•The authors develop a tool able to assist engineers during the most repetitive tender phases.•The tool’s aim is saving time and bring strategic advantage to the adopting companies.•It allows the semi-automatic treatment of tender’s large technical documentation.•The methodology is tested in the industrial setting of a leading train manufacturer.•The test shows a large performance increase compared to previously adopted solutions. Tenders or technical terms contain a large quantity of both technical, legal, managerial information mixed in a nested and complex net of relationships. Extracting technical and design information from a document whose aim is both legal and technical, and that is written using several specific jargons, is not a trivial task: the purpose of the research is to try to detect, extract, split and assign information from the text of a tender in an automatic way. It means being able to understand technical and legal terms and organize them in multiple ways: according to product structure, internal organisational structure, etc. The focus is in providing a handy tool that could speed up and facilitate human analysis and allow tackling also the process of transforming customer’s requirements into design specifications. The approach chosen to overcome the various issues is to support state-of-the-art Computational Linguistic tools with a wide Knowledge Base. The latter has been constructed both manually and automatically and comprises not only keywords but also concepts, relationships and regular expressions. The implementation of the methodology has been carried out during a project for AnsaldoBreda S.p.A. (now Hitachi Rail Europe). A case study about the tender for a high-speed train has been included to show the functioning and output of the entire software system.