Guardrails AI
Python framework for validating what goes into and comes out of a model.
Made by Guardrails AIAI guardrails
About Guardrails AI
Guardrails AI offers Guardrails, which the homepage describes as the guardrails framework for building, governing, and scaling production GenAI across any LLM and deployment environment. The homepage describes deploying runtime guardrails that detect policy violations, hallucinations, and data leakage.
A banner on the homepage announces that Guardrails AI joins Harvey. A related article listed on the blog is titled Guardrails x MLflow: Deterministic Safety, PII, and Quality Validators as GenAI Scorers.
Drafted from guardrailsai.com · not yet confirmed by Guardrails AI
How it works
Guardrails is a Python framework for wrapping an LLM call with checks. You define "validators" that run on the input and the output: toxicity, PII, prompt injection, format constraints, competitor mentions, whatever you need. If a validator fails, Guardrails can fix the output, re-ask the model, or raise an error. There's a public hub of prebuilt validators, many of them wrapping open classifiers.
It's the plumbing, not the judgment. The quality of each check depends on the validator you plug in. The company behind it also sells a hosted server version with a dashboard and managed validators.
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