Today we're announcing $1.1 billion in funding across our Series Seed and Series A, led by General Catalyst and AMP PBC, with strategic investment from NVIDIA and AMD Ventures and participation from Y Combinator and Temasek. The round accelerates our mission: to build powerful personal AI that knows you and works for you, and to put ownership of that intelligence in the hands of the people and organizations who use it. It starts with giving developers and companies the tools to train, tune, and own their own AI models.
Most companies using AI today run general-purpose models trained on the entire internet and designed for the broadest possible audience. They are powerful, but they are not built for any one organization in particular. Until now, building a custom model required a dedicated infrastructure team, specialized hardware, and months of work — putting it out of reach for most companies.
The River API changes that. Any enterprise can complete a complex reinforcement learning run in 15 to 20 minutes with no infrastructure team required, at two to four times the cost savings relative to closed-source alternatives. We deliver state-of-the-art LoRA fine-tuning and reinforcement learning for frontier open-weight models, and the platform handles the underlying complexity — fast weight transfers, sampling-training consistency, and elastic compute — so developers can focus on improving their models rather than managing infrastructure. Trained models deploy instantly to production, and billing is strictly metered on the tokens used for training and inference, eliminating the cost of idle GPU capacity.
“The way AI is built today is not how it will be built in the future. AI should be open, freely available, and affordable. It should feel like it is working for the person using it, not the lab that trained it. We started River to allow people and companies to own their intelligence.”
Igor Babuschkin, Co-Founder & CEO, River AIOur ambition goes beyond the API. We are building powerful personal AI — an AI that learns from you, that you actually control, and that knows you well enough to act in your interest. Rather than aligning one model to billions of users, we align AI directly to each person. Today the API puts that ownership in the hands of developers and enterprises. Over time, we will extend the same control to every individual. We wrote more about why in Introducing River AI.
Getting there means building the full stack end to end: training infrastructure that makes fine-tuning accessible to any developer, products built around personalization and continual learning, and new hardware that lets personal AI live close to you, running for you rather than in someone else's data center.
“American leadership in AI urgently requires leadership in open-weight models, while maintaining a lead in closed frontier models. Igor and the River AI team have the experience to make this happen, and we view their agenda as a priority for American resilience. The core philosophy of putting ownership of intelligence in the hands of the people using it will prove to be on the right side of history for the open-weight ecosystem.”
Hemant Taneja, CEO, General CatalystOur founding team brings hands-on experience from xAI and Tesla at the leading edge of deep learning and reinforcement learning, with the rare ability to execute at speed across the entire AI stack. Before founding xAI, Igor worked on generative modeling and reinforcement learning at Google DeepMind and spearheaded large-scale training efforts at OpenAI.
“There is a gap between what AI can do and what most companies actually experience. Until now, companies have lacked a cost-efficient way to train, tune, and own custom AI models. River closes this gap, helping any company build models on their own data, tailored to how they actually work.”
Marc Bhargava, Managing Director, General CatalystThis funding accelerates every layer of that stack. If you want to help build an AI that people actually own, come build with us.
— The River AI team