reverse.fashion raises fresh capital for AI textile sorting
reverse.fashion is combining computer vision, machine learning and sensing to automate the difficult sorting step behind textile reuse and recycling.
Circular fashion has a physical bottleneck: used garments are highly varied and expensive to sort at scale.
What happened
Berlin startup reverse.fashion secured a seven-figure extension to its pre-seed round from High-Tech Gründerfonds.
The company combines computer vision, machine learning, advanced sensing and Digital Product Passport integration to classify used garments by attributes including condition, brand, style, size and material composition.
Items can then be routed toward reuse, repair, resale, upcycling or recycling.
Why it matters
Textile circularity depends on sorting quality.
When garments are inspected manually, throughput is limited and valuable items can be routed into lower-value recycling streams. Better classification can improve both recovery economics and the proportion of clothing kept at its highest possible value.
The new capital supports commercial rollout of the company’s software and automated sorting system.
The bigger picture
Climate tech increasingly involves applying AI to messy physical industries.
Textiles are a strong example because circularity requires more than consumer resale apps. It also needs industrial infrastructure that can identify, separate and route millions of heterogeneous products. reverse.fashion is building that layer.