Industries
Healthcare
Evidence-verified outputs for clinical, administrative, and payer workflows — where unsupported claims create patient and legal risk.
What Kenshiki Labs Does Here
A clinical recommendation that reads correctly but isn't grounded in approved protocol is worse than no recommendation at all. Kenshiki Labs unifies build and orchestration with control in a single three-plane architecture — without touching clinical application logic. The Claim Ledger decomposes clinical and administrative claims and checks each against approved protocols, policy, and source records before emission. The Boundary Gate enforces cross-plane policy propagation before care-adjacent claims leave the system. SIRE provides portable agent identity, scoping PHI evidence boundaries so teams act on AI-assisted output with evidentiary confidence.
- Verifies care-adjacent AI assertions against approved clinical guidance and local policy
- Constrains patient-facing responses when evidence is incomplete or conflicting
- Enforces role and relationship boundaries for PHI-sensitive retrieval and output
- Maintains full citation lineage for each emitted claim across care and claims flows
- Supports deterministic replay for adverse-event and compliance investigations
Regulatory Context
Healthcare AI systems operate in a tightly governed environment where privacy, safety, and documentation standards are enforceable obligations.
- HIPAA and HITECH require strict controls over protected health information access and disclosure
- CMS documentation and billing integrity rules demand traceable support for operational decisions
- FDA guidance and SaMD expectations increase scrutiny of software-influenced clinical pathways
- Joint Commission and accreditation requirements emphasize reproducible safety processes
- State privacy and patient-rights statutes add jurisdiction-specific governance obligations