Conversational Bots

Our initial idea was to develop a comprehensive framework that supports a cognitive and highly adaptable conversational bot that operates on or uses data stored in a Blockchain. We started by learning a wide range of technological trends, as we knew that the final outcome of the project would be continuously evolving.
The goal was to design a Conversational Bot that could sit on a supermarket shelf and proactively offer customers information about the product they selected. The envisioned scenario involved a voice interaction between the user and the bot sitting near the shelf. Upon detecting a customer picking up a product from the shelf, it would initiate a conversation with the customer, congratulating them on their choice and encouraging them to inquire about other aspects of the product, such as preservation, storage, temperature, usage, origin, and product composition.

To explore this solution, we began a study of Machine Learning techniques (ML) applied to the human-machine interaction interface. Our goal was to identify intelligent properties and improve the user experience (UX) of the interaction. This solution considers several components, namely the interaction with human users, which is improved by using ML techniques and its processing component. The interaction component takes advantage of progress in artificial intelligence used to improve the user experience (UX), in particular NLP, image and speech recognition.

The Research and Development project is fully in line with LOAD’s strategic growth objectives, as it allows us to research and develop innovative solutions in the field of new user interfaces, with a particular focus on “Natural Interactions.”
To meet the evolving demands of customers and organizations, we are committed to researching disruptive and intelligent human-computer interactions. By applying Machine Learning techniques, we can enhance the User Experience (UX) and provide more accurate and reliable responses to end-user needs.