A European vehicle leasing company
Automotive, vehicle leasing
Front-end and back-end development
AWS, Apollo GraphQL, Next.js, Vercel, Amazon Textract


The client is a European vehicle leasing company with a large web platform detailing different car models and handling leasing contracts. As the number of vehicles in the client’s database increased, the web pages became slow to load, which impacted user experience and conversion rates. The data on different car models was aggregated from multiple sources, adding to the overall delay. Also, the process of vehicle leasing, insuring, and returning relied heavily on manual document handling, which led to costly human errors. The company was looking for reliable back-end and front-end developers to eliminate these inefficiencies.

Our team was tasked with:
Adding new functionality, designing, and developing new web pages
Performing tests to find and fix any existing bugs
Optimizing the platform’s performance to minimize page loading time and improve user experience
Automating document processing
Migrating the front end from AWS to Vercel’s frontend cloud


In the context of updating the existing website and adding new functionality, our team took the following steps:
Designed and built new web pages, including “car review” pages, and “in stock lease deals” functionality, which allows clients to search for the right car based on budget requirements, fuel type, and other parameters.
Deployed micro front-end development architecture to transfer the “checkout” page and all the related functionality into a separate module. We designed the corresponding web pages and implemented the business logic behind them.
To optimize the vehicle leasing software performance, we accomplished the following:
Used Lighthouse, a web app audit tool, to perform tests and track performance, accessibility, and speed metrics of different web pages
Compressed some icons and other graphic elements to speed up loading
Migrated from Apollo Gateway to Apollo Router, which made queries on the website significantly faster as the Router’s response time is close to that of direct querie
Used lazy loading strategy to only load the parts of a web page that are being displayed on the screen, and load more components as the viewer scrolls through the page. This approach decreased the web pages’ loading time and made the displayed parts immediately available for interaction without waiting for the entire page to load.
Performed end-to-end (E2E) automated tests for popular flows, such as search and filtering, to make sure that our optimization efforts didn’t compromise functionality. Our team designed and documented these tests, and integrated them into the CI/CD pipeline for all environments except the production. During the E2E tests, we also discovered and fixed some critical errors, such as mistakes in the leasing price calculation.
Our team also worked on document parsing. Originally, all the documents related to leasing and insurance were processed manually, and human errors were common. Our developers automated document handling and enhanced the process with Amazon Textract – an intelligent document processing service, which includes a machine learning component for document analysis.
vehicle leasing software
vehicle leasing software development


Thanks to our team’s optimization efforts, the vehicle leasing software became more interactive, and the web pages started to load much faster, leading to a better user experience and willingness to use this platform
Automated document parsing significantly reduced human errors and streamlined car leasing and insuring processes
We discovered and eliminated functionality glitches, such as leasing price calculations for some vehicles

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