What it is
Export lets you turn annotation results from a queue into a structured dataset you can use for fine-tuning, evaluation, or offline analysis. You can export directly into a FutureAGI dataset or download as JSON/CSV.Export to Dataset
Choose a target dataset
Create a new dataset by entering a name, or select an existing dataset from the dropdown.
Export as JSON/CSV
Open the Export menu
Open queue detail and click the Export button. Choose your format — JSON or CSV.
Export data structure
Each exported record contains the following fields:| Field | Description |
|---|---|
| item_id | Queue item ID |
| source_type | Type of annotated source (trace, span, session, etc.) |
| source_id | ID of the annotated entity |
| status | Item status (completed, skipped, etc.) |
| annotations | Array of label values with annotator info |
| notes | Annotator notes (if any) |
Use cases for exported data
- Fine-tuning — Use annotated traces as training data for model improvement.
- Evaluation datasets — Create golden datasets for automated eval pipelines.
- Quality reports — Analyze annotation patterns and model failure modes offline.
- Model comparison — Compare model outputs across annotated dimensions.
Export to Dataset creates a full FutureAGI dataset that you can use with all dataset features including experiments, evaluations, and prompt management.
Next steps
Analytics & Agreement
Review annotation progress and agreement before exporting.
Dataset Overview
Learn about FutureAGI datasets and what you can do with exported data.
Queues API
Export annotations programmatically via the REST API.