BenchGen
Simulated environments for benchmarking AI agents on multi-step tasks, with trajectory-level scoring
BenchGen evaluates AI agents inside simulated operational environments rather than on single prompts. Agents run complete multi-step workflows against digital twins of real systems (CRM, ERP, databases, APIs) in a sandboxed runtime, and every step of the decision path is scored.
The output is trajectory data: which tools were called, what was retrieved, where the run failed. Reports cover task completion rates, per-step accuracy and failure modes by workflow stage, and the same trajectories can be exported as reinforcement learning datasets for PPO, GRPO and PRM-style training.
It supports on-premise and air-gapped deployment, which is the reason it appears in defense, energy and financial services. Pricing is not public; the site routes to sales.
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