P&P Optica develops and sells a patented Smart Imaging System that uses hyperspectral imaging to capture chemical signatures of food products at line speed. The system provides real-time quality metrics such as fat/lean ratio, tenderness, protein/water/fat content, and can detect muscle myopathies like woody breast and other product flaws. Its imaging also identifies a broad range of foreign-material contaminants—including rubber, cardboard, clear plastics and bone—that are often missed by x-rays and metal detectors. Using machine learning and AI, PPO’s software learns from inspection data over time to identify new contaminants and deliver sophisticated trend analysis and actionable insights to processors. Proceeds from the Series B will be used to accelerate implementation of PPO’s detection systems in food processing plants across Canada and the US and to expand development of the company’s advanced software and AI-based insights. PPO is based in Waterloo, Ontario, and emphasizes reducing food waste, increasing food safety, and improving supply-chain sustainability. P&P Optica has built a patented Smart Imaging System that uses hyperspectral (chemical) imaging combined with machine learning and artificial intelligence to inspect food on production lines. The system is designed to detect and identify foreign objects such as plastics, rubber, metal and paper in-line at line speeds while also providing analytics on shelf life, composition, flavour, fat content and quality variation. PPO positions its solution as a complete, real-time approach to detect, grade and sort food to improve safety and reduce waste. The company announced a $3.1 million funding round to advance system development and deployment in the food processing industry. The financing was announced as a partnership with Fulcrum Global Capital, which the article describes as an early-stage VC focused on agtech and food-production technologies. The announcement was issued from Waterloo, Ontario.

Total raised

$3M

Funding rounds

2

Latest round

Equity

Latest activity

Jun 2018