FAQ's

Deepnest is Greyparrot’s packaging waste intelligence platform for brands, retailers and packaging producers. It helps producers measure their packaging’s real-world recoverability, and make data-driven improvements that balance recycling rates with brand goals.

Deepnest is the world’s first packaging waste intelligence platform. It provides packaging teams at CPG companies with their first large-scale insight into the post-consumption journey of their products. The platform aggregates packaging waste data from Greyparrot’s fleet of 200+ Analyzer units, which are installed in recovery facilities across 20+ countries.

Those units detected over 52 billion objects in 2025, accurately identifying and tracing branded products.

Deepnest is the first platform to offer brands full visibility into their packaging's performance as it passes through realthe sorting and recycling systems. It opens the “black box” of packaging's post-consumption journey, with billion-dollar implications for brands using it to improve recyclability and reduce regulatory risks.
 

We designed Deepnest for consumer packaged goods (CPG) brands, retailers and packaging producers track their products in global waste systems.

While initial partners are large brands, Deepnest is designed to scale and can provide insights for most mid- to large CPG and packaging providers looking to improve packaging sustainability and performance.
 

Packaging waste intelligence is actionable insight into packaging's destination beyond the bin.

Deepnest uses detailed waste data to track the post-consumption journey of consumer packaged goods, surfacing the insights that brands need to design sustainable, compliance-ready packaging.

Deepnest is differentiated by scale, accuracy, and ease of adoption. No other platform provides real-time, global insight into packaging recovery directly from waste processing streams.

As the first AI-powered packaging waste intelligence platform, Deepnest is the only solution that does not rely on packaging modifications like digital watermarks or RFID tags.

No other platform has aggregated packaging waste data at this scale. Greyparrot has gathered the world’s most comprehensive packaging waste database, revealing how products actually perform over time. Unlike one-off

tests or hypothetical models, it provides an active feedback loop from real facilities, and can account for regional differences in recovery rates.

The data and insights on the Deepnest platform come from our global network of Greyparrot Analyzer units. The Analyzer system uses computer vision AI to identify more than 50 billion waste objects each year, identifying each item’s brand, material, function and more.

Deepnest AI can currently detect 2000+ products and 70 material classes. The system can identify branded objects without alterations like watermarks, barcodes or RFID.

Whenever a new brand is onboarded, Greyparrot’s machine learning engineers train the system to recognise in-scope products with 95+% accuracy.

Analyzer units are currently active in 12 UK facilities, giving us around 12% coverage of UK recovery streams.

In the EU …

In the USA …

Globally …

• Benchmark sortability against competitors and industry averages

• Determine circular design best practices backed by data
• Compare packaging formats within sub-brands
• Identify recyclability challenges in priority markets
• Quantify the impact of R&D and packaging changes
• Model the impact of waste regulation and ensure packaging is compliant

Deepnest data frequently reveals that intent is often misaligned with sorting reality. Even products designed with materials and formats that are technically recyclable are often not recovered in reality.

Part of the challenge is the lack of data-backed best practices for brands and retailers. Until now, packaging teams have lacked visibility into the performance of materials and formats in real waste systems. Deepnest is changing that.

Brands use Deepnest to understand their current exposure to waste regulation, and respond with design improvements that lead to measurable recovery. Each customer’s requirements are different, but most users follow a basic path to data-driven design:

1. Deepnest’s AI identifies in-scope products as they pass through relevant facilities, tracing each SKU’s recovery journey.

2. Brands use recoverability benchmarks to prioritise design improvements, targeting the packaging that most exposes them to regulatory fees.

3. Packaging teams use Deepnest’s database to compare the sortability of different materials and formats in global or local facilities – identifying the design choices that will translate to higher recovery rates, and comparing their recovery rates to the wider landscape.

With that said, Deepnest is more than a data platform – Greyparrot’s team of analysts and waste experts collaborate with producers to understand the implications of every insight.

While it’s too early to estimate exact savings from Deepnest, we know that CPGs already spend millions of dollars on sustainable innovation.

The top 20 CPG companies spend nearly $25B annually on R&D alone, which includes machinery, tooling, packaging materials, and product raw materials. Out of that $25B, there is a significant amount of money dedicated to sustainable innovation.

On top of that, there are additional budgets for sustainability, CSR, and marketing linked to sustainability efforts.

P&G spends $2B, and Reckitt spends $337M each year on R&D. This demonstrates a strong existing financial commitment to innovation and sustainability, and an opportunity to replace guesswork with data-backed business cases for innovation.

2040, virgin plastic packaging will represent around $100B in projected regulatory exposure.

Brands need accurate data to ensure their packaging complies with EPR (Extended Producer Responsibility) in the USA and UK, and the Packaging, Packaging Waste Regulation (PPWR) in the EU, ESG disclosure, and sustainability targets.

Deepnest makes it possible to model current exposure to regulatory fees, back sustainability claims with concrete data, and prove the impact of circular design improvements.

Deepnest has revealed that seemingly minor differences in colour, format and design features can completely change packaging’s fate. Greyparrot’s team have already identified that small factors like label size and plastic colour are strong determinants of recoverability:

• In one UK facility, clear PET recovery was close to 95%. For some coloured PET products, it was as low as 15%.

• Comparing HDPE bottles from two brands revealed that bottles with label sleeves were recovered just 16% of the time, while those without saw 67% recovery rates. A minor adjustment could boost recovery by a massive 51%

Early data has also revealed that the shape and mass of some products can “confuse” ballistic separators, particularly when separating fibre-based composites from plastics:

• Despite being made of materials that are all individually recyclable, composite packaging is also frequently lost to landfills and incinerators. Today’s sorting systems are optimised to recover pure streams of material, rather than to chemically separate plastic and metal linings from fibre-based products. As a result, all of those materials are frequently lost.