T-Rex Label

Vision MLOps end-to-end. Annotate, train, deploy.

Annotation tooling, auto-labelling, hosted training, and edge deployment for computer-vision projects. Strong default when you're shipping a custom vision model rather than reaching for a multimodal LLM.

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.

Data factory for AI teams — labeling, evals, and human data for training.

Labelbox is a platform for generating and managing training data for AI models, combining annotation tools (Annotate), data curation (Catalog), and model-assisted labeling and evaluation (Model Foundry). It now spans reinforcement-learning data, custom evals, robotics datasets, and an on-demand network of expert human labelers, metered by a usage-based Labelbox Unit (LBU).

FiftyOne — open-source vision data platform.

Open-source toolkit for exploring, debugging, and curating vision datasets. Strong story for finding model failure modes, balancing classes, and tracking experiment drift across visual data at scale.