Layout Overview
The Enrich tab is organized into three areas.| Region | Purpose |
|---|---|
| Model Picker | Select one or more models to run against the dataset |
| Preview Panel | Inspect a sample of model output before committing to a full run |
| Progress View | Track the status of running enrichment jobs and review past jobs |
Model Picker
The model picker lists every enrichment model available for the dataset. Each entry shows the model name, its task type, and a short description. Selecting a model highlights it, and Add Models includes additional models in the same run. Available models cover a range of enrichment tasks:| Task Type | Purpose |
|---|---|
| Object detection | Draws bounding boxes and classifies each detected object. Feeds the Objects view in the Explore tab. |
| Image tagging | Assigns labels to the entire image. Populates the Labels section of the Insights Panel. |
| Image and object captioning | Generates descriptive text that powers Caption Search. |
| Semantic search embeddings | Powers Semantic Search across the dataset. For the theory, see How Semantic Search Understands Language. |
| Face detection | Detects faces and facial landmarks. |
Some models require pre-existing enrichments before they can run. For example, VL-Object-Captioner requires Object Detection to have been applied first, and semantic search models require captions or embeddings from a prior enrichment step.
Preview Panel
The preview panel runs the selected model(s) on a small sample of images and displays the output so a reviewer can inspect the results before committing to a full dataset run. A Generate Models Preview button produces the sample, and when multiple models are selected the panel allows switching between them to compare outputs. An Enrich Dataset button commits every selected model to a full run across all images and frames in the dataset. For the end-to-end procedure, see Enrich Your Datasets.Progress View
The progress view tracks enrichment jobs from start to finish. Each job entry shows the models being run, a live progress indicator, and a timestamp. Completed jobs remain in the view as history. Enrichment runs do not block exploration. You can continue to search, filter, and select in the Explore tab while a job is in flight, and newly generated metadata becomes available in the Insights Panel and filter options once the job completes. For live status across every dataset in the workspace, use the Task Manager. Notifications for completed enrichment runs appear in the bell icon in the dataset header — see Monitoring and Alerts for the full notification system.Related Resources
Enrich Your Datasets
How enrichment works and the end-to-end run flow
Model Catalog
Every available enrichment model, task type, and dependency
Task Manager
Monitor every running task, including enrichment jobs
Explore Tab
Where enriched metadata becomes filterable and searchable