The project introduces an innovative visual method for analysing libraries and archives, with a focus on Bibliotheca Hertziana’s library collection. This collection, which dates back over a century, is examined by integrating user loan data with deep mapping techniques to reveal usage patterns and thematic clusters. To achieve this, dimensionality reduction is employed to visualise the catalogue, map- ping books based on their loans, and prompt engineering with large language models helps to identify loan clusters with detailed descriptions and titles. This approach not only paves the way for cultural analytics but also provides the basis for dynamic classification and developing a recommendation system. This project offers alternative insights into the art historical research conducted at Bibliotheca Hertziana, capturing the collection’s evolution and usage. The method established here provides a flexible framework for visually mapping cultural and academic collections in the digital humanities.