Prime Intellect Raises $130 Million to Help Firms Train AI Agents
Prime Intellect raised $130 million in a Series A funding round to scale its tech stack and target new problems with its “open superintelligence stack.”
The company trains open frontier models and provides customers with the compute, large-scale reinforcement learning (RL), environments, sandboxes, evaluations and deployment they need for training, deploying and continuously improving their own artificial intelligence agents, it said in a Wednesday (July 8) blog post.
“Pre-training concentrated frontier AI in a handful of labs,” Prime Intellect said in the post. “RL breaks that open: companies can now own their model optimization loop — train directly on their own product, optimize for their specific workflows and build agents that improve continuously in production.”
Prime Intellect has 6,000 customers, including AI startups, neolabs and enterprises, and generates over $100 million in annualized revenue, according to the post.
With the new funding, the company will scale its stack to include larger compute clusters, larger RL runs, and the stack for agentic training, inference and continual learning.
It will also build infrastructure for problems such as long-horizon agents and recursive language models, automation of AI research and science, and continual learning, per the post.
Prime Intellect’s Series A round brings its total funding to over $150 million, according to the post. The company announced in February 2025 that it had raised $15 million in funding that brought its total funding at the time to $20 million.
The latest round was led by Radical Ventures, with participation from Nvidia Ventures, Intel Capital, Dell Technologies Capital and existing investors.
Intel Capital Principal Alexandra Farmer and Investment Director Assaf Araki said in a Wednesday blog post that Prime Intellect represents “the next generation of AI infrastructure.”
Reinforcement learning is emerging as a new way to generate data and train models for specific tasks, but running RL on large language models (LLMs) is far more complex than standard fine-tuning, they said.
“Going forward, we believe every AI builder will need reliable RL infrastructure to create competitive models and products, accelerating the demand for RL tooling,” Farmer and Araki said. “Intel Capital is excited to partner with Prime Intellect as they continue to capture this market.”
