Scale AI

Data platform to curate, label, and manage AI training data.

An enterprise data development platform for preparing high-quality training data across images, video, documents, audio, DICOM, and 3D point clouds. It pairs AI-assisted labeling (SAM auto-segmentation, object tracking) with data curation, model evaluation, and workflow tooling, plus LLM-powered data agents for document tasks. Used heavily in medical imaging, robotics, and other physical-AI domains.

Open-source multi-type data labeling and AI evaluation.

Widely-used open-source tool for labeling and annotating data across images, text, audio, video, and time-series, with a standardized export format for training and fine-tuning. ML backends can pre-label data to speed up human review, and it increasingly doubles as a human-in-the-loop AI evaluation surface. Maintained by HumanSignal, which offers a hosted Starter tier and Label Studio Enterprise.

Enterprise data engine for labeling and managing unstructured AI data.

An AI-ready data platform that manages, labels, and orchestrates unstructured data — images, video, LiDAR, audio, and text — across the model lifecycle. It pairs data management and human-in-the-loop annotation with a serverless pipeline layer for pre/post-processing, RLHF, and RAG, plus a model-and-app marketplace. Originally focused on computer-vision production pipelines.

All-in-one computer vision platform to curate, label, and train models.

A unified computer vision platform covering data curation, annotation, model training, and deployment across images, video, 3D point clouds, and medical imagery. AI-assisted labeling, experiment tracking, and a large catalog of installable apps make it customizable for most CV workflows. Free for researchers and small teams; Pro and self-hostable Enterprise editions for companies.