News
Zhenlan Water Meter Goes Live on AI Agent Platform
Release time:
2025-11-26
The deepening application of AI technology is driving the industry to shift from a past focus on competing over the functionality of metering devices to today’s diversified competition centered on unlocking data value and building intelligent service ecosystems. Recently, the AI agent platform jointly developed by Zhenlan Water Meter and Mozhi Technology, along with its first business-specific AI agent, has officially gone live. As a scalable AI capability hub, this platform will cover core areas such as R&D, production, customer service, and management.
The deepening application of AI technology is driving the industry to shift from a past focus on competing over the functionality of metering devices to today’s diversified competition centered on unlocking data value and building intelligent service ecosystems. Recently, the AI agent platform jointly developed by Zhenlan Water Meter and Mozhi Technology—and its first business-specific AI agent—have officially been put into operation. As a scalable AI capability hub, this platform will cover core areas such as R&D, production, customer service, and management.
AI agent technology is expected to help enterprises improve quality and efficiency in four key areas:
1) Predictive maintenance: By analyzing operational data, proactively warn of equipment failures, thereby reducing operation and maintenance costs and water resource leakage.
2) Intelligent customer service: Provides 24/7 support for high-frequency inquiries such as meter readings and billing, enhancing response efficiency and user experience.
3) Data-driven R&D: Optimize product design based on actual operational data to accelerate the iteration of new products that meet market demands.
4) Operational efficiency enhancement: Automate processes such as human resources and finance to free up resources and enable a focus on business innovation.
The implementation of this platform provides the instrumentation industry with an optional pathway for large-scale AI applications, and AI technology will continue to empower the industry to move toward greater efficiency and intelligence.
Source: Fuzhou Zhenlan
Editor: Li Jingshuai
First Instance: Zhou Qi
Second Instance: Zhang Wenjiang
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