Evidence-based AI for high-stakes decisions

Make confident AI decisions in healthcare—without the guessing.

Chief Health AI helps organizations translate evidence into testable claims, deployment plans, and monitoring signals. We're building the discipline of evidence-based AI for high-stakes decisions across healthcare and life sciences.

We don't sell AI tools. We help you decide what to trust, how to test it, and how to monitor it over time.

What Makes This Different
01

Claim-first discipline

Every decision starts with: claim → evidence → limitations → what would change our mind

02

Living evidence systems

Not static reports. A structured workspace with an AI layer that answers questions on demand as evidence evolves.

03

Deployment reality

Evaluation and monitoring plans designed to survive real workflows, model drift, and organizational constraints.

Example Use Cases
Use Case 01

Healthcare systems deciding whether to deploy ambient AI scribes

Example: Build an EvidenceAtlas covering claims about burnout reduction, documentation time, and efficiency—with limitations and monitoring requirements clearly mapped.

View EvidenceAtlas
Use Case 02

Life sciences companies evaluating AI-augmented research tools

Example: Create EvidenceCards on accuracy claims, workflow fit, and regulatory implications to inform procurement and pilot design.

Use Case 03

Academic medical centers establishing governance for clinical AI

Example: Develop EvidenceBench plans defining what to measure pre-deployment and how to monitor for drift, bias, and safety signals post-launch.