SAN FRANCISCO — Labelbox, an AI platform powering reinforcement learning for frontier models and managed agents for enterprises, has raised more than $100 million in Series E financing, including equity and a credit facility. The round was led by Infinitum Partners, with participation from Wipro Ventures, Andreessen Horowitz (a16z), B Capital, Tau Ventures, Snowpoint Ventures, and others.Labelbox works with more than 400 customers, including over 90% of leading U.S. AI labs. The company reached profitability in 2026 while growing more than fivefold year over year.
As AI models become capable of performing increasingly complex tasks, the next challenge is enabling them to learn from experience and reliably execute work in real-world environments. Labelbox is addressing this opportunity through two core products: Horizon, which provides reinforcement learning environments and evaluation infrastructure for frontier AI labs, and Recursion Managed Agents, which enables enterprises to deploy fleets of agents that work inside existing business applications and improve with every run.
“Every company will soon run on AI systems that learn from their own work. Getting there takes innovation at every layer, from sandbox infrastructure and the agent harness to reinforcement learning post-training. Labelbox brings those layers together in one platform, and this funding lets us push each one further, so that frontier labs and enterprises can build AI that gets better with every run,” said Manu Sharma, CEO and co-founder of Labelbox.
The Series E financing will support continued research and engineering across Horizon and Recursion Managed Agents, as well as expansion of the teams bringing these products to customers.
Labelbox combines agent infrastructure, sandbox environments, and reinforcement learning post-training systems to support the development and deployment of AI systems. By innovating at every layer, the company aims to help both frontier labs and enterprises build systems that learn from their own work and improve over time.
