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.

Data Capture

Capture industrial/deadstock (unsold, returns, overruns) and post-consumer (donations, rejects, export bales) inflows in a 1–2 minute prompt-led flow—log item, condition, images—and convert them into structured, decision-ready data.

AI Classification

Train classification logic on community-tagged data to recognise standardised apparel signals (type, fibre clues, condition, trims) and output confidence + flags for each item or lot—ready for routing at scale.

Actionable Routing

Outputs drive acceptance guides, pricing inputs, and compliance-ready traceability, so operators route materials to their highest-value next use faster, with lower storage/write-offs and higher value recovery.