Greyparrot

What Greyparrot does

Greyparrot is the leader in AI waste analytics, applying AI to globally scale recycling and save millions of tonnes of waste from landfills and incinerators. By providing deeper, more intelligent insights about waste stream composition and financial value, Greyparrot helps the waste sector recover more value from waste processing lines and reduce the environmental impact of waste. The company’s waste intelligence platform, including Greyparrot Analyzer and Greyparrot Sync (API), reveals real-time insights on over 70 waste categories across seven layers of data, including financial value, brand, and GHG emissions, captured at multiple locations across a recycling facility. In 2023, Greyparrot analysed over 25 billion waste objects helping drive efficiency to save hundreds of thousands, to millions, of dollars per facility – while diverting millions of tonnes of waste. Greyparrot aims to digitise the waste value chain and accelerate the transition to a circular economy, supporting waste professionals, guiding packaging producers, and informing regulators.

Products

• Greyparrot AnalyzerAn AI waste analytics system with hardware mounted above conveyor belts, paired with a cloud portal of dashboards for operations, engineering, and commercial teams. It captures continuous data on every item that passes, including plastics, fibres, metals, glass, and more, across over 111 material categories. It provides real-time insights on material composition, throughput, and purity.
• Greyparrot SyncAn API that connects live Analyzer data into existing hardware and software systems. It enables waste intelligence to drive automation, equipment control, and BI pipelines. It offers both software integrations for recovery facilities (ERP, Power BI, operational tools) and hardware integrations for OEMs and technology partners (sortation, NIR + AI fusion, automated sampling & belt control).
• DeepnestThe world's first packaging waste intelligence platform. It reveals how packaging is sorted in real recovery systems globally, replacing lab models with field evidence. It provides sortability scores by product and benchmarks against category competitors and PPWR/EPR thresholds, helping brands design more recoverable packaging.
• Analyzer PortalThe AI platform built for sorting process optimisation, turning raw data into clear, actionable insights for operations, engineering, quality, and commercial teams. It includes dashboards for Inspection & Alerts, Summary, Alerts, and Flow Map.
• Greyparrot InsightsA data delivery service that filters Greyparrot's data to track packaging from brands taking part in pilot programs, providing insights on a dashboard or exporting to business intelligence platforms.

Key capabilities

• Continuous AI monitoring of every line
• 100% throughput coverage
• Real-time alerts and intervention
• Data-led optimisation
• Automated reporting
• Inspection & Alerts dashboards
• Replace manual sampling for PRO and regulatory reporting
• Sortability scores by product (Deepnest)
• Benchmark against category competitors and PPWR/EPR thresholds (Deepnest)
• 250+ Analyzer units in active deployment
• 65+ materials recovery facilities across 20+ countries
• 111+ material categories in recognition library
• 52bn+ waste objects analysed in 2025 alone
• Hardware mounted above conveyor belts
• Cloud portal of dashboards
• Connects live Analyzer data into existing hardware and software (Sync)
• Packaging waste intelligence platform (Deepnest)
• Live data on material composition
• Review composition down to the minute
• Replay actual line images
• Identify exactly where and when issues happened
• Generate compliance, shift, and supplier reports automatically
• Export reports to Excel, Power BI, or Tableau
• Real-time alerts and line replay for operations
• Inspection dashboard and Materials reports for engineering
• Summary dashboards and scheduled PDF reports for commercial teams
• Minute-level composition across every monitored line
• Virtual Analyzers (combine multiple units)
• Summary view (composition, throughput, value, belt availability)
• Scheduled reports (daily, weekly, end-of-shift)
• Materials reports (CSV export)
• Shift analysis
• Time Labels (custom intervals)
• Threshold alerts (by mass, item count, material category)
• Email and SMS alerts
• Custom KPI dashboards
• Per-belt views
• Whole-plant flow map
• Contaminant flagging
• Yields, purities
• 7 layers of detail (mass, item count, market value, end-use, volume, brand/SKU, GHG emissions)
• 95%+ accuracy in AI recognition
• Software integrations for recovery facilities (ERP, Power BI, operational tools)
• Hardware integrations for OEMs and integration partners (sortation, NIR + AI fusion, automated sampling & belt control)
• Dynamic control for sorting equipment
• Automated sorting capabilities (belt control, drive sortation, dynamic adjustments)

Use cases

• Running a more profitable Materials Recovery Facility (MRF)
• Designing more recoverable packaging
• Continuous AI monitoring of every line in MRFs
• Reacting in real-time to composition shifts
• Making data-backed decisions for engineers
• Reporting with confidence for commercial teams
• Replacing manual sampling for PRO and regulatory reporting
• Improving sortability scores for packaging
• Benchmarking packaging against competitors and regulatory thresholds
• Optimising sorting processes in facilities
• Diagnosing purity drops quickly to save reprocessing fees
• Increasing PET recovery revenue
• Monitoring large volumes of waste with real-time alerts
• Closing the loop on recovered material for recyclers
• Transforming and connecting the plastic value chain
• Automating waste analytics
• Investigating waste composition in detail
• Generating compliance, shift, and supplier reports automatically
• Optimising equipment with evidence
• Assessing supplier batches
• Centralising KPIs across all lines and shifts
• Automating reporting for compliance workflows (PRN submissions, MRF Code of Practice)
• Reducing time-to-decision by embedding waste intelligence into ERP systems
• Driving sortation with robotic arms and air jets
• Combining NIR polymer recognition with AI object identification
• Automating sampling cabins, belt speed, and material routing
• Adapting to changes in feedstock composition
• Purging or recirculating based on available recoverables
• Maximising feed rate without losing purity
• Calibrating equipment through performance feedback loops
• Protecting size-reduction equipment from harmful material
• Responding to flow changes and reducing blockage impact
• Achieving packaging sustainability goals
• Innovating packaging design decisions and material choices
• Informing ESG and EPR Reporting
• Backing up sustainability claims with data
• Tracking packaging from design to disposal
• Assessing true recyclability of packaging
• Comparing individual brands and products in the waste stream
• Flagging priority products that the waste sector struggles to recover
• Redesigning packaging with recyclability in mind
• Prioritising investment in new designs and materials
• Assessing the impact of changes to maximise recovery rates
• Forecasting the impact of scope 3 reporting and extended producer responsibility
• Automating compliance reporting process
• Monitoring sorting machinery performance
• Improving material separation on residue lines
• Conducting rapid process testing and iterative improvement
• Making data-driven decisions on final product blends
• Tracking quality of suppliers' material
• Visualising belt downtime to identify trends and maintain steady throughput
• Using waste data as a sales tool

AI approach

Greyparrot uses AI, specifically computer vision and deep learning, to analyze waste streams in real-time. Their Analyzer units, equipped with cameras, are mounted above conveyor belts in sorting facilities to capture images of waste flows. Their proprietary AI identifies over 111 categories of material and characteristics like mass, brand, and emissions potential with 95%+ accuracy. This data is then used to provide insights through their Analyzer portal and Deepnest platform, as well as to integrate with third-party hardware and software for automation and optimization.

Tech named: computer vision, deep learning, AI, machine vision, machine learning

Industries served

• Waste Management
• Recycling
• Materials Recovery Facilities (MRF)
• Reprocessors
• Brands
• Packaging Producers
• Consumer Packaged Goods (CPG)
• Material Science Companies
• Original Equipment Manufacturers (OEMs)
• Plant Builders
• Technology Partners

What it says sets it apart

• Global leader in AI waste analytics
• Largest waste analytics network in the world
• Continuous AI monitoring with 100% coverage vs. <0.1% manual sampling
• Real-time insights on over 70 waste categories across seven layers of data (financial value, brand, GHG emissions)
• AI is unique in its ability to identify characteristics like mass, brand, emissions potential
• 95%+ accuracy, as precise as a human sorter
• Retrofitting Analyzer Units above conveyor belts
• Deepnest reveals real-world sorting performance of packaging, replacing lab models
• Ability to detect brand and SKU of waste packaging even without labels
• Comprehensive recognition library of 111+ material categories
• Integrated platform with Analyzer, Sync, and Deepnest working together
• Proven financial impact: saving millions of dollars per facility, diverting millions of tonnes of waste
• ISO 27001 and Cyber Essentials certified
• Ability to integrate with existing hardware and software (ERP, Power BI, optical sorters, robotic arms)
• Focus on aligning all stakeholders in the plastic value chain
• Founded by serial tech entrepreneurs with 20+ years of AI experience
• Recognised with multiple awards (TIME's Best Inventions 2025, UK Green Business Awards, TechRound AI 45, BusinessCloud Enviro Tech 50)

Funding rounds we track

From the AI funding tracker — rounds as reported by the linked publications.