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 Audit

XAI Audit

XAI Audit

A review process that evaluates whether AI explainability outputs meet internal policies and regulatory requirements, ensuring sufficient transparency.

A review process that evaluates whether AI explainability outputs meet internal policies and regulatory requirements, ensuring sufficient transparency.

Updated

A systematic examination (by internal compliance teams or external auditors) of explanation artifacts, comparing them against policy checklists (e.g., “Does every high-risk decision include a counterfactual explanation?”), regulatory mandates (e.g., GDPR right to explanation), and stakeholder needs. The audit assesses both technical correctness and usability, documents findings, and issues remediation plans for any gaps in explanation coverage or quality.

Example

A financial regulator conducts an XAI Audit on a bank’s credit-scoring AI. Auditors sample denials, review corresponding explanations, verify that each includes clear rationales and remedial suggestions, and confirm that explanation logs are retained for the required five-year period. Any missing or inadequate explanations prompt corrective action by the bank.

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.