We’re pleased to tell you about an amazing fleet management software for small businesses that we've worked on recently.
It is the most significant fleet management solution we had the chance to be a part of and one of the biggest challenges Celadon has faced: we had to take over the project with the unfinished legacy code.
We conducted a comprehensive analysis of the code and performed up-to-date work. We came to the conclusion that the selected approach had architectural issues and its quality was below the standard required for such a project to perform smoothly on the scale.
Fleet administration software for remote management of workers, vehicles, and routing optimization. Web and Mobile system includes cloud backend
Fleet management app features provide insights for the management about the location of staff and vehicles
We started fleet management software development with legacy code refactoring and improving the UX/UI. We knew that gaps and mistakes in fleet management software design can lead to disastrous wasting of time and nothing less than software architecture approach errors. We quickly managed to implement an alternative architectural solution and reuse the biggest part of the written backend code. However, most of the frontend had to be rewritten because the wrong UX approach had been chosen at the beginning.
Once we had a clear vision of where we stood with the project (it took less than one month to reach this), we started the management software development of a new functional. We used the best fleet management technologies to reach our goals.
The system comprises a fleet management app development with GPS, orders, navigation, and a complex fleet management web interface with flexible permission-based role managing systems.
The interactive cross-platform map with navigation, information overlay, and special modes for different roles deserves some special attention.
Due to our Business Intelligence and Machine Learning background we’ve integrated the right approach to capture and store the operations data for further analysis and system automation.
As a result of our ongoing engagement, the client managed to reach savings on the operational cost of up to 30%. At the same time, the client accumulated valuable data that we’ve already started to use for building the ML models for fleet management automation features for further enhancement. So, despite the wide selection range of fleet management software companies, the client has picked us to order the development of fleet management software.
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