Describe how customer data flows through your stack and the AI draws collection, identity, storage, audiences, and every activation destination
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Unify identities, events, and traits into real-time profiles for activation and analytics
Describe which warehouse models feed which business tools and the AI draws the activation layer, syncs, audiences, and the systems they land in
Implement policies, access controls, lineage, and approvals to keep data compliant
Common questions about ai customer data platform architecture generator
Yes, and drawing both is the usual way teams make the decision: the packaged version shows the vendor in the middle, the composable version shows the warehouse in the middle with best-of-breed pieces around it. The diagrams make the ownership and cost differences visible immediately.
Identity stitching renders as its own stage (anonymous IDs, login events, and the matching logic between them) with assumptions annotated as assumptions. Most CDP diagrams hand-wave exactly this part, which is why they do not survive contact with engineering.
Consent flags, policy filters, and deletion propagation can be drawn as explicit paths. For EU-facing stacks that is the difference between a diagram you can show a DPO and one you cannot.
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