True AI, securely and compliantly,
running in your own cloud.

Retrieval-tuned AI over the record with citations per claim, role-scoped tools, and refusals that name their rule — on the foundation model you bring.

Every pending claim scored before submission, from your own adjudication history — each factor cited to real counts.

Criteria checked against the chart, evidence gathered, and the appeal drafted — into the signature queue, never past it.

Two-directional review: findings the record supports but the codes miss, and billed codes the documentation does not support.

Every release checked against the requesting jurisdiction's requirements; hard failures block with the requirement named.

The records the law guards most closely — addiction treatment, mental health, HIV, reproductive and genetic care — are flagged as they arrive, and anything uncertain waits for a person.

Any model, any kind: registered, enabled and activated into capability slots through one audited control panel.

Live performance metrics, population-stability drift recognition, and alerts that never close themselves.

Fifteen vendors, bulk and streaming, in and out — each vendor's real seams honored and refusals recorded.

Cohorts, quality measures, no-show risk, trial pre-screening — on a plane that returns counts, never patient lists.

Record a visit from the browser — behind a state-law consent gate — and the capture lands in the Data Store, on the chart, audited.

A genuine vision inference over the pixels: technique, findings, measurements from the acquisition scale — drafted to the queue.

Plain-language instructions written from the chart — then a second model pass fails the draft on a single invented assertion.

A transparent risk score — every factor and its points printed — and an AI call script per patient, staged for a human to dial.

Protocols screened against the whole corpus in SQL; the model reads the charts as a recall-biased second reader that never rules out.

Real numerators over real denominators, computed from the corpus on page load — arithmetic in the open, counts never lists.

The claims model examined across sex, age and payer subgroups — calibration gaps, printed thresholds, an AI reading of the results.

Integrity rules sweep every record in the store; the model argues root causes and fix order — it never quarantines anything itself.

AI output is a draft until a licensed person signs it. Only the signed artifact acquires a write path to the EMR.

The hash chain is re-verified on screen, in front of you — including the refusals, which is the point.