AgileRL Emerges with $7.5M to Help Companies Speed Up Reinforcement Learning by 10x

AgileRL, a startup accelerating the development of reinforcement learning for training AI models, today announces their seed, led by Fusion Fund, along with Flying Fish, Octopus Ventures, Entrepreneur First, and Counterview Capital, bringing their total funding to $7.5 million. Its platform reduces the time and cost of RL by 10x with performant end-to-end tooling. AgileRL plans to use the funding to open a San Francisco office and hire more than a dozen roles across engineering and go-to-market.

Enterprise’s RL Problem: Expensive, Slow, and Manual

Building an RL program in-house means effectively creating a small AI research lab. You need teams of expensive PhDs, months of trial runs, and big compute budgets. Companies must assemble everything from scratch each time: simulators, reward design, data collection, hyperparameter search, distributed training, evaluation suites, monitoring, safety guardrails, and deployment pipelines. Every new use case breaks the old setup and starts the work over. It’s slow, expensive, and brittle, and all but the largest technology companies can afford to effectively do it at scale.

“Arena has significantly streamlined our RL development workflow, making training and deploying agents a breeze,” said Andrew Nestor, a Machine Learning Engineer at Decision Lab. “The platform’s hyperparameter tuning capabilities have dramatically accelerated our experimentation and improved the performance of our models.”

AgileRL’s Solution: End-To-End RL Platform for Any Company

AgileRL offers both a free open-source RL platform and Arena, a managed full-stack RLOps platform that handles all the difficult engineering work. AgileRL’s key differentiator is its ability to train a population of identical agents, constantly adjusting their hyperparameters as they learn, and evolve the best performers forward. The result is streamlined development, 10x improvement in training speed, and superior AI model performance compared to standard approaches.

“Having built a reinforcement learning system from scratch at my last company, I saw firsthand how costly and complex it is,” said Param Kumar, co-founder of AgileRL. “No company in 2026 should need a full AI research lab just to use RL. Our goal is to make reinforcement learning a standard tool in every company’s tech stack.”

AgileRL’s key features include:

• Single, Multi-agent and LLM Support: Train on-policy, off-policy, offline, multi-agent, contextual multi-armed bandits and large language models with unmatched speed and performance
• Evolutionary Hyperparameter Optimization: Achieve automatic, optimal performance in a single training run through hyperparameter and neural network evolution
• Distributed Training: Take full advantage of your entire compute stack for online and offline reinforcement learning with multi-GPU support
• Environment Validation: Ensure everything is configured correctly before training begins with guided setup and testing
• One-click deployment: Instantly use your trained model in production without complex pipelines
• Community Driven: Benefit from the contributions of top research labs and institutions, shaped by academic citations and 300,000+ downloads

The company’s framework is already being used by labs at institutions including MIT, Roblox, Carnegie Mellon and University of Waterloo, for applications that span defense, robotics, finance, and others.

“Reinforcement learning remains the gold standard of AI training, yet very few companies actually have the resources to implement it in house,” stated Lu Zhang, Founder and Managing Partner at Fusion Fund. “As hundreds of thousands of companies continue to invest in AI, AgileRL will undoubtedly play a key role in powering this revolution.”

Companies can learn more and try for free at: https://www.agilerl.com.

About AgileRL

AgileRL is a machine learning startup accelerating reinforcement learning for building superhuman intelligence. Its open-source framework has been downloaded more than 250,000 times and gives organisations of any size access to state-of-the-art RL algorithms at scale. Its RLOps platform, Arena, is used by companies that include IBM, Airbus and Decision Lab. Based in London and San Francisco, AgileRL is backed by Fusion Fund, Flying Fish, Octopus Ventures, Entrepreneur First, and Counterview Capital. Learn more at https://www.agilerl.com..

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