How we researched and ranked training data companies
Last updated: November 9, 2026
What we did
- Built a candidate list. We started with companies that repeatedly appear in 2025–2026 reporting and buyer discussions of AI training data, RLHF and evaluation vendors.
- Read each company's own site. On November 9, 2026 we read the official homepage and the relevant product or pricing pages for every listed company. We recorded what they currently offer, who they say they serve and how they price.
- Cross-checked with reporting. We used reputable outlets (Associated Press, Forbes, Bloomberg Law, CNBC) for ownership, funding and revenue facts. Where we cite a revenue figure from a third-party market register, we label it as reported.
- Ranked with a weighted judgment. We did not use a single formula.
Ranking criteria
- Frontier relevance (highest weight): Evidence of work on current post-training needs such as expert RLHF/SFT, evaluations and RL environments, including named lab customers or partners.
- Breadth and depth of data types: Coverage of languages, modalities, domains, and physical-AI or robotics data.
- Scale and staying power: Reported revenue, funding and years in operation.
- Transparency: Public documentation, benchmarks, published research and pricing.
- Buyer fit: Whether a typical buyer, from a frontier lab to an enterprise team, can actually engage the vendor.
What we did not do
- We did not buy or test any service hands-on, and we make no claims of testing.
- We did not collect or publish user reviews.
- We do not accept payment for placement, and no company reviewed this list before it was published.
- We did not independently audit company claims such as workforce size, accuracy rates or customer counts. These are attributed to the company in the text.
Why some companies are not listed
We listed only companies whose current official pages clearly describe training-data services for buyers. Some well-known names were left out because their public pages are aimed mainly at recruiting contributors, which did not give us enough buyer-facing evidence. We would rather list fewer companies than pad the ranking.
Limitations
Most vendors are private and do not disclose comparable metrics. Revenue periods differ, and some companies mix data work with staffing or consulting. The order within the middle of the list depends on the use case, so read the "Best for" line, not just the rank number.
Updates
We review the list when material changes happen, such as funding, acquisitions (for example, EXL's acquisition of iMerit), product launches or pricing changes. The date at the top shows the last full review.