Matoha makes technology powered by NIR sensing and AI that helps businesses with textile waste sorting, grading and fibre sensing at affordable costs.
Matoha has now sold over 900 material identification and sorting solutions in 60 countries. The company has recently launched a new handheld FabriTell textile scanner, which has upgraded performance and specifications than previous iterations – allowing customers to quickly identify fabric fibre types on-the-move without the need for expensive lab tests or sorting lines, in industries ranging from quality control to fibre-to-fibre recycling.
The firm has also rolled out the S-Bench AI sorting station, a game-changing solution for faster returns and post-consumer garment grading. The S-Bench uses cutting-edge cameras and material sensing to analyse features on every item that needs grading, to provide garment-level tracking through textile sorting facilities, increasing manual sorting consistency and reducing time wasted. It will soon be able to support a direct upload of photos and data to inventory and resale platforms, as well as automated pricing for maximising the value of each garment. In less than four months, Matoha has deployed five units in the UK and the USA.
Matoha is also finalising its patent-pending FabriBot prototype, a first-of-its-kind, modular, cost-effective robotic solution for automated non-rewearable textile waste sorting, with a first pilot planned for end of 2026.
Why Matoha joined UKFT
“Matoha sees the urgent need among for data-enabled ecosystems to help unlock textile waste circularity and extended producer responsibility, without sacrificing commercial viability and human compassion. We are part of UKFT because many of its members face these same challenges that we are trying to solve and have the same values as we do. We want to be part of the conversation and action on textile circularity in the UK of which UKFT is at the heart of, and build this ecosystem with UKFT members.”
Matoha is a UKFT member? Find out more about UKFT membership here.
