Trust intelligence for healthcare AI
Healthcare AI has life-or-death stakes. Deploy AI with the trust, safety, and compliance that patients and regulators demand.
In healthcare, AI failures aren't just expensive — they're dangerous
Healthcare AI is different
Healthcare AI has life-or-death stakes. Most AI tools aren't ready for healthcare's trust requirements.
Hallucination risk
AI confidently recommending wrong treatments. In healthcare, confident mistakes can be fatal.
Bias and equity
Models trained on unrepresentative populations. Healthcare AI must serve all patients fairly.
Drift over time
Performance degrades as patient populations change. What worked last year may not work today.
Opacity problem
Clinicians can't understand or verify AI reasoning. And they shouldn't trust what they can't verify.
"Clinical AI that clinicians actually use — because they can understand it, verify it, and trust it."
Trustworthy clinical decision support
AI can synthesize patient data, literature, and guidelines faster than any human. But clinicians won't trust black-box recommendations — and they shouldn't.
Guardian — Clinical AI Monitoring
Continuous monitoring for hallucination and drift. Bias monitoring across demographics. Confidence calibration tracking. Know when your clinical AI is uncertain — before it gives wrong advice.
Reasoning Capture — Explainability
Full reasoning chain for every recommendation. Citation of evidence and guidelines. Confidence levels with uncertainty quantification. Audit trail for M&M review and liability protection.
Steer — Behavior Guardrails
Enforce clinical guidelines at runtime. Prevent recommendations outside scope. Require human confirmation for high-risk decisions. Adjust based on clinician feedback without retraining.
Eval — Continuous Validation
Ongoing evaluation against clinical outcomes. A/B testing of model versions. Fairness testing across patient populations. Regression testing for updates.
Clinical decision support applications
Diagnostic support
Imaging, pathology, lab interpretation with explainable reasoning.
Treatment recommendations
Evidence-based suggestions with confidence levels and citations.
Drug interaction checking
Real-time alerts with reasoning and alternatives.
Risk stratification
Patient risk scoring with transparent methodology.
AI for healthcare operations
Beyond clinical care, healthcare organizations are deploying AI for revenue cycle, patient access, and administrative efficiency.
Trust Cascade for Prior Authorization
Rules for straightforward approvals. ML for pattern-based decisions. AI for complex medical necessity. Human review for edge cases. Result: 70% auto-adjudication, 40% cost reduction.
ETL-C for Patient 360
Unified view across EHR, claims, and social determinants. Contextual understanding of patient journey. Real-time data for operational decisions. Semantic joins across disparate systems.
Guardian for Operational AI
Monitor scheduling AI for drift. Track coding accuracy over time. Detect anomalies in automation. Central visibility into all operational AI systems.
Operational use cases
Revenue cycle
Prior auth automation, coding assistance, denial management, claims optimization.
Patient access
Scheduling optimization, capacity management, no-show prediction, wait time reduction.
Administrative
Document processing, patient communication, staff scheduling, supply chain optimization.
Patient-facing AI that builds trust
Patients increasingly interact with AI — symptom checkers, scheduling, care navigation, health coaching. The stakes are high.
Safety First
Guardian monitors for harmful outputs, hallucination, and drift. Never provide dangerous medical advice. Know when to escalate to humans.
Appropriate Boundaries
Steer enforces safety boundaries and escalation triggers. Require human handoff for clinical decisions. Protect patient privacy in every interaction.
Full Accountability
AgentOps provides complete audit trail. Human-in-loop workflows for sensitive decisions. Documentation for liability protection.
Personalized Context
ETL-C enables patient context for personalization — HIPAA-compliant. Better responses based on patient history, without compromising privacy.
Built for healthcare compliance
Our solutions support healthcare's complex regulatory landscape from day one.
HIPAA
Privacy and Security Rules compliance. PHI protection in all processing. Audit logs for compliance.
FDA AI/ML Guidance
Model documentation for SaMD (Software as Medical Device). Support for FDA submission requirements.
ONC Requirements
Information blocking rules compliance. Interoperability requirements supported.
Equity & Fairness
Bias testing for equity requirements. Fairness monitoring across patient populations.
Start your healthcare AI journey
Healthcare AI Assessment
$35K
3 weeks. Current AI inventory and risk assessment. Compliance gap analysis. Use case prioritization. Trust architecture recommendations.
Clinical AI Pilot
$100K
8-10 weeks. Implement Guardian + Eval for one clinical use case. Demonstrate trust metrics improvement. Build clinician confidence and adoption.
Enterprise Healthcare Platform
$400K+
6-9 months. Full trust infrastructure deployment. Integration with EHR and clinical systems. Clinical and technical team enablement.
Healthcare AI that patients and clinicians trust
Life-or-death stakes demand AI you can verify. Let's build it together.