We define modality, labeling rules, edge cases and acceptance criteria around your clinical use case before annotation starts.
The same full-time medical annotation team works your project end to end — not a rotating freelance pool.
Every batch is reviewed against the protocol and linked to a clear annotation and review record.
Data Handling
No data is requested or transferred before your discovery call. Every project runs under a defined protocol built for sensitive medical data — not a generic NDA.
De-identification steps agreed before any data changes hands
Role-based access, limited to the annotators and specialists assigned to your project
NDA-bound specialists and annotators on every engagement
Every batch traceable to its annotator and reviewing specialist
Project: 2,365 Medical images
Annotation Type: Polygon
Team Members: 17
Project: 138945 Medical images
Annotation Type: Polygon & Keypoint
Team Members: 4
Project: 5837 Medical images
Annotation Type: Polygon
Team Members: 4
Blood, tissue and partial occlusion made surgical tool boundaries difficult to define, while access to surgeon oversight was costly and difficult to scale.
Subul assembled 10 medical image annotators supervised by 5 surgeons, using polygon annotation and multi-level quality control to label 2,365 medical images.
The project reported 99% accuracy in surgical tool recognition.
We align on the modality, annotation guidelines, edge cases and acceptance criteria.
Start with a free 4–6 hour trial batch to validate the workflow and expected quality.
Dedicated annotators complete the work, with clinical specialists supporting quality review.
Receive structured, model-ready outputs and refine the next batches through continuous feedback.
Medical AI needs more than correctly placed labels. Subul combines dedicated teams, clinical input and structured quality checks — consistent from the first trial batch through scaled delivery.
Full-time annotators — not shared freelancer pools.
Every batch linked to its review record.
Medical specialists guide complex cases.
Trained teams grow with your data needs.
Frequently Asked Questions
We support medical imaging and video projects across oncology, cardiology, surgery and colonoscopy.
After the discovery call, we complete a free 4–6 hour trial batch so you can evaluate our quality and workflow before committing to a project.
Dedicated, full-time annotators work on your project, with clinical specialists supporting complex cases.
Yes. We align on your labels, edge cases and acceptance criteria before full production begins.
Structured reviews and continuous feedback keep every batch consistent as volumes grow.
Every project runs under the Subul Clinical Data Protocol — data-access and handling requirements are agreed before the project begins. De-identified or synthetic data can also be used for trial batches.
Tell us about your data, annotation guidelines and quality requirements. We'll recommend the right workflow and prepare a free 4–6 hour trial batch after the call.
Clinically reviewed medical training data, delivered by dedicated annotation teams.
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