Data Flows Overview
Data Flows track how information moves into and out of AI systems.
They provide the visibility required to understand risk, enforce policies, and audit behavior.
Why data flows matter
AI risk is not just about which tools are used.
It is about what data is being sent, how it is processed, and where it goes next.
Without data flow visibility, you cannot:
Prevent sensitive data exposure
Enforce data policies
Understand model behavior
Audit decisions
What Peridot tracks
Peridot captures:
Sources
Files
SaaS systems
Databases
APIs
Logs
Destinations
AI models
Applications
External systems
Context
Who initiated the interaction
Which system executed it
Which policies applied
Mapping data movement
Each data flow represents a path:
Source → Processing → Destination
This allows you to:
Trace how data moves
Identify risky patterns
Apply controls at specific points
Data flows as a control surface
Data flows are not passive logs.
They are active control points where policies can:
Restrict access
Filter data
Route requests
Trigger approvals
Continuous tracking
Data flows are updated in real time as:
New interactions occur
Systems change
Policies evolve
What to do next
Review Monitoring AI Data Movement for deeper visibility
Apply controls using Policies Overview