Eval directory
Evals for Paxton AI
3 evaluation packs covering adversarial robustness, safety gates, workflow quality, and operator-level checks for Paxton AI AI products.
About Paxton AI
Paxton AI is a generative-AI legal assistant designed for legal operations. Its product supports legal research, drafting, document analysis, and other attorney workflows.
Industry
Legal Technology / Legal AI
Website
www.paxton.aiHow 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
3/3 packs
Scoring metrics
3/3 packs
Judge rubrics
3/3 packs
Use-case maps
0/3 packs
Pack context
3/3 packs
Available eval packs for Paxton AI
3 packs ready to run.
Citations Source Linking Verifiability
CorrectnessAnswer Relevance48 graded scenarios covering edge cases, failure modes, and quality checks.
Legal Research Q A Contextual Research With Jurisdictional Coverage
CorrectnessAnswer Relevance47 graded scenarios covering edge cases, failure modes, and quality checks.
Paxton Ai Citator Case Status Treatment
CorrectnessAnswer Relevance16 graded scenarios covering edge cases, failure modes, and quality checks.
Why eval Paxton AI AI
Paxton 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 Paxton 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 Paxton AI's public product surface and runnable in Corsac with your own data.