The text discusses the automation of procurement processes through the digitization of documents like Purchase Orders, Invoices, and Delivery Notes, highlighting the benefits of reduced costs and errors. It delves into the 3-way matching process—a critical step in ensuring consistency across these documents from both the buyer's and seller's perspectives—and the challenges associated with manual matching, including human errors and delays. Various technologies for document digitization are examined, from traditional template-based methods to advanced AI techniques like OCR, NLP, and Deep Learning, with a focus on their limitations. The text introduces Nanonets' Intelligent Automation Platform as a solution, emphasizing its use of Graph Convolutional Neural Networks and other advanced technologies to efficiently extract and process data, overcoming common issues such as quality, language barriers, and data drift. The discussion is complemented by examples of frequent errors in document matching, like vendor, product, and quantity mismatches, and concludes with a push for further exploration of automation solutions.