The Best Artificial Intelligence Tools In The Fashion Industry

Billboards about Artificial Intelligence have been lining Highway 101 in San Francisco for as long as I've lived here, over 3 years.  As I talk to people about AI they wonder, what does someone interested in Fashion care about Artificial Intelligence?

Now is the time, more than ever when years of research are being applied to industry.  We've seen projects like IBM's Watson market to a wide range of industries and entrepreneurs looking for opportunities to Innovate (with a capital "I".)

So what are some of the most interesting things happening with AI in the Fashion Industry?  Here are the top 3:

#1 - Streamlining Design Processes

If you haven't been following the start-up Techpacker, start now.  They're solving one of the biggest pain points in the fashion design process and they have the technical chops and the industry experience to do it right.  If you're a technical designer, I would suggest looking into getting your team to rethink their design processes and change over to their software services.  The future of Techpacks starts here and with every feature addition, they're thinking of the designer and how to streamline communication with factories. 

Fashion Designers have not had the tools for simple innovations like Version Control.  Techpacker has introduced that feature:

Brands spend millions of dollars on PLMs that their designers refuse to use because they're horribly inconvenient and don't allow for the flexibility they need to move quickly.  Techpacker is fixing that by allowing designers to set their techpacks in stages.

What do these features have to do with AI?  Nothing, here's what's next:

Techpacker is working on building a community where technical designers can leverage each others work to create tech packs faster.  With advanced computer vision algorithms, you can search for similar products and construction details for that product.  Learning together saves everyone in the industry time and money.  Imagine a future where designers can rank construction techniques and materials with success ratings.  New designs are easier to take risks with when you have access to more data that's presented in a comprehensible way.

#2 - Search Optimization and Product Discovery

Late last year, retailer Etsy acquired a small Bay Area company called Blackbird Technologies. 

Why?  Blackbird is optimizing search for retailers with a wide variety of goods using deep learning applied to computer vision.  This means these retailers, like Etsy, no longer need to rely on heavy manual tagging for product discovery.  Instead, these computer vision algorithms are able to predict what is inside an image of a product.  For example, a black v-neck tee shirt or a brown dresser.  These things don't have to have the proper data attached to them because they've trained neural nets to understand when a brown dresser is in a given image.

#3 - Predictive Analytics

Predictive analytics are giving businesses competitive advantage in a number of areas like: inventory prediction and size prediction.  I've mentioned companies like Fit Analytics before.  Fit Analytics looks at what people are buying and what their rate of return is.  Their API surveys buyers with just a couple of questions to deliver valuable data to give them buying confidence.  Importantly, they're growing a huge dataset to learn about human preferences and finding powerful correlations in delivering garments that fit closer to the customer's expectation.

What else is this important?  For starters, small improvements in inventory prediction will save retailers a ton of resources and lend a hand in leading a dangerously high polluting industry to more sustainable practices.