Intelligent Document Processing (IDP) automates extraction and categorization of information from unstructured and semi-structured documents. While standard optical character recognition (OCR) computerizes the parsing of printed and scanned documents, so-called parsing tools like PyPDF2 and React-PDF take on the extraction of text from digital files. Emerging developments in IDP apply large language models (LLMs) to enhance natural language processing (NLP) to ensure the efficient interpretation, classification, and analysis of the extracted data. This paper provides a survey of IDP technologies with possible applications in financial and retail sectors-invoice processing, purchase order matching, and fraud detection. It also focuses on accuracy, scalability, and outlook of LLM-based IDP on the cloud, toward next-generation automation in more detail.