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

Quota Management

Quota Management

Quota Management

The controls and limits placed on AI resource usage (e.g., API calls, compute time) to enforce governance policies and prevent runaway costs or abuse.

The controls and limits placed on AI resource usage (e.g., API calls, compute time) to enforce governance policies and prevent runaway costs or abuse.

Updated

Implements throttling, rate-limiting, and daily or monthly caps on resource consumption per user, team, or application. Quotas protect against denial-of-service, uncontrolled spending, and model-extraction attacks. Governance defines quota policies aligned to SLAs and budgets, monitors usage dashboards, and auto-notifies or blocks users when thresholds are reached, ensuring fair usage and cost predictability.

Example

A research organization sets a monthly GPU-hour quota of 100 hours per project. When a project exceeds 80 hours, an automated notification emails the team lead; at 100 hours, further training jobs are queued until quota increases are approved, preventing unexpected cloud charges and resource contention.

Govern the AI you actually use.

Govern the AI you actually use.

Govern the AI you actually use.

Start with whatโ€™s in use.

Start with whatโ€™s in use.

Start with whatโ€™s in use.

Book a demo and weโ€™ll show you how Enzai finds the AI in use, gives each system an owner and keeps the record.

Book a demo and weโ€™ll show you how Enzai finds the AI in use, gives each system an owner and keeps the record.