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Industrial AI is moving from scenario applications to reconstruction of production systems. As competition deepens into yield, equipment efficiency and delivery value, vendors' value increasingly depends on whether they can understand industrial sites and turn that understanding into capabilities for continuous decision-making, collaborative execution and autonomous optimization.

On October 12, IDC released the IDC MarketScape: China Industrial AI and Agent Platforms 2026 Vendor Assessment. Evaluating from two dimensions—current capabilities and future strategy—Gtrontec successfully entered the Leaders Quadrant. Deep industrial knowledge built through long-term focus on semiconductors, model and agent capabilities validated in production scenarios, and an AI-native strategy evolving toward industrial ontology models and FDE delivery constitute the core support for Gtrontec's position in the Leaders Quadrant.

IDC noted in the report that the industrial AI and agent platform market is moving toward a key stage of platform-based scaled deployment. The penetration of model capabilities into industrial software does not happen automatically; it requires building a platform layer between models and scenarios that connects the two. Industrial AI and agent platforms encapsulate fragmented model capabilities into reusable, composable and governable scenario-based agents, and provide capabilities such as model access and management, agent orchestration and development, knowledge engineering and data governance, application operations and effectiveness evaluation, significantly lowering the threshold for enterprises to move from 'models available' to 'scenarios usable'.

This trend makes the organization and reuse of industrial knowledge critical. Software and equipment in factories run simultaneously and continuously generate data, while process rules, equipment status and business constraints are interrelated. For AI to participate in production decisions, it needs to understand problems within these relationships and identify the joint impact of an adjustment on quality, capacity, energy consumption and logistics.

Gtrontec, located in the Leaders Quadrant, differentiates itself from other selected vendors through the combination of pan-semiconductor site knowledge and industrial AI accumulation. The company has long focused on semiconductors, covering high-complexity scenarios such as wafers, packaging and panels, and has accumulated more than 30,000 models and engineering experiences in process, equipment, yield and scheduling. Positioned as an AI-native company, Gtrontec is using the 'Octopus Brain' industrial intelligent decision-making hub as its core to drive the transformation of site knowledge and AI accumulation into industrial ontology models, organizing production objects, relationships, rules and constraints into a knowledge system that AI can understand and invoke, forming intelligent assets with industry characteristics.

This change is also reshaping Gtrontec's business delivery model. Gtrontec is using Forward Deployed Engineers (FDEs) to go deep into customer sites, integrating business diagnosis, model construction and scenario validation throughout the delivery process, and driving the transition from consulting-based customized projects to 'FDE + scenario-based ontology model' delivery. At present, more than 300 industrial AI and agent projects have been deployed, and the knowledge and capabilities formed in these projects will continue to be accumulated and reused, providing a foundation for deployment and iteration in more scenarios.

In specific intelligent equipment business, this path corresponds to clear evolution directions. The AMHS business addresses material flow in semiconductor processes, using AI to reconstruct handling and scheduling models, optimizing collaboration under process and equipment constraints, and pursuing maximum line shipment output; the AOI business focuses on advanced packaging and testing defect inspection, strengthening AI recognition and analysis capabilities for complex defects. Together, they strengthen Gtrontec industrial AI's understanding and optimization of production processes.

It is noteworthy that this is another IDC recognition for Gtrontec after its previous inclusion in IDC Market Glance: China Industrial AI and Agents, 2Q26. Gtrontec's long-term goal is to enable AI to collaboratively drive industrial software and site equipment, and under safety, process and resource constraints, push production quality and yield, equipment intelligence and predictive maintenance, carbon emissions and logistics efficiency continuously closer to achievable optimal levels, gradually forming autonomous governance capabilities. From industrial knowledge modeling to delivery model transformation, this AI-native path points toward an AI factory capable of continuous perception, decision-making, execution and learning.