Privacy and audit readiness for healthcare RAG.
Detect sensitive data exposure and unsupported healthcare claims before RAG responses reach users, reviewers, or downstream systems.
Example Privacy Finding
A response repeats sensitive identifiers from context.
Detected patterns
Email-like identifier, medical-record-style token, and diagnosis-code-like reference.
Safer output
Sensitive fragments are masked and the audit record captures what was detected.
Healthcare AI needs privacy evidence, not just good answers.
PHI-like leakage
Context can contain identifiers that are repeated in generated answers.
Unsupported claims
Clinical, insurance, or operational claims need traceable support from approved context.
Review gaps
Teams need records that show what was checked, why it was flagged, and what happened next.
What HardRAG checks in healthcare scenarios.
HardRAG combines deterministic pattern checks with model-based review so teams can inspect privacy and grounding risks together.
Important compliance note
HardRAG helps healthcare teams review privacy, grounding, and audit evidence. It does not make a healthcare system legally compliant by itself. Final compliance depends on your deployment, policies, data handling, legal review, and organizational controls.
Review healthcare RAG privacy risk before rollout.
Start with a focused privacy and audit-readiness assessment using simulated or approved test data.