Healthcare
CareVision
A vision-and-language pipeline that turns unstructured clinical records and imagery into structured output — every extracted field held for human review, never written in unchecked.
The problem
Clinical records and imagery arrive unstructured — scanned notes, photos, mixed formats — and turning that into structured, usable data by hand doesn't scale. In healthcare, the cost of a rushed, unreviewed extraction is much higher than the cost of a slower, checked one.
The approach
A vision-and-language pipeline that extracts structured fields from unstructured records and imagery, with every extracted field presented for human review rather than written directly into a record unchecked. The system's role is to reduce the work a reviewer has to do, not to remove the reviewer.
What we evaluate
Extraction accuracy is measured field by field against a clinician-reviewed reference set, with particular attention to false positives — a wrong field going unreviewed is a worse failure mode than a slow one.
Status today
Live, processing records as part of the client's review workflow.
Architecture and evaluation specifics beyond what's above are covered by the client's NDA. Get in touch if you'd like to talk through what's relevant to your own engagement.