KPM Analytics Creates OEM Division to Expand AI Vision Inspection in Global Food Processing

KPM Analytics has launched a new business division dedicated to serving original equipment manufacturers (OEMs), aiming to accelerate the integration of AI-driven vision inspection and foreign material detection technologies into food production equipment.
The Westborough, Massachusetts-based company said the initiative will allow it to partner more directly with equipment makers, integrators, and engineering firms across baking, meat and poultry, confectionery, and root crop industries.
KPM’s portfolio includes EyePro System, Sightline Process Control, and Smart Vision Works, brands with more than five decades of combined expertise in inspection technology and 17 years of AI model development for food applications.
“We have become a reference for the industry on vision inspection technology for food production thanks to our longevity and experience in the industry,” said Andrea Bertuolo, Managing Director for Vision Inspection Systems at KPM. “By embedding our inspection systems into OEM equipment, we are helping manufacturers deliver tools that add real value for processors on day one.”
The company’s systems are designed to identify product defects, monitor uniformity, and support compliance with customer specifications. Applications range from product counting on packaging lines to advanced inspection and rejection systems.
“As food manufacturers face mounting demands for quality assurance, operational efficiency, food safety, and transparency, our new OEM business division aims to make our vision-based inspection technologies more accessible than ever,” said Brian Mitchell, KPM’s Chief Executive Officer.
KPM will showcase its technology at the International Baking Industry Expo (IBIE) 2025 in Las Vegas, including a system combining vision inspection with an online near-infrared moisture analyzer.
The company said it is seeking partnerships globally to expand adoption of integrated inspection systems in food production equipment.















