The year of global disruption became a time of reckoning for the fashion industry. E-commerce, changing consumer priorities and tides of social media attention have been eroding the foundation of brick-and-mortar retail for years. Coronavirus restrictions accelerated its demise. Once ubiquitous, JCPenney filed for bankruptcy to re-emerge with livestream shopping under new ownership. Rapid evolution is driving fashion’s quest for survival. Forward-thinking brands have introduced chief digital and chief innovation officer positions, adopting tech on an unprecedented scale. One of the key concerns for designers and shoppers alike is the ability to try-on clothing and accessories as part of the purchasing decision. Some brands augmented bespoke practices in-store. The fashion app boom of 2020 saw dozens of start-ups entering the niche. The market-wide need attracted competition for a sizing solution: TrueFit, triMirror, and others. Research shows people are five times more likely to buy an item given an option of virtual fitting. It is no coincidence that one of the promising players in the field of retail digitization and virtual customization is a woman-founded, women-led fashion tech startup. I met with StyleScan founder Larissa Posner to find out how a former-model-turned-financial-advisor set her entrepreneurial sights on fashion’s biggest challenge; and what Star Trek has to do with it.

How did the idea for StyleScan come about?

Larissa Posner: I used to be a catalog model and learned first-hand how many pins, clips, and strips of tape go into making garments look better in ads than they do in real life. On top of that, there is post-production and Photoshop. Then, as a financial advisor on Wall Street, I worked with some of the world’s smartest mathematicians, analysts, and engineers. I tasked them with figuring out how to make e-commerce more personalized and true to life. That meant seeing the garment in 3-D and seeing the clothing on yourself rather than on the pictured model. They liked the challenge of applying brainpower to something as practical as clothing. Turned out there was a way to reimagine the 3-D visualization algorithms and the entire process. With our technology, what you see is what you get. Consumers can finally be their own best models. No tricks.

How is StyleScan different from other fitting apps and what can consumers look forward to?

Fitting apps generally tell you if you are a small, medium or large. StyleScan goes beyond that by providing a visualization tool. We digitally render garments in 3-D, using our proprietary process. Through this, brands and retailers can show their garments online in 360-degrees – on mannequins as well as a diverse range of models. Everything fits hyper-realistically from multiple angles. The world is moving in a direction of increased personalization and consumers are wanting to see garments on themselves. Later this year, they will be able to do that by taking selfies and using StyleScan for virtual try-on.

You got involved with your tech team in 2018, only a few years ago. How did you get this going so quickly?

The team has been developing Machine Learning models long before they knew it was called Machine Learning. With their expertise, it took just a small step for the technology to be applied to fashion.

People don’t usually associate Machine Learning with fashion.  

I agree. The team I am working with has rare experience – they design proprietary Machine Learning algorithms and classifiers, none of which is off the shelf – from worlds beyond fashion. Our Chief AI Officer Rob Reitzen and CTO Hein Hundal have used Machine Learning for stock trading and predicting Wall Street futures. Additionally, they used Machine Learning to beat poker, blackjack and many other games. They’ve gained substantial advantages and turned those advantages into impressive profits. It is no coincidence that Rob is in the Blackjack Hall of Fame and Hein worked with a top-secret clearance on military projects at Raytheon. 

Okay. I can see how this can be used to beat games and the stock market. But can you explain how it applies to what you guys are doing with fashion? 

Remember the universal translator in Star Trek? It was a program that looked for consistencies in all languages, whether spoken by humans, animals or even aliens. That is Machine Learning. It is like a universal translator. You can be working on curing cancer – as one of our partners does – and I can be working on stock trading. Without even understanding cancer, I would be able to apply Machine Learning techniques to it. That’s because Machine Learning is not domain specific. The same algorithms apply to a wide range of things, whether they are the spawning patterns of fish or genetics or the fitting of apparel.  

How open is the industry to adopting this technology?

Very much so. We are in testing phases with many fashion brands, including NYDJ, with which we look forward to launching in the near future. They, like all of our clients, understand that the industry is going through transformation and they want to be on the cutting edge. We work with brands that recognize the need for this new technology. We’re here to help them achieve their goals.