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TOPIC CLUSTER · 4 POSTS

AI & Healthcare Compliance

Architecture, BAA mechanics, and guardrails for shipping AI features in regulated healthcare contexts — chatbots, ambient scribes, code-review automation.

Healthcare teams are shipping AI right now — patient intake, clinical scribes, claims summarization, triage chatbots, automated compliance scoring. The teams getting it right treat HIPAA as an architectural decision they make on day one. The teams getting it wrong paste a clinical note into ChatGPT and call it a feature. This cluster is for the first group.

The architecture for HIPAA-safe AI is not about which model you pick — it's about which BAA-eligible endpoint you call, where PHI sits before and after that call, how your audit log captures the AI hop, and what happens when the model hallucinates. Every guide here treats the AI feature as a HIPAA application in full: the same encryption obligations, the same access controls, the same six-year audit trail. There is no "AI exception" in 45 CFR Parts 160-164.

The cluster also tracks the BAA landscape — which AI vendors will sign one (OpenAI, Anthropic, Google, AWS Bedrock all do, with caveats), which configurations are required for the BAA to be in force, and where the contracts have gotten teams in trouble. Start with the pillar guide for the architecture overview, or jump to your specific build (scribe, intake bot, code-review automation).


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