Scale AI was founded in 2016 by Alexandr Wang, who was just 19 years old at the time, making him one of the youngest billionaire founders in tech. Based in San Francisco, the company has raised over $600 million in funding and reached a valuation above $14 billion.
Scale’s original business was data labeling — the unglamorous but essential work of annotating images, text, and other data so AI models can learn from it. They built a platform that combines human workers with automation to label data at high quality and speed. This turned out to be an incredibly well-timed bet, as the AI boom created massive demand for labeled training data.
Scale’s client list is a who’s-who of AI: OpenAI, Meta, Microsoft, Toyota, General Motors, and the US Department of Defense all use Scale for data preparation. The company expanded beyond labeling into broader AI infrastructure, offering model evaluation, RLHF (reinforcement learning from human feedback) data, and enterprise AI deployment tools.
Scale’s government business has grown significantly, with contracts across defense and intelligence agencies. The company launched Donovan, an AI platform specifically for government and defense use cases. Wang has become an active voice in AI policy discussions, particularly around maintaining US competitiveness in AI development. Scale essentially positioned itself as the “picks and shovels” company of the AI gold rush — not building the models, but providing the critical data infrastructure that makes them work.
