As manufacturing demands increase, integrating AI-powered visual systems into quality inspection processes becomes increasingly beneficial. While traditional inspection methods have been the cornerstone of quality control in manufacturing, they come with limitations such as subjectivity, fatigue, and scalability challenges. AI-powered visual inspection systems address these issues. Leveraging advanced algorithms and machine‑learning models, they analyze images with high accuracy, identifying defects that may be invisible to the human eye.  This not only enhances the reliability of quality assessments but also increases operational efficiency, allowing manufacturers to streamline their processes and reduce costs.  The capability to detect anomalies in real-time empowers companies to address issues before they escalate, ensuring that only the highest-quality components progress through production. To find out more about the application of Visual AI Inspection in manufacturing, I recently sat down with Priyansha Bagaria who is the Founder and CEO of Loopr AI.