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Guardrails AI

Output validation, structural constraints, and real-time corrections for LLMs.

Open source

Best when agent or LLM outputs must conform to schemas, safety policies, and business rules before being acted upon—beyond simple content filtering.

Selection advice

Choose Guardrails AI when correctness and safety must be enforced at the output layer, not just suggested in prompts. It's a safety net for agent actions.

Best for

  • schema validation
  • output guardrails
  • structured generation
  • safety enforcement

Not ideal for

  • teams that only need prompt-level constraints
  • projects without structured output requirements

Core concepts

guardsvalidatorsRAIL speccorrective re-asks

Minimal implementation shape

Define a RAIL spec with Pydantic-style schemas, wrap your LLM call, and let Guardrails validate, correct, or reject the output before the agent uses it.

Sources