The company’s solution uses AI image processing to monitor production lines for defects

Scarlett Evans, Assistant Editor, IoT World Today

February 15, 2023

1 Min Read

Predictive maintenance group Razor Labs has received an order worth $1.9 million for its autonomous product-monitoring solution, following the success of initial tests.

The solution automatically detects and classifies various product defects during the production process, using CCTV-based visual inspection technology and AI image processing to rapidly scan and monitor production lines for anomalies.

"We are proud to have hit this significant milestone ahead of the planned timeline and have proven the ability of our solutions to decrease operational costs and improve productivity and safety of the staff,” said Raz Roditti, Razor Labs CEO. “We remain committed to driving innovation and growth while providing our customers with the most advanced and reliable solutions available in the asset-intensive market."

The announcement follows news that the company signed a Memorandum of Understanding with an undisclosed global defense company in May last year. The deal is set to take place over 18 months, with Razor Labs providing four AI systems to automatically detect and classify a range of ammunition defects at the production stage. 

"This milestone is a testament to the growing trust and satisfaction of our customers in the solutions provided by Razor Labs, particularly as the market shifts towards increased automation and the adoption of the Industrial Internet of Things (IIOT),” said Tomer Srulevich, Razor Labs CBO. “The success of our solutions has been demonstrated by the increased operational efficiency, heightened staff safety, and decreased costs - all essential factors that resulted in achieving this milestone."

About the Author(s)

Scarlett Evans

Assistant Editor, IoT World Today

Scarlett Evans is the assistant editor for IoT World Today, with a particular focus on robotics and smart city technologies. Scarlett has previous experience in minerals and resources with Mine Australia, Mine Technology and Power Technology. She joined Informa in April 2022.

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