The tool breaks through the limitations of single-document conversion and innovatively supports the architectural design of main PDF + auxiliary PDF. Technically, it uses a vector database to build a cross-document semantic index, and when processing the main document, the system will retrieve the relevant concepts in the auxiliary PDF in real time. For example, when uploading the main specification of the drug, related to clinical trial reports and white papers, the AI will automatically label the cross-references such as "See Appendix 3 Pharmacokinetic Data".
The value is evident in enterprise-level applications: product teams can link user manuals and technical specifications to generate training materials; research organizations can integrate papers and lab logs to create audio reviews. Internal testing has shown that introducing 3 contextual PDFs can increase the accuracy of terminology interpretation from 68% to 92%, dramatically reducing the one-sidedness of information in a single document.
This answer comes from the articleNVIDIA PDF to Podcast: AI Tool for Converting PDF to Podcast by Setting Guiding PromptsThe
