Healthcare adds patient safety risk on top of standard data protection obligations — a security or governance failure here isn't just a HIPAA violation, it can directly affect a clinical decision. That changes what "acceptable risk" actually means compared to most other industries deploying AI.
Protected health information now moves through systems that were never designed with PHI in mind — prompts, RAG retrieval pipelines, and agent tool calls all create exposure paths HIPAA's original technical safeguards didn't anticipate. On top of that, clinical decision support systems carry FDA Software as a Medical Device obligations and adversarial-input risk that has direct patient safety consequences, and any healthcare RAG deployment depends on de-identification that has to actually survive contact with a probabilistic model rather than just looking sufficient on paper.
How PHI actually moves through LLM prompts, RAG pipelines, and agent tool calls — and the technical safeguards that keep that movement HIPAA-compliant rather than just assumed to be.
Read the full guide →FDA SaMD requirements, adversarial input resistance, and the patient safety considerations that make clinical decision support AI fundamentally higher-stakes than most enterprise AI deployments.
Read the full guide →De-identification, consent management, and secure RAG architecture specifically for clinical knowledge bases — where the data governance failure modes look different from generic enterprise RAG.
Read the full guide →The HexTyx AI Security Assessment covers PHI exposure paths, retrieval security, and compliance readiness in one scored report.