flobotics.io/agents/eligibility-check-automation Published: 2026-02-26 Updated: 2026-02-26 --- [Home](https://www.flobotics.io/)/[What we do](https://www.flobotics.io/what-we-do)/Eligibility & benefits verification Workflows we automate # Eligibility & Benefits Verification Automation We automate patient insurance checks, capture coverage and benefit details, and record the results in your systems. Your team reviews the exceptions instead of processing every patient manually. [Book a 30-minute call →](https://www.flobotics.io/book)[See client results](#results) Illustration of an eligibility verification run. Three scheduled patients are checked with their payers. For two, coverage and benefit details are captured and each record is marked verification completed. The third has a member ID that does not match the payer's records, so it is routed to staff review. Eligibility verification run - Gather - Verify - Record - Flag exceptions Verification queue · tomorrow - A. Rivera09:30 · Lakeshore PPOVerification completed - J. Okafor10:15 · Northfield HMOVerification completed - M. Chen11:00 · Riverside AdvantageStaff review Current check · A. Rivera Member IDLKP 4410 2291 Date of service09:30 tomorrow Inquiry → Payer connection ← Response CoverageActive Specialist copay$40 Deductible remaining$650 of $1,500 Coinsurance20% Saved to the patient record, with source and time Example with made-up patients and values. Not every payer returns every field. PauseReplay Client result · PTCoA ## How PTCoA automated eligibility checks Their staff checked insurance in several payer portals for every visit, then copied the results between the EHR and the billing system by hand. Now every new appointment starts a check automatically: coverage, copay and deductible are verified, saved in the EHR (PrognoCIS) and sent to billing (TriZetto). Inactive coverage and missing IDs go to staff. [Read the PTCoA case study →](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) Measured results 5–7 min →to 40 sper eligibility check 8,000+checks a month ~3 FTEof staff time saved The case study also reports 100% ROI in 23 days for this eligibility automation together with Denial Hunter, our denials automation, and $180,000 in projected savings for the first year. Another client cut each check from about 5 minutes to about 1 minute, across several payer portals. [Read the case study →](https://www.flobotics.io/case-studies/halving-monthly-backlog---eligibility-automation-in-action) What we automate ## Every step of an eligibility check. An eligibility check is a series of small, repetitive tasks. These are the ones we automate. - 01Prepare Get every patient ready for a clean check. - Find the patients to check in your schedule, new orders or work queues. - Pull each patient's details, insurance, member ID and date of service. - Flag missing information before checking with the payer. - 02Verify Ask the payer and capture the answer. - Check eligibility with the payer through a direct connection, a clearinghouse or the payer's portal. - Capture coverage status, plan details and coverage dates. - Capture copays, coinsurance, deductibles and other benefits the payer returns. - 03Record Put the result where your team works. - Save the results, or a standard note, in your system. - Note where and when each check was done. - Keep a copy of the payer's response if your process requires it. - 04Resolve Hand off what needs a person. - Send inactive coverage, mismatches and failed checks to your staff. - Retry checks that failed for a temporary reason. - Check again before the visit, or when details change. - Keep track of finished and open cases. We set up the workflow for your systems, payers and rules. Your team only handles the cases that need a person. An eligibility check shows what the payer reports at that moment. It doesn't guarantee that a claim will be paid. Sending prior authorization requests is a separate workflow. Patient cost estimates, finding unknown coverage and checking whether a service needs authorization can be added if they fit the project. Is it a good fit? ## Eligibility automation usually pays off when most of these are true. - You check eligibility for many patients every day. - Staff look up the same patient in several systems and payer portals. - Results are typed into patient records by hand. - Most checks follow the same steps, and you know which cases need a person. What affects your savings - How many eligibility checks you do each month - How long each check takes by hand - Which payers you can reach, and how - How many checks still need a person - What it costs to build and maintain The return is different for every organization. Schedule a call and we'll give you a quick, honest estimate of whether it's worth it for yours. [Book a 30-minute call →](https://www.flobotics.io/book) How eligibility automation works with your systems ## The automation works between your systems and your payers. Your staff keep using the systems they know. We pick the method for each step: a direct connection or clearinghouse where one exists, UiPath or Python where the work happens in portals and desktop apps, and AI where a response or document needs reading. Example of the automation between three places. It reads tomorrow's schedule from the EHR, checks each patient with the payer through a portal or clearinghouse, and saves the result back to the EHR. A patient whose member ID is not found is sent to the staff review queue with the reason. Your EHR · schedule, tomorrow TimePatientPlanEligibility 09:30A. RiveraLakeshore PPO✓ VerifiedCopay $40 10:15J. OkaforNorthfield HMO✓ VerifiedDeductible $1,200 11:00M. ChenRiverside Adv.Needs review Flobotics automation Your rulestomorrow's visitssave copay & deductibleID mismatch → staff - Reading tomorrow's schedule · 3 patients - A. Rivera → Lakeshore PPO - Coverage active · saved to EHR ✓ - J. Okafor → Northfield HMO - Coverage active · saved to EHR ✓ - M. Chen → Riverside Adv. - Member ID not found → staff review - Done · 2 verified, 1 sent to staff Payer portal or clearinghouse Member IDLKP 4410 2291 Date of birth03/11/1984 Service datetomorrow Check eligibility ResponseActive · Copay $40 · Deductible left $650 Your staff · review queue M. Chen · 11:00Member ID not found by the payer. Check the insurance card. No exceptions yet Monitored and maintained by us. We watch every run and update the workflow when payers or your systems change. Example with made-up patients. The method differs by payer: direct connection, clearinghouse or portal. PauseReplay Patient data (PHI) What happens to your patient data Your data is safe. Where it runsOn a machine you own: usually a virtual machine on your side, or your own AWS or Azure account. What we storeWe don't store patient data. The automation reads it, uses it and writes the result back. In the rare case PHI has to be in transaction data, it's encrypted. Who can access itOnly the developer who builds and maintains the automation. On your machine, you decide who else gets access. What we signA BAA before we see any patient data. AI runs on AWS, Azure or Google under BAAs, and your data isn't used to train models. [How we handle patient data →](https://www.flobotics.io/security)[Request our security policies →](https://trust.inc/flobotics) Related workflows ## Eligibility is the first step. These come after it. - 01Eligibility & benefitsCheck coverage before the visit and save it to the patient record.You are here - [02Prior authorizationPrepare and submit authorization requests, then follow up on them.85% faster submissionsPTCoA→](https://www.flobotics.io/agents/prior-authorization-automation) - [03Claims managementPrepare, submit and track claims.98% less manual claim prepGentem Health→](https://www.flobotics.io/agents/claims-management-automation) - [04Denials managementSort, correct and resubmit denied claims.$50K saved in the first monthMedtech company, California→](https://www.flobotics.io/agents/denials-management-automation) [Explore revenue cycle management automation →](https://www.flobotics.io/rcm-automation) Talk to us ## Is automating your eligibility checks worth it? Book a 30-minute call with Karl, our CTO, or Bart, our Head of AI. If you'd rather write, send us a message. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through how you check eligibility now. We'll tell you which parts we can automate, what it would cost, and whether it's worth doing. Karl & Bart --- # Prior Authorization Automation Solutions | AI Agents | RPA Canonical: https://www.flobotics.io/agents/prior-authorization-automation Published: 2026-02-26 Updated: 2026-02-26 --- [Home](https://www.flobotics.io/)/[What we do](https://www.flobotics.io/what-we-do)/Prior authorization Workflows we automate # Prior Authorization Automation We gather the information for prior authorization requests, fill payer forms, and submit the supporting documents. The automation checks for updates and saves them in your systems. Your team handles missing information and cases that need review. [Book a 30-minute call →](https://www.flobotics.io/book)[See client results](#results) Illustration of a prior authorization run. Three new orders are in the queue. For two, the automation pulls the order and insurance details, attaches the clinical note, fills the payer form, submits the request and saves the confirmation number and time. The third is missing the required clinical note, so it goes to staff review before submission. The example ends with 2 submitted and 1 needing a clinical note. No payer decision is shown. Prior authorization submission - Gather - Prepare - Submit - Follow up Authorization queue · new orders - A. RiveraOrder 4471 · MRI, lumbar spineSubmitted · confirmation saved - J. OkaforOrder 4472 · CT, chestSubmitted · confirmation saved - M. ChenOrder 4473 · Sleep studyStaff review · clinical note missing 2 submitted · 1 needs a clinical note Current request · A. Rivera OrderOrder 4471 PayerLakeshore PPO Request →Payer portal← Confirmation Patient & insurancePulled Clinical noteAttached Payer formFilled ConfirmationPA-55821 · 10:42 Confirmation saved to the order · next check scheduled Example with made-up patients. Submission is not a payer decision. PauseReplay Client result · PTCoA ## How PTCoA automated prior authorization submissions PTCoA's team prepared requests across several payer portals. We built automation to transfer order details, submit requests, and save confirmations. A separate follow-up process checks for payer updates and sends cases needing attention to staff. [Read the PTCoA case study →](https://www.flobotics.io/case-studies/85-faster-submissions-8-ftes-saved-prior-authorization-automation) Measured results 10–15 min →to 1–2 minper authorization packet submission 8+ FTEof staff capacity freed ~11% →to <1%submission error rate Results from PTCoA's project. Submission time is separate from the time a payer takes to decide. A genetic diagnostic lab cut handling time from 8–12 minutes to under 1 minute by moving order details and documents from its lab system into an authorization portal. [Read the lab case study →](https://www.flobotics.io/case-studies/90-faster-packet-submissions-prior-authorization-automation) Explore our [laboratory automation workflows](https://www.flobotics.io/who-we-help/laboratories) for related document and payer-portal tasks. What we automate ## The tasks behind a prior authorization request. Each request involves gathering information, preparing documents, submitting a form, and checking for an answer. These are the tasks we automate. - 01Gather Pull the information already recorded for the order. - Find new orders or requests in your work queue. - Pull patient, insurance, provider, and service details from your systems. - Collect the available clinical notes and other required documents. - 02Prepare Check the request against the payer's requirements. - Check authorization and document requirements where the payer makes them available. - Fill the required fields using the information on the order. - Flag missing documents, conflicting details, or questions needing clinical review. - 03Submit Send the request and keep its confirmation. - Submit through the supported payer connection or portal. - Attach the required documents for the right patient and order. - Save the confirmation number, submitted packet, and submission time. - 04Follow up Check what changed and record the answer. - Check open requests on an agreed schedule. - Save payer decisions, authorization details, and validity dates when returned. - Send information requests, denials, and unresolved cases to your staff. We set up the workflow for your systems, payers, and rules. Your team handles the cases that need a person. The payer decides whether to approve a request. An approval does not guarantee that the claim will be paid. Is it a good fit? ## Prior authorization automation usually pays off when most of these are true. - Your team prepares many authorization requests each week. - Staff copy order details and upload the same documents into payer portals. - Someone checks pending requests repeatedly for updates. - Most requests follow known steps, and you know which cases need clinical review. What affects your savings - How many requests you submit each month - How long preparation, submission, and follow-up take by hand - Which payer connections and portals are available - How often documents are missing or clinical review is needed - What it costs to build and maintain The return is different for every organization. Schedule a call and we'll give you a quick, honest estimate of whether it's worth it for yours. [Book a 30-minute call →](https://www.flobotics.io/book) How prior authorization automation works with your systems ## The automation moves requests between your systems and payer portals. Your staff keep using the systems they know. We use a direct connection where one is available, or UiPath and Python to work with portals and desktop apps. AI can read documents and payer messages. Questions that need clinical judgment go to your team. Example of the automation between three places. It reads new orders from the EHR or lab system, enters the patient details and attachments in the payer portal, submits the request and saves the confirmation back to the order. The second request stays pending. The third order is missing its clinical note, so it goes to the staff review queue before submission. Later, a payer update approves the first request, and the authorization number and dates are saved. Your EHR or lab system · authorization queue OrderPatientAuth no.Request 4471A. Rivera—Ready 4472J. Okafor—Ready 4473M. Chen—Ready Clinical note.pdf · on file Flobotics automation Your rulesUse order detailsCheck required attachmentsMissing note → staff Payer portal or direct connection Later payer update Member IDServiceAttachmentSubmit request Confirmation— Your staff · review queue M. Chen · order 4473Required clinical note is missing. Request it from the care team. No exceptions yet Monitored and maintained by us. We check the runs and update the workflow when payer portals or your systems change. Example with made-up patients. The connection and required documents differ by payer. Payer updates are shown at a later point in the example. PauseReplay Eligibility checks and claim submission are separate workflows. Authorization appeals can be added where the process and review rules are clear. Patient data (PHI) What happens to your patient data Your data is safe. Where it runsOn a machine you own: usually a virtual machine on your side, or your own AWS or Azure account. What we storeWe don't store patient data. The automation reads it, uses it and writes the result back. In the rare case PHI has to be in transaction data, it's encrypted. Who can access itOnly the developer who builds and maintains the automation. On your machine, you decide who else gets access. What we signA BAA before we see any patient data. AI runs on AWS, Azure or Google under BAAs, and your data isn't used to train models. [How we handle patient data →](https://www.flobotics.io/security)[Request our security policies →](https://trust.inc/flobotics) Related workflows ## The billing workflows around prior authorization. - 01[Eligibility & benefits](https://www.flobotics.io/agents/eligibility-check-automation)Check coverage before the visit and save the result in the patient record.~40 s per checkPTCoA · [Case study](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks)→ - 02Prior authorizationPrepare and submit authorization requests, then check for updates.You are here - 03[Claims management](https://www.flobotics.io/agents/claims-management-automation)Prepare, submit, and track claims.98% less manual claim preparationGentem Health · [Case study](https://www.flobotics.io/case-studies/98-reduction-in-manual-claim-prep-claims-management-automation)→ - 04[Denials management](https://www.flobotics.io/agents/denials-management-automation)Prepare supported corrections and appeals, then track payer responses.Up to 300 resubmissions a dayPathGroup · [Case study](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation)→ [Explore revenue cycle management automation →](https://www.flobotics.io/rcm-automation) Talk to us ## Is automating your prior authorization work worth it? Book a 30-minute call with Karl, our CTO, or Bart, our Head of AI. If you'd rather write, send us a message. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through how your team prepares and follows up on authorization requests. Within the first 15 minutes, we can usually tell whether automation makes sense. We'll discuss the work involved and what we'd need to estimate the cost. Karl & Bart --- # Athenahealth rolls out 80+ AI-native revenue cycle features Canonical: https://www.flobotics.io/rcm-industry-news/athenahealth-80-ai-native-revenue-cycle-tools Published: 2026-06-03 Updated: 2026-07-19 --- [Home](https://www.flobotics.io/)/[RCM industry news](https://www.flobotics.io/rcm-industry-news)/Athenahealth rolls out 80+ AI-native revenue cycle features Revenue Cycle Management # Athenahealth rolls out 80+ AI-native revenue cycle features Becker's Hospital ReviewJune 3, 2026 Athenahealth built more than 80 AI-native features into athenaOne, targeting high-friction tasks such as insurance verification, coding, prior authorization and denials. AI voice agents place over 23,000 prior authorization calls each month, some completed in under an hour. Voice AI uses AI agents to place more than 23,000 prior authorization calls each month. Source: [Becker's Hospital Review](https://www.beckershospitalreview.com/finance/revenue-cycle-management/athenahealth-unveils-80-ai-native-revenue-cycle-tools/) Voice AI uses AI agents to place more than 23,000 prior authorization calls each month. Source: [Becker's Hospital Review](https://www.beckershospitalreview.com/finance/revenue-cycle-management/athenahealth-unveils-80-ai-native-revenue-cycle-tools/) Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Find even more ## Related news & updates The latest industry news, interviews, technologies, and resources. [ Regulatory & CMS ### CMS proposes rule for electronic prior authorization of drugs (CMS-0062-P) A proposed CMS rule extends electronic prior authorization requirements from non-drug items to drugs, adopts FHIR standards for prior auth transactions and mandates API metrics reporting. Most compliance dates begin October 1, 2027. CMSApril 10, 2026 ](https://www.flobotics.io/rcm-industry-news/cms-electronic-prior-authorization-drugs-rule)[ Prior Authorization ### Optum unveils two new AI tools for digital prior authorization Optum is launching two AI tools — Digital Auth Complete and InterQual Auth Accelerator — to cut prior authorization delays. Digital Auth Complete integrates into the EHR and automates multiple parts of the process to return responses faster. Fierce HealthcareJuly 19, 2026 ](https://www.flobotics.io/rcm-industry-news/optum-ai-digital-prior-authorization-tools)[ Competitive & Market ### UiPath launches agentic AI solutions for healthcare administration UiPath announced agentic AI solutions for healthcare: medical records summarization, claim denial prevention and resolution, and prior authorization — using agentic automation to accelerate revenue cycle management. UiPath (Investor Relations)July 19, 2026 ](https://www.flobotics.io/rcm-industry-news/uipath-agentic-ai-healthcare-admin) [All RCM news →](https://www.flobotics.io/rcm-industry-news) --- # Optum unveils two new AI tools for digital prior authorization Canonical: https://www.flobotics.io/rcm-industry-news/optum-ai-digital-prior-authorization-tools Published: 2026-07-19 Updated: 2026-07-19 --- [Home](https://www.flobotics.io/)/[RCM industry news](https://www.flobotics.io/rcm-industry-news)/Optum unveils two new AI tools for digital prior… Prior Authorization # Optum unveils two new AI tools for digital prior authorization Fierce HealthcareJuly 19, 2026 Optum is launching two AI tools — Digital Auth Complete and InterQual Auth Accelerator — to cut prior authorization delays. Digital Auth Complete integrates into the EHR and automates multiple parts of the process to return responses faster. Digital Auth Complete integrates into the electronic health record and automates multiple parts of the process to provide responses faster. Source: [Fierce Healthcare](https://www.fiercehealthcare.com/payers/optum-unveils-2-new-ai-powered-tools-digital-prior-authorization) Digital Auth Complete integrates into the electronic health record and automates multiple parts of the process to provide responses faster. Source: [Fierce Healthcare](https://www.fiercehealthcare.com/payers/optum-unveils-2-new-ai-powered-tools-digital-prior-authorization) Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Find even more ## Related news & updates The latest industry news, interviews, technologies, and resources. [ Prior Authorization ### Abridge teams with Availity to scale real-time prior authorization An integration between Abridge and Availity aims to speed prior authorization from weeks to minutes, shifting the process from post-visit to real time during the patient exam. Fierce HealthcareJuly 19, 2026 ](https://www.flobotics.io/rcm-industry-news/abridge-availity-real-time-prior-auth)[ Revenue Cycle Management ### Athenahealth rolls out 80+ AI-native revenue cycle features Athenahealth built more than 80 AI-native features into athenaOne, targeting high-friction tasks such as insurance verification, coding, prior authorization and denials. AI voice agents place over 23,000 prior authorization calls each month, some completed in under an hour. Becker's Hospital ReviewJune 3, 2026 ](https://www.flobotics.io/rcm-industry-news/athenahealth-80-ai-native-revenue-cycle-tools)[ Regulatory & CMS ### CMS proposes rule for electronic prior authorization of drugs (CMS-0062-P) A proposed CMS rule extends electronic prior authorization requirements from non-drug items to drugs, adopts FHIR standards for prior auth transactions and mandates API metrics reporting. Most compliance dates begin October 1, 2027. CMSApril 10, 2026 ](https://www.flobotics.io/rcm-industry-news/cms-electronic-prior-authorization-drugs-rule) [All RCM news →](https://www.flobotics.io/rcm-industry-news) --- # UiPath launches agentic AI solutions for healthcare administration Canonical: https://www.flobotics.io/rcm-industry-news/uipath-agentic-ai-healthcare-admin Published: 2026-07-19 Updated: 2026-07-19 --- [Home](https://www.flobotics.io/)/[RCM industry news](https://www.flobotics.io/rcm-industry-news)/UiPath launches agentic AI solutions for healthcare… Competitive & Market # UiPath launches agentic AI solutions for healthcare administration UiPath (Investor Relations)July 19, 2026 UiPath announced agentic AI solutions for healthcare: medical records summarization, claim denial prevention and resolution, and prior authorization — using agentic automation to accelerate revenue cycle management. UiPath launches agentic AI solutions to break administrative and financial bottlenecks for clinicians and healthcare admins. Source: [UiPath (Investor Relations)](https://ir.uipath.com/news/detail/428/uipath-launches-agentic-ai-solutions-to-break-administrative-financial-bottlenecks-for-clinicians-and-healthcare-admins) UiPath launches agentic AI solutions to break administrative and financial bottlenecks for clinicians and healthcare admins. Source: [UiPath (Investor Relations)](https://ir.uipath.com/news/detail/428/uipath-launches-agentic-ai-solutions-to-break-administrative-financial-bottlenecks-for-clinicians-and-healthcare-admins) Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Find even more ## Related news & updates The latest industry news, interviews, technologies, and resources. [ Prior Authorization ### Abridge teams with Availity to scale real-time prior authorization An integration between Abridge and Availity aims to speed prior authorization from weeks to minutes, shifting the process from post-visit to real time during the patient exam. Fierce HealthcareJuly 19, 2026 ](https://www.flobotics.io/rcm-industry-news/abridge-availity-real-time-prior-auth)[ Revenue Cycle Management ### Athenahealth rolls out 80+ AI-native revenue cycle features Athenahealth built more than 80 AI-native features into athenaOne, targeting high-friction tasks such as insurance verification, coding, prior authorization and denials. AI voice agents place over 23,000 prior authorization calls each month, some completed in under an hour. Becker's Hospital ReviewJune 3, 2026 ](https://www.flobotics.io/rcm-industry-news/athenahealth-80-ai-native-revenue-cycle-tools)[ Regulatory & CMS ### CMS proposes rule for electronic prior authorization of drugs (CMS-0062-P) A proposed CMS rule extends electronic prior authorization requirements from non-drug items to drugs, adopts FHIR standards for prior auth transactions and mandates API metrics reporting. Most compliance dates begin October 1, 2027. CMSApril 10, 2026 ](https://www.flobotics.io/rcm-industry-news/cms-electronic-prior-authorization-drugs-rule) [All RCM news →](https://www.flobotics.io/rcm-industry-news) --- # Abridge teams with Availity to scale real-time prior authorization Canonical: https://www.flobotics.io/rcm-industry-news/abridge-availity-real-time-prior-auth Published: 2026-07-19 Updated: 2026-07-19 --- [Home](https://www.flobotics.io/)/[RCM industry news](https://www.flobotics.io/rcm-industry-news)/Abridge teams with Availity to scale real-time prior… Prior Authorization # Abridge teams with Availity to scale real-time prior authorization Fierce HealthcareJuly 19, 2026 An integration between Abridge and Availity aims to speed prior authorization from weeks to minutes, shifting the process from post-visit to real time during the patient exam. The integration could significantly speed up prior auth from months to minutes. Source: [Fierce Healthcare](https://www.fiercehealthcare.com/ai-and-machine-learning/jpm26-abridge-teams-availity-scale-real-time-prior-authorization) The integration could significantly speed up prior auth from months to minutes. Source: [Fierce Healthcare](https://www.fiercehealthcare.com/ai-and-machine-learning/jpm26-abridge-teams-availity-scale-real-time-prior-authorization) Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Find even more ## Related news & updates The latest industry news, interviews, technologies, and resources. [ Revenue Cycle Management ### Athenahealth rolls out 80+ AI-native revenue cycle features Athenahealth built more than 80 AI-native features into athenaOne, targeting high-friction tasks such as insurance verification, coding, prior authorization and denials. AI voice agents place over 23,000 prior authorization calls each month, some completed in under an hour. Becker's Hospital ReviewJune 3, 2026 ](https://www.flobotics.io/rcm-industry-news/athenahealth-80-ai-native-revenue-cycle-tools)[ Regulatory & CMS ### CMS proposes rule for electronic prior authorization of drugs (CMS-0062-P) A proposed CMS rule extends electronic prior authorization requirements from non-drug items to drugs, adopts FHIR standards for prior auth transactions and mandates API metrics reporting. Most compliance dates begin October 1, 2027. CMSApril 10, 2026 ](https://www.flobotics.io/rcm-industry-news/cms-electronic-prior-authorization-drugs-rule)[ Prior Authorization ### Optum unveils two new AI tools for digital prior authorization Optum is launching two AI tools — Digital Auth Complete and InterQual Auth Accelerator — to cut prior authorization delays. Digital Auth Complete integrates into the EHR and automates multiple parts of the process to return responses faster. Fierce HealthcareJuly 19, 2026 ](https://www.flobotics.io/rcm-industry-news/optum-ai-digital-prior-authorization-tools) [All RCM news →](https://www.flobotics.io/rcm-industry-news) --- # CMS proposes rule for electronic prior authorization of drugs (CMS-0062-P) Canonical: https://www.flobotics.io/rcm-industry-news/cms-electronic-prior-authorization-drugs-rule Published: 2026-04-10 Updated: 2026-07-19 --- [Home](https://www.flobotics.io/)/[RCM industry news](https://www.flobotics.io/rcm-industry-news)/CMS proposes rule for electronic prior authorization of… Regulatory & CMS # CMS proposes rule for electronic prior authorization of drugs (CMS-0062-P) CMSApril 10, 2026 A proposed CMS rule extends electronic prior authorization requirements from non-drug items to drugs, adopts FHIR standards for prior auth transactions and mandates API metrics reporting. Most compliance dates begin October 1, 2027. CMS now proposes to require impacted payers to incorporate coverage and documentation requirements into those APIs to support the electronic prior authorization of drugs covered under a medical benefit beginning October 1, 2027. Source: [CMS](https://www.cms.gov/newsroom/fact-sheets/2026-cms-interoperability-standards-prior-authorization-drugs-proposed-rule) CMS now proposes to require impacted payers to incorporate coverage and documentation requirements into those APIs to support the electronic prior authorization of drugs covered under a medical benefit beginning October 1, 2027. Source: [CMS](https://www.cms.gov/newsroom/fact-sheets/2026-cms-interoperability-standards-prior-authorization-drugs-proposed-rule) Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Find even more ## Related news & updates The latest industry news, interviews, technologies, and resources. [ Prior Authorization ### Abridge teams with Availity to scale real-time prior authorization An integration between Abridge and Availity aims to speed prior authorization from weeks to minutes, shifting the process from post-visit to real time during the patient exam. Fierce HealthcareJuly 19, 2026 ](https://www.flobotics.io/rcm-industry-news/abridge-availity-real-time-prior-auth)[ Revenue Cycle Management ### Athenahealth rolls out 80+ AI-native revenue cycle features Athenahealth built more than 80 AI-native features into athenaOne, targeting high-friction tasks such as insurance verification, coding, prior authorization and denials. AI voice agents place over 23,000 prior authorization calls each month, some completed in under an hour. Becker's Hospital ReviewJune 3, 2026 ](https://www.flobotics.io/rcm-industry-news/athenahealth-80-ai-native-revenue-cycle-tools)[ Prior Authorization ### Optum unveils two new AI tools for digital prior authorization Optum is launching two AI tools — Digital Auth Complete and InterQual Auth Accelerator — to cut prior authorization delays. Digital Auth Complete integrates into the EHR and automates multiple parts of the process to return responses faster. Fierce HealthcareJuly 19, 2026 ](https://www.flobotics.io/rcm-industry-news/optum-ai-digital-prior-authorization-tools) [All RCM news →](https://www.flobotics.io/rcm-industry-news) --- # States Continue Efforts to Regulate AI in Healthcare: A Review of Legislation Passed in 2026 Canonical: https://www.flobotics.io/rcm-industry-news/2026-07-19-states-continue-efforts-to-regulate-ai-in-healthcare Published: 2026-05-26 Updated: 2026-07-19 --- [Home](https://www.flobotics.io/)/[RCM industry news](https://www.flobotics.io/rcm-industry-news)/States Continue Efforts to Regulate AI in Healthcare: A… Regulatory & CMS # States Continue Efforts to Regulate AI in Healthcare: A Review of Legislation Passed in 2026 Holland & KnightMay 26, 2026 A 2026 legislative review tracks state laws enacted this year regulating insurers' use of AI in prior authorization and claims decisions. States including Georgia, Maryland, Washington and Utah added disclosure, human-oversight and reporting requirements for AI-assisted adverse determinations. AI may be used to assist and streamline insurance operations, but a health insurer cannot rely upon it as the sole basis for denying care. Source: [Holland & Knight](https://www.hklaw.com/en/insights/publications/2026/05/states-continue-efforts-to-regulate-ai-in-healthcare) AI may be used to assist and streamline insurance operations, but a health insurer cannot rely upon it as the sole basis for denying care. Source: [Holland & Knight](https://www.hklaw.com/en/insights/publications/2026/05/states-continue-efforts-to-regulate-ai-in-healthcare) Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Find even more ## Related news & updates The latest industry news, interviews, technologies, and resources. [ Revenue Cycle Management ### Athenahealth rolls out 80+ AI-native revenue cycle features Athenahealth built more than 80 AI-native features into athenaOne, targeting high-friction tasks such as insurance verification, coding, prior authorization and denials. AI voice agents place over 23,000 prior authorization calls each month, some completed in under an hour. Becker's Hospital ReviewJune 3, 2026 ](https://www.flobotics.io/rcm-industry-news/athenahealth-80-ai-native-revenue-cycle-tools)[ Regulatory & CMS ### CMS proposes rule for electronic prior authorization of drugs (CMS-0062-P) A proposed CMS rule extends electronic prior authorization requirements from non-drug items to drugs, adopts FHIR standards for prior auth transactions and mandates API metrics reporting. Most compliance dates begin October 1, 2027. CMSApril 10, 2026 ](https://www.flobotics.io/rcm-industry-news/cms-electronic-prior-authorization-drugs-rule)[ Prior Authorization ### Optum unveils two new AI tools for digital prior authorization Optum is launching two AI tools — Digital Auth Complete and InterQual Auth Accelerator — to cut prior authorization delays. Digital Auth Complete integrates into the EHR and automates multiple parts of the process to return responses faster. Fierce HealthcareJuly 19, 2026 ](https://www.flobotics.io/rcm-industry-news/optum-ai-digital-prior-authorization-tools) [All RCM news →](https://www.flobotics.io/rcm-industry-news) --- # How AI is transforming revenue cycle management right now Canonical: https://www.flobotics.io/rcm-industry-news/2026-07-19-how-ai-is-transforming-revenue-cycle-management Published: 2026-04-29 Updated: 2026-08-12 --- [Home](https://www.flobotics.io/)/[RCM industry news](https://www.flobotics.io/rcm-industry-news)/How AI is transforming revenue cycle management right now Competitive & Market # How AI is transforming revenue cycle management right now Oliver WymanApril 29, 2026 Oliver Wyman's 2026 Healthcare RCM Survey of 200+ decision-makers and 90 end users finds AI adoption moving from pilots to enterprise scale. Ambient documentation, coding automation and electronic prior authorization are the top investment areas cited by respondents. Revenue cycle management (RCM) is emerging as one of the first areas where AI is delivering tangible, repeatable impact at scale. Source: [Oliver Wyman](https://www.oliverwyman.com/our-expertise/perspectives/health/2026/may/ai-impact-revenue-cycle-healthcare.html) Revenue cycle management (RCM) is emerging as one of the first areas where AI is delivering tangible, repeatable impact at scale. Source: [Oliver Wyman](https://www.oliverwyman.com/our-expertise/perspectives/health/2026/may/ai-impact-revenue-cycle-healthcare.html) Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Find even more ## Related news & updates The latest industry news, interviews, technologies, and resources. [ Regulatory & CMS ### States Continue Efforts to Regulate AI in Healthcare: A Review of Legislation Passed in 2026 A 2026 legislative review tracks state laws enacted this year regulating insurers' use of AI in prior authorization and claims decisions. States including Georgia, Maryland, Washington and Utah added disclosure, human-oversight and reporting requirements for AI-assisted adverse determinations. Holland & KnightMay 26, 2026 ](https://www.flobotics.io/rcm-industry-news/2026-07-19-states-continue-efforts-to-regulate-ai-in-healthcare)[ Prior Authorization ### Optum unveils two new AI tools for digital prior authorization Optum is launching two AI tools — Digital Auth Complete and InterQual Auth Accelerator — to cut prior authorization delays. Digital Auth Complete integrates into the EHR and automates multiple parts of the process to return responses faster. Fierce HealthcareJuly 19, 2026 ](https://www.flobotics.io/rcm-industry-news/optum-ai-digital-prior-authorization-tools)[ Revenue Cycle Management ### Athenahealth rolls out 80+ AI-native revenue cycle features Athenahealth built more than 80 AI-native features into athenaOne, targeting high-friction tasks such as insurance verification, coding, prior authorization and denials. AI voice agents place over 23,000 prior authorization calls each month, some completed in under an hour. Becker's Hospital ReviewJune 3, 2026 ](https://www.flobotics.io/rcm-industry-news/athenahealth-80-ai-native-revenue-cycle-tools) [All RCM news →](https://www.flobotics.io/rcm-industry-news) --- # Autonomize AI Launches Genie AI Autonomous Agent Canonical: https://www.flobotics.io/rcm-industry-news/autonomize-ai-launches-genie-ai-autonomous-agent Published: 2026-07-15 Updated: 2026-07-20 --- [Home](https://www.flobotics.io/)/[RCM industry news](https://www.flobotics.io/rcm-industry-news)/Autonomize AI Launches Genie AI Autonomous Agent Competitive & Market # Autonomize AI Launches Genie AI Autonomous Agent Autonomize AI (GlobeNewswire)July 15, 2026 Autonomize AI launched Genie AI, a healthcare-native AI agent that lets clinicians, care managers, and operations staff build automated workflows using natural language. The tool targets utilization management, prior authorization, appeals, and care coordination, and is designed to keep generated workflows auditable and governed within existing enterprise systems. We built Genie around a simple belief: the people closest to a problem are often best positioned to solve it. Source: [Autonomize AI (GlobeNewswire)](https://www.globenewswire.com/news-release/2026/07/15/3327948/0/en/Autonomize-AI-Launches-Genie-AI-Autonomous-Agent-Transforming-Every-Healthcare-Expert-into-an-AI-Builder.html) We built Genie around a simple belief: the people closest to a problem are often best positioned to solve it. Source: [Autonomize AI (GlobeNewswire)](https://www.globenewswire.com/news-release/2026/07/15/3327948/0/en/Autonomize-AI-Launches-Genie-AI-Autonomous-Agent-Transforming-Every-Healthcare-Expert-into-an-AI-Builder.html) Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Find even more ## Related news & updates The latest industry news, interviews, technologies, and resources. [ Prior Authorization ### Optum unveils two new AI tools for digital prior authorization Optum is launching two AI tools — Digital Auth Complete and InterQual Auth Accelerator — to cut prior authorization delays. Digital Auth Complete integrates into the EHR and automates multiple parts of the process to return responses faster. Fierce HealthcareJuly 19, 2026 ](https://www.flobotics.io/rcm-industry-news/optum-ai-digital-prior-authorization-tools)[ Competitive & Market ### UiPath launches agentic AI solutions for healthcare administration UiPath announced agentic AI solutions for healthcare: medical records summarization, claim denial prevention and resolution, and prior authorization — using agentic automation to accelerate revenue cycle management. UiPath (Investor Relations)July 19, 2026 ](https://www.flobotics.io/rcm-industry-news/uipath-agentic-ai-healthcare-admin)[ Prior Authorization ### Abridge teams with Availity to scale real-time prior authorization An integration between Abridge and Availity aims to speed prior authorization from weeks to minutes, shifting the process from post-visit to real time during the patient exam. Fierce HealthcareJuly 19, 2026 ](https://www.flobotics.io/rcm-industry-news/abridge-availity-real-time-prior-auth) [All RCM news →](https://www.flobotics.io/rcm-industry-news) --- # MDaudit Adds Auditor Assist to Its Continuous Risk Monitoring Suite Canonical: https://www.flobotics.io/rcm-industry-news/mdaudit-adds-auditor-assist-continuous-risk-monitoring Published: 2026-07-15 Updated: 2026-07-20 --- [Home](https://www.flobotics.io/)/[RCM industry news](https://www.flobotics.io/rcm-industry-news)/MDaudit Adds Auditor Assist to Its Continuous Risk… Claims & Denials # MDaudit Adds Auditor Assist to Its Continuous Risk Monitoring Suite MDaudit (GlobeNewswire)July 15, 2026 MDaudit added Auditor Assist, an AI-powered companion that helps human auditors review coding-integrity cases faster while keeping a human in control of the final call. The launch responds to a reported 30% year-over-year rise in payer audit volume, with coding-related denials up as much as 26%. Meaningful AI means we ask one question before anything ships: does this change the outcome? Source: [MDaudit (GlobeNewswire)](https://www.globenewswire.com/news-release/2026/07/15/3327808/0/en/MDaudit-Advances-Its-Meaningful-AI-Strategy-with-the-Addition-of-Auditor-Assist-to-Its-Continuous-Risk-Monitoring-Solutions-Suite.html) Meaningful AI means we ask one question before anything ships: does this change the outcome? Source: [MDaudit (GlobeNewswire)](https://www.globenewswire.com/news-release/2026/07/15/3327808/0/en/MDaudit-Advances-Its-Meaningful-AI-Strategy-with-the-Addition-of-Auditor-Assist-to-Its-Continuous-Risk-Monitoring-Solutions-Suite.html) Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Find even more ## Related news & updates The latest industry news, interviews, technologies, and resources. [ Prior Authorization ### Optum unveils two new AI tools for digital prior authorization Optum is launching two AI tools — Digital Auth Complete and InterQual Auth Accelerator — to cut prior authorization delays. Digital Auth Complete integrates into the EHR and automates multiple parts of the process to return responses faster. Fierce HealthcareJuly 19, 2026 ](https://www.flobotics.io/rcm-industry-news/optum-ai-digital-prior-authorization-tools)[ Competitive & Market ### UiPath launches agentic AI solutions for healthcare administration UiPath announced agentic AI solutions for healthcare: medical records summarization, claim denial prevention and resolution, and prior authorization — using agentic automation to accelerate revenue cycle management. UiPath (Investor Relations)July 19, 2026 ](https://www.flobotics.io/rcm-industry-news/uipath-agentic-ai-healthcare-admin)[ Prior Authorization ### Abridge teams with Availity to scale real-time prior authorization An integration between Abridge and Availity aims to speed prior authorization from weeks to minutes, shifting the process from post-visit to real time during the patient exam. Fierce HealthcareJuly 19, 2026 ](https://www.flobotics.io/rcm-industry-news/abridge-availity-real-time-prior-auth) [All RCM news →](https://www.flobotics.io/rcm-industry-news) --- # Black Book Research Recognizes Inovalon for End-to-End Revenue Cycle Platform and Eligibility Intelligence Canonical: https://www.flobotics.io/rcm-industry-news/black-book-research-recognizes-inovalon-rcm-platform Published: 2026-07-15 Updated: 2026-07-20 --- [Home](https://www.flobotics.io/)/[RCM industry news](https://www.flobotics.io/rcm-industry-news)/Black Book Research Recognizes Inovalon for End-to-End… Revenue Cycle Management # Black Book Research Recognizes Inovalon for End-to-End Revenue Cycle Platform and Eligibility Intelligence Business Wire (Inovalon)July 15, 2026 Inovalon was named a top-rated revenue cycle management vendor by Black Book Research in two categories: full-suite intake-to-final-payment platform breadth, and real-time eligibility and benefits verification. The ranking is based on evaluations from more than 1,300 hospital and health system finance leaders. Provider RCM buyers are drawing clear distinctions between platforms that deliver end-to-end control and those that address only pieces of the problem. Source: [Business Wire (Inovalon)](https://www.businesswire.com/news/home/20260715219967/en/Black-Book-Research-Recognizes-Inovalon-for-End-to-End-Revenue-Cycle-Platform-and-Eligibility-Intelligence) Provider RCM buyers are drawing clear distinctions between platforms that deliver end-to-end control and those that address only pieces of the problem. Source: [Business Wire (Inovalon)](https://www.businesswire.com/news/home/20260715219967/en/Black-Book-Research-Recognizes-Inovalon-for-End-to-End-Revenue-Cycle-Platform-and-Eligibility-Intelligence) Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Find even more ## Related news & updates The latest industry news, interviews, technologies, and resources. [ Prior Authorization ### Optum unveils two new AI tools for digital prior authorization Optum is launching two AI tools — Digital Auth Complete and InterQual Auth Accelerator — to cut prior authorization delays. Digital Auth Complete integrates into the EHR and automates multiple parts of the process to return responses faster. Fierce HealthcareJuly 19, 2026 ](https://www.flobotics.io/rcm-industry-news/optum-ai-digital-prior-authorization-tools)[ Competitive & Market ### UiPath launches agentic AI solutions for healthcare administration UiPath announced agentic AI solutions for healthcare: medical records summarization, claim denial prevention and resolution, and prior authorization — using agentic automation to accelerate revenue cycle management. UiPath (Investor Relations)July 19, 2026 ](https://www.flobotics.io/rcm-industry-news/uipath-agentic-ai-healthcare-admin)[ Prior Authorization ### Abridge teams with Availity to scale real-time prior authorization An integration between Abridge and Availity aims to speed prior authorization from weeks to minutes, shifting the process from post-visit to real time during the patient exam. Fierce HealthcareJuly 19, 2026 ](https://www.flobotics.io/rcm-industry-news/abridge-availity-real-time-prior-auth) [All RCM news →](https://www.flobotics.io/rcm-industry-news) --- # CMS CY 2027 Physician Fee Schedule Proposed Rule Includes Interoperability RFI Canonical: https://www.flobotics.io/rcm-industry-news/cms-2027-physician-fee-schedule-interoperability-rfi Published: 2026-07-14 Updated: 2026-07-20 --- [Home](https://www.flobotics.io/)/[RCM industry news](https://www.flobotics.io/rcm-industry-news)/CMS CY 2027 Physician Fee Schedule Proposed Rule Includes… Regulatory & CMS # CMS CY 2027 Physician Fee Schedule Proposed Rule Includes Interoperability RFI CMSJuly 14, 2026 CMS's CY 2027 Physician Fee Schedule proposed rule includes a Request for Information on duplicate laboratory testing and imaging caused by data siloed within electronic health record systems. Comments on the RFI are due September 14, 2026. Diagnostic imaging and laboratory test results are frequently siloed within acquiring electronic health record systems, leaving treating healthcare providers unaware of their existence and unable to access them across care settings. Source: [CMS](https://www.cms.gov/newsroom/fact-sheets/calendar-year-cy-2027-medicare-physician-fee-schedule-proposed-rule) Diagnostic imaging and laboratory test results are frequently siloed within acquiring electronic health record systems, leaving treating healthcare providers unaware of their existence and unable to access them across care settings. Source: [CMS](https://www.cms.gov/newsroom/fact-sheets/calendar-year-cy-2027-medicare-physician-fee-schedule-proposed-rule) Let’s talk! It’s a 30-minute call. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) Find even more ## Related news & updates The latest industry news, interviews, technologies, and resources. [ Prior Authorization ### Optum unveils two new AI tools for digital prior authorization Optum is launching two AI tools — Digital Auth Complete and InterQual Auth Accelerator — to cut prior authorization delays. Digital Auth Complete integrates into the EHR and automates multiple parts of the process to return responses faster. Fierce HealthcareJuly 19, 2026 ](https://www.flobotics.io/rcm-industry-news/optum-ai-digital-prior-authorization-tools)[ Competitive & Market ### UiPath launches agentic AI solutions for healthcare administration UiPath announced agentic AI solutions for healthcare: medical records summarization, claim denial prevention and resolution, and prior authorization — using agentic automation to accelerate revenue cycle management. UiPath (Investor Relations)July 19, 2026 ](https://www.flobotics.io/rcm-industry-news/uipath-agentic-ai-healthcare-admin)[ Prior Authorization ### Abridge teams with Availity to scale real-time prior authorization An integration between Abridge and Availity aims to speed prior authorization from weeks to minutes, shifting the process from post-visit to real time during the patient exam. Fierce HealthcareJuly 19, 2026 ](https://www.flobotics.io/rcm-industry-news/abridge-availity-real-time-prior-auth) [All RCM news →](https://www.flobotics.io/rcm-industry-news) --- # Blog | Page 2 | Flobotics Canonical: https://www.flobotics.io/blog/page/2 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Page 2 Articles · page 2 of 21 # Everything about RCM automation From failed bots to million-dollar recoveries – stories, frameworks, and lessons from the field. AllAI 49Claims 3Denials 2Eligibility 10Healthcare 92RCM 78RPA 88Search articles [ AI ### What Is Google Antigravity | Basics Guide What is Google Antigravity? A basics guide to how it works, its free tier for production workflows, and how it compares to Claude Code. Bart TeodorczukJune 29, 2026 ](https://www.flobotics.io/blog/what-is-google-antigravity)[ AIHealthcareRCM ### ChatGPT 5.2 for Healthcare ChatGPT 5.2 for healthcare: where it delivers real production value in RCM, and why precision-critical workflows still need a human control gate. Bart TeodorczukJune 18, 2026 ](https://www.flobotics.io/blog/chat-gpt-healthcare-5-2)[ RCMAIHealthcare ### XiFin Implementation: A CFO’s Perspective XiFin implementation for CFOs: cutting through the marketing buzz on revenue recognition, ASC 606, and real ROI before you sign. Krzysztof SzwedJune 17, 2026 ](https://www.flobotics.io/blog/xifin-implementation-for-cfo)[ HealthcareAIRCM ### XiFin - 101 Guide What is XiFin? A 101 guide - plus why a private equity firm holding it for 12 years, nearly double the industry norm, matters for buyers. Jędrzej SzymulaJune 15, 2026 ](https://www.flobotics.io/blog/xifin-101-guide)[ HealthcareRCM ### Digital Patient Engagement: What It Is and Why It Matters Digital patient engagement, explained: how portals, apps, and online billing shape patient payment rates and RCM collections. Bart TeodorczukJune 09, 2026 ](https://www.flobotics.io/blog/digital-patient-engagement-explanation)[ HealthcareRCM ### What Is HIPAA? Rules, Penalties and Impact on RCM What is HIPAA? The federal law governing PHI privacy and security in US healthcare - RCM teams face penalties up to $1.9M per violation category. Karl MielnickiJune 08, 2026 ](https://www.flobotics.io/blog/health-insurance-portability-and-accountability-act-hipaa-explanation)[ HealthcareRCM ### What Is a LIMS? Laboratory Information Management Systems What is a LIMS? A laboratory information management system tracks samples, experiments, and results to streamline lab operations and reporting. Jędrzej SzymulaJune 07, 2026 ](https://www.flobotics.io/blog/laboratory-information-management-system-lims)[ HealthcareRCM ### What Is PHI? Protected Health Information Explained What is protected health information (PHI)? A HIPAA guide to identifiable patient data and the RCM controls needed - breaches risk penalties up to $1.9M. Krzysztof SzwedJune 05, 2026 ](https://www.flobotics.io/blog/protected-health-information-phi)[ HealthcareRCM ### Net Collection Rate (NCR): Formula and Benchmarks Net Collection Rate (NCR) explained: the RCM metric measuring collectible revenue actually captured. Best practice is 95-99% - below that, revenue leaks. Bart TeodorczukJune 04, 2026 ](https://www.flobotics.io/blog/net-collection-rate-ncr) No articles match. Clear filters [1](https://www.flobotics.io/blog)[2](https://www.flobotics.io/blog/page/2)[3](https://www.flobotics.io/blog/page/3)[4](https://www.flobotics.io/blog/page/4)[5](https://www.flobotics.io/blog/page/5)[6](https://www.flobotics.io/blog/page/6)[7](https://www.flobotics.io/blog/page/7)[8](https://www.flobotics.io/blog/page/8)[9](https://www.flobotics.io/blog/page/9)[10](https://www.flobotics.io/blog/page/10)[11](https://www.flobotics.io/blog/page/11)[12](https://www.flobotics.io/blog/page/12)[13](https://www.flobotics.io/blog/page/13)[14](https://www.flobotics.io/blog/page/14)[15](https://www.flobotics.io/blog/page/15)[16](https://www.flobotics.io/blog/page/16)[17](https://www.flobotics.io/blog/page/17)[18](https://www.flobotics.io/blog/page/18)[19](https://www.flobotics.io/blog/page/19)[20](https://www.flobotics.io/blog/page/20)[21](https://www.flobotics.io/blog/page/21) --- # Blog | Page 3 | Flobotics Canonical: https://www.flobotics.io/blog/page/3 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Page 3 Articles · page 3 of 21 # Everything about RCM automation From failed bots to million-dollar recoveries – stories, frameworks, and lessons from the field. AllAI 49Claims 3Denials 2Eligibility 10Healthcare 92RCM 78RPA 88Search articles [ HealthcareRCM ### Charge Capture: What It Is and How It Works in RCM What is charge capture? How converting clinical services into billable charges kicks off the revenue cycle, and why missed charges are lost revenue. Karl MielnickiJune 03, 2026 ](https://www.flobotics.io/blog/charge-capture-explanation)[ HealthcareRCM ### Patient Access: The Front End of the Revenue Cycle What is patient access? A guide to the front-end RCM steps - scheduling, registration, eligibility checks, and prior authorization - that start every claim. Jędrzej SzymulaJune 02, 2026 ](https://www.flobotics.io/blog/patient-access-explanation)[ HealthcareRCM ### Clean Claim Rate (CCR): Definition and Benchmarks Clean Claim Rate (CCR) guide: the foundational RCM metric behind denials, DAR, and collections, with a 98%+ target. Bart TeodorczukJune 01, 2026 ](https://www.flobotics.io/blog/clean-claim-rate-ccr-explanation)[ HealthcareRCMAI ### CFO's Take On: AWS Connect Health AWS Connect Health, a CFO's take: what you're actually buying before committing capital, and the Business Associate Agreement gaps to check first. Krzysztof SzwedMay 31, 2026 ](https://www.flobotics.io/blog/aws-connect-health-cafc9)[ HealthcareRCM ### Intelligent Document Processing (IDP) in Healthcare RCM Intelligent Document Processing (IDP) uses AI, OCR, and NLP to turn scanned EOBs and faxes into automated RCM workflows in 2026. Krzysztof SzwedMay 31, 2026 ](https://www.flobotics.io/blog/intelligent-document-processing-idp-explanation)[ AIHealthcareRCM ### Claude for Healthcare: Technical Integration Claude for healthcare technical integration: what to confirm in your Anthropic BAA on audit trails and PHI data-loss prevention before you sign. Jacek ŻukowskiMay 29, 2026 ](https://www.flobotics.io/blog/claude-for-healthcare-technicals)[ RCMHealthcare ### Value-Based Care (VBC): What It Means for RCM Value-based care (VBC) guide: what outcomes-based reimbursement means for quality reporting, risk adjustment, and RCM documentation. Jędrzej SzymulaMay 28, 2026 ](https://www.flobotics.io/blog/value-based-care-vbc-explanation)[ AIRCMHealthcare ### Claude for Healthcare from Anthropic Claude for Healthcare from Anthropic: what's still unclear on data storage, routing, and third-party access before you roll it out to staff. Dominik PutMay 26, 2026 ](https://www.flobotics.io/blog/anthropic-annoucement-claude-for-healthcare)[ HealthcareRCM ### Turnaround Time (TAT) in Healthcare RCM: Benchmarks Turnaround Time (TAT) in healthcare RCM, explained - see how automation compresses claim and denial TAT by 60-80% and cuts Days in AR. Karl MielnickiMay 26, 2026 ](https://www.flobotics.io/blog/turnaround-time-tat-explanation) No articles match. Clear filters [1](https://www.flobotics.io/blog)[2](https://www.flobotics.io/blog/page/2)[3](https://www.flobotics.io/blog/page/3)[4](https://www.flobotics.io/blog/page/4)[5](https://www.flobotics.io/blog/page/5)[6](https://www.flobotics.io/blog/page/6)[7](https://www.flobotics.io/blog/page/7)[8](https://www.flobotics.io/blog/page/8)[9](https://www.flobotics.io/blog/page/9)[10](https://www.flobotics.io/blog/page/10)[11](https://www.flobotics.io/blog/page/11)[12](https://www.flobotics.io/blog/page/12)[13](https://www.flobotics.io/blog/page/13)[14](https://www.flobotics.io/blog/page/14)[15](https://www.flobotics.io/blog/page/15)[16](https://www.flobotics.io/blog/page/16)[17](https://www.flobotics.io/blog/page/17)[18](https://www.flobotics.io/blog/page/18)[19](https://www.flobotics.io/blog/page/19)[20](https://www.flobotics.io/blog/page/20)[21](https://www.flobotics.io/blog/page/21) --- # Blog | Page 4 | Flobotics Canonical: https://www.flobotics.io/blog/page/4 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Page 4 Articles · page 4 of 21 # Everything about RCM automation From failed bots to million-dollar recoveries – stories, frameworks, and lessons from the field. AllAI 49Claims 3Denials 2Eligibility 10Healthcare 92RCM 78RPA 88Search articles [ HealthcareRCM ### Net Promoter Score (NPS) in Healthcare Net Promoter Score (NPS) in healthcare ties patient loyalty to billing experience - and increasingly to Value-Based Care reimbursement. Bart TeodorczukMay 21, 2026 ](https://www.flobotics.io/blog/nps-net-promoter-score-explanation)[ HealthcareRCM ### Days in Accounts Receivable (DAR): Formula and Benchmarks Days in Accounts Receivable (DAR) guide: why 30-35 days is best practice and anything above 50 signals collection trouble. Krzysztof SzwedMay 21, 2026 ](https://www.flobotics.io/blog/days-in-accounts-receivable-dar-explanation)[ RCMHealthcare ### NextGen Automation | 2026 NextGen EHR automation: stop manual payer-portal copy-paste and validate claims against insurer rules before submission, not after denial. Bart TeodorczukMay 19, 2026 ](https://www.flobotics.io/blog/nextgen-automation)[ AIHealthcareRCM ### AWS Connect Health: RCM Salvation or Infrastructure Play? AWS Connect Health: is Amazon's new healthcare platform an RCM solution or just an infrastructure play? We break down what it actually delivers. Bart TeodorczukMay 18, 2026 ](https://www.flobotics.io/blog/aws-connect-health)[ HealthcareRCM ### Initial Denial Rate: How to Measure and Lower It Initial denial rate, explained: what counts as a first-pass claim rejection and how to benchmark and lower yours in 2026. Jędrzej SzymulaMay 18, 2026 ](https://www.flobotics.io/blog/initial-denial-percentage-explanation)[ HealthcareRCM ### Cost to Collect (CTC): Definition and Benchmarks Cost to Collect (CTC) benchmarks sit at 3-5% of net revenue - a 1% cut on $10M in collections frees up $100,000 in cash. Karl MielnickiMay 18, 2026 ](https://www.flobotics.io/blog/cost-to-collect-ctc-explanation)[ AIRPA ### UiPath's Agentic AI: Orchestrating Autonomous Agents in Enterprise Automation UiPath's agentic AI - Maestro, Agent Builder, Autopilot - orchestrates autonomous agents at scale, benchmarked against Microsoft and Automation Anywhere. Bart TeodorczukMay 15, 2026 ](https://www.flobotics.io/blog/uipaths-agentic-ai-orchestration)[ HealthcareAI ### Claude for Healthcare Overview | 2026 Claude for Healthcare: Anthropic's 2026 toolkit for US medical data, with HIPAA compliance details and case studies from Banner Health and Novartis. Jędrzej SzymulaMay 06, 2026 ](https://www.flobotics.io/blog/claude-for-healthcare)[ HealthcareAI ### DrChrono EHR Automation | 2026 DrChrono EHR automation: how the 2026 CMS Prior Authorization Final Rule turns RCM automation from optional to mandatory for practices billing $500K-$8M. Jędrzej SzymulaMay 04, 2026 ](https://www.flobotics.io/blog/dr-chrono-automation) No articles match. Clear filters [1](https://www.flobotics.io/blog)[2](https://www.flobotics.io/blog/page/2)[3](https://www.flobotics.io/blog/page/3)[4](https://www.flobotics.io/blog/page/4)[5](https://www.flobotics.io/blog/page/5)[6](https://www.flobotics.io/blog/page/6)[7](https://www.flobotics.io/blog/page/7)[8](https://www.flobotics.io/blog/page/8)[9](https://www.flobotics.io/blog/page/9)[10](https://www.flobotics.io/blog/page/10)[11](https://www.flobotics.io/blog/page/11)[12](https://www.flobotics.io/blog/page/12)[13](https://www.flobotics.io/blog/page/13)[14](https://www.flobotics.io/blog/page/14)[15](https://www.flobotics.io/blog/page/15)[16](https://www.flobotics.io/blog/page/16)[17](https://www.flobotics.io/blog/page/17)[18](https://www.flobotics.io/blog/page/18)[19](https://www.flobotics.io/blog/page/19)[20](https://www.flobotics.io/blog/page/20)[21](https://www.flobotics.io/blog/page/21) --- # Blog | Page 5 | Flobotics Canonical: https://www.flobotics.io/blog/page/5 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Page 5 Articles · page 5 of 21 # Everything about RCM automation From failed bots to million-dollar recoveries – stories, frameworks, and lessons from the field. AllAI 49Claims 3Denials 2Eligibility 10Healthcare 92RCM 78RPA 88Search articles [ HealthcareRCM ### Underpayment Recovery in Healthcare, Explained Underpayment recovery uses automated contract comparison to catch the 3-10% of claims payers routinely underpay. Jędrzej SzymulaMay 04, 2026 ](https://www.flobotics.io/blog/underpayment-recovery-explanation)[ HealthcareRCM ### Claim Turnaround Time (CTT): Benchmarks and Root Causes Claim Turnaround Time (CTT), explained: why 14-21 days is best-in-class and 45+ days signals a billing cycle problem. Krzysztof SzwedMay 04, 2026 ](https://www.flobotics.io/blog/claim-turnaround-time-ctt-explanation)[ HealthcareRCM ### Healthcare Reimbursements: How Payment Rates Are Set Healthcare reimbursement guide: how payment rates are set and where automation closes the gap between allowed and collected amounts. Karl MielnickiMay 01, 2026 ](https://www.flobotics.io/blog/reimbursements-explanation)[ HealthcareRCM ### What Is Prior Authorization (Pre-Auth) in Healthcare? Prior authorization (pre-auth), explained: the process behind healthcare's 13-hour weekly physician burden - and how automation cuts each cycle to minutes. Bart TeodorczukApril 30, 2026 ](https://www.flobotics.io/blog/prior-authorization-pre-auth-explanation)[ HealthcareRCM ### Predictive Analytics in RCM: Key Applications Predictive analytics in RCM forecasts denials and non-payment risk, turning reactive billing into proactive revenue protection. Krzysztof SzwedApril 28, 2026 ](https://www.flobotics.io/blog/predictive-analytics-explanation)[ HealthcareRCM ### Patient Statement: What to Include on a Medical Bill Patient statement guide: what belongs on the final bill patients receive - and why clarity here drives faster payment. Jędrzej SzymulaApril 23, 2026 ](https://www.flobotics.io/blog/patient-statement-explanation)[ Healthcare ### Medicare ICGP | 2026 Medicare ICGP explained: CMS's new machine-learning audit engine flags billing errors in real time, raising remediation costs 100-150% for hospitals that lag. Jędrzej SzymulaApril 22, 2026 ](https://www.flobotics.io/blog/medicare-icgp)[ HealthcareRCM ### Posting Correspondence in RCM: EOBs, ERAs and Automation Posting correspondence, explained: why every unprocessed EOB or ERA means delayed cash and a missed denial in your RCM workflow. Karl MielnickiApril 17, 2026 ](https://www.flobotics.io/blog/posting-correspondence-explanation)[ HealthcareAIRPA ### Epic Automation | 2026 Epic Systems revenue cycle automation: why the EHR powering 300+ health systems still needs RPA to close labor, payer, and margin gaps in 2026. Jędrzej SzymulaApril 10, 2026 ](https://www.flobotics.io/blog/epic-automation) No articles match. Clear filters [1](https://www.flobotics.io/blog)[2](https://www.flobotics.io/blog/page/2)[3](https://www.flobotics.io/blog/page/3)[4](https://www.flobotics.io/blog/page/4)[5](https://www.flobotics.io/blog/page/5)[6](https://www.flobotics.io/blog/page/6)[7](https://www.flobotics.io/blog/page/7)[8](https://www.flobotics.io/blog/page/8)[9](https://www.flobotics.io/blog/page/9)[10](https://www.flobotics.io/blog/page/10)[11](https://www.flobotics.io/blog/page/11)[12](https://www.flobotics.io/blog/page/12)[13](https://www.flobotics.io/blog/page/13)[14](https://www.flobotics.io/blog/page/14)[15](https://www.flobotics.io/blog/page/15)[16](https://www.flobotics.io/blog/page/16)[17](https://www.flobotics.io/blog/page/17)[18](https://www.flobotics.io/blog/page/18)[19](https://www.flobotics.io/blog/page/19)[20](https://www.flobotics.io/blog/page/20)[21](https://www.flobotics.io/blog/page/21) --- # Blog | Page 6 | Flobotics Canonical: https://www.flobotics.io/blog/page/6 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Page 6 Articles · page 6 of 21 # Everything about RCM automation From failed bots to million-dollar recoveries – stories, frameworks, and lessons from the field. AllAI 49Claims 3Denials 2Eligibility 10Healthcare 92RCM 78RPA 88Search articles [ HealthcareAIRPA ### Oracle Healthcare Automation | 2026 Oracle health automation: from database vendor to clinical and financial operations player - what RCM directors need to know about Oracle Health in 2026. Jędrzej SzymulaApril 10, 2026 ](https://www.flobotics.io/blog/oracle-healthcare-automation)[ HealthcareRCM ### What Is Payment Posting (Cash Posting) in Medical Billing? Payment posting (cash posting) reconciles payer and patient payments against claims, surfacing denials faster in 2026. Bart TeodorczukApril 10, 2026 ](https://www.flobotics.io/blog/payment-posting-cash-posting-explanation)[ EligibilityHealthcareRCM ### Insurance Eligibility Verification in Healthcare, Explained Eligibility verification guide: confirming insurance coverage and patient financial responsibility before the visit, in real time. Krzysztof SzwedApril 08, 2026 ](https://www.flobotics.io/blog/eligibility-verification-explanation)[ HealthcareRCM ### What Is Medical Coding? ICD-10 vs. CPT/HCPCS Medical coding, explained: how ICD-10 diagnoses and CPT/HCPCS procedures become the codes that drive clean claims and reimbursement. Jędrzej SzymulaApril 07, 2026 ](https://www.flobotics.io/blog/medical-coding-explanation)[ AIRPA ### We are a "Top Workday Implementation Partner for 2026" according to SuperbCompanies! Flobotics named a Top Workday Implementation Partner for 2026 by SuperbCompanies, ranked among 49 vetted firms for delivery and optimization results. Jędrzej SzymulaApril 05, 2026 ](https://www.flobotics.io/blog/flobotics-superbcompanies-top-workday-implementation-company-2026)[ HealthcareRCM ### What Is Denials Management? Process and Benchmarks Denials management tackles denial rates now above 20%, where every reworked claim costs about $44 - and prevention pays off. Karl MielnickiApril 02, 2026 ](https://www.flobotics.io/blog/denials-management-explanation)[ HealthcareRCM ### Medical Necessity: How Payers Decide What They Cover Medical necessity, explained: how payers decide if a service qualifies for coverage, and what proof stops denials before they start. Bart TeodorczukMarch 30, 2026 ](https://www.flobotics.io/blog/medical-necessity-explanation)[ HealthcareAIRCM ### Meditech Automation | 2026 Meditech automation: why strong transaction handling still stalls on cross-workflow orchestration, and how to scale past it. Jędrzej SzymulaMarch 25, 2026 ](https://www.flobotics.io/blog/meditech-automation)[ HealthcareRCM ### What Is Claim Scrubbing? What Gets Checked Before Submission Claim scrubbing, explained: how automated pre-submission checks catch errors that cost $25-$44 per claim to fix after denial. Krzysztof SzwedMarch 24, 2026 ](https://www.flobotics.io/blog/claim-scrubbing-explanation) No articles match. Clear filters [1](https://www.flobotics.io/blog)[2](https://www.flobotics.io/blog/page/2)[3](https://www.flobotics.io/blog/page/3)[4](https://www.flobotics.io/blog/page/4)[5](https://www.flobotics.io/blog/page/5)[6](https://www.flobotics.io/blog/page/6)[7](https://www.flobotics.io/blog/page/7)[8](https://www.flobotics.io/blog/page/8)[9](https://www.flobotics.io/blog/page/9)[10](https://www.flobotics.io/blog/page/10)[11](https://www.flobotics.io/blog/page/11)[12](https://www.flobotics.io/blog/page/12)[13](https://www.flobotics.io/blog/page/13)[14](https://www.flobotics.io/blog/page/14)[15](https://www.flobotics.io/blog/page/15)[16](https://www.flobotics.io/blog/page/16)[17](https://www.flobotics.io/blog/page/17)[18](https://www.flobotics.io/blog/page/18)[19](https://www.flobotics.io/blog/page/19)[20](https://www.flobotics.io/blog/page/20)[21](https://www.flobotics.io/blog/page/21) --- # Blog | Page 7 | Flobotics Canonical: https://www.flobotics.io/blog/page/7 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Page 7 Articles · page 7 of 21 # Everything about RCM automation From failed bots to million-dollar recoveries – stories, frameworks, and lessons from the field. AllAI 49Claims 3Denials 2Eligibility 10Healthcare 92RCM 78RPA 88Search articles [ HealthcareRCMAI ### athenahealth Automation | 2026 athenahealth automation: what its shared rules engine standardizes well, and where you still need custom workflow control. Jędrzej SzymulaMarch 23, 2026 ](https://www.flobotics.io/blog/athenahealth-automation)[ Healthcare ### Contractual Adjustment (Allowance): Meaning in Medical Billing Contractual adjustment (allowance), explained: why this write-off isn't lost revenue - and how mistracking hides real underpayments. Krzysztof SzwedMarch 20, 2026 ](https://www.flobotics.io/blog/contractual-adjustment-allowance-explanation)[ HealthcareRCM ### Denials Appeal Process: Levels of Appeal Explained Denials appeal process, explained: with commercial overturn rates dropping from 56% to 45%, see what still wins appeals. Bart TeodorczukMarch 18, 2026 ](https://www.flobotics.io/blog/denials-appeal-explanation)[ HealthcareRCM ### Credit Balance Resolution in Healthcare, Explained Credit balance resolution, explained: why federal law gives providers 60 days to repay Medicare and Medicaid overpayments. Jędrzej SzymulaMarch 18, 2026 ](https://www.flobotics.io/blog/credit-balance-resolution-explanation)[ Healthcare ### What Is an HRA? | 2026 What is a Health Risk Assessment (HRA)? See how HRAs now drive population health strategy and revenue cycle performance. Jędrzej SzymulaMarch 16, 2026 ](https://www.flobotics.io/blog/what-is-hra)[ RCMHealthcare ### Revenue Cycle Management in Cardiology Cardiology revenue cycle management: why complex procedures like electrophysiology demand a more sophisticated RCM back-end. Jędrzej SzymulaMarch 11, 2026 ](https://www.flobotics.io/blog/revenue-cycle-management-cardiology)[ HealthcareRCM ### No Surprises Act from an RCM Perspective | 2026 No Surprises Act, explained: key provisions, RCM impact, and the compliance steps that avoid costly billing disputes. Jędrzej SzymulaMarch 09, 2026 ](https://www.flobotics.io/blog/no-suprises-act-rcm)[ HealthcareRCM ### Clinical Documentation Integrity (CDI): Why It Matters Clinical Documentation Integrity (CDI), explained: how documentation gaps drive undercoding and silent revenue leakage. Karl MielnickiMarch 03, 2026 ](https://www.flobotics.io/blog/clinical-documentation-integrity-cdi-explanation)[ RCM ### Dental Revenue Cycle Management | 2026 Dental revenue cycle management: how practices are moving from semi-automated billing to predictive, human-in-the-loop RCM in 2026. Jędrzej SzymulaMarch 02, 2026 ](https://www.flobotics.io/blog/dental-revenue-cycle-management) No articles match. Clear filters [1](https://www.flobotics.io/blog)[2](https://www.flobotics.io/blog/page/2)[3](https://www.flobotics.io/blog/page/3)[4](https://www.flobotics.io/blog/page/4)[5](https://www.flobotics.io/blog/page/5)[6](https://www.flobotics.io/blog/page/6)[7](https://www.flobotics.io/blog/page/7)[8](https://www.flobotics.io/blog/page/8)[9](https://www.flobotics.io/blog/page/9)[10](https://www.flobotics.io/blog/page/10)[11](https://www.flobotics.io/blog/page/11)[12](https://www.flobotics.io/blog/page/12)[13](https://www.flobotics.io/blog/page/13)[14](https://www.flobotics.io/blog/page/14)[15](https://www.flobotics.io/blog/page/15)[16](https://www.flobotics.io/blog/page/16)[17](https://www.flobotics.io/blog/page/17)[18](https://www.flobotics.io/blog/page/18)[19](https://www.flobotics.io/blog/page/19)[20](https://www.flobotics.io/blog/page/20)[21](https://www.flobotics.io/blog/page/21) --- # Blog | Page 8 | Flobotics Canonical: https://www.flobotics.io/blog/page/8 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Page 8 Articles · page 8 of 21 # Everything about RCM automation From failed bots to million-dollar recoveries – stories, frameworks, and lessons from the field. AllAI 49Claims 3Denials 2Eligibility 10Healthcare 92RCM 78RPA 88Search articles [ RCMHealthcare ### RCM Automation in Healthcare | 2026 RCM automation in healthcare: how RPA, AI, and OCR cut billing errors, speed up claims, and reduce manual work in 2026 revenue cycle management. Bart TeodorczukFebruary 25, 2026 ](https://www.flobotics.io/blog/rcm-automation-healthcare)[ RCMRPA ### #5 Globally in GoodFirms’ Top RPA Companies for 2026! Flobotics ranked #5 globally among 857 vetted RPA companies by GoodFirms in 2026, recognized for non-invasive automation and verified client results. Jędrzej SzymulaFebruary 19, 2026 ](https://www.flobotics.io/blog/flobotics-goodfirms-top-rpa-companies-2026)[ RCM ### Revenue Cycle Management for Physician Practices RCM for physician practices: how the revenue cycle runs from appointment to final payment, and where precision pays off. Jędrzej SzymulaFebruary 19, 2026 ](https://www.flobotics.io/blog/revenue-cycle-management-for-physician-practices)[ AI ### Agentic AI Workflows Agentic AI workflows, explained: how autonomous AI agents handle multi-step RCM tasks beyond traditional rule-based RPA. February 04, 2026 ](https://www.flobotics.io/blog/agentic-ai-workflows)[ AIHealthcareRPA ### Compliance Automation in Healthcare Healthcare compliance automation: how Continuous Control Monitoring and Agentic AI cut administrative drag by 20-30% in 2026. February 04, 2026 ](https://www.flobotics.io/blog/compliance-automation-healthcare)[ HealthcareRCMAI ### RCM Outsourcing in Healthcare | 2026 RCM outsourcing in 2026: why offshore labor arbitrage is failing, and how Agentic AI outsourcing is replacing it. Bart TeodorczukFebruary 02, 2026 ](https://www.flobotics.io/blog/rcm-outsourcing-healthcare)[ RPAAI ### Top Software Development Company in Indiana? Yes! According to DesignRush Flobotics named a top Indiana software development company by DesignRush - see why we made the list among leading US automation and RPA firms. Jędrzej SzymulaJanuary 29, 2026 ](https://www.flobotics.io/blog/flobotics-designrush-top-software-company-indiana)[ RPAAI ### We Are Among the Top Business Consulting Companies in the USA for 2026! Flobotics named a top business consulting company in the USA for 2026 by Selectedfirms - recognized for business growth and strategy expertise. Jędrzej SzymulaJanuary 26, 2026 ](https://www.flobotics.io/blog/flobotics-top-business-consulting-companies-2026)[ RCMAIHealthcare ### RCM Statistics | 2026 Overview RCM statistics for 2026: denial rates hover near 5% and cost-to-collect keeps rising as manual processes lose ground. See the data. Jędrzej SzymulaJanuary 07, 2026 ](https://www.flobotics.io/blog/rcm-statistics-overview) No articles match. Clear filters [1](https://www.flobotics.io/blog)[2](https://www.flobotics.io/blog/page/2)[3](https://www.flobotics.io/blog/page/3)[4](https://www.flobotics.io/blog/page/4)[5](https://www.flobotics.io/blog/page/5)[6](https://www.flobotics.io/blog/page/6)[7](https://www.flobotics.io/blog/page/7)[8](https://www.flobotics.io/blog/page/8)[9](https://www.flobotics.io/blog/page/9)[10](https://www.flobotics.io/blog/page/10)[11](https://www.flobotics.io/blog/page/11)[12](https://www.flobotics.io/blog/page/12)[13](https://www.flobotics.io/blog/page/13)[14](https://www.flobotics.io/blog/page/14)[15](https://www.flobotics.io/blog/page/15)[16](https://www.flobotics.io/blog/page/16)[17](https://www.flobotics.io/blog/page/17)[18](https://www.flobotics.io/blog/page/18)[19](https://www.flobotics.io/blog/page/19)[20](https://www.flobotics.io/blog/page/20)[21](https://www.flobotics.io/blog/page/21) --- # Blog | Page 9 | Flobotics Canonical: https://www.flobotics.io/blog/page/9 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Page 9 Articles · page 9 of 21 # Everything about RCM automation From failed bots to million-dollar recoveries – stories, frameworks, and lessons from the field. AllAI 49Claims 3Denials 2Eligibility 10Healthcare 92RCM 78RPA 88Search articles [ RPAAI ### What Is Agentic AI? | The Not-So-Obvious Guide What is agentic AI? A clear guide to how autonomous AI agents reason, act, and differ from traditional rule-based automation. Jędrzej SzymulaDecember 09, 2025 ](https://www.flobotics.io/blog/agentic-ai)[ RPAAI ### Agentic AI Frameworks | 2026 Agentic AI frameworks in 2026: which stacks Google and other leaders are betting on, explained with clear, research-backed answers. Jędrzej SzymulaDecember 02, 2025 ](https://www.flobotics.io/blog/agentic-ai-frameworks)[ RCMAIHealthcare ### Top RCM Trends | 2026 Top RCM trends for 2026: what healthcare finance leaders at Deloitte, HFMA, and beyond are prioritizing to strengthen revenue cycles. Karl MielnickiNovember 24, 2025 ](https://www.flobotics.io/blog/top-rcm-trends-healthcare)[ RCMAIHealthcare ### Top 20 Healthcare Software Platforms in 2026 | The Execs’ Guide Payer software and more: explore the top 20 healthcare software platforms for 2026, from claims tools to EHR systems cutting denial rates. Jędrzej SzymulaOctober 27, 2025 ](https://www.flobotics.io/blog/top-20-healthcare-software-examples)[ RCMAIHealthcare ### Fixing Denial Codes | Agentic AI in Revenue Cycle Management Denial codes in healthcare billing: how AI automation fixes, resubmits, and prevents claim denials before they hit your revenue. Jędrzej SzymulaOctober 11, 2025 ](https://www.flobotics.io/blog/fixing-denial-codes-rcm-automation)[ AI ### The Hottest Agentic AI Examples and Use Cases in 2026 Agentic AI examples and use cases: how AI agents are automating healthcare RCM, legal drafting, and retail inventory in 2026. Jędrzej SzymulaOctober 02, 2025 ](https://www.flobotics.io/blog/hottest-agentic-ai-examples-and-use-cases)[ RCMAIHealthcare ### Agentic AI in Healthcare: From Hype to Real-World Impact Agentic AI in healthcare: how it differs from generative AI like ChatGPT and where it's already driving real clinical impact. Jędrzej SzymulaSeptember 22, 2025 ](https://www.flobotics.io/blog/agentic-ai-in-healthcare)[ RPAAI ### Agentic AI Tools and Platforms Overview 2026 Agentic AI platforms for 2026: an overview of the tools driving autonomous workflows, plus Gartner's cost-saving forecast. Jędrzej SzymulaSeptember 16, 2025 ](https://www.flobotics.io/blog/agentic-ai-tools-platforms-overview)[ RPAAI ### Agentic AI vs Generative AI: The Next Frontier of Intelligent Automation Generative AI vs. Agentic AI, explained: from ChatGPT's 100 million users in two months to the rise of autonomous automation in 2026. Jędrzej SzymulaSeptember 08, 2025 ](https://www.flobotics.io/blog/agentic-ai-vs-generative-ai) No articles match. Clear filters [1](https://www.flobotics.io/blog)[2](https://www.flobotics.io/blog/page/2)[3](https://www.flobotics.io/blog/page/3)[4](https://www.flobotics.io/blog/page/4)[5](https://www.flobotics.io/blog/page/5)[6](https://www.flobotics.io/blog/page/6)[7](https://www.flobotics.io/blog/page/7)[8](https://www.flobotics.io/blog/page/8)[9](https://www.flobotics.io/blog/page/9)[10](https://www.flobotics.io/blog/page/10)[11](https://www.flobotics.io/blog/page/11)[12](https://www.flobotics.io/blog/page/12)[13](https://www.flobotics.io/blog/page/13)[14](https://www.flobotics.io/blog/page/14)[15](https://www.flobotics.io/blog/page/15)[16](https://www.flobotics.io/blog/page/16)[17](https://www.flobotics.io/blog/page/17)[18](https://www.flobotics.io/blog/page/18)[19](https://www.flobotics.io/blog/page/19)[20](https://www.flobotics.io/blog/page/20)[21](https://www.flobotics.io/blog/page/21) --- # Blog | Page 10 | Flobotics Canonical: https://www.flobotics.io/blog/page/10 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Page 10 Articles · page 10 of 21 # Everything about RCM automation From failed bots to million-dollar recoveries – stories, frameworks, and lessons from the field. AllAI 49Claims 3Denials 2Eligibility 10Healthcare 92RCM 78RPA 88Search articles [ RPA ### What Is RPA? | Robotic Process Automation Robotic Process Automation (RPA), explained: how software bots run a 24/7 digital workforce that cuts costs and human error. Bart TeodorczukSeptember 01, 2025 ](https://www.flobotics.io/blog/robotic-process-automation)[ RCMHealthcare ### Key Revenue Cycle Management Metrics | 2026 Revenue cycle management metrics: the 25 KPIs healthcare leaders track in 2026, from denial rate to days in A/R and collections. Karl MielnickiAugust 26, 2025 ](https://www.flobotics.io/blog/revenue-cycle-management-metrics)[ RPAAI ### We saved $2 Million from a 50% improvement for PRMG using UiPath! PRMG loan processing automation case study - see how UiPath RPA delivered a 6:1 ROI and $1.2M in labor savings over 36 months for this mortgage lender. Jędrzej SzymulaAugust 07, 2025 ](https://www.flobotics.io/blog/flobotics-prmg-loan-processing-rpa-automation)[ RPA ### Axpo | $186,000 of profit in year one Axpo automation case study - see how RPA streamlined invoicing and reporting for Europe's largest renewable energy trader, saving $186K in year one. Bart TeodorczukJuly 22, 2025 ](https://www.flobotics.io/blog/axpo-automation)[ RPAHealthcare ### 10 Benefits of Artificial Intelligence in Healthcare Benefits of artificial intelligence in healthcare: 10 ways AI cuts administrative costs, speeds prior authorizations, and improves data accuracy. Bart TeodorczukJuly 22, 2025 ](https://www.flobotics.io/blog/benefits-artificial-intelligence-healthcare)[ RPAAI ### Agentic AI vs RPA: The Next Frontier of Intelligent Automation Agentic AI vs. RPA: how autonomous agents and traditional bots differ, where each fits, and why a hybrid approach is the 2026 strategy for CTOs. Bart TeodorczukJuly 14, 2025 ](https://www.flobotics.io/blog/agentic-ai-vs-rpa)[ RCMRPAHealthcare ### How Data Entry Automation Transforms Healthcare Operations Healthcare data entry automation: see how automated workflows sync patient records instantly and stop denied claims before they start. Michał RejmanJune 30, 2025 ](https://www.flobotics.io/blog/data-entry-automation-healthcare)[ RCMHealthcare ### How to Improve Revenue Cycle Management: 8 Strategies for Healthcare Leaders Revenue cycle management strategy: 8 practical steps healthcare leaders can use to boost collections and speed up the revenue cycle. Krzysztof SzwedJune 25, 2025 ](https://www.flobotics.io/blog/revenue-cycle-management-strategy)[ RCMRPAHealthcare ### Healthcare Document Processing: From Paperwork Pain to Automated Gain Healthcare document processing: see how automation turns intake forms, claims, and billing paperwork into a faster, error-free workflow. Bart TeodorczukJune 10, 2025 ](https://www.flobotics.io/blog/healthcare-document-processing) No articles match. Clear filters [1](https://www.flobotics.io/blog)[2](https://www.flobotics.io/blog/page/2)[3](https://www.flobotics.io/blog/page/3)[4](https://www.flobotics.io/blog/page/4)[5](https://www.flobotics.io/blog/page/5)[6](https://www.flobotics.io/blog/page/6)[7](https://www.flobotics.io/blog/page/7)[8](https://www.flobotics.io/blog/page/8)[9](https://www.flobotics.io/blog/page/9)[10](https://www.flobotics.io/blog/page/10)[11](https://www.flobotics.io/blog/page/11)[12](https://www.flobotics.io/blog/page/12)[13](https://www.flobotics.io/blog/page/13)[14](https://www.flobotics.io/blog/page/14)[15](https://www.flobotics.io/blog/page/15)[16](https://www.flobotics.io/blog/page/16)[17](https://www.flobotics.io/blog/page/17)[18](https://www.flobotics.io/blog/page/18)[19](https://www.flobotics.io/blog/page/19)[20](https://www.flobotics.io/blog/page/20)[21](https://www.flobotics.io/blog/page/21) --- # Blog | Page 11 | Flobotics Canonical: https://www.flobotics.io/blog/page/11 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Page 11 Articles · page 11 of 21 # Everything about RCM automation From failed bots to million-dollar recoveries – stories, frameworks, and lessons from the field. AllAI 49Claims 3Denials 2Eligibility 10Healthcare 92RCM 78RPA 88Search articles [ RCMRPAAI ### EHR Implementation: How to Not Screw It Up EHR implementation plan, explained: avoid costly integration mistakes and connect billing, records, and labs without disrupting patient care. Yana PokoraMay 26, 2025 ](https://www.flobotics.io/blog/ehr-implementation-plan)[ RPA ### UiPath Licensing Simplified: How BPO Makes Automation More Affordable Business process outsourcing for UiPath licensing: cut costs, avoid confusing tiers, and scale automation without overhiring. Karl MielnickiMay 16, 2025 ](https://www.flobotics.io/blog/business-process-outsourcing)[ RPA ### RPA Reloaded: 50+ Robotic Process Automation Statistics to Know in 2026 RPA statistics 2026: 50+ data points on robotic process automation adoption, ROI, and where the technology is headed next. Yana PokoraApril 15, 2025 ](https://www.flobotics.io/blog/rpa-statistics)[ AIRCM ### Forbes named us "#3 Best Polish Startup of 2025"! Flobotics named #3 on Forbes Poland's Best Polish Startups of 2025 (Service Company category) - recognized for scaling RPA and AI services in the US. Jędrzej SzymulaMarch 18, 2025 ](https://www.flobotics.io/blog/flobotics-forbes-polish-best-startups-2025)[ RCMRPAAI ### AI vs. RPA vs. ML in Healthcare RCM: A Deep Dive AI vs. RPA vs. ML in healthcare RCM: how each technology improves efficiency, accuracy, and compliance, and which to adopt first. Krzysztof SzwedFebruary 22, 2025 ](https://www.flobotics.io/blog/ai-rpa-ml-rcm)[ RPA ### Top Automation Trends in 2026 Automation trends for 2026: eight shifts in RPA, AI, and workflow automation that will shape how businesses operate this year. Krzysztof SzwedFebruary 03, 2025 ](https://www.flobotics.io/blog/top-automation-trends)[ Healthcare ### Top 30 Software Solutions for Healthcare in 2026 Healthcare software solutions: explore 30 essential tools for 2026, organized by function, to strengthen clinical care and streamline admin tasks. Yana PokoraDecember 23, 2024 ](https://www.flobotics.io/blog/healthcare-software)[ RPA ### Why Automation Training Is Key to Successful RPA Implementation RPA automation training: why employee training makes or breaks automation adoption, and how to prepare your team for working with bots. Karl MielnickiDecember 03, 2024 ](https://www.flobotics.io/blog/automation-training)[ AIHealthcare ### GenAI in Healthcare: Unlocking New Opportunities for Care and Operations Generative AI in healthcare: how GenAI builds on RPA to unlock new opportunities for hospitals, insurers, and pharma operations. Krzysztof SzwedNovember 06, 2024 ](https://www.flobotics.io/blog/genai-in-healthcare) No articles match. Clear filters [1](https://www.flobotics.io/blog)[2](https://www.flobotics.io/blog/page/2)[3](https://www.flobotics.io/blog/page/3)[4](https://www.flobotics.io/blog/page/4)[5](https://www.flobotics.io/blog/page/5)[6](https://www.flobotics.io/blog/page/6)[7](https://www.flobotics.io/blog/page/7)[8](https://www.flobotics.io/blog/page/8)[9](https://www.flobotics.io/blog/page/9)[10](https://www.flobotics.io/blog/page/10)[11](https://www.flobotics.io/blog/page/11)[12](https://www.flobotics.io/blog/page/12)[13](https://www.flobotics.io/blog/page/13)[14](https://www.flobotics.io/blog/page/14)[15](https://www.flobotics.io/blog/page/15)[16](https://www.flobotics.io/blog/page/16)[17](https://www.flobotics.io/blog/page/17)[18](https://www.flobotics.io/blog/page/18)[19](https://www.flobotics.io/blog/page/19)[20](https://www.flobotics.io/blog/page/20)[21](https://www.flobotics.io/blog/page/21) --- # Blog | Page 12 | Flobotics Canonical: https://www.flobotics.io/blog/page/12 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Page 12 Articles · page 12 of 21 # Everything about RCM automation From failed bots to million-dollar recoveries – stories, frameworks, and lessons from the field. AllAI 49Claims 3Denials 2Eligibility 10Healthcare 92RCM 78RPA 88Search articles [ RPA ### Exploring the Distinction Between Attended and Unattended Bots in RPA Attended vs. unattended bots: understand the key differences between these two RPA bot types and when to use each one. Jacek ŻukowskiOctober 07, 2024 ](https://www.flobotics.io/blog/attended-unattended-bots)[ RCMHealthcare ### Revenue Cycle Management (RCM) in Healthcare Revenue cycle management, explained: how US hospitals and practices stay compliant with payer policy and keep cash flow steady in 2026. Bart TeodorczukSeptember 30, 2024 ](https://www.flobotics.io/blog/revenue-cycle-management)[ Healthcare ### Laboratory Automation Solutions: Enhancing Efficiency and Compliance in Healthcare Laboratory automation solutions: streamline sample processing and test result interpretation to future-proof your lab operations. Bart TeodorczukSeptember 24, 2024 ](https://www.flobotics.io/blog/laboratory-automation-solutions)[ RPA ### How to Build an Effective Automation Department in Your Company [+ Infographic] Building an automation department: a factory-model guide to structuring your team, standardizing processes, and scaling governance. Jacek ŻukowskiSeptember 15, 2024 ](https://www.flobotics.io/blog/automation-department-infographic)[ RPA ### How Flobotics Built Its Company Values [Company Culture Case Study] Flobotics company culture case study: how our core values shape daily work and build a workplace people want to be part of. Gosia GomolaJuly 15, 2024 ](https://www.flobotics.io/blog/company-values-culture-case-study)[ RPA ### Document Understanding Tools Overview Document understanding tools compared: top platforms, use cases, and how they streamline document management workflows for teams. Krzysztof SzwedJuly 04, 2024 ](https://www.flobotics.io/blog/document-understanding-tools)[ RPA ### DocPlanner | A super scalable automation for multiple EHRs DocPlanner automation case study: see how this healthcare unicorn scaled across multiple EHRs without adding headcount. Jędrzej SzymulaJune 24, 2024 ](https://www.flobotics.io/blog/docplanner-automation)[ RPA ### 15 Use Cases of RPA in the Energy Sector RPA in energy and utilities: 15 use cases showing how automation boosts compliance, efficiency, and innovation across the sector. Yana PokoraJune 24, 2024 ](https://www.flobotics.io/blog/use-cases-rpa-in-energy)[ RPA ### More Than Just Reading Text: Why Your Document Understanding Sucks Document understanding challenges, explained: why most automations underperform, what's really failing beyond the OCR tool, and how to fix it. Karl MielnickiJune 05, 2024 ](https://www.flobotics.io/blog/why-document-understanding-sucks) No articles match. Clear filters [1](https://www.flobotics.io/blog)[2](https://www.flobotics.io/blog/page/2)[3](https://www.flobotics.io/blog/page/3)[4](https://www.flobotics.io/blog/page/4)[5](https://www.flobotics.io/blog/page/5)[6](https://www.flobotics.io/blog/page/6)[7](https://www.flobotics.io/blog/page/7)[8](https://www.flobotics.io/blog/page/8)[9](https://www.flobotics.io/blog/page/9)[10](https://www.flobotics.io/blog/page/10)[11](https://www.flobotics.io/blog/page/11)[12](https://www.flobotics.io/blog/page/12)[13](https://www.flobotics.io/blog/page/13)[14](https://www.flobotics.io/blog/page/14)[15](https://www.flobotics.io/blog/page/15)[16](https://www.flobotics.io/blog/page/16)[17](https://www.flobotics.io/blog/page/17)[18](https://www.flobotics.io/blog/page/18)[19](https://www.flobotics.io/blog/page/19)[20](https://www.flobotics.io/blog/page/20)[21](https://www.flobotics.io/blog/page/21) --- # Blog | Page 13 | Flobotics Canonical: https://www.flobotics.io/blog/page/13 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Page 13 Articles · page 13 of 21 # Everything about RCM automation From failed bots to million-dollar recoveries – stories, frameworks, and lessons from the field. AllAI 49Claims 3Denials 2Eligibility 10Healthcare 92RCM 78RPA 88Search articles [ RPA ### Specific Content Limitations in UiPath [RPA Developer’s Investigation] UiPath content limitations: Specific Content was removed from Get Queue Items in 2024 - see what fields disappeared and how to retrieve queue data now. Dominik PutMay 21, 2024 ](https://www.flobotics.io/blog/specific-content-limitations-in-uipath)[ RPAAI ### Building Your Automation Toolkit: 100 Automation Technologies and Platforms You Should Know RPA programming and automation technologies: explore our curated toolkit of 100 platforms, with pros, cons, and top use cases for 2026. Karl MielnickiMay 12, 2024 ](https://www.flobotics.io/blog/automation-technologies)[ RPAAI ### Pay on Time, Every Time: Streamlining Invoice Workflows with Invoice Automation Invoice automation, explained: how RPA, OCR, and IA streamline accounts payable and speed up every invoice workflow. Karl MielnickiApril 04, 2024 ](https://www.flobotics.io/blog/invoice-automation)[ RPA ### Automation’s for Everyone: 100 Real-World RPA Use Cases Across Industries | 2026 RPA use cases across industries: see 100 real-world examples of process automation in action, from healthcare to manufacturing. Michał RejmanFebruary 23, 2024 ](https://www.flobotics.io/blog/rpa-use-cases-across-industries)[ RPA ### Automated Document Processing: How to Do Away with Manual Paperwork? Automated document processing: how RPA turns insurance claims, loan statements, and patient forms into a paperwork-free workflow. Karl MielnickiFebruary 11, 2024 ](https://www.flobotics.io/blog/automated-document-processing)[ AIEligibility ### Generative AI in Finance and Banking: What’s All the Buzz and Why You Should Care Generative AI in finance and banking: explore practical use cases, from fraud detection to reporting, transforming the sector in 2026. Michał RejmanJanuary 30, 2024 ](https://www.flobotics.io/blog/generative-ai-finance)[ RPA ### Solutions Management Feature in UiPath - How Does It Work? [Dev's Perspective] UiPath Orchestrator features: how the new Solutions Management tool moves assets and triggers between orchestrators without manual errors. Dominik PutJanuary 24, 2024 ](https://www.flobotics.io/blog/uipath-orchestrator-new-features)[ RPA ### Small Effort, Big Impact: What Is RPA Testing, How to Do It & Why It Matters RPA testing, explained: why skipping it leads to costly post-launch fixes, and how to test your automation before it goes live. Bart TeodorczukJanuary 02, 2024 ](https://www.flobotics.io/blog/rpa-testing)[ RPA ### UiPath vs. Python? Choosing the Right RPA Tool for Your Automation Job UiPath vs. Python: compare strengths, use cases, and when to choose code over low-code for your next automation project. Krzysztof SzwedDecember 11, 2023 ](https://www.flobotics.io/blog/uipath-python) No articles match. Clear filters [1](https://www.flobotics.io/blog)[2](https://www.flobotics.io/blog/page/2)[3](https://www.flobotics.io/blog/page/3)[4](https://www.flobotics.io/blog/page/4)[5](https://www.flobotics.io/blog/page/5)[6](https://www.flobotics.io/blog/page/6)[7](https://www.flobotics.io/blog/page/7)[8](https://www.flobotics.io/blog/page/8)[9](https://www.flobotics.io/blog/page/9)[10](https://www.flobotics.io/blog/page/10)[11](https://www.flobotics.io/blog/page/11)[12](https://www.flobotics.io/blog/page/12)[13](https://www.flobotics.io/blog/page/13)[14](https://www.flobotics.io/blog/page/14)[15](https://www.flobotics.io/blog/page/15)[16](https://www.flobotics.io/blog/page/16)[17](https://www.flobotics.io/blog/page/17)[18](https://www.flobotics.io/blog/page/18)[19](https://www.flobotics.io/blog/page/19)[20](https://www.flobotics.io/blog/page/20)[21](https://www.flobotics.io/blog/page/21) --- # Blog | Page 14 | Flobotics Canonical: https://www.flobotics.io/blog/page/14 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Page 14 Articles · page 14 of 21 # Everything about RCM automation From failed bots to million-dollar recoveries – stories, frameworks, and lessons from the field. AllAI 49Claims 3Denials 2Eligibility 10Healthcare 92RCM 78RPA 88Search articles [ RPA ### Effective Naming Conventions in UiPath: A Comparative Analysis UiPath naming conventions: a practical guide to consistent naming and folder structure for Object Repository automation projects. Maciek MatuszczakDecember 03, 2023 ](https://www.flobotics.io/blog/naming-conventions-uipath)[ RPAAI ### Task Mining Tools Explained: Benefits, Use Cases and Leading Options Task mining tools introduced: an overview of UiPath, Celonis, and Kyp.ai to help you pick the right software for automation discovery. Bart TeodorczukNovember 20, 2023 ](https://www.flobotics.io/blog/task-mining-tools)[ RPAAI ### UiPath vs. Celonis vs. Kyp.ai: Comparing Top Task Mining Tools UiPath vs. Celonis vs. Kyp.ai: features and pricing compared to help you pick the right task mining tool for 2026. Bart TeodorczukNovember 20, 2023 ](https://www.flobotics.io/blog/uipath-vs-celonis-vs-kypai)[ RPA ### Streamlining Supply Chains: Transforming Warehousing and Transport with RPA Warehouse automation with RPA: how robotic process automation transforms warehousing and transport across modern supply chains. Yana PokoraOctober 17, 2023 ](https://www.flobotics.io/blog/warehouse-automation-process)[ Healthcare ### Healthcare Compliance Automation: Laws, Benefits and Examples Compliance automation software for healthcare: how RPA helps organizations meet evolving regulations without adding manual review work. Filip NasiadkoOctober 09, 2023 ](https://www.flobotics.io/blog/compliance-automation)[ RPAHealthcare ### Interoperability in Healthcare: What You Need to Know (And How to Get There with RPA) Healthcare interoperability, explained: how RPA connects clinics, insurers, and EHRs for faster, more reliable patient data flow. Michał RejmanOctober 03, 2023 ](https://www.flobotics.io/blog/interoperability-in-healthcare)[ RPA ### Canada Satellite | Hundreds of SIM cards & healthy CRM Canada Satellite automation case study - see how Flobotics streamlined hundreds of SIM cards into one clean, reliable CRM system. Bart TeodorczukSeptember 25, 2023 ](https://www.flobotics.io/blog/canada-satelite)[ RPA ### What's Workflow Automation? How It Works, How It Helps & What Software to Use Workflow automation, explained: how it works, what it helps with, and which software to use to cut manual tasks and boost efficiency in 2026. Filip NasiadkoSeptember 17, 2023 ](https://www.flobotics.io/blog/workflow-automation) No articles match. Clear filters [1](https://www.flobotics.io/blog)[2](https://www.flobotics.io/blog/page/2)[3](https://www.flobotics.io/blog/page/3)[4](https://www.flobotics.io/blog/page/4)[5](https://www.flobotics.io/blog/page/5)[6](https://www.flobotics.io/blog/page/6)[7](https://www.flobotics.io/blog/page/7)[8](https://www.flobotics.io/blog/page/8)[9](https://www.flobotics.io/blog/page/9)[10](https://www.flobotics.io/blog/page/10)[11](https://www.flobotics.io/blog/page/11)[12](https://www.flobotics.io/blog/page/12)[13](https://www.flobotics.io/blog/page/13)[14](https://www.flobotics.io/blog/page/14)[15](https://www.flobotics.io/blog/page/15)[16](https://www.flobotics.io/blog/page/16)[17](https://www.flobotics.io/blog/page/17)[18](https://www.flobotics.io/blog/page/18)[19](https://www.flobotics.io/blog/page/19)[20](https://www.flobotics.io/blog/page/20)[21](https://www.flobotics.io/blog/page/21) --- # Blog | Page 15 | Flobotics Canonical: https://www.flobotics.io/blog/page/15 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Page 15 Articles · page 15 of 21 # Everything about RCM automation From failed bots to million-dollar recoveries – stories, frameworks, and lessons from the field. AllAI 49Claims 3Denials 2Eligibility 10Healthcare 92RCM 78RPA 88Search articles [ RPA ### Top 10 RPA Implementation Challenges to Be Aware of Challenges of RPA implementation: the top 10 obstacles slowing projects down and proven strategies to keep your automation on track. Krzysztof SzwedAugust 22, 2023 ](https://www.flobotics.io/blog/rpa-challenges)[ RPA ### Unearthing RPA Potential: What You Need to Know About Task Mining & UiPath UiPath task mining, explained: see how its process-discovery tools help you find and prioritize the best tasks to automate. Bart TeodorczukJuly 28, 2023 ](https://www.flobotics.io/blog/task-mining-uipath)[ RPA ### Cohen | 2 FTEs saved via full invoice processing automation RPA in accounting case study: how Cohen automated invoice processing and saved 2 full-time employees’ worth of manual work. Jędrzej SzymulaJuly 25, 2023 ](https://www.flobotics.io/blog/rpa-in-accounting)[ RCMRPAHealthcare ### Medical Billing Management: Best Practices, Key Metrics and Automation Medical billing management: the 8-stage billing cycle, the metrics and reports that show revenue leakage, and 8 best practices to fix it. Yana PokoraJuly 25, 2023 ](https://www.flobotics.io/blog/medical-billing-management)[ RPAEligibility ### A Day Ahead, Not a Single Dollar Short: A Quick Guide to RPA in Payroll RPA in payroll: how automating manual payroll tasks boosts accuracy, speeds processing, and improves quality of life for HR and finance teams. Michał RejmanJuly 20, 2023 ](https://www.flobotics.io/blog/payroll-process-rpa)[ RPA ### SAP Automation Tools and You: Which One to Choose (And Why RPA Is Our Pick) SAP automation tools compared: strengths, weaknesses, and why RPA remains our top pick for optimizing SAP functions and workflows. Karl MielnickiJuly 11, 2023 ](https://www.flobotics.io/blog/sap-automation)[ RPA ### Your 6-Minute Guide to Process Automation with Python: Pros, Cons, Use Cases & Examples Python automation, explained: why the second most popular language on GitHub is a natural fit for RPA, plus pros, cons, and use cases. Krzysztof SzwedJuly 05, 2023 ](https://www.flobotics.io/blog/automation-python)[ RPA ### Robotic Process Automation vs. Machine Learning: Differences, Similarities, and Synergies RPA vs. machine learning: key differences, overlaps, and how combining both technologies can boost your automation strategy. Bart TeodorczukJune 21, 2023 ](https://www.flobotics.io/blog/robotic-process-automation-vs-machine-learning)[ RPA ### From Warehouse to Delivery: 12 Best RPA Use Cases in the Retail Industry RPA in retail: 12 use cases from warehouse to delivery that help retailers cut costs and improve the shopping experience. Michał RejmanJune 15, 2023 ](https://www.flobotics.io/blog/rpa-use-cases-retail) No articles match. Clear filters [1](https://www.flobotics.io/blog)[2](https://www.flobotics.io/blog/page/2)[3](https://www.flobotics.io/blog/page/3)[4](https://www.flobotics.io/blog/page/4)[5](https://www.flobotics.io/blog/page/5)[6](https://www.flobotics.io/blog/page/6)[7](https://www.flobotics.io/blog/page/7)[8](https://www.flobotics.io/blog/page/8)[9](https://www.flobotics.io/blog/page/9)[10](https://www.flobotics.io/blog/page/10)[11](https://www.flobotics.io/blog/page/11)[12](https://www.flobotics.io/blog/page/12)[13](https://www.flobotics.io/blog/page/13)[14](https://www.flobotics.io/blog/page/14)[15](https://www.flobotics.io/blog/page/15)[16](https://www.flobotics.io/blog/page/16)[17](https://www.flobotics.io/blog/page/17)[18](https://www.flobotics.io/blog/page/18)[19](https://www.flobotics.io/blog/page/19)[20](https://www.flobotics.io/blog/page/20)[21](https://www.flobotics.io/blog/page/21) --- # Blog | Page 16 | Flobotics Canonical: https://www.flobotics.io/blog/page/16 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Page 16 Articles · page 16 of 21 # Everything about RCM automation From failed bots to million-dollar recoveries – stories, frameworks, and lessons from the field. AllAI 49Claims 3Denials 2Eligibility 10Healthcare 92RCM 78RPA 88Search articles [ RPA ### UiPath vs. GCP (Google Cloud Platform): Which to Choose for Your Next Automation Project? UiPath vs. Google Cloud Platform: compare RPA capabilities, pricing, and scalability to pick the right automation tool for your 2026 project. Krzysztof SzwedMay 30, 2023 ](https://www.flobotics.io/blog/uipath-vs-gcp)[ RPAHealthcare ### ChatGPT for Healthcare: How Intelligent Chatbots Can Transform Medicine ChatGPT for healthcare: how intelligent chatbots support clinicians and patients, and where the technology's limits lie. Bart TeodorczukMay 15, 2023 ](https://www.flobotics.io/blog/chatgpt-for-healthcare)[ RPA ### The Complete Guide to Sales Process Automation: From Idea to Implementation Sales process automation, explained: a step-by-step guide to automating repetitive sales tasks and freeing reps to sell more. Filip NasiadkoMay 12, 2023 ](https://www.flobotics.io/blog/sales-process-automation)[ RPA ### Process Mining vs RPA: How They Work Together to Improve The Efficiency of Your Business Process mining and RPA: how combining the two turns automation candidates into measurable efficiency gains for your business. Bart TeodorczukJanuary 30, 2023 ](https://www.flobotics.io/blog/process-mining-automation)[ RPA ### What Is Smart Process Automation and How Can Your Business Benefit From It? Smart process automation vs. RPA: what sets it apart, which industries benefit most, and how it can take your automation strategy further. Bart TeodorczukDecember 21, 2022 ](https://www.flobotics.io/blog/smart-process-automation)[ RPA ### RPA in Manufacturing - What Operational Processes Should You Automate Today? RPA in manufacturing: which back-office processes to automate first, from supply chain to order processing and customer service, in 2026. Yana PokoraNovember 29, 2022 ](https://www.flobotics.io/blog/rpa-in-manufacturing)[ RPAEligibility ### Bots You Can Bank On | What’s RPA for Finance and What’s in It for You? Finance process automation: how RPA helps banks and financial firms cut manual work in heavily regulated, data-intensive workflows. Filip NasiadkoNovember 21, 2022 ](https://www.flobotics.io/blog/rpa-for-finance)[ RPA ### eCommerce Automation: How Is RPA Disrupting Online Retail? Ecommerce automation: how RPA helps online retailers tackle order processing, inventory, and customer service challenges at scale. Filip NasiadkoNovember 07, 2022 ](https://www.flobotics.io/blog/ecommerce-automation)[ RPA ### How RPA Is Changing the Logistics Industry and Supply Chain Management RPA in logistics: see which supply chain management processes to automate first and how companies streamline logistics operations with robots. Michał RejmanOctober 18, 2022 ](https://www.flobotics.io/blog/rpa-logistics-supply-chain-management) No articles match. Clear filters [1](https://www.flobotics.io/blog)[2](https://www.flobotics.io/blog/page/2)[3](https://www.flobotics.io/blog/page/3)[4](https://www.flobotics.io/blog/page/4)[5](https://www.flobotics.io/blog/page/5)[6](https://www.flobotics.io/blog/page/6)[7](https://www.flobotics.io/blog/page/7)[8](https://www.flobotics.io/blog/page/8)[9](https://www.flobotics.io/blog/page/9)[10](https://www.flobotics.io/blog/page/10)[11](https://www.flobotics.io/blog/page/11)[12](https://www.flobotics.io/blog/page/12)[13](https://www.flobotics.io/blog/page/13)[14](https://www.flobotics.io/blog/page/14)[15](https://www.flobotics.io/blog/page/15)[16](https://www.flobotics.io/blog/page/16)[17](https://www.flobotics.io/blog/page/17)[18](https://www.flobotics.io/blog/page/18)[19](https://www.flobotics.io/blog/page/19)[20](https://www.flobotics.io/blog/page/20)[21](https://www.flobotics.io/blog/page/21) --- # Blog | Page 17 | Flobotics Canonical: https://www.flobotics.io/blog/page/17 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Page 17 Articles · page 17 of 21 # Everything about RCM automation From failed bots to million-dollar recoveries – stories, frameworks, and lessons from the field. AllAI 49Claims 3Denials 2Eligibility 10Healthcare 92RCM 78RPA 88Search articles [ RPAAI ### Keep Bookkeeping Easy – Why Should You Consider Automating Your Accounting Processes? Accounting process automation: how RPA replaces manual bookkeeping tasks with faster, more accurate financial workflows. Filip NasiadkoOctober 14, 2022 ](https://www.flobotics.io/blog/automating-accounting-processes)[ RPA ### RPA in Real Estate and Property Management: Benefits, Applications, and Use Cases RPA in real estate and property management: explore real automation use cases and see how firms cut manual work across leasing and maintenance tasks. Michał RejmanSeptember 26, 2022 ](https://www.flobotics.io/blog/rpa-in-real-estate)[ RPA ### UiPath vs. Automation Anywhere: Choose Your Perfect RPA Tool UiPath vs. Automation Anywhere: compare features and capabilities to find the right RPA platform for your organization. Bart TeodorczukSeptember 07, 2022 ](https://www.flobotics.io/blog/uipath-vs-aa)[ RPA ### Blue Prism or UiPath? Choosing the Best RPA Tool for Your Business Blue Prism vs. UiPath: compare features, pricing, and support to choose the right RPA platform for your automation project. Bart TeodorczukAugust 22, 2022 ](https://www.flobotics.io/blog/blueprism-vs-uipath)[ RCMHealthcare ### How (and Why) Should You Build an Automated Medical Billing System? Automated medical billing system: a step-by-step guide to automating repetitive billing tasks and reducing errors in your healthcare practice. Karl MielnickiAugust 15, 2022 ](https://www.flobotics.io/blog/how-to-build-automated-medical-billing-system)[ RCMHealthcare ### [WEBINAR FOR MEDICAL BILLING] How to Process 6x More Patients Without Hiring a Single Person Medical billing webinar: watch how Robotic Process Automation lets practices process 6x more patients without adding headcount. August 11, 2022 ](https://www.flobotics.io/blog/webinar-medical-billing)[ RPA ### Mystic River Consulting | $100K saved in a few days Mystic River Consulting case study - how RPA automated a tax return process for a debt relief program, saving $100K in days. Jędrzej SzymulaAugust 01, 2022 ](https://www.flobotics.io/blog/mystique-river)[ Healthcare ### 5 Processes in the Healthcare Industry You Didn’t Know Could Be Automated Healthcare workflow automation: 5 everyday processes - from claims to billing - you can automate with RPA starting today. Michał RejmanAugust 01, 2022 ](https://www.flobotics.io/blog/healthcare-workflow-automation) No articles match. Clear filters [1](https://www.flobotics.io/blog)[2](https://www.flobotics.io/blog/page/2)[3](https://www.flobotics.io/blog/page/3)[4](https://www.flobotics.io/blog/page/4)[5](https://www.flobotics.io/blog/page/5)[6](https://www.flobotics.io/blog/page/6)[7](https://www.flobotics.io/blog/page/7)[8](https://www.flobotics.io/blog/page/8)[9](https://www.flobotics.io/blog/page/9)[10](https://www.flobotics.io/blog/page/10)[11](https://www.flobotics.io/blog/page/11)[12](https://www.flobotics.io/blog/page/12)[13](https://www.flobotics.io/blog/page/13)[14](https://www.flobotics.io/blog/page/14)[15](https://www.flobotics.io/blog/page/15)[16](https://www.flobotics.io/blog/page/16)[17](https://www.flobotics.io/blog/page/17)[18](https://www.flobotics.io/blog/page/18)[19](https://www.flobotics.io/blog/page/19)[20](https://www.flobotics.io/blog/page/20)[21](https://www.flobotics.io/blog/page/21) --- # Blog | Page 18 | Flobotics Canonical: https://www.flobotics.io/blog/page/18 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Page 18 Articles · page 18 of 21 # Everything about RCM automation From failed bots to million-dollar recoveries – stories, frameworks, and lessons from the field. AllAI 49Claims 3Denials 2Eligibility 10Healthcare 92RCM 78RPA 88Search articles [ RPA ### UiPath vs. Power Automate - Which RPA Tool To Choose? UiPath vs. Power Automate: compare features and pricing to decide which RPA tool best fits your 2026 process automation needs. Bart TeodorczukJune 27, 2022 ](https://www.flobotics.io/blog/uipath-vs-powerautomate)[ RCMHealthcare ### Revenue Cycle Management Automation in Healthcare – Everything You Need to Know What is revenue cycle management? A clear guide to RCM in healthcare and how automation streamlines it from patient intake to payment. Bart TeodorczukJune 08, 2022 ](https://www.flobotics.io/blog/what-is-revenue-cycle-management)[ RPA ### How to Find and Hire a Great RPA Consultant RPA consultant hiring guide: what to look for and how the right partner turns manual tasks into fast, reliable automated workflows. Karl MielnickiMay 19, 2022 ](https://www.flobotics.io/blog/how-to-find-and-hire-a-great-rpa-consultant)[ RCMHealthcare ### Medical Coding Automation: Why (and How) Should You Start? Medical coding services, automated: how RPA improves claims accuracy and cuts manual coding errors for healthcare providers. Karl MielnickiMay 13, 2022 ](https://www.flobotics.io/blog/medical-coding)[ Eligibility ### Payroll Process Improvement Ideas You Can Implement RPA in payroll: proven process-improvement ideas to cut manual work, reduce errors, and speed up your payroll cycle. Michał RejmanFebruary 07, 2022 ](https://www.flobotics.io/blog/rpa-payroll-process)[ RPA ### What Should the Model RPA Development and Implementation Process Look Like? RPA development lifecycle: what to expect from an automation implementation partner and the key steps in a successful RPA project. Radek MoczydlowskiJanuary 25, 2022 ](https://www.flobotics.io/blog/rpa-development-process)[ RPA ### How to Measure RPA Success: A Guide to Robotic Process Automation Metrics How to measure RPA success: the key business and technical metrics to track ROI and prove your automation program is profitable. Bart TeodorczukDecember 23, 2021 ](https://www.flobotics.io/blog/rpa-successs-metrics)[ RPA ### Which Processes Should You Automate to Maximize Your Business Efficiency? What processes should I automate? A guide to picking the right RPA candidates and building an implementation plan with the highest ROI. Krzysztof SzwedDecember 22, 2021 ](https://www.flobotics.io/blog/what-processes-to-automate)[ RPA ### What Does The "UiPath Certified Developer" Title Actually Mean? UiPath Certified Developer title, explained: what the certification actually proves - and what to check before you hire. Karl MielnickiNovember 26, 2021 ](https://www.flobotics.io/blog/uipath-certified-developer-title-meaning) No articles match. Clear filters [1](https://www.flobotics.io/blog)[2](https://www.flobotics.io/blog/page/2)[3](https://www.flobotics.io/blog/page/3)[4](https://www.flobotics.io/blog/page/4)[5](https://www.flobotics.io/blog/page/5)[6](https://www.flobotics.io/blog/page/6)[7](https://www.flobotics.io/blog/page/7)[8](https://www.flobotics.io/blog/page/8)[9](https://www.flobotics.io/blog/page/9)[10](https://www.flobotics.io/blog/page/10)[11](https://www.flobotics.io/blog/page/11)[12](https://www.flobotics.io/blog/page/12)[13](https://www.flobotics.io/blog/page/13)[14](https://www.flobotics.io/blog/page/14)[15](https://www.flobotics.io/blog/page/15)[16](https://www.flobotics.io/blog/page/16)[17](https://www.flobotics.io/blog/page/17)[18](https://www.flobotics.io/blog/page/18)[19](https://www.flobotics.io/blog/page/19)[20](https://www.flobotics.io/blog/page/20)[21](https://www.flobotics.io/blog/page/21) --- # Blog | Page 19 | Flobotics Canonical: https://www.flobotics.io/blog/page/19 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Page 19 Articles · page 19 of 21 # Everything about RCM automation From failed bots to million-dollar recoveries – stories, frameworks, and lessons from the field. AllAI 49Claims 3Denials 2Eligibility 10Healthcare 92RCM 78RPA 88Search articles [ Healthcare ### RPA in Clinical Trials: 5 Ways Robotic Process Automation Innovates Medical Research Robotic process automation in clinical trials: 5 ways RPA speeds up medical research while keeping data compliance fully intact. Michał RejmanOctober 08, 2021 ](https://www.flobotics.io/blog/automate-clinical-trials)[ HealthcareEligibilityClaims ### Implementing Automated Claims Processing in the Medical Industry Medical claims processing automation: see how RPA replaces costly manual workflows with automated claims for practices of every size. Karl MielnickiOctober 01, 2021 ](https://www.flobotics.io/blog/claims-processing-in-medical-industry)[ RPA ### 8 Best Security Practices for RPA Implementation RPA security best practices: 8 steps to manage the security risks of your organization's automation implementation. Krzysztof SzwedSeptember 20, 2021 ](https://www.flobotics.io/blog/8-security-practices-for-rpa-implementation)[ Healthcare ### Building Automated HIPAA Compliance Workflows with RPA: What Do You Need to Know? HIPAA-compliant automation: how to build RPA workflows that keep healthcare data secure and satisfy HIPAA requirements fully. Michał RejmanAugust 23, 2021 ](https://www.flobotics.io/blog/hipaa-compliance-rpa)[ RPAEligibility ### Top RPA Use Cases in the Insurance Industry RPA use cases in insurance: see how robotic process automation streamlines claims, underwriting, and other core workflows. Yana PokoraAugust 10, 2021 ](https://www.flobotics.io/blog/rpa-in-insurance-use-cases)[ RCMHealthcare ### How to Improve Electronic Health Records Processing with Automation EHR automation with RPA: fix electronic health record imperfections without a system overhaul - pros, cons, and real use cases. Bart TeodorczukAugust 09, 2021 ](https://www.flobotics.io/blog/electronic-health-records-rpa)[ EligibilityClaims ### Insurance Claims Processing Automation With RPA: Reasons for Implementation and Use Cases Insurance claims processing automation: how RPA speeds up claims handling, with reasons to implement it and real case studies. Michał RejmanJuly 21, 2021 ](https://www.flobotics.io/blog/insurance-claims-processing-rpa-automation-use-cases)[ RPA ### RPA Failures: 10 Most Common Reasons and How to Avoid Them RPA failures: Flobotics' CTO breaks down the 10 most common reasons automation projects fail and how to avoid them. Karl MielnickiJuly 06, 2021 ](https://www.flobotics.io/blog/rpa-failures) No articles match. Clear filters [1](https://www.flobotics.io/blog)[2](https://www.flobotics.io/blog/page/2)[3](https://www.flobotics.io/blog/page/3)[4](https://www.flobotics.io/blog/page/4)[5](https://www.flobotics.io/blog/page/5)[6](https://www.flobotics.io/blog/page/6)[7](https://www.flobotics.io/blog/page/7)[8](https://www.flobotics.io/blog/page/8)[9](https://www.flobotics.io/blog/page/9)[10](https://www.flobotics.io/blog/page/10)[11](https://www.flobotics.io/blog/page/11)[12](https://www.flobotics.io/blog/page/12)[13](https://www.flobotics.io/blog/page/13)[14](https://www.flobotics.io/blog/page/14)[15](https://www.flobotics.io/blog/page/15)[16](https://www.flobotics.io/blog/page/16)[17](https://www.flobotics.io/blog/page/17)[18](https://www.flobotics.io/blog/page/18)[19](https://www.flobotics.io/blog/page/19)[20](https://www.flobotics.io/blog/page/20)[21](https://www.flobotics.io/blog/page/21) --- # Blog | Page 20 | Flobotics Canonical: https://www.flobotics.io/blog/page/20 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Page 20 Articles · page 20 of 21 # Everything about RCM automation From failed bots to million-dollar recoveries – stories, frameworks, and lessons from the field. AllAI 49Claims 3Denials 2Eligibility 10Healthcare 92RCM 78RPA 88Search articles [ RPA ### Why Your Non-Technical RPA Developer Sucks RPA for non-technical developers: why coding skills still matter and where non-technical RPA developers fall short. Karl MielnickiJune 15, 2021 ](https://www.flobotics.io/blog/rpa-non-technical-developer)[ RPA ### 5 Ways RPA Can Take Your Customer Experience To A New Level [With Examples!] RPA and customer experience: 5 practical ways robotic process automation speeds up service and improves every interaction. Michał RejmanJune 07, 2021 ](https://www.flobotics.io/blog/rpa-customerexperience)[ RPA ### BPM vs. RPA: The Difference and What It Means for Your Business RPA and BPM integration: the key differences between the two, and how combining them strengthens your automation strategy. Filip NasiadkoMay 19, 2021 ](https://www.flobotics.io/blog/bpm-vs-rpa-the-difference-and-what-it-means-for-your-business)[ RPA ### RPA in Supply Chain Management: Pros, Cons and The Best Use Examples RPA supply chain use cases: pros, cons, and real examples of how automation cuts costs across the logistics industry. Michał RejmanMay 07, 2021 ](https://www.flobotics.io/blog/rpa-in-supply-chain-management-use-examples)[ RPA ### How Is Robotic Process Automation Changing HR and Recruitment? RPA in HR and recruitment: how automation takes over routine tasks so HR managers can focus on strategic, people-first work. Michał RejmanJanuary 20, 2021 ](https://www.flobotics.io/blog/rpa-in-hr-and-recruitment)[ Eligibility ### How Is Robotic Process Automation Disrupting the Banking and Finance Industry? RPA in banking and finance: top reasons automation and financial institutions work well together, with real use cases inside. Filip NasiadkoJanuary 15, 2021 ](https://www.flobotics.io/blog/rpa-in-finance-and-banking)[ ### XiFin vs. TELCOR vs. Quadax XiFin vs. TELCOR vs. Quadax: features, pricing, and which lab billing platform fits your diagnostics RCM needs in 2026. September 06, 2026 ](https://www.flobotics.io/blog/xifin-vs-telcor-vs-quadax)[ RPA ### T Bank T-Bank case study - how one RPA bot cut SBA loan processing from 15 minutes to 6 seconds, delivering $5M in savings and 300,000% ROI. Michał RejmanSeptember 06, 2026 ](https://www.flobotics.io/blog/t-bank)[ RPA ### Evidence-Based Treatment Centers of Seattle (EBTCS) EBTCS case study - see how automated Salesforce-to-Valant EHR data transfer cut per-case handling time 20x for this Seattle mental health network. Michał RejmanSeptember 06, 2026 ](https://www.flobotics.io/blog/evidence-based-treatment-centers-of-seattle-ebtcs) No articles match. Clear filters [1](https://www.flobotics.io/blog)[2](https://www.flobotics.io/blog/page/2)[3](https://www.flobotics.io/blog/page/3)[4](https://www.flobotics.io/blog/page/4)[5](https://www.flobotics.io/blog/page/5)[6](https://www.flobotics.io/blog/page/6)[7](https://www.flobotics.io/blog/page/7)[8](https://www.flobotics.io/blog/page/8)[9](https://www.flobotics.io/blog/page/9)[10](https://www.flobotics.io/blog/page/10)[11](https://www.flobotics.io/blog/page/11)[12](https://www.flobotics.io/blog/page/12)[13](https://www.flobotics.io/blog/page/13)[14](https://www.flobotics.io/blog/page/14)[15](https://www.flobotics.io/blog/page/15)[16](https://www.flobotics.io/blog/page/16)[17](https://www.flobotics.io/blog/page/17)[18](https://www.flobotics.io/blog/page/18)[19](https://www.flobotics.io/blog/page/19)[20](https://www.flobotics.io/blog/page/20)[21](https://www.flobotics.io/blog/page/21) --- # Blog | Page 21 | Flobotics Canonical: https://www.flobotics.io/blog/page/21 --- [Home](https://www.flobotics.io/)/[Articles](https://www.flobotics.io/blog)/Page 21 Articles · page 21 of 21 # Everything about RCM automation From failed bots to million-dollar recoveries – stories, frameworks, and lessons from the field. AllAI 49Claims 3Denials 2Eligibility 10Healthcare 92RCM 78RPA 88Search articles [ RPA ### North Pole Inc. North Pole Inc. automation case study - how OCR, ML routing, and RPA helped Santa's operations process 2.2 billion actions and cut packing time 78%. Michał RejmanSeptember 06, 2026 ](https://www.flobotics.io/blog/north-pole-inc)[ AIRCMHealthcare ### FHIR The question isn't whether FHIR in RCM matters. The question is: what's your number? What does prior authorization cycle time cost your organization per service line, per denied claim, per day your capital sits locked in accounts receivable? Krzysztof SzwedAugust 31, 2026 ](https://www.flobotics.io/blog/fhir) No articles match. Clear filters [1](https://www.flobotics.io/blog)[2](https://www.flobotics.io/blog/page/2)[3](https://www.flobotics.io/blog/page/3)[4](https://www.flobotics.io/blog/page/4)[5](https://www.flobotics.io/blog/page/5)[6](https://www.flobotics.io/blog/page/6)[7](https://www.flobotics.io/blog/page/7)[8](https://www.flobotics.io/blog/page/8)[9](https://www.flobotics.io/blog/page/9)[10](https://www.flobotics.io/blog/page/10)[11](https://www.flobotics.io/blog/page/11)[12](https://www.flobotics.io/blog/page/12)[13](https://www.flobotics.io/blog/page/13)[14](https://www.flobotics.io/blog/page/14)[15](https://www.flobotics.io/blog/page/15)[16](https://www.flobotics.io/blog/page/16)[17](https://www.flobotics.io/blog/page/17)[18](https://www.flobotics.io/blog/page/18)[19](https://www.flobotics.io/blog/page/19)[20](https://www.flobotics.io/blog/page/20)[21](https://www.flobotics.io/blog/page/21) --- # Up to 80% Higher Throughput in RCM – Denials Management Automation Canonical: https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation Published: 2026-01-28 Updated: 2026-04-08 --- [Home](https://www.flobotics.io/)/[Client Results](https://www.flobotics.io/case-studies)/Up to 80% Higher Throughput in RCM – Denials Management… Denials Management # Up to 80% Higher Throughput in RCM – Denials Management Automation See how we automated PathGroup’s systems and connected it with a custom laboratory information system data exchange. Up to 80%Higher throughput in RCM. See how we automated PathGroup’s systems and connected it with a custom laboratory information system data exchange. ClientPathGroup WorkflowDenials Management Headline resultUp to 80% On this page - [About PathGroup](#about-pathgroup) - [Main Challenge | Denials Management](#main-challenge-denials-management) - [Solutions | AI Automation to the Rescue!](#solutions-ai-automation-to-the-rescue) - [Denials Hunter & CPT Code Fixer](#denials-hunter-cpt-code-fixer) - [Impact](#impact) - [Summary](#summary) Book a callWant results like these? 30 minutes with someone who builds automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book) Share [](#)[](#) ## About PathGroup PathGroup is one of the largest physician–led pathology and laboratory service providers in the U.S. They serve more than 95 hospitals and thousands of physician groups nationwide and process thousands of claims a day. In the past, their RCM team was manually operating on two hard to integrate systems: - athenahealth (previously IDX) – a major legacy billing and patient management platform for patient charges handling, claim generation, and payer reporting. - PathSys Laboratory Information System – private proprietary legacy EHR software, built in – house to manage diagnostic data, lab results, and test coding at scale. The lack of integration between the two systems created a growing denials backlog, which soon became a serious operational bottleneck. ## Main Challenge | Denials Management Before automation, processing a denied claim typically required 10–15 minutes of manual work. Manual cross–checks, data correction, claim resubmission… At scale, this volume made it impossible for the team to keep up. At the top of that, constant rework generating costs, delayed time to reimbursements, and prolonged Account Receivables (AR). Hiring more staff would only inflate Cost–To–Collect (CTC) instead of solving throughput. In short: Automation was inevitable. ## Solutions | AI Automation to the Rescue! After breaking down their revenue cycle piece by piece, we knew that PathGroups situation required: - Improved operational capacity, - Cost To Collect (CTC) optimization, - Precise end– to– end denial handling. That’s why we’ve started by creating an AI digital bridge between athenahealth and PathSys LIS. We designed the solution to handle both: - structured processes – such as athenahealth billing workflows and lab order synchronization, - unstructured data exchanges – between the PathSys LIS and the billing environment. We also built our automation in a HIPAA–compliant environment, with encrypted PHI transfer and full audit traceability across both systems. Here’s what we provided: ### Denials Hunter & CPT Code Fixer As a second step, we’ve decided to implement a Denial Hunter – an automation that takes over the repetitive and error – prone parts of denials management. We aimed to find and classify denial types, pull missing or corrected data, fix claims, and resubmit them to payer portals automatically. In PathGroup's case, 90% of denials are due to minor mistakes, such as eligibility, coverage or incorrect coding issues. Out of these 90%, a limited number of error types are very repetitive and easy to fix. We designed the solution to handle both structured billing workflows and unstructured data exchanges between systems. Only sophisticated or unique cases were allowed to end up in human hands. We ensured the automation could ingest and process new denial records continuously, 24/7. At the end of the entire process, a summary report is generated showing the ratio of successfully processed cases to all cases handled, which serves as a basic accuracy metric. How Denial Handling Automation Works? Fig. 01 · Denials UHC resubmitter Automated denials management and UHC resubmission - 01Identifies the denial response - 02Classifies and matches the error type - 03Retrieves missing or corrected data - 04Fixes and resubmits denials - 05Sends the rest to a person for review ## Impact The implementation of Denial Hunter unlocked PathGroup’s RCM operations. Within weeks, the team moved from double-checking spreadsheets to unattended, 24/7 data verification between billing and laboratory systems. Supported by additional features such as CPT Code Fixer, Laboratory Tests Management Automation, and Patient Registration Automation, our automation reduced the backlog in the targeted denial queues to near-zero levels. Now, with Denial Hunter and its companion automations running in the background, up to 300 claims per day are automatically verified, corrected, and successfully resubmitted. But most importantly, PathGroup’s RCM team can finally stay focused on strategic improvements and complex cases that actually require human judgment. Here are the results: - About 0.5 FTE of staff capacity saved on an ongoing basis, roughly 6 FTE-months of work a year. - 200 per day -> 2 per day Initial CPT error rate (roughly), - Seamless data consistency between PathSys LIS and athenahealth, - Continuous scalability without additional headcount. - Claim processing speed: 10 min → 55 sec per case That’s the power of smart, modular automation – tailored to PathGroup’s architecture, built to grow with their business. ### Summary PathGroup’s journey shows that RCM doesn’t have to be automated all at once. Smart process automation, even if applied step by step, brings almost instant ROI. Which brings us to the following point: We combine proven, ready–to–deploy automations with custom builds – always fitting seamlessly into each client’s existing architecture. Metric | Result | Claim Processing Speed | 10 min → 55 sec per case | Staff Capacity Saved | ~0.5 FTE (about 6 FTE-months a year) | Reworking denied claims by hand too? 30 minutes with Karl, our CTO, or Bart, our Head of AI. Within the first 15, we’ll know if automation works for you. [Book a 30-minute call →](https://www.flobotics.io/book) More work ## More case studies Real deployments, with the numbers our clients measured. [ Eligibility Checks 100%ROI in 23 days from eligibility automation plus Denial Hunter, with $180,000 in savings after year one. ### 100% ROI in just 23 days. We Automated Eligibility Checks! Read the case study → ](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) [All case studies →](https://www.flobotics.io/case-studies) --- # What We Do: AI, RPA & UiPath Automation | Flobotics Canonical: https://www.flobotics.io/what-we-do --- [Home](https://www.flobotics.io/)/What we do What we do # AI agents, RPA and UiPath, implemented and run inside your systems. Advice is the easy part. We implement automation inside the systems you already use, then operate and improve it with your team, from the first workflow to a Center of Excellence. [Book a 30-minute call →](https://www.flobotics.io/book)[How we price](https://www.flobotics.io/pricing) 1,000+ automations delivered 10+ industries automated Official UiPath partner Five things we do [01AI & AutomationAI agents, RPA bots and workflow automation.→](https://www.flobotics.io/ai-automation) [02Data & IntegrationsConnect systems and move data without retyping.→](https://www.flobotics.io/data-integrations) [03Dedicated TeamsDevelopers, analysts and support inside your team.→](https://www.flobotics.io/dedicated-teams) [04Maintenance & SupportWe monitor, fix and take over automations.→](https://www.flobotics.io/maintenance-support) [05UiPath ServicesCertified developers and license advice.→](https://www.flobotics.io/uipath-services) Healthcare revenue cycle ## Our healthcare examples Each of these pages shows how we automate one revenue cycle workflow around your systems and your payer rules. [AI agent→ ### Eligibility Check Plan type, effective and term dates, PCP assignment, copay, deductible and COB, checked end to end. 80%automated by the agent ](https://www.flobotics.io/agents/eligibility-check-automation) [AI agent→ ### Prior Authorization Gathers documentation, fills the forms, selects CPT/HCPCS codes and submits through payer portals. 60% fasterpre-auth turnaround ](https://www.flobotics.io/agents/prior-authorization-automation) [AI agent→ ### Claims Management Clearinghouse reconciliation, payer responses and adjudications, with stuck claims flagged and followed up. 99%payment tracking accuracy ](https://www.flobotics.io/agents/claims-management-automation) [AI agent→ ### Denials Management Analyzes each EOB, finds the CARC/RARC root cause and builds the appeal packet for resubmission. 4x fasterre-submission turnaround ](https://www.flobotics.io/agents/denials-management-automation) Outside healthcare, we automate back-office work in manufacturing, energy, finance, tax, travel and telecom. [Custom RCM automation →](https://www.flobotics.io/rcm-automation) [Business process automation →](https://www.flobotics.io/business-process-automation) How we work ## From a call to an automation your team relies on - ### A 30-minute call You tell us what your team does by hand. Within 15 minutes, you’ll know whether automation makes sense. - ### A walkthrough You show us the process. We work out the effort, the savings and the ROI. If it isn’t worth automating, we tell you. - ### We build it Around your systems and your rules, and tested on real cases before it goes live. - ### We keep it running We monitor, fix and improve it. Cases that need a person go to your team. Pricing, in the open$15,000 – $25,000 Most projects fall in this range. If ChatGPT or Claude can do the job on its own, we’ll tell you in the first 15 minutes of the call and show you how, for free. [How we price →](https://www.flobotics.io/pricing)[Estimate your ROI](https://www.flobotics.io/roi-calculator) Client work ## Projects we’ve written up [Docplanner ### 10+ EHRs connected to a booking app in four countries UiPath recommended us. We rebuilt the integration so it could grow to new EHRs, clinics and countries. →](https://www.flobotics.io/case-studies/docplanner) [Global View ### Account activations in 1 second instead of about 10 minutes Built by one UiPath developer in under three weeks. →](https://www.flobotics.io/case-studies/global-view-automation) [Sugar producer ### 4,685 hours of manual work saved a year in SAP The client came to us from another RPA vendor. It became one of our longest partnerships. →](https://www.flobotics.io/case-studies/sugar-producer-automation) [PRMG ### Loan processing automation for a U.S. mortgage lender Six core steps of PRMG’s loan processing, automated with UiPath. →](https://www.flobotics.io/blog/flobotics-prmg-loan-processing-rpa-automation) Articles from our developers [UiPath Licensing Simplified: How BPO Makes Automation More AffordableKarl Mielnicki · May 16, 2025→](https://www.flobotics.io/blog/business-process-outsourcing) [What Does The “UiPath Certified Developer” Title Actually Mean?Karl Mielnicki · November 26, 2021→](https://www.flobotics.io/blog/uipath-certified-developer-title-meaning) [UiPath’s Agentic AI: Orchestrating Autonomous Agents in Enterprise AutomationBart Teodorczuk · May 15, 2026→](https://www.flobotics.io/blog/uipaths-agentic-ai-orchestration) [Solutions Management Feature in UiPath: How Does It Work?Dominik Put · January 24, 2024→](https://www.flobotics.io/blog/uipath-orchestrator-new-features) [What You Need to Know About Task Mining & UiPathBart Teodorczuk · July 28, 2023→](https://www.flobotics.io/blog/task-mining-uipath) [UiPath vs. Power Automate: Which RPA Tool To Choose?Bart Teodorczuk · June 27, 2022→](https://www.flobotics.io/blog/uipath-vs-powerautomate) [What Should the Model RPA Development and Implementation Process Look Like?Radek Moczydlowski · January 25, 2022→](https://www.flobotics.io/blog/rpa-development-process) [What Is RPA Testing, How to Do It & Why It MattersBart Teodorczuk · January 2, 2024→](https://www.flobotics.io/blog/rpa-testing) [The Distinction Between Attended and Unattended Bots in RPAJacek Żukowski · October 7, 2024→](https://www.flobotics.io/blog/attended-unattended-bots) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Who We Help: Labs, Providers, RCM Teams & Payers | Flobotics Canonical: https://www.flobotics.io/who-we-help --- [Home](https://www.flobotics.io/)/Who we help Who we help # We automate the manual work of labs, practices, billing companies, health tech and payers. Each of them has its own repetitive work: requisitions, eligibility checks, prior authorizations, claims, denials and correspondence. We know it step by step. We automate in other industries too. [Book a 30-minute call →](https://www.flobotics.io/book)[See all our work](https://www.flobotics.io/case-studies) ## Choose your organization [01 ## Diagnostic & pathology laboratories Accessioning, prior authorization, missing records and denials across the LIS, XiFin and payer portals. See how we help →](https://www.flobotics.io/who-we-help/laboratories) [02 ## Specialty practices & provider networks Intake, eligibility, prior authorization and claims. See how we help →](https://www.flobotics.io/who-we-help/providers) [03 ## RCM & medical billing companies Claim prep, claims tracking, denials and eligibility. See how we help →](https://www.flobotics.io/who-we-help/rcm-billing-companies) [04 ## Healthcare technology companies The manual work around your platform: data transfer, documents and denials. See how we help →](https://www.flobotics.io/who-we-help/healthcare-technology) [05 ## Payers & health plans Administrative work only. Clinical decisions stay with people. See how we help →](https://www.flobotics.io/who-we-help/payers) [06 ## Other industries Manufacturing, energy, finance, tax, travel and telecom. See our work outside healthcare →](https://www.flobotics.io/business-process-automation) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Laboratory Revenue Cycle Management Automation | Flobotics Canonical: https://www.flobotics.io/who-we-help/laboratories --- [Home](https://www.flobotics.io/)/[Who we help](https://www.flobotics.io/who-we-help)/Laboratories Diagnostic & pathology laboratories # Your lab systems do the heavy lifting. We automate the work between them. Prior authorizations, missing medical records, reconsiderations and denied claims. We automate the manual work [connecting your LIS, XiFin, and payer portals](https://www.flobotics.io/data-integrations). [Book a 30-minute call →](https://www.flobotics.io/book)[What we’ve built in XiFin](#xifin) XIFIN · IN PRODUCTION 61automations involving XiFin 16workflows with UnitedHealthcare What they do - Medical record uploads - Missing-document requests - Reconsiderations - Appeals - Payer status checks - Updates back to XiFin Proven in XiFin ## We know XiFin. We’ve built 61 automations around it. 61 automations involving XiFin are running in production, including 16 workflows with UnitedHealthcare. We don’t change XiFin or replace it. The [automations do the work around it](https://www.flobotics.io/xifin-in-rcm), in payer portals, Availity, email and scanned mail, and write every result back to XiFin. Some payers have an API and some only have a portal. We use whichever works for each payer. [See what we’ve automated →](https://www.flobotics.io/case-studies) EXAMPLE · UNITEDHEALTHCARE RECONSIDERATIONS What the automation does, every day - Pulls the denied accessions from XiFin. - Downloads the related medical records. - Matches each record to the right UnitedHealthcare claim. - Uploads the documents and submits the reconsideration. - Updates the claim status in XiFin and sends the team a summary. ~50denials handled a day 30 sper case, down from 6 minutes ## Laboratory revenue cycle management workflows 01 ### Pre-accession workflows Orders and authorization requests often arrive before an accession exists in XiFin. We can capture the information when it arrives, start the work early, and connect it to the accession once it’s created. 02 ### Document intake & matching We digitize incoming mail and faxes, read them, match each document to the right accession and post it in XiFin. Documents that don’t clearly match go to your team. 03 ### Missing records & UHC appeals Our automations retrieve supporting medical records, upload missing documentation to UnitedHealthcare, submit reconsiderations and update XiFin. 04 ### Prior authorization & denials We gather clinical documentation, [prepare authorization packets](https://www.flobotics.io/agents/prior-authorization-automation), submit requests, follow up with payers, and [process routine denial corrections](https://www.flobotics.io/agents/denials-management-automation). 05 ### Account cleanup in XiFin We automate routine XiFin housekeeping: overrides, incorrect balances, adjustments, write-offs and refunds. See how [claims processing automation](https://www.flobotics.io/agents/claims-management-automation) handles claim preparation, submission and payer follow-up. [Explore revenue cycle management automation →](https://www.flobotics.io/rcm-automation) ## Proven in production [ Client caseDenials Management 80%of a 3,000-claim backlog cleared in three weeks. ### XiFin and UnitedHealthcare reconsideration automation Read the case study → ](https://www.flobotics.io/case-studies/50k-saved-in-1-month-ai-agent-for-denials-management) [ Denials Management 10 min → 55 secper denied claim. ### PathGroup denial processing automation Read the case study → ](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation) [ Client casePre-Auths 8–12 min → under 1 minper prior authorization packet. ### Prior authorization for a genetic testing lab Read the case study → ](https://www.flobotics.io/case-studies/90-faster-packet-submissions-prior-authorization-automation) [Explore our laboratory case studies →](https://www.flobotics.io/case-studies) Talk to us ## Show us where your lab gets stuck. Accessions waiting on authorization, payers waiting for records, denials piling up in a queue. Show us the work, and we’ll tell you what can be automated and whether it pays off. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Automation for Specialty Practices & Provider Networks | Flobotics Canonical: https://www.flobotics.io/who-we-help/providers --- [Home](https://www.flobotics.io/)/[Who we help](https://www.flobotics.io/who-we-help)/Providers Specialty practices & provider networks # Grow your practice without growing the back office. We automate eligibility checks, prior authorizations, claims and the follow-up, in your EHR and in the payer portals your staff uses today. Cases that need a person go to your team. [Book a 30-minute call →](https://www.flobotics.io/book)[See client results](#proven) PTCOA · ELIGIBILITY CHECKS · IN PRODUCTION 8,000+eligibility checks a month ~40 sper check, down from 5–7 minutes How it works - Starts when an appointment is booked. - Checks coverage in the payer portal. - Saves the result in PrognoCIS, the EHR. - Sends the billing data to TriZetto. - Inactive coverage and missing IDs go to staff. ## What we automate for providers 01 ### Registration and intake We check patient details and intake forms before the visit and enter them into your EHR. Missing or mismatched details go to your front desk. 02 ### Eligibility and benefits Plan, effective and term dates, PCP, copay, deductible, coinsurance and coordination of benefits, checked in payer portals and saved to the patient record. 03 ### Prior authorization We collect the order and clinical documents, fill in and submit the request, and check its status until the payer answers. The payer still makes the decision. 04 ### Claims and follow-up We prepare and submit claims, check their status, and flag the ones that are stuck or denied. 05 ### Payment posting We post remittances to the right patient, claim and service line, and flag duplicates and mismatches. Home medical equipment ## DME and HME companies: 46 automations in Brightree. Home medical equipment companies handle orders, CMNs, resupply, deliveries and equipment returns, on top of billing. We have 46 automations involving Brightree in production. They cover documents, orders, billing and the warehouse. BRIGHTREE · IN PRODUCTION 46automations involving Brightree Where they run - Orders and clinical work: 16 - Warehouse, shipping and assets: 13 - Documents and CMNs: 9 - Billing, claims and payments: 6 - Device platforms: 2 Systems we work in PrognoCISTriZettoathenahealthBrightreeAvailityPayer portals [Eligibility check agent →](https://www.flobotics.io/agents/eligibility-check-automation) [Prior authorization agent →](https://www.flobotics.io/agents/prior-authorization-automation) Further reading [RCM Automation for FQHCsCEO Notes · Filip Nasiadko · August 14, 2026→](https://www.flobotics.io/blog/rcm-automation-for-fqhcs) [Why Community Hospitals Need More Than an API? Meditech ExampleCEO Notes · Filip Nasiadko · July 23, 2026→](https://www.flobotics.io/blog/why-community-hospitals-need-more-than-an-api) [How Agentic AI Automates Payer Portals Without an APIJędrzej Szymula · July 27, 2026→](https://www.flobotics.io/blog/agentic-ai-payer-portals-without-api) ## Proven in production [ Eligibility Checks 100%ROI in 23 days from eligibility automation plus Denial Hunter, with $180,000 in savings after year one. ### Eligibility checks for a 13-clinic pain management network Read the case study → ](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) [ Pre-Auths 85%faster prior authorization submissions, from 10–15 minutes to 1–2 minutes each, with 8+ FTEs of work freed. ### Prior authorization across payer portals Read the case study → ](https://www.flobotics.io/case-studies/85-faster-submissions-8-ftes-saved-prior-authorization-automation) [ Client casePre-Auths 85%faster prior authorization packet submission for a cancer treatment clinic. ### Pre-auth automation project for a cancer treatment clinic See it on our pricing page → ](https://www.flobotics.io/pricing) Talk to us ## Show us the work your staff does by hand. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Automation for RCM & Medical Billing Companies | Flobotics Canonical: https://www.flobotics.io/who-we-help/rcm-billing-companies --- [Home](https://www.flobotics.io/)/[Who we help](https://www.flobotics.io/who-we-help)/RCM & billing companies RCM & medical billing companies # Take on more clients without hiring more billers. Every new client brings another EHR, more payers and more rules. We automate the repeatable billing work across all of them, from EHR data to the clearinghouse and back. Your billers handle the exceptions. [Book a 30-minute call →](https://www.flobotics.io/book)[See client results](#proven) GENTEM HEALTH · CLAIM PREP · IN PRODUCTION 98%less manual claim prep ~95%clean claim rate, up from ~80% How it works - Every day, pulls patient, provider, appointment, service and payment data from each practice’s EHR. - Writes it into Gentem’s billing database. - Claims are prepared from that data, without retyping. ## What we automate for billing teams 01 ### Claim prep from EHR data We pull patient, provider, appointment and service data from each client’s EHR into your billing platform every day, so nobody retypes it. 02 ### Documents to claims We read superbills, PDFs and scanned forms and turn them into claim-ready records. Documents with missing fields go to your team. 03 ### Eligibility We check coverage, copays and deductibles in payer portals and Availity, and write the results back to the patient record. 04 ### Claim status and AR We check clearinghouse and payer status, find the claims that are stuck or unworked, and put them in the right queue. 05 ### Denials We read the EOB, find the CARC/RARC reason, fix the errors we can fix and prepare the resubmission or appeal. The rest goes to your team. 06 ### Payment posting We post 835 remittances to the right claim and service line, and flag duplicates and mismatches. Client after client ## Your next client on the same EHR costs less to automate. Much of the work repeats from client to client: logging in, finding the patient, reading the payer’s answer, writing it back. We build those parts once and reuse them. A new EHR or a new payer still needs its own work, and we’ll tell you how much before we start. We don’t replace your billing platform, and we don’t become your billing vendor. We work in the tools you already use. They were easy to get in contact with and the whole collaboration went smoothly. The automation has saved us a considerable amount of time. Everyone in the team confirmed it works fantastically and that it’s freed them up a lot of time. Manny AkintayoCo-founder & CTO at Gentem Health Related [Claims management agent →](https://www.flobotics.io/agents/claims-management-automation) [Denials management agent →](https://www.flobotics.io/agents/denials-management-automation) [The state of claim denials →](https://www.flobotics.io/blog/claim-denials-in-healthcare-usa) ## Proven in production [ Claims Management 98%less manual claim prep. Up to 250 hours a week of manual work removed. ### EHR-to-claim data pipeline for Gentem Health Read the case study → ](https://www.flobotics.io/case-studies/98-reduction-in-manual-claim-prep-claims-management-automation) [ Client caseClaims Management ~24 h → ~7 hfrom uploaded document to claim-ready record, about 70% faster. ### Superbills turned into claims for SuperBill Read the case study → ](https://www.flobotics.io/case-studies/70-faster-claim-turnaround-time-ctt-claim-management-automation) [ Client caseEligibility Checks 5 min → ~1 minper eligibility check, with the monthly backlog cut in half. ### Eligibility checks for a U.S. health-tech company Read the case study → ](https://www.flobotics.io/case-studies/halving-monthly-backlog---eligibility-automation-in-action) Talk to us ## Show us the billing work your team does by hand. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Automation for Healthcare Technology Companies | Flobotics Canonical: https://www.flobotics.io/who-we-help/healthcare-technology --- [Home](https://www.flobotics.io/)/[Who we help](https://www.flobotics.io/who-we-help)/Healthcare technology Healthcare technology companies # We automate the manual work your software doesn’t reach. Your product does its job. But every new customer brings a different EHR, payer portals, faxes and spreadsheets, and someone on your team moves that data in and out by hand. We automate that work around your platform. [Book a 30-minute call →](https://www.flobotics.io/book)[See client results](#proven) DOCPLANNER · EHR INTEGRATION · IN PRODUCTION 10+EHR systems connected 10,000+transactions automated a month What it does - Reads patients and appointments from clinics’ legacy EHRs. - Moves them into the Docplanner app, with insurance details. - Handles scheduling, canceling and rescheduling. - Runs in Spain, Italy, Brazil and Poland. ## What we automate for technology companies 01 ### Data from your customers’ systems We pull data from each customer’s EHR, LIS or billing system into your platform, through an API, scheduled exports or the user interface, whichever that system allows. 02 ### Documents to records We read uploaded documents and forms and turn them into validated, claim-ready or authorization-ready records. 03 ### Results written back We send statuses, authorization numbers, claim outcomes and notes back into your customers’ systems, so nobody copies them by hand. 04 ### Denials and payer correspondence We handle missing records, reconsiderations and payer letters in billing systems and payer portals, and update the record when it’s done. Related [Claims management →](https://www.flobotics.io/agents/claims-management-automation) [Denials management →](https://www.flobotics.io/agents/denials-management-automation) How we work with your team Your platform stays at the center. We build and maintain the customer-specific connections around it. Cases that need a person go to your staff with the reason. Tell us which manual process grows with every new customer, and we’ll tell you whether automation pays off. [Book a 30-minute call →](https://www.flobotics.io/book) ## Proven in production [ Client caseEHR Integration 10,000+transactions automated a month, across 10+ EHRs in four countries. ### EHR integration for Docplanner Read the case study → ](https://www.flobotics.io/case-studies/docplanner) [ Claims Management 98%less manual claim prep. Up to 250 hours a week of manual work removed. ### EHR-to-claim data pipeline for Gentem Health Read the case study → ](https://www.flobotics.io/case-studies/98-reduction-in-manual-claim-prep-claims-management-automation) [ Client caseClaims Management ~24 h → ~7 hfrom uploaded document to claim-ready record, about 70% faster. ### Superbills turned into claims for SuperBill Read the case study → ](https://www.flobotics.io/case-studies/70-faster-claim-turnaround-time-ctt-claim-management-automation) [ Client caseDenials Management 6 min → 30 sper denial, with about 90% of manual rework gone. ### Denials and payer mail for a California medtech company Read the case study → ](https://www.flobotics.io/case-studies/50k-saved-in-1-month-ai-agent-for-denials-management) Talk to us ## Tell us which manual process grows with every new customer. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Automation for Payers & Health Plans | Flobotics Canonical: https://www.flobotics.io/who-we-help/payers --- [Home](https://www.flobotics.io/)/[Who we help](https://www.flobotics.io/who-we-help)/Payers Payers & health plans # We automate the administrative work. Clinical decisions stay with people. Payer teams spend hours on intake, correspondence and provider data changes. We can automate those administrative steps. Clinical, medical necessity and benefit decisions stay with your staff. [Book a 30-minute call →](https://www.flobotics.io/book)[Where we draw the line](#line) WHERE WE DRAW THE LINE We automate - Reading and sorting documents - Pulling out key fields - Routing to the right queue - Entering data between systems - Logging every step People decide - Clinical decisions - Medical necessity - Benefit interpretation - Claim and authorization decisions - Anything unclear ## Administrative work we can automate 01 ### Intake We read incoming applications and documents, pull out the key fields and send each one to the right queue. Incomplete ones are flagged. 02 ### Correspondence We sort letters, faxes and appeals, link each one to the right case, and send anything unclear to a person. 03 ### Provider data We check change requests, such as a new practice address or phone number, and queue the updates for your provider directory. 04 ### Data entry between systems We move data between your core platform, CRM, case management and spreadsheets, and log every step for audit. What we bring ## We know payer systems from the provider side. For labs and providers, we’ve built automations that work in UnitedHealthcare, Availity and other payer portals: status checks, medical record uploads, reconsiderations and appeals. That includes 16 workflows with UnitedHealthcare for our lab clients. We haven’t worked for a health plan directly yet. We would bring the same engineering to your side: the documents, queues and systems your staff works in every day. Every automation logs what it read, what it did and when, so your team can check every step. Anything the automation isn’t sure about goes to a person, with the reason. Where we draw the line A person reviews every clinical item. We automate the administrative steps: reading, extracting, routing and entering data. Clinical decisions, medical necessity and benefit decisions are never automated. If you run payer operations, tell us which administrative queue costs you the most time. We’ll tell you honestly whether automation pays off. [News: states regulating AI in prior authorization and claims decisions →](https://www.flobotics.io/rcm-industry-news/2026-07-19-states-continue-efforts-to-regulate-ai-in-healthcare) Talk to us ## Show us the payer queue that costs you the most time. Let Karl, our CTO, or Bart, our Head of AI, take a look. We’ll tell you honestly whether automation pays off. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # RCM Automation Resources: ROI Calculator, Glossary & News | Flobotics Canonical: https://www.flobotics.io/resources --- [Home](https://www.flobotics.io/)/Resources What we think · Resources # Tools and reading for deciding what to automate. Check whether a process is worth automating with your own numbers, find the right automation for your RCM workflow in three clicks, look up a term, or catch up on RCM news. All free. [Calculate your savings →](https://www.flobotics.io/roi-calculator)[Take the quiz](https://www.flobotics.io/quiz) On this page [01ToolsROI calculator and automation quiz.→](#tools) [02ReferenceGlossary and library of trusted sources.→](#reference) [03RCM industry newsThe latest items, summarized.→](#news) [04WebinarThe 4-step RCM automation stack.→](#webinar) [05Our writingArticles, case studies and briefings.→](#writing) 01 Tools ## Two quick ways to test an idea. Before you book a call, see whether your process is a good automation candidate and which kind of automation fits it. [ROI calculator ### Your CFO will love this one ROI % Adjust the initial data, drag the sliders and see how fast the automation of your process pays off. It accounts for agent development and maintenance costs, with industry benchmarks from 100+ automation projects. Calculate your savings →](https://www.flobotics.io/roi-calculator) [Automation quiz · 3 clicks ### Find the right automation for your RCM workflow 1 / 3 Three questions: the bottleneck that limits your RCM most, the system type you run, and the RCM metric that is your priority now. Your obstacle, your goal, our solution. Start quiz →](https://www.flobotics.io/quiz) 02 Reference ## Terms and sources we rely on. An RCM glossary that keeps everyone on the same page, and the market reports our editorial team works from. [Glossary · 38 terms ### RCM automation terms & metrics From “CARC” and “CTT” to “DOS” and “LOS”. Explained like you’re new, but smart. AI Automation · 5Healthcare · 4RCM Metrics · 9RCM Terms · 20 Browse terms →](https://www.flobotics.io/glossary) [Library of trusted sources ### RCM reports we rely on Our hand-selected collection of RCM market reports and data. Download the original files or save time with our editorial team’s reviews. - AHA’s Intelligent Revenue Cycle Management Market Scan | 2026 Edition - XiFin’s Payor Denial Impact Report | 2025 Edition - BlackBook’s Research on AI in RCM Managed Services | 2026 Edition - Flobotics Review of Claude in Healthcare | 2026 Open the library →](https://www.flobotics.io/library-of-trusted-sources-rcm) 03 RCM industry news ## The latest from revenue cycle, in short. From regulatory updates to billing trends and reimbursement strategies, summarized with a link to the original source. [ Prior Authorization ### Optum unveils two new AI tools for digital prior authorization Optum is launching two AI tools — Digital Auth Complete and InterQual Auth Accelerator — to cut prior authorization delays. Digital Auth Complete integrates into the EHR and automates multiple parts of the process to return responses faster. Fierce HealthcareJuly 19, 2026 ](https://www.flobotics.io/rcm-industry-news/optum-ai-digital-prior-authorization-tools) [ Competitive & Market ### UiPath launches agentic AI solutions for healthcare administration UiPath announced agentic AI solutions for healthcare: medical records summarization, claim denial prevention and resolution, and prior authorization — using agentic automation to accelerate revenue cycle management. UiPath (Investor Relations)July 19, 2026 ](https://www.flobotics.io/rcm-industry-news/uipath-agentic-ai-healthcare-admin) [ Prior Authorization ### Abridge teams with Availity to scale real-time prior authorization An integration between Abridge and Availity aims to speed prior authorization from weeks to minutes, shifting the process from post-visit to real time during the patient exam. Fierce HealthcareJuly 19, 2026 ](https://www.flobotics.io/rcm-industry-news/abridge-availity-real-time-prior-auth) [All RCM industry news →](https://www.flobotics.io/rcm-industry-news) 04 Webinar · recording soon ## The 4-step RCM automation stack A 30-minute live session from June 10, 2026 on four steps (prior auth, eligibility, denials, and claims) and how to automate them without ripping out your EHR. The recording will be available on demand soon. [See the session page →](https://www.flobotics.io/webinar) - ### Prior authorization - ### Eligibility - ### Denials - ### Claims 05 Our writing ## Signed by people who build the automations. Every article is signed by a person you can call. [Articles ### Every article from the team Stories, frameworks and lessons from the field on RCM, AI and automation. Browse articles →](https://www.flobotics.io/blog) [Case studies ### Real stories, real numbers How healthcare teams cut costs, reduced denials and automated RCM workflows. See our work →](https://www.flobotics.io/case-studies) [Editorial team ### Who writes our content The people who build and run our automations write about them, and the methodology behind it. Meet the team →](https://www.flobotics.io/our-editorial-team) Technology briefings ### AI tools in healthcare Where each tool fits in revenue cycle work. - [Claude](https://www.flobotics.io/claude-for-healthcare-automation) - [ChatGPT](https://www.flobotics.io/chat-gpt-for-healthcare) - [Microsoft Dragon Copilot](https://www.flobotics.io/microsoft-dragon-copilot) - [Google Antigravity](https://www.flobotics.io/google-antigravity-in-healthcare) - [AWS Connect Health](https://www.flobotics.io/aws-connect-health) - [XiFin](https://www.flobotics.io/xifin-in-rcm) Talk to us ## Show us the process your team is tired of doing manually. Let Karl, our CTO, or Bart, our Head of AI, take a look. It’s 30 minutes with someone who designs the automations, not a sales script. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the process your team does by hand. We’ll tell you whether it’s worth automating and how we’d approach it. Karl & Bart --- # Security and Patient Data (PHI) | Flobotics Canonical: https://www.flobotics.io/security --- [Home](https://www.flobotics.io/)/Security and patient data Security and patient data # How we protect your data across AI and automation We build AI agents, integrations and automations that work with patient information. Here is how we handle protected health information (PHI): where it is processed, who can access it and what we sign before work with patient data begins. - ## Where your data is processed Most workflows run in your environment or in an AWS or Azure account you own. The setup depends on your systems and the work involved. An integration can move information between your applications. When a step needs cloud AI, document content or other information needed for that task is processed by the selected service. - ## How we use AI services For document reading and other AI steps, we use services from AWS, Microsoft Azure or Google Cloud. For patient-data workflows, the service must be covered by the applicable Business Associate Agreement (BAA). We use services under terms that do not allow providers to train their general-purpose models on your patient data. Retention and logging are separate: they depend on the selected service, features and configuration. - ## What we sign We sign a Business Associate Agreement (BAA) before accessing patient data. If you are showing us a workflow with real patient information, the BAA comes first. - ## Who can access it In an environment you own, your team controls who has access. We need access to build, test and maintain the workflow. Access can include project team members and the accounts used by integrations or automation. Permissions depend on the work those people and services need to do. - ## Storage and retention The workflow reads and processes patient data to complete the task, then writes the results back into your systems. Temporary files, transaction records and provider logs can have their own retention requirements. Where transaction data includes PHI, it is encrypted. The details depend on the workflow and services involved. - ## Policies and compliance Our security policies are available through our trust center. Your security or procurement team can request access to the policies and a security questionnaire there. [Open our trust center →](https://trust.inc/flobotics) Have a question about security that isn't answered here? Ask Karl, our CTO, or Bart, our Head of AI, [on a call](https://www.flobotics.io/book), or [write to us](https://www.flobotics.io/contact). --- # AI & Automation Services | Flobotics Canonical: https://www.flobotics.io/ai-automation --- [Home](https://www.flobotics.io/)/[What we do](https://www.flobotics.io/what-we-do)/AI & Automation AI & Automation # We build AI agents that work in your existing systems. Our AI agents read documents, check the information, make routine decisions and complete tasks in the software your team already uses. We combine AI, RPA and integrations, depending on the process. When a case needs someone’s judgment or approval, the agent sends it to your team. [Book a 30-minute call →](https://www.flobotics.io/book)[See client results →](#results) ## What can an AI automation do? 01 · Read ### Read and understand The agent extracts information from emails, PDFs, faxes and forms, even when they don’t follow the same format. 02 · Check ### Check and decide The agent compares the information with your systems and business rules, finds what’s missing, and makes decisions when the criteria are clear. 03 · Act ### Work in your software The agent enters data, updates records, submits requests and checks statuses. We use APIs when they’re available and automate the user interface when they’re not. 04 · Ask ### Know when to ask for help Routine cases run automatically. Cases with missing information, unclear results or a need for approval go to the right person on your team. ## How an AI agent handles incoming requests Example run · four requestsMade-up data - Read - Check - Act - Ask your team Inbox - FaxReferral from Lakeshore Family Medicine3 pages · Anna RiveraDone - EmailLab results from Northfield LabPDF · James OkaforDone - FaxReferral from Riverside Clinic2 pages · Tom BeckerTo your team - FormAddress change from the patient portalWeb form · Maria LopezDone Now working on Referral from Lakeshore Family Medicine What it read PatientAnna Rivera Date of birth03/14/1961 OrderedLumbar MRI InsuranceLakeshore PPO What it checked - Patient found in the EHR - Insurance is active - Order is signed Referral filed to the chart. Scheduling request created. Done automatically3 - Referral filed, scheduling request created - Results attached, Dr. Chen notified - Address updated in the EHR and billing Your team1 - Tom Becker’s referral: no signature on page 2 Example with made-up patients. The AI agent reads each request, checks it against the EHR and your rules, and completes it in your systems. A referral without a signature goes to your team.PauseReplay ## What our AI agents work with Most manual work starts with something a person has to read: a fax, a letter, a scanned form or a message in a payer portal. The agent reads it, finds the information it needs and checks that information against your systems. If a document is unclear or a field doesn’t match, the agent doesn’t guess. It sends the case to your team. In healthcare - Insurance cards and patient details - Referrals, orders and lab requisitions - Medical records for prior authorizations and appeals - Eligibility, claim status and authorization responses - EOBs, remittances and denial letters - Faxes, scanned mail and payer portal messages In other industries - Invoices and accounting documents - Reports, emails and business forms - Records in ERP systems such as SAP ## AI when it’s useful. Regular automation when it isn’t. Not every process needs AI. We use AI for work that involves reading documents, interpreting information, or handling variations that are hard to describe with rules. For predictable steps, we use code, APIs and RPA. This makes the automation easier to test, maintain and control. Even when AI reads the document, the steps that change your records follow fixed rules. The same case always gets the same result, and we can test it before it goes live. Each run is logged: what the agent read, what it checked and what it changed. We reuse components from earlier projects, but every automation is built around your systems and your rules. And if your systems don’t share information, we connect them too. [Explore Data & Integrations →](https://www.flobotics.io/data-integrations) ## We’ve automated processes in different industries. Healthcare · AI agents for denials and mail ### A molecular diagnostics company in California The billing team worked denials and paper mail from payers by hand, in XiFin and in payer portals. Our AI agents read each denial and each letter, match it to the right claim, and then resubmit the claim or post the letter in XiFin. Cases that need a person go to the team. 30 sper denial, down from 6 minutes 80%of a 3,000-claim backlog cleared in three weeks 95%less manual work on payer mail [Read the case study →](https://www.flobotics.io/case-studies/50k-saved-in-1-month-ai-agent-for-denials-management) Healthcare · eligibility checks ### Pain Treatment Centers of America PTCoA’s staff checked insurance in payer portals by hand and copied the results between the EHR and the billing system. We automated the whole process. ~40 sper check, down from 5–7 minutes 8,000+checks a month ~3 FTEof staff time saved [Read the case study →](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks) GPS tracking · UiPath RPA ### Global-View Activation requests came in by email, and staff set up accounts and devices in several applications. A UiPath robot now checks the payment, sets up the account and devices, and emails an administrator when there’s a problem. 1 sper activation, down from about 10 minutes 600xfaster 1UiPath developer, under three weeks [Read the case study →](https://www.flobotics.io/case-studies/global-view-automation) Outside healthcare, we’ve automated work in manufacturing, energy, finance, tax, travel and telecom. [See business process automation →](https://www.flobotics.io/business-process-automation) ## Healthcare workflows we know well We’ve built reusable components for the most common revenue cycle work. We adapt them to each client’s systems and rules. ### [Eligibility verification](https://www.flobotics.io/agents/eligibility-check-automation) Check coverage, benefits and deductibles, then update the patient record. ### [Prior authorization](https://www.flobotics.io/agents/prior-authorization-automation) Collect the clinical documents, prepare and submit the request, and track it until there’s an answer. ### [Claims management](https://www.flobotics.io/agents/claims-management-automation) Check claims, find errors, and handle the routine corrections and follow-ups. ### [Denials management](https://www.flobotics.io/agents/denials-management-automation) Find out why a claim was denied, gather what’s needed, and prepare the correction or appeal. [Explore healthcare automation →](https://www.flobotics.io/rcm-automation) ## How we work - ### Understand the process You show us the manual work, the systems and the exceptions. We estimate the effort, the savings and the ROI. If a process isn’t worth automating, we tell you. If patient data is involved, we sign a BAA first. - ### Build and test We pick the technology that fits, build around the applications you already have, and test on real examples before anything goes live. - ### Run and maintain We put it live, watch the results, fix problems, and update it when your systems or rules change. [How we price →](https://www.flobotics.io/pricing) Talk to us ## What would you like to automate? Show us the work your team does by hand. We’ll tell you what can be automated, where AI makes sense and what it would take to build. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message →](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the work your team does by hand. We’ll tell you which parts we can automate, what it would cost, and whether it’s worth doing. Karl & Bart --- # Healthcare Data Integration & Automation | Flobotics Canonical: https://www.flobotics.io/data-integrations --- [Home](https://www.flobotics.io/)/[What we do](https://www.flobotics.io/what-we-do)/Data & Integrations Data & Integrations # How much you can automate depends on your data. More work will be done by software and AI agents. But they can only do that work if they can find the right information, use it, and update the systems involved. We organize your data and connect your systems, so your people, your applications and your automations have the information they need. [Book a 30-minute call →](https://www.flobotics.io/book) ## Your data is more important than the tools you use. AI models and automation tools keep getting better. But if your data is spread across systems that don’t talk to each other, full of inconsistencies or hard to get to, even the best tool can only do so much. Getting your data organized solves problems today and makes it easier to automate more work later. And you shouldn’t have to rebuild your data setup every time you add an application or an AI agent. Example · one patient, four systemsMade-up data Where the data is - EHRMatchedRIVERA, ANNADOB 03/14/1961 · Visit Oct 20, 9:30 - Lab systemMatchedAnna M. Rivera1961-03-14 · Lipid panel, final - BillingMatchedRivera, Anna3/14/61 · Lakeshore PPO, $40 copay - Scanned documentsMatchedreferral_rivera.pdfA. Rivera · signed referral One record Anna Rivera Date of birthMar 14, 1961 Next visitOct 20, 9:30 Latest labLipid panel, final InsuranceLakeshore PPO, $40 copay ReferralSigned 4 records, one patient Who uses it - Booking appShows the Oct 20 visit - ReportsCount one patient, not four - AI agentChecks her insurance before the visit - Your staffFind everything in one record Example with made-up data. The same patient is written four different ways in four systems. Once the records are matched, the booking app, reports, an AI agent and your staff all work from one record, and each sees only what it’s allowed to.PauseReplay ## What an automation needs from your data An automation acts on the data it finds. If it finds the wrong patient, an outdated status or a duplicate record, it makes the same mistake every time it runs. That’s why we build these checks into our integrations. ### The right record We match records by ID, such as a member ID, claim number or accession number, not by name alone. Two patients can have the same name. ### One correct version When two systems disagree, we agree with you on which system is correct for each piece of information. ### Statuses that mean what they say A claim that was submitted hasn’t necessarily been accepted. The automation records what actually happened. ### Nothing entered twice If a step has to run again, the automation first checks what already went through. ### No guessing When information is missing or doesn’t match, the automation sends the case to a person instead of filling in a guess. ### Where the data came from We record the source and the time, so you know how current the information is. ## What we build ### Data lakes & warehouses We bring data from different systems into one place, keep the history, and make it available for analysis and to authorized applications, automations and people. ### Data migrations & cleanup We move data between platforms, remove duplicates, standardize formats, and make sure records are accurate and consistent. ### System integrations We connect EHRs, billing platforms, CRMs and databases through APIs, or through automation when there is no API. ### Data pipelines & access We keep information up to date between systems and make it available to dashboards, applications and AI agents, with access controls. ## How we connect your systems We use whatever each system supports. Most integrations combine several of these methods. For example, one automation can look up a claim through an API, upload a document in a payer portal and write the result back to the billing system. APIWhen a system has an API that covers the task, we use it. It’s usually the most stable connection. ScreensWhen there’s no API, or it doesn’t cover what you need, the automation works in the application the way your staff does: it signs in, searches, reads and types. We do this in payer portals, older EHRs and desktop software. FilesExports, reports and spreadsheets in CSV, Excel or PDF. We read them, check them and load the data where it needs to go. DocumentsFaxes, scans and letters. We extract the information with OCR and AI, and send unclear documents to a person. Healthcare data integration ## What does this mean in practice? Take a [prior authorization request](https://www.flobotics.io/agents/prior-authorization-automation). The patient’s details are in the EHR. The clinical documents are stored somewhere else. The insurance has to be checked with the payer. And the answer has to go back into the EHR. Without connections between those systems, someone on your team collects it all by hand. With them, an automation or an AI agent can collect the information, send the request and update the systems. Your staff handles the cases that need their attention. The same data can also be used for reporting, other automations and future applications. ## How we approach it - ### Understand your systems We find out where your data lives, how it’s structured, who needs it, and where it’s missing or duplicated. - ### Organize and connect We work out whether you need a data lake, a warehouse, a migration, new integrations, or just better access to the systems you have. Then we build that. - ### Make it usable We test the connections, check the data, set up access controls, and make sure your applications and automations can rely on it. Your data stays in your systems. In most cases, the automation runs on a machine you own, and we sign a BAA before we see any patient data. [How we handle patient data →](https://www.flobotics.io/security)[How we price →](https://www.flobotics.io/pricing) Client examples ## We’ve connected systems that weren’t built to work together. Docplanner · EHR integration Clinics using Docplanner’s booking app often kept their old EHRs, and some of those are hard to connect. We built the integrations that move patient and appointment data between those EHRs and the app, in Spain, Italy, Brazil and Poland. 10+ EHR systems integrated 10,000+ transactions automated a month 98%+ of cases processed automatically [Read the Docplanner case study →](https://www.flobotics.io/case-studies/docplanner) Laboratories · XiFin and payer portals Many labs bill in XiFin, but much of the follow-up happens in payer portals. Our automations start from an account in XiFin, get what they need from the payer portal, submit the request or upload the missing records, and write the result back to XiFin. 61 automations involving XiFin, running in production 16 work with UnitedHealthcare [How we work with laboratories →](https://www.flobotics.io/who-we-help/laboratories) Talk to us ## Is your data ready for more automation? Show us where your data lives and what you want to do with it. We’ll tell you what needs to be organized, connected or migrated. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Show us where your data starts and where it needs to go. We’ll tell you how we’d connect it, what it would cost, and whether it’s worth doing. Karl & Bart --- # Dedicated Automation Teams | Flobotics Canonical: https://www.flobotics.io/dedicated-teams --- [Home](https://www.flobotics.io/)/[What we do](https://www.flobotics.io/what-we-do)/Dedicated Teams Dedicated Automation Teams # Your own automation team, without hiring one. You get a dedicated automation team, backed by our project managers, senior engineers and specialists. We build, deploy and maintain the automations. You decide which processes matter most. We handle the technical work. [Book a 30-minute call →](https://www.flobotics.io/book) Client · Docplanner “The team communicates effectively and is proactive in both product discovery and development. I love the business drive of the team and their flexibility.” Kamil Walczak, Product Lead, Docplanner [Read the case study →](https://www.flobotics.io/case-studies/docplanner) ## What’s included ### A dedicated team The same people work on your automations for the whole engagement. They learn your systems, build and test the automations, and fix issues. ### Project management Keeps the work organized, sets the priorities with you, and tells you where things stand. ### Senior engineering support Our senior developers and architects help with technical decisions, code reviews and complex problems. ### Additional specialists When a process needs AI, Python, [UiPath](https://www.flobotics.io/uipath-services), APIs or data engineering, we bring in people from our team with the right experience. ## How we work - ### We start with five processes Before you commit to anything, we look at five processes you’d like to automate. We estimate the work, the savings and the ROI. This assessment is free. If we can’t find five processes worth automating, we won’t suggest a team. - ### We start building Your team gets to know your systems and starts on the first automation. We handle the development, testing, deployment and technical issues. - ### We move to the next process Once an automation is running, we move on to the next one, and keep maintaining what we’ve built. Over time, the team knows your systems well, and new automations reuse code and components from the earlier ones. ## Who does what Your side - Decide which processes come first. - Show us the work on a screen share, with the person who does it. - Give us access to the systems. If patient data is involved, we sign a BAA first. - Explain the rules that aren’t visible on the screen, such as payer or billing rules. - Test with real cases and approve each automation before it goes live. - Decide what to do with the cases an automation sends to your team. Our team - Maps each process and estimates the effort and the savings. - Chooses the technology: UiPath, Python, APIs, AI or a combination. - Builds, tests and deploys the automations. - Fixes problems and updates the automations when your systems change. - Keeps you informed about progress and problems. ## Six-month engagement. Cancel in the first 30 days at no cost. Our standard engagement is six months. You can cancel for any reason in the first 30 days. The 30 days start when the team starts work, not at the first call. If you cancel, you owe nothing for the first month or the remaining five months. If you continue, we invoice at the end of each month, after the work is done. [Our 30-day promise →](https://www.flobotics.io/our-promise)[How we price →](https://www.flobotics.io/pricing) Team agreement · six monthsHow the 30 days work - BeforeFree assessmentWe assess five processes with you. You haven’t signed anything yet. - Day 1The team startsYour 30 days start on the day the team starts work. - Day 30You decideCancel for any reason and owe $0. Or continue, and we invoice the first month after the work is done. - Months 2–6The work continuesThe team builds, deploys and maintains your automations. We invoice at the end of each month, never in advance. How the six-month team agreement works: a free assessment first, then 30 days to decide after the team starts, then invoices at the end of each month. ## One project or a dedicated team? One project ### One process with a clear scope You have one process to automate. After we’ve seen the process, you get an exact price. We build the automation, put it live, and can maintain it afterward. [How we price →](https://www.flobotics.io/pricing) A dedicated team ### Several processes, and more to come You have several processes to automate, the list keeps growing, and you want the same people to build and maintain them. Each new automation reuses what the team has already built for you. [How the team agreement works →](https://www.flobotics.io/our-promise) Talk to us ## Have several processes you want to automate? Tell us what your team does by hand. We’ll review five processes for free and tell you whether a dedicated team makes financial sense. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Tell us what you want to automate this year. We’ll tell you what kind of team it needs, or whether one project is enough. Karl & Bart --- # Automation Maintenance & Support | Flobotics Canonical: https://www.flobotics.io/maintenance-support --- [Home](https://www.flobotics.io/)/[What we do](https://www.flobotics.io/what-we-do)/Maintenance & Support Maintenance & Support # We maintain your automations. Even the ones we didn’t build. Automations need maintenance. Websites change, software gets updated, and processes change over time. We monitor your automations, investigate failures, make fixes, and keep them working. [Book a 30-minute call →](https://www.flobotics.io/book) ## What we take care of ### Monitoring We check that each automation ran, how many cases it finished, and which ones it sent to your team. A run can end without errors and still miss work, so we look at the results, not only at the run. ### Fixing problems When an automation stops working, we find out what changed, fix it, and test it before it goes back into production. ### Updates & changes When an application, a website, a data format or a business rule changes, we update the automation to match. ### Improvements We improve existing automations so they handle more cases, make fewer errors or process work faster. ## Why automations stop working An automation works in systems that other people change. Most failures start with one of these. Sign-insA password expires, an account gets locked, or the multi-factor sign-in changes. Portals and websitesA payer changes its portal: a new page layout, a new field or a new rule for what it accepts. Software and outagesAn application, a browser or the machine the automation runs on gets updated, or a system is slow or down. DocumentsA form or a letter arrives in a layout the automation hasn’t seen before. DataA record is missing, doesn’t match another system, or is linked to the wrong account. RulesYour process, a payer’s rule or a coding convention changes. Some unfinished cases aren’t failures at all. The automation worked correctly and sent the case to your team because a person has to decide. When we look at a run, we tell the two apart. ## What happens when an automation breaks Example · payment posting · one weekMade-up data Run log - Mon 6:00128 payments128 posted - Tue 6:00135 payments134 posted · 1 to your team - Wed 6:00141 paymentsStopped after 37 postedRe-run after the fix · 102 posted · 2 to your team · 0 posted twice - Thu 6:00133 payments133 posted - Fri 6:00139 payments137 posted · 2 to your team What we did on Wednesday - NoticedThe run stopped after 37 of 141 payments. - Found the causeThe payer had shortened its portal sessions, so the portal signed the automation out in the middle of the run. - Fixed and testedThe automation now signs in again when a session ends. We tested the fix before the re-run. - Ran the restThe automation checked each payment before posting it. The 37 already posted were skipped, so nothing was posted twice. - ReportedWe told your team what happened and what we changed. Example with made-up data: payment posting from a payer portal. On Wednesday the portal signed the automation out in the middle of the run. We found the cause, fixed and tested it, posted the remaining payments without posting any twice, and told your team what changed.PauseReplay ## Someone else built your automations? We can take over. We maintain [UiPath](https://www.flobotics.io/uipath-services), Power Automate, Python and other custom automations, including ones built by your own team or another vendor. - ### Review what you have We look at your automations, the code, where they run, the accounts they use, the documentation and the problems you already know about. - ### Agree on what’s covered We agree on what to fix first, which automations we monitor, and what support includes. If an automation would be cheaper to rebuild than to fix, we tell you. - ### Start maintaining We take responsibility for those automations, look into every failure, and make the updates they need. If you have a [dedicated team](https://www.flobotics.io/dedicated-teams) with us, maintaining your automations is part of its work. If you only need support, we agree on which automations it covers and what it includes. [How we price →](https://www.flobotics.io/pricing) Client example ## We’ve taken over from other automation providers. One of the largest sugar producers in the world came to us after working with another RPA vendor. We started with SAP automations in controlling and finance, then moved into client service, sales and logistics. It became one of our longest partnerships. [Read the case study →](https://www.flobotics.io/case-studies/sugar-producer-automation) SAP automation program 4,685 h of manual work saved a year, across the whole automation program. Talk to us ## Need someone to maintain your automations? Show us what you run and what keeps going wrong. We’ll look at it and tell you what supporting it would involve. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Show us what runs today and what keeps failing. We’ll tell you what we’d fix first and what taking it over would cost. Karl & Bart --- # UiPath Development Services | Gold Partner | Flobotics Canonical: https://www.flobotics.io/uipath-services --- [Home](https://www.flobotics.io/)/[What we do](https://www.flobotics.io/what-we-do)/UiPath Services UiPath Services # Your next UiPath automation shouldn’t start from zero. We’re a UiPath Gold Partner with our own development framework. Each new automation we build for you on the same systems reuses parts of the ones before it, so it costs less to build. We also recommend only the licenses you need. [Book a 30-minute call →](https://www.flobotics.io/book)[What UiPath wrote about us](#proof) - UiPath Gold Partner - Certified UiPath developers - Featured by UiPath FOUR AUTOMATIONS · SAME SYSTEMSEXAMPLE What we build new, and what we reuse 1st2nd3rd4th Login and sessions Moving between screens Screens and fields Error handling and retries Logs and reports Process steps Cost (1st = 100%)100%~55%~40%~25% Built newReused from our library Based on one client’s projects. How much you save depends on how much the processes have in common. Our framework ## We build every automation so the next one can reuse it. The first automation on a system takes the most work: learning the system, handling logins, mapping every screen and field, and deciding what happens when something goes wrong. We build each of those pieces once, as a reusable component. The next automation on the same system reuses them, so we only build what’s different about the new process. [How we structure UiPath projects →](https://www.flobotics.io/blog/naming-conventions-uipath) What goes into our library - Logins and sessions for each system - Moving between screens - Screens and fields, shared between projects - Error handling and retries - Logs and reports - Project structure and naming rules Licenses ## We only recommend the licenses you need. Licenses are a large part of what UiPath costs. Before we recommend any, we look at how much work your robots will do and when your team needs the results. Each robot that runs on its own needs its own license. So we schedule your automations to share robots where they can, and you buy fewer licenses. Our goal is the best return on your automation, not the biggest license order. Robot schedule24 hours Without a plan3 robots Robot 1 Robot 2 Robot 3 With a plan1 robot Robot 1 12 a.m.6 a.m.Noon6 p.m.12 a.m. Eligibility checksClaim status checksPayment posting Illustration. Whether automations can share a robot depends on when your team needs the results. Proof ## UiPath has written about our work and recommended us to a customer. Customer story on uipath.com ### PRMG, a U.S. mortgage lender PRMG’s loan volume was growing faster than its team could handle. We automated six core steps of its loan processing, and UiPath published a customer story about the project. 550tasks automated a day 40 hof manual work saved a day 6:1return on investment “Within very short-term working sessions, they’re able to automate the steps I communicate to them.” PRMG, quoted by UiPath Figures as UiPath reported them at the time. [Read the story on uipath.com ↗](https://www.uipath.com/resources/automation-case-studies/prmg)[Our summary →](https://www.flobotics.io/blog/flobotics-prmg-loan-processing-rpa-automation) Recommended by UiPath ### Docplanner, a platform for booking doctor appointments Docplanner needed to move data between clinics’ EHRs and its app. UiPath built a first version for one EHR and recommended us to build the full system. We rebuilt it from scratch so it could grow to new EHRs, clinics and countries. 10,000+transactions automated a month 10+EHRs connected 4countries [Read the case study →](https://www.flobotics.io/case-studies/docplanner) More of our UiPath work: [SAP automations for a large sugar producer](https://www.flobotics.io/case-studies/sugar-producer-automation), [account activations for Global-View](https://www.flobotics.io/case-studies/global-view-automation), and [denials and payer mail in XiFin, with UiPath and AI](https://www.flobotics.io/case-studies/50k-saved-in-1-month-ai-agent-for-denials-management). Our story ## Why we started Flobotics “Before Flobotics, I worked as an RPA architect at large corporations. What mattered there was how much a project billed, not the quality of what the client got at the end. I didn’t want to work that way, so we started a company where the quality of what the client gets comes first.” Karl MielnickiCo-founder and CTO ## UiPath implementation, support and licensing ### Starting with UiPath We find what’s worth automating and build your first automations. ### Adding more automations Each new automation reuses what we’ve already built for you. ### Paying for too many licenses We check your licenses and tell you what you can stop paying for. ### Robots that keep breaking We fix unreliable robots, including ones another partner built. We also maintain automations as your systems change. [Maintenance and support](https://www.flobotics.io/maintenance-support) ### A dedicated UiPath team Our developers work as part of your team, for as long as you need them. [Dedicated teams](https://www.flobotics.io/dedicated-teams)[Our 30-day promise](https://www.flobotics.io/our-promise) ### Not only UiPath If another tool fits a process better, we’ll tell you. Sometimes a Python script or an API connection does the job without a robot license. We compare the total cost, including maintenance, not only the license price. Talk to us ## Getting the most out of UiPath? Book a 30-minute call with Karl, our CTO, or Bart, our Head of AI. If you’d rather write, send us a message. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Show us your robots and your licenses. We’ll tell you what we can build or fix, and where you might be paying for more than you use. Karl & Bart --- # Our Promise: 30 Days to Earn Your Trust | Flobotics Canonical: https://www.flobotics.io/our-promise --- Our promise # You don’t trust us yet. Give us 30 days to change that. Plenty of companies promise that AI and automation will save you time and money, and we know we sound like one more of them. Working with us means trusting us with your systems, your processes, your staff and your budget. That is a lot to ask of a company you haven’t worked with before. So rather than ask you to take our word for it, we let you judge our work first, and we carry the cost if you decide we’re not the right fit. TEAM AGREEMENT · 6 MONTHSP. 2/6 The first 30 days - The 30 days start on the day the team starts work. - The client may cancel within the first 30 days, for any reason. - A client who cancels owes $0. Not happy? You pay nothing. Karl Mielnicki, CTO - 01We assess five processes for free - 02You get a dedicated team on a six-month agreement - 03You have 30 days to decide, and owe $0 if you cancel 01Free ## First, we find five processes worth automating, for free. Together with your team, we look for five processes where automation would clearly save money, not ones that only look good in a presentation. For each process, we work out together: - how the process works today - how often it runs and how much time it takes - what it costs you - which systems, documents and people are involved - what exceptions and technical limits exist - how automation would work and which technology fits - how much you could realistically save, and the return to expect We base the estimates on your real volumes and costs, not general assumptions. If a process shouldn’t be automated, we tell you. The assessment is free, and you’re under no obligation to continue. If we can’t find five processes that are worth automating, we won’t suggest a team engagement. 02Six-month agreement ## Then we sign a six-month agreement and assign your team. Once we agree on the five processes and how to automate them, we sign a six-month agreement and assign a team with the skills those processes need. The team builds and runs the automations themselves, inside the systems you already use. Depending on the process, that may mean UiPath, Python, API integrations, AI agents or a combination of them. We choose the technology to fit the process, not the other way around. 0330 days ## You have 30 days to decide whether to continue. The 30 days start on the day our team starts working with yours. In that time you’ll see how we communicate, how we deal with difficult problems, how we make technical decisions and what we deliver. Thirty days isn’t enough to automate everything, but it is enough to tell whether we’re the right people for the job. At the end of the 30 days, you decide. ### If you continue We keep working under the six-month agreement. We invoice at the end of each month, never in advance. ### If you cancel You can cancel for any reason, for example: - Don’t like the quality of our work?Cancel - Don’t like how we communicate?Cancel - Woke up on the wrong side of the bed?Cancel - A black cat crossed your path this morning?Cancel - Don’t like Karl’s mustache?Cancel You don’t need to explain why, and nobody will call you to change your mind. 04If you cancel ## If you cancel in the first 30 days, you owe us nothing. $0 - We don’t invoice the first 30 days. - There is no cancellation fee. - You owe nothing for the remaining five months. - We cover the cost of the work we’ve already done. The only thing you’ve spent is your team’s time. We’ll make sure that time is useful. Even if you cancel, you’ll come away with a clear picture of your five processes, what automating them would take and what it would save. 05The terms ## The terms in full There is no small print beyond this. Here is exactly how the arrangement works. The assessment is free.We assess five processes with you before any team engagement starts. The agreement is for six months.Once we’ve agreed on the five processes and the plan, we sign a six-month team agreement. You have 30 days to decide.The 30 days start on the day the team starts work. You pay nothing in advance.We invoice at the end of each month, never before. If you cancel in the first 30 days, you pay nothing.We don’t invoice the first month, and you are released from the remaining five months. If you continue past 30 days, monthly billing starts.The six-month agreement continues, invoiced at the end of each month. This offer applies to our six-month automation team agreements. 06Why ## Why we offer this For most companies, the bigger question isn’t whether automation works. It’s whether we are the right company to do it. A sales call can’t tell you whether we’ll understand your operations, solve difficult problems, communicate well and deliver work you’re confident putting into production. You only find that out by working with us, so we make it possible to do that without financial risk. If we turn out not to be the right fit, we accept that. If we are, we hope the six months are the start of a long working relationship. You don’t need to convince us to keep your business. ## We need to convince you. [Let’s find your five processes →](https://www.flobotics.io/book) --- # Healthcare Document Processing Automation | Flobotics Canonical: https://www.flobotics.io/healthcare-document-processing Published: 2026-10-11 Updated: 2026-10-11 --- [Home](https://www.flobotics.io/)/[What we do](https://www.flobotics.io/what-we-do)/Document processing Workflows we automate # Healthcare Document Processing Automation We turn faxes, scanned forms, PDFs and images into checked data for your EHR, LIS or billing system. The automation reads the document, extracts the fields you need and sends unclear or incomplete records to your team. [Book a 30-minute call →](https://www.flobotics.io/book)[See client results](#results) Illustration with three made-up documents. The automation reads a referral fax and a superbill PDF, checks their required fields and saves the extracted data. A scanned form has an unreadable service date and goes to staff review. Two records are saved and one needs review. Document reading and validation - Read - Extract - Check - Write Document inbox - A. Rivera · document D-1041Referral faxChecked data saved - J. Okafor · document D-1042Superbill PDFChecked data saved - M. Chen · document D-1043Scanned intake formStaff review · unreadable date 2 records saved · 1 needs review Current document · A. Rivera · document D-1041 DocumentD-1041 TypeReferral fax Data →Your system← Saved Document textRead Required fieldsComplete Service date2026-10-08 RecordSaved Checked data saved to the record Example with made-up patients and documents. Unclear information goes to staff review. PauseReplay Client result · SuperBill ## From uploaded documents to claim-ready records SuperBill's team reviewed uploaded PDFs and images by hand. We built a workflow that reads the documents, structures the claim data and routes exceptions to specialists. [Read the SuperBill case study →](https://www.flobotics.io/case-studies/70-faster-claim-turnaround-time-ctt-claim-management-automation) Measured results ~24 h →to ~7 hdocument-to-claim cycle ~95%of documents processed without intervention 300–500uploaded files handled each day Results from SuperBill's document-processing workflow. The roughly 70% reduction measures preparation time, not payer reimbursement time. What we automate ## From incoming documents to usable records. Referrals, requisitions, intake forms, superbills and payer correspondence. We scope the document types and required fields with your team. - 01Read Collect documents from the places you already use. - Receive files from your existing fax, email or upload process. - Read text from faxes, scans, PDFs and images. - Keep the source document with the extracted information. - 02Extract Capture the fields your next task needs. - Extract patient, provider, insurance and billing details already present in the document. - Structure the data for the receiving system. - Use the model and extraction instructions selected for your documents. - 03Check Check the result against your rules. - Check required fields and formatting. - Flag unreadable scans, missing fields and conflicting information. - Route cases that need judgment to staff. - 04Write Save checked data where your team works. - Transfer the data and source document into your EHR, LIS or billing system. - Use an API or screen automation for the connection. - Route the record to the next agreed workflow. Your team reviews unclear information. Document extraction prepares existing information for the next task; claim submission and authorization decisions remain separate workflows. Is it a good fit? ## Document automation usually pays off when most of these are true. - Your team reads many faxes, scans or PDFs each day. - Staff copy the same fields into an EHR, LIS or billing system. - The required information and validation rules are clear. - You know which exceptions need staff review. What affects your savings - How many documents you process each month - How long reading and data entry take by hand - Document quality and the range of formats - How often a record needs staff review - Model usage, integration and maintenance costs The return is different for every organization. We'll discuss the work involved and what we'd need to estimate the cost. [Book a 30-minute call →](https://www.flobotics.io/book) How document processing works with your systems ## Your documents, models and systems. Illustration of document processing between three places: your document inbox, the automation and your receiving system. Two documents have readable required fields and their data is saved. The third has an unreadable service date and is sent to staff review. Your fax, email or upload inbox DocumentPatientLast updateStatus D-1041A. Rivera—Ready D-1042J. Okafor—Ready D-1043M. Chen—Ready Flobotics automation Your rulesCheck required fieldsSave checked dataMissing information → staff Your EHR, LIS or billing system DocumentPatientService dateSave checked data Record update— Your staff · review queue M. Chen · document D-1043Service date is unreadable. Check the source document. No exceptions yet Monitored and maintained by us. We check the runs and update the workflow when document formats or your systems change. Example with made-up patients and documents. Unclear information goes to staff review. PauseReplay We adjust extraction instructions and validation rules, then check the results again. The receiving system can use an [API or screen automation](https://www.flobotics.io/data-integrations). Cases the workflow cannot reliably handle go to staff. Patient data (PHI) What happens to your patient data Your data is safe. Where it runsOn a machine you own: usually a virtual machine on your side, or your own AWS or Azure account. What we storeWe don't store patient data. The automation reads it, uses it and writes the result back. In the rare case PHI has to be in transaction data, it's encrypted. Who can access itOnly the developer who builds and maintains the automation. On your machine, you decide who else gets access. What we signA BAA before we see any patient data. AI runs on AWS, Azure or Google under BAAs, and your data isn't used to train models. [How we handle patient data →](https://www.flobotics.io/security)[Request our security policies →](https://trust.inc/flobotics) Related workflows ## The workflows that use your document data. - 01[Eligibility & benefits](https://www.flobotics.io/agents/eligibility-check-automation)Check coverage before the visit and save the result in the patient record.~40 s per checkPTCoA · [Case study](https://www.flobotics.io/case-studies/100-roi-in-just-23-days-we-automated-eligibility-checks)→ - 02[Prior authorization](https://www.flobotics.io/agents/prior-authorization-automation)Prepare and submit authorization requests, then check for updates.85% less submission timePTCoA · [Case study](https://www.flobotics.io/case-studies/85-faster-submissions-8-ftes-saved-prior-authorization-automation)→ - 03[Claims management](https://www.flobotics.io/agents/claims-management-automation)Prepare, submit, and track claims.98% less manual claim preparationGentem Health · [Case study](https://www.flobotics.io/case-studies/98-reduction-in-manual-claim-prep-claims-management-automation)→ - 04[Denials management](https://www.flobotics.io/agents/denials-management-automation)Prepare supported corrections and appeals, then track payer responses.Up to 300 resubmissions a dayPathGroup · [Case study](https://www.flobotics.io/case-studies/up-to-80-higher-throughput-in-rcm---denials-management-automation)→ - 05Document processingTurn faxes, scans and PDFs into checked data for your systems.You are here [Explore revenue cycle management automation →](https://www.flobotics.io/rcm-automation) [Read our guide to healthcare document processing →](https://www.flobotics.io/blog/healthcare-document-processing) Talk to us ## Which documents slow your team down? Book a 30-minute call with Karl, our CTO, or Bart, our Head of AI. If you'd rather write, send us a message. [Book a 30-minute call →](https://www.flobotics.io/book)[Send a message](https://www.flobotics.io/contact#contact-form) 30-minute callKarl or BartOur CTO, or our Head of AI Walk us through the documents your team reads by hand and where the data needs to go. We'll discuss what can be automated and what we'd need to estimate the cost. Karl & Bart