Text, image, video, audio
AI data annotation
Scope AI data annotation before labels enter the dataset.
Prepare multilingual datasets with clear labels, examples, acceptance rules, and file format before annotation begins.
Guideline, examples, output schema
Language coverage reviewed by scope
For annotation work, scope starts with label definitions, examples, review samples, and output schema. Language review is added when meaning, dialect, script, or audio context affects the label decision.
What this page helps you scope
- Text classification, entity review, image labeling, video tagging, and audio segmentation.
- Multilingual annotation where language context affects labels.
- Dataset review with clear acceptance rules and file format requirements.
- Pilot batches where the label guide needs testing before scale.
What you receive
- Annotation scope brief.
- Label taxonomy and example set.
- Output format and review notes.
Questions teams ask first
What should be ready before annotation starts?
A label taxonomy, examples, edge-case rules, file format, and review sample help prevent avoidable rework.
Can language specialists support annotation?
Yes. Multilingual annotation can be scoped with language reviewers when labels depend on meaning, dialect, or cultural context.