AI Medical Scribe & Clinical Documentation Agent

An AI Clinical Documentation Agent generates, quality-reviews, and submits clinical documentation while keeping physician accountability intact. Ambient intelligence captures the encounter, checks the note for CDI gaps, and auto-generates discharge summaries and prior auth documents. Physicians review and sign in 5 to 10 minutes instead of 30 to 90.

One tap activates ambient capture — the physician consults normally, no dictation required. Clinical NLP identifies symptoms, findings, diagnoses, and the care plan in real time, then assembles a structured SOAP note waiting in the EHR to edit and sign. Post-encounter documentation drops to 3–8 minutes from 20–45.

Peer-reviewed studies show strong accuracy: DAX matched or beat physician-written notes in 76% of cases, and Abridge's UPMC deployment captured 95%+ of key clinical facts. Physician-in-the-loop review covers any gaps, and the model fine-tunes on your organisation's documentation patterns over time.

Certified integrations for Epic (App Orchard, SMART on FHIR R4), Oracle Cerner, Meditech Expanse, athenahealth, and Allscripts/Veradigm. The agent reads patient context via authenticated FHIR API and writes signed notes back to the chart as the official medical record.

CDI analysis runs before the physician signs, flagging unspecified ICD-10 codes, CC/MCC implied by labs or treatment but not documented, unrecorded secondary diagnoses, and HEDIS/CMS Star Rating gaps. Each opportunity surfaces as an ACDIS-compliant query with supporting clinical evidence attached.

Encounter audio is AES-256 encrypted and not retained beyond the configured period. Notes are delivered via authenticated HL7 FHIR API and not stored in Bonami infrastructure after the session, all PHI access is logged to an immutable audit trail, and model improvement uses de-identified data only. A BAA is executed before every deployment.

Yes. The HCC capture module compares current documentation against the patient's historical HCC code set and flags chronic conditions missing from the note. Organisations deploying AI HCC capture see 8–15% improvement in risk score capture — $200–$600 per member per year in additional capitated revenue.

ROI lands across capacity recovery (50–72% less documentation saves 40,000–60,000 physician-hours a year per 200 physicians), a 2% attrition drop ($2M–$4M in avoided replacement costs), CDI uplift (3% CMI improvement = $4M–$8M at a 15,000-admission hospital), and denial reduction ($500K–$2M annually). Most organisations recover implementation cost within the first quarter.

Traditional medical scribe software relies on dictation commands or a human scribe transcribing the visit. Ambient clinical documentation listens to the natural physician-patient conversation and drafts the note automatically. Bonami's ai medical scribe identifies symptoms, findings, diagnoses, and the care plan in real time, assembling a structured SOAP note the physician signs in 5 to 10 minutes.

Bonami's ai medical scribe works as clinical documentation software inside the EHR workflows physicians already use. The ai clinical documentation engine reads patient context through authenticated HL7 FHIR APIs and writes the signed note back to Epic, Oracle Cerner, Meditech, athenahealth, and Allscripts as the official record. The physician retains full clinical and legal accountability for every note.