Scale AI is a company founded in 2016 by Alexandr Wang and Lucy Guo, initially focused on providing labeled data for self-driving car perception systems before broadening into data annotation services for the wider Machine learning industry, including Computer vision labeling, document processing, and, increasingly through the late 2010s and 2020s, the human feedback data used to train Large language model systems.
Role in the RLHF supply chain
As labs including OpenAI, Anthropic, Google DeepMind, and Meta AI scaled up RLHF and other human-preference based training methods, Scale AI positioned itself as a primary contractor supplying the large, carefully managed workforces of human raters and domain experts needed to produce comparison data, Red teaming (AI) evaluations, and reinforcement signal at the volume frontier labs required. This made the company an important, if largely invisible to end users, part of the pipeline behind ChatGPT, Claude (AI model family), and comparable assistants, and it also supplied labeled and synthetic evaluation data used in AI benchmark and LLM evaluation work, and government and defense contracts for AI systems.
Meta investment and leadership change
In June 2025, Meta announced an investment reported at roughly 14 billion dollars for a roughly 49 percent stake in Scale AI, an unusually large deal for a data-services company and one widely read as Mark Zuckerberg's effort to secure talent and training infrastructure amid an industry-wide race for AI researchers. As part of the arrangement, Alexandr Wang left his chief executive role at Scale to lead a new Meta Superintelligence Labs unit, while Scale continued to operate with new leadership. The deal drew scrutiny from some of Scale's other customers, including labs that had previously relied on Scale for annotation and evaluation work but grew wary of sharing sensitive data pipelines with a close Meta affiliate, and several reportedly reduced or paused their use of Scale's services following the announcement.
Data quality debates
Scale AI's business has also drawn scrutiny over labor practices in its global annotator workforce, often distributed across lower-wage countries and working through the company's Remotasks platform, raising questions similar to those faced by other firms in the Training data and Synthetic data supply chain about pay, working conditions, and psychological exposure to disturbing content during moderation and safety-labeling tasks. The company's central position in the industry nonetheless made it, alongside firms supplying GPU (in AI) compute, one of the more consequential but less publicly visible infrastructure businesses of the generative AI boom.