Driver App Development for a Ride-Sharing Platform
Highlights
- Driver-facing app for route guidance and ride execution
- Custom rerouting and fast route planning
- Built-in localization and city-specific configuration logic
- Deeplink support for faster development and testing
- Conducted automated UI and unit tests
Client
The client is a ride-sharing startup with a broader ecosystem that includes rider and driver apps, onboarding flows, and partner tools.
Challenge
The client needed a driver app that could do more than basic navigation. It had to support custom routes, fast rerouting, and clear communication during live operations. The app also had to work across different cities and countries, where rules, language, and operating logic could change. That made flexibility a core requirement. A single product had to adapt to different regions without turning into a set of separate apps that would be costly to maintain.
Solution
SoftTeco helped build and extend the driver app as part of the broader platform. The application guides drivers through custom routes, notifies them about route changes, and supports ride execution inside the platform’s operating model. The app also supports localization and city-level configuration, so the same core product can operate across different markets while adhering to local rules.
Tech Stack
Components
Zendesk
MVVM
Google Maps
Deeplinks
Unit tests
CityConfig
How it works
SoftTeco joined the project at an early product stage and became part of the long-term development and testing team. Our team worked on both mobile versions of the driver app and gave them a cleaner technical structure. On iOS, we used the Model-View-Presenter (MVP) pattern with the Coordinator pattern for navigation. On Android, we used MVVM and the Navigation Component. That gave the product a more scalable architecture and made feature delivery easier as the platform kept growing.
One of the most important parts was flexibility across cities and countries. We implemented the CityConfig mechanism, which allows the same app to adapt to different regional rules and operating logic without splitting the product into multiple codebases. We also supported built-in localization, which reduced duplication and made rollout to new markets more practical.
To speed up delivery and reduce regression risk, SoftTeco added deeplinks and performed automated UI and unit testing. Deeplinks made testing and feature validation faster. The automated test layer stabilized releases and helped the team support long-term product growth with less manual overhead.
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Results
SoftTeco has delivered a driver app that has become part of a broader ride-sharing platform. The product now supports route execution, rerouting, localization, and city-specific logic within a single app.
The technical structure has also become stronger. Better navigation patterns, configuration logic, and automated test coverage have given the client a more maintainable product and a more reliable development process, as the platform continues to grow.
