RAAPID Featured In a KLAS Emerging Company Spotlight Report for Defensible Coding & Audit-Ready Retrospective Risk Adjustment

RAAPID's AI-powered risk adjustment solution received an A+ would-buy-again grade (Emerging Data, n=5) from interviewed customers in the May 2026 KLAS Emerging Company Spotlight, citing AI accuracy and audit defense as standout strengths.

LOUISVILLE, Ky.--(BUSINESS WIRE)--​RAAPID, INC., a leading Neuro-Symbolic AI-powered risk adjustment platform for payers and at-risk providers, today announced that it has been featured in the May 2026 KLAS Emerging Company Spotlight on Retrospective Risk Adjustment. The report reflects interviews with RAAPID customers and highlights the platform's audit defensibility, AI accuracy, and partnership quality.

The report, Enhancing Risk Adjustment Coding Defensibility Through Neuro-Symbolic AI Solutions, is based on interviews with RAAPID customers, including health plans and a provider-sponsored payer.

Key findings:

• AI-driven platform delivers strong accuracy, efficiency, and workflow improvements.
• Improved coding accuracy, chart-review efficiency, and streamlined coding workflows.
• Excellent partnership with real human connection and involved support staff.
• RAAPID listens, adapts, and implements customer feedback.

“The Neuro-Symbolic AI is very accurate. We did a second-level review on some of the documents that our NLP also picked up, and we found additional opportunities. The general feedback from our coders was that RAAPID’s tool handled inpatient records really well compared to our primary tool. There are thousands of pages in those records, and the tool had to review all of those, but it was able to accurately pinpoint the evidence a high percentage of the time, reducing the amount of work needed. The overall platform, including some of the project management aspects, is very well laid out.” —VP, other executive

"Defensibility has been the foundation of RAAPID's risk adjustment platform from day one, not a feature we added when the regulatory pressure arrived. We built our entire solution around it: Neuro-Symbolic AI that links every code to verbatim clinical evidence, explains every recommendation, and produces documentation that holds up under RADV review. When KLAS interviewed customers, they gave an A+ would-buy-again grade (Emerging Data, n=5), which is confirmation that we've built what risk adjustment leaders actually need," said Chetan Parikh, Founder and CEO of RAAPID.

"Risk adjustment organizations are under increasing pressure to improve accuracy, efficiency, and audit defensibility, and RAAPID’s customers highlighted meaningful performance in each of those areas. An A+ would-buy-again grade (Emerging Data, n=5) reflects a high level of customer confidence and suggests that RAAPID is helping organizations address some of the most pressing challenges in retrospective risk adjustment.”— Mac Boyter, VP of Engagement, KLAS Research".

Request a full KLAS spotlight report.

ABOUT RAAPID INC

RAAPID is the AI-native risk adjustment platform purpose-built for Medicare Advantage, ACA, and at-risk provider organizations. Powered by proprietary Neuro-Symbolic AI, RAAPID delivers 92% AI accuracy, 5x coder productivity, and 3–10x ROI across retrospective chart review, prospective gap closure, and RADV audit workflows, with full "Glass Box" defensibility. Recognized by Modern Healthcare as a 2025 Best in Business Healthcare IT honoree, RAAPID is HITRUST r2-certified, SOC 2-compliant, and deployed on Microsoft Azure. Backed by M12 (Microsoft's Venture Fund), UPMC Enterprises, and Healthworx. Learn more at raapidinc.com

ABOUT KLAS

KLAS is a research and insights firm on a global mission to improve healthcare. Working with thousands of healthcare professionals and clinicians, KLAS gathers data and insights on software and services to deliver timely reports and performance data that represent provider and payer voices and act as catalysts for improving vendor performance. The KLAS research team publishes reports covering the most pressing questions facing healthcare technology today, including emerging technology insights, that provide early insights on the future of healthcare technology solutions. KLAS also fosters measurement and collaboration between healthcare providers and payers and best practice adoption.