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

Key Risk Indicator

Key Risk Indicator

Key Risk Indicator

A leading metric (e.g., frequency of out-of-scope predictions, rate of unexplainable decisions) that signals emerging AI risks before they materialize.

A leading metric (e.g., frequency of out-of-scope predictions, rate of unexplainable decisions) that signals emerging AI risks before they materialize.

Updated

A forward-looking measure that indicates rising exposure to particular AI risks, such as an uptick in low-confidence or out-of-distribution inferences, increases in flagged policy violations, or spikes in alert volumes. KRIs enable proactive governance by surfacing potential problems early, triggering risk-mitigation playbooks (e.g., throttling, human review), and feeding into enterprise risk dashboards alongside financial and operational KRIs.

Example

A healthcare provider monitors the KRI “percentage of model inferences with confidence < 50%.” When the KRI rises above 5% in a week, it signals data-drift or system issues, prompting data-science teams to investigate input pipelines and retrain the diagnostic model before patient care is impacted.

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.