Abstract In the last decade, the major private IT companies have developed lots of cloud platforms for Natural Language Understanding (NLU), that are widely used for research and commercial purposes. One of the main reasons for the success of NLU platforms is because they allow to simplify the Chatbots or Spoken Dialogue Systems (SDS) development and, in many cases, without knowledge about programming languages. In this paper, we present a general description and a taxonomy that brings together features and constraints of different cloud-based NLU services available on the market. Furthermore, we provide an evaluation and a comparison concerning the ability to recognise the underlying intents of different sentences. The sentences used are a collection of requests made by users in Italian on an e-learning platform. This analysis wants to help the company, owner of the e-learning platform, to understand in which NLU platform it is better to build a chatbot for the Italian language aiming at answering the most frequently asked questions.