This is Moonbounce’s label-first experience. If you’re looking for the
policy-first experience, switch using the version selector above.
The loop
Everything you do in the label-first experience follows one loop:Craft a label
Create a named label that captures the concept you want to detect, and
describe what should and shouldn’t match.
Test it against its dataset
Every label carries its own set of test examples. Run your work-in-progress
against that dataset, read the results, and refine.
Publish a version
When you’re happy with the results, publish. Publishing mints an immutable
snapshot — a version — that never changes underneath you.
Why label-first
- The label is self-contained. Test data and version history live with the label, so there’s no separate object to wire together before you can iterate.
- Published versions are reproducible. Because a published version is an immutable snapshot, the results you saw while testing are the results you get in production.
- You iterate in isolation. Editing happens on a draft that auto-saves, so your live, published versions are never disturbed while you experiment.
Where to next
Labels, Versions & Datasets
The core concepts: drafts vs. published versions, immutability, and
per-label datasets.
Integrating a Label
Get a label version id and send it to the evaluate API to classify content
in production.
We’d Love to Hear From You
Whether you have a suggestion, feedback, or a bug to report, here are the best ways to get in touch:- In the App: Use the Feedback button for direct suggestions.
- On Slack: Reach out to the team in your shared channel.
- With your AM: Talk to your dedicated account manager.
- Via Email: Send a message to support@moonbounce.io.
- Security, availability, or other incidents: Use the in-app Feedback button or email support@moonbounce.io. See Customer Feedback for what to include.