Regulatory Feasibility Audit — AI Voice Agent

What was broken

The client wanted an autonomous AI voice agent to place outbound calls to physician practices, navigate front-desk gatekeepers, qualify interest, and book doctors onto a specialist's calendar — every call logged to a CRM. On the surface, a standard voice-agent build. Underneath, one of the most heavily regulated sales contexts in the country: federal robocall law (TCPA), state AI-disclosure statutes (FL HB 919, CA AB 1018), FDA/FTC regulation of claims for non-FDA-approved biologics, two-party recording consent, and HIPAA boundaries — simultaneously. A single misconfigured assumption isn't a bug; it's per-call statutory liability of $500–$1,500 with no cap.

What we built

Instead of quoting the build and wiring telephony, Trenith ran a structured feasibility audit across every regulatory surface the system would touch: TCPA artificial-voice consent requirements, state AI-disclosure law, the product's federal regulatory status, advertising and claim risk, recording-consent rules, the HIPAA data boundary, and operating liability. The finding: technically feasible, but lawful only under a compliance-first architecture — AI identity, non-FDA-approved status, and recording consent disclosed in the opening seconds of every call; the agent restricted to qualification and booking with all medical and efficacy discussion routed to a licensed physician; build-and-handoff so operating liability stays where it legally belongs; and a capped, supervised pilot with qualified-counsel sign-off before live calling. The client elected not to proceed under those constraints — the engagement working exactly as intended.

AI & automation layer

The stack

Outcomes

What this proves

Trenith audits before it builds in regulated industries — and would rather stop a project than hand a client a liability with our name on it.