Former xAI co-founder Igor Babuschkin’s River AI raises $1.1 billion to build your own personal AI

River AI, the AI startup founded this year by former xAI co-founder Igor Babuschkin, has raised $1.1 billion across its seed and Series A rounds to pursue an ambitious idea: AI that belongs to the people and companies using it rather than the labs that created it.

General Catalyst and AMP PBC led the funding, with strategic investments from Nvidia and AMD Ventures and participation from Y Combinator and Temasek. The unusually large financing gives the young company serious backing as it takes on one of AI’s biggest questions: who should own the intelligence that increasingly knows our work, preferences, and data?

“We’ve raised $1.1B to build AI that is owned and shaped by each of us. Check out the article published by The New York Times that explains River AI’s mission and where we’re going next,” Babuschkin said in a post on X.

River’s first step is far less philosophical. The startup has launched River API, a platform that lets developers and businesses fine-tune open-weight AI models using their own data without building the infrastructure normally required for large-scale training.

River says its platform supports models ranging from 35 billion to 1 trillion parameters and can complete complex reinforcement learning runs in 15 to 20 minutes. The company claims customers can do this at two to four times the cost savings of closed-source alternatives.

The API supports LoRA fine-tuning and reinforcement learning for frontier open-weight models. River handles weight transfers, sampling-training consistency and elastic compute behind the scenes. Models can then move directly into production, with customers paying for tokens used during training and inference rather than 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.”

River AI is betting that the future of AI is personal

River’s larger plan goes beyond selling another developer API.

Babuschkin wants to build a full personal AI stack where models learn continuously from individual users and operate according to their interests. That means building training infrastructure, personalized software and eventually hardware capable of running AI closer to its owner instead of relying entirely on somebody else’s data center.

The distinction could become increasingly important as AI assistants gain access to emails, documents, calendars, conversations and other deeply personal information. Most leading AI products still depend on general-purpose models controlled by large technology companies. River is betting that users will eventually want something different: intelligence they can train, customize and own.

“American leadership in AI urgently requires leadership in open-weight models, while maintaining a lead in closed frontier models,” General Catalyst CEO Hemant Taneja said. “Igor and the River AI team have the experience to make this happen, and we view their agenda as a priority for American resilience.”

River AI (Credit: River AI)

Babuschkin brings heavyweight AI credentials to the effort. He helped found xAI and previously worked on generative modeling and reinforcement learning at Google DeepMind. Before xAI, he worked at OpenAI, where River says he led large-scale training efforts. River’s founding team includes veterans of xAI and Tesla with experience spanning deep learning, reinforcement learning and AI infrastructure.

That pedigree helps explain investor enthusiasm, but $1.1 billion places enormous expectations on a company founded only this year.

River now has to prove that personal AI is more than an appealing alternative to centralized AI platforms. Its API gives the company a concrete starting point. The much bigger test will be whether developers, businesses, and eventually consumers really want to own their intelligence rather than keep renting it from someone else.