Spyglass connected offerings release AI-driven manufacturing visual inspection solution that minimizes defects, reduces costs

Spyglass Connected Solutions announced on Friday release of Spyglass Visual Inspection that harnesses the power of artificial intelligence, IIoT, and computer image recognition to help manufacturers improve product quality, while reducing the costs associated with defects.

Spyglass is rooted in data and the power of data to help manufacturers gain more insights and make better decisions. Spyglass solutions are unique because they were created specifically to solve the two biggest barriers to AI and IoT adoption for manufacturers: excessive cost and access to infrastructure. Spyglass is a lean approach to AI and IoT – starting small, thinking big, and going fast.

Spyglass Visual Inspection is a rapid time-to-value QA optimization solution for manufacturers of any scale. It is powered by Microsoft Azure and was created to aid manufacturers in accurately detecting manufacturing defects so that action can be taken to reduce waste and improve customer satisfaction; driving continuous quality improvement by enabling greater visibility with a bird’s eye view of product quality across multiple lines or facilities so manufacturers can proactively improve processes; using predictive analytics to improve quality processes and perform root cause analysis, implementing and ramping up quickly ensuring a rapid return on investment, and extending the value of existing industrial vision systems in which manufacturers have already made investments.

Spyglass Visual Inspection uses AI to augment those systems providing greater precision in defect detection and classification. Every manufacturer is different and every defect detection requirement is unique. It’s critical to determine that Spyglass Visual Inspection is the right fit to meet quality goals and match operating conditions.

It starts with a low cost proof of value engagement with Spyglass team to determine unique accuracy requirements and train the machine learning model accordingly. For most customers, the Proof of Value stage can be completed in four weeks or less at a very low cost. Then, the company will operationalize the solution in factories using Spyglass as the platform to implement customized visual inspection solution.

Finally, the company will maintain and Improve the machine learning model. On a quarterly basis, Spyglass will meet with quality teams and help the model learn from any mistakes it has made. In this way, the accuracy will continue to improve over time.

Manufacturers can get started with Spyglass Visual Inspection with a low cost four-week Proof of Value program. During the program, the team at Spyglass determines the unique defect detection accuracy requirements that deliver value to the manufacturer and trains the AI model accordingly. Manufacturers will be able to determine the immediate impact to their product quality initiatives and better understand the potential cost savings to be gained.

“With the launch of Spyglass Visual Inspection, manufacturers can use a lean approach to implementing AI and IIoT technologies so that they can control costs and gain value at every stage,” said Philip Morris, CEO and co-founder of Spyglass. “We believe in the value of starting small, thinking big, and going fast as the path to achieving the most significant return. We are excited to launch Spyglass Visual Inspection, in partnership with Microsoft and our customers, to ensure that manufacturers of all sizes can intelligently minimize defects and reduce costs. Our foundational customer, a global glass manufacturer, will achieve over $1 million dollars in quarterly savings with Spyglass Visual Inspection and Microsoft Azure – that’s a significant impact to the bottom line.”


IoT Innovator Newsletter

Get the latest updates and industry news in your inbox! Enter your email address and name below to be the first to know.