M A N D A R I N E A C A D E M Y

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One year ago, we have begun to use artificial intelligence in our training platforms. Find out in this article how we use AI.

Why does Mandarine Academy use artificial intelligence?

Thanks to our SaaS training platforms, we offer our customers a customizable platform to discover all the uses and products of a solution. Our platforms allow us to integrate a large number of content to meet all expectations, and have a powerful logistics engine for communication management up to training. We build our platforms with you to ensure that all elements, from communication to training, are designed to adopt your users’ uses.

However, through our years of experience in the field of training, we have found that we all have a different perspective. Our profiles, our professions, our operating methods, and our companies are different, so our uses are also different.

We are all different. So why follow the same training path?

Digital & training

Today, digital technology brings new ways of learning. It allows us to:

  • Advice: by analysing training needs
  • Communicate: by creating a differentiated and engaging communication model for each user
  • Training: by automatically creating training courses adapted to the profiles of users, employees of the same company, and the needs of each use
  • Predict: AI allows us to anticipate expectations in order to be able to predict high expectations, and to predict the organization and logistics of training.
  • Monitor: monitor skills through interactions with a BOT

So that’s why we started working with artificial intelligence. We want to be able to customize each user’s training through adaptive learning.

adaptive learning

Adaptive Learning, how does it work?

We had to create a model to provide relevant content for learners with artificial intelligence. This includes course descriptions, tags, video indexing, etc. We then had to make sure we knew more about our learners. about their jobs, their sectors of activity, their interests, and track their activity on our platforms.

The model then requires to be executed and refined over time and to offer a fully customized training page to each user. The development of the model is, in fact, done by each learner. Each user is an actor in the proposed recommendations because AI is based on the activity of each user on our training platforms. The more the user consults the platform, the more the AI will be able to recommend other relevant content.

recommendation index

Would you like more information? Contact us now