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Physical AI​

PrefactorTech focuses on early-stage factory planning using Visual Components–based Digital Twin simulation to validate production flow, layout, and automation feasibility during the design phase. This reduces deployment risk and shortens project timelines. As an NVIDIA Connect: Advancing ISV partner, PrefactorTech applies a Physical AI–driven approach to ensure consistency from virtual planning to physical execution.

Digital Twin

PrefactorTech focuses on early-stage factory planning, using Visual Components–based Digital Twin simulation to validate production flow, layout, and automation feasibility during the design phase. This approach reduces deployment risk and shortens project timelines. As an NVIDIA Connect: Advancing ISV partner, PrefactorTech applies a Physical AI–driven approach to connect simulation and real-world equipment, ensuring alignment from virtual planning to physical execution.​

About Prefactor

PrefactorTech is a government-certified AI technology service provider recognized by the Ministry of Digital Affairs, and a certified automation engineering service provider recognized by the Ministry of Economic Affairs. By combining factory-level experience with system integration capabilities, we deliver integrated solutions across automation, Digital Twin, and AI—leveraging AI vision, edge computing, and LLM technologies to improve productivity, quality, and enable smart manufacturing.​

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Creating Autonomous, Decision-Driven Productivity​

PrefactorTech places Physical AI at the core of smart manufacturing, integrating automation equipment, Digital Twin technologies, and AI to enable production systems to perceive on-site conditions, make decisions, and respond in real time—delivering greater efficiency and flexibility on the factory floor.
As product lifecycles shorten and changeovers accelerate, hardware automation alone is no longer sufficient. Using Digital Twin and Visual Components simulation, PrefactorTech validates equipment, robots, and processes before deployment, then applies AI vision and data analytics to support automated inspection, quality decisions, and anomaly feedback during operation.
With Physical AI, simulation becomes a decision-making tool rather than a visual aid. Engineers reduce risk and trial-and-error before deployment, while systems continue to optimize decisions with real-world data after go-live—turning automation into a sustainable, evolving source of productivity.