The layer between raw medicine and a model you can trust. Licensed clinicians label, evaluate, benchmark, and create the data your models are trained, aligned, and tested on.
Medical AI is only as good as its data. Crowd labels and a model grading itself will not survive a hospital, a regulator, or an investor asking how you know it is right.
The data work behind a medical model, at every stage of its life, done by licensed clinicians.
Raw medical data into ground truth: imaging labels, clinical extraction, and classification.
Model outputs graded against a clinician read, every critical miss surfaced, in a report you can defend.
Clinician-written gold answers and preference data to fine-tune and align on.
A clinician judges the output on each axis that decides whether it is safe to put in front of a patient.
Whether the output is correct, partly correct, or wrong.
Unsafe advice, missed red flags, and failure to escalate or refer.
Whether the urgency assigned is clinically defensible.
Whether the stated reasoning actually supports the conclusion.
Whether every claim is supported by the source material.
Multi-step tool use, and where in the chain it goes wrong.
Not a one-off score. A suite your team re-runs after every prompt change and every model update.
Cases built to probe a defined capability, not sampled at random.
Verified clinical ground truth for every case.
What counts as correct, agreed in writing before the first case is judged.
Inputs written to break the model, not to flatter it.
Where the source material is incomplete or disagrees with itself.
The evaluated cases and their answers, yours to re-run forever.
Send data, licensed clinicians review it, you get it back. One pipeline, an API around it.
Push items through the API or the dashboard, to label or to grade.
Licensed specialists work each case, several reviewers per item, combined into a consensus.
Labeled data or scored reports, delivered by API and signed webhook, keyed to your case IDs.
How medical data is handled separates a result you can stand behind from a liability.
Medical specialists review your data, one case at a time. Not a crowd, and not a model grading a model.
Several clinicians review each item, combined with inter-reviewer agreement so you see where they concur.
Your data is de-identified before review and walled off from every other client.
Every review recorded: who did it, what they decided, and when.
Extraction, coding, and summaries.
X-ray, CT, and MRI.
Whole-slide and histology.
Evaluation, safety, and preference data.
Variant and multi-omic data.
PHI detection and redaction.
Start with a slice, see the value, then scale. Book a demo, or read the docs and start from code.