Praxess

Prior authorization delays care because the evidence needed for approval is scattered across the clinical conversation, note, FHIR record, payer policy, patient, and outside providers. Key facts get lost between what the patient says and what enters the chart. Teams discover those gaps after submission, when the payer requests more information or denies the case. Praxess is a world-model prototype for prior authorization. It maintains a living case state from the moment the patient enters the room, with source provenance attached to each claim. Claude structures evidence from the transcript and separates doctor and patient turns. Praxess then verifies quoted spans against their source before adding them to the case state. It tracks the difference between clinician-documented, conversation-enriched, patient-reported, verified, and unknown information. The decision engine rolls candidate actions forward and scores them using expected approval lift, information gain, time cost, and staff burden. A person approves consequential actions. Each new observation updates the state and changes the recommendation. Praxess records reviewed state-action transitions, creating the foundation for learned dynamics as authorization outcomes accumulate. The demo follows one authorization from encounter capture through evidence recovery, patient outreach, external record retrieval, packet generation, submission, denial, and appeal. If you want to check it out yourself, here's the link: https://praxess-production.up.railway.app/