Cherwell Unveils Integration of Azure Machine Learning with Cherwell Service Management
Predictive Analytics Deliver Powerful Intelligence, Helping IT Teams Work Smarter and Deliver Better Services
October 5, 2016 - Colorado Springs, CO. - Cherwell Software, a global leader in IT service management (ITSM) solutions, announced today to customers at its annual conference that the Cherwell® Service Management platform is utilizing Microsoft® Azure® Machine Learning to integrate predictive analytics into its ITSM solution.
Azure Machine Learning, part of the Microsoft Cortana® Intelligence Suite, provides a cloud-based service that enables companies to apply statistical techniques to large amounts of data and leverage analytics to solve problems and create smarter applications. Cherwell customers can now harness the power of Azure Machine Learning to analyze incident and ticket data stored within Cherwell Service Management, and utilize pattern recognition to create algorithms that assist with incident prioritization, triage, and resolution.
“Azure Machine Learning and the Cortana Intelligence Suite offer an easy way to add powerful intelligence to existing applications. By integrating Azure Machine Learning with Cherwell Service Management, Cherwell has introduced the next generation of service management,” commented Dawson Stoops, VP of Technical Alliances at Cherwell.
Cherwell Service Management is built on a flexible, codeless platform, empowering Cherwell customers to rapidly embrace new innovations such as machine learning and artificial intelligence to enrich the service management experience of their business users.
“We have already been using Microsoft Cortana at Dartmouth-Hitchcock for purposes outside of service management,” said Bill Weyrick, Director of Information Systems for Dartmouth-Hitchcock Medical Center, at Cherwell’s global customer conference. “The integration of machine learning into Cherwell Service Management is remarkable in and of itself, but perhaps even more exciting are the countless scenarios in which advanced services can be quickly and easily integrated with Cherwell’s solutions. I am essentially ‘future-proofing’ my service management environment because I can rapidly take advantage of new services as they become available.”
“With Cherwell, the future of service management is here and now,” said Josh Caid, VP of Innovation at Cherwell. “Azure Machine Learning, when combined with Cherwell Service Management, extracts the intelligence hidden within vast amounts of data to help IT teams work smarter and deliver better services. But the bigger story here is that the Cherwell platform enables customers to implement next-generation capabilities and solutions as they emerge, and apply them to their service models to drive superior outcomes. For Cherwell customers, the possibilities are truly endless.”
The Azure Machine Learning integrations, which can be downloaded and applied to Cherwell Service Management instances in a matter of minutes, will be available shortly on the Cherwell mApp Exchange.
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About Cherwell Software
A global leader in IT and enterprise service management, Cherwell Software empowers IT to lead through the use of powerful and intuitive technology that enables better, faster, and more affordable innovation. The Cherwell® Service Management platform is built from the ground up with a unique codeless architecture that enables rapid time to value, infinite flexibility, and frictionless upgrades every time—at a fraction of the cost and complexity of legacy solutions. Because of Cherwell’s focus on delivering solutions that are easy to configure, customize, and use, IT organizations extend the Cherwell platform to solve a wide range of IT and business problems. With an unwavering commitment to putting customers first and being easy to do business with, Cherwell enjoys 98%+ customer satisfaction. Cherwell has a global network of expert partners serving customers in more than 40 countries. Corporate headquarters are in Colorado, USA, with global offices in the United Kingdom, Germany and Australia.
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