E-learning application suite

  • Country


  • Industry

    Media & Education

  • Type

    Web, Desktop,
    Mobile, Backend

  • Duration

    15 Years


The client’s software is intended to help language learners memorize new words and broaden their vocabulary in any one of some 100 languages and dialects, including those not so wide-spread.

The application is based on the flashcard concept. Each new word to learn is displayed on a card. The reverse side of this card defines the term in a user’s mother tongue, an explanation, and an image to illustrate the new entry.

The app’s vocabulary consists of the more frequently used words and expressions associated with them.

Words are presented to a user based on an intricate proprietary algorithm, displaying them in a particular order that varies depending on how often a user viewed a word, and on whether a user gave a positive or negative answer when asked if he/she already remembers the word. The more often a user studied a word, the less often it is displayed to him/her.

It is possible to generate statistics on the vocabulary learned. The statistic presented to a user in the form of infographics.

The functionality of the app also allows keeping history on each of the words the user studied a while now and tracking related progress.


Transparent Language approached us with a request to develop the iOS and Android versions of their legacy e-learning application.

Envion Software team of 4 iOS and Android developers, assigned to implement the project, came across several highly formidable challenges. The main one was neither of the two target platforms had sufficient language support.

There are a lot of nuances directly influencing on rendering in written form in many languages. For example, differences in the way the same letter is written depending on where it appears, the need to use certain letters in certain parts of sentences, and so forth. Only several dozen widespread languages are rendered properly by iOS/Android, while the rest require preprocessing for correct rendering.


To overcome the above challenge, the project team had to implement a custom cross-platform text processing engine combined with a HarfBuzz library to enable support of the OpenType features.

They also implemented a custom multilayer text-rendering engine with a FreeType library to function as a rasterization backend.

As a result, such complex languages as Hindi, Thai, Farsi, and others came to be rendered perfectly well.

Also, vocabulary cards are shared between all the company’s products. So, we needed to deliver a solution for efficiently distinguishing one card from another.

The project team implemented a special library that identically pre-processed card texts on all the platforms. The preprocessed texts are then used to generate a special hash-value serving as the identifier of a particular card. We used a meta-programming paradigm for creating the library and allowed generating source code in C++, Java, ActionScript 3, and JavaScript.

The project has been ongoing for over a decade now. Currently, our team provides support for the app and occasionally adds some new capabilities (for example, notifications about new features, the word of the day capability, and more).


  • Objective-C
  • C/C++
  • Android SDK
  • Android NDK
  • JNI
  • Java
  • JSON
  • REST
  • SQLite
  • Python
  • ORM
  • CMU Sphinx
  • Mathlab
  • JavaScript
  • HTML
  • Moodle

Michael Quinlan

CEO of Transparent Language

“Envion Software team has developed a range of essential projects for our web, desktop, mobile platforms and server managed devices. Our product line and technology strategy delivered efficiently by Envion Software, we can truly call them our partners rather than just a company we outsource our programming too. Cooperation with Envion Software is a competitive advantage of our business. Therefore, our company plans to continue the collaboration with Envion Software, not to mention all the amazing products to come as the fruitful result of our partnership.”

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