Healthcare is where AI hype goes to be humbled. The stakes are real, the data is messy, the regulations exist for good reasons, and clinicians have zero patience for tools that waste their time. We build for healthcare anyway — carefully.
Documentation first
We started with the least glamorous problem: documentation. Clinicians spend hours a day writing notes, and burnout follows. Our medical documentation assistant drafts structured notes from encounters for the clinician to review and sign. The clinician stays the author; the AI holds the pen.
Speaking FHIR
Health data lives in FHIR resources, and our FHIR assistants let care teams query it in plain language — medication histories, lab trends, care gaps — with every answer traceable to the underlying resource. No more clicking through twelve screens to answer one question.
Patients deserve intelligence too
Patient education may be the highest-leverage use of language models in healthcare: explaining a diagnosis at the right reading level, in the patient's own language, as many times as they need to hear it. Judgment stays with clinicians. The explaining, the searching, the paperwork — that's where AI belongs today.