Scale AI produces and labels data used to train large language models and other AI systems. The company has begun hiring PhD scientists and senior software engineers to generate higher-quality data for frontier AI labs. Scale confirmed a significant investment from Meta that values the startup at $29 billion. The company said Meta’s investment will be used to pay investors and shareholders and to fuel growth, and emphasized it remains an independent entity. Co-founder and CEO Alexandr Wang is stepping down to join Meta, with Jason Droege — Scale’s chief strategy officer — serving as interim CEO; Wang will remain on Scale’s board as a director. The article notes Scale raised $1 billion last year from investors including Amazon and Meta at a $13.8 billion valuation and that SingalFire data showed a 4.3% loss of top talent last year. Scale AI provides data-labeling and annotation services, meshing machine learning with human-in-the-loop oversight to prepare large, often unstructured, datasets for AI training across industries. It specializes for different use cases such as camera and lidar data for self-driving cars and annotated text for NLP. Customers include Microsoft, Toyota, GM, Meta, the U.S. Department of Defense and OpenAI. Founded in 2016, the company says it will use new capital to accelerate the creation of “frontier data” and support scaling large language models toward future generational advances. The company experienced a 20% workforce reduction last year amid broader headwinds. After the Series F, Scale’s valuation doubled relative to earlier rounds, reflecting strong investor interest in data infrastructure for AI. Scale AI builds data-labeling and information-curation services for AI applications, serving enterprise clients across industries. Founded in 2016 by Alexandr Wang while he was at MIT, the company counts customers including General Motors, Nvidia, Nuro and Zoox. TechCrunch reports Scale is a break-even business. The company plans a large-scale increase in headcount as it builds new products and expands into additional markets. Alexandr Wang, a former Quora and Addepar employee, remains CEO as Scale scales its offerings. Scale AI is a four-year-old startup that built a visual data-labeling platform combining software and tens of thousands of human contractors to prepare image, text, voice and video data for machine-learning models. Its customer base began with autonomous-vehicle companies and now includes legacy automakers (GM, Toyota), chipmaker Nvidia, AV startups (Nuro, Zoox) and enterprise customers such as Airbnb, OpenAI, DoorDash and Pinterest. The company has expanded beyond labeling with Nucleus, an AI development platform for organizing, curating and managing large datasets, and acquired a four-person startup called Helia to support real-time video and neural-network training work. Scale is focused on building Nucleus into a fully integrated platform and on entering new markets and adding product and platform capabilities. Financially, Scale raised $155 million in its latest funding round, pushing its post-money valuation to more than $3.5 billion, and the company says it is now break-even. It plans to grow headcount from about 200 employees to roughly 350 by the end of next year (not counting its contractors). Scale AI supplies labeled training data (text, audio, images and video) to train machine-learning systems, using a mix of software and human annotation. The company delivers data via an API and applies human contractors to segment images, label frames, and add contextual language annotations to improve model accuracy. It combines a relatively small full-time staff (around 100 employees) with nearly 30,000 contractors who perform the bulk of labeling and quality control. Customers named in the article include Waymo, OpenAI, Airbnb and Lyft. The startup is three years old, and CEO Alexandr Wang (22) said the new funding will let Scale capitalize on its ambitions and that he hopes it will be the company’s last fundraise. While Scale aims to reduce reliance on humans over time through automation, the article emphasizes that human insight remains critical today to minimize bias and ensure high-quality labels, and Bloomberg reported the round values the company above $1 billion.

Total raised

$15.9B

Funding rounds

7

Latest round

Equity

Latest activity

Jun 2025