River AI, the startup founded by xAI co-founder Igor Babuschkin, has raised $1.1 billion in a seed and Series A round led by General Catalyst and AMP PBC, with participation from Nvidia, AMD Ventures, Y Combinator and Temasek. The company emerged from stealth in June with a plan to rebuild the AI stack from training and models to product and hardware, arguing that the long-term goal should be personally trainable assistants rather than systems aimed primarily at replacing human workers. River already offers an API priced per 1 million tokens that lets developers apply reinforcement learning and low-rank adaptation fine-tuning to open models, positioning the product as an alternative to prompt engineering and a way for enterprises to train and serve models they can control. River says its neocloud platform can complete a complex reinforcement-learning run in 15 to 20 minutes without an infrastructure team, at two to four times the cost savings relative to closed-source alternatives. The financing underscores continued investor demand for AI infrastructure that reduces cost and vendor lock-in as companies increasingly seek a mix of open and proprietary models.