CombineHealth is a self-learning autonomous medical coding platform that analyzes the full clinical encounter, applies coding guidelines and payer-specific rules, and generates explainable, billing-ready medical codes. Also referred to as Amy AI, the platform uses large language models to read completed encounter documentation directly from the EMR and produce professional and facility codes—ICD-10-CM, CPT, HCPCS Level II, E/M levels, modifiers, and provider attribution—each with a traceable rationale.

Unlike coding tools that stop at code assignment, CombineHealth learns payer behavior from claim outcomes—denials, reimbursements, and underpayments—and adapts its coding strategy per payer. The result is a measurably lower denial rate, not just accurate codes.

Key Features

Autonomous coding at scale — Handles both routine and complex scenarios, delivering automation rates of up to 85% while maintaining coding accuracy exceeding 98% at large scale.
Payer intelligence — Learns payer-specific coding behavior, requirements, and patterns from real claim outcomes and uses it to inform future coding decisions.
Explainable coding decisions — Every code carries a traceable audit trail linked to the source documentation, so coders, auditors, and compliance teams can validate exactly why each code was assigned. No black-box outputs.
Denial reduction — Continuously evaluates coding decisions against downstream outcomes; proven to drive up to a 75% reduction in coding-related denials.
Works inside existing workflows — Operates within existing EHR, PMS, and RCM systems without introducing a separate coding environment.
Documentation gap detection — Surfaces missing or insufficient documentation that could alter coding or reimbursement, with provider-level insights.