Platform and SDK for building, evaluating, debugging, and monetizing reinforcement learning environments for AI model post-training.
HUD provides an end-to-end platform to create trainable RL environments, run thousands of concurrent agent tasks, and evaluate and debug agent behavior with automated QA. Features include failure analysis, prompt-grader alignment checks, false positive and negative detection, and reward hacking detection. Environment builders can sell their work to research teams via the HUD vendor marketplace. The platform is compatible with any agent framework and is SOC 2 compliant. HUD is a product of HUD.