Nowadays, volatile, uncertain, complex and ambiguous (VUCA-) markets are changing rapidly influenced by globalization, technological advance and many other factors. As a result, companies appear and disappear at a pace that is breath-taking.
Document processing time can be more or less important depending on the service delivered and the complexity of the document. In contrast, high precision is important at all times, no matter the complexity or size of the processed document.
In our 5th blog, we compared whether a complete solution or a self-service offering makes more sense, and which individual building blocks need to be linked in a self-service offering. In the next part, we looked at how the billing should be done. Per document or per page. In the following list you will find all the terms that are important for the successful introduction of an IDP system in the company:
If the offer includes an end-to-end solution, the company achieves automation in the entire document processing process for the customer. This means that the service provider offers the customer a simple way to upload documents via different channels (e.g. email, scan-per-mail, upload, API, etc.). The customer gets the data back as requested without intervening in the process (end-to-end). With such an offering, we are talking about intelligent document processing. In this process, the AI-based OCR is only one part of the value chain.
The AI's Learning capability is an important aspect of achieving automation. The faster the AI learns through feedback from a human, the faster it is possible to send the data to the next systems in an automated fashion or with little manual validation. In the best-case scenario, additional machine validations are executed during an IDP system's post-processing step, increasing the level of automation.
OCR technology and intelligent document processing (IDP) systems has been initiated by explaining a few basics of what OCR actually is and how Digicust applies this technology to digitalize the customs industry.
Optical Character Recognition (OCR) technology is a solution for automatically extracting printed or written text from a scanned document, PDF- or Image file and then converting the text into a machine-readable form that can be used for further data processing
The AI's Learning capability is an important aspect of achieving automation. The faster the AI learns through feedback from a human, the faster it is possible to send the data to the next systems in an automated fashion or with little manual validation.