A WhatsApp ordering journey connected to menu management, kitchen queues, staff actions, customer notifications, and feedback.
Operating system
Conversational commerce
Operating context
A busy hospitality team needs the ordering channel, fulfilment queue, and customer updates to behave like one system. Manual transcription creates missed items, uncertain wait times, and weak order traceability.
The challenge
Let a customer order naturally in chat while preserving deterministic prices, quantities, order states, staff accountability, and a practical fallback when language understanding is uncertain.
The system response
The experience combines natural-language parsing with a structured menu and explicit confirmation flow. Orders move into a staff and kitchen workspace with quick status actions, scheduling, payment state, customer notifications, and an audit trail.
Product scope
System architecture
A narrative view of the system boundary. Each layer creates a cleaner handoff into the next and keeps consequential work visible.
The chat layer interprets customer intent against a controlled menu.
A confirmation boundary converts conversation into an order record.
Kitchen and staff surfaces manage the fulfilment state machine.
Status changes trigger customer-facing updates.
Operations data feeds menu, customer, and feedback views.
What the work demonstrates
These outcomes describe the product and operating model visible in the repository. They are not presented as confidential client KPIs.
Natural conversation without sacrificing transaction structure
One order state shared by customers, staff, and kitchen operators
A reusable pattern for chat-led commerce beyond hospitality
Repository evidence
Technical material
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