Demo Scenarios
Demo scenarios show how Compex supports Train, Analyze, and Serve workflows on synthetic data. They are designed to make governance visible: policy, approval, execution, outputs, and evidence records.
Scenario examples
Train: risk model evaluation
Train or evaluate a model against a synthetic regulated dataset while recording approval and output review.
Analyze: cohort query
Run an aggregate query with bounded outputs and a visible evidence trail.
Serve: scoped API
Serve a model or application to approved users without exposing the underlying synthetic records.
What this means
For business readers, demo scenarios make the abstract idea concrete. They show the governed path between a data owner, an AI company or processor, and a DPO / legal reviewer.
Current status
Demo scenarios should be treated as product education material. They help scope a pilot but are not substitutes for pilot-specific configuration.
Limitations
Demo results are synthetic and should not be used to infer model performance, legal approval, or production readiness.
Request a guided pilot discussion
If a demo scenario maps to a real use case, start a pilot request with scope and roles.