This talk addresses the challenges in effectively leveraging the full capabilities of Large Language Models (LLMs) for data extraction creating effective knowledge corpora and learning workflow options. We’ll explore strategies for handling diverse file formats including PDFs, CSVs, Excel sheets, and unstructured text, as well as data volume limitations. The presentation will demonstrate practical workflows for loading, transforming, and extracting data using GPT-enhanced processes, with a focus on optimizing import/export operations across different formats. We’ll discuss techniques for creating and curating knowledge corpora and developing custom GPTs tailored to specific document types and industry needs. Real-world examples from pharmaceutical and clinical research will illustrate how these techniques can significantly accelerate document processing, improve data accessibility, and unlock insights, showcasing the transformative potential of GPT-enhanced documentation in rapidly absorbing and synthesizing information.