Adversarial testing and failure-mode analysis.
Overview
What is model testing?
Model testing stress-tests AI systems with adversarial inputs, edge cases and capability benchmarks before they reach users. It is the QA layer between training and production.
Models that pass standard benchmarks still fail in production on edge cases, adversarial prompts and distribution shift. Systematic red-teaming finds those failures while they are cheap to fix.
Structured red-teaming for jailbreaks and prompt injection.
Custom benchmarks aligned to your target skills.
Root-cause categorization of every discovered failure.
Fixes verified with targeted retest cycles before ship.
Workflow
How we do it
- 01Threat modeling
We map the failure modes and adversarial surfaces relevant to your deployment.
- 02Test design
Adversarial prompt sets and capability benchmarks built to your risk profile.
- 03Red-team execution
Trained red-teamers probe the model for jailbreaks, bias and capability gaps.
- 04Failure cataloging
Every failure logged, categorized and severity-scored for triage.
- 05Report & retest
Detailed report delivered, with retesting once fixes are applied.
Case study
Red-team a customer-facing chatbot before public launch
Structured adversarial testing across 12 risk categories, with severity-scored reporting.
Ready to get startedwith model testing?
Tell us about your project and we will scope a pilot within 48 hours.