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High Performance Dating App with Unique Custom Matching Algorithm for Android

A tech-savvy start-up company had a clear vision of its Android dating app with original gamification features. It was searching for a contractor with proven mobile app development expertise, who would put into life the idea, provide the app’s scalability with regard to a growing number of users and guarantee the stability of its functioning.
R-Style Lab was chosen for its extensive record of successful Android projects, clearly defined teamwork processes and reasonable rates.

A tech-savvy start-up company had a clear vision of its Android dating app with original gamification features. It was searching for a contractor with proven mobile app development expertise, who would put into life the idea, provide the app’s scalability with regard to a growing number of users and guarantee the stability of its functioning.
R-Style Lab was chosen for its extensive record of successful Android projects, clearly defined teamwork processes and reasonable rates.
Technologies & tools
Server- and web-based components: PostgreSQL (including Poistgres-XC and Pgpool-clustering for read/write scalability), Amazon RDS Cloud;
Mobile app: Android SDK, Retrofit, RxJava, Dagger, OkHttp, Socket.IO, Google API, Twitter API, Facebook API;
Project team
2 Android developers, 1 Team Lead, 2 PHP developers, 1 Tech Lead, 1 Project Architect, 1 PM, 1 QA.

Solution

The intelligent matching algorithm which the R-Style Lab mobile app development team implemented was the most challenging part of the development phase. The algorithm works as follows: a user answers a range of closed-ended questions (yes/no/maybe), then the app analyzes the received data, filters similar profiles and offers matches to the user. The matching potential is displayed on the icon associated with a user’s profile and reflects a growing or decreasing level of matching with a prospective partner. More questionnaires and, as a result, more filters are available to paid users to make the selection process more precise.

To support a growing number of users, R-Style Lab developers offered the Amazon RDS and PostgreSQL tech stack. The PostgreSQL database, enhanced by its geospatial extension, allows to improve the application performance when searching for the closest match. The Amazon Service supports the app’s scaling up in the cloud.

The key features of the end product include:

  • User accounts which provide for secure registration and authorization, feature social single sign-on via social media API integration, and enable profile management and secure data exchange with the back-end implemented with SSL protocol.
  • Built-in live chat with message exchange being open only to users who have ‘liked’ each other, as users’ privacy and the security of their communication was one of the client’s priorities.
  • In-app purchases which unlock specific matching categories.
  • User-friendly admin web panel based on our custom-made PHP framework to access the app’s reports and statistics and monitor user activities.

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