Customize annotation layouts to enable any multimodal data labeling workflow. Leverage multimodal context to achieve high-quality training data at scale.

Label any image accurately using range of annotation tooling including bounding boxes, polylines, polygons, object primitives, keypoints and bitmasks. Use SAM 2 natively within Encord to accurately detect, segment and classify objects within images 10x faster.

Preserve temporal context and avoid frame synchronization issues by eliminating frame splitting with a video-native annotation platform. Automatically segment and track objects using SAM 2.

Use multi-channel annotation, nested ontologies and customizable attribute classes to label complex audio files with extreme precision down to the millisecond.

Streamline medical imaging AI workflows with 3D annotations for enhanced accuracy and multi-plane views for comprehensive annotation.

Flexibly label text data using intuitive text highlight tooling as well as bounding boxes for multimodal content within documents and text files.

Use intuitive text highlighting and file classification to label HTML files with ease.

Master complex 3D scenes with all sensors unified on a timeline for ADAS, autonomous vehicles and drone use cases. From raw sensor data, point clouds from LiDAR, and multiple camera angles, you can manage, search, curate, label your data and test models with ease.

Accurately annotate rendered ECG with a PACS-style interface and use nested ontologies to capture detail.