Agentic evaluation is where crowd models break. Task authoring, environment engineering and trajectory grading are engineering disciplines, and they are the founding team’s specialty.
A run that ends green can still be wrong in the middle. Scoring the trajectory is what separates an agent benchmark from a unit test.
What you receive
Benchmarks that hold up under scrutiny, with gold solutions and grading pipelines you can re-run.
Terminal-Bench-style task authoring, environment setup and trajectory grading.
Dockerised environments, verified solutions and step-level trajectory grading for CLI agents. Authored by engineers who have built and graded these tasks in production pipelines.
Deliverables
Repository-level task curation and patch verification.
Test-harness validation and failure-mode analysis for software-engineering agents, with reproducible pass/fail evidence per instance.
Deliverables
Web-task design, human demonstration recording and trajectory review.
Success-criteria grading for browser-use agents, including recorded human demonstrations as reference trajectories.
Deliverables
Tool-use correctness and multi-step reasoning-trace scoring.
Rubric-based trajectory scoring and safety-boundary probing for arbitrary agent frameworks, independent of your orchestration layer.
Deliverables
End-to-end benchmark construction as a managed program.
Task taxonomy → environment engineering → gold solutions → grading pipeline → leaderboard-grade reporting, run as a single accountable workstream.
Deliverables