To design a modular edge computing platform that allows the deployment of an in-store infrastructure capable of capturing information related to the activity of a store (sensor network, video, Smart tags, indoor location…), as well as offering support for the virtual assistant model (displays, sales panels, audiovisual systems…).


To integrate and merge data collected from heterogeneous sources (stock management systems, sales management, personnel, OLD, in-store infrastructure, RRSS…) into an intelligent software platform to generate a knowledge base that handles, on the one hand, operational information and, on the other hand, the set of registered customer profiles.


To design AI algorithms that allow predictions to be made based on the history of in-store operations (anonymous information) and the profile of the customers who visit the store (personalised data), in order to develop strategies (decision support system) that optimise sales based on a series of commercial objectives.


To define a solution for the optimisation of in-store operations that provides an intelligent system for stock management and allows direct interaction with customers.


To validate the solution for the improvement of the customer experience throughout the purchase process in a use case that allows to evaluate the impact generated in the brand/customer relationship.