The internal workspace that turns raw robotics video into buyer-ready data.
This MVP view makes the second side of the platform visible: annotators label robotics data, reviewers check quality, and HumanoidLayer packages verified outputs for buyers.
Active files
3
QA reviews
2
Avg score
84
Active video task
Warehouse exception handling video set
pick-scan-exception-042.mp4
Task
temporal segmentation
Assignee
J. Okafor
Due
2026-05-08
QA checklist
Reviewers check consistency before data becomes buyer-ready.
Label taxonomy matches buyer schema
Segments have start/end boundaries
Sensitive content flags reviewed
License/source notes attached
Export format validated
QA decision model
Tasks are approved, rejected, or sent back for fixes. Quality scores become marketplace trust signals.
Annotation queue
Mock tasks show how contributor work moves through labeling, submission, and review.
Warehouse exception handling video set
pick-scan-exception-042.mp4
Task type
temporal segmentation
Assigned to
J. Okafor
Quality score
91/100
ALOHA bimanual subset
tool-use-demo-118.hdf5
Task type
object labeling
Assigned to
Maya Chen
Quality score
88/100
Kitchen manipulation pilot
drawer-open-close-021.mp4
Task type
QA review
Assigned to
R. Alvarez
Quality score
73/100
Workflow inside the refinery
The annotation surface is where the metaphor becomes operational: raw data becomes structured, reviewed, versioned, and useful.