Demos
Martlet.ai, a healthcare AI company spun out of John Snow Labs, today announced the launch of its Risk Adjustment Data Validation (RADV) Audit Readiness Platform, a new solution that helps Medicare Advantage Organizations and healthcare payers prepare for CMS’s expanded Risk Adjustment Data Validation audits in 2025.
Built on proprietary healthcare-specific natural language processing (NLP) and large language models (LLMs), the RADV platform automates chart review, evidence validation, and Hierarchical Condition Category (HCC) coding reconciliation, enabling payers to identify, document, and defend risk-adjusted conditions with unprecedented accuracy.
“RADV audits are no longer retrospective events, but a year-round operational priority,” said Ritwik Jain, Co-Founder and CRO, Martlet.ai. “With CMS expanding its audit scope and applying extrapolation across populations, health plans need proactive systems that ensure data integrity, clinical defensibility, and compliance at scale, and our platform delivers exactly that.”
The Martlet.ai RADV Audit Readiness Platform integrates directly into clients’ environments and workflows, ensuring full HIPAA compliance and data governance. By combining chart-level NLP insights with evidence-based scoring, the system produces auditable summaries for each HCC, highlighting potential gaps before CMS auditors do.
“We designed this platform to mirror the precision and transparency auditors expect, but with the speed and scalability only AI can provide,” said Hasham Ul Haq, Co-Founder and CTO, Martlet.ai. “Because it runs entirely within the client’s environment, our solution can be fine-tuned to their documentation style, data structure, and population health profile, enhancing accuracy without sacrificing security.”
The launch of the RADV Audit Readiness Platform follows a broader mission to modernize risk adjustment, coding, and help payers and providers bring these capabilities in-house. The company’s modular HCC Engine, also built on proprietary healthcare-trained LLMs and NLP models, powers suspecting, retrospective coding, and now audit readiness in one unified framework.
Key capabilities of the RADV Audit Readiness Platform include:
- Automated evidence validation: AI models are trained on clinical indicators to detect missing or non-defensible documentation.
- Audit scoring and benchmarking: Generate audit-readiness reports mapped to CMS criteria and cohort-level benchmarks.
- Customer controlled deployment: Run as a container within the client’s secure environment (AWS, Azure, or on-prem) for compliance.
- Configurable workflows: Adaptable to payer-specific coding policies and audit methodologies.
“The RADV Audit Readiness platform delivers tangible, risk-avoidance results for its customers,” said David Talby, CEO, John Snow Labs. With automated evidence validation and chart review, users can reduce the risk of costly CMS recoupments, enforce high coding integrity, and scale audit readiness across enterprise workflows. In today’s environment, that translates directly into protecting margins, minimizing disruption, and strengthening payer confidence in their data.”
For more information about the RADV Audit Readiness Platform, visit www.martlet.ai or contact info@martlet.ai.
About Martlet.ai
Martlet.ai is an AI platform created to automate Hierarchical Condition Category (HCC) coding and streamline risk-adjustment workflows for high-compliance environments. Medicare Advantage and Medicaid MCOs, commercial insurers, ACOs, provider organizations, and revenue-cycle management (RCM) firms trust Martlet.ai for its secure, on-premise coding engine, ensuring accuracy, auditability, and transparency at every step. Made possible with domain-specific LLMs, Martlet.ai optimizes reimbursement while maintaining regulatory alignment.
