u/Away_Pirate_1186

Most “HIPAA-compliant” voice agent stacks stop at:
- “Our cloud signs a BAA”
- “Our STT/TTS/LLM vendors sign BAAs”
- “We encrypt in transit + at rest”

That’s necessary, but not sufficient once real PHI hits production agents.

I wrote up a short post on the gaps we keep seeing when teams assume “BAA = compliant” for AI voice agents (blog link in comments)

Quick summary of the problem areas:

- Fragmented audit trail across telephony, STT/TTS, LLM, tools, dashboards.
- LLMs treated as an unbounded PHI sink via prompts, tools, and memory.
- BAA coverage that breaks somewhere in the vendor/subprocessor chain.
- Behavioral leaks (what the agent *says* on calls) even when infra looks secure.

With Masker.dev, I’m treating PHI minimization as a first-class design constraint: sit between your voice platform and LLM, detect and redact PHI, swap in surrogates so the agent stays coherent, and keep an audit log of every redaction.

Curious how folks here are handling PHI minimization and auditability across multi-vendor voice stacks. Happy to jam in comments or DMs.

Trying to map where healthcare voice AI deployments actually stall.
What I think I’m seeing:
\- STT vendors (Deepgram, AssemblyAI, Speechmatics): BAA available, mostly fine.
\- TTS vendors (ElevenLabs, Cartesia, PlayHT) — BAA available.
\- LLM hop: OpenAI and Anthropic either won’t sign or scope BAA coverage narrowly enough that legal still flags.
\-Customers want PHI not to touch the LLM at all, regardless of what the BAA says.

For founders who’ve actually pushed a healthcare voice agent past procurement:

1. Where did the deal slow down- BAA negotiation, SOC 2 ask, or something further down (HITRUST, audit log review, VPC deployment)?
2. How are you handling the LLM hop today — Azure OpenAI for the BAA, on-prem model, redaction layer, or just hoping nobody asks?

Building in this space and the technical part is the easy part. Trying to understand the actual GTM wall before I run into it.

The problem: Your STT and TTS vendors sign a BAA. Then the transcript hits your LLM and PHI is in the clear.

What Masker does: Sits between your voice platform and your LLM. Redacts PHI on the way in, restores it on the way out with surrogate values so the LLM keeps coherent context. The caller hears a normal conversation. Your LLM never sees real identifiers. Every redaction is logged for audit.

How you use it: Change one field — the custom LLM URL in Vapi, Retell, or Bolna. Bring your own model (OpenAI, Anthropic, self-hosted).

Status:
• 9 of 18 HIPAA Safe Harbor identifiers at full coverage, 3 partial, 5 in progress
• 45–95ms added latency in streaming mode
• Production beta May 30

Product and demo link in comments.

Beta is hands-on — onboarding builders one at a time. If you’re shipping voice into healthcare, legal, or financial, drop a comment or DM.

Navi