Sortile is changing the landscape of textile recycling by developing AI-driven and data analytics solution for textile waste. Our current product accurately identify fiber composition, enabling textile-to-textile recycling and fostering circular fashion.
This is only the begining!
Sortile empowers current sorting infrastracture with NIR spectroscopy and machine learning to efficiently identify fibers, unlocking the potential to sort by fiber composition and enable textile-to-textile recycling. Additionally we provide data analytics capabilities, giving visibility of the waste stream.
Sortile has accuracy over 95% to identify over five fiber compositions.
Reduces processing time by eliminating the use of clothing tags for sorting.
Our service provides data analytics and reporting for a more transparent and efficient management
Co-Founder & CEO
Columbia University MBA '22
Industrial Engineer with a minor in Computer Science from Pontificia Universidad Católica de Chile
Co-Founder & COO
Columbia Univeristy MPA '21
Master in Economics with a bachelor in Business from Pontificia Universidad Católica de Chile.
IoT Product Manager
Electrical Engineer with vast experience in the development of electronic products, taking them from ideation to commercialization.
Machine Learning Engineer
Industrial Engineer and MSc in Electrical Engineering with a career in data analytics using AI, image processing and machine learning.
Software Engineer with backend and frontend web development experience.