Labelbox, founded in 2018 and headquartered in the United States, builds data infrastructure for AI teams. The company combines enterprise annotation software, managed labeling services, and an expert marketplace into a single platform designed to produce the training data that underpins modern AI development. It has raised $189 million in funding and counts more than 80% of leading AI labs in the United States among its partners, alongside Fortune 500 companies and research organizations.
The platform is organized around three core offerings. Enterprise annotation tools provide software for large-scale data labeling workflows. Frontier data labeling services handle more demanding use cases, including reinforcement learning data generation, reinforcement learning from human feedback (RLHF), model evaluation, and robotics dataset creation. The third component is Alignerr, an expert marketplace connecting clients with a global network of over one million knowledge workers across 40+ countries who provide specialized training data.
Labelbox's technical focus is decidedly applied: its infrastructure is built to support the data pipelines that AI teams need to train, fine-tune, and evaluate models at scale. This includes tooling for annotation, quality control, and the delivery of domain-specific datasets for advanced use cases such as robotics and frontier model development. The combination of software and human services in a single platform is central to how the company positions its offering relative to standalone annotation tools or purely managed-service providers.