Scale
Prepare training datasets and evaluate how models perform.
Scale AI Funding History
Scale AI provides data infrastructure for developing and evaluating AI systems. Its work includes data labeling and evaluation for customers building foundation models and other AI applications, connecting human input and data operations with model training and assessment.
Company Overview
Founded 2016 · San Francisco, California
Official WebsiteScale AI Funding Timeline
Series F
$1B · $13.8B valuation
The deal combined new capital with secondary sales of existing shares.
Led by Accel. Participation included Amazon, Meta, Index Ventures, Cisco Investments, ServiceNow Ventures.
Source · techcrunch.com ↗Series E
$325M · $7.3B valuation
Scale had started with autonomous-vehicle customers. At the time of the round, CEO Alexandr Wang said demand was growing across other industries and in government.
Led by Dragoneer Investment Group, Greenoaks Capital, Tiger Global.
Source · scale.com ↗Series D
$155M · $3.5B valuation
Scale said the funding would grow its team and extend its tools for building and evaluating AI systems.
Led by Tiger Global.
Source · techcrunch.com ↗Series C
$100M · $1B valuation
Scale was building out its training-data platform, which customers already used for mapping, robotics, and e-commerce as well as autonomous vehicles.
Led by Founders Fund.
Source · scale.com ↗Series B
$18M
Scale was using its data-labeling service to turn self-driving car footage into training data. Index identified autonomous vehicles as a promising market for the service.
Led by Index Ventures. Participation included Accel, Y Combinator.
Source · indexventures.com ↗Series A
$4.5M
Scale’s later Series B announcement dated this financing to May 2017, before Accel publicly announced its investment.
Led by Accel. Participation included Y Combinator.
Source · medium.com ↗Strategic Private Placement (Meta)
$14.3B · $29B valuation
Scale said it would use some proceeds to develop products and strengthen customer partnerships, and distribute some to shareholders and vested equity holders. Founder Alexandr Wang joined Meta.
Led by Meta.
Source · reuters.com ↗
Scale AI Founding Team
Scale AI started in 2016 with a focus on supplying labeled data for machine learning. Alexandr Wang and Lucy Guo started the company through Y Combinator.
Scale AI Products
Scale AI Company Development
Data Work Beyond Labeling
Scale grew from producing labeled datasets into evaluating how models behave. That change matters to a customer commissioning work after a model is already in use, when the main task may be to specify a failure mode and assemble examples that expose it.
Scale AI Competitive Landscape
Commissioning Data and Testing Behavior
Scale and Snorkel AI both supply data and evaluation work. Scale's services extend from annotation to model evaluation, while Snorkel's data-factory approach includes simulated environments that let teams define the tasks and conditions their models should encounter.
FAQ
Why did Meta's stake get structured as exactly 49% non-voting?
To stay under the regulatory line a controlling stake would cross: ~US$14.3B for ~49% with no voting power — one of Meta's largest deals since WhatsApp — engineered to avoid scrutiny. The structure also preserved the commercial fiction that mattered: Scale's customers were Meta's rivals. xAI's all-stock absorptions of X Corp and then SpaceX made control the point; here, avoiding it was the deal.
Why did Google, OpenAI and Microsoft stop working with Scale after June 2025?
Because the shared data layer stopped looking neutral: Google alone was worth roughly US$150M of 2024 spend, and with Meta holding ~49% and founder Alexandr Wang moving to lead Meta's superintelligence division — board seat retained — every rival read the vendor as an arm of a competitor. That churn is why the ~US$29B mark is really a bet on neutrality the deal itself destabilized.
What does Scale's valuation ladder measure besides Scale?
The boom's phases: US$1B (2019) on autonomous-vehicle labeling, US$3.5B (2020), US$7.3B (2021) in the surge, US$13.8B (2024) on model-era data demand — each step a distinct industry moment. The last step is the outlier: ~US$29B priced Meta's strategic need rather than the standalone market, about 33x Scale's ~US$870M of 2024 revenue, set by a buyer who wanted exclusivity more than returns.
Is Alexandr Wang still Scale's CEO?
No — since June 2025 he has led Meta's superintelligence division while keeping his Scale board seat, with Jason Droege serving as interim CEO. That triangle — founder employed by the largest shareholder, an operating executive in the top job, Meta at ~49% non-voting — is why the status line reads 'independent,' and why that single word now carries so much of the investment case.
How did Scale grow from a YC company into an AI data provider?
By catching each wave's data problem in turn: autonomous vehicles (the 2019 unicorn round), then government and enterprise contracts, then frontier-model labeling — with Amazon and Meta joining the 2024 Series F syndicate as customer-investors. The 2025 irony closed the arc: those customer-investors became customers-lost, flipping the story from picks-and-shovels to contested neutrality.
Why is customer data handling a separate question from Scale's ownership?
An equity stake does not describe who can access a customer's datasets. Scale's ownership history and data-services business raise different questions. To assess data handling, examine the relevant contractual and security arrangements rather than inferring access rights from the cap table alone.