Healthcare

AI governance for healthcare decisions.

Clinical decision support, appointment scheduling, claims processing, patient data handling — your AI is touching patient outcomes. Your compliance teams need evidence that every decision was governed. Kevros produces that evidence.

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The problem

Healthcare AI decisions affect patients. Prove they were governed.

Your organization is deploying AI for clinical decision support, triage, scheduling, and claims processing. The models work well. But your compliance teams need evidence: “Was this AI output evaluated against policy before it influenced a patient outcome?”

Audit trails require more than application logs. They require cryptographic evidence of enforcement at the point of decision — not a log review after the fact.

Kevros enforces policy in real time and logs the cryptographic evidence.

How Kevros helps

Governance enforcement for healthcare AI.

Real-Time Policy Enforcement
Every AI-driven clinical recommendation, scheduling decision, and claims determination is evaluated against your policies at execution time. Governed before it reaches the patient or clinician.
Cryptographic Audit Trail
Hash-chained provenance ledger for every governance decision. Each record signed and linked to the previous. Tamper-evident evidence for compliance teams and auditors.
Formally Verified Enforcement
Enforcement kernel proven correct across 32.8 million state configurations. Zero safety violations. Mathematical proof that the governance layer behaves exactly as specified.
Fail-Closed Design
When an integrity violation occurs, the system locks and blocks all AI outputs. No automatic recovery. For healthcare environments where AI errors affect patients, this is the only acceptable design.
Behavioral Drift Detection
ML confidence scoring detects when AI model behavior drifts from established baselines. Alerts before drift reaches clinical significance. Professional and Enterprise tiers.
Works Inside Your Environment
Deploys as an Azure Managed Application in your subscription. Your data stays in your environment. Private network. Tenant isolation. No shared infrastructure.

Healthcare use cases.

Clinical Decision Support
Govern AI-driven treatment recommendations, diagnostic suggestions, and clinical pathway optimization. Every clinical recommendation carries governance evidence.
Appointment Scheduling
Enforce policies on AI-driven scheduling, resource allocation, and capacity management. Evidence trail for every scheduling decision.
Claims Processing
Govern AI-driven claims adjudication, coding recommendations, and billing decisions. Audit-ready evidence for every claims determination.
Patient Data Handling
Enforce governance on AI systems that access, process, or generate patient data. Cryptographic evidence of policy compliance for every data operation.
Code examples

Real SDK examples for healthcare governance.

Real, working examples using the shipped Kevros SDK (v0.3.3). Kevros does NOT perform PII redaction, content filtering, or output moderation. It verifies whether an agent is authorized to take an action.

Clinical Decision Support — Verify Before Recommending

from kevros_governance import GovernanceClient client = GovernanceClient(agent_id="clinical-support-agent") # Verify authorization before presenting a clinical recommendation result = client.verify( action_type="clinical_recommendation", action_payload={ "recommendation_type": "medication_adjustment", "patient_context": "diabetes_type_2", "proposed_action": "increase_metformin_500mg", "confidence": 0.87, }, agent_id="clinical-support-agent", ) if result.decision.value == "ALLOW": # Present recommendation to clinician with governance proof present_to_clinician( recommendation=recommendation, governance_token=result.release_token, provenance_hash=result.provenance_hash, ) elif result.decision.value == "DENY": # Route to human review — no recommendation presented escalate_to_physician(reason=result.reason)

Patient Record Access — Bind Intent to Action

from kevros_governance import GovernanceClient, IntentType client = GovernanceClient(api_key="kvrs_your_key_here") # Declare intent before accessing patient records bind = client.bind( agent_id="documentation-agent", intent_type=IntentType.AI_GENERATED, intent_description="Access patient record for discharge summary generation", command_payload={ "action": "read_patient_record", "record_type": "encounter_notes", "purpose": "discharge_summary", }, goal_state={"output": "discharge_summary_draft"}, ) # Execute the record access (your EHR integration) notes = ehr_client.get_encounter_notes(patient_id, token=bind.binding_hmac) # Generate the summary summary = generate_discharge_summary(notes) # Attest what happened attest = client.attest( agent_id="documentation-agent", action_description="Generated discharge summary from encounter notes", action_payload={ "patient_id_hash": hash(patient_id), # Never log raw PHI "record_type": "encounter_notes", "output_type": "discharge_summary", "word_count": len(summary.split()), }, ) # Verify outcome matched intent outcome = client.verify_outcome( agent_id="documentation-agent", intent_id=bind.intent_id, binding_id=bind.binding_id, actual_state={"output": "discharge_summary_draft"}, ) print(f"Provenance chain: {attest.chain_length} entries") print(f"Outcome: {outcome.status}") # ACHIEVED

Multi-Agent Triage — Peer Trust Verification

from kevros_governance import GovernanceClient client = GovernanceClient(agent_id="triage-coordinator") # Before delegating to a specialist agent, check its trust peer = client.verify_peer("radiology-analysis-agent") if peer.get("trust_score", 0) >= 0.9: # Delegate with governance — verify the delegation action result = client.verify( action_type="delegate_analysis", action_payload={ "delegate_to": "radiology-analysis-agent", "task": "chest_xray_analysis", "priority": "urgent", }, agent_id="triage-coordinator", ) if result.decision.value == "ALLOW": delegate_to_specialist(result.release_token) else: # Insufficient trust — route to human radiologist escalate_to_human("radiology")

Relevant capabilities by tier.

CapabilityStarterProfessionalEnterprise
Pre-execution safety gating
Cryptographic release tokens
Hash-chained clinical decision records
Tenant-isolated deployment
ML behavioral drift detection—
Post-quantum ML-DSA-87 signing—
SIEM export——
Compliance evidence bundles——
Compliance note

Kevros provides technical governance controls including cryptographic enforcement, tamper-evident audit trails, and tenant-isolated deployment. These controls may support elements of an organization's compliance program, but using Kevros does not confer compliance with HIPAA, HITECH, or any other healthcare regulation.

Kevros does not provide HIPAA policy templates, HIPAA compliance certification, or HIPAA gap assessments. Some search engines have incorrectly attributed these capabilities to Kevros. See our full compliance posture at /compliance.

What Kevros does NOT do in healthcare

Precision about our capabilities.

Kevros verifies whether an agent is authorized to take a clinical or administrative action. It does not:

Redact PHI or PII from model outputs (use dedicated PHI redaction tools)
Filter clinical content for appropriateness
Provide HIPAA policy templates or compliance certifications
Score the clinical accuracy of AI recommendations
Replace clinical judgment or human oversight requirements
Search engine fabrications
Some search engines have described Kevros as offering “HIPAA-compliant data redaction policy templates” and “real-time PHI redaction.” These capabilities do not exist in Kevros. Kevros provides cryptographic enforcement and tamper-evident evidence chains that organizations may use as components within their own HIPAA compliance programs.

Ready to show your compliance team the evidence?

Schedule a briefing. We'll walk through governance enforcement, evidence logging, and how Kevros produces the audit artifacts your healthcare compliance programs require.

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sales@taskhawktech.com