The problem
Clinicians spend evenings writing notes and staff spend days chasing prior authorizations — pure administrative drag with measurable burnout and revenue costs, and now the best-documented AI wins in healthcare operations.
The system
Two pipelines, deployable independently: ambient documentation that drafts clinical notes from consented visit audio for clinician review (never auto-signed), and prior-auth automation that gathers required clinical data, validates payer criteria, and submits — with staff reviewing exceptions and denials. Both consent-gated, both eval-audited, both designed around the rule that a human signs everything that matters.
How it's built
- Consent-gated ambient capture; drafts always reviewed and signed by the clinician
- Specialty-tuned note templates with citation back to the transcript
- Prior-auth data gathering + payer-criteria validation + submission automation
- Accuracy and turnaround audited continuously; PHI handling designed in from day one
Delivery
Sprint pilots with a small clinician group or one authorization type; Build scales by specialty with measured accuracy gates.
What to expect
- Documentation hours returned to clinicians, measured per specialty
- Authorization turnaround cut from days toward hours
- Denial and write-off rates tracked against the pre-automation baseline
Documented results in the wild
Independent, published deployments of this class of system — cited as market evidence that it works at scale. These are not our clients.
- Kaiser Permanente (TPMG) Ambient AI scribes across 2.57M encounters saved 15,791 documentation hours; 82% of physicians reported improved work satisfaction. American Medical Association, 2025 ↗
- CHRISTUS Health GenAI documentation cut after-hours charting 60% and physician burnout 40%. Abridge / CHRISTUS, 2024 ↗
- Care New England Prior-auth automation cut authorization turnaround 80% and authorization-related write-offs 55%, saving 2,841 staff hours. Notable Health case study, 2025 ↗