Novolyze EMP Adds Predictive Insight, Machine Learning to Boost Food Safety

Better compliance, outbreak forecasting, and prediction of pathogens such as listeria or salmonella

Published: Monday, May 15, 2023 - 12:01

(Novolyze: Washington, D.C.) -- Novolyze, a leader in food safety solutions and quality digitization technology, has upgraded its environmental monitoring program (EMP) to include advanced predictive analytics and machine learning. This latest upgrade will enable Novolyze’s technology to automatically generate trend charts and digital “heat” maps using digital data. This, in turn, will lead to better outbreak forecasting and prediction of pathogens such as listeria or salmonella, which have surged in recent months.

An EMP is a crucial tool for food and beverage manufacturers to maintain food safety and quality, especially for ready-to-eat (RTE) foods. Those are foods that require no further cooking or processing before consumption. As such, they are at higher risk of contamination by foodborne pathogens.

Novolyze’s EMP has always been a critical tool for ensuring food safety and compliance. By testing the environment, including surfaces and equipment, the EMP helps manufacturers identify potential contamination risks and take appropriate corrective action to remove the risk. With the new upgrade, Novolyze’s EMP is even more robust, providing manufacturers with real-time predictive analytics that enable them to stay one step ahead of potential foodborne illness outbreaks.

“We are committed to providing the latest technology and solutions to help the food industry reduce risk and maintain the highest levels of food safety,” says Novolyze CEO Karim-Franck Khinouche. “With this latest upgrade, our EMP is more powerful than ever, and we are excited to continue helping our customers keep their food safe.”

The use of predictive insight in an EMP can help food and beverage manufacturers identify potential areas of contamination before they become a problem. By collecting and analyzing data on environmental conditions, such as temperature, humidity, and sanitation practices, manufacturers can develop models to predict where and when potential contamination events may occur. This allows them to take proactive measures to prevent contamination, rather than waiting for a problem to arise and then reacting to it.

For example, if manufacturers use predictive models to identify specific areas in the facility that are at a higher contamination risk, they can take steps to increase sanitation measures in that area or adjust production processes to reduce that risk. By doing so, they can prevent potential food safety issues and ensure that the RTE foods they produce are safe for consumption. Novolyze’s EMP can support these efforts.

Additionally, the use of predictive insight in an EMP can also help improve product quality. By monitoring and analyzing data on environmental conditions, manufacturers can identify and address issues that may affect the quality of the product, such as changes in temperature or humidity. This can help ensure that the products are of consistent quality and meet the expectations of consumers.

“Novolyze’s EMP is particularly relevant in the current climate, with foodborne illness outbreaks becoming far too common,” says Khinouche. “By utilizing the latest technology, including predictive analytics and machine learning, Novolyze’s EMP is helping to cut down on food safety and quality control issues, enabling manufacturers to maintain the highest levels of food safety and ensuring that consumers can trust the foods they eat.”

For more information, visit novolyze.com.

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