AI-powered waste intelligence company Greyparrot has partnered with consumer health company Kenvue to improve global recycling for its brand packaging in commercial-scale sorting facilities.
Using Greyparrot’s Deepnest platform, Kenvue aims to transition from theoretical design-for-recycling models to evidence-based data derived from real-world recycling environments. As regulatory frameworks like the EU’s Packaging and Packaging Waste Regulation (PPWR) and Extended Producer Responsibility (EPR) tighten, Kenvue hopes to validate the performance of its packaging in sorting facilities.
Greyparrot says its Deepnest technology provides Kenvue with a digital twin of real-world recycling systems, utilizing AI-driven recognition to capture data on how products behave in operational recycling facilities across the U.K. and U.S; pinpoint how components such as pumps or labels impact detection and recovery rates; and forecast the financial impact of EPR on design changes such as adjusting translucency or switching material types before physical prototypes are manufactured.
Other industry players utilizing Greyparrot’s technology include L’Oréal Groupe, Unilever and McDonald’s.
At the start of the year PepsiCo announced a multi-year collaboration with Siemens and NVIDIA, aiming to apply digital twins and AI technology to reshape how its plant and warehousing facilities are digitally simulated and tested, with early pilots underway in the U.S. PepsiCo is using Siemens’ Digital Twin Composer which enables industrial companies to combine 2D and 3D digital twin data from Siemens’ digital twin and physical real-time information from a managed, real-time photorealistic virtual scene accelerated by NVIDIA Omniverse libraries.
In our latest edition of the Brief, we report on how intelligent sorting technologies including digital watermarking, AI-driven analytics and advanced sensor systems are emerging as critical tools to meet demand for the recycling industry to deliver higher-quality recyclate, better traceability, and improved circularity. We examine recent advances in the field and the enabling conditions required to scale these technologies to the levels needed to meet regulatory demands.
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