How should Local AI Discovery adapt to a hub-and-spoke Digital Twin when a multi-location brand adds new locations or changes local regulations?

In a hub-and-spoke Digital Twin, Local AI Discovery surfaces localized signals that reference the hub's canonical facts via language-aware mappings. To adapt when new locations or regulatory changes occur: 1) map locale signals to hub fact_ids and attach locale-specific proofs; 2) run drift detection to flag local mappings that diverge from hub facts; 3) route updates through Change Control, version the changes, and publish locale updates back to the locale surfaces; 4) maintain a provenance panel to attribute which locale contributed which proofs without duplicating central content; 5) preserve a single source of truth in the hub while keeping localized surfaces responsive to AI queries.