Micro1 is the leanest of the fast-growing expert data companies: founded in 2021 as an AI recruiting startup, it turned its vetting technology into a pipeline that supplies top-tier domain experts to frontier AI labs, and reported revenue that roughly doubled in months as training budgets exploded. Growth like that puts a vendor on shortlists, and shortlists produce comparison shopping. This guide covers who competes with micro1 in each lane, and when the better answer is not an expert network at all but the underlying data.
What micro1 is known for
Micro1's engine is automated vetting. Its AI recruiter, Zara, screens applicants at scale, and the company reports accepting roughly the top 1 percent, typically PhDs in fields like medicine, law, and physics, or senior software engineers. Those experts produce demonstrations, evaluations, and RLHF data for AI labs, with the company handling workflow, quality assurance, and payroll compliance across more than 90 countries.
The trajectory has been steep by press accounts: reported annualized revenue around 100 million dollars in late 2025 and around 300 million by spring 2026, on a 35 million dollar Series A raised at a 500 million dollar valuation in September 2025. It has also been broadening from labs toward Fortune 1000 companies building internal copilots, especially in healthcare, legal, and finance.
Teams look for alternatives for the usual reasons: diversification across vendors, wanting a larger or longer-tenured partner for mission-critical programs, needing depth in a specific lane, or discovering that the real gap is training data that exists in the world rather than data experts produce to order.
Alternatives for expert data and demonstrations
The direct competitors are the other expert networks, each with a different recruiting engine. Mercor is the biggest, recruiting working professionals across industries and expanding into evals and RL environments by acquisition. Handshake AI draws PhDs from its university career network. Surge AI is the premium name for frontier-grade human feedback, and Scale AI runs the largest full-stack programs, with the Meta ownership caveat every buyer now weighs. Turing specializes in expert engineers and coding data, AfterQuery pairs expert data with published benchmarks, and Toloka and Prolific come at it from managed crowds and vetted participants; our guide to Prolific alternatives covers that participant-pool side.
For Turing specifically, see our guide to Turing alternatives.
For the human feedback lane in full, see our guide to RLHF data providers.
When the answer is data, not experts
Expert networks sell knowledge work produced to order. That is the right purchase when your model lacks judgment or domain skill. It is the wrong purchase when your model lacks contact with the real world: video models need real motion, voice agents need natural conversation, world models need gameplay and first-person footage, agents need genuine workflow traces. No vetted expert can write that data. It has to be captured from reality and licensed from whoever owns it, a different market covered in our guide to AI training data marketplaces.
The landscape
| Provider | Category | Best for |
|---|---|---|
| Micro1 | Expert recruiting | AI-vetted specialists, lean challenger economics |
| Mercor | Expert marketplace | Domain-expert demonstrations, evals, environments |
| Handshake AI | Expert network | PhD-level reasoning data from a university pipeline |
| Surge AI | RLHF and evaluation | Frontier-grade preference data |
| Scale AI | Full-stack data services | Very large programs, Meta caveat applies |
| Turing | Expert data | Coding data and expert engineers |
| AfterQuery | Expert data and benchmarks | Benchmarked SFT and RLHF data |
| Toloka | Managed global crowds | Scaled human data with global reach |
| Prolific | Vetted participant pool | Representative human feedback and evals |
| Troveo | Licensed data marketplace | Rights-cleared video, audio, gameplay, and business data |
How to choose
The expert networks now differ mainly on three axes. Recruiting engine: AI-driven vetting (micro1), professional marketplaces (Mercor), university pipelines (Handshake AI). Depth versus scale: the premium feedback vendors go deepest per task, the networks go widest per dollar. And maturity: a vendor doubling revenue every few months is impressive and stretched, so confirm your program gets dedicated capacity regardless of who you pick.
And if the gap is world knowledge rather than expert knowledge, stop comparing networks: that budget belongs in licensed data.
Where Troveo fits
Troveo does not run an expert network. Troveo licenses the data experts cannot write: real-world video, audio, gameplay, and business data from more than 7,000 rights holders, cleared for AI training with documentation per asset and delivered training-ready. The two purchases are complements, and serious model programs make both. Browse the catalog in Lens or talk to us about what your model is missing.