We unleash the power of unstructured text
Language and communication are one of the ground pillars of society, and text has been the most efficient and reliable way to create, aggregate, and store information for the past few thousand years. It will continue to be so for the foreseeable future; as we are still only at the very beginning of the Big Data explosion.
We’re getting better and better at harnessing the power of structured data, but we strongly believe that data in the form of unstructured text is equally important to truly understand the world around us and make better decisions.
Our software understands meaning
The majority of this text data comes from sources such as surveys, reviews, emails, chat conversations, and social media. The language used in these texts is often productive, informal, and multilingual – and shows little respect for grammar rules and lexical conventions.
As you can understand, this is a difficult environment for traditional approaches to text analytics, because they are based on a processing pipeline that presumes stability and consistency.
AI-driven semantic memory
We anticipate a transformative shift towards meaning-based data management and analysis. That’s why we have built state-of-the-art solutions with unparalleled performance to solve some of the major problems in the IT industry when it comes to language technology.
Extreme scalability, learning, automation, and language agnosticism are some features of our technology, which is based on a neurologically plausible method that models meaning on-the-fly because it is built like a semantic memory.
Text analysis for everyone
Our vision is to establish our unsupervised language AI as the global standard for a semantic base layer which will be an integral and fundamental part of all emerging technologies and solutions dealing with large amounts of unstructured language data. We want to democratize the power of analyzing unstructured data and make it available to anyone with a need to truly understand the world around them.
The scientific foundation of our technology was created by Gavagai’s founders Dr. Jussi Karlgren and Dr. Magnus Sahlgren, who have done research in the field of wordspace technology for more than 20 years. Our research team has published more than 450 academic papers so far, and we continue to contribute to the field of Natural Language Processing (NLP) by participating in the Wallenberg AI, Autonomous Systems and Software Program (WASP) graduate school.
Here is a small selection of our publications. You can find them all at Gavagai Labs.