Exosomes, nanoscale extracellular vesicles, are a hot area of investigation in the biomedical field, as they have been shown to play a crucial role in the physiology of numerous tissues, including bone. This study explores the landscape of exosome-based bone regeneration research using infometric techniques. By relying on BERTopic, an advanced topic modeling algorithm, we analyzed a comprehensive corpus of scientific literature to identify key themes and trends in exosome research in the bone regeneration field. We then extracted significant concepts from the abstracts of the corpus and we used them to create knowledge graphs using GPT 3.5 turbo Large Language Model, to map the distribution of information within this domain. The resulting ide-oscape highlights the key ideas that aggregate most of the recent research in the area, from mesenchymal stem cell-derived exosomes to engineered exosome-integrated biomaterials. This exploration provides a holistic view of the field and uncovers its emerging trends, providing useful insight to guide future research directions.