Scalable Ride-Hailing Technology
A robust cab booking solution with seamless navigation, real-time features, and optimized performance, enabling efficient ride management and enhanced user experience.
The Challenge
Utoo Cabs was operating with a fragile, monolithic booking system that couldn't handle surge demand reliably. Drivers and riders frequently experienced dropped connections, inaccurate ETAs, and booking failures during peak hours. The existing app had no real-time ride tracking, and manual dispatch was consuming significant operational overhead. They needed a ground-up rebuild that could scale to thousands of concurrent rides while maintaining sub-second responsiveness.
Our Solution
We rebuilt the platform from scratch on a microservices architecture with WebSocket-based real-time communication at its core. The rider and driver apps were developed in parallel, sharing a live location infrastructure powered by a geospatial database. We implemented a custom matching engine that factors in driver proximity, traffic conditions, and vehicle type to assign the optimal driver within seconds. Surge pricing logic, trip lifecycle state machines, and an admin dispatch console were all built as independent, deployable services.
Our Approach
Platform Architecture & Tech Selection
Evaluated ride-hailing infrastructure requirements and selected a stack centered around WebSockets, Redis pub/sub for real-time updates, and PostGIS for geospatial queries. Designed the service boundaries and data flow between rider, driver, and dispatch systems.
Rider & Driver App Development
Built native-quality cross-platform apps for both riders and drivers using React Native. Rider app covers booking flow, live tracking, fare estimation, and in-app payments. Driver app handles job acceptance, navigation handoff, earnings dashboard, and availability toggling.
Real-Time Matching Engine
Developed a geospatial matching engine that queries available drivers within configurable radius rings, ranks candidates by estimated arrival time, and handles automatic re-assignment if the primary driver doesn't respond within a timeout window.
Ops Dashboard & Launch
Delivered an operations dashboard showing live fleet positions, ongoing trips, and cancellation rates. Ran a phased beta with 200 drivers before the public launch to surface edge cases in payment settlement and trip cancellation flows.
"The new platform handled our launch-day demand without a single outage. Driver acceptance rates jumped immediately because the app actually works the way drivers expect it to."
Let's Build Together
Have a similar challenge? We'd love to hear about your project.