Retrieval-Augmented Generation to Support Railways Engineering Tasks: A Case Study
摘要
The growing number and complexity of technical regulations represent an important challenge for all professionals in regulated industries. This paper describes a case study, from design to deployment, of building a Retrieval-Augmented Generation system for the consultation of complex technical regulations in the railway domain. Although developed for the railway sector, this testimony of an industrial experience is of particular value for technical domains where regulatory compliance and accurate information retrieval from complex documentation are essential requirements. It also constitutes a human-centered approach for implementing LLM-powered technical documentation consultation across various regulated industries, balancing technological capabilities with domain expertise.
引用
@article{arxiv.2607.01244,
title = {Retrieval-Augmented Generation to Support Railways Engineering Tasks: A Case Study},
author = {Andrea Gerardo Russo and Federico Ruggeri and Ivan Tomarchio and Davide Bombini and Nicolò Donati and Gianmarco Pappacoda and Paolo Torroni and Giuseppe-Emiliano La Cara},
journal= {arXiv preprint arXiv:2607.01244},
year = {2026}
}