Don't Let a Silent Model Update Break Your Clinical Workflow.
DriftWatch AI guards healthcare LLM features—intake summarization, symptom triage, clinical note extraction, and prior-auth parsing—against unexpected schema drift and output degradation.
Catch Model Drift in CI/CD Before Production Deployments
Run your clinical prompt test suites through DriftWatch on every pull request. Each run returns a pass/fail schema report, and builds are blocked automatically when drift exceeds your safety threshold — so a provider model update never reaches clinicians unverified.
# .github/workflows/llm-drift.ymljobs:drift-check:runs-on: ubuntu-lateststeps:- uses: actions/checkout@v4- name: Healthcare LLM Drift Checkrun: npx driftwatch-cli test --schema clinical_note_v2.json --threshold 0.99# ✓ 248/248 prompts passed · schema conformance 99.6%# ✗ build blocked if conformance drops below 0.99
Audit-Ready Logs for Clinical Compliance Officers
Every model version change, schema violation and automated failover is captured as a timestamped, exportable record — giving compliance and quality management systems (QMS) the evidence trail they need to review how AI outputs behaved over time.
Download your workspace's timestamped schema drift audit trail (CSV or JSON) for QMS review.
Pre-Built Schemas for Healthtech Workflows
ICD-10 Code Extraction
Validates code format, description and confidence for every extracted diagnosis.
Medication List Parsing
Enforces drug name, dose, route and frequency fields on structured med lists.
Structured SOAP Note Output
Guarantees Subjective, Objective, Assessment and Plan sections are always present.
Enterprise Data Handling & PHI Notice
DriftWatch AI is designed with payload minimalism and optional local zero-retention modes. For custom HIPAA deployment architectures, BAA execution, or isolated single-tenant instances, contact our team.
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