Tools

Data labeling & annotation

9 tools compared: how each is priced, where it runs, and what to consider instead.

Tool Pricing model Free tier Open source
CVAT Open-source, self-hosted tool focused on image and video annotation for computer vision, with bounding boxes, polygons and tracking. Open source + paid Yes Yes
Encord Multimodal data platform covering curation, AI-assisted annotation and model evaluation for vision, video, audio, text and medical imaging. Quote only No No
Label Studio Open-source, self-hosted annotation tool supporting images, text, audio, video and time-series data through a configurable UI. Open source + paid Yes Yes
Labelbox Enterprise annotation and data-curation platform (Annotate, Catalog) that has expanded into RLHF and agent-training data services. Quote only Yes No
Scale AI Large-scale data-labeling and data-engine platform combining tooling, managed human workforces and RLHF services for AI training data. Usage-based Yes No
Snorkel AI Programmatic-labeling platform (Snorkel Flow) that generates training labels from heuristic rules and weak supervision instead of manual annotation. Quote only No No
SuperAnnotate Multimodal annotation and MLOps platform with a customizable editor, data curation and analytics for scaling AI training-data projects. Quote only No No
Surge AI Human-data platform providing an expert labeling workforce and off-the-shelf RL environments for training and evaluating LLMs. Quote only No No
V7 Annotation platform for images, video and documents, strong in medical imaging formats, with AI-assisted and auto-tracking labeling. Quote only No No

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