RAG in Production: the Case Study of SEA Trasformatori

This work presents a comprehensive study of the design, development, and deployment of a Retrieval-Augmented Generation (RAG) chatbot system developed to enhance knowledge accessibility and information retrieval efficiency within SEA Trasformatori. The proposed system enables technical personnel to access the full corpus of technical instructions for electrical transformers efficiently, thereby reducing retrieval time and supporting improved operational decision-making.