EZ Eye Delivers Fast, Highly Accurate Deep Learning Solution for Inspection of Transparent Medical Components

When a leading medical device manufacturer sought to leverage deep learning in its inspection of transparent medical components, EZ Automation offered a quickly deployed, highly accurate automated vision inspection system.   The Problem  Medical device manufacturers have long relied on machine vision for quality assurance. But traditional rules-based vision systems do not adapt well to environmental...

EZ Automation Improves Yield, Reduces Waste at Production Speeds for Medical Component Manufacturer 

When a global manufacturer of transparent medical components needed to reduce waste from false rejects while improving defect detection rates, EZ Automation’s EZ Eye platform delivered production-speed inspection that dramatically improved both quality and efficiency.    The Problem  A leading global manufacturer of transparent medical components confronted a dual challenge in its quality assurance operations:...

Beyond the Hype: Why Traditional Machine Vision Still Outperforms VLMs in Industrial Inspection

In the race toward AI-powered automation, vision-language models (VLMs) are gaining attention for their ability to interpret images using natural language prompts. However, when it comes to industrial inspection systems, not every cutting-edge model translates into real-world reliability. At EZ Automation Systems, our experience shows that traditional rule-based and deep learning inspection systems—when properly designed...

EZ Automation Platform Accelerates AI-Training for Machine Vision Inspection Applications as Demand for Automated Quality Control Solutions Grows

Jacksonville, Fla., October 2, 2025—EZ Automation, a leader in advanced automation, introduced the latest benchmark for the efficiency gains that its EZ Eye automated inspection can deliver for quality assurance operations. Analysis of customer project data showed that EZ Eye enabled a 55% reduction in the work hours required to train deep-learning systems for challenging...