Our Technology

The strength of Cognovi Labs’ proprietary technology is inextricably linked to the world-class research team at the Ohio Center of Excellence in Knowledge-Enabled Computing (Kno.e.sis) at Wright State University.

The Kno.e.sis team – Computing for Human Experience
The Kno.e.sis team focuses on translating information into meaning. It is led by Dr. Amit Sheth, Co-Founder and Technical Advisor to Cognovi Labs. The university-based center consists of 13 labs and approximately 100 multi-disciplinary researchers, including 15 faculty members and more than 50 Ph.D. students, representing the fields of computer science, biomedical sciences, health informatics and cognitive science.

Emotions-Based Decision Making
Understanding how emotions drive decision-making at the topic-specific level is the founding principle of Cognovi Labs. Since emotions are integral in all aspects of our lives, they influence decision-making, shape daily behavior and affect business events. By understanding how emotion is expressed on social media, Cognovi Labs can predict subsequent behavior as it relates to purchasing, preferences, voting and other actions.

Proprietary Technology Platform
Cognovi AI has been successfully applied in diverse settings, including sales forecasting, company fundamentals, product performance, economic trends, marketing and political events. Our continual, heuristic research ensures that Cognovi’s clients benefit from the timely and relevant learning of our Kno.e.sis team.

Our technology platform is built on two levels. The first level is part of an analytics algorithm called the “Emotion Recognition Machine” (ERM) that processes text and identifies targeted, expressed emotions in real time. The ERM learning algorithm is “trained” on a substantial training set of 2.5 million, which gives it the accuracy and broad applicability it has today.

At the second level, ERM’s output is used to extract meaning from processed conversations. Cognovi Labs leverages these topic-specific emotional components to structure predictive insights for its clients.