With the festive season fast approaching, what better way to celebrate than with a Christmas-themed use case? This time, we explore quality inspection of Christmas chocolate boxes—specifically focusing on completeness inspection. In...

Deep learning for railway safety inspections? We recently tackled an unconventional use case—automating the inspection of locks and latches on slowly moving railway carriages!

Explore how PEKAT VISION's Anomaly Detector streamlines packaging inspection in meat production, detecting foreign contaminants like foil or paper and ensuring the highest quality before sealing. Learn more about its speed, accuracy, and flexibility for food inspection.

PEKAT VISION’s AI solution streamlines cup cleanliness inspection for reusable drinkware, detecting defects and contamination, ensuring quality at festivals around Europe.

Discover how PEKAT VISION's deep-learning software helped a leading pasta manufacturer achieve precise quality inspection, ensuring perfect pasta length with a fast, scalable solution tailored to high-speed production lines.

Learn how Machine Vision Consulting Srl used PEKAT VISION’s Classifier module to automate plant selection. The system inspects each plant’s health and density, offering consistent quality assessment at scale.

Recently we helped Arimation Robotics to develop a deep learning-based solution to rapidly sort over 6,000 PCB bords into 20 categories based on precious metal content, a task that was impossible for human operators due to the sheer volume and complexity.

Learn how PEKAT VISION helped a textile manufacturer overcome challenges in detecting defects on large-scale materials using the Anomaly Detection module and custom preprocessing.

See how PEKAT VISION ensures cleanliness of plastic boxes in the production of plastic toys, identifying and classifying various contaminants and anomalies.

Explore how NIR illumination enhances contrast between objects and penetrates certain materials, allowing us to 'see through' layers, and proving invaluable in scenarios where traditional lighting methods fall short.