Insider Brief
- Labelbox, an AI platform for reinforcement learning and enterprise agents, has raised more than $100 million in Series E financing, including equity and a credit facility, in a round led by Infinitum Partners with participation from Wipro Ventures, Andreessen Horowitz, B Capital and others.
- The company serves more than 400 customers, including over 90% of leading U.S. AI labs, and reached profitability in 2026 while growing more than fivefold year over year through its Horizon reinforcement learning platform for frontier labs and its Recursion Managed Agents product for enterprises.
- CEO and co-founder Manu Sharma said the funding will push forward each layer of its platform, from sandbox infrastructure to reinforcement learning post-training, with the capital supporting research, engineering and team expansion as Labelbox opens its managed agents to enterprise customers.
PRESS RELEASE — Labelbox, the AI platform powering reinforcement learning for frontier models and managed agents for enterprises, announced it 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.
Advancing AI from training to execution
Horizon: Reinforcement learning for frontier AI
Horizon provides reinforcement learning environments, expert feedback, and evaluation infrastructure that help AI labs train and improve frontier models. Its environments simulate complex, multi-step work across coding, research, and other demanding tasks, enabling models to practice, receive feedback on their performance, and improve through reinforcement learning. Labelbox works with leading AI labs and hyperscalers on post-training programs.
Recursion Managed Agents: AI agents for enterprise workflows
Recursion Managed Agents enables companies to deploy fleets of AI agents inside the applications their teams already use. Agents can initiate work in response to schedules, alerts, tickets, and other triggers, coordinate across tools, and have their output evaluated against defined standards. Each run can inform the agent’s memory, helping it improve how it approaches future tasks.
Labelbox already uses more than 50 agents internally across functions including engineering, research, product, sales, marketing, and finance. Earlier this month, the company opened Recursion Managed Agents to enterprise customers, extending its approach to continuous improvement beyond AI research labs.
Investing in the next phase of AI
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.
For more on the vision driving Labelbox’s next chapter, read the Labelbox Series E announcement.
About Labelbox
Labelbox provides the data, reinforcement learning infrastructure, and managed agent platform that help AI systems learn and perform real work. Its products support frontier AI labs developing more capable models and enterprises deploying AI agents across their operations. Labelbox serves more than 400 customers, including leading AI labs, hyperscalers, startups, and Fortune 500 companies.
For more information, visit https://labelbox.com.
SOURCE
Insider Brief
- Labelbox, an AI platform for reinforcement learning and enterprise agents, has raised more than $100 million in Series E financing, including equity and a credit facility, in a round led by Infinitum Partners with participation from Wipro Ventures, Andreessen Horowitz, B Capital and others.
- The company serves more than 400 customers, including over 90% of leading U.S. AI labs, and reached profitability in 2026 while growing more than fivefold year over year through its Horizon reinforcement learning platform for frontier labs and its Recursion Managed Agents product for enterprises.
- CEO and co-founder Manu Sharma said the funding will push forward each layer of its platform, from sandbox infrastructure to reinforcement learning post-training, with the capital supporting research, engineering and team expansion as Labelbox opens its managed agents to enterprise customers.
PRESS RELEASE — Labelbox, the AI platform powering reinforcement learning for frontier models and managed agents for enterprises, announced it 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.
Advancing AI from training to execution
Horizon: Reinforcement learning for frontier AI
Horizon provides reinforcement learning environments, expert feedback, and evaluation infrastructure that help AI labs train and improve frontier models. Its environments simulate complex, multi-step work across coding, research, and other demanding tasks, enabling models to practice, receive feedback on their performance, and improve through reinforcement learning. Labelbox works with leading AI labs and hyperscalers on post-training programs.
Recursion Managed Agents: AI agents for enterprise workflows
Recursion Managed Agents enables companies to deploy fleets of AI agents inside the applications their teams already use. Agents can initiate work in response to schedules, alerts, tickets, and other triggers, coordinate across tools, and have their output evaluated against defined standards. Each run can inform the agent’s memory, helping it improve how it approaches future tasks.
Labelbox already uses more than 50 agents internally across functions including engineering, research, product, sales, marketing, and finance. Earlier this month, the company opened Recursion Managed Agents to enterprise customers, extending its approach to continuous improvement beyond AI research labs.
Investing in the next phase of AI
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.
For more on the vision driving Labelbox’s next chapter, read the Labelbox Series E announcement.
About Labelbox
Labelbox provides the data, reinforcement learning infrastructure, and managed agent platform that help AI systems learn and perform real work. Its products support frontier AI labs developing more capable models and enterprises deploying AI agents across their operations. Labelbox serves more than 400 customers, including leading AI labs, hyperscalers, startups, and Fortune 500 companies.
For more information, visit https://labelbox.com.
SOURCE
