Scale AI

These companies are built to exhibit resilience amid volatility—and deliver better-than-average growth in the long term.

The Future 50

These 50 companies exemplify the innovation, progress, and potential of AI.

AI Innovators 2025-Scale

Fortune 50 AI Innovators

The essential guide to a sector that’s now attracting one out of every four startup investment dollars.

AI-Innovators-2023-Scale

AI automates, but to get to the sophistication of chatbots like ChatGPT requires humans—and a lot of them. While the LLMs behind OpenAI's ChatGPT or Anthropic's Claude learn the statistical connections in language on their own, to guide and refine the responses these models will provide through a chatbot interface, companies turn to a process known as reinforcement learning from human feedback (or RLHF) where human evaluators judge whether the model's answers are useful, helpful, and "safe" (usually meaning not offensive or likely to be used for harm). Then the model is rewarded for producing answers more like those that the human evaluators labelled as good. But all that requires humans. Which is where Scale comes in. Its whole business is around providing the data labels that AI companies need. Often, those labelers work for low wages in the developing world. In Kenya, for example, Scale AI, a Silicon Valley darling, paid workers between $1 and $3 to train AI models, according to The Verge. (A spokesperson said the company adheres to minimum wage law in all counties in which it operates.) Founded by Alexandr Wang in 2016, who was then only 19 years old, Scale is best known as the data maven behind many of the world’s most sophisticated AI models, including those used by a number of self-driving car companies and to support decision-making in defense. The tasks are often simple and monotonous: identify characteristics of retail products or identify objects in an image. While Scale got its start labeling objects in image data for self-driving algorithms, it has now expanded its training to a wide assortment of AI models for customers like Etsy, Instacart, Meta, and, of course, OpenAI. And it’s ridden the AI boom to raise a total of approximately $600 million at a most recent valuation of $7.3 billion. CTO Vijay Karunamurthy said, however, that Scale, which also builds its own AI algorithms, is looking to go beyond finding laypeople to more curated experts, like an authority in ancient Aramaic, to help train models: “Expert feedback is incredibly valuable to help the model structure its thinking.”

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Paul Copplestone is the CEO and Co-founder of Supabase, the open source Postgres development platform designed for web and mobile apps to scale quickly. The company knows a thing or two about growing fast – only 5 years old, this April they raised $200 million in Series D funding round and were valued at $2 billion. Paul stopped by Term Sheet to talk about how he builds a remote and egoless company culture, why he likes hiring founders, and how being from New Zealand has impacted his entrepreneurial journey.

The “Egoless” Company Culture that Powers Supabase with CEO Paul Copplestone

Tech

Organizations today are striving to achieve the agility of a startup while maintaining robust control of a global enterprise. Can agentic AI be the key to bridging this gap? This interactive panel will delve into tangible use cases and offer candid insights on how AI agents can drive innovation and efficiency at scale within your organization.

Breakfast Roundtable: Who's Driving Your Innovation – You or the Agent?

Conferences

AI success isn’t just about experimentation—it’s about executing well and knowing where to invest. In this session, industry leaders will discuss their most effective AI projects and how they’ve measured outcomes. From agents that improve customer experience to automation that boosts productivity on the factory floor, we’ll analyze where AI is making the biggest operational impact. Learn how AI is helping businesses streamline workflows and fundamentally change the way they operate—driving meaningful returns at scale.

Insight Exchange: AI That Pays Off: Maximizing Your ROI

As tech decouples from its traditional centers of gravity, new hubs are rising. Innovation does not just move across a map; it has to be adapted to local contexts, industries, and workforces. Emerging technologies such as AI and robotics are being tested and scaled at different speeds across regions, reshaping the competitive landscape. What does it take to build, scale, and succeed globally, and which countries are positioning themselves at the center of this new innovation map?

Chan Ih-Ming
Executive Vice President, Member of the Executive Committee Singapore Economic Development Board (EDB) 

Wendy Tan White
Chief Executive Officer, Intrinsic 

Hans Tung
Managing Partner, Notable Capital

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