The challenge
Clinicians needed decision support at the point of care, but patient records could not leave their jurisdiction, and the model the clinical team wanted to use was hosted somewhere that guaranteed nothing about where inference ran.
Earlier attempts had stalled on the same question every time: how do you evaluate a clinical model when you cannot pool the data you would need to evaluate it against?
What we did
Inference runs inside each jurisdiction, pinned to region, with the model shipped to the data rather than the reverse. No patient record crosses a border at any point in the request path.
Evaluation runs against a federated harness: each region reports aggregate quality metrics on its own data, and only those aggregates are compared centrally.
Every inference is logged with the model version and the inputs that produced it, because a clinical recommendation nobody can reconstruct six months later is not usable evidence.
Where it landed
Decision support is live in production with a full audit trail per inference, and the compliance review that had blocked two previous attempts cleared in a single pass.
Response times sit well inside the threshold where clinicians will actually wait for an answer rather than routing around the tool.
Something similar on your side? Tell us the shape of it.