Enhance Product Safety with AI and Web 3.0 Technologies

Merck and Zebra Technologies collaborate to improve product verification, authenticity, and traceability through advanced digital solutions. Their joint initiative, M-Trust™, is the first cyber-physical trust platform integrating mobile scanning and Web 3.0 cryptographic security to combat counterfeiting and ensure data integrity in AI systems. The partnership combines Merck’s authentication expertise with Zebra’s mobile computing and asset visibility capabilities, aiming to enhance supply chain security and AI model reliability.

The first product from this collaboration is a handheld scanner, built on Zebra’s TC58 mobile computer, designed to securely verify products and integrate seamlessly with the M-Trust™ platform. A prototype will be showcased at Hannover Messe 2025.

M-Trust™ is like a digital fingerprinting system for products. It creates a secure digital record of each item, linking physical products to their digital identity. The handheld scanner is a special mobile computer with a built-in authenticity checker. The scanner reads security features like barcodes, embedded pigments, or unique product markers, it instantly checks the product’s digital record in M-Trust™ to confirm if it is real or fake. The scanned data is securely stored and shared via Wi-Fi 6E or 5G, keeping supply chains transparent and safe.

The aim of the compananies is to stops counterfeits and track products easily, so companies can trace products across the supply chain. In short, this scanner + M-Trust™ combo helps businesses and consumers trust what they buy, sell, and use in a digital, AI-powered world.

Powered by Web 3.0 technology, the M-Trust™ platform is designed to adapt to evolving technologies and regulatory requirements, such as the EU Digital Product Passport, empowering businesses to thrive in a rapidly changing landscape and remain competitive and trustworthy to consumers and regulators.

The collaboration will also offer organizations high quality data for training and testing AI models, enhancing analytics capabilities as AI solutions are operationalized.