Greyparrot raised $27 million in Series B funding on July 28, 2026, in a round led by technology investor Omar Mir. The London company plans to expand its AI waste-intelligence systems in North America and Europe, grow its AI, data science, and product teams, and scale toward its stated goal of helping abate more than one million tonnes of waste by 2030.
Greyparrot announced a $27 million Series B round on July 28, 2026, led by technology investor Omar Mir. The London company builds camera-based systems that measure material moving through recycling facilities and plans to use the financing to expand in North America and Europe while adding staff across AI, data science, and product development.
Measuring what moves through a recycling line
Greyparrot Analyzer places machine-vision cameras above sorting belts and classifies materials, products, and brands in real time. The company says its systems operate in more than 20 countries and have recorded more than one trillion object detections. Waste operators use that continuous view to adjust sorting, monitor material quality, document compliance, and identify valuable material that would otherwise be lost in residue streams.
The same dataset also supports Greyparrot's Deepnest platform, which gives packaging companies information about how products behave after disposal. Greyparrot names customers and users across both sides of the market, including waste operators and consumer-goods companies, but the July announcement does not provide audited portfolio-wide performance data.
What the new capital is meant to fund
Greyparrot says the round will support geographic expansion and product development as recycling operators face more complex packaging and stricter reporting requirements. Its stated 2030 objective is to help abate more than one million tonnes of waste. The company also estimates that the materials observed across its detection network represent $2.5 billion in potential recoverable value. Both figures are company estimates and should be treated as targets or modeled opportunity, not realized results.
For data and operations teams, the significance is less about replacing sorting equipment than adding a measurement layer to existing plants. Continuous object-level data can make recovery losses visible and create feedback loops for process changes, packaging design, and regulatory reporting. The financing signals investor interest in applying computer vision to physical industrial workflows, but future evidence should focus on independently verified recovery gains, deployment economics, and whether the system maintains classification quality across facilities with different waste streams.
Key Points #
- 1Greyparrot raised $27 million in Series B funding led by technology investor Omar Mir and plans to expand in North America and Europe.
- 2Its Analyzer systems use cameras and AI above recycling belts; the company reports deployments in more than 20 countries and over one trillion object detections.
- 3The company will grow its AI, data science, and product teams and is targeting more than one million tonnes of waste abatement by 2030.
- 4Operational value depends on independently verified recovery gains, classification quality, and deployment economics across different facilities.
Scoring Rationale #
The $27 million round supports practical computer-vision deployment in a large physical industry and gives the company resources to expand internationally. Impact is moderated because waste-abatement, recoverable-value, and performance figures are company targets or estimates without independent portfolio-wide validation.
Sources #
Primary source and supporting public references used for this report.
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