What it does
Benchgen evaluates LLM-powered agents by running them against simulated versions of the systems they would use in practice, such as APIs, databases and workflow engines, instead of testing single prompts. Each run is recorded as a trajectory of tool calls, retrieval steps and decisions, and every step is scored, not only the final answer. Environments run in isolated runtimes on cloud or on-premise GPU and CPU servers and can connect to enterprise data sources such as CRM, ERP, databases and APIs. The site says the platform can be deployed in sovereign or air-gapped infrastructure, so model weights, evaluation data and results stay inside the customer's environment. A benchmark report covers task completion rates, per-step accuracy, failure modes and where they occur, comparisons across model versions or prompt variants, and audit-ready logs. The recorded trajectories can be filtered into datasets for supervised fine-tuning with LoRA, RLVR with GRPO, and distillation. The site also publishes benchmark rankings and a leaderboard, and its main audience is organisations in areas such as defence, energy and finance. Access is by contacting the company.
Capabilities
- Simulated environments that mirror real operational systems
- Trajectory-based scoring of every agent step
- Benchmark reports with failure modes and audit logs
- Trajectories exportable as training data
- Cloud, on-premise or air-gapped deployment
- Public benchmark rankings and leaderboard
When to use it
- You are preparing an LLM agent for production and need to test multi-step behaviour
- You need auditable evaluation in a regulated, sovereign or air-gapped setting
- You want to compare model versions or prompt variants on the same tasks
- You want to turn agent runs into data for fine-tuning
