Insights

Insights is original parallel software for building predictive models from data, automatically, by evolutionary, self-organizing modelling approaches. Taking observational data that describes a problem, system, or process, the software constructs a working mathematical model. Compatible with data stored in a variety of popular formats (e.g., Microsoft Excel), its AI-powered, self-organizing, modeling algorithms allow users to easily extract new and useful knowledge to support decision-making.

Insights introduces Systems of Equations, a superset of Vector Auto-regressive Models, to allow model development from observation data of linear and non-linear interdependent systems and processes for easy multi-step ex ante forecasting. Accompanying examples such as forecasting the U.S., Japanese, or German national economies until 2021, compared to forecasts provided by the International Monetary Fund, demonstrate the power and productivity of this outstanding modeling technology.

Whether applied to sales prediction, energy forecasting, engineering problems, climate change, health or life sciences related questions, or mining collections of data from government agencies, INSIGHTS opens up a wealth of new possibilities to individuals, small business owners, and scientists that were previously available only to large entities that could afford expensive data mining applications. Users in nearly any field can employ the easy-to-use software to analyze noisy data sets and build powerful models, which can be used to help to gain new insights into complex phenomena, predict future behavior, simulate "what-if" questions, and identify methods of controlling processes.

Selected Features:

• Original, high-dimensional, self-organizing, inductive knowledge mining from observation data based on Deep Learning
• Systems of Equations for model development of linear and non-linear interdependent systems and processes for easy multi-step ex ante forecasting
• Automatically develops analytical models and model ensembles from data along with explicit mathematical equations that describe the data as an interpretation of how the model works
• Integrates all complex tasks - such as relevant variables selection from up to 25,000 inputs, knowledge extraction, model development and validation - into one process that hides it from the user
• Cost-optimized, prevalence-sensitive classification and sequential Similar Patterns technologies
• Model deployment and export to Microsoft Excel, ready-to-use Python, Objective-C, AppleScript source code, or TEXT to be used in Matlab