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.
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.
Industrial Engineer in software and computer science from Pontificia Universidad Católica de Chile