River AI has secured $1.1 billion as the company seeks to make customized AI models faster, cheaper and more accessible to developers and companies.
The funding round was led by General Catalyst and AMP PBC, with participation from NVIDIA and AMD Ventures, Y Combinator and Temasek.
Founded by former DeepMind, OpenAI and xAI researcher Igor Babuschkin, the AI startup is building a personalized AI infrastructure that lets users customize and continually train models for their own needs.
The company said general-purpose models can be powerful but are rarely tailored to the specific data and workflows of individual organizations. Until now, creating a custom model typically required specialized hardware, an infrastructure team and months of development.
River’s API aims to reduce that complexity. The company said enterprises can complete complex reinforcement-learning training runs in as little as 15 to 20 minutes without maintaining an infrastructure team, while achieving two to four times the cost savings of closed-source alternatives.
