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.
"Build or Buy" for NLP and text analytics means choosing between building from open source, licensing a basic cloud API, or customizing an NLP platform. This paper explains that choice in depth, including what to expect if you choose to build, and how to choose the best text analytics and NLP provider.
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.
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.
This white paper is a useful primer on the fundamentals and mechanisms of Natural Language Processing (NLP).
Today I’m excited to share the news that Lexalytics has been acquired by InMoment, the leader in Experience Improvement (XI). If you haven’t already seen the press release it can be viewed here. For nearly […]
While much of the tech world has come through Covid-19 relatively unscathed, some tech-focused industries have definitely felt the effects of the pandemic. As an AI and NLP software vendor with clients in myriad industries […]
Popular media and hype cycles are leading us to expect radical changes and perfect results from artificial intelligence. But you don’t read perfectly, so why should your AI? In this blog, Tim Mohler explains when “good” is good enough for AI.
Bias in AI causes machine learning-based systems to discriminate against particular groups. We investigated why AI bias occurs, and how to fight back.
One of the most important and most-used functions in text analytics and NLP is sentiment analysis — the process of determining whether a word, phrase, or document is positive, negative, or neutral. The first step […]
It pretty much started here: McCulloch and Pitts wrote a paper  describing an idealized neuron as a threshold logic device and showed that an arrangement of such devices could express any propositional logic formula. […]