Healthcare AI Trust
AI Trust for clinical safety, PHI handling, and HIPAA-AI obligations.
Built for healthcare AI risk
Healthcare AI sits across a brutal compliance perimeter — HIPAA, FDA AI/ML SaMD, EU AI Act high-risk classification, state-level AI bias laws, and the clinical-safety bar. Infrarails combines a platform that scores every AI interaction for clinical safety + PHI + bias with consulting that gets you audit-ready against the actual frameworks your auditors will ask about.
- Every AI interaction scored against healthcare-specific failure modes, not generic safety checks
- Mapped directly to the regulations your auditors cite — HIPAA and FDA AI/ML SaMD, among others
- Signed, replayable evidence built for the exact review your regulator or carrier will run
PHI leakage via prompts or outputs
Patient identifiers slipping into prompts, RAG context, or LLM outputs — directly material under HIPAA Security Rule + Privacy Rule.
Clinical advice hallucinations
AI surfaces confident but wrong dosing / diagnosis suggestions. Reputational + liability exposure if shipped without guardrails.
Bias against protected populations
Triage models, hiring models, and benefit-eligibility models that systematically disadvantage protected groups. EEOC + state-level regulatory exposure.
Off-label or unapproved use surfaces
AI suggesting therapies outside indications. FDA SaMD scope and product-liability exposure.
How healthcare teams run Infrarails
One policy, scoped to your healthcare obligations — evaluated on every AI interaction, not just at audit time.
curl -X POST https://api.infrarails.ai/v1/evaluate \
-H "Authorization: Bearer YOUR_KEY" \
-d '{"policy": "healthcare_compliance", "prompt": "...", "response": "..."}'Guard
Real-time PHI redaction + clinical-safety filters on every LLM call
Evaluate
Score every AI interaction across safety + bias + privacy pillars
Govern
HIPAA + FDA + EU AI Act mapping, policy library, signed evidence
Documents
Clinical-protocol + policy-document handling with HITL review
Regulatory Mapping
Every AI system in your healthcare estate mapped against the frameworks your regulators actually cite — kept current as the rules change.
Audit-Ready Evidence
Every evaluation produces a signed, tamper-evident record — the artifact your auditors, examiners, or carrier will ask to see.
HIPAAFDA AI/ML SaMDEU AI ActState AI bias laws21 CFR Part 11
What a typical healthcare engagement looks like
Anonymised profile drawn from sector patterns — not a specific client.
Profile
Mid-size US health system deploying LLM-based clinical decision support across multiple service lines
Drivers
- Imminent HIPAA audit + state regulator inquiry into AI use
- FDA pre-submission strategy for a digital health product
- Patient + advocacy-group pressure on AI transparency
Bundle
AI Readiness Assessment (4 weeks) → Regulatory Readiness Program against HIPAA-AI + FDA SaMD (5 months) → AI Red Team Engagement on clinical-decision-support endpoint (6 weeks)
Outcome
Audit-ready HIPAA-AI evidence pipeline, FDA pre-submission package, and a clinical-decision-support endpoint with documented PHI handling + clinical-safety guardrails in production.
Talk to the Healthcare practice
60-90 minute scoping call, routed to the healthcare practice lead. Free.