Hospitality / Event Catering
Order Intelligence
An AI order engine for multi-city coffee catering — ops answers a quiz about how they actually serve, then the system calculates quantities and lets a manager review, apply, or revert every suggestion.
Order Intelligence
The challenge
Event Espresso was guessing cups, milk, staff, and specialty drinks from memory. Over-ordering wasted inventory. Under-ordering killed the event. The knowledge lived in people’s heads, not in the order.
Our solution
We built Order Intelligence as its own engine inside the catering stack: an ops quiz, a deterministic calculator, and an AI review-and-apply loop.
Ops answers canonical questions on beverages, supplies, staffing, and event type — cups per attendee, oat-milk share, wedding vs corporate multipliers, waste, and buffer. Those answers become order line quantities. Missing or bad answers fall back to the old rules.
OpenAI then suggests adjustments from event context and business knowledge. Managers view, apply, or revert. Nothing writes blindly. A natural-language Q&A box sits on top of the current order.
Technology used
- Django / DRF
- OpenAI
- Next.js 16
- React 19
- TypeScript
- TanStack Query
The results
Live inside BrewTrack at app.wecatercoffee.com for real event orders.
Model output is trustworthy because it is reversible and grounded in ops-authored answers.
Separated from the ops platform so the AI engine can be judged on its own: quiz → calc → review-and-apply.
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