Aurora Mobile (NASDAQ: JG) and Tokyo-listed AI Storm Co., Ltd. (3719) are placing AI customer engagement and workflow software inside a live Japanese contact center, responding to acute labor shortages that have made real-world automation a near-term operational priority.
The project and the products
The companies will test EngageLab, a multi-channel customer engagement platform, and GPTBots.ai, an enterprise AI agent that connects knowledge bases and workflows to automate service tasks. The tools will run in the business environment of Nippon Telesystem Co., Ltd. (NTS), a wholly owned subsidiary of AI Storm. The goal is to measure how the combination of unified customer data and AI execution affects response times and experience quality in a production setting, not a lab.
Why Japan's support industry is a proving ground
Japan's contact center and BPO industries face persistent staffing gaps and rising customer expectations. For support leaders, the question has shifted from whether to experiment with AI to how to weave it into daily operations in ways that produce measurable results. For call center supervisors managing this transition, an AI Learning Path for Call Center Supervisors can help teams build the skills to work alongside production AI systems.
From proof of concept to production
"Our goal is not merely to replace human labor with AI, but to harness the power of AI to 'redefine customer relationships,'" said Weidong Luo, Chairman and Chief Executive Officer of Aurora Mobile. "By combining Aurora Mobile's technology with AI Storm's local execution capabilities, we look forward to helping Japanese enterprises elevate their AI implementation from the Proof of Concept stage to real-world Production." Aurora Mobile said it will continue to deepen the collaboration with AI Storm after the NTS verification project.
Why this matters for customer support professionals
This partnership signals that enterprises are moving past AI pilots and into systems that handle live customer conversations daily. For support teams, that means AI agents will increasingly become part of the tool stack. The ability to escalate to AI, interpret its outputs, and manage hybrid workflows is likely to become a core competency alongside traditional service skills.
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