This data sheet offers a general overview of what we do, how we do it, and who we do it for, including our NLP features, products, deployment options, industries and applications, and more.
Learn how we solve precision and accuracy issues in text analytics by tuning the system or training a machine learning "micromodel" to solve particularly tricky challenges.
Semantria Storage & Visualization adds web-based data storage, document management, and data visualization tools to your Lexalytics Intelligence Platform solution.
This solution profile explains how RPA vendors can solve more and broader enterprise use cases by integrating a complete, customizable text analytics solution into their platform, and why Lexalytics is the perfect technical partner to add that next level of analytical differentiation.
Learn how Lexalytics combines our semi-structured data parser with NLP to unlock the full value of contracts, medical billing code updates, and other financial, medical and legal documents.
Salience is a set of on-premise software libraries that adds powerful, customizable text analytics and natural language processing (NLP) to your own enterprise analytics stack or data analytics product.
Semantria wraps the text analytics and natural language processing features of our Salience engine into a flexible, easy-to-deploy RESTful API with graphical configuration tools.
Learn how Lexalytics, a company with more than a decade of experience in the space, uses machine learning to solve tricky problems in natural language processing and text analytics.
We’ve developed a particular philosophy around how to customize a text analytics system to better fit your business. This white paper explains why you should "Tune First, Then Train".
This white paper explains how we break down sentences into n-grams and noun phrases and evaluate the themes and facets within to help you perform contextual analysis.
Large-scale "AI for regulatory compliance" systems often fall short. Here's how Lexalytics creates time savings and cost reductions by building targeted, semi-custom applications.
With so much hype and so many options out there, how can you be sure you're choosing the right AI partner? Start by using these 4 questions to guide your search.
Text is one of the most important modes of human communication. Seth Redmore explains how starting from the question, rather from data, helps you truly listen to your customers, partners, competitors, and employees.
Sentiment analysis is the process of determining whether a piece of writing is positive, negative or neutral. This paper dives deep into how it works, including the role of machine learning and AI.
Categorization of text documents means sorting them into groups. This paper explains how Lexalytics combines natural language processing (NLP) and machine learning to automatically classify customer reviews, support tickets, or any other type of text document based on their contents.
Who are they talking about? Learn how we extract people, places, dates, companies, products, jobs, and titles from text documents.
This white paper is a useful primer on the fundamentals and mechanisms of Natural Language Processing (NLP).
Discover how the top 6 text analytics vendors differ from one another and learn about which platform suits which use case. This comprehensive text analytics guide serves as the who’s who and the what’s what in natural language processing.
Robotic Process Automation (RPA) is moving towards larger, transformational initiatives. As part of that shift, RPA vendors must improve their natural language processing (NLP) capabilities to support trending text analytics use cases. In this article, we explore your options as an RPA vendor looking to add new text analytics and NLP capabilities to your platform.
Paul Barba explains the role of machine learning and AI in natural language processing, how to apply machine learning to solve problems in natural language processing and text analytics, and why a hybrid ML-NLP approach is best.
Robotic Process Automation (RPA) reduces costs and increases profitability by freeing workers to focus on higher-value work. This article explains how text analytics and natural language processing fit into that picture, and why RPA providers looking to add text analytics and NLP into their platform are better-off buying and integrating a solution from an established vendor.
Artificial intelligence has rendered HIPAA obsolete. As AI in healthcare becomes commonplace, data privacy, security and ethical issues are growing. We explored the uses of AI in healthcare, the ethical issues involved, and why experts are raising flags about healthcare data storage and data security practices.