Structured adversarial testing to elicit failures—unsafe outputs, policy violations, data leaks—before users or attackers find them.
Red teaming in AI borrows from security: diverse prompts, tool abuse attempts, and edge cases probe the system. Outputs feed mitigations, guardrails, and monitoring.
Complements
Works alongside responsible AI processes and LLM observability in production.