The MOD holds an enormous amount of unstructured text data. One of the barriers to using standard models to gain insights from this data is the extensive use of bespoke acronyms: there are more than 21k acronyms commonly in use across the MOD, with some of them representing up to 17 different meanings. This complexity means creating a straightforward acronym dictionary was impossible. They needed a tailored solution to recognise and retrieve the long explanation of acronyms in text.