River AI, founded by xAI co-founder Igor Babuschkin, has raised $1.1 billion in funding led by General Catalyst and AMP PBC. The round includes strategic investments from NVIDIA and AMD Ventures, with additional backing from Y Combinator and Temasek. The Palo Alto-based company offers an API that enables enterprises to complete complex reinforcement learning training runs in 15 to 20 minutes without requiring an infrastructure team, at two to four times the cost savings versus closed-source alternatives. River AI's platform provides state-of-the-art LoRA fine-tuning and reinforcement learning for frontier open weight models. The company aims to make AI ownership accessible to developers and organisations rather than relying solely on general-purpose models. Babuschkin previously worked at Google DeepMind and OpenAI before co-founding xAI.

General Catalyst leads $1.1B round into 2-month-old River AI |. River AI, an AI startup founded by xAI co-founder Igor Babuschkin, has secured $1.1 billion in funding in a seed/Series A round led by General Catalystand AMP PBC, with participation from Nvidia, AMD Ventures, Y Combinator, and Temasek. (AMP PBC is an AI-focused investment firm founded in 2026 by former Andreessen Horowitz general partner Anjney Midha, backer of companies at a16z like Black Forest Labs, Mistral AI, LMArena and OpenRouter.) River came out of stealth in June with a fascinating mission. Babuschkin, whose resume includes AI roles at DeepMind and OpenAI, intends to reinvent AI from scratch, beginning with how models are trained. This is in order to turn agents into personally trainable assistants, rather than following the trajectory other AI labs are on: human worker replacements. "To get there, we believe the stack has to be rebuilt end to end: training, models, the product layer, and new hardware that lets personal AI live close to you," he wrote in his launch blog. "Capable agents will be a normal part of everyday life. Less like the assistants you call on today when you need a task done, more like guardian angels: quietly present, on your side, helping with what actually matters to you. They will know you well, and they will be yours, not someone else's," he envisions. River already offers an API, billed per 1 million tokens, with rates dependent on the open model used. The API allows developers to use both reinforcement learning (RL) and low-rank adaptation (LoRA) fine-tuning on the models. This first product is intended to be an antidote to prompt engineering. "Prompting steers a model you don't own and can't improve. River lets you train open models into ones that are truly yours - and serve them like any other endpoint," the product literature says. While this round is an eye-popping-size investment for a nascent company, and perhaps another indication of the overheated AI atmosphere, River's premise comes at a particularly auspicious time. Enterprises are waking up to wanting to control their AI model destiny by using a mix of models, including open weight. River is promising to solve the post-training expertise part of that problem with its neocloud offering. "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," it wrote in its funding announcement. The bigger vision of this company is that everyone will have their own agents, trained by themselves, and working on their behalf. We are already seeing this concept in action with the rise of personal, locally running agents in the form of OpenClaw and its derivatives. Plus, we are already seeing Nvidia partner with PC makers like Dell, Microsoft, and HP for AI-capable hardware. How River's tech will differ remains to be seen. But it's starting out with a war chest full of cash to try. When you purchase through links in our articles, we may earn a small commission. This doesn't affect our editorial independence.

River AI raises $1.1B led by General Catalyst and AMP PBC to build open AI stack. Founded by xAI co-founder Igor Babuschkin, River AI gives developers and enterprises the tools to train, tune, and own custom AI models PALO ALTO, Calif.-(BUSINESS WIRE)-River AI, the full-stack AI company founded by xAI co-founder Igor Babuschkin, today announced $1.1 billion in funding, led by General Catalyst and AMP PBC with strategic investment from NVIDIA and AMD Ventures. Additional investors include Y Combinator and Temasek. The round will accelerate River AI's mission to build powerful personal AI and to give developers and companies the tools to train, tune, and serve their own AI models, putting ownership of AI directly in the hands of the people and organizations who use it. Today, most companies using AI are running 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. With River's API, any enterprise can complete a complex reinforcement learning training run in 15 to 20 minutes with no infrastructure team required, at two to four times the cost savings relative to closed-source alternatives. "The way AI is built today is not how it will be built in the future," said Igor Babuschkin, co-founder and CEO of River AI. "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." River's API delivers state-of-the-art LoRA fine-tuning and reinforcement learning for frontier open weight models. The platform handles the underlying infrastructure complexity, including fast weight transfers, sampling-training consistency, and elastic compute, so developers can focus on improving their models rather than managing infrastructure. Trained models can be deployed instantly to production, and billing is strictly metered on tokens used for training and inference, eliminating the cost of idle GPU capacity. River is building a full, integrated stack: new hardware that lets personal AI live close to the people it serves, training infrastructure that makes fine-tuning accessible to any developer, and products built around personalization and continual learning. Rather than aligning one model to billions of users, River aligns AI directly to each user. Today, that means giving developers and enterprises the tools to build and control their own models; River's long-term goal is to extend that same control to every individual. "American leadership in AI urgently requires leadership in open weight models, while maintaining a lead in closed frontier models," said Hemant Taneja, CEO of General Catalyst. "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." Babuschkin previously worked on generative modeling and reinforcement learning at Google DeepMind and spearheaded large-scale training efforts at OpenAI before co-founding xAI. River's 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. "There is a gap between what AI can do and what most companies actually experience," added Marc Bhargava, Managing Director at General Catalyst. "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." About River AI River AI is a full-stack AI company founded by Igor Babuschkin to create personal, continually improving AI. Its platform allows any developer to train, tune, and serve custom models without a dedicated infrastructure team or expensive hardware. Through its API, River delivers state-of-the-art LoRA fine-tuning and reinforcement learning for frontier open weight models, with token-metered billing and instant deployment to production. River AI is headquartered in Palo Alto, California, and backed by General Catalyst, AMP PBC, NVIDIA, AMD Ventures, Y Combinator, Temasek, and others. Learn more at river.ai River AI. Release Versions