Scroll through the operator-controlled workflow: intake readiness, policy research, evidence review, risk scoring, binder assembly, and the learning loop that improves future reviews.
The operator enters or imports the case, chooses the payer, attaches evidence, and confirms the PHI posture. The app stays quiet until the run is explicitly launched, then records a clean audit trail from the first event.
Browser agents launch per selected payer after the run starts. The UI can show live progress, captured source targets, and structured policy findings while failed payer lookups are isolated from the rest of the case.
The evidence layer extracts medical-necessity themes, documentation gaps, and payer-specific requirements. Local public-policy references can answer common coverage questions before a live research step is needed.
A governed analytics layer scores denial risk and evidence gaps while the app keeps a clean case timeline for operator review. The public workflow shows outcomes and confidence, not internal infrastructure details.
The app assembles the evidence binder, appeal draft, submission checklist, and source manifest for a human reviewer. Nothing is auto-submitted; the hospital operator controls every outbound step.
After the payer responds, outcomes can feed aggregate rules and training examples for future cases. The loop is designed for governance: no raw PHI in public demos, no automatic clinical decisioning, and no outbound submission without review.
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