Autonomous AI agents
that do the coding work.

Reads the clinical note the way a senior coder would and proposes complete, guideline-level coding — including the status codes the medication list supports — while leaving out anything uncertain, incidental, or assumed. It never sees patient identifiers.

Checks every code the AI proposes against the official reference before a coder ever sees it. A code that doesn't exist is discarded; the description, billable status, HCC category and risk weight are corrected to the official values.

Re-checks the whole code set every time it changes: the code exists for that year, it is billable, it doesn't conflict with another code on the chart, it fits the patient's age and sex, it is sequenced correctly, and it satisfies your organisation's own coding policies. It decides what blocks and what warns, and it controls the Submit button.

Looks for coded diagnoses the chart's own measurements disprove — a BMI that doesn't support a morbid-obesity code, a kidney-function result that doesn't match the coded stage — and points to the exact reading in the note. It is deliberately conservative: it flags only when every reading disagrees, and it respects the clinical exceptions.

For every risk-adjusting diagnosis, finds the evidence that it was Monitored, Evaluated, Assessed and Treated — the actual sentence in the note, the result, or the medication — and cites it. The audit package writes itself as the coder works.

Keeps watching approved charts. Whenever new evidence arrives or a coding policy changes, it re-checks them and queues the codes that should come off, ranked by what is at stake, with the same evidence that would have caught them the first time. Every decision — keep, query, or retract — goes into a permanent ledger.