Support for all key modalities

Visually inspect data outliers with embedding plots. Find underrepresented areas of your datasets and fill these gaps.

Simplify data cleansing

Build balanced and representative datasets by identifying underrepresented visual quality metrics and corrupt images to enhance AI model performance.

Advanced filtering options

Connect to AWS, GCP, Azure, or OTC cloud storage in a few clicks and access all nested files in an instant. Data changes in storage are instantly reflected in Encord Index with data refresh.

Multimodal annotation

Efficiently label data of any modality including image, video, medical imagery, or geospatial data and audio. Map relationships between modalities with sophisticated labeling ontologies. 

Streamline data operations

Monitor team and annotator performance with actionable dashboards to ensure training data quality.

Collaborate across teams

Seamlessly control user roles with permissioning, manage task assignment, and infinitely scale your MLOps workflows.

Find & fix data issues with ease

Identify edge cases and underrepresented classes and conduct robustness and regression tests to uncover failure modes and issues in your models.

Evaluate model performance

Deconstruct model performance with automatic reporting on metrics like mAP, mAR, and F1 Score.

Compare model performance

Integrate humans-in-the-loop to build active learning workflows to refine model performance iteratively, significantly reducing deployment timelines.