Monitoring AI Data Movement

Monitoring allows you to observe how data moves through AI systems in real time.

It is the operational layer built on top of data flows.

What monitoring provides

Peridot enables you to:

• View live data movement across systems

• Identify sensitive data exposure

• Track model usage

• Detect anomalies and policy violations

Key monitoring dimensions

Source visibility

Understand where data originates.

Model visibility

See which models process the data.

Destination visibility

Track where outputs are sent.

Policy context

See which policies applied to each interaction.

Detecting risk

Monitoring helps identify:

• Sensitive data sent to unapproved models

• Unexpected data movement patterns

• Unauthorized system access

• Policy violations

Real-time vs historical monitoring

Peridot supports:

Real-time monitoring

Immediate visibility into ongoing activity.

Historical analysis

Audit past interactions and trends.

Monitoring and incidents

Monitoring feeds directly into incident creation.

When defined conditions are met, Peridot can:

• Trigger alerts

• Create incidents

• Launch playbooks

From monitoring to enforcement

Monitoring is not the end state.

It enables:

• Policy enforcement

• Incident response

• Continuous governance

What to do next

• Define controls in Policies Overview

• Create workflows in AI Incident Playbooks