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

Sanctioned Use Policy

Sanctioned Use Policy

Sanctioned Use Policy

Defined rules and controls that specify approved contexts, users, and purposes for AI system operation to prevent misuse.

Defined rules and controls that specify approved contexts, users, and purposes for AI system operation to prevent misuse.

Updated

A formal policy document, enforced via technical controls (role-based access, policy-as-code engines), that delineates who may use an AI system, for what tasks, and under what conditions. It lists prohibited use cases (e.g., mass surveillance, deceptive advertising), required approvals for sensitive operations, and monitoring protocols. Governance automates policy checks at runtime and regularly reviews policies to capture new risks or regulatory changes.

Example

A research lab’s Sanctioned Use Policy requires any team wanting to use its facial-recognition API to obtain ethical-committee approval, sign end-user–license agreements forbidding surveillance, and log every invocation. A policy-engine gateway enforces these rules automatically at the API layer.

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.