The Next Generation of Clinical Decision Support
Clinical decision support is moving from interruptive alerts toward contextual, source-grounded assistance that fits the clinician workflow.
From the blog
Research updates, product announcements, and insights from the Health Council team.
Clinical decision support is moving from interruptive alerts toward contextual, source-grounded assistance that fits the clinician workflow.
Healthcare teams are already surrounded by data. The missing layer is organized, trustworthy context at the moment of care.
Patient intake can become more adaptive, complete, and useful when conversational collection produces structured, reviewable clinical context.
Developer tools show how expert software can reduce context switching, expose provenance, and keep automation under user control.
In clinical workflows, the most valuable AI may be reliable, bounded, reviewable, and quietly useful rather than dazzling.
A practical framework for deciding which healthcare AI components must stay inside your private cloud boundary, from PHI and retrieval to inference and audit logs.
Retrieval-augmented generation can make clinical AI more useful, but only when retrieval, permissions, provenance, and clinician review are designed together.
In healthcare AI, security is not just about preventing breaches. It is about understanding where patient data goes, who can access it, and who truly controls it.
Hospitals are moving from "Should we use AI?" to "Where does it live, and how do we keep patient data safe?" A practical breakdown of deployment patterns and PHI considerations.
We're excited to introduce Council 1, our newest fine-tuned medical diagnosis model—and the top performer on the MedAsk symptom-checking benchmark across the frontier models we tested.