AI HIPAA Compliance Monitoring Agent

How Cassidy automates this using AI

Step 1: Trigger on audit log events

The Workflow activates when new EHR access logs, authentication events, or DLP alerts arrive—whether via API, syslog, or FHIR event streams from your ePHI systems.

Step 2: Normalize and enrich event data

Cassidy standardizes log formats across EHRs and ancillary systems, then enriches each event with identity context from IAM/SSO, HR roster data, care relationship lookups, and shift schedules to establish baseline expectations.

Step 3: Apply UEBA and policy-based detection

The Workflow runs behavioral analytics to detect anomalies—VIP chart access, off-hours activity, bulk record pulls, or access outside treatment relationships—while layering deterministic rules for known privacy risks like coworker snooping or excessive privileges.

Step 4: Risk-score and prioritize alerts

Cassidy calculates a composite risk score combining anomaly severity, policy violations, and contextual factors, then routes high-priority cases to your Privacy Officer queue with lower-risk events batched for periodic review.

Step 5: Auto-generate investigation case files

For flagged events, Cassidy assembles evidence exhibits: event timelines, user profiles, care relationship verification, policy rationale, and hashed log excerpts—ready for investigator review without manual assembly.

Step 6: Orchestrate response and sanctions workflows

The Workflow notifies relevant stakeholders, collects user attestations, and integrates with HR systems to document corrective actions and sanctions per your progressive discipline policy.

Step 7: Produce OCR-ready compliance reports

Cassidy generates audit-ready documentation mapped to OCR Audit Protocol controls—including information system activity reviews, access management samples, incident response records, and breach risk assessments with chain-of-custody attestations.