How to Prevent Food Recalls with Computer Vision

Food recalls, often due to undeclared allergens, pose significant health risks and financial losses for manufacturers. In 2024, undeclared allergens accounted for over 34% of all food recalls, primarily caused by labeling errors. Historically, manual checks have been used to prevent these errors, but human fatigue and production speed make them inefficient. The advent of computer vision technology offers a solution by enabling automated, 24/7 monitoring to identify labeling inconsistencies before products leave the factory. The process involves a two-stage verification system using AI models like RF-DETR and Gemini 3 Pro to detect and cross-check ingredient lists against allergen statements. This system reduces the risk of recalls by ensuring accurate labeling, thus enhancing consumer safety and preserving brand trust. Automating the detection and verification process not only improves efficiency but also lowers the likelihood of human error, ultimately preventing costly recalls and protecting consumer health.