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

Vendor Risk Management

Vendor Risk Management

Vendor Risk Management

Assessing and monitoring third-party suppliers of AI components or services to identify and mitigate potential compliance, security, or ethical risks.

Assessing and monitoring third-party suppliers of AI components or services to identify and mitigate potential compliance, security, or ethical risks.

Updated

A lifecycle process of vendor due-diligence: issuing security and ethics questionnaires, reviewing third-party audit reports (SOC-2, ISO certifications), conducting on-site or virtual assessments, and integrating vendor risk profiles into an enterprise registry. Ongoing monitoring includes periodic reassessments, performance‐and‐compliance SLAs, and contingency planning (fallback vendors) to address vendor failure or non-compliance.

Example

An insurance firm engages a third-party model-hosting provider. Before contracting, they review the provider’s SOC-2 report, run a security questionnaire, and conduct an ethics audit of its model-training data. The vendor is classified as “medium-risk,” triggering quarterly reassessments and a contractual right to audit, ensuring continuous oversight of third-party AI services.

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.