Digital document analysis thanks to AI-based software

2022-08-22
Use Case
René Weseler

We need everything in black and white: the invoice on paper, a signature on the other sheet and then all receipts in digital form, for example to be able to exchange an item. The flood of paper is enormous. How does digital document analysis actually work?

The document cycle

Documents usually end up where it all began - in the company. Due to a multitude of channels and possibilities, online and digital as well as offline on paper, companies receive various requests and documents in different formats. The aim is to assign them specifically to the right area or channel. However, this task is made even more difficult by the fact that many documents have to be manually recorded and checked by various people in order to be processed further in systems and processes. In our increasingly fast-paced world, customers also expect fast processing.

Support from artificial intelligence - without replacing existing systems

This can be remedied by an input management tool that can be connected to existing systems - without replacing existing systems. Customer concerns and documents are simply captured intelligently and fully automatically from various sources thanks to A.I. algorithms. The type of document is determined, the so-called classification. It can be an invoice, a contract or a delivery bill; or something very specific such as the lottery ticket of the internal betting community.

The possibilities in input management with K.I. are unlimited. Content and structures are recognized and automatically assigned without much manual effort, so that all requests can then be assigned to the right channels, processes, systems or people in the company. For example, you can create your own models with the properties that are required for the respective business. Standard and classic document types such as invoices or contracts can be supplemented with customer-specific properties and thus adapted to the company's own documents.

Machine learning: at the heart of the document processing of the future

Machine learning mechanisms are used to automatically identify the correct type of document. The more documents are processed, the better the quality of the processing result. The document can then be validated and manually reworked if necessary. With the support of this technology, employees are able to process incoming documents more simply and much more efficiently than before.