Labelbox

Labelbox provides a reinforcement learning (RL) data engine and platform designed for AI teams, offering data, environments, and evaluation infrastructure for building and improving AI models. It supports tasks such as data integration, scenario generation, RL training, and continuous model improvement.

Labelbox is designed for frontier AI labs, enterprises, and innovators looking to build, evaluate, and deploy AI models, particularly those focused on specialist agents and real-world applications. It serves organizations that require high-quality data and evaluation frameworks.

Labelbox enables the creation of structured evaluation frameworks, including expert-built scenarios, synthetic edge cases, and rubrics for outcome and process evaluation. It also provides human preference signals and real-world grounding data to assess model performance.

Labelbox supports a range of data types, including video, trajectories, and multimodal annotations, as well as RL environments for reasoning, tool use, computer use, and other AI tasks. It also integrates enterprise APIs, databases, and internal systems for simulation environments.

Yes, Labelbox offers full-stack data products for robotics foundation models, including video data, trajectories, and rich multimodal annotations for pre-training, post-training, and evaluation.

Labelbox employs expert-built scenarios, structured rubrics, and quality assurance processes to ensure high-quality data and evaluations. It also leverages human preference signals and real-world grounding from a network of knowledge experts.