NLU in Document AI: Transforming the way we process information

Welcome to our latest episode of the podcast where we’ll be delving into the world of NLU in Document AI.

We’ll start by discussing Optical Character Recognition (OCR) and how it differs from Natural Language Understanding (NLU). OCR allows for the transformation of non-digital formats into digital ones, but it does not provide understanding of the content. NLU, on the other hand, goes beyond OCR by providing a readable version for the computer, allowing it to understand any kind of document.

Traditionally, understanding documents was a rule-based process that relied on the word order in a phrase. However, this system lacked semantic understanding and was not portable, requiring the building of new systems for each industry, resulting in longer and less accurate processes.

At 1000ml, we’ve worked with a variety of industries to adapt Contract AI, a field of Document AI, to their specific needs. For example, in the pharmaceutical industry, we built a pipeline for categorizing invoices and contracts according to the medicine they bought. In the legal industry, we worked on a system that allowed NLU to focus on patent documentation. In the financial and insurance industries, our work centered around form information extraction, resulting in faster and more accurate processes. And in healthcare, we combined different information about a patient in one place.

All paper-driven industries can benefit from Document AI, especially when NLU is involved. Join us next week as we continue to explore the exciting world of NLU in Document AI.

Let’s cut through the jargon, myths and nebulous world of data, machine learning and AI. Each week we’ll be unpacking topics related to the world of data and AI with the awarding winning founders of 1000ML. Whether you’re in the data world already or looking to learn more about it, this podcast is for you.