BayesiaLab is a powerful desktop application (Windows/Mac/Unix) for knowledge discovery, data mining, analytics, predictive modeling and simulation - all based on the paradigm of Bayesian networks. Bayesian networks have become a very powerful tool for deep understanding of very complex, high-dimensional problem domains, ranging from bioinformatics to marketing science.

BayesiaLab Professional Edition 

The BayesiaLab Professional Edition is the most comprehensive version of BayesiaLab. In addition to the features found in the Standard Edition, the Professional Edition includes a wide range of machine learning tools for knowledge discovery. As such it is geared towards research and analytics applications.

BayesiaLab Standard Edition 

The BayesiaLab Standard Edition was developed primarily for expert knowledge modeling, i.e. building Bayesian networks manually. As such, the Standard Edition only has a small subset of the machine learning and analytical capabilities of the Professional Edition.

BayesiaLab Analyst Edition 

The BayesiaLab Analyst Edition is a “player” version of the BayesiaLab Professional Edition. It provides read-only access to previously generated XBL files while providing the large range of analysis, inference and simulation tools. This edition does not have any access to datasets. This is ideally suited for researchers who wish to share their models with a broader audience, while preventing any modifications to the original model.

A free 30-day evaluation version of the latest release of BayesiaLab 5.1 Professional Edition is available for immediate download from the Bayesia S.A.S. server:

Click here to register and download BayesiaLab (Windows, OS X, Linux/Unix, 32/64-bit)

This will allow you to experiment with new the features of BayesiaLab 5.1, plus you can try out all the Bayesian network examples explained in our or series of white papers.

Overview

We offer a number of licensing options for BayesiaLab in order to suit your specific business requirements, including License Purchase (perpetual) and License Rental. Additionally, our new Elastic Pricing program offers a high degree of flexibility with several pay-as-you-go plans. For academic customers, we offer select configurations at very favorable rates.

The following matrix provides a general overview of the available editions and their licensing options.

To compare the features of the Analyst, Standard and Professional Editions of BayesiaLab, please see the Feature Comparison Matrix.

Download Complete Price List (April 2013)

All prices are expressed in U.S. Dollars and exclude any applicable taxes. Prices, features and configurations are subject to change without notice.

The Bayesia portfolio of research software is the result of over 20 years of continuous research and development by two French professors in the field of artificial intelligence, Dr. Lionel Jouffe and Dr. Paul Munteanu. Their team of computer scientists and software developers at Bayesia S.A.S. has embraced the Bayesian networks paradigm and built tools for making it accessible to a broad audience, and practical for a wide range of research tasks.

As of today, Bayesia's software program includes:

• BayesiaLab 5.1
• Bayesia Choice Simulator 1.6
• BEKEE 1.6 (Bayesia Expert Knowledge Elicitation Environment)
• Bayesia Engine API

Download the product overview (PDF, 5.5MB)

The idea of Bayesian networks dates back to the mid-1980s, when Professor Judea Pearl of UCLA began to formalize their semantics in a series of seminal works. The study of Bayesian networks has since grown into a large body of work with dozens of books and countless scientific papers exploring all their properties.

However, thanks to Bayesia’s software tools, and the ever-increasing power of computers, Bayesian networks have become powerful and practical tool well beyond the world of academia. For applied research in all domains, Bayesian networks can facilitate deep understanding of very complex, high-dimensional problem domains. Their computational efficiency and inherently visual structure make Bayesian networks attractive for exploring and explaining complex domain. Most importantly, Bayesian networks allow reasoning about such domains in a formally correct yet highly intuitive way.

BayesiaLab and Bayesia Market Simulator are unique in their ability to use Bayesian networks for choice modeling and market share simulation. Together they provide a comprehensive toolset for simulating market shares of future products based on their key characteristics, without requiring new and costly experiments. As a result, BayesiaLab and Bayesia Market Simulator allow using a vast range of existing research for market share predictions.

Everybody is talking about "Big Data" and all the manifold opportunities that are associated with it. Very often though, we hear almost as much about the challenges that come with this flood of data. Where to store it, how to analyze it, how to explain it, the list goes on and on. We think this is a very nice problem to have. Much more serious problems exist on the opposite end of the spectrum, where there is not enough data. Unfortunately, all the advanced knowledge discovery algorithms fail in the absence of data. 

The BayesiaLab code has been under continuous development since 1997 and since its first commercial release in 2002, the number of users around the world has grown steadily. It now includes hundreds of researchers and practitioners from very diverse domains, e.g. academia, pharmaceutical research, defense, consumer goods, telecom and many others. It has emerged as the software of choice for those who recognize the power of Bayesian networks in their research.

As of 2007, Procter & Gamble has become Bayesia's worldwide strategic partner, which illustrates BayesiaLab's capabilities as an industrial-strength research tool.

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