Create a release
Freeze approved content with an explicit export contract.
Freeze approved content with an explicit export contract.
Release creation starts inside the project—not from the workspace My Releases gallery. The project Releases page scopes the eligible annotated data and exposes the queue, data-type, format, distribution, and export-token controls used for that delivery.
Resolve or explicitly exclude rejected, invalid, failed, escalated, or unreviewed work.
Choose the downstream consumer and schema requirements.
Name the release owner and validation owner.

Open Project › Releases and choose Release. The dialog shows the eligible annotated item count, selected queue scope, included data types, export format, train/validation/test distribution, and optional export token URL before creation.
Releases are created from a project’s Releases page:
The user opens the export dialog.
The user chooses the source scope: the full project or one/more Batch Queues.
The user selects one or more data families inside that scope.
Unitlab previews releasable counts, annotation/review progress, format compatibility, and recommended format.
The user chooses an export format or per-family Standard Bundle formats.
The user selects a license when required.
The user enters nonnegative integer train, validation, and test percentages that sum to 100.
The user optionally enables stable tokenized item URLs.
Unitlab creates the versioned release.
Invalid latest histories are excluded from ordinary releasable counts. Cloud-storage-sourced releases are forced private.
Queue scope
Whole project is correct only when every eligible item is approved for this handoff.
Content scope
Make data types, inclusions, and exclusions explicit and reviewable.
Format
Choose for downstream fidelity, not convenience alone.
Splits
Use a reproducible policy that prevents leakage across related items or groups.
Token URL
Enable only for an approved access workflow; never publish or log the resulting secret.
Sources
Balance reproducibility, storage, access, and sensitive-data requirements.
Inspect sample output and counts.
Download into a controlled validation environment.
Record downstream acceptance or required correction.
Explore related Unitlab capabilities: training-data curation workflows