AI Solutions
for the manufacturing industry
The manufacturing industry faces challenges such as labor shortages, an aging workforce, and the need for skill transfer. As global competition intensifies and stable operations become critical, maintaining efficient production with limited staff is essential.
We support this transformation with AI solutions for defect detection, automation, and smart factory development, combining IoT, robotics, and model-based design to drive innovation and train future AI talent.
How We Solve
Use Cases
Automotive & Precision Equipment
Visual Inspection and Anomaly Detection
Equipment Lifetime and Failure Prediction
Supply Chain Risk Detection
Digitalization of Tacit Knowledge
Factories & Plants
Real-Time Monitoring of Equipment Operations
Enhanced Safety through Anomaly Detection
Reduced Downtime with Predictive Maintenance
Food, Chemical & Material
Foreign Object Detection in Production Lines
Stable Operations through Time-Series Data Analysis
Inventory and Expiration Loss Minimization
How We Solve
Solutions
From video and speech to language and sensor data, our expert team builds AI solutions that tackle real-world challenges using deep learning.
How We Solve
FAQ
How long does it take to complete a PoC?
Although it depends on the task and the state of data preparation, in most cases results can be confirmed within 2 to 3 months. For small-scale testing, it is possible to complete it in about 1 month.
How should I estimate costs (initial costs and operating costs)?
It varies depending on the type of AI used, the amount of data, and the scale of operation. It is common to clarify the necessary costs through a PoC, and then estimate the running costs during the actual implementation. If you contact us, we can provide you with a rough estimate that includes the initial and operating costs.
Is it possible to introduce AI even if there is little initial data?
Yes, it is possible. Even if you have little data, there are various approaches you can take, such as using existing public data or generating training data from existing data to train the model.
Can it be installed in an on-premise environment?
Yes, it is possible. Because the manufacturing industry handles highly confidential data, there is a high need for on-premise deployments. Our AI solutions are compatible with both cloud and on-premise deployments, and can be deployed on GPU servers or in existing environments.
Is it possible to introduce AI into computing environments and edge devices?
Although it depends on the equipment you use and the installation environment, it can basically be installed on edge devices such as production lines and inspection equipment. Please contact us for more information.
Is it possible to detect equipment abnormalities using existing sensors?
Yes, you can use data from existing temperature, vibration, current sensors, etc. AI can analyze "signs" that are difficult to detect using conventional threshold judgments, so by retrofitting existing equipment with AI, it can also lead to predictive maintenance that prevents breakdowns before they occur.