Anomaly Detection using Vision
Leverage advanced computer vision technology to identify unusual patterns in real-time, ensuring quick detection and response to potential issues.
Manufacturing Line Defect Detection
Our models employ the latest machine learning algorithms to analyze real-time data in a production line, like images or videos captured by cameras, to predict the likelihood of defects occurring on a product, allowing for early intervention and quality control measures to be taken before a defective product is fully manufactured. Our models also provide capability for real-time defect rejection for defective products.
Egg Grade Quality
Our AI models analyze images of eggs and automatically classify them into different quality grades (like Grade AA, Grade A, and Grade B) based on visual characteristics like shell condition, yolk position, and albumen consistency, essentially automating the egg grading process.
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Bottle Cap Mfg Line
Our AI models use latest computer vision AI algorithms to detect defects in bottle caps by analyzing images captured on the production line, identifying issues like misaligned caps, missing caps, improper sealing, color variations, dents, scratches, or incorrect printing, allowing for real-time quality control and removal of faulty caps before they reach the consumer.
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Fault Detection
Our AI models identify trained classes of anomalies or defects in a production line by analyzing data from sensors and cameras, allowing for early intervention and quality control by automatically detecting issues as they occur.