At VRAIN, we work with recommender systems, which are tools that extract a set of criteria and evaluations from user data to make predictions about recommendations of items that might be useful or valuable to the user or companies. These types of systems can be applied, for example, to online shopping services, where user preferences are extracted from a purchase history or from interactions with the service itself (such as Amazon, Netflix, or Spotify). They can also be used to improve processes within a company, for example, to recommend candidates for a specific position in the HR department.