Identifying and Organizing Information – Making Predictions

Cayce Alpha and her add-on end-user products can cluster and segment originally unorganized text based information. They can identify diversions and irregularities or similarities and correlations in mass data. Cayce Alpha predicts future events based on historical information and even delivers proposals to minimize or avoid negative consequences of those events.

CA services

Comparing to statistical and other machine learning methods, the solution developed by Nordic Analysis allows easily to synthesize regression models of any level of complexity. Combining variety of numerical and textual data sources, Cayce Alpha performs validation of the data diversity leveraging its built-in Sensitivity Analysis service.
Transfer learning-based functionality is another key feature of Cayce Alpha. It simultaneously adapts and optimizes model architecture whilst learning underlying data sets.

With the help of Cayce Alpha and the services provided by Nordic Analysis, organizations will be easily able to see and understand the key information in complex patterns, trends and issues which are highly relevant for the course of their business/operations, but which are usually obscured for human beings due to complexity, information overload or lack of correlation understanding.

Contextual Analysis – New possibilities to search for Information

Like humans, Cayce Alpha can detect denotation and connotation in text based human language. This makes her the ideal tool for contextual analysis and innovative search engines. While regular search engines are looking for identical key words, Cayce Alpha and her associated end-user products are looking for information, which is semantically similar to the provided content. They focus on the relationship between signifiers—like words, phrases, signs, and symbols—and what they stand for, their denotation. This means that Cayce Alpha can for example find names, locations, data, event types, effects, etc. which are close to the original input information.