AI Order & Driver Manager
Budget: £250 – £750 GBP
I am building an AI-driven solution that lets takeaway and restaurant staff see incoming orders in real time, have those orders routed intelligently to the right driver, and record the exact cash or card amount collected on every drop-off without anyone keying numbers in by hand. The system must run seamlessly as both a web application for the restaurant dashboard and a companion mobile app that drivers carry on the road.
Core workflow
• Orders arrive from the POS or online channel and appear instantly on the web dashboard.
• A routing engine evaluates driver location, capacity, and estimated delivery time, then assigns the job automatically.
• When the driver marks the delivery complete in the mobile app, the order status closes and the cash balance for that run is logged automatically; totals are visible per shift and per driver.
• Integrated payment processing handles card transactions inside the same flow so there is a single ledger for cash and electronic payments.
What I expect you to deliver
• Production-ready web dashboard (React, Vue, or comparable) for order management and real-time monitoring.
• Cross-platform mobile app (Flutter, React Native, or comparable) for drivers with live push updates, navigation link-outs, and proof-of-delivery capture.
• AI/logic layer for automatic driver assignment that can learn from historical delivery times and driver performance.
• Secure database and API layer tying everything together, with role-based access for managers, kitchen staff, and drivers.
• Automated cash count reporting per order, per driver, and per shift, exportable as CSV/PDF.
• Basic test suite and deployment instructions so I can launch on my own cloud account.
Acceptance criteria
1. Creating a test order triggers an assignment within 2 seconds and places the job on the selected driver’s mobile queue.
2. Marking the job complete updates the cash ledger instantly on the web dashboard and in the reporting export.
3. At least 90 % of orders in a 100-order stress test are assigned to the optimal driver (shortest ETA) according to preset rules.
4. Web and mobile interfaces remain usable on standard modern browsers and both iOS & Android phones.
If you have relevant experience with real-time dispatch, route optimization, or payment integration, I would like to review examples of your work alongside your proposed tech stack and timeline.
Core workflow
• Orders arrive from the POS or online channel and appear instantly on the web dashboard.
• A routing engine evaluates driver location, capacity, and estimated delivery time, then assigns the job automatically.
• When the driver marks the delivery complete in the mobile app, the order status closes and the cash balance for that run is logged automatically; totals are visible per shift and per driver.
• Integrated payment processing handles card transactions inside the same flow so there is a single ledger for cash and electronic payments.
What I expect you to deliver
• Production-ready web dashboard (React, Vue, or comparable) for order management and real-time monitoring.
• Cross-platform mobile app (Flutter, React Native, or comparable) for drivers with live push updates, navigation link-outs, and proof-of-delivery capture.
• AI/logic layer for automatic driver assignment that can learn from historical delivery times and driver performance.
• Secure database and API layer tying everything together, with role-based access for managers, kitchen staff, and drivers.
• Automated cash count reporting per order, per driver, and per shift, exportable as CSV/PDF.
• Basic test suite and deployment instructions so I can launch on my own cloud account.
Acceptance criteria
1. Creating a test order triggers an assignment within 2 seconds and places the job on the selected driver’s mobile queue.
2. Marking the job complete updates the cash ledger instantly on the web dashboard and in the reporting export.
3. At least 90 % of orders in a 100-order stress test are assigned to the optimal driver (shortest ETA) according to preset rules.
4. Web and mobile interfaces remain usable on standard modern browsers and both iOS & Android phones.
If you have relevant experience with real-time dispatch, route optimization, or payment integration, I would like to review examples of your work alongside your proposed tech stack and timeline.