Guardrails
Predefined constraints or checks (technical and policy) embedded in AI systems to prevent unsafe or non-compliant behavior at runtime.
Defensive layers - both algorithmic (confidence thresholds, input sanitization, adversarial detectors) and procedural (approval gates, human-in-the-loop) - that enforce policy boundaries. Guardrails limit outputs (e.g., no hate speech), restrict decision domains, and trigger fail-safe actions. Effective guardrail governance requires reviewing and updating constraints as new threats emerge and monitoring bypass attempts.
A content-moderation AI has guardrails that block profanity and extremist content. When the NLP filter’s confidence is below 70%, the system routes the post to a human moderator rather than posting automatically - ensuring unsafe content never reaches the feed without oversight.
“What used to take weeks of manual reviews and policy work is now structured and auditable in Enzai within minutes. It’s the first time AI governance has felt operational, not theoretical.”
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