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Scale AI Stock (SCAI)

Scale AI offers data labeling services to transform raw data into high-quality training datasets for machine learning models. They combine human-in-the-loop labeling with AI-powered automation, aiming to improve efficiency and accuracy. Scale AI has provided data labeling services for companies like OpenAI and Airbnb.

Scale is an API for training data, providing access to human-powered data for a multitude of use cases.

About Scale AI Stock

Founded

2013

Headquarters

San Francisco, CA, US

Total Funding

28.6B

Industries

Software, Data and Analytics, Science and Engineering

Please note: All shares offered are post the cash dividend paid to shareholders from Meta's investment in Scale AI.

Scale AI is a data-labeling startup that specializes in helping companies curate data for artificial intelligence applications. Scale AI's core offerings include data generation and labeling, model evaluation, foundation model fine-tuning, and enterprise platforms that integrate customer data into advanced generative AI models, all aimed at supporting the end-to-end machine learning lifecycle. The company’s stated mission is to accelerate AI development by delivering better data and enabling faster deployment of performance AI models for a wide range of clients.

Scale AI Press Mentions

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Investors in Scale AI

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Scale AI Management

Leadership team at Scale AI

Interim CEO

Jason Droege

Chief Financial Officer

Dennis Cinelli

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Scale AI Key Facts

  • Strong Revenue Growth and Financial Health: Scale AI is demonstrating robust financial performance. The company's revenue reportedly grew to $870 million by the end of 2024, or 160% revenue growth. It is also projected to more than double its revenue to $2 billion in 2025. This rapid revenue growth, driven by the massive demand for data to train large language models, reinforces its position as a dominant "picks-and-shovels" player in the AI ecosystem.
  • Pivoting to the Physical AI Market: Scale AI has made a strategic and successful pivot from its initial focus on data for text and vision models to the new frontier of Physical AI and robotics. In September 2025, the company announced it is providing a comprehensive data engine that collects and annotates the high-quality datasets needed to train foundation models for humanoid robots and other autonomous systems. This initiative expands its addressable market and positions it at the forefront of the next wave of AI innovation.
  • Strategic Partnerships: Collaborations with companies like Meta and Microsoft, as well as partnerships with industry leaders in autonomous vehicles, healthcare AI, and retail analytics, underscore Scale AI's market influence and ability to drive industry standards in data annotation and AI model training.
  • Competitive Landscape: Rivalry from companies like Labelbox, Appen, and Amazon Mechanical Turk, which offer scalable data labeling solutions and AI training data services, poses a direct challenge to Scale AI's market expansion and customer acquisition efforts. 
  • Layoffs and Client Sentiment: The company has undergone a series of significant layoffs, including a 14% workforce reduction in July 2025 that impacted 200 full-time employees and 500 contractors. These cuts, following a multibillion-dollar investment from Meta, have led to concerns among key clients about potential conflicts of interest and data security. Major partners like Google are reported to have begun exploring alternative vendors, creating a risk of significant customer churn.
  • Legal Battle Over Trade Secret Theft: Scale AI is involved in a federal lawsuit against its rival, Mercor, which it accuses of stealing trade secrets and customer information. The lawsuit, filed in September 2025, alleges that a former Scale employee downloaded over 100 confidential documents and shared them with Mercor while still employed at Scale. This legal battle is a significant operational and reputational risk as it highlights the vulnerability of the company's proprietary data and could damage its brand image as a trusted data partner.

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