The co-pilot for every doctor.
AI augments; the doctor decides. Real-time intelligence at the point of care — so physicians can focus on patients, not paperwork.
Clinical intelligence
Real-time analysis of symptoms, history, labs and guidelines.
Evidence-based
Guideline-aligned suggestions for diagnosis, treatment and follow-up — each with its citation.
Patient insights
Genomics, nutrition, lifestyle and risk factors shape every recommendation.
Workflow automation
Documentation, coding, summaries and follow-ups — drafted, then reviewed.
Continuous improvement
Learns from real-world outcomes and reviewer edits to sharpen every recommendation.
Two clicks to evidence
From any statement, the underlying evidence is reachable in no more than two interactions.
Endpoints, pre-registered.
We publish no performance multipliers for the co-pilot, because none has been independently validated. These are the endpoints the anchor-site evaluation is designed to measure — and we will publish the results whether or not they are favourable.
Comparator is matched standard care, with analysis accounting for clustering by site and clinician, and early-period learning reported separately from steady state.
A clinician adopts the co-pilot only if reviewing and signing its output is faster and safer than reaching the same decision unaided — including the time spent verifying it.
Which is why explainability is a functional requirement here, not a feature. If drilling to evidence is slow, clinicians stop doing it, and the safety property that justifies the whole architecture quietly disappears.
We monitor the reviewer rejection rate for a healthy band rather than minimising it. A rate approaching zero is read as a warning — it usually means review has stopped being real.
Put the co-pilot beside your physicians.
Clinics and health systems start with a defined specialty and named clinicians.