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

XAI Framework

XAI Framework

XAI Framework

A structured approach or set of guidelines that organizations use to implement, measure, and govern explainability practices across their AI systems.

A structured approach or set of guidelines that organizations use to implement, measure, and govern explainability practices across their AI systems.

Updated

A formalized program (often comprising policy documents, technical standards, and process workflows) that prescribes when and how to apply explainability techniques, defines required explanation formats (e.g., textual, visual), sets roles (explanation owners, auditors), and establishes checkpoints (design review, pre-deployment validation, periodic audits). It ensures consistent, auditable XAI deployment aligned with organizational risk and regulatory requirements.

Example

A healthcare provider adopts an XAI Framework that mandates: (1) all diagnostic models include local explanations for each prediction; (2) explanation fidelity must exceed 90% as measured by agreement with ground-truth feature influences; and (3) quarterly XAI audits validate that explanations remain accurate after model retraining.

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.