Mercor Gains Momentum in AI Data Race as Micro1 Raises $500M at $500M Valuation

A major shift is unfolding in the AI data market as leading AI labs like OpenAI and Google DeepMind cut ties with Scale AI following Meta’s $14 billion investment in the company and the hiring of its CEO. Concerns over data security and potential leaks of proprietary research to Meta have prompted these departures, creating a vacuum that startups are rushing to fill. Among the beneficiaries is Mercor, an AI hiring platform founded less than three years ago, which is now attracting investor interest with reported offers for a Series C at a $10 billion valuation—just seven months after raising a Series B at $2 billion. Mercor claims it’s on track to reach $500 million in annual recurring revenue (ARR) faster than Anysphere, the company behind Cursor, which hit that milestone a year after launch. Another strong contender is Surge, a larger competitor that reportedly generated $1.2 billion in revenue in 2024 without venture capital backing and is now seeking a $25 billion valuation in new fundraising talks. Despite Surge’s lead, Mercor’s rapid growth is posing a serious challenge to established players. Meanwhile, Micro1, a three-year-old startup focused on managing human contractors for AI data labeling and training, has raised a $35 million Series A led by O1 Advisors, co-founded by former Twitter executives Dick Costolo and Adam Bain. The round values Micro1 at $500 million. CEO Ali Ansari, just 24 years old, says the company is now generating $50 million in ARR—up from $7 million at the start of 2025—and is working with major AI labs including Microsoft and Fortune 100 companies. The shift in demand is key: while Scale AI initially thrived by hiring low-cost global contractors for basic data labeling, AI labs now need higher-quality, domain-specific data. This means recruiting experts—such as senior engineers, doctors, and professional writers—rather than general labor. Micro1’s solution is Zara, an AI-powered recruiter that interviews and vets candidates, helping the company bring in thousands of experts, including professors from Stanford and Harvard. Beyond labeling, the next frontier is creating simulated training environments for AI agents—virtual spaces where AI can learn complex tasks through interaction. Micro1 is expanding into this space, aligning with a growing industry trend. These environments are becoming critical for training autonomous AI agents, and startups that can deliver them are poised for major growth. Despite the competition, the market remains open. AI labs are increasingly working with multiple data providers, as no single company can meet all their needs. This multi-vendor approach ensures room for growth across the board. The AI data market is evolving fast, driven by new demands for expert-level data and advanced training environments. Startups like Micro1, Mercor, and Surge are stepping into the gap left by Scale AI’s controversial ties to Meta, offering not just data labeling but also expert recruitment and next-gen simulation tools. As AI models continue to advance, the demand for high-quality, human-in-the-loop data will only grow—making these startups essential players in the future of AI development.