Infrastructure for clinical AI agents

Every agent needs a slice of the patient's history — not all of it.

Thalamus filters, structures and routes raw clinical data into exactly the context each agent needs to reason well: no more, no less, and every point traceable back to its source.

L1
L2
L3
L4
RAW PATIENT DATA ROUTED AGENT CONTEXT
The problem

Clinical AI companies drown their own agents in context.

Patient data arrives from EHRs, lab reports, imaging, clinical PDFs, wearables, doctor notes and agent conversations — fragmented across sources, duplicated across visits, and accumulating over years. Most teams hand all of it to the agent and hope it finds what matters.

RESULT 01
Lower quality reasoning
RESULT 02
Higher hallucination rate
RESULT 03
Unnecessary token usage
RESULT 04
Added latency, weaker coherence
The architecture

Four layers, one continuously updating patient state.

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.

L1

Raw clinical data

Every document a patient generates, kept in full. Nothing is discarded at this layer.

L2

Atomic clinical data points

Every document broken into discrete, tagged clinical facts — each one linked back to its source document, timestamp and provenance.

L3

Computed patient state

Active vs. resolved conditions, current medications, disease control, longitudinal trends — inferred from the atomic layer and kept current as new data arrives.

L4

Intelligence layer

Compiles the right context for each agent, matches patient state against clinical guidelines, and surfaces care gaps before an agent starts reasoning.

Read the full architecture →
Who it's for

Built for the companies building the agent, not the hospital or the patient.

Thalamus sits as infrastructure between raw healthcare data and whatever's reasoning over it.

CATEGORY

Clinical agents & scribes

Teams building narrow-task agents and AI scribes that need a precise, task-scoped slice of context rather than a full chart dump.

CATEGORY

Care management & decision support

Platforms that need a live, continuously updated view of patient state to flag risks, gaps and follow-ups as new data lands.

CATEGORY

Virtual care & digital health

Products spanning many care journeys that need one consistent, explainable patient state underneath every agent they ship.

Explainability

Nothing an agent sees is unaccountable.

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.

Building a clinical AI agent?

Tell us what you're building and what your agents are struggling to reason over.

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