Reinforcement learning environments for post-training AI models on scientific reasoning and performance engineering tasks.
Cuebench builds specialized reinforcement learning environments targeting areas where frontier AI models still fail more than 80% of the time, including scientific reasoning, experiment design, and inference engineering. The platform is designed for post-training AI models through multi-step environments where agents form hypotheses, design experiments, verify results, and iterate on increasingly difficult tasks. Cuebench works with frontier AI labs and academic groups to build research harnesses, evaluation benchmarks, and post-training environments. Cuebench is a product of CueBench.