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

Mitigation Strategies

Mitigation Strategies

Mitigation Strategies

Planned actions (e.g., bias remediation, retraining, feature re-engineering) to address identified AI risks and compliance gaps.

Planned actions (e.g., bias remediation, retraining, feature re-engineering) to address identified AI risks and compliance gaps.

Updated

A catalog of interventions mapped to risk types: data-drift triggers → retraining pipelines; fairness violations → bias-mitigation algorithms; security threats → input-sanitization layers; performance degradation → architecture tuning. Governance entails selecting appropriate strategies, documenting implementation, and verifying their effectiveness through follow-up assessments and tests.

Example

After a bias audit finds that loan approvals favor one demographic, the team applies re-weighting of training samples and adds fairness constraints. They then conduct post-mitigation testing to confirm that approval rates now meet the bank’s equity thresholds.

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.