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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

Reasoning Chain

Reasoning Chain

Reasoning Chain

The multi-step logical process an AI agent follows to move from an initial objective to a final action or output.

The multi-step logical process an AI agent follows to move from an initial objective to a final action or output.

Updated

For agentic AI governance, the reasoning chain is the internal monologue of the AI. Tracking this chain is essential for traceability and auditability under the EU AI Act. It allows human auditors to see not just what the agent did, but why it chose a specific tool or path at each intermediate step, which is critical for root-cause analysis after a failure.

Example

A travel-booking agent's reasoning chain shows it first checked flight availability, then compared loyalty points, then checked the traveler's calendar, and finally chose a flight that maximized points while avoiding a meeting conflict.

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.