Healthcare · Voice AI
Voice-first incident reporting for a healthcare network
Clinicians speak; the system captures, structures, and files a compliant incident report — turning a 40-minute form into a 4-minute conversation.
The challenge
Incident reporting is mandatory — and universally dreaded. Nurses faced a 14-screen form at the end of an already long shift, so minor incidents went unreported, serious ones were filed late with thin detail, and the patient-safety team was working from an incomplete picture of what was happening on their floors.
What we built
A voice-first reporting workflow that meets clinicians where they are — on their feet, between patients:
- Hands-free capture — clinicians describe the incident in their own words from any workstation or shared device.
- AI structuring — speech is transcribed and mapped onto the network's incident taxonomy; the system asks targeted follow-up questions only for missing required fields.
- Compliance built in — reports are generated in the format regulators and insurers require, with an auditable trail; PHI handling reviewed with the client's compliance office from week one.
- Safety analytics — a dashboard for the patient-safety team surfacing trends by unit, shift, and incident type.
The outcome
Reporting stopped being an end-of-shift chore. Volume went up — not because incidents increased, but because near-misses finally got captured — and the safety team now sees patterns weeks earlier. The network's own IT group runs the system and rolled out facilities four through six without us.