- Detection of the subtlety and variability of possible defects as well as variation in acceptable appearance
- Achieving a level of quality that cannot be matched by other types of visual inspection
Identify visual imperfections on a large quantity of small, curved objects.
Unrivaled reliability in detecting cosmetic defects
Top quality guarantee
Our AI-powered solutions reliably inspect these delicate products to spot even the most subtle cosmetic defects, such as dents or scratches. This ensures that only impeccable products reach your customers, building their trust in your quality and loyalty to your brand.
Reduced risk of defective products
By preventing defective products from reaching your customers, you significantly reduce the risk of returns, complaints or customer dissatisfaction. This allows you to maintain a strong reputation and lower returns management costs.
Unrivaled level of quality
With our classification tool trained on a set of images showing intact and damaged products, you can guarantee an exceptional level of quality. Your customers receive products without any imperfections, which reinforces their satisfaction and loyalty to your brand.
3D inspection of finished product and packaging
Defect detection and surface validation Identification of cakes, individual cakes, candies and cookies Checking the height of the icing Checking volume and flatness
Quality inspection of chocolate boxes
Compliance with strict standards Identification of physical defects Identification of irregularities
Automated Meat and Poultry Inspection
Accuracy during visual classification of already packaged meat Visual identification of plastic or polystyrene foam Rapid detection of physical contamination elements
Foreign body detection
Intervention of contamination and foreign bodies, e.g. air pockets, dust, particles, hairs, etc. Defect detection in high-speed production environments Locate, analyze and classify complex contamination issues in real-time to prevent contact of contaminants in the supply chain on high-volume lines
Inspection and sorting of nuts
Distinction between acceptable forms and unacceptable states Rapid classification of nuts as acceptable or unacceptable Neither manual inspection nor other forms of machine vision can achieve the same speed and accuracy in this task
Inspection of coffee beans
Identification of batches of grains confirmed before their inventory Verification of detection of physical contaminants, such as plant matter, stones, etc. Acceptance of variation in overall differences between coffee bean varieties
Detect volume and portion errors to maximize yield and reduce waste Measuring the volume of food products during assembly to check portion size
Verification of product uniformity
Identification of packet patterns and stamps, despite changes in orientation, angle, lighting, etc. Rejection of damaged and broken products before packaging or distribution