Collaboratively Create & Manage Training Data with Image Annotation
Automate image annotations with pixel-perfect, AI-assisted labeling to develop high quality training data & build production-ready models up to 10x faster with the industry’s leading platform for image annotation.
Trusted by pioneering AI teams
Supporting your annotation needs
Efficiently label any computer vision modality across image, video, DICOM, or geospatial data and choose from a variety of tools to meet your annotation needs.
Keypoint Skeleton Pose
Create fully customized, automated ML pipelines to improve the efficiency and quality of your annotation workforce.
Master complexity with ontologies
We offer the industry’s most advanced labeling ontologies enabling you to create as many nested classifications to support your labeling operation and help you create a better Ground Truth.
Label 10x faster with AI-assisted labeling
Effectively train micro-models with a handful of labels to automate annotation without compromising on label quality. Solve labeling tasks over 10x faster to scale your training data creation.Learn more
Manage your data with ease
Securely manage all of your training data in one easy-to-use platform.
In-depth performance analytics
Uncover data-driven insights on label quality and annotator performance, to optimize workforce efficiency and ensure model excellence.
Supercharge models in production
Evaluate training datasets using a trained model and imported model predictions with entropy, least confidence, margin, and variance with pre-built implementations.
Segment anything, anytime
Harness the power of foundation models to automate annotations. Let models like Meta's SAM pre-label data & fine-tune to optimize for your specific use case.Learn more
Expert labeling services, on-demand
Encord matches your annotation use case to highly-skilled labeling professionals to deliver high-quality training data whilst lowering costs. Collaborate in real-time and scale your project effectively.Learn more
Supporting AI teams like yours
Stanford’s Division of Nephrology achieved an 80% reduction in experiment duration, while processing 3x more images with Encord’s annotation tools.
Stanford relied on three separate software tools to identify, annotate, & quantify podocytes and glomeruli in microscopy images.
Stanford adopted Encord's annotation tools & SDK to automate segmentations & measurements.
Stanford researchers decreased experiment duration from an average of 21 to 4 days, while processing 3x the images.