Scale

Scale builds the data infrastructure behind many advanced AI systems, helping teams manage the entire machine-learning lifecycle through high-quality data and full-stack technology. Founded in 2016 and headquartered in San Francisco, the company employs about 1,000 people and has grown steadily from a small startup since its inception.

The company's platform covers the full ML lifecycle, including reinforcement learning from human feedback (RLHF), data generation, model evaluation and safety alignment for large language models and generative models. Its technical work spans AI data infrastructure, machine-learning lifecycle management and safety alignment. In addition, a global contributor network supplies human feedback and data used to train AI models; Scale reports more than 15 billion human decisions processed to train AI models and $1 billion paid out to contributors worldwide.

Scale serves AI labs, government and public-sector bodies, and Fortune 500 enterprises. The company describes its work as mission-driven, focused on developing reliable AI systems for critical decisions, with an emphasis on operational excellence alongside cutting-edge technology and a continuous-improvement approach - summarised internally as the view that better data produces better AI. Its contributor community is distributed worldwide.