Scale
Founded Year
2016Stage
Corporate Minority | AliveTotal Raised
$16.403BValuation
$0000Last Raised
$14.8B | 5 mos agoRevenue
$0000Mosaic Score The Mosaic Score is an algorithm that measures the overall financial health and market potential of private companies.
+19 points in the past 30 days
About Scale
Scale provides data labeling, model training, and curation services for artificial intelligence (AI) applications, along with a generative AI platform that uses enterprise data to improve AI models. Scale serves the technology sector, government agencies, and the automotive industry. It was formerly known as Scale Labs. The company was founded in 2016 and is based in San Francisco, California.
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Scale's Product Videos
ESPs containing Scale
The ESP matrix leverages data and analyst insight to identify and rank leading companies in a given technology landscape.
The defense & national security AI copilots market employs AI technologies to support decision-making, operational efficiency, and strategic planning in defense and security sectors. These AI copilots assist military personnel and security analysts by providing real-time data analysis, threat detection, intelligence gathering, and mission planning. They automate routine tasks, offer predictive ins…
Scale named as Highflier among 15 other companies, including Palantir, C3 AI, and Microsoft.
Scale's Products & Differentiators
Scale Rapid
Scale Rapid is self-serve, on-demand labeling to train AI with high quality ground truth data and enables machine learning engineers and researchers to receive high quality labels and instruction feedback in a matter of hours and scale to production volumes in days. With Rapid, customers can create their labeling projects, upload data labeling via UI or API, design and submit their labeling instructions and direct quality improvements with new or updated evaluation tasks. This allows customers to unlock early AI/ML prototyping as well as more insight and control over the labeling workflow, as customers can receive prompt feedback on labeling instructions and potential edge cases for rapid iteration.
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Research containing Scale
Get data-driven expert analysis from the CB Insights Intelligence Unit.
CB Insights Intelligence Analysts have mentioned Scale in 24 CB Insights research briefs, most recently on Oct 15, 2025.
Oct 15, 2025 report
State of Venture Q3’25 Report
Sep 10, 2025 report
Book of Scouting Reports: Industrial AI Agents & Copilots
Aug 25, 2025 report
State of Tech Exits H1’25
Aug 22, 2025
The top angel investors in AI
Aug 14, 2025
310+ AI companies transforming government
Jul 31, 2025 report
State of AI Q2’25 Report
Jul 10, 2025 report
State of Venture Q2’25 ReportExpert Collections containing Scale
Expert Collections are analyst-curated lists that highlight the companies you need to know in the most important technology spaces.
Scale is included in 7 Expert Collections, including Auto Tech.
Auto Tech
2,663 items
Companies working on automotive technology, which includes vehicle connectivity, autonomous driving technology, and electric vehicle technology. This includes EV manufacturers, autonomous driving developers, and companies supporting the rise of the software-defined vehicles.
Unicorns- Billion Dollar Startups
1,297 items
Artificial Intelligence (AI)
37,333 items
Companies developing artificial intelligence solutions, including cross-industry applications, industry-specific products, and AI infrastructure solutions.
Tech IPO Pipeline
539 items
Track and capture company information and workflow.
AI 100 (All Winners 2018-2025)
100 items
Winners of CB Insights' 5th annual AI 100, a list of the 100 most promising private AI companies in the world.
Generative AI
2,951 items
Companies working on generative AI applications and infrastructure.
Scale Patents
Scale has filed 18 patents.
The 3 most popular patent topics include:
- artificial neural networks
- computer vision
- molecular biology
Application Date | Grant Date | Title | Related Topics | Status |
|---|---|---|---|---|
1/14/2022 | 2/25/2025 | Global Positioning System, Live-preview digital cameras, Color space, GPS navigation devices, Avionics | Grant |
Application Date | 1/14/2022 |
|---|---|
Grant Date | 2/25/2025 |
Title | |
Related Topics | Global Positioning System, Live-preview digital cameras, Color space, GPS navigation devices, Avionics |
Status | Grant |
Latest Scale News
Nov 11, 2025
Meta chief AI officer Alexandr Wang has shared advice for young teens who want to be successful in the future. The 28 year old AI executive had earlier led Scale AI before Meta took a 49% stake in the AI startup. Speaking at the TBPN podcast, Wang said that the current 13 year old's should follow the example of Bill Gates and Mark Zuckerberg to learn the new technology to have a ‘huge advantage' in the future. Wang drew the parallels between the current AI age to the time when the personal computers came and said that the young adults may even have an edge over the adults. Alexandr Wang's advice to 13 year old: “It's almost like when personal computers first came about, or just computing in general, the people who spent the most time with them, or who grew up with it had this immense advantage in future economy like Bill Gates or even the Mark Zuckerberg of the world. I think that moment is happening right now” “If you are like 13 years old, You should spend all your time coding and just, you know, that's how you live your life” he added “I think it's actually in some ways an incredible moment of discontinuity where if you just happen to spend like 10,000 hours playing with the tools and figure out how to use them better than other people, that's a huge advantage” he further noted Wang's advice to young adults is to spend all their time learning how to use the new AI tools and ‘vibe code' new things with them. In case you aren't aware, vibe coding is a new approach to software development where developers use natural language prompts to get a product developed via an AI tool. The term was cointed by OpenAI cofounder Andrej Karpathy with the idea that developers can use AI to "fully give in to the vibes" and “forget the code even exists.” Notably, Wang became the youngest self-made billionare at the age of 25 by embracing the power of AI with his startup Scale AI that he had launched at the age of 19. Earlier this year, Zuckerberg's Meta invested $14.3 billion in Scale AI which valued the startup at over $29 billion
Scale Frequently Asked Questions (FAQ)
When was Scale founded?
Scale was founded in 2016.
Where is Scale's headquarters?
Scale's headquarters is located at 303 2nd Street, San Francisco.
What is Scale's latest funding round?
Scale's latest funding round is Corporate Minority.
How much did Scale raise?
Scale raised a total of $16.403B.
Who are the investors of Scale?
Investors of Scale include Meta, Y Combinator, Index Ventures, Accel, Founders Fund and 63 more.
Who are Scale's competitors?
Competitors of Scale include Superb AI, TaskUs, SuperAnnotate, Humans in the Loop, Encord and 7 more.
What products does Scale offer?
Scale's products include Scale Rapid and 4 more.
Who are Scale's customers?
Customers of Scale include Brex, iRobot, Flexport, Toyota Research Institute (TRI) and U.S. Air Force.
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Compare Scale to Competitors
Labelbox provides services and software for artificial intelligence (AI) data management and model evaluation within the artificial intelligence and machine learning sectors. The company offers managed labeling services, a platform for building data factories, and a network for hiring experienced AI trainers. Labelbox serves AI teams and organizations seeking to improve their model training and evaluation. It was founded in 2018 and is based in San Francisco, California.
24x7Offshoring is involved in artificial intelligence (AI) and machine learning workflows within the technology sector. The company provides services for data collection, data labeling, localization, and outsourced services, with a focus on AI training models. It serves sectors such as science, technology, education, medical research, and public service. It was founded in 2020 and is based in New Delhi, India.
Toloka focuses on artificial intelligence development and large language model fine-tuning within the tech industry. The company provides data across various domains and languages for machine learning processes, including supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF). Toloka offers services including data labeling and AI model evaluation. It was founded in 2014 and is based in Schiphol, Netherlands.
Sama specializes in providing high-accuracy data annotation solutions for the development of computer vision AI models across various industries. The company offers a suite of services, including image and video annotation, 3D point cloud labeling, and data validation, to support machine learning professionals and AI team leads. Sama primarily serves sectors such as ADAS and autonomous vehicles, retail and e-commerce, consumer tech and media, robotics and manufacturing, and agriculture and food. It was founded in 2008 and is based in San Francisco, California.
V7 operates in document processing and data labeling within the artificial intelligence and machine learning sectors. The company provides tools for automating workflows, extracting data from various file formats, and offering artificial intelligence (AI) assisted labeling services. Its platforms aim to improve efficiency by automating tasks and ensuring training data for AI models. The company was founded in 2018 and is based in London, United Kingdom.
iMerit provides artificial intelligence (AI) data solutions, focusing on data annotation and model fine-tuning for machine learning and artificial intelligence applications. The company offers services including computer vision, natural language processing, and content services for preparing data for artificial intelligence (AI) training and development. iMerit's clientele includes large enterprises in sectors such as healthcare, autonomous vehicles, and financial services. It was founded in 2012 and is based in San Jose, California.
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