River AI, an artificial intelligence startup co-founded by Igor Babuschkin—who previously helped build xAI—has raised $1.1 billion in a combined seed and Series A funding round. The investment was spearheaded by General Catalyst and AMP PBC, with additional backing from Nvidia, AMD Ventures, Y Combinator, and Temasek. AMP PBC is a dedicated AI investment firm established in 2026 by Anjney Midha, a former general partner at Andreessen Horowitz known for backing companies like Black Forest Labs, Mistral AI, LMArena, and OpenRouter.

River emerged from stealth in June with an ambitious vision. Babuschkin, whose career includes roles at DeepMind and OpenAI, aims to rebuild AI from the ground up, starting with how models are trained. His goal is to transform agents into personally trainable assistants, diverging from the path other AI labs are taking toward replacing human workers. In his launch post, he explained, "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 envisions capable agents becoming an everyday presence, describing them as "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."

River already offers an API priced per million tokens, with rates depending on the open model selected. This API lets developers apply both reinforcement learning (RL) and low-rank adaptation (LoRA) fine-tuning to the models. The initial product is designed to counter the limitations of prompt engineering. According to the product materials, "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."

Although this funding round is notably large for a young company—and possibly a sign of the overheated AI market—River’s concept arrives at a timely moment. Enterprises are increasingly seeking control over their AI models by adopting a mix of approaches, including open-weight models. River aims to address the post-training expertise gap through its neocloud offering. In its funding announcement, the company stated, "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."

The broader vision is that everyone will eventually have their own agents, trained by themselves and operating on their behalf. This trend is already emerging with the rise of personal, locally-running agents like OpenClaw and its variants. Additionally, Nvidia is partnering with PC manufacturers such as Dell, Microsoft, and HP to produce AI-capable hardware. How River’s technology will stand apart remains uncertain, but the company is starting with substantial financial resources to pursue its goals.