Eval directory
Evals for vLex (Vincent AI)
3 evaluation packs covering adversarial robustness, safety gates, workflow quality, and operator-level checks for vLex (Vincent AI) AI products.
Available eval packs for vLex (Vincent AI)
3 packs ready to run.
Vlex Ask A Research Question Grounded Legal Q A
44 graded scenarios covering edge cases, failure modes, and quality checks.
Vlex Document Intake Auto Triage
36 graded scenarios covering edge cases, failure modes, and quality checks.
Vlex Multi Jurisdictional Research 50 State Survey Compare Jurisdictions
32 graded scenarios covering edge cases, failure modes, and quality checks.
Why eval vLex (Vincent AI) AI
vLex (Vincent AI)'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 vLex (Vincent AI) 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 vLex (Vincent AI)'s public product surface and runnable in Corsac with your own data.