AI Guardrails
Deploy with confidence by enforcing real-time safety and quality constraints on every LLM output.
PII Masking
Detect and redact personally identifiable information like names, IDs, medical records, or addresses in real-time—before responses leave your system. Powered by state-of-the-art models on the Guardrails Hub.
Hallucination Detection
Ground responses against your knowledge base or tools. Flag unsubstantiated claims or fabrications using semantic similarity and custom judges—no more “sounds good” lies.
Tone & Policy Enforcement
Enforce your brand voice, constitution, or compliance rules (e.g., no toxicity, no off-topic drifts). Corrective actions retry the LLM until it aligns—guaranteed SLAs, not best-effort prompts.
Prompts aren’t enforcement—guardrails are
Prompts alone are “best effort”—jailbreaks, leaks, and drifts slip through. Guardrails hard-code validation for 100% enforcement.
Catch production failures before users see them
Post-production risks like regressions or PII violations kill trust. Real-time layers catch them inline, logged and versioned.
Production-ready from open source to enterprise scale
From OSS to enterprise (Guardrails Server): scales to millions of requests/week, integrates anywhere (any LLM, any deployment). No more “oops” in prod.
Built for Production AI Teams
For teams building production AI systems who need evaluation data that's realistic, comprehensive, and fast.
~500 scenarios in 30 minutes
Replace weeks of manual curation with automated generation
Enterprise context grounding
Scenarios reflect your domain, terminology, and user patterns
Live system interaction
Tests adapt to actual AI responses, not assumed behavior
Multi-turn conversation support
Evaluate complex dialogue flows, not single-exchange Q&A
Programmatic edge case discovery
Systematically explore failure modes humans wouldn't think to test
Risk quantification
Move from "we tested it" to "here's our measured risk surface"