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

Query Privacy

Query Privacy

Query Privacy

Techniques and policies to protect sensitive information in user queries, ensuring that logged inputs do not compromise personal or proprietary data.

Techniques and policies to protect sensitive information in user queries, ensuring that logged inputs do not compromise personal or proprietary data.

Updated

Involves anonymization or pseudonymization of query text before storage, selective redaction of PII, and access controls on raw query logs. Privacy-preserving query logging frameworks apply rules (regex masking, tokenization) and enforce strict retention or deletion schedules. Governance audits log-handling processes and ensures compliance with privacy regulations and internal data-usage policies.

Example

A legal research AI masks client names and case references in query logs by replacing them with tokens (e.g., CLIENT_ID_123). Only compliance officers with special clearance can view re-identification tables, ensuring that sensitive client queries are protected while preserving logs for analytics.

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.