Guardrails AI for AI agent security: Features, pricing, and alternatives

Guardrails AI, an open-source framework designed to validate and correct AI model outputs, offers a crucial layer of security for production AI deployments by focusing on output validation rather than authentication. Founded by Shreya Rajpal and Diego Oppenheimer, the platform has gained traction for its ability to catch hallucinations, prevent data leaks, and filter toxic content, leveraging a community-contributed library of over 100 validators. The framework operates independently of specific large language models (LLMs), facilitating integration with providers like OpenAI and Anthropic. Guardrails AI provides both a free, self-hosted core and a managed service, Guardrails Pro, which offers hosted validation and observability dashboards for enterprise support. While Guardrails AI focuses on runtime validation, WorkOS provides complementary authentication infrastructure, handling user access and identity management, thus ensuring that only authorized users interact with AI agents. This dual approach underscores the necessity of both output validation and robust authentication in securing AI applications, particularly for enterprise deployments where output safety and user authentication are critical.