ARCHITECTURE BRIEF / HOSPITALITY / AI

Hospitality operations that survive offline

CafeChee’s edge-to-cloud architecture for multi-branch operations, recommendation serving, and durable local writes during network interruptions.

GoOffline-firstAI

Architecture briefs supplied for this portfolio. Scope figures are from the brief; production outcomes are not independently verified.

Localdurable write path
Asyncedge-to-cloud sync
AIversioned recommendations
System topology
System topologyBranch operations → Local transactional store; Local transactional store → Transactional outbox; Transactional outbox → Retrying sync agent; Retrying sync agent → Cloud ingestion; Cloud ingestion → Operations analytics; Versioned recommendation model → Branch model cache; Branch model cache → Branch operationsVersioned recommendationmodelBranch model cacheBranch operationsLocal transactional storeTransactional outboxRetrying sync agentCloud ingestionOperations analytics

Keep the branch operational

The supplied CafeChee brief calls for multi-branch restaurant operations and recommendations during unreliable network conditions. The critical write path belongs at the branch, while analytics and model distribution can converge asynchronously.

Transactional outbox

Write the business record and the outgoing event in one local transaction. A synchronization worker delivers events with stable IDs. The cloud acknowledges only after durable storage, and duplicate delivery is handled with a uniqueness constraint.

Conflict policy

Orders are append-oriented records, not shared mutable documents. Inventory corrections are explicit adjustment events. Configuration uses version numbers, with a documented conflict policy and a review path instead of silent overwrites.

Recommendation serving

Cache a versioned model or recommendation artifact at each branch. Keep a deterministic fallback when the artifact expires or model evaluation fails. Changes to the recommendation model must not block checkout or order recording.

Operating questions

  • How much local disk is available before sync lag becomes dangerous?
  • How are clock drift and out-of-order events handled?
  • Can an operator inspect and retry a failed synchronization batch?
  • Which personal data is necessary, and what is its retention period?

Validation plan

Exercise the system through a simulated network outage, duplicated batches, and a model rollback. Publish throughput and business improvements only with evidence; the brief does not supply verified restaurant counts or measured AI outcomes.