Overview of Encord Active

Encord Active logo

Active is tightly integrated with Encord Annotate, with Active and Annotate being hosted by Encord.

Encord Active is active learning solutions that help you find failure modes in your models, and improve your data quality and model performance.

Use Active to visualize your data, evaluate your models, surface model failure modes, find labeling mistakes, prioritize high-value data for relabeling and more!

When to use Encord Active?

Encord Active helps you understand and improve your data, labels, and models at all stages of your machine learning journey.

Whether you've just started collecting data, labeled your first batch of samples, or have multiple models in production, Encord Active can help you.

encord active diagram

Example use cases

To give you a better idea about how Active and Annotate work together, here are some use cases.

Data Curation and Label Error Correction

Encord Active workflow

Optimize Model Performance

Encord Active workflow



Before going any further, you should know what a Collection is in Encord Active. Collections provide a way to save interesting groups of data units and labels, to support and guide your downstream workflow. For more information on Collections go here.

Clickable Div Data Cleansing/Curation Label Correction/Validation Model/Prediction Evaluation

What data does Encord Active support?



Active supports analysis (Advanced Metrics and Embeddings) on images and videos up to 4K resolution. Performance is affected for images and videos over 4K.

For optimal performance, we strongly recommend downscaling images and videos over 4K to 4K resolution.

Data typesjpg, png, tiff, mp4
Labels1classification, bounding box, polygon, polyline, bitmask, key-point
Number of images500,000 per project (unlimited projects)
Videos2 hours @ 30fps
Data exploration
Label exploration
Similarity search
Off-the-shelf quality metrics
Custom quality metrics
Data and label tagging
Image duplication detection
Label error detection
Outlier detection
Model evaluation
Label synchronization
Natural language search
Search by image
Integration with Encord Annotate
Nested Attributes
Custom metadata

1: Objects and classifications are both supported:


  • Objects + all attributes
  • Classification + all attributes

Model evaluation:

  • Objects and Classifications cannot be mixed
  • Classification support includes top level radio button
  • Object support includes top level object