Manual chart coding was slow and costly, limited to a few dozen charts per coder per day, and quality depended on individual judgment.
The team needed AI assistance but required full auditability, because coders and auditors must see why each code was assigned. Generic LLM tools were unsuitable since an unexplained code is unbillable and unauditable.
Tensile built a role-based coder workspace plus an autonomous coding pipeline for a US healthcare revenue-cycle operation. It runs OCR, clinical NLP entity extraction, and UMLS/SNOMED-backed ICD-10/CPT mapping through an LLM coder with hallucination detection and an independent reviewer model, with human accept-edit gates and full audit logging.
Each suggested code links back to the exact source chart text with confidence scoring, keeping outputs billable and auditable.
Pre-validation, coding, and an independent reviewer model, with human accept/edit gates, guard against hallucinated codes.
The coder workspace and autonomous pipeline reached POC, live with a launch design partner.
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