NLP combines behavioral science, linguistics, and data science to analyze patterns in and make sense of large amounts of natural language data. Natural language understanding (NLU), a subtopic of NLP, uses ML techniques to comprehend text data and understand its content. Combined, NLP and NLU algorithms can be trained to enable processes like automatically routing emails or requests to different departments, as well as reading and classifying news articles.
Guidehouse leverages the best of breed across the full ML technology landscape, using a diverse tool stack and offering technology-agnostic solutions to help you identify and execute NLP and NLU use cases that enable your organization’s objectives. Our AI and robotic process automation (RPA) expertise allows us to develop specialized intelligent automation solutions to reduce bottlenecks associated with the ingestion of large text data and optimize text analysis workflows. We leverage RPA to interact with source systems to gather information into ML and text-processing workflows that enable our analysts to quickly derive insights from vast amounts of unstructured data with NLP and NLU. This leads to increased efficiency in processing text data, driving a greater capacity for rigorous information extraction. By integrating RPA, solutions are built to be easily understandable and repeatable, giving you the power to iterate and scale for future analyses.
Example use cases:
- Intel Client: Used ML to predict case complexity scores for incoming clearance investigations to help investigators prioritize cases more efficiently.
- NLP and Social Media: Gathered and mined social media and open-source data and leveraged NLP to predict public sentiment around healthcare initiatives.