Eval directory
Evals for Everlaw
4 evaluation packs covering adversarial robustness, safety gates, workflow quality, and operator-level checks for Everlaw AI products.
About Everlaw
Everlaw is a cloud-native litigation and e-discovery platform used by law firms, corporations, and government agencies to manage the full discovery lifecycle — from document review and analysis to deposition prep and trial. Its AI features accelerate review, surface key documents, and assist with case narrative and writing.
How complete this published benchmark library is across datasets, metrics, rubrics, use-case maps, and pack context. This is library coverage, not an agent performance score.
Test datasets
4/4 packs
Scoring metrics
4/4 packs
Judge rubrics
4/4 packs
Use-case maps
0/4 packs
Pack context
4/4 packs
Available eval packs for Everlaw
4 packs ready to run.
Batch Genai Actions At Scale
16 graded scenarios covering edge cases, failure modes, and quality checks.
Coding Suggestions Tiered Ai Coding With Justifications
16 graded scenarios covering edge cases, failure modes, and quality checks.
Predictive Coding Statistical Defensibility
38 graded scenarios covering edge cases, failure modes, and quality checks.
Writing Assistant Storybuilder Draft Quality
51 graded scenarios covering edge cases, failure modes, and quality checks.
Why eval Everlaw AI
Everlaw'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 Everlaw 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 Everlaw's public product surface and runnable in Corsac with your own data.