Labeling Verification: AI-Powered Quality Inspection

Use
‍cases

Label failures can be cosmetic or functional. The Elementary system can catch detect and track either type of failure to improve labeling processes.

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Positioning and Quality

Verify that product labels are correctly placed and free of common defects such as wrinkles, peeling, tears, or bubbles.

Text and Date Time Codes

Read product names, ingredients lists, and date-time codes to verify that products are accurately labeled, with no training required.

Barcodes

Scan barcodes of all common types (UPC, QR, and more) to verify that the product matches the label.

Key features
and benefits

Elementary's AI-driven inspection system empowers your production line and create tangible benefits for your business, from increased accuracy to significant cost savings.

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Traceability

Complex supply chains often result in companies pointing the finger at each other when quality issues arise - having the data on hand can quickly end the debate.

AI for Difficult Defects

Find the most difficult defects such as small scratches or marks that can vary in size, orientation, intensity, or location.

Multi camera Inspection

Use multiple cameras to capture all sides of parts and automatically correlate inspection results to accurately count good and bad parts.

Easy Setup & Scale

Quickly capture, label, train, and deploy models within the application.

Quick Corrective Action

Defect classification provides users the ability to go beyond Pass-Fail and take corrective actions specific to the issue they are observing.

Out-of-the-Box Analytics

Elementary provides users with the ability to look back at historical data to understand product yield and scrutinize defects in a specific time period.

Incident Alerts

Quality Events alert users with notification when urgent issues arise enabling manufacturers to more quickly escalate and address issues.