Short answer
AI guardrails are the rules and technical controls that keep an AI system within safe, approved boundaries: which topics it can handle, which data it can access, which actions it can take, and what it must refuse or escalate. Agentforce, Breeze and Claude all provide guardrail settings.
AI Guardrails explained
Guardrails work at several layers: instructions that define scope and tone, permissions that limit data and actions, filters that block toxic or sensitive output, data masking, rate and spending limits, and escalation rules that hand off to a person. Testing guardrails with realistic and adversarial prompts before launch is essential.
Guardrails are the practical way an AI governance policy gets enforced inside each tool.
How Vantage Point helps: we configure and test guardrails for AI agents and assistants, and document them for compliance review.
Frequently asked questions
What is the difference between AI guardrails and AI governance?
Governance is the policy: what is allowed and who decides. Guardrails are the technical controls that enforce that policy inside each AI tool.
How do you test guardrails?
With structured test sets that include normal requests, edge cases and attempts to push the AI outside its scope.