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Efficiency improvement solution for incoming inspection utilizing generative AI-OCR.

Take a photo with your smartphone and let the AI read the manufacturer-specific label! Thorough prevention of incoming inspection errors and incorrect storage.

**Challenges in Incoming Inspection** Food and chemical manufacturers handle a variety of raw materials and components, and incoming goods come in various packaging forms such as cardboard boxes, one-gallon cans, craft bags, and bottles. Upon arrival, it is necessary to visually confirm product information such as "product name," "lot number," "capacity," and "expiration date," and cross-check it with the incoming data. This process can be particularly time-consuming and labor-intensive for items without barcodes. Additionally, since the inspection is conducted visually by humans, there are risks of human errors such as incorrect storage and variations in inspection accuracy due to differing levels of experience. **Solution Using Generative AI-OCR** - Simply take a photo with a smartphone, and the generative AI automatically reads the necessary items. - It can flexibly read various labels without the need for format training. - By cross-referencing the reading results with the incoming data, it prevents inspection errors and reduces work time. - Issue internal management labels with QR codes, which can also be used for inventory management, stocktaking, and shipping inspections. *For more details, please download the PDF or feel free to contact us.*

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AI-OCR Incoming Inspection Efficiency Solution for the Manufacturing Industry

Preventing incoming inspection errors by reading manufacturer labels with smartphone photography.

In the manufacturing industry, handling a wide variety of parts and raw materials requires a significant amount of time and effort for visual inspections upon arrival. Particularly in cases where there are no barcodes, the verification of item names and lot numbers becomes complicated, increasing the risk of human error leading to incorrect inventory entries. Our AI-OCR-based solution for streamlining incoming inspection processes addresses these challenges. 【Use Cases】 - Reading labels of parts without barcodes - Inspection tasks by cross-referencing with incoming data - Integration with inventory management, stocktaking, and shipping inspections 【Benefits of Implementation】 - Reduction in incoming inspection task time - Decrease in human errors such as incorrect inventory entries - Improvement and standardization of inspection accuracy - Enhanced inventory management through the issuance of internal management labels

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AI-OCR Utilization Solution for Retail: Streamlining Incoming Inspection Efficiency

Preventing product confirmation errors by reading manufacturer labels with smartphone photography.

In the retail industry, product verification can be time-consuming and labor-intensive due to the diverse range of products arriving in various forms. This process involves visually confirming information such as product names, lot numbers, capacities, and expiration dates, and matching them with incoming data. This task becomes even more complicated for products without barcodes. Additionally, manual verification carries risks such as incorrect stock entries and variations in inspection accuracy. Our efficiency solution for incoming inspections utilizing generative AI-OCR addresses these challenges. 【Use Cases】 - Inspection during product arrivals at stores - Confirmation of product acceptance in the backroom - Verification of products requiring expiration date management 【Benefits of Implementation】 - Automatically reads necessary information by simply taking a photo with a smartphone, streamlining the verification process - No format learning required, compatible with various manufacturer labels - Reduces the risk of inspection errors and incorrect stock entries - Contributes to standardizing operations from incoming inspections to inventory management.

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Logistics Industry Solution for Streamlining Incoming Inspection Efficiency with Generative AI-OCR

AI reads cargo labels through smartphone photography to prevent inspection errors and incorrect storage.

In the logistics industry, handling a wide variety of cargo involves a lot of effort and time spent on visually confirming information such as product names, lot numbers, and capacities, and cross-referencing this with incoming data. This task becomes even more complicated, especially for cargo without barcodes. Manual visual checks carry risks such as human errors like incorrect inventory entries and variations in inspection accuracy depending on the skill level of the personnel involved. Our generative AI-OCR-based solution for streamlining incoming inspection addresses these challenges and enhances the accuracy and efficiency of operations. 【Use Cases】 - Incoming inspection of cargo without barcodes - Tasks that take time for visual confirmation - Situations where there is a desire to reduce the risk of incorrect inventory entries - Standardization and labor-saving of inspection tasks 【Benefits of Implementation】 - Reduction of work time through automatic reading via smartphone photography - No need for format learning, accommodating various labels - Prevention of inspection errors through cross-referencing with incoming data - Integration with inventory management, stocktaking, and outgoing inspection through the issuance of internal management labels

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AI-OCR Incoming Inspection Efficiency Solution for Food Manufacturers

Automatically read expiration dates with smartphone photography! Prevent inspection errors during incoming goods and streamline operations.

In food manufacturing, it is necessary to visually confirm items such as "product name," "lot number," "capacity," and "expiration date" upon the arrival of diverse raw materials and components, and to cross-check them with the scheduled arrival data. This task, especially for items without barcodes, requires a significant amount of time and effort, and the reliance on manual visual checks introduces risks such as human errors like incorrect storage and variations in inspection accuracy. Our AI-OCR-based solution for streamlining arrival inspections automatically reads these necessary items simply by taking a photo with a smartphone. It accommodates various labels without format training and prevents inspection errors by cross-referencing the reading results with the scheduled arrival data, thereby reducing work time. 【Usage Scenarios】 - Arrival of items in various packaging forms such as cardboard boxes, one-gallon cans, craft bags, and bottles - Arrival inspections of raw materials and components without barcodes - Visual confirmation tasks for expiration dates, lot numbers, etc. - Cross-checking tasks with scheduled arrival data 【Benefits of Implementation】 - Increased efficiency and reduced time in arrival inspection tasks - Reduction of incorrect storage and inspection errors - Achieving stable inspection accuracy that does not depend on skill level - Improved accuracy in expiration date management

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AI-OCR Arrival Inspection Efficiency Solution for Electronic Devices

AI reads the model number label through smartphone photography to prevent inspection errors.

In the electronics industry, accurate verification of part numbers, lot numbers, and other details is required for the inspection of incoming diverse components and materials. Especially for parts without barcodes, the visual inspection process can be time-consuming and labor-intensive, and there is a risk of human error leading to incorrect inventory entries. Our solution automatically reads necessary information from manufacturer-specific labels using AI, simply by taking a photo with a smartphone. This is expected to improve the efficiency and accuracy of the inspection process. 【Use Cases】 - Inspection of incoming electronic components without barcodes - Automatic reading of part numbers, lot numbers, etc. - Prevention of inspection errors through verification against incoming data 【Benefits of Implementation】 - Reduction in inspection time for incoming goods - Decrease in human errors such as incorrect inventory entries - Standardization of inspection accuracy

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