Natural Language Processing deals with how to recognize patterns in natural, unstructured text. Think of structured text as data in a database or excel table, for instance a register of names. By unstructured information we mean text in emails, documents, manuals etc. The term natural highlights that the text data has been generated by a human for another human.
Handwritten documents can be read out and prefilled using machine learning algorithms. By further input, these documents can be edited again, which again benefits the accuracy of the algorithm.
Electronic patient records can be evaluated using machine learning algorithms. This automatically provides doctors with suggestions for diagnoses and therapy options.
Companies working with thousands of customers and suppliers need to categorize their documents so that requests can be handled in time.
Standard documents can be classified and automatically completed using voice input and machine learning algorithms. This document can be checked and edited afterwards.
Construction plans are complex and include a high amount of relevant data. This information, however, is not standardized and available in a structured format. Therefore, data cannot be analyzed accurately and construction projects cannot be compared on a profound basis.
Companies receive dozens of invoices every day. Handling invoices and ensuring payment deadlines are met is a central task at every accounting division.
Rental contracts are often very complex and have dozen of pages. However, for some tasks, like in a Due Diligence process, only some information is important.
Machine learning algorithms allow standard clauses and deviations from the standard to be defined and identified on the basis of historical contracts. This makes it possible to highlight deviations and identify and categorize contracts according to predefined criteria.
Customer service agents enter information on complaints or complaints in forms. Information from these clusters can flow into the optimization of business processes.