How Industry-Grade AGI Is Reshaping “Made in China”: Kutesmart’s Answer
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Kutesmart’s two-decade bet on data and customization has quietly produced one of the world’s most advanced examples of industry-grade AGI in action.
While Silicon Valley continues to debate when Artificial General Intelligence (AGI) will truly arrive, a company in Qingdao believes it already has. At Kutesmart (SZSE: 300840), AGI is no longer a concept confined to slide decks or research papers—it is a working production system.
Inside Kutesmart’s pilot factories and expanding clusters of agent-driven enterprises, there is no plant manager, no workshop supervisor, and no layers of approvals. Instead, a single chairman interfaces with a fully digital, intelligent operating system to run the entire business. What sounds like science fiction is already a functioning reality.
As the global AI race enters its second half, competitive advantage is no longer defined by dazzling virtual demos, but by the ability to rebuild real-world industries. Kutesmart’s experience suggests that industry-grade AGI is not a future promise—it is already here.
Two Decades in the Making
Kutesmart’s head start in the AGI race can be traced back to a bold decision made more than 20 years ago. In 2003, as China’s apparel industry struggled with chronic overcapacity and inventory backlogs, Kutesmart’s predecessor, Red Collar Group, took a contrarian path: it turned its own factory into a testbed for C2M (Customer-to-Manufacturer) large-scale mass customization.
The transformation was costly and disruptive. Founder Zhang Daili reinvested most of the company’s profits into building a flexible, intelligent manufacturing operating system. At the time, the move appeared radical—if not reckless. In hindsight, it created a strategic asset few companies possess today: two decades of high-quality, real-world production data that is usable, validated, and trustworthy.
“Data is the core—there is no question about that,” Zhang says. “Everyone is rushing into AI and large models, but very few truly value data. That is a serious problem.”
This long-term data accumulation, combined with years of digital transformation, has allowed Kutesmart to carve out a distinct position in the AI era. Today, its AGI platform is deeply integrated into Huawei’s digital ecosystem and is focused squarely on one goal: using AGI to rebuild enterprise value, redesign corporate intelligence, and give organizations something akin to a digital ‘brain.’
As Chairman Zhang Yunlan puts it: “Technology exists to create value. Enterprises are the creators of value. If technology cannot empower companies and generate productivity, it has no meaning.”
Rewriting the Rules of Production
A walk through Kutesmart’s factory floor reveals a fundamentally different manufacturing paradigm. Workers receive individualized task instructions on their screens. Laser cutters slice unique fabric pieces, each tagged with a digital “identity.” Intelligent overhead conveyor systems move materials autonomously from one process to the next.
“What you see here is a factory without managers,” Zhang Daili explains. “No plant director, no workshop leaders, no approvals. One chairman runs the enterprise through a single system. AGI has completely reshaped productivity—and with it, production relations. Efficiency is dramatically higher, and costs are significantly lower.”
At the center of this operation is Kutesmart’s enterprise-grade intelligent operating system—a unified AI control layer built around three native AI products: Kuxiaojiang (Demand Side – AI Designer) This module translates customer intent directly into production data. Customers can submit images, voice commands, or text descriptions, and the system instantly generates patterns, process instructions, and bills of materials. The result is true “what-you-see-is-what-you-get” manufacturing, with zero manual interpretation.
Kuxiaoyi (Operations Side – AI Operations Assistant) Designed around a “conversation equals work” philosophy, Kuxiaoyi turns AI-generated strategies into executable tasks. It monitors progress in real time, flags issues, assigns work, and even organizes meetings—shifting management from “people searching for data” to “data assisting people.”
Kuxiaozhi (Governance Side – AI Organizational Architect) This module continuously evaluates execution outcomes and dynamically optimizes organizational structures and workflows. It enables natural-language development and zero-code application creation, allowing non-technical staff to participate directly in innovation. Over time, rigid IT systems are broken down into modular, recomposable intelligence blocks.
Together, these systems form a closed-loop intelligent manufacturing brain spanning demand, operations, and governance. The results are tangible: management costs reduced by more than 50 percent and overall efficiency improved by over 20 percent. Just as importantly, the system is designed for simplicity—because scalability depends on ease of use.
From Factory Testbed to Industrial Blueprint
Once validated internally, Kutesmart’s model began pointing toward a much larger ambition. “We now have a complete methodology,” Zhang explains. “With a training team, an evaluation team, and the right tools, this system can be replicated across enterprises. A good standard is one that creates value, improves efficiency, reduces costs, and is easy to replicate.”
Kutesmart’s long-term vision is ambitious: to build 100 agent-driven enterprise clusters, serve a collaborative network of 500,000 people, and construct a high-level intelligent supply-and-demand ecosystem. The model is designed to expand beyond apparel into multiple industries, enabling AGI adoption at scale.
After visiting Kutesmart, Cui Peng, tenured associate professor at Tsinghua University’s Department of Computer Science, observed:
“If we see AI as the fulcrum of the Fourth Industrial Revolution, the key question is whether it can truly become productive force—whether it can empower industries and transform production relations. Kutesmart’s practice is a highly valuable and replicable exploration along this path, with strong implications for the broader ‘AI + Industry’ strategy.”
A Signal for the Next Phase of AI Competition
Kutesmart’s experience sends a clear signal: the future of AI competition will not be decided by simply attaching large models to existing workflows. It will be defined by how deeply data and algorithms penetrate the industrial core—reshaping enterprises into AI-native organizations.
As data-driven decision-making replaces layered management, and virtual intelligence fuses with physical production, a new manufacturing paradigm is taking shape. This is not just Kutesmart’s story—it marks a critical inflection point in China’s industrial intelligence transformation, and potentially, a preview of what global manufacturing may soon become.
