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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

Weight Auditing

Weight Auditing

Weight Auditing

Examining model weights and structures for anomalies, backdoors, or biases that could indicate tampering or unintended behaviors.

Examining model weights and structures for anomalies, backdoors, or biases that could indicate tampering or unintended behaviors.

Updated

A deep-inspection process where model parameters are analyzed for irregular distributions, hidden triggers (e.g., backdoor patterns), and disproportional weight magnitudes tied to sensitive features. Governance involves automated tools that scan weight histograms, detect outlier parameters, and flag suspicious patterns for security and fairness review, preventing corrupted or maliciously manipulated models from deployment.

Example

A security team runs a weight-audit tool on a customer-segmentation model and discovers a cluster of weights spiking for encrypted backdoor features. They quarantine the model, perform forensic analysis to uncover a poisoning attack, and retrain from a clean checkpoint, eliminating the malicious backdoor before any production use.

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.