Your organization, just like many other, probably possesses increasingly big amounts of data. But are you processing it correctly and putting it to good use?
If your organization processes many documents daily, manually classifying them is a time-consuming process, which also creates room for inconsistencies and errors. Are you related with this case? Well, the best solution would no doubt be Automated document classification.
In this 3-part article, we will explore the ins and outs of document classification. We hope this article help explain what document classification is all about. Check It out and stay tuned for part 2…
Documents have been processed for a long time… manually! Thanks to the advancements in technology this task has become faster and automated. Nowadays, AI can automatically process various types of documents, in a much timelier manner and with less error than humans are able to.
We’ve wrote before about the advantages of using AI to automate data extraction. In this article, we’ll explore deeply into it.
Document data extraction is the process of extracting meaningful data from semi-structured and/or unstructured documents for later use or storage. When referring to the use of AI or Machine Learning to perform that task, it’s called Automated Document Data Extraction.
In today’s digital world, the ability to collect, analyse and process data is one of the most principal factors for any organization, due to the vital role that data plays in day-to-day company decisions. With that, the amount of data generated keeps increasing, and with it the challenges of processing such amounts of data.
The definition of data extraction is “the task of automatically extracting data from unstructured or semi-structured documents”. With the advancements in technology, this task gets more important with each passing day. But, if the data is unstructured, how can it be processed automatically?