Intelligent Document Processing (IDP) is a software collection that organizes and processes enterprise documents to extract information and provide actionable insights, significantly speeding up document-centric workflows, freeing staff for more strategic work, and reducing data entry errors. Large language models (LLMs) take IDP to the next level by understanding and generating natural language, enabling accurate extraction of information from hundreds of pages and distilling essence into concise memos. LLMs can handle complex documents, produce comparable human-written text, and quickly sift through large collections of documents to identify relevant data, filling in predefined templates, summarizing key points, and generating reports or portfolios based on extracted information. Industries such as finance, insurance, healthcare, and legal institutions benefit from LLM-powered IDP by using queries to navigate through documents, identifying the most appropriate answers in the data, and generating reports, summaries, or portfolios. Real-world examples of LLM-based IDP include auditing financial compliance, private equity due diligence, and real estate underwriting, showcasing its potential to extract information from large and complex documents, generate reports, and assist human analysts.