Policies Overview
Policies define how AI is controlled in your organization.
They determine which models can be used, what data can be accessed, how integrations behave, and what actions are allowed.
Without policies, visibility does not translate into control.
What policies control
Policies can govern:
Model usage
Allowed providers and models
Routing logic
BYOK requirements
Data access
What data can be sent to AI systems
Which sources are restricted
Context-based filtering
Integrations
Which systems can be accessed
What actions are permitted
Workflows and actions
When approvals are required
What actions can execute automatically
Policy-based routing
Peridot supports policy-based routing of AI requests.
This allows you to:
Route sensitive workloads to approved models
Enforce provider restrictions
Separate environments (dev vs production)
Routing decisions are made centrally, not within individual applications.
Enforcement
Policies are enforced in real time.
Enforcement actions may include:
Blocking requests
Re-routing to approved systems
Triggering human approvals
Logging violations
Policies as a control layer
Policies operate across:
AI Inventory
Data Flows
Applications
Integrations
This ensures that control is consistent across the entire AI environment.
Why this matters
Most organizations define policies but cannot enforce them.
Peridot turns policies into executable control.
What to do next
Create your first policy in Creating Policies
Connect policies to workflows using Enforcement Actions