Scale
Founded Year
2016Stage
Corporate Minority | AliveTotal Raised
$16.403BValuation
$0000Last Raised
$14.8B | 1 mo agoRevenue
$0000Mosaic Score The Mosaic Score is an algorithm that measures the overall financial health and market potential of private companies.
+8 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 data annotation market provides services and platforms for labeling large volumes of structured and unstructured data to train AI and machine learning models. This market includes text classification, image annotation, video labeling, audio transcription, and semantic segmentation solutions, with offerings ranging from fully managed human annotation services to AI-assisted automation platforms…
Scale named as Leader among 15 other companies, including Capgemini, Google Cloud, and IBM.
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 15 CB Insights research briefs, most recently on Mar 21, 2025.
Oct 4, 2024
The 3 generative AI markets most ripe for exits
Jul 31, 2024 report
State of CVC Q2’24 Report
Jul 30, 2024 report
State of AI Q2’24 Report
Jul 3, 2024 report
State of Venture Q2’24 Report
Expert 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 6 Expert Collections, including Auto Tech.
Auto Tech
2,557 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
1,277 items
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
2,272 items
Companies working on generative AI applications and infrastructure.
Artificial Intelligence
9,913 items
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
Jul 1, 2025
Nesta segunda-feira (30), o cofundador e CEO da Meta , Mark Zuckerberg , anunciou grande reestruturação no setor de inteligência artificial (IA) da empresa. A ideia do executivo é o de desenvolver a chamada “superinteligência” de IA , sistemas que realizam tarefas tão bem, ou, ainda, melhor do que humanos . Big tech reestruturou completamente seu setor de IA (Imagem: miss.cabul/Shutterstock) O anúncio de Zuckerberg foi realizado via e-mail enviado aos funcionários da dona de Facebook, Instagram, Threads e WhatsApp, informou a Bloomberg . O que Zuckerberg disse no e-mail endereçado aos funcionários da Meta? Confira uma recapitulação da reestruturação da Meta, que o Olhar Digital já tinha antecipado aqui : Segundo Zuckerberg, o setor de IA da Meta passa a ser responsabilidade de um novo grupo, chamado Meta Superintelligence Labs; Essa nova área será comandada por Alexandr Wang, ex-CEO da Scale AI, empresa de rotulagem de dados; O executivo, segundo Zuckerberg, será diretor de IA na nova divisão; Ainda, Nat Friedman, ex-CEO do GitHub, firmará parceria com Wang para liderar o grupo, além de chefiar o trabalho da Meta em produtos de IA e pesquisa aplicada; Essas informações foram obtidas pela Bloomberg em um memorando interno da Meta. “À medida que o ritmo do progresso da IA acelera, o desenvolvimento da superinteligência está se tornando visível. Acredito que este será o início de uma nova era para a humanidade e estou totalmente comprometido em fazer o que for preciso para que a Meta lidere o caminho”, escreveu Zuckerberg no e-mail. Leia mais: Big tech deixou metaverso de lado para priorizar a IA Este ano, a IA virou “obsessão” para Zuckerberg, ao passo em que compete com outros grandes players do mercado, como OpenAI e Google, na luta para criar modelos de última geração e assistentes de IA que ele imagina que, um dia, serão onipresentes. Tal investimento foi realizado em infraestruturas, como chips e data centers, bem como no recrutamento de pessoal e aquisições. Processo de investimento No início de junho, a Meta investiu US$ 14,3 bilhões (R$ 77,67 bilhões, na conversão direta) na Scale AI, além de ter contratado Wang no meio do caminho. Ainda, a big tech negociou com a Perplexity e a Runway AI, sem contar que ela deve, em breve, adquirir a startup que usa IA para replicar vozes PlayAI. Indo além dessa reestruturação, Zuckerberg comunicou 11 contratações no setor de IA. Isso inclui pesquisadores de OpenAI, Anthropic e Google. Ex-pesquisadores do Google DeepMind foram recrutados por Zuckerberg (Imagem: Photo For Everything/Shutterstock) No “balaio” de contratações, estão: Os ex-pesquisadores do Google DeepMind, Jack Rae e Pei Sun; Diversos pesquisadores da OpenAI, como Jiahui Yu, Shuchao Bi, Shengjia Zhao e Hongyu Ren; Joel Pobar, da Anthropic, que já passou pela Meta no passado, tendo ficado lá por mais de uma década.
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, Accel, Index Ventures, Coatue and 33 more.
Who are Scale's competitors?
Competitors of Scale include Snorkel AI, Chalk, Surge AI, V7, MetAI 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.
Snorkel AI specializes in data-centric artificial intelligence solutions for the enterprise domain. The company offers an AI data development platform that enables the development of AI applications by programmatically labeling and curating data, fine-tuning large language models, and building specialized AI models. It primarily serves sectors such as banking, healthcare, government, insurance, and telecom with its AI technology. The company was founded in 2019 and is based in Redwood City, California.
Datasaur specializes in NLP data labeling and LLM development platforms. It offers a suite of tools for customizable data annotation, quality control management, and automation to enhance the efficiency of NLP and LLM projects. Datasaur's products are designed to meet the complex needs of industries such as legal, healthcare, financial, media, e-commerce, and government. It was founded in 2019 and is based in Livermore, California.
CloudFactory is a company that operates within the artificial intelligence sector, providing data annotation, model monitoring, and oversight services. They offer services to aid in the development and deployment of AI models for various industries. It was founded in 2010 and is based in Reading, England.
Hive provides cloud-based AI solutions in the fields of content understanding, search, and generation. The company offers a suite of pre-trained AI models and turnkey software for tasks such as content moderation, brand protection, and data labeling. Hive's technology is widely used in platform integrity, sponsorship measurement, and context-based advertising, among other applications. It was founded in 2013 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.
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