AI brings order to label diversity Vision AI Label Reader automates label capture and ensures process reliability Goods-in operations in the electronics industry are under increasing pressure. Countless components from a wide range of manufacturers arrive with constantly changing label layouts, multilingual markings and ever shorter throughput times. What could once be managed manually has now become a bottleneck. Damaged barcodes or reflective packaging further increase effort and make processes more error-prone The Vision AI Label Reader from collective mind GmbH (COMI) demonstrates how this complexity can be managed. The AI-based image processing system automates the capture and interpretation of item information in goods-in and logistics - regardless of layout, language or code type. Designed for industrial use, the solution improves process reliability, enhances data quality and streamlines workflows. A uEye CP industrial camera from IDS Imaging Development Systems GmbH provides the image data required for analysis. Fully automated capture instead of manual inspection The Vision AI Label Reader is designed for applications where a wide variety of items, labels and packaging are processed on a daily basis. This makes it particularly suitable for electronics manufacturing service providers as well as companies with complex logistics processes and extensive inventories. One concrete example is Rutronik Elektronische Bauelemente GmbH, a globally leading broad-line distributor of electronic components, where the system is already in successful operation. The goal is to automatically capture all relevant item information and make it available in a structured format. To achieve this, the system recognizes all labels on an object, reads printed text as well as 1D and 2D codes, and then interprets the content using artificial intelligence. Handwritten entries can also be processed if required. Crucially, recognition does not rely on predefined label standards. New layouts, languages or code formats can be handled without retraining - a