Incorporating AI and machine learning, we implemented a system that can digitally learn and dynamically route documents to different locations by their type.
Furniture of America’s daily sales activity results in over 2,000 printedinvoice pages per day. The administrative effort to gather, match, andfile invoice documentation takes hours and can spill over to the next business day. Additionally, it can take up to half-an-hour to locate and pull a requested document as well as another half-an-hour to refile the pulled document.
Imagine a system that can learn, OCR, route, and make accessible your documents on-premise, in the cloud, or both in minutes.
Young Systems proposed a solution using AI automation to solve the paper record keeping conundrum.
Young Systems suggested a solution using Microsoft’s Azure Form Recognizer, which uses AI automation to transform scanned documents into usable digital data. This propelled their business productivity to the next level by reducing workload and redundancy.
Artificial intelligence can execute a 3-Way-Match between multiple scanned documents, like physical purchase orders, invoices and packing slips. We used a machine-learning algorithm customized to FOA’s needs; the algorithm learns the document’s environment, and the systems adapt to recognize where unique identifiers are printed on the documents. This 3-Way-Match is completed after the documents are combined and filed away automatically on the cloud in seconds, where the files are easily searchable and can be retrieved at anytime, from anywhere.