Tune the open bases into scientific agent brains — don’t train 70B from scratch, train the right behaviors.
We don’t ship base weights. We ship the recipes that turn open base models into Skills-fluent scientific agents — continued pretraining, SFT on skill-execution traces, RL against scientific impasse tasks, and Skills-adapter LoRAs that teach any base to consult the Knowledge registry mid-run.
BioUniGen.xyz is an integrated model platform for computational biology and drug discovery that unifies recognition and generation within a shared biological representation framework. Instead of treating tasks like molecule design, protein folding, function annotation, and de novo sequence generation as separate problems, it connects molecular sequences, 3D structures, and functional mechanisms in one adaptable system. By combining multi-modal biological inputs with joint predictive analysis and generative design, BioUniGen supports end-to-end research workflows such as molecular optimization, structural simulation, and functional mining. The goal is to overcome the fragmentation of existing biological AI tools and provide a more coherent engine for life science research.