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 inspection applications.

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 inspection applications.

"As manufacturers increasingly deploy deep learning to quality inspection, automation solutions like EZ Eye offer an essential competitive advantage," said Ahmed Tawfik, CEO at EZ Automation. "The technology doesn't just accelerate and simplify the training of AI-based machine vision systems, it enhances the accuracy of inspection operations — particularly those tasked with foreign matter detection."

At the core of EZ Eye's efficiency gains is EZ Sift, an algorithmic tool that significantly accelerates the training process for deep learning-based vision systems. Traditional image grading requires human operators to manually sort through extensive image datasets to assign a pass or fail designation to each image. This time-intensive process becomes exponentially more challenging when training systems to detect rare objects that may occur in less than 1% of inspected items.

EZ Sift applies cyclic optimization principles to identify patterns in human grading behavior, allowing the system to automatically categorize similar images and focus human attention on grading novel or ambiguous cases. This intelligent sorting capability has proven particularly effective for small object detection scenarios, where testing has demonstrated the technology's ability to maintain model accuracy above 96% while reducing the time that human operators spend grading by as much as 97%.

EZ Eye distinguishes itself as a comprehensive, technology-agnostic platform that integrates with virtually any machine vision or process control system, enabling enterprise-level integration through PLC communication for real-time status and results exchange.

This flexibility allows the EZ Eye platform to accommodate client-defined tolerances to address inspection applications across a broad range of manufacturing sectors, such as medical device production, food processing, semiconductor fabrication, and pharmaceutical production.

Driven by more stringent regulatory requirements and demand for product traceability, quality assurance operations are showing more interest in AI-based machine vision inspection systems. The EZ Eye platform's ability to perform intelligent automated inspection tasks while generating comprehensive documentation makes it well-suited for regulated industries that require detailed compliance records.

"Manufacturers need integration partners who bring comprehensive toolkits rather than point solutions," added Tawfik. "EZ Eye's strength lies in its purposeful design gaps that - with EZ Automation's collaborative integration expertise - allows users to adapt the technology to the specific demands of any application."

EZ Eye has been successfully deployed in production environments since 2018, when EZ Automation developed the original deep learning-based system for a customer who needed to rapidly deploy a foreign matter inspection solution. The six-month development timeline, achieved before deep learning became widespread in industrial applications, demonstrated the company's capability to deliver advanced solutions quickly.

EZ Automation will be exhibiting at booth 310 during the ISA Automation Summit and Expo in Lake Buena Vista, Florida, October 5-7, 2025.