Autonomous RADV Audit Readiness with
AI-Powered Diagnostic Extraction

Complete CMS RADV audit submissions with AI-powered HCC coding extraction with confidence and precision

Autonomous RADV Audit Readiness

AI Precision for RADV Audits.

Remove uncertainty from RADV audits with autonomous diagnostic extraction, clinical validation, and CMS-ready submissions at scale.

Increase in Productivity
0 x
Reduction in Manual Chart Reviews
0 %
CMS-Ready Audit Trails
0 %

BENEFITS

Transform Audit Process
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Ease the heavy lift of RADV audits with smartness of AI

  • Heavy manual chart reviews done swiftly.​
  • Context mapping of structured and unstructured medical records
  • HCC Code evidences mapped with precision
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End-to-end chart reviews to RADV-ready submissions

  • Ingests PDFs, scans, faxes, and EHR exports at scale.​
  • Uses advanced clinical-AI to extract diagnoses and map to CMS-HCC.​
  • Generates RADV-ready reports with full audit trails.​

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    Key features

    RADV Powered by Clinical AI

    Autonomous diagnostic extraction from unstructured charts.​​

    Autonomous diagnostic extraction from unstructured charts.​

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    Less time on charts.
    Less risk in audits.

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    Enterprise-grade security for PHI.

    Enterprise-grade security for PHI.​

    Why RADV AI makes sense?

    Purpose-built for RADV audits and HCC coding

    Deep clinical AI and risk adjustment expertise in one platform

    Proven impact on manual effort, accuracy, and penalty reduction

    Question & Answers​

    Frequently Asked Questions

    Explore this section to learn more about our products.

    It automates HCC coding and RADV audit preparation by extracting diagnoses from unstructured records and generating CMS-ready reports with full audit trails.​

    PDFs, scanned images, faxes, EHR exports, and HL7/FHIR feeds can all be ingested and processed.​

    Yes, human-in-the-loop workflows enable QA review and overrides where needed.

    Yes, the platform is designed for HIPAA environments and supports SOC-2, HITRUST, and CMS compliance frameworks.

    By validating every HCC against encounter-level clinical evidence before CMS submission.

    RADV AI is deployed rapidly and scales across large audit volumes without disrupting existing workflows.

    Experience RADV AI firsthand.

    See how autonomous HCC coding can transform your next RADV audit cycle.​
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