Insights: Software that extracts knowledge from data. Model. Predict. Simulate. Discover. Associate. Gain new Knowledge and Insights from noisy data. Easily and Reliably. Ultra-fast, parallel, self-organizing, high-dimensional modeling of real-world processes and complex systems. INSIGHTS
Press Release
June 7, 2013
Insights for OS X: Data Mining App, "KnowledgeMiner," Renamed "Insights"

Berlin, Germany - KnowledgeMiner Software today is pleased to announce that its critically acclaimed application, KnowledgeMiner free for OS X, has been renamed Insights. Insights 1.6 takes its new name from the app's ability to bring conventional data mining to a new level of sophistication and applicability. 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. Insights is currently used by NASA, Boeing, MIT, Columbia University, Merck, Mobil, Notre Dame, Pfizer, Apple, and many other corporations, universities, research institutes, and individuals worldwide.

"The new product name highlights the app's core value and functionality very well," commented Frank Lemke, founder and president of KnowledgeMiner Software. "It now better describes and reflects our vision of the power of a new generation of self-organizing and self-learning predictive modeling systems. This latest generation of systems will allow significant strides toward new knowledge about a variety of complex processes, enabling powerful, automatically generated forecasts and solutions from streaming data."

Feature Highlights:

  • Brings high-performance, predictive modeling to users with unprecedented ease of model building and deployment, and it takes full advantage of the computing power of your Mac;
  • Hides all complex processes of knowledge extraction, model development, dimension reduction, variables selection, noise filtering, and model validation from the user;
  • Self-organizes forecasting and classification models and model ensembles, and it generates the equation that describes the data;
  • Checks if, and the extent to which, the developed model reflects a valid relationship or if it just models noise, which makes a model useless for predictive purposes;
  • Live Prediction Validation technology - for the first time, gives direct information about model stability for the given input values;

Complex systems demand that we abandon the classical, hard approach of creating analytical models using theoretical systems analysis, since we often have incomplete knowledge of the processes involved, which forces us to make vague guesses about the internal workings at various stages of the analysis. Environmental, social, and socio-economic systems are but three examples. This approach is time consuming, inflexible, and leads to results that are questionable, ambiguous, and qualitative in nature. These challenges, as well as the nascent Internet of Things, require a paradigm shift in model building toward inductive modeling and forecasting technologies based on self-organization.

Insights is a professional, yet convenient tool for building predictive models from data autonomously. 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. All models can be exported to Excel for further deployment.

Whether applied to sales prediction, financial and resource planning, engineering problems, climate change, health/life science related questions, or mining collections of data from government agencies, Insights opens up a wealth of new possibilities. Now, individuals, small business owners, and scientists can create models that were previously available only to large entities that could afford expensive data mining applications.

"I invite everyone interested in Insights to download our free Demo version," stated Frank Lemke. "Discover the true computing power of your Mac with Insight's implementation of 64-bit parallel computing, with support for vector processing, and multi-core and multi-processor machines."

Language Support:

  • English, Spanish, and German

System Requirements:

  • OS X 10.8.3 or later
  • Any Mac with 64-bit CPU
  • Minimum screen resolution of 1280 x 768 pixel
  • For Excel support, Excel versions 2011 or 2008

Pricing and Availability:

Insights 1.6 is free and available worldwide through the Mac App Store in the Business category.

Located in Berlin, Germany, KnowledgeMiner Software was founded in 1993 by Frank Lemke. The company is active in research, development, consulting, and application of unique, self-organizing modeling and knowledge discovery technologies. KnowledgeMiner Software has been doing consulting in model development and prediction of toxicological and eco-toxicological hazards and risks of chemical compounds from experimental data for regulatory purposes within REACH, and it has participated in three international research projects funded by the European Commission related to QSAR modeling and model evaluation. Other fields of activity have been climate change related modeling and prediction problems, sales and demand predictions, macro- and micro-economic modeling problems like national economy and balance sheet prediction, energy consumption analysis and prediction, medical diagnosis of diseases, and wastewater reuse problems. Copyright (C) 1993-2013 KnowledgeMiner Software. All Rights Reserved. KnowledgeMiner is a registered trademark of KnowledgeMiner Software in the U.S. Apple, the Apple logo, iPhone, and iPod are registered trademarks of Apple Inc. in the U.S. and/or other countries.

More Information:


Deep Learning and noise immunity of GMDH adaptive self-learning and self-organizing data mining, forecasting and classification of streams of data