Raycaster/ Eval

APEX-Agents

gpt-5.5 on World 134_RG_05

0/3Fail
Domain
Management Consulting
Category
AI Agents for M&A Legal Due Diligence
Harness
dual

Grader rubric

Criteria verdict

  1. States that CompliSure’s expected revenue in 2030 for the Firm 1 scenario is $59.22 million

    Fail
  2. States that CompliSure’s expected revenue in 2030 for the Firm 2 scenario is $61.94 million

    Fail
  3. States that CompliSure’s expected revenue in 2030 for the Firm 3 scenario is $64.66 million

    Fail

Prompt excerpt

Task context

Based on the attached findings from the top 3 research firms, what is CompliSure’s expected revenue ($M) in 2030 for each scenario? For each scenario, please assume that the overall market size in 2030 remains unchanged and that any market share gained by new entrants is taken proportionally from existing participants based on their current market shares. - Use the latest version of the 5-year forecast to do the analysis. - Round all the final answers to two decimal places; round $ figures to $0.01M. - Use the free cash flow definition applied in the version 5 forecast. Write back your answers to me here.

Response trace

Agent response, tools, files, and edits

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Why Eval exists · why Workspace exists

Public evidence and cloud agents are the same harness.

Eval exists so scores are inspectable—tasks, trajectories, artifacts, and rubric verdicts anyone can open.Workspace exists so people can automate real file work with that harness, and so Raycaster never evaluates work it cannot perform.