Current text processing solutions are capable of analyzing tabular structured data formats with numerous rows and columns that are easier to process and store. This includes names, phone numbers, and addresses.

Text artificial intelligence (AI), also referred to as text mining, is a technology that uses natural language processing (NLP) to convert unstructured data from various sources into structured data that can be used for further analytics using machine learning algorithms to derive patterns and trends. NLP is the application of pattern recognition to understand human language. It can be applied to either text or voice channels. Typically, NLP front-ends other AI applications such as chatbots. Natural language understanding is a narrow subtopic of NLP that deals with machine reading comprehension. It refers to the process of teaching machines to comprehend and interpret what the text really means. NLP focuses on what is to be said, and NLU focuses on what is meant to be said. Technology vendors are developing AI neural networks that can process this content in real time and with great accuracy.

Text AI can measure sentiment and emotion, undertake competitor analysis, and even parse complex information such as personality traits and communication style from text to help companies better understand their customers.

This study provides a brief overview of top competitors’ advances in the text AI industry and notes several innovative companies to watch. It also explores growth opportunities in the financial services, knowledge management, security, defense, healthcare, and pharmaceutical industries.

Author: Ignacio Perrone