Benchgen

BenchGen provides a robust learning infrastructure for digital agents, offering an open platform for developers to discover benchmarks and interactive environments. Key features include: • Access to diverse benchmarks and environments • Comprehensive evaluation of agent systems (model and harness) • Verifiable reward mechanisms for performance assessment • Export clean trajectory data for iterative training and refinement This platform enables developers to rigorously test and improve their agent's capabilities in simulated worlds. By running agents through interactive environments, BenchGen captures full decision trajectories, verifies outcomes, and transforms every evaluation run into valuable training data. This continuous feedback loop of benchmarking, evaluation, refinement, and re-evaluation is central to enhancing agent performance. BenchGen is ideal for developers and engineering teams focused on building and refining digital agents. It supports a structured approach to agent development, ensuring that systems are robustly tested against real-world scenarios and continuously improved through data-driven insights. The platform’s ability to generate clean training data from evaluation runs makes it an invaluable resource for iterative development cycles.