NICE Announces Global Robotics User Community Providing the Industry’s Richest Source for Information and Best Practice Sharing
January 23, 2019 at 06:30 am
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NICE announced the introduction of the NICE Robotic Automation Community, a global, communal educational platform providing vast resources and assets to accelerate the professional growth of the fast growing Robotic Process Automation (RPA) industry. The proliferation of RPA across industries is driving an upsurge in the need for professionals with specialist automation skills, a trend that is expected to continue. The NICE Robotic Automation Community helps organizations meet this demand by offering rich and varied educational resources, allowing employees to grow their professional automation skills, as well as enabling established professionals to hone their expertise from peer to peer experiences and global best practices. At the heart of the new community is NICE's 16 years of RPA experience and a plethora of successful large-scale deployments which makes it the vendor best equipped to offer the most comprehensive resources and expertise. By joining the NICE Robotic Automation Community, entry level employees as well as experts can learn how to harness the exponential growth the industry is experiencing and cultivate their skills and careers. Open to customers, partners, system integrators, as well as domain professionals across industries and from around the globe, the NICE Robotic Automation Community offers a variety of materials on one central platform. Materials include short articles, how to videos, white papers, in-depth e-learning content for technical employees and consultants, as well as certification programs. The community includes a forum that encourages discussions among peers and with NICE experts, enabling the sharing of best practices, guidelines and experiences that members can learn from and adopt in their own implementations. NICE's community is integrated with NICE Dojo, one of the largest global learning networks which enables users to easily access training assets and choose flexible learning paths to suit their individual and professional needs. The new Robotic Automation Community is backed by NICE’s vast knowledge and long-standing success rate in RPA, spanning 16 years of industry experience with large-scale and complex enterprise grade implementations. With over 550 deployments, many in Fortune 100 companies, and 500 000 robots in production, NICE is best equipped to deliver technical insights, industry leading best practices and practical guidelines that fuel RPA project success. In addition, as attended automation leaders, augmented by the launch of NEVA (NICE Employee Virtual Attendant), a first of its kind virtual attendant for employees, NICE's community members will have access to leading insights on NEVA’s cutting edge virtual assistant technology, as well at the latest cognitive innovations and trends in the industry. NICE RPA was named a ‘Leader’ and 'Star Performer', and Best-in-Breed for RDA (Robotic Desktop Automation) in Everest Group's PEAK Matrix™, part of their RPA Technology Vendor Assessment 2018 report.
NICE Ltd., formerly NICE-Systems Ltd., is a global enterprise software provider. The Company's segments include Customer Interactions Solutions, and Financial Crime and Compliance Solutions. The Customer Interactions Solutions segment provides data driven insights that enable businesses to deliver personalized experience to customers. The Financial Crime and Compliance Solutions segment provides real time and cross-channel fraud prevention, anti-money laundering, brokerage compliance and enterprise-wide case management. The Company serves contact centers, back office operations and retail branches, covering various industries, including communications, banking, insurance, healthcare, business processes outsourcing (BPO), government, utilities, travel and entertainment. Its Multi-Channel Recording and Interaction Management enables organizations to capture structured and unstructured customer interaction and transaction data from multiple channels.