Capability 02
For teams building clinical products. Evidence retrieval ranked by study quality, decision support a clinician can audit, and the health data integrations underneath. Built with you, or built for you.
What it does
Whole system or one layer of it. Most teams come to us with two of these already working and the other two stuck.
01
Generic vector search returns whatever is nearest. Clinical questions need the strongest study, not the closest sentence. We rank on study design, recency and relevance, and the answer carries its citations.
02
Draft recommendations built from your own clinical rules, with a provider approving every output and a path from the recommendation back to the source it came from.
03
Labs, EHRs, HL7 and FHIR feeds, and the twelve page PDFs nobody wants to touch. Structured fields out of unstructured clinical documents.
04
How you know it still works six weeks after launch. Benchmarks against frontier models, regression suites on real clinical questions, and drift you can see before a customer does.
The rules it runs under
Nothing reaches a patient on the model's say so. The system produces a draft and a person approves it. That boundary lives in the product, not in a policy document.
From the recommendation to the paper, the lab value or the rule it came from, in one click. An answer nobody can check is an answer nobody can defend in front of a regulator.
What reaches the model, which third parties see it, how long it is kept and who can read it. Settled before the first line, not audited after the first incident.
How the retrieval underneath this actually works is written up in detail on evidence retrieval systems.
The one that works in the demo and falls over in front of a clinician. We will tell you where it is failing and what it takes to fix.
Thirty minutes, free, no pitch
