Data Labeling Software

Delivers expert human data for frontier AI, with 30 years of data excellence helping teams build, train, and deploy trustworthy AI models across 500+ locales.

End-to-end platform to annotate, version, and manage ground truth data for your AI, ranked the #1 data annotation platform on G2.

Formerly TELUS International; enriches data with a global range of human-annotation services at scale, spanning generative AI, physical AI, and robotics data.

Formerly marketed as Scale Rapid; collects, curates, and annotates data to train and evaluate models with high-quality labels from domain experts.

Now positioned as an RL data engine for AI teams, partnering with leading AI labs on environments, custom evaluations, and enterprise agent training.

Formerly SageMaker Data Labeling; helps build highly accurate training datasets and now includes hands-on support to fine-tune generative AI models.

An enterprise-first AI development platform combining data management, models, pipelines, and human feedback in one unified, ready-to-go environment.

Multi-sensor LiDAR annotation and calibration tools to accelerate computer vision training for autonomous vehicles, robotics, and physical AI.

The most flexible open-source data labeling and AI evaluation platform, supporting agent traces, LLM evals, RLHF, computer vision, and NLP.

A leading platform for building high-quality visual datasets, now maintained under the independent cvat-ai GitHub org (moved from Intel's OpenVINO Toolkit).

A graphical image annotation tool; now archived and part of the Label Studio community, with the repository preserved under HumanSignal's GitHub org.

A tool for labeling image and video data for computer vision research, built in Python with a lightweight, extensible design.

An AI-enabled text annotation tool at its core for NLP, supporting PDF, Markdown, CSV, HTML, and tweets to create labeled datasets.