Updated 8 Nov 2026
Labelbox vs Scale AI, by the numbers.
Scale AI ranks higher by the money on record: its revenue is on record, $870M (FY2024), and Labelbox's is not, so Labelbox is ranked on a $1.3B valuation (2026).
Both sell RL environments, expert and human data and evaluations and benchmarks. Only Scale AI sells labeling software, datasets, annotation and simulation. 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.
| Labelbox | Scale AI | |
|---|---|---|
| Labelbox | Scale AI | |
| Place on the rankings | #21 of 78 | #5 of 78 |
| Ranked on | $1.3B Valuation, 2026 | $870M Revenue, FY2024 |
| Revenue, twelve months | Not on record | $870M FY2024 over time |
| Newest valuation | $1.3B Oct 2026 | $29B Jun 2025 |
| Disclosed funding | $100M in 1 record | $15.3B in 2 records |
| Sells | RL environments, Expert and human data, Evaluations and benchmarks | Labeling software, RL environments, Datasets, Expert and human data, Evaluations and benchmarks, Annotation, Simulation |
| Works on | Coding, Business work, Finance, Legal, Medical, Robotics, Speech and audio, Images and video | Coding, Computer use, Business work, Robotics, Medical |
| Made from | Recorded from people and the real world, Made by experts and contractors | Made by experts and contractors, Replicas of real software |
| Takes data from companies | Its own programme | Through our introductions |
| Headquarters | San Francisco, California, US | San Francisco, California, US |
| Founded | 2018 | 2016 |
| In its own words | “Labelbox builds the environments frontier labs train AI on, and the agents engineering and research teams hand their backlog to.” Its page | “Scale delivers proven data, evaluations, and outcomes to AI labs, governments, and the Fortune 500.” 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 Labelbox or Scale AI
What each says it pays a company for its data, what it wants and when it pays, in its own published terms.
| Labelbox | Scale AI | |
|---|---|---|
| Takes data from companies | Its own programme | Through our introductions |
| What it says it pays | $50K to $1M Labelbox Prism, home page, 5 Nov 2026 | $10K to $1M Scale AI, data partnership page, 7 Nov 2026 |
| What it wants | Work documents (coding sessions, scientific and financial workflows, research traces) and operational systems (Salesforce, Jira, Slack, SAP, ServiceNow, Zendesk, CAD, financial workbooks). Its page marks financial and scientific reasoning traces and cross-system workflow data as urgent. | Structured, de-identified records from data warehouses, chat, email, documents, work tools and business platforms. |
| When it pays | "From first call to first wire in under 21 days", with a written quote within 48 hours of scoping. It pays an upfront licensing fee at signing plus a revenue share on downstream use. | Not published. A scoping call first; a partnership can begin with a very limited scope. |
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.
- Robotics training data companiesLabelbox #8, Scale AI #1 of 31
- Medical AI training data companiesLabelbox #12, Scale AI #4 of 26
- Coding data companies for AILabelbox #15, Scale AI #5 of 33
- RL environment companiesLabelbox #15, Scale AI #5 of 36
- Best AI data labs and human data companiesLabelbox #17, Scale AI #5 of 41
- AI evaluation companiesLabelbox #19, Scale AI #5 of 60
The latest money moves
The newest rounds, valuations and revenue figures of the two, each linked to its record.
- 14 Oct 2026Labelbox raised $100M at a $1.3B valuation
- 10 Feb 2026Labelbox was acquired by Labelbox
- 12 Jun 2025Scale AI raised $14.3B at a $29B valuation
- 8 Jun 2025Scale AI reported $870M revenue (FY2024)
- 21 May 2024Scale AI raised $1B at a $13.8B valuation
The questions people ask
- Is Labelbox bigger than Scale AI?
- Scale AI ranks higher by the money on record: its revenue is on record, $870M (FY2024), and Labelbox's is not, so Labelbox is ranked on a $1.3B valuation (2026).
- What is the difference between Labelbox and Scale AI?
- Labelbox builds the environments and expert data frontier AI labs train on, and AI agents for engineering and research teams. Scale AI provides training data, RL environments, and model evaluations to AI labs, governments, and enterprises. Both sell RL environments, expert and human data and evaluations and benchmarks. Only Scale AI sells labeling software, datasets, annotation and simulation.
- Which raised more money, Labelbox or Scale AI?
- Labelbox: $100M disclosed, valued at $1.3B (2026). Scale AI: $15.3B disclosed, valued at $29B (2025).
- Do Labelbox and Scale AI buy data from companies?
- Labelbox takes data from the companies that hold it, through a published programme. Scale AI takes data from the companies that hold it, through a published programme.
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