Updated 8 Nov 2026
Toloka vs Appen, by the numbers.
By revenue, Appen is the larger: $249M (12 months to Jun 2026), against Toloka's $26.4M (FY2024). Toloka's figure is the older by 18 months; no later one is on record.
Both sell RL environments, datasets, expert and human data, evaluations and benchmarks and annotation. Only Appen sells labeling software. Every figure below is linked to the filing or article it comes from; what each sells is in its own words, from its own pages.
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Side by side
Revenue over twelve months, the newest valuation, disclosed funding and what each says it does.
| Toloka | Appen | |
|---|---|---|
| Toloka | Appen | |
| Place on the rankings | #18 of 78 | #11 of 78 |
| Ranked on | $26.4M Revenue, FY2024 | $249M Revenue, 12 months to Jun 2026 |
| Revenue, twelve months | $26.4M FY2024 over time | $249M 12 months to Jun 2026 over time |
| Newest valuation | Not on record | Not on record |
| Disclosed funding | $72M in 1 record | Not on record |
| Sells | RL environments, Datasets, Expert and human data, Evaluations and benchmarks, Annotation | Labeling software, Datasets, Expert and human data, RL environments, Evaluations and benchmarks, Annotation |
| Works on | Coding, Computer use, Business work, Finance, Legal, Medical, Science, Math, Security, Robotics, Images and video, Creative, Languages | Coding, Business work, Finance, Legal, Medical, Science, Robotics, Speech and audio, Images and video, Languages |
| Made from | Recorded from people and the real world, Made by experts and contractors, Generated | Recorded from people and the real world, Made by experts and contractors, Licensed from its owners, Generated |
| Takes data from companies | Does not say so | Its own programme |
| Headquarters | Amsterdam, Netherlands | Kirkland, Washington, US and Sydney, New South Wales, Australia (dual headquarters) |
| Founded | 2014 | 1996 |
| In its own words | “Toloka is a provider of expertly curated data for AI agents and models development.” Its page | “We deliver the expert-validated data that trains frontier models, ensuring AI systems understand nuance, context, and complexity at scale.” Its page |
- The rule.
- Each company is ranked on the first of these it has on record: its revenue over twelve months (a run rate or a year as published, or its last four quarters added up; an AI segment where the rest of its business is not AI data), then its newest valuation, then the money it disclosed raising. No company pays for a place. The full method and every change to it.
- Twelve months.
- A run rate or ARR is the company's own annualised figure; a year is the year it published. Gross revenue of a human data company includes what it pays its experts.
- Pays companies for data.
- "Through our introductions": it takes companies' data through AIData.Broker's introductions and pays us a referral fee when one goes ahead. That never moves its place: the order is the money on record. "Its own programme": a published programme for buying data. "Says it buys data": its own words, linked.
- Why this pair.
- People search for this comparison: Google suggests it, read on 8 Nov 2026. Neither company asked for or paid for this page.
Selling your company's data to Toloka or Appen
What each says it pays a company for its data, what it wants and when it pays, in its own published terms.
| Toloka | Appen | |
|---|---|---|
| Takes data from companies | Does not say so | Its own programme |
| What it says it pays | Not published | Not published |
| What it wants | Not published | Operational documentation (procedures, wikis, QA), decision and escalation records (support desk, ITSM, CRM, project tracking, messaging) and systems of record (ERP, warehouse, contracts, HR, procurement). |
| When it pays | Not published | "Payment is on acceptance rather than submission." |
You need not choose one: AIData.Broker values a company's data free and introduces it to every buyer whose own rules take it. Value your data
On the same rankings
The lists both are ranked on, with each one's place.
- Synthetic training data companiesToloka #5, Appen #2 of 15
- Best AI data collection companiesToloka #6, Appen #3 of 30
- Robotics training data companiesToloka #6, Appen #4 of 31
- Multilingual training data providersToloka #7, Appen #4 of 17
- Finance AI training data companiesToloka #9, Appen #6 of 25
- Best data labeling companiesToloka #9, Appen #7 of 40
- Legal AI training data companiesToloka #10, Appen #7 of 17
- Video and image training data companiesToloka #10, Appen #6 of 37
- Medical AI training data companiesToloka #11, Appen #9 of 26
- RL environment companiesToloka #12, Appen #9 of 36
- Coding data companies for AIToloka #14, Appen #10 of 33
- Best AI data labs and human data companiesToloka #16, Appen #11 of 41
- AI evaluation companiesToloka #16, Appen #10 of 60
- Best AI training data providersToloka #17, Appen #10 of 53
The latest money moves
The newest rounds, valuations and revenue figures of the two, each linked to its record.
- 27 Aug 2026Appen reported $249M revenue (12 months to Jun 2026)
- 7 May 2025Toloka raised $72M
- 30 Apr 2025Toloka reported $26.4M revenue (FY2024)
- 12 Mar 2024Appen was acquired by Innodata
The questions people ask
- Is Toloka bigger than Appen?
- By revenue, Appen is the larger: $249M (12 months to Jun 2026), against Toloka's $26.4M (FY2024). Toloka's figure is the older by 18 months; no later one is on record.
- What is the difference between Toloka and Appen?
- Toloka provides curated data, RL environments and evaluations, made with human experts, for AI agents and models. Appen provides AI training data, data annotation and model evaluation to AI labs and other AI teams. Both sell RL environments, datasets, expert and human data, evaluations and benchmarks and annotation. Only Appen sells labeling software.
- Which raised more money, Toloka or Appen?
- Toloka: $72M disclosed. Appen: no disclosed round on record.
- Do Toloka and Appen buy data from companies?
- Toloka does not say it buys data from companies. Appen takes data from the companies that hold it, through a published programme.
More comparisons
Each company against its whole field, and the other comparisons people search.