Solution
Annotation workflows, with reviewers in the loop.
Define the labels, the validation, and the review chain for your data labeling work. Annotators see only what they need; reviewers catch what they miss.
Where labeling pipelines break
Annotators apply labels inconsistently because the guidelines live in a separate doc.
There is no review stage, so errors only surface once they have polluted the dataset.
Everyone can see everything, when annotators should only see their own task.
Final labels come out in a shape your pipeline then has to reformat.
Built for annotation teams
Multi-stage review
Annotate, review, and adjudicate — each stage a distinct role with its own queue.
Validation rules
Require fields, enforce ranges, mandate evidence. Bad labels never reach the next stage.
Roles your team understands
Annotators, reviewers, leads — each with their own view and permissions.
Export keyed to your schema
Final labels exported in the structure your pipeline expects.
From raw items to clean labels
- 1
Define labels and rules
Set the label set, validation, and the review chain — no developer needed.
- 2
Assign annotators
Annotators get their own queue and see only the items they need to label.
- 3
Review and adjudicate
Reviewers catch bad labels; leads adjudicate disagreements before they land.
- 4
Export keyed labels
Final labels export in the exact structure your pipeline expects.