Document Understanding is a pretty wide area and there is a lot to cover. In this post, I want to focus on the basics. In the coming blog posts, I will talk about the framework, which helps while building the solutions and also ML models and how to train them, with some examples and videos. So stay tuned !
There is no company having no documents to process. Processing documents is a challenge, especially if the work is done manually. It is prone to human error, takes time, costs money and most importantly is a repetitive task, which is perfect for automation.
An automated Document Understanding technology powered by AI can wipe out those challenges and lead to cost and time efficiency by removing the risk of making any mistakes. The trapped data in those documents, then, can be extracted and successfully processed.
Based on the type of the documents, one can choose to use AI or not since the choice brings together some other challenges to be considered, which I will list out below.
But first, let's go through the different types of documents:
- Structured Documents are the easiest ones to tackle with since their format is fixed, like passports, driving licenses and time sheets.
- Semi-structured Documents contain fixed and variable parts like tables. To give some examples; invoices, receipts and purchase orders fall into this category.
- Unstructured Documents are the most challenging ones since analysing and extracting data from them is a complex process. Emails, contracts and agreements are all unstructured documents.