Delve into how Guardrails works
Discover the largest library of custom validators for your AI applications.
Designed to shape your AI experiences precisely and effortlessly
This validator uses a pre-trained multi-label model to check whether the generated text is toxic.
Neutral or positive tone
Ensure responses are provided in a neutral or positive tone to match your brand personality
The response should not contain any financial advice in line with FINRA quidelines
Ensure no other user’s personal data is leaked in the response
Prevent mentions of competitors and replace with alternate phrasing
Source of truth
Get the truthiness of the response based on a source data set.
See a chatbot with active guardrails
With our dashboard, you are able to go deeper into analytics that will enable you to verify all the necessary information related to entering requests into Guardrails AI.
Explore Guardrails AI
Library of pre-built validators
Unlock efficiency with our ready-to-use library of pre-built validators. Optimize your workflow with robust validation for diverse use cases.
Flexible AI model provider support
Explore our adaptability with support for various AI model providers. Whether you prefer GPT-3 or others, we've got you covered.
Empower your projects with a dynamic frameworks for creating, managing, and reusing custom validators.
Flexible and adaptable to your use cases
Where versatility meets ease, catering to a spectrum of innovative applications easily.
Pydantic-style validation of LLM output
Ensures that outcomes are in line with expectations, precision, correctness and reliability in interactions with LLMs.
Corrective actions when validation fails
By verifying and indicating where the error is, you are able to quickly generate a second output option