Enzai MCP server
Connects to your AI.
Any MCP-compatible agent gets the same governed connection, right where your teams already work.
Some of our integrations
Workflow tools
Jira, ServiceNow
Model providers
Anthropic, OpenAI
Agent tools
Copilot Studio, Claude Enterprise
Development environments
Azure AI Foundry, Amazon Bedrock, Databricks

Glossary

Guardrails

Guardrails

Guardrails

Predefined constraints or checks (technical and policy) embedded in AI systems to prevent unsafe or non-compliant behavior at runtime.

Predefined constraints or checks (technical and policy) embedded in AI systems to prevent unsafe or non-compliant behavior at runtime.

Updated

Defensive layers, both algorithmic (confidence thresholds, input sanitization, adversarial detectors) and procedural (approval gates, human-in-the-loop), that enforce policy boundaries. Guardrails limit outputs (e.g., no hate speech), restrict decision domains, and trigger fail-safe actions. Effective guardrail governance requires reviewing and updating constraints as new threats emerge and monitoring bypass attempts.

Example

A content-moderation AI has guardrails that block profanity and extremist content. When the NLP filter’s confidence is below 70%, the system routes the post to a human moderator rather than posting automatically, ensuring unsafe content never reaches the feed without oversight.

Govern the AI you actually use.

Govern the AI you actually use.

Govern the AI you actually use.

Start with what’s in use.

Start with what’s in use.

Start with what’s in use.

Book a demo and we’ll show you how Enzai finds the AI in use, gives each system an owner and keeps the record.

Book a demo and we’ll show you how Enzai finds the AI in use, gives each system an owner and keeps the record.