River AI has raised $1.1 billion in funding to expand its full-stack artificial intelligence platform. The round was led by General Catalyst and AMP PBC with strategic backing from NVIDIA and AMD Ventures, while Y Combinator and Temasek also participated.
The Palo Alto-based company was founded by Igor Babuschkin, a former co-founder of xAI. Babuschkin previously worked on generative modelling and reinforcement learning at Google DeepMind and led large-scale training efforts at OpenAI before helping launch xAI. The founding team also includes experience from xAI and Tesla, giving River expertise across deep learning and reinforcement learning.
River plans to use the capital to grow its operations and product development. The company is building infrastructure designed to give developers and businesses greater control over their AI models, focusing on training, deployment, hardware and personalized AI products. Its platform provides an API for custom model development, offering LoRA fine-tuning and reinforcement learning for frontier open-weight models. This allows developers to adapt models without building extensive infrastructure themselves.
The company says enterprises can complete complex reinforcement learning runs within 15 to 20 minutes and claims its platform can deliver costs two to four times lower than closed-source alternatives. Features include fast weight transfers, consistent sampling during training and elastic computing resources that adjust as workloads change. Trained models can move directly into production through the platform, which uses token-based billing for training and inference to reduce spending on unused GPU capacity.
Babuschkin said the company believes AI should become more open and affordable, arguing that AI should work for its users rather than the laboratories that build it. River aims to put greater ownership of intelligence into users’ hands. Beyond enterprise software, the company is developing hardware intended to bring personal AI closer to users and working on products focused on personalization and continual learning.
The participation of NVIDIA and AMD Ventures as strategic investors reflects the importance of computing infrastructure to River’s expansion. General Catalyst CEO Hemant Taneja said open-weight models are increasingly important to AI leadership and highlighted River’s focus on giving users greater ownership. The investment supports a broader push toward more accessible AI development.
As AI adoption expands, enterprises need systems that understand their data and operating environments while maintaining control over how those systems are trained and deployed. River’s strategy of combining customizable models, predictable token-based pricing and a full-stack approach positions it to address those demands across multiple layers of the AI stack.
