Review-heavy by default
Diagnostic data can't tolerate sloppy labels. We run multiple review passes and consensus checks so ambiguous cases are resolved deliberately, not guessed.
Sector · Healthcare
Annotation for medical & healthcare imaging.
Medical imaging demands a different kind of care — slower, more deliberate, review-heavy. We bring the same QA rigor from our agritech work to labelling the scans, slides and images that train diagnostic-support and screening AI.
What we label
What we annotate.
Organ & lesion segmentation
Radiology bounding boxes
Cell & nuclei counting
Pathology slide regions
Anatomical landmark keypoints
Image-level classification
Multi-reviewer consensus
Built for careful work
How it's used.
Privacy-conscious handling
We treat medical data as sensitive by default — controlled access, on-premise storage where required, and clear handling agreements before any project begins.
Specialists on the bench
We are actively growing a team with medical-annotation experience so radiology, pathology and cell-imaging work is handled by people who understand the domain.
We are expanding into medical imaging and welcome pilot datasets — a small calibration set lets us align on your protocol before scaling.
