AI guardrails
Expanded definition
Guardrails can include input filters, output validators, policy checks, retrieval constraints, tool permissioning, human approval, data loss prevention, and monitoring. They do not replace model quality or evaluation, but they reduce risk in production systems where generated output can affect users, data, or external tools.
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AI guardrails FAQ
What is AI guardrails?
AI guardrails are controls that constrain, monitor, or validate model behavior before outputs or tool actions reach users or systems.
How is AI guardrails used in AI systems?
Guardrails can include input filters, output validators, policy checks, retrieval constraints, tool permissioning, human approval, data loss prevention, and monitoring. They do not replace model quality or evaluation, but they reduce risk in production systems where generated output can affect users, data, or external tools.
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