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Ambient AI scribe

Ambient AI scribe

Word-level audio-span citations on every scribed section. Find it inside any open encounter.

How it works

  1. getUserMedia()MediaRecorder (16 kHz WAV) records the visit.
  2. Audio sent to the tenant’s STT provider (task=scribe) with verbose_json — returns full transcript plus word-level timestamps (start_ms, end_ms) per word.
  3. SOAP draft generated with character-span citations into the transcript — each SOAP section carries the byte range that evidences it.
  4. Click “Apply to encounter” → posts as a FHIR Composition with section.extension carrying (transcript_id, span).

Hover-to-evidence

Hover any SOAP section in the encounter detail → the supporting words highlight in the transcript pane. Click → audio playback jumps to that span. This is what makes the scribe defensible — every claim is provably derived from a specific moment in the visit.

Privacy

  • Audio is streamed to the STT provider over TLS; the raw WAV file is stored only if the tenant has scribe.retain_audio = true in settings.
  • Transcripts persist as DocumentReference resources tied to the Encounter.
  • Citations are portable FHIR primitives — any downstream consumer reading the Composition sees the same evidence chain Pollen8 does.

Continuous medication reconciliation

The scribe also pushes proposed med deltas (add / discontinue / change_dose) to the Med Reconciliation surface as the visit progresses. Provider reviews + accepts before sign-off.

Provider workflow

The scribe runs in the background. No “click to start” — opens with the encounter. Provider talks to the patient, glances at the transcript pane at sign-off, accepts the SOAP, codes flow into the encounter via the code suggester.