Given the ubiquity of fakes among re-sellers, buyers often examine pre-owned fashion to deduce authenticity, often analyzing the stitching, font size and interior labels. But sometimes, a copy is just so well-made that the human eye can't tell it from the original.
That's where technology can help.
Entrupy is a portable scanning device that instantly detects imitation designer bags by taking microscopic pictures that take into account details of the material, processing, workmanship, serial number, and wear/tear. It then employs the technique of deep learning to compare the images against a vast database that includes top luxury brands and if the bag is deemed authentic, users immediately get a Certificate of Authenticity.
After launching as a paid service in September 2016, the New York-based venture now has over 130 paid customers, almost all of whom are American businesses drawn to the 97.1 percent accuracy rate, explained Entrupy CEO Vidyuth Srinivasan.
Other investors include New York University, deep learning pioneer Yann LeCun, and Japanese venture capital firm Accord Ventures.
"We're choosing to start with second-hand re-sellers initially as we see a huge lack of trust in the luxury goods space, especially online," Srinivasan told CNBC.
In 2015, Singapore-based e-tailer The Fifth Collection, which specializes in secondhand luxury fashion, became one of Entrupy's early investors.
At the time, founders Nejla Matam-Finn and Michael Finn were self-funding The Fifth Collection and hadn't even paid themselves a salary but they called the Entrupy investment a no-brainer.