Industrial AI company onepredict will present its AI Native Factory vision and data-centric approach to manufacturing transformation at AMWS 2026. While AI adoption across manufacturing continues to accelerate, many factories still struggle to realize its full value because data remains fragmented across disconnected systems.
According to Sung Min-seok, Vice President of onepredict, the key to making AI work in manufacturing is not simply collecting more data, but designing the right data architecture.
"Many manufacturers have successfully digitized their operations, yet their data remains isolated because different systems use different formats and standards," Sung explained. "Future manufacturing competitiveness will depend not on the performance of individual AI models, but on the ability to connect fragmented data into a unified context and consistently expand intelligence across the factory."
onepredict's AI Native Factory addresses this challenge by placing AI at the center of factory operations. Rather than treating AI as an additional automation layer, the concept envisions an intelligent manufacturing system where the entire production workflow is designed around continuously connected data.
"Simply accumulating data is not enough," Sung said. "Data must flow in real time to enable AI to become the operational core of the factory."
This vision is realized through cyclone, onepredict's manufacturing data integration platform, and pdx, its industrial AI platform.
Using ontology-based data integration, cyclone automatically connects data generated across equipment and manufacturing processes into a unified structure. pdx builds on this foundation by supporting operational decision-making across manufacturing functions, including quality, energy management, and predictive maintenance.
According to Sung, AI should not merely analyze data—it should transform factory operations by delivering actionable insights that produce measurable business outcomes.
The company's technology has already demonstrated tangible value across multiple manufacturing environments.
In semiconductor production lines, onepredict reduced OHT (Overhead Hoist Transport) operating manpower by 60% while shortening recovery lead times by 40%. In other manufacturing facilities, its AI detected critical equipment failures before they occurred, preventing significant production losses.
The company has also achieved measurable improvements in battery manufacturing, including lower defect rates and higher production efficiency, demonstrating that industrial AI can deliver real business value rather than remaining an experimental technology.
According to onepredict, its competitive advantage comes from combining AI with deep manufacturing domain expertise.
"The key to industrial AI is understanding the causal relationships between different data sources," Sung explained. To achieve this, onepredict has developed precise time-synchronization technology that aligns data collected from multiple manufacturing systems, enabling AI models to learn from accurately correlated events.
The company has also developed a Manufacturing Foundation Model (MxFM) that enables AI deployment using relatively small amounts of data, allowing manufacturers of various sizes to implement AI more quickly.
At AMWS 2026, onepredict's exhibition booth will demonstrate more than individual AI features. Visitors will experience the complete intelligent manufacturing workflow—from data collection and integration to analysis and AI-driven decision-making.
"The focus at AMWS is not the AI model itself," Sung said. "We want to show how data is connected and how that connected data enables intelligence across the entire factory."
He noted that manufacturing AI is rapidly evolving from analyzing individual signals toward integrated analysis across multiple data sources. As AI expands beyond individual processes to factory-wide operations, establishing a unified data infrastructure has become increasingly important.
Looking ahead, Sung believes competitive advantage will come not from AI models alone, but from the ability to reuse and continuously expand manufacturing data across multiple AI applications.
onepredict plans to continue expanding its AI Native Factory OS ecosystem beyond predictive maintenance into quality management, production optimization, process control, and energy management.
"Our goal is to create a manufacturing environment where the entire factory operates as a single intelligent system," Sung said. "We also aim to establish an industrial AI standard that can be adopted globally."
Interview Highlights
How does onepredict view manufacturing transformation in the AI era?
Manufacturing is moving beyond automation and digitalization toward AI-centric operations. While factories already possess large volumes of data, disconnected systems often prevent that data from improving real-world operations. onepredict believes the key lies in designing data architectures that enable continuous data flow and connected decision-making across the factory.
What are onepredict's flagship solutions and key achievements?
The company offers cyclone, a manufacturing data integration platform, and pdx, an industrial AI platform that supports decision-making across quality, energy management, and equipment operations. These solutions have already delivered measurable improvements in semiconductor manufacturing, equipment diagnostics, and battery production.
What differentiates onepredict from competitors?
onepredict combines manufacturing domain expertise with AI. Its precise time-synchronization technology aligns data collected from different industrial systems, enabling AI to accurately learn causal relationships. Combined with its Manufacturing Foundation Model (MxFM), the company can rapidly deploy AI even in environments with limited training data.
What trends are shaping the manufacturing AI market?
Manufacturing AI is evolving from analyzing isolated data sources toward integrated analysis across diverse information streams. As AI expands from individual production processes to factory-wide operations, unified data infrastructure, data reuse, and scalability are becoming critical competitive advantages.
What is onepredict's strategy for 2026?
The company will continue expanding the AI Native Factory OS ecosystem beyond predictive maintenance into quality, production, process control, and energy management. Rather than offering standalone applications, onepredict aims to deliver an integrated platform capable of operating an entire factory as a unified intelligent system.
What message does onepredict hope visitors take away from AMWS 2026?
According to onepredict, manufacturing transformation is driven not by individual AI models but by how data is integrated, connected, and reused. At AMWS 2026, the company will demonstrate how this data-centric architecture enables practical AI deployment across real manufacturing environments.
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Industrial AI company onepredict will present its AI Native Factory vision and data-centric approach to manufacturing transformation at AMWS 2026. While AI adoption across manufacturing continues to accelerate, many factories still struggle to realize its full value because data remains fragmented across disconnected systems.
According to Sung Min-seok, Vice President of onepredict, the key to making AI work in manufacturing is not simply collecting more data, but designing the right data architecture.
"Many manufacturers have successfully digitized their operations, yet their data remains isolated because different systems use different formats and standards," Sung explained. "Future manufacturing competitiveness will depend not on the performance of individual AI models, but on the ability to connect fragmented data into a unified context and consistently expand intelligence across the factory."
onepredict's AI Native Factory addresses this challenge by placing AI at the center of factory operations. Rather than treating AI as an additional automation layer, the concept envisions an intelligent manufacturing system where the entire production workflow is designed around continuously connected data.
"Simply accumulating data is not enough," Sung said. "Data must flow in real time to enable AI to become the operational core of the factory."
This vision is realized through cyclone, onepredict's manufacturing data integration platform, and pdx, its industrial AI platform.
Using ontology-based data integration, cyclone automatically connects data generated across equipment and manufacturing processes into a unified structure. pdx builds on this foundation by supporting operational decision-making across manufacturing functions, including quality, energy management, and predictive maintenance.
According to Sung, AI should not merely analyze data—it should transform factory operations by delivering actionable insights that produce measurable business outcomes.
The company's technology has already demonstrated tangible value across multiple manufacturing environments.
In semiconductor production lines, onepredict reduced OHT (Overhead Hoist Transport) operating manpower by 60% while shortening recovery lead times by 40%. In other manufacturing facilities, its AI detected critical equipment failures before they occurred, preventing significant production losses.
The company has also achieved measurable improvements in battery manufacturing, including lower defect rates and higher production efficiency, demonstrating that industrial AI can deliver real business value rather than remaining an experimental technology.
According to onepredict, its competitive advantage comes from combining AI with deep manufacturing domain expertise.
"The key to industrial AI is understanding the causal relationships between different data sources," Sung explained. To achieve this, onepredict has developed precise time-synchronization technology that aligns data collected from multiple manufacturing systems, enabling AI models to learn from accurately correlated events.
The company has also developed a Manufacturing Foundation Model (MxFM) that enables AI deployment using relatively small amounts of data, allowing manufacturers of various sizes to implement AI more quickly.
At AMWS 2026, onepredict's exhibition booth will demonstrate more than individual AI features. Visitors will experience the complete intelligent manufacturing workflow—from data collection and integration to analysis and AI-driven decision-making.
"The focus at AMWS is not the AI model itself," Sung said. "We want to show how data is connected and how that connected data enables intelligence across the entire factory."
He noted that manufacturing AI is rapidly evolving from analyzing individual signals toward integrated analysis across multiple data sources. As AI expands beyond individual processes to factory-wide operations, establishing a unified data infrastructure has become increasingly important.
Looking ahead, Sung believes competitive advantage will come not from AI models alone, but from the ability to reuse and continuously expand manufacturing data across multiple AI applications.
onepredict plans to continue expanding its AI Native Factory OS ecosystem beyond predictive maintenance into quality management, production optimization, process control, and energy management.
"Our goal is to create a manufacturing environment where the entire factory operates as a single intelligent system," Sung said. "We also aim to establish an industrial AI standard that can be adopted globally."
Interview Highlights
How does onepredict view manufacturing transformation in the AI era?
Manufacturing is moving beyond automation and digitalization toward AI-centric operations. While factories already possess large volumes of data, disconnected systems often prevent that data from improving real-world operations. onepredict believes the key lies in designing data architectures that enable continuous data flow and connected decision-making across the factory.
What are onepredict's flagship solutions and key achievements?
The company offers cyclone, a manufacturing data integration platform, and pdx, an industrial AI platform that supports decision-making across quality, energy management, and equipment operations. These solutions have already delivered measurable improvements in semiconductor manufacturing, equipment diagnostics, and battery production.
What differentiates onepredict from competitors?
onepredict combines manufacturing domain expertise with AI. Its precise time-synchronization technology aligns data collected from different industrial systems, enabling AI to accurately learn causal relationships. Combined with its Manufacturing Foundation Model (MxFM), the company can rapidly deploy AI even in environments with limited training data.
What trends are shaping the manufacturing AI market?
Manufacturing AI is evolving from analyzing isolated data sources toward integrated analysis across diverse information streams. As AI expands from individual production processes to factory-wide operations, unified data infrastructure, data reuse, and scalability are becoming critical competitive advantages.
What is onepredict's strategy for 2026?
The company will continue expanding the AI Native Factory OS ecosystem beyond predictive maintenance into quality, production, process control, and energy management. Rather than offering standalone applications, onepredict aims to deliver an integrated platform capable of operating an entire factory as a unified intelligent system.
What message does onepredict hope visitors take away from AMWS 2026?
According to onepredict, manufacturing transformation is driven not by individual AI models but by how data is integrated, connected, and reused. At AMWS 2026, the company will demonstrate how this data-centric architecture enables practical AI deployment across real manufacturing environments.