Robotics labels live in 3D and in time. Trained annotators deliver segmentation, pose, grasp, action, and language labels through a two-pass QA loop — signal, not noise.
2D/3D segmentation, 6-DoF pose, grasp points, and keypoints — labeled against calibrated multi-view footage and point clouds so they stay consistent across cameras and frames.
Demonstrations segmented into skills and sub-tasks, with success/failure, recovery events, and contact phases marked frame-accurately — the structure skill-conditioned policies need.
We write and verify instructions, sub-goal captions, and paraphrase sets per episode — checked against the footage so language never drifts from what the robot did.
Annotation without measurement is guesswork. Each batch runs through a calibrated review loop before it ships.
Gold tasks and guideline tests qualify every annotator on your ontology first.
Production labeling with embedded gold tasks tracking live accuracy per annotator.
A second-pass reviewer audits geometry, timing, and language on every episode.
Batches ship with agreement stats, error taxonomies, and per-episode quality scores.
Share 20 episodes and your ontology. We'll return them fully labeled with QA metrics so you can judge the quality yourself.