Case study · Food delivery
AI dispatch and live tracking for a food delivery startup
A fast-growing urban food delivery startup was losing customers to slow deliveries at peak times. We built AI order dispatching and connected restaurants, drivers and customers in real time.
Context
The client and the situation.
The client connects restaurants and customers through a mobile-first platform in major cities. It was growing quickly, but its operations could not keep up at lunch and dinner peaks.
Challenge
What was holding them back.
- Deliveries were slow at peak hours.
- Orders were dispatched inefficiently.
- Restaurants and drivers were poorly coordinated.
- Delays were hurting customer satisfaction.
Approach
How we framed the problem.
We treated this as real-time optimization combined with experience design. Dispatch uses live data, and every party sees accurate timing.
What we built
The product, module by module.
AI dispatching
Assigns orders by driver location, traffic and restaurant preparation time.
Operations dashboard
Live order tracking, driver performance and delivery heatmaps.
Driver app
Optimized routes, an order queue and real-time updates.
Customer app
Accurate delivery estimates, live tracking, checkout and one-tap reorder.
Restaurant dashboard
Order management, preparation-time optimization and demand forecasting.
Results
What changed.
Results reported for the project after launch.
Technology
Stack used.
- React
- React Native
- Node.js
- Routing and dispatch optimization
- Google Maps API
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