Thalamus continuously computes each patient's clinical state from every new test, wearable reading and agent conversation, then gives every agent the same coherent state, so no two agents draw conflicting conclusions from the same patient.
Three sources are growing fastest: frequent testing and full-body screenings, wearables, and agent call transcripts, on top of the usual EHRs, lab reports, imaging and doctor notes. Most teams store all of it and hand it to the agent as-is.
Named for the brain's own relay station: the structure that filters and routes signal to the right destination. Thalamus does the same for clinical data.
Every document a patient generates, kept in full. Nothing is discarded at this layer.
Every document broken into discrete, tagged clinical facts, each one linked back to its source document, timestamp and provenance.
Active vs. resolved conditions, current medications, disease control, longitudinal trends, computed from the atomic layer and selectively updated as new evidence changes them.
Gives each agent the relevant slice of computed state, matches it against clinical guidelines, and surfaces care gaps before an agent starts reasoning.
Thalamus sits as infrastructure between raw healthcare data and whatever's reasoning over it.
Teams building narrow-task agents and AI scribes that need a precise, task-scoped slice of a patient's computed state rather than a full chart dump.
Platforms that need a live, continuously updated view of patient state to flag risks, gaps and follow-ups as new data lands.
Products spanning many care journeys that need one consistent, explainable patient state underneath every agent they ship.
Every atomic data point links back to its original document, timestamp and source. Every computed patient state traces back to the atomic points that produced it.
Tell us what you're building and what your agents are struggling to reason over.