Collaboration will help Kenvue validate its packaging performance
Greyparrot, the leader in AI-powered waste intelligence, today announced a strategic collaboration with Kenvue, the world's largest pure-play consumer health company, to advance circularity across its global packaging portfolio.
By leveraging Greyparrot's Deepnest platform, Kenvue will 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, the ability to track actual recyclability has shifted from an aspirational effort to a financial and operational necessity. This partnership is aimed at empowering to validate the performance of its iconic brand packaging inside commercial-scale sorting facilities.
Bridging the Gap Between Design and Recovery
While many packaging formats are technically "recyclable" by design, their actual recovery rate is often hindered by variables such as component materials or regional infrastructure variations. Deepnest provides Kenvue with a digital twin of real-world recycling systems utilizing AI-driven recognition to:
- Quantify Sortation and Processability Performance: Capture real-world data on how products behave in operational recycling facilities across the U.K. and U.S.
- Identify Design Optimization: Pinpoint how specific components, such as pumps or labels, impact detection and recovery rates.
- Model "What-If" Scenarios: Forecast the financial impact of EPR on design changes such as adjusting translucency or switching material types before physical prototypes are manufactured.
A Growing Force in Global CPG
The collaboration with Kenvue marks a significant milestone in Greyparrot's mission to provide the waste intelligence layer for the circular economy. Kenvue joins an elite ecosystem of industry leaders utilizing Greyparrot technology, including L'Oréal Groupe, Unilever, McDonald's, and more.
"To help achieve our circular packaging goals, we must move beyond aspirational guidelines and embrace real-world evidence. Our partnership with Greyparrot and the integration of Deepnest represents a fundamental shift in how we approach sustainable packaging. AI-driven waste intelligence allows us to go beyond simple tracking and into advanced scenario modeling, helping us identify the most impactful design changes and implement innovative solutions across our global portfolio faster and more cost-effectively than ever before."
David Lickstein, Global Head, Packaging Innovation, Sustainability, and Experience, Kenvue
"Circular packaging is no longer an aspiration, it is fast becoming the standard. We're proud to partner with Kenvue to turn design intent into measurable impact, helping set a new benchmark for how the industry designs, measures and delivers circularity."
Ambarish Mitra, Co-founder, Greyparrot
"Data is the ultimate catalyst for change in the sustainable packaging landscape, and AI has provided the means to deliver those insights at a truly global scale. This collaboration with Kenvue represents a significant step beyond waste tracking; it's about utilizing Deepnest's predictive capabilities to model real-world recovery scenarios. By doing so, we are empowering Kenvue to make actionable, data-led design changes quicker and more cost-effectively than ever before, accelerating the transition to a truly circular economy."
Yaseed Chaumoo, Managing Director of Deepnest by Greyparrot
About Greyparrot
Greyparrot is the pioneer of AI-powered waste intelligence, providing the data needed to transition to a circular economy. Its Deepnest platform analyzes waste directly inside recycling facilities, providing brands, waste managers, and regulators with the evidence-based data required to improve recovery rates, meet compliance standards, and design out waste.
View source version on businesswire.com: https://www.businesswire.com/news/home/20260520484514/en/
Contacts:
Media Contact:
Tsai-Ni Ku
PRforGreyparrot@Bospar.com



