What is Guardrails?

Explained

Guardrails combine classifiers, allow/deny lists, structured output schemas, and human escalation to cap model risk. They are essential for customer-facing assistants and regulated workflows.

Decision guides that use this term

• Agentic AI vs generative chatbots: does your use case need an agent or a good assistant?
• AI agents vs RPA: which one should automate your process, and when should you combine them?
• Human in the loop vs autonomous agents: how much should an AI agent decide on its own?
• LLM evals vs human review: how should you assure the quality of enterprise AI?

Further reading

• Ethical AI: Building Responsible AI Experiences for Enhanced User Trust
• Taming LLM Hallucinations: A Confidence-Driven Approach for Accurate Customer Experiences

Related terms

• LLM Model trained on vast text; basis of ChatGPT, Claude, and similar systems.
• Bias Distortion in data or model that produces unfair or inaccurate results.
• Constitutional AI Training approach that aligns models with explicit rules and self-critique.
• Ethical AI AI designed and deployed with ethical principles (transparency, fairness, privacy).
• EU AI Act European regulation that classifies AI systems by risk and mandates compliance.
• Explainability Ability to explain how a model reaches a conclusion (Explainable AI, XAI).