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iOS Social Networking App

Optimizes UI operations through parallel threads, employs ML-driven activity stream

  • Autofac
  • xUNit
  • Entity Framework
  • Getstream.io
  • IdentityServer4
  • React.js
  • redux
  • axios
  • Xamarin
  • Microsoft Azure

iOS social networking app


Media and Entertainment

Engagement model

Fixed Price



  • Xamarin Developers
  • Backend Developers
  • Frontend Developer
  • Business Analyst
  • QA Lead
  • QA Engineer
  • Project Manager



The client had an idea of a service, which started off as a playful social experiment. Each member of the experiment would have had one’s own “IOU currency”, which he/she could exchange and redeem for favors performed. To be able to keep track of and easily manage each member’s personal currencies, it was decided to create a dedicated mobile app.


Softeq delivered an iOS app, admin panel with a backend, and a landing page. The solution has the following features:

  • Posting and accepting favors
  • Following friends to view, like, share and comment on their favors
  • Creating a personal currency and using it as a digital IOU for favors
  • Tracking the collected currencies from completed favors
  • Viewing the currency performance compared to others
  • Cashing out currencies in the user’s wallet for future use in the network
  • Using the Admin Panel the system administrator may block inappropriate or abusive users and view the transactions stats.

Technological Facilitators

To make the app’s UI smooth and responsive, the team employed Texture, an iOS framework built on top of UIKit. The framework allows moving such expensive UI operations as image decoding, text sizing, rendering, and others, off the main thread. This way the thread is kept available to respond to user interaction. This helps optimize the time for executing the entire layout and drawing code.

The app also relies on GetStream.io, an API for building an engaging activity stream, which loads fast, facilitates content discovery, and ensures the users see the most relevant and current content. The API’s personalization technology leverages machine learning to improve the feed based on user engagement.


The app is integrated with Facebook and employs the platform enabled user authentication mechanism.


The solution was delivered on budget and on time. The customer researches potential investment opportunities to extend the app with an Android version.