Autonomous RADV Audit Readiness
with AI-Native Chart Abstraction
RADV AI autonomously validates every chart for HCC accuracy bringing speed
and confidence to RADV audit submissions
PROBLEM
Risks for
RADV Audit Cycle
- Which submitted HCCs have no clinical evidence behind them?
- Which charts are best evidences for RADV audit submission?
- How much time and effort is required for RADV audit prep & submission?
- Which HCC coding discrepancies will cause RADV audit failure and penalties?
CORE CAPABILITIES — Review Every Chart, in under 5 minutes
Autonomous HCC Checks with Confidence and Precision
RADV AI autonomously completes chart abstraction, performs encounter-level HCC validation, and maps the HCCs, bringing speed to RADV audit preparedness
Autonomous Diagnostic Extraction
Encounter-Level HCC Validation
RADV AI validates each HCC against encounter-level clinical evidence and ranks the strength of that support
Validates and ranks all the charts with confidence
CMS and HHS HCC Mapping
RADV-Ready Reporting
Speed to Audit-Readiness
without Adding Additional Resources
Measurable risk adjustment performance through autonomous chart review, medical LLM reasoning,
and full audit traceability on every submitted HCC
100%
HCC validation with clinical
evidence ranking
100%
HCCs with traceable
audit trails
5x-7x
Increase in chart
review productivity
90%
Reduction in manual
chart review time
*Results may vary by organization and documentation quality
RADV AI is a Smart Risk Adjustment Data Validation Tool that Saves Time & Resources
Manual and NLP workflows take 30–60 minutes per chart and depend on large auditing teams, leaving plans to meet RADV timelines by adding additional headcount and vendors.
RADV AI reviews every record in under 5 minutes, returning ranked clinical evidence for each HCC before submission, saving precious time and resources bring speed to audits with accuracy.
100%
HCC Validation
Evidence-Ranked
Findings
Full CMS and HHS
HCC Mapping
Complete Audit
Trail for Compliance
Built in Smart Encoder
with HCC mapping
Scalable Across
Provider Networks
KEY FEATURE
Complete Clinical Validation Across
Every Layer of the Submission
RADV AI does more than extract codes. It gives risk adjustment, coding, and compliance teams evidence-backed intelligence on every record, letting them manage RADV audit with confidence
Smart Chart
Intake Management
RADV AI smartly manages chart chases, tracking collection, mapping members accurately and routing every retrieved record directly into extraction and validation
Chases created and charts collected before review begins
Autonomous
Diagnostic Extraction
Clinical LLM powered workflow maps handwritten, typed, and mixed-format charts, with context mapping across structured and unstructured documentation, bringing first-level review results to the HCC auditors
Clinically relevant diagnoses pulled from unstructured records
Encounter-Level
HCC Validation
Each HCC is validated at the encounter level against CMS and HHS RADV guidelines, with MEAT criteria applied for chronic diagnosis and every finding presented alongside its clinical evidence
Every HCC is checked against the documentation
Readmissions
Reporting
LEADERSHIP DASHBOARD
For Leaders Who
Need Answers,
Not More Reports
The CAiRE+ leadership dashboard surfaces the metrics that matter most at a glance, in real time — so leaders can answer ‘what’s in it for me’ immediately.
- Real-time insights
- Actionable intelligence
- Better decisions, better outcomes
RADV-Ready
Reporting & Audit Trails
Compliance reports aligned with CMS and HHS RADV guidelines, plus a full audit trail for each extracted diagnosis HCC code, exportable in RADV-ready formats
A traceable record behind every code submitted
Provider Scorecards & Human-in-the-Loop
Review
HIPAA and PHI protections, end-to-end encryption, role-based access, MFA, and detailed audit logs on zero-trust networking. Review interfaces, QA workflow, and a user feedback loop keep auditors in control
Auditor oversight on a zero-trust foundation
Interoperability and
Real-Time Data Access
SMART on FHIR, HL7 API services carry real-time EMR data for AI-powered clinical assessment while BigQuery and Firestore power metadata with intelligent AI analytics
Connected to what you already run
Download the RADV 
Whitepaper
Request the whitepaper to review RADV AI capabilities in detail and circulate it across your risk adjustment, coding, and compliance teams.
Question & Answers
Frequently Asked Questions
RADV AI ingests PDFs, scanned images, faxes, EHR exports, and HL7/FHIR feeds, and returns RADV-ready reports, ICD-10-CM HCC code sets, dashboards, provider scorecards, and CMS exports, enhancing your risk adjustment compliance program.
Yes. RADV AI is built on a secure Google Cloud Platform with HIPAA-ready enterprise security, including identity and access management (IAM), network isolation (VPC Service Controls), data loss prevention (DLP), and encryption key management (KMS) — with SOC-2 and HITRUST support.
RADV AI processes every medical record via proprietary clinical AI for HCC abstraction. Each chart goes through diagnostic extraction, encounter-level HCC validation, and HCC mapping. A workflow audit trail generated
Plans using RADV AI validate 100% of HCCs with clinical evidence ranking, complete chart reviews in under 5–10 minutes instead of 30–60 minutes spent on each record; this increasing reviewers productivity by 5x–7x, and reduces manual chart review time by up to 90 —all without adding headcount.
RADV AI handles first-pass extraction and validation autonomously, letting HCC auditors and compliance staff focus on findings that require clinical judgment, rather than the manual chart searches and time consuming abstraction on excel sheets.
RADV AI is deployed rapidly and scales across large audit volumes without disrupting existing workflows.
Perform your RADV audits with confidence
Enhance your RADV Compliance program. Protect Revenue. Reduce RADV error exposure
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