Eval directory
Evals for CoCounsel (Thomson Reuters)
3 evaluation packs covering adversarial robustness, safety gates, workflow quality, and operator-level checks for CoCounsel (Thomson Reuters) AI products.
About CoCounsel (Thomson Reuters)
CoCounsel (Thomson Reuters) is an AI platform serving legal professionals, helping law firms and legal departments automate research, drafting, and review workflows with greater accuracy and speed than manual processes.
Available eval packs for CoCounsel (Thomson Reuters)
3 packs ready to run.
Cocounsel Deep Research Westlaw Grounded Retrieval
Answer Relevance6 graded scenarios covering edge cases, failure modes, and quality checks.
Cocounsel Guided Agentic Workflows
71 graded scenarios covering edge cases, failure modes, and quality checks.
Cocounsel Skills Library Skill Invocation
72 graded scenarios covering edge cases, failure modes, and quality checks.
Why eval CoCounsel (Thomson Reuters) AI
CoCounsel (Thomson Reuters)'s AI features ship behind brand promises about accuracy, safety, and reliability. Buyers and integrators need to know those promises hold up under adversarial prompts, edge-case workflows, and the long tail of real customer inputs — not just the demo path.
The Corsac eval library for CoCounsel (Thomson Reuters) measures four dimensions teams care about most when deploying legal ai agents:
- Adversarial robustness — does the agent resist prompt injection, jailbreaks, and social-engineering attempts?
- Workflow quality— does it complete the task buyers were shown in the demo, on inputs that don't look like the demo?
- Safety gates — does it escalate or refuse when it should, and only then?
- Operator quality — does it preserve analyst trust by surfacing the right context at the right time?
Every eval pack above is hand-authored against CoCounsel (Thomson Reuters)'s public product surface and runnable in Corsac with your own data.