Long-horizon tasks
Work that takes more than a single answer. Multi-step tasks that test planning, tool use, and recovery when the first attempt does not work.
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Better agents start with better measurements. We build benchmarks and evals tailored to your workflows, tools, and data so you can measure how agents perform on your actual work and where they need to improve.
Benchmarks and evals
An agent is more than its model. Evaluate the whole system, including the harness, tools, and runtime, on tasks that reflect the work you need done.
Compare configurations, find failure modes, and check whether an improvement holds up beyond a single score.
Let’s talk evals- Quality
- Does the agent complete the task? Evaluate outcomes against clear, task-specific criteria.
- Cost & latency
- What does a successful run take? Compare quality alongside inference cost and time.
- Reliability
- Does it work again? Surface regressions, brittle behavior, and failures across repeated runs.
Evaluation environments
Realistic tools, data, and constraints in a repeatable setup. Give agents room to act, and measure whether they reach the right outcome.
Get in touchAgent trajectories
The path behind the result: tool calls, intermediate decisions, and failed attempts. Traces that help explain what worked, what broke, and where to improve.
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