Mondrian AI’s MonPlant Enables No-Code Model Development and Equipment Control

Data collected from production equipment can now be used for AI model training and process control. Users can develop models without coding, monitor performance changes after deployment, and retrain models when needed.

AI infrastructure, platform, and cloud technology company Mondrian AI will showcase its manufacturing-focused AI platform, MonPlant, at the 2026 Industrial AI EXPO. The platform brings together manufacturing data integration, model development and operations, and equipment control integration in a single environment.

The 2026 Industrial AI EXPO is a specialized exhibition for AI technologies and solutions that drive real industrial operations. It highlights AI use cases across manufacturing and other industries, while showcasing how the ecosystem is using AI to advance technological innovation and develop new business opportunities.

MonPlant connects with existing on-site systems, including programmable logic controllers (PLCs), manufacturing execution systems (MES), and enterprise resource planning (ERP) systems, to collect and integrate data distributed across different equipment in real time.

The platform also includes dedicated labeling tools for vision inspection images and time-series sensor data. Users can label whether products in inspection images are normal or defective, or mark periods of anomalies in sensor data collected over time. These features help create the reference data needed to train AI models. Data collected from heterogeneous systems is consolidated on a single platform and prepared in a format suitable for AI model training.

A key feature of the platform is that on-site engineers can develop AI models directly. MonPlant provides a no-code development environment where users can train and evaluate models by selecting the required items on screen, without writing code. It also includes pre-trained models optimized for manufacturing use cases, such as vision inspection, time-series forecasting, and anomaly detection. Mondrian AI explained that MonPlant lowers the barriers to AI development for on-site personnel and reduces the time required from data preparation to model training.

The model development process is also supported by an AI Copilot. Users can request dataset uploads, model training, or deployment in natural language, and the platform carries out those requests as an integrated workflow. Training history and deployment status can also be generated as conversational reports, helping users review the information needed for model management.

Once trained, AI models can be deployed to systems connected to production sites, including APIs, edge devices, and PLCs. Through machine learning operations (MLOps), which manages model versions and operational status, users can continuously monitor performance changes that occur in real production processes

The platform also detects data drift, where the characteristics of field data change from those present during training, and can initiate retraining procedures when necessary. This helps address declining accuracy after deployment and supports continuous model performance management.

These operational capabilities also extend to on-site monitoring and equipment control. MonPlant provides customizable dashboards that configure key performance indicators (KPIs) for goals such as quality optimization, vision inspection, and predictive maintenance. When real-time analysis detects abnormal signals, the platform notifies operators and connects with preconfigured control logic to support immediate on-site responses.

Mondrian AI has also shared a real-world manufacturing deployment case. In March, the company completed the initial implementation of a MonPlant-based process AI system for the cathode material production process at COSMO AM&T Co., Ltd., a Korean manufacturer of battery materials. The company integrated production-process data and provided data analytics, AI model training and inference, and real-time dashboard capabilities in one environment.

The project was carried out as part of the Ministry of Trade, Industry and Energy’s AI Autonomous Manufacturing Leading Project, which supports the advancement and automation of production processes by introducing AI, robots, and equipment into manufacturing sites.

At the exhibition, Mondrian AI will introduce MonPlant’s data integration, model development, and operations capabilities based on this manufacturing deployment experience. The company also plans to demonstrate its technological capabilities across AI infrastructure, platforms, and cloud through AI transformation (AX) cases involving large enterprises and public institutions.

On the final day of the exhibition, October 23, CTO Jimin Hwa will speak at the AI-Tech Seminar. The session, focused on practical manufacturing AX, will cover the process of applying AI technologies in manufacturing environments and real-world implementation approaches.

Mondrian AI plans to expand industry-specific AX initiatives by combining MonPlant with its proprietary AI infrastructure and platform technologies. A company representative said, “The core of AI adoption is not simply building massive infrastructure, but transforming field data into business value.” The company added that it will support AI transformation across Korea’s manufacturing and industrial sectors through MonPlant and integrated AX consulting.

The 2026 Industrial AI EXPO will be held at KINTEX in Ilsan from October 21 to 23. It will be linked to K Connect AI, the national industrial AI platform promoted by the Ministry of Trade, Industry and Energy, and will feature industrial AI technology and solution exhibitions, conferences, export consultations, investment programs, and open innovation initiatives.