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AI-powered image-based classification for optimized process control and fast root cause analysis.
Download Data sheetAI-powered image-based classification for optimized process control and fast root cause analysis.
Download Data sheetc-Alice is an AI-powered image classification app, built for complex production environments that depend on high-volume image data from multiple systems for quality control.
Results go straight to your IoT Data Platform or reporting and control tools – just where and when you need them, which leads to optimized process control and fast root cause analysis.
"After a quick implementation into our infrastructure, we can use c-Alice to automatically evaluate images at many monitoring points in the manufacturing process. The application is easy to use, so engineers and technicians are able to implement their specific use cases themselves. By using c-Alice, we have already been able to identify several process problems at an early stage and save considerable costs by significantly improving yields."
Dejan Simic Head of Metrology at Semikron-Danfoss
"With c-Alice, we are able to evaluate the data generated during our inspection processes more accurately and reliably. We can detect errors at different levels in the production process, we can see at which levels they occur and whether they are ultimately relevant to the product. Our experts can apply AI methods in a simple and intuitive way and transfer their knowledge to so-called recipes, which can be created, configured, trained, released and implemented using a simple workflow."
Site manager Jörg Amelung and defect density engineer Juliane Weise at Fraunhofer IPMS
Everything inside c-Alice is designed to work intuitively for engineers and technicians – without requiring AI knowledge or code. The system adapts to your production setup with maximum flexibility.
Any type of inspection / microscopy, wafer maps, test maps and others.
Easily adjust, monitor, and expand AI models without in-depth AI knowledge.
Low maintenance, increases throughput and reduces personel requirements.
To organize images with their meta data and classify them.
To improve, monitor or deploy trained recipes.
To version, organize and deploy recipes for full traceability.
To feed result data exactly where you need them.
