Zinier, a leading provider of intelligent field service automation, today introduced Intelligent Service Automation and Control (ISAC), an AI-driven platform enabling field service organizations to operate more efficiently. Through its machine learning and analytics capabilities, ISAC helps organizations optimize every aspect of their field service operations, resulting in the highest levels of automation-driven outcomes.

As the volume and complexity of field service requests continue to rise, field service organizations are looking for ways to drive efficiency and lay the groundwork for continued growth. At the same time, technology trends such as 5G in telecom and a sharp increase in the number of IoT-connected devices are creating a flood of new data streams, forcing organizations to move away from manual methods of collecting, analyzing, and acting on data.

Zinier’s ISAC platform uses machine learning to analyze data and provide real-time insights, driving productivity and enabling customers to inject automation into every step of the service delivery chain. By comparing a constant flow of field data against historical trends, ISAC is able to recommend the best course of action at any given time. And with a flexible, open architecture, customers can easily apply AI to specific use cases, whether it’s scanning a closeout package for anomalies or recommending a stock transfer by predicting parts required for a work order and an individual technician’s parts on-hand.

“After reviewing a number of solutions, we determined that Zinier was the only one that met all our requirements for flexibility and end-to-end automation,” said Luis Miguel Diaz Ortiz, Head of Telecom & Technology, Mexico at NCR Corporation. “ISAC’s AI and automation capabilities will help us manage infrastructure and work more proactively. We consider it a terrific investment in providing better service.”

With ISAC as the foundation, field service organizations can easily build AI solutions for the use cases most important to them. All they need to do is determine the scope, criteria, and threshold for AI recommendations, and ISAC will take it from there.

“Most companies are looking for ways to drive automation and turn data into actionable insights, but execution remains a challenge,” said Arka Dhar, co-founder and CEO of Zinier. “With ISAC, we’re helping our customers fully embrace automation by giving them a highly configurable tool that can be applied to their specific needs, driving efficiency and providing recommendations based on real-time data and user feedback.”

Key features/benefits of ISAC include:

  • Flexible, Configurable Platform: Unlike legacy solutions that can take months to update, ISAC was designed with flexibility and scalability in mind. Instead of being limited to a few use cases, customers can easily configure the features to apply AI to their operations by defining criteria and letting ISAC evaluate data accordingly.
  • Real-Time AI Recommendations: ISAC is constantly running in the background, observing user actions and providing recommendations. In some cases, ISAC will immediately implement a recommendation once it has been accepted by the user. In other cases, it will suggest a course of action for a back-office coordinator or field technician.
  • Seamless Integrations: Organizations can easily connect all of their critical systems using Zinier’s set of APIs and integrations, ensuring that all relevant information is factored into each recommendation and insight.

About Zinier

Zinier is an intelligent field service automation platform that helps organizations work smarter, faster, and more efficiently. Zinier’s end-to-end solution, Field Service Elements, is powered by ISAC and uses artificial intelligence, proactive insights, and an intuitive, all-in-one mobile experience to supercharge every aspect of an organization’s field service operations, from the back office all the way to the field. Zinier has international offices in Silicon Valley, Mexico City, Singapore, and Bengaluru. To learn more, visit www.zinier.com.

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