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Predixion Software Announces Six New Customers

Predixion Software announced today six new customers, including healthcare leaders Aetna and Centene Corporation who are using Predixion’s enterprise-class collaborative predictive analytics solution to help identify patients at high risk of readmission before they leave the hospital. Data driven, targeted interventions using Predixion Insight™ are resulting in improved patient outcomes and reduced healthcare costs at many of today’s premiere healthcare organizations.

“Predixion offers an affordable and powerful way for healthcare organizations to quickly and efficiently identify at-risk patients so that they can improve patient outcomes and reduce costs,” said John Squire, Microsoft Senior Director, Partners and Cloud Strategy, US Health and Life Sciences. “The importance of business intelligence and predictive analytics is growing rapidly in healthcare due to the shift in reimbursement models from fee-for-service to pay-for-performance. At Microsoft, we’re incredibly excited about the continued customer adoption of Predixion and Microsoft Business Intelligence in healthcare.”

New customers also include a Branch of the United States Armed Forces and American Career College/West Coast University. These customers chose Predixion’s predictive intelligence platform to address a wide range of business challenges ranging from predicting student success to advanced scenario planning. Ease of use, speed to insights and return on investment were key drivers in the selection processes.

“Predixion provides cost-effective SaaS and on-premises solutions for delivering a self-service predictive analytics experience that is tightly integrated with the Microsoft BI stack and delivers analytic insights to the business. What’s unique is their 'last mile of analytics' concept that puts actionable predictions into the hands of non-technical information workers,” said William McKnight, president of McKnight Consulting Group.

“We are delighted to welcome these new customers. We are focused on delivering advanced, easy-to-use predictive analytics solutions for mainstream users and our efforts are starting to pay huge dividends,” said Predixion co-founder and CEO Simon Arkell. “With our recent and ongoing sales successes in healthcare and other verticals, we are confident that predictive analytics is crossing over into mainstream business applications and uses.”

About Predixion Enterprise Insight™

Predixion has created a world class predictive platform for big data. Predixion Insight is natively integrated with the Microsoft BI stack, leverages Apache Mahout Algorithm libraries and is fully integrated with Microsoft SQL Server®, Greenplum and Hadoop Hive, with other analytic platforms on the way. An advanced deployment framework was designed to simplify the process of sharing models across an enterprise, automate predictions directly from source data to line of business applications and Predixion’s own thin client app for PCs and tablets, and squeeze complexity out of the end user experience, resulting in self-service predictive analytics.

About Predixion Software

Predixion Software is a disruptive predictive analytics software company with a unique focus on the last mile of analytics – the deployment of powerful predictions to the people who need to act upon them. Predixion offers an easy-to-deploy self-service predictive analytics solution that allows customers to unlock deep insights within their data with technology that integrates with leading business intelligence platforms, business applications and clinical systems. Predixion has over 80 companies using the Predixion Enterprise Insight in 26 countries. For more information visit us at www.predixionsoftware.com.

Predixion Software recognizes all of the trademarks referenced in this press release.

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Copyright © 2009 Business Wire. All rights reserved. Republication or redistribution of Business Wire content is expressly prohibited without the prior written consent of Business Wire. Business Wire shall not be liable for any errors or delays in the content, or for any actions taken in reliance thereon.

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