The company wants to launch a revolutionary marketing tool for large customers. This tool collects information about users through a variety of sources, analyses the information and makes decisions independently based on predefined by marketers client filters.
One of these data sources is the use of mobile phones by the user. To do this we need to develop a library for iOS and Android both native and hybrid for Cordova /
In collaboration with the project management we design the architecture of the library and API server. A study was performed to verify that the user can obtain data from your device and at the least intrusive manner as possible taking into account the legal limitations in this area.
This library must be also very simple to implement in any third-party app and offer the minimum collision with other libraries from other developers. Should consume little battery and little data, it must also behave intelligently depending on the charge state of the mobile or the quality of the data connection.
The library should be able to be manipulated remotely by the server to avoid possible having to resubmit applications that use the Apple and Google stores every change to decide to do.

Artifical intelligence for sales


Retail company


Create Android and iOS libraries – both native and hybrid- for Cordova. They were designed to consume very little battery and mobile device data.

Developed solution

After analysing the data can be obtained from mobile and use both Android and iOS (including their differences) and once we defined its legality below the following tasks:

  • Previous documentation with the list of data to be obtained
  • Creating iOS library for Objective-C
  • Creating Java library for Android
  • Creating plugin for Cordova / Phonegap with Objective C, Java and Javascript
  • Defining the API server with Swagger
  • Creating test apps for Android, iOS and Cordova
  • Pre-testing to QA
  • Code refactoring to reduce resource consumption: battery, data, etc.
  • First tests on the implementation of a real client app.
  • API documentation of the library.

Results obtained

  • Library compatible data collection iOS, Android and Cordova.
  • Battery consumption and data optimised to the maximum.
  • Communication system with the Rest of asynchronous server API based on the
  • Existence of Internet client
  • Excellent quality data for further analysis in the backend.

Baterry consumption optimization


Data quality improvement


Performance improvement