Radical Numerics launched with $50 million in seed funding to build integrated AI models trained directly on biological data across DNA, RNA, and proteins. The round was led by Emergence Capital with participation from Obvious Ventures, Triatomic Capital, Factory, and First Spark Ventures, and the company said pre-seed backing included Patrick Collison. The startup plans to develop multimodal models for use cases spanning cancer diagnostics, drug target identification, and biosecurity. Radical Numerics also previewed an emerging genomic language model dubbed Omnii and said it is partnering with an undisclosed cancer diagnostics company to apply its models to pancreatic and multi-cancer detection. As compute- and data-intensive biology AI advances accelerate, the seed funding signals sustained investor confidence that multimodal representations can improve translational performance beyond single-data-type approaches.