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Innovation | Converte Global
AI-Powered Circular Infrastructure
We’re developing a data-first system that converts industrial deadstock and post-consumer apparel inflows into decision-ready data, then scales sorting with AI-assisted classification and at-scale category routing.
The outcome: bankable stock, new revenue streams, and measurable jobs, growth and opportunity for women and youth.
UK company · SEIS/EIS approved.
Building the routing OS for apparel waste
Communities capture standardised item and condition data at source, creating the training foundation for AI-assisted image classification that will determine category routing at scale.
Operators use the shared baseline to accelerate sorting, reduce waste and write-offs, increase value recovery from “dead” stock, and generate a clear, DPP-like audit record, unlocking jobs and entrepreneurial opportunities in the process
What We Do
We turn uncatalogued inflows into reliable outputs by combining community/partner data capture, AI-assisted classification, and actionable category routing across industrial deadstock and post-consumer streams.

What makes us different
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First-mover in apparel-waste classification (routing OS)
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Community-powered dataset (women & youth) = defensible moat
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DPP/EPR-ready traceability + ESG reporting
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Scalable across the Global South and West

Roadmap
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M0–6: Dataset MVP (community capture + labelling)
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M6–12: Model prototype (target ≥80% in scoped tasks)
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M12–24: Pilot sorting (target ≥90% in defined categories)
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M24–36: Scale deployments (tools/API + reporting)

Pilot KPIs
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Sort time per item ↓
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Classification accuracy ↑
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Routing yield ↑
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Unnecessary transport ↓
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Sell-through / value recovery ↑
Note: KPI mix is tailored to operator workflows & compliance; baselines set at pilot start.
