What it sells
Rapid medical data annotation
Business model breakdown
Buyer: who owns the budget?
UnverifiedRadiology AI teams, medical imaging AI companies and research groups (case studies with Olea Medical, Qure, RapidAI).
Trigger: what makes them buy now?
Need to generate ground-truth annotations for medical imaging AI models faster; claims 60% faster ground truth and 5x faster than manual annotation.
Workflow: what inputs become what output?
Upload DICOM data, create cohorts, annotate with 3D contouring and SAM-powered automated segmentation in the browser, and manage the annotation cycle for model training.
Distribution: how it reaches customers
Gated 'Get access' request form (demo/sales-led); documentation and security pages.
Funding history and coverage
| Round date | Stage | Amount | Investors | Source |
|---|---|---|---|---|
| — | Y Combinator Winter 2022 | — | Y Combinator | ycombinator.com |
Profiles summarize public reporting and company websites. Business-model notes are MaxBC's reading of that material, not confirmed facts; unknowns are left blank rather than guessed. Updated 2026-10-12.