• SolutionsDevelopment
  • Technologies

    AngularJs, JavaScript, Python, Slack

  • Country Norway


QArea was asked to develop new functionality for the real estate web-application and implement it into the existing legacy code. Users had to be capable of filtering the results by the type, size, and approximate price of the property, and by the specific region of the city in which they want to sell or buy real estate.

Our team had to redesign the application and create a responsive mobile view of it from scratch in order to implement the lacking functionality. The app wasn’t compatible with major web browsers, so we also had to make sure it works flawlessly on the latest versions of Internet Explorer, Google Chrome, Mozilla Firefox, and Microsoft Edge.


Project Duration

7 months

Team Composition

Designers – 2

PM -1

Developers – 2


We were able to integrate the new, requested features into the existing code by using Python as well as AngularJS and Stylus frameworks.

To tackle the goal of making a responsive, user-friendly interface, the QArea team rebuilt the applications front-end completely from scratch. Our team implemented the required redesign following the clients Figma mockups. The app’s performance was improved by simplifying the interface and leaving only the most needed functionality.

The app’s backend was also changed. We personalized Google Maps API with custom bundles, clusters, and pop-overs so that users could find the properties easier. With the help of a neural network, we managed to create a filter that analyzes and estimates property prices according to the given information such as location, floor, the number of rooms, elevator and balcony availability, etc. The algorithm eliminates the possibility of fraud, which allows this app to stand out from the number of already existing aggregators that pull up real estate’s prices from other web resources instead of generating and outputting real numbers.


Engagement Model:

Dedicated team, Time and Material



Our Development

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Implemented features

  • Icon Checked Filter that analyzes and estimates property prices
  • Icon CheckedPersonalized Google Maps API
  • Icon CheckedUser-friendly interface
  • Cta-block-image

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    So far, all functionality implementations have been carried out seamlessly, which took us 7 months. However, the client wants to add more features, so we continue working on this project. Meanwhile, users can enjoy the Beta version of the app and find the desired properties by the honest, smartly-estimated price.


    Satisfaction rate


    Conversion of mobile app


    Bounce rate decrease

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