Infor Announces Coleman A.I. for Healthcare

United States – March 26, 2018, 09:00 AM

Infor, a leading provider of industry-specific cloud applications, today announced new artificial intelligence capabilities for the healthcare industry. Built upon Infor Coleman™ , an enterprise-grade AI platform, the first set of AI applications for healthcare will enable healthcare organizations to increase efficiency and quality outcomes while maximizing human work potential. The Coleman applications for healthcare further expand the robust capabilities of Infor CloudSuite Healthcare, and include Coleman for Benchmarking, Coleman for HCM Self-Service, and Coleman for Embedded Learning.

"The impact artificial intelligence will have on the healthcare industry is immeasurable," said Mark Weber, senior vice president, Infor Healthcare. "The vast data sets from Infor CloudSuite Healthcare and Infor CloudSuite HCM, coupled with deep machine learning capabilities enable Coleman to provide powerful artificial intelligence augmenting human workers to increase the quality of healthcare outcomes at an organization while improving bottom line results for healthcare providers."

Infor Cloudsuite Healthcare, is a complete software platform designed for healthcare-that includes a comprehensive suite of business solutions purpose-built for healthcare, including finance, planning, supply chain, human capital, asset management, relationship management, and clinical interoperability. In the coming months, new Coleman functionality that will further augment the Infor's healthcare-specific applications include:

  • Coleman for Benchmarking - This application will leverage clinical, operational, and population data to reveal insights derived by identifying the relevant drivers of deviations from optimal practice. This will help to support the goals of value-based care by determining opportunities to improve both the cost and quality of care.
  • Coleman for Embedded Learning - Infor will combine the power of Coleman and Infor Learning Management to deliver an impactful embedded learning capability which directly sources the embedded learning content library and intuitively recommends relevant information on demand within any connected Infor application. Ultimately, the platform will provide the most impactful embedded learning content for its users before they ask for it. This will reduce training costs and time away from work, along with improving learning retention through immediate re-enforcement by doing.
  • Coleman for HCM Self Service - This new application will provide conversational user experiences through text, voice, or image recognition to provide information and execute routine tasks from virtually anywhere. Powered by Amazon Lex, organizations can lower the administrative burden of care-givers allowing, them more time to spend with patients, and ultimately reduce overhead costs.

For more information please visit https://www.infor.com/industries/health/ or https://www.infor.com/product-summary/technology/coleman/.

This announcement reflects the direction Infor may take with regard to the specific product(s) described herein, all of which is subject to change by Infor in its sole discretion, with or without notice to you. This announcement is not a commitment to you in any way and you should not rely on this document or any of its content in making any decision. Infor is not committing to develop or deliver any specified enhancement, upgrade, product or functionality, even if such is described in this announcement and even if such description is accompanied by words such as "anticipate," "believe," "expect," "intend," "may," "plan," "project," "predict," "should," "will," and/or similar expressions. Many factors can affect Infor's product development plans and the nature, content and timing of future product releases, all of which remain in the sole discretion of Infor. This announcement, in whole or in part, may not be incorporated into any contractual agreement with Infor or its subsidiaries or affiliates. Infor expressly disclaims any liability with respect to this announcement.

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