A HIPAA-aware privacy and governance layer for clinical AI workflows, designed to prohibit LLM exposure to patient-identifying data while keeping AI useful, auditable, and policy-aware.
Why clinical AI needs PHI exposure prevention built in from the start.
Healthcare organizations want to leverage generative AI platforms like OpenAI, AWS Bedrock, and Google Gemini to analyze complex clinical notes, extract insights, and assist doctors.
But PHI exposure risk makes ordinary AI workflows difficult to approve, govern, and trust in real clinical settings.
The Warden creates a PHI-safe AI boundary, helping teams use clinical intelligence while prohibiting patient-identifying data from reaching the model.
It also adds AI request guardrails, policy enforcement, and audit-ready governance, so clinical users can receive useful answers without exposing PHI to the model.
How the Warden turns clinical AI into a secure, HIPAA-aware workflow.
Patient-identifying information is prohibited from model exposure while the workflow preserves enough clinical context for useful reasoning.
AI requests are screened against safety policies to reduce prompt injection risk, block unauthorized data access, and keep clinical workflows within approved boundaries.
AI decisions and governance events are captured in a PHI-conscious audit trail, giving teams visibility without turning logs into a liability.
Security controls aligned with NIST and HIPAA priorities.
Map, Measure, Manage: The Warden helps teams identify AI risks, apply request-level guardrails, and support governance reviews with evidence.
Audit & Access Controls: Supports auditability and least-privilege design by tracking governance decisions while minimizing sensitive data exposure in logs.
Technical Safeguards: Designed around HIPAA Security Rule safeguards (§164.312), including controls that prohibit PHI from being read by the LLM.