River AI, founded by xAI co-founder Igor Babuschkin, raised $1.1 billion in a seed/Series A round led by General Catalyst and AMP PBC, with participation from Nvidia, AMD Ventures, Y Combinator, and Temasek.
Babuschkin, who previously held AI roles at DeepMind and OpenAI, launched River from stealth in June with the aim of rebuilding the AI stack, including training methods, models, and hardware, to create personally trainable assistants rather than agents designed to replace human workers. He described his vision of future agents functioning like constant, personalized companions loyal to individual users rather than institutions.
River currently offers a token-based API allowing developers to fine-tune open models using reinforcement learning and low-rank adaptation techniques, positioning the product as an alternative to prompt engineering by letting users train and own their own models rather than relying on models they cannot modify.
The company said enterprises can complete complex reinforcement learning runs in 15 to 20 minutes without dedicated infrastructure teams, at significantly lower cost than closed-source alternatives. The funding arrives as enterprises increasingly seek greater control over their AI infrastructure through mixed and open-weight model strategies, and as personal, locally-run AI agents gain broader traction across the industry.
Featured image: Credit: River AI
