Prior authorization agents that navigate payer portals autonomously. Scheduling and referral coordination. Discharge documentation synthesis. Real work, not demos.

Healthcare AI
15 years in HIPAA-regulated environments. Cedars-Sinai. City of Hope. Hoag. UCI Health. We know what healthcare AI actually requires — and what it doesn't.
Healthcare AI is different
Most AI consultancies learn healthcare vocabulary during the sales cycle. We learned it over 15 years of implementation work inside health systems — navigating Epic integrations, HIPAA audit prep, and the operational realities that don't show up in case studies.
15 years inside health systems
- [·]Cedars-Sinai Medical Center
- [·]City of Hope
- [·]Hoag Health Network
- [·]UCI Health
Frameworks we build against
Where AI creates value in healthcare
RAG architectures on Epic, Oracle Health, and Veradigm data. Clinical documentation intelligence. Patient history synthesis for care teams. All on-premise or in your VPC — data never leaves.
PHI handling policies. Access control for AI systems. Audit trails for every AI-assisted decision. Explainability documentation for clinical AI. Built by people who've worked in HIPAA environments for 15 years.
Clinical staff have seen enough technology implementations fail to be skeptical. We design adoption programs that earn trust — starting with what AI actually does well in clinical contexts, not hype.
Non-deterministic AI outputs in clinical decision contexts need rigorous validation. Evaluation harnesses, adversarial testing, and ongoing quality monitoring that meets healthcare's higher bar.
Scored assessment across data infrastructure, governance readiness, workforce capability, and integration complexity. Specific to healthcare's regulatory and operational context.
Book a healthcare AI conversation — your regulatory environment first, no generic pitches.
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