How Greyparrot’s Deepnest is turning post-consumption reality into packaging intelligence

From waste analytics to packaging intelligence

Greyparrot was founded six years ago with a mission to turn waste from an operational cost into a recoverable resource and accelerate the transition to a circular economy. Built by a team with deep roots in AI and decades of experience deploying computer vision systems globally, the company developed AI-powered Analyzer units – camera hardware installed above sorting lines that observe and classify every item moving through a facility.

“The way I frame it,” says Yaseed, “is that facilities have eyes, brains and limbs. We’re the eyes and brains – observing every object, and identifying what each item actually is.”

Greyparrot’s technology has helped waste operators across 20 countries understand loss points, material leakage and operational inefficiencies at unprecedented scale. In 2025 alone, Greyparrot’s AI analysed 43.5 billion individual packaging items moving through real sorting plants – creating what is arguably largest dataset of packaging recoverability in existence. Deepnest sharpens that focus for brands, identifying specific products down to the SKU level.  

The simple question which sparked Deepnest’s development was: if AI can identify polymers, shapes and materials, can it also recognise specific products and the brands behind them? Not via logos alone, but through the full visual fingerprint of packaging – colour, geometry, texture, and format.

“The model works like face recognition on your phone,” Yaseed explains. “It clusters what it sees and asks, ‘Who is this?’ Then we label it.”

That capability transforms waste data into something far more powerful: packaging waste intelligence.

Designing from reality, not assumptions

For consumer brands navigating EPR and PPWR (and preparing for modulated fees), Deepnest arrives at a critical moment. Regulation has moved from abstract policy to material financial pressure, and many of the assumptions underpinning recyclability no longer hold up under real-world scrutiny.

“There are design-for-recyclability standards, and they’re not wrong,” says Yaseed. “But brands can’t just adopt them wholesale. If everyone uses the same materials, colours and formats, everything looks the same. Brand visibility collapses. It’s a balancing act.”

Deepnest is designed to support that balance, not by prescribing a single “correct” solution, but by revealing how specific design choices behave across markets, facilities, and infrastructures.

The platform’s first core capability is baseline performance: measuring where products end up, whether they are correctly sorted, misidentified, or lost to residue. Across billions of observations, the worst performers are often formats that brands already suspect, but have struggled to quantify. Black plastics, metallised films, EPS, and low-grade fibres are difficult to sort, while clear PET bottles, white dairy tubs, corrugated board, and aluminium consistently deliver high capture rates and clean material streams. But the real value emerges when brands begin to model change.

“We can say, if you make this colour change, this is what will happen,” Yaseed explains. “If you adjust opacity, pigment or format, this is how it’s likely to behave, because we’re modelling it against a wide, real dataset.”

That ability reframes packaging development from trial-and-error to an informed roadmap. With 2030 targets looming and packaging decisions often locked in years in advance, predictive insight becomes essential rather than optional. In categories like health and personal care – where sachets, pumps, tubes and shrink-wrapped formats dominate – Greyparrot’s work with leading brands shows that many ‘recyclable’ designs underperform once they hit the sorting line, placing significant portions of today’s portfolios on course for the red end of modulated fee scales in 2026.

“Mould choices can take two years. Pigments can take six months,” Yaseed notes. “If you’re working towards 2030, you need to be making decisions now.”