We developed Boxiz for iOS and Android platforms using Flutter. Flutter allows us to write code once and then use it on multiple platforms. This saves lots of time and provides a 100% guarantee of UI and business logic consistency for both platforms. 

Since Boxiz is intended to run in portrait mode, we took this into account when designing and developing the application. 

We analyzed our client business idea to define a product vision and prioritize the scope of work. Then we started developing the app architecture, using the established Clean Architecture standards, defined the data structure, designed the UI, deployed the app, and published it to the Stores. 

In the app, we created a dynamic line and localization manager that enables admins to edit any text lines (like headers, footers, and buttons) in the application from the Admin dashboard. Also, thanks to our added dynamic resources, most of the icons, images, colors, and other UI items can be changed from the Admin dashboard. 

We split the development process into two phases and first developed an MVP version of Boxiz with the most important functionality in four months. Once we got feedback from users, we went on developing other features.

To tell prospective users about Boxiz, build the brand, and create a better user experience, we developed a landing page. 

For some features, we needed to integrate external services. For example, we integrated Twilio to send alerts and reminders connected with the game mode, prizes, and referral bonuses. To enable push notifications, we used Firebase. We also implemented SportsDataIO to collect sports data in real time and ABIOS for Esport games, allowing us to get the most detailed data and broadest coverage of matches. 

We built the frontend using React, to add statistics we used S3.

We developed the backend with Python 3.7 and Django 2.2. We also used the Django REST framework to support REST API.

When creating the architecture of Boxiz, we crafted a one-size-fits-all solution that allows us to easily integrate all leagues and games.

During development, we focused on speed and high performance. We wrote load tests to see how well our system is optimized. Those tests showed that a normal server wouldn’t meet high traffic demands. This is why we integrated AWS auto scaling.

One of the nontrivial tasks was to find services which provide real-time sports data via an API and integrate with them. Another challenge was that different games have different periods like quarters, halves, and innings. We made the period system universal, easy to scale, and easy to modify by the administrator.