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

Observability

Observability

Observability

The capability to infer an AI system’s internal state and behavior through collection and analysis of logs, metrics, and outputs for effective monitoring and troubleshooting.

The capability to infer an AI system’s internal state and behavior through collection and analysis of logs, metrics, and outputs for effective monitoring and troubleshooting.

Updated

Goes beyond basic monitoring to provide deep insights into system health. Observability pipelines collect structured logs (requests, errors), metrics (latency, resource use), and traces (execution paths) from data-ingestion, training, and inference services. With correlations and dashboards, teams can pinpoint root causes of issues, replay events, and perform post-mortems. Governance defines which signals to capture, retention policies, and alert thresholds to maintain system reliability and compliance.

Example

A fraud-detection platform integrates OpenTelemetry to emit traces for every transaction, logs model decisions with confidence scores, and tracks CPU/GPU usage. When latency spikes, the SRE team drills into traces to discover a slow feature-store query, fixes the indexing, and restores normal performance within 15 minutes.

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.