[Industry News = Reporter Hyun-woo Park] As the digital transformation of manufacturing sites accelerates, massive amounts of data are pouring out from all corners of factories. Paradoxically, however, as data increases, the phenomenon of 'information islands'—where data fails to communicate—is worsening. There is a company tackling this issue head-on.
onepredict aims to realize an 'ai-native factory' where the entire factory operates as a single intelligent system by organically integrating fragmented field data. With the data integration platform 'cyclone' and the field intelligence solution 'pdx' as its two main pillars, onepredict has built substantial achievements across various manufacturing industries such as semiconductors, batteries, and heavy industry. Along with its global market entry in 2026, the company plans to fully launch the establishment of an 'ai native factory os' ecosystem. We sat down for a Q&A session with Min-seok Sung, Vice President of onepredict.
Min-seok Sung, Vice President of onepredict, stated, "onepredict is making the future a reality where the entire factory operates as a single intelligent system by connecting fragmented islands of data and transforming chaotic raw data into high-value assets." [Photo = onepredict]
AI is the major issue here. Where is onepredict focusing its capabilities?
onepredict is leading the paradigm shift toward an 'ai-native factory,' where the entire factory process is designed and driven with AI at its core. Currently, many manufacturing sites are undergoing digital transformation and generating vast amounts of data, but they face the paradox of increasing 'information islands'—unable to communicate with each other due to different formats and standards.
We believe that future manufacturing competitiveness lies beyond merely automating equipment; it depends on how consistently a factory's intelligence can be expanded by weaving scattered information into a single context. Therefore, rather than getting bogged down in building individual AI models, onepredict is concentrating its enterprise-wide capabilities on designing an 'optimal data architecture' where AI can practically operate. Moving past the stage of simply stockpiling data, allowing it to flow in real time so that operation-centric AI can drive the factory's entire intelligent system is the core strategy onepredict pursues.
What are the core solutions of onepredict?
'cyclone', which transforms chaotic field data into valuable assets, and 'pdx', which realizes field intelligence based on this data, make up onepredict's core lineup. 'cyclone', a data integration platform, automatically combines multimodal raw data based on an ontology. A semiconductor manufacturing line that adopted this achieved a 60% reduction in OHT (Overhead Hoist Transport) operational personnel and shortened recovery lead times by up to 40%.
The data integration platform 'cyclone' automatically combines multimodal raw data based on an ontology, while 'pdx' integrally manages decision-making across quality, energy, and predictive maintenance domains. [Photo = onepredict]
Furthermore, 'pdx' integrally manages decision-making in the areas of quality, energy, and predictive maintenance. In an actual use case with Company G, it preemptively detected a fatal defect in core equipment 39 days in advance, preventing annual losses of over $700,000. In addition, it has created tangible business value across various industries, such as reducing the defect rate by up to 15% and improving productivity by 8% in battery manufacturing processes.
Where does the differentiation of these solutions come from?
onepredict's unrivaled strength is rooted in its 'domain knowledge-based industrial AI' technology, perfectly transplanting over 20 years of equipment experts' know-how into AI algorithms. In particular, we have resolved the issue of time discrepancies between systems—the biggest barrier to implementing industrial AI—through high-precision reference time alignment technology, ensuring that the AI accurately learns causal relationships.
Additionally, by utilizing the latest 'Manufacturing Foundation Model (MxFM)', we have secured Few-shot adaptation technology that rapidly operationalizes AI with only a small amount of field data. This leads to the scalability of fully preparing 'AI-ready data' within a short period, regardless of the site size. Based on this reliability, we have been officially recognized for our execution capabilities by being selected as a specialized ai factory enterprise and acquiring Level 3 certification in the smart factory supplier competency assessment.
How do you forecast recent trends in industrial sites?
Recently, industrial sites have been rapidly restructuring toward 'linked analysis', integrally interpreting heterogeneous data—such as process loads, operational modes, and maintenance history—moving beyond the limitations of single-pattern analysis like vibration signals.
The market now demands robust infrastructure capable of horizontally deploying AI across the entire factory, moving past the level of one-off Proof of Concepts (PoC). Industrial data platforms will establish themselves as core assets that define an organization's operational capabilities.
To simultaneously satisfy security, real-time performance, and cost-efficiency, a hybrid deployment encompassing both on-premises and cloud edge environments will become an essential technical standard. We predict that a virtuous cycle structure where data is reused across multiple models will become the key indicator determining the future competitiveness of manufacturing enterprises.
What are your plans for 2026?
In 2026, onepredict plans to consolidate all its capabilities into building an 'ai native factory os' ecosystem where the entire factory autonomously learns and operates. Going beyond the existing predictive maintenance domain, we are strengthening our intelligent solution lineup to encompass overall manufacturing operations—including AI-based Quality Management Systems (AI-QMS), AI-Programmable Logic Controllers (AI-PLC), AI-Manufacturing Execution Systems (AI-MES), AI-Maintenance Management Systems (AI-MMS), and AI-Factory Energy Management Systems (AI-FEMS)—and accelerating their commercialization.
In particular, using the monumental achievement of signing our first overseas supply contract in 2025 as a stepping stone, we are expanding our entry into the global market in earnest. Based on our proven technology and certified security systems, we aim to lead the global standard for reliable industrial AI.
What message do you want to emphasize at this AW 2026?
The essential message onepredict wants to convey at this event is that the success of manufacturing innovation depends not on individual AI models, but on the 'organic integration of data.' The investment urgently needed at industrial sites right now is not simply adopting AI with flashy performance, but designing a fundamental data architecture where AI can continuously learn and scale.
onepredict is making the future a reality where the entire factory operates as a single intelligent system by connecting fragmented islands of data and transforming chaotic raw data into high-value assets. This AW 2026 will serve as an opportunity to witness how AI becomes the essence of manufacturing, maximizing corporate productivity and realizing disruptive innovation.
Source: Industry News (https://www.industrynews.co.kr)
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[Industry News = Reporter Hyun-woo Park] As the digital transformation of manufacturing sites accelerates, massive amounts of data are pouring out from all corners of factories. Paradoxically, however, as data increases, the phenomenon of 'information islands'—where data fails to communicate—is worsening. There is a company tackling this issue head-on.
onepredict aims to realize an 'ai-native factory' where the entire factory operates as a single intelligent system by organically integrating fragmented field data. With the data integration platform 'cyclone' and the field intelligence solution 'pdx' as its two main pillars, onepredict has built substantial achievements across various manufacturing industries such as semiconductors, batteries, and heavy industry. Along with its global market entry in 2026, the company plans to fully launch the establishment of an 'ai native factory os' ecosystem. We sat down for a Q&A session with Min-seok Sung, Vice President of onepredict.
Min-seok Sung, Vice President of onepredict, stated, "onepredict is making the future a reality where the entire factory operates as a single intelligent system by connecting fragmented islands of data and transforming chaotic raw data into high-value assets." [Photo = onepredict]
AI is the major issue here. Where is onepredict focusing its capabilities?
onepredict is leading the paradigm shift toward an 'ai-native factory,' where the entire factory process is designed and driven with AI at its core. Currently, many manufacturing sites are undergoing digital transformation and generating vast amounts of data, but they face the paradox of increasing 'information islands'—unable to communicate with each other due to different formats and standards.
We believe that future manufacturing competitiveness lies beyond merely automating equipment; it depends on how consistently a factory's intelligence can be expanded by weaving scattered information into a single context. Therefore, rather than getting bogged down in building individual AI models, onepredict is concentrating its enterprise-wide capabilities on designing an 'optimal data architecture' where AI can practically operate. Moving past the stage of simply stockpiling data, allowing it to flow in real time so that operation-centric AI can drive the factory's entire intelligent system is the core strategy onepredict pursues.
What are the core solutions of onepredict?
'cyclone', which transforms chaotic field data into valuable assets, and 'pdx', which realizes field intelligence based on this data, make up onepredict's core lineup. 'cyclone', a data integration platform, automatically combines multimodal raw data based on an ontology. A semiconductor manufacturing line that adopted this achieved a 60% reduction in OHT (Overhead Hoist Transport) operational personnel and shortened recovery lead times by up to 40%.
The data integration platform 'cyclone' automatically combines multimodal raw data based on an ontology, while 'pdx' integrally manages decision-making across quality, energy, and predictive maintenance domains. [Photo = onepredict]
Furthermore, 'pdx' integrally manages decision-making in the areas of quality, energy, and predictive maintenance. In an actual use case with Company G, it preemptively detected a fatal defect in core equipment 39 days in advance, preventing annual losses of over $700,000. In addition, it has created tangible business value across various industries, such as reducing the defect rate by up to 15% and improving productivity by 8% in battery manufacturing processes.
Where does the differentiation of these solutions come from?
onepredict's unrivaled strength is rooted in its 'domain knowledge-based industrial AI' technology, perfectly transplanting over 20 years of equipment experts' know-how into AI algorithms. In particular, we have resolved the issue of time discrepancies between systems—the biggest barrier to implementing industrial AI—through high-precision reference time alignment technology, ensuring that the AI accurately learns causal relationships.
Additionally, by utilizing the latest 'Manufacturing Foundation Model (MxFM)', we have secured Few-shot adaptation technology that rapidly operationalizes AI with only a small amount of field data. This leads to the scalability of fully preparing 'AI-ready data' within a short period, regardless of the site size. Based on this reliability, we have been officially recognized for our execution capabilities by being selected as a specialized ai factory enterprise and acquiring Level 3 certification in the smart factory supplier competency assessment.
How do you forecast recent trends in industrial sites?
Recently, industrial sites have been rapidly restructuring toward 'linked analysis', integrally interpreting heterogeneous data—such as process loads, operational modes, and maintenance history—moving beyond the limitations of single-pattern analysis like vibration signals.
The market now demands robust infrastructure capable of horizontally deploying AI across the entire factory, moving past the level of one-off Proof of Concepts (PoC). Industrial data platforms will establish themselves as core assets that define an organization's operational capabilities.
To simultaneously satisfy security, real-time performance, and cost-efficiency, a hybrid deployment encompassing both on-premises and cloud edge environments will become an essential technical standard. We predict that a virtuous cycle structure where data is reused across multiple models will become the key indicator determining the future competitiveness of manufacturing enterprises.
What are your plans for 2026?
In 2026, onepredict plans to consolidate all its capabilities into building an 'ai native factory os' ecosystem where the entire factory autonomously learns and operates. Going beyond the existing predictive maintenance domain, we are strengthening our intelligent solution lineup to encompass overall manufacturing operations—including AI-based Quality Management Systems (AI-QMS), AI-Programmable Logic Controllers (AI-PLC), AI-Manufacturing Execution Systems (AI-MES), AI-Maintenance Management Systems (AI-MMS), and AI-Factory Energy Management Systems (AI-FEMS)—and accelerating their commercialization.
In particular, using the monumental achievement of signing our first overseas supply contract in 2025 as a stepping stone, we are expanding our entry into the global market in earnest. Based on our proven technology and certified security systems, we aim to lead the global standard for reliable industrial AI.
What message do you want to emphasize at this AW 2026?
The essential message onepredict wants to convey at this event is that the success of manufacturing innovation depends not on individual AI models, but on the 'organic integration of data.' The investment urgently needed at industrial sites right now is not simply adopting AI with flashy performance, but designing a fundamental data architecture where AI can continuously learn and scale.
onepredict is making the future a reality where the entire factory operates as a single intelligent system by connecting fragmented islands of data and transforming chaotic raw data into high-value assets. This AW 2026 will serve as an opportunity to witness how AI becomes the essence of manufacturing, maximizing corporate productivity and realizing disruptive innovation.
Source: Industry News (https://www.industrynews.co.kr)