April is Artificial Intelligence month at All Raise and our third AI #WCW is Ashwini Asokan, co-Founder and CEO of Vue.ai which announced its Series B funding today. All Raise’s ‘Women Crush Wednesdays’ (#WCW) is a series where we highlight genius women who are funding or founding tech companies. Please come back to the All Raise Medium blog every Wednesday to find a new profile of an awe-inspiring female VC or founder.
There is no one like Ashwini Asokan in most venture portfolios. As the Founder and CEO of Vue.ai (Mad Street Den), she has managed to do what seems impossible. As Ashwini says herself “I’m a brown woman in AI, running an enterprise startup, in a category called Retail Automation, using computer vision.” It’s hard enough to build an AI-enabled enterprise company, let alone a fast-growing enterprise platform that deploys AI at scale in a rapidly changing industry.
Vue.ai’s visual intelligence platform promises intelligent retail automation. The platform puts powerful AI tools in the hands of retailers and their teams helping them automate several functions across their workflow. From fashion photography to catalog management to personalized styling and outfitting, Vue.ai is used by retailers as a one-stop-automation solution. On the one hand, it helps retailers get 10x more efficient and productive, helping them compete with the Amazons of the world. On the other, it helps the customer shop more effectively using AI enabled styling. Vue.ai makes Cher Horowitz’s outfit-matching software in Clueless seem like not just a Hollywood dream.
With a strong use case, rapid growth and large retail clients such as ThredUp, Zilingo, Tata and a truly global portfolio, investors had to pay attention. After a Series A led by Sequoia India, Vue.ai just announced their $17M Series B round led by Falcon Edge Capital. Navroz Udwadia joined the board along with existing investors Sequoia India, Exfinity Ventures & KDDI Japan. The company plans to use this funding to continue to accelerate growth and scale globally. I chatted with Ashwini and asked her what it took to raise her Series B and how she manages a cross-border company.
Q: What did it take to raise your Series B? What proof points did investors look for?
A: Here’s what I did. I created my own version of the 5-point ‘exploding heart’ technique: (Sorry for that Kill Bill reference!) Metrics-focused growth, A crystal clear story about value, Solid testimonials and customer stories that become the qualitative data revealing the details behind that growth. Repeatable, scalable processes from a solid team. And finally, the TAM. The rest is all luck all the way.
Q: How did you demonstrate each of the proof points?
This last year, we’ve seen 4x growth and if you take a close look at where retail is headed, it’s a story of pulling out the guts and plumbing the system again. So much of the Series B has been about showing scale and credibility. We have some big logos and retailers that we’ve brought on board. That coupled with building momentum and brand recognition in the AI and retail space brought many different types of people to the table.
We’ve styled 3B outfits with our AI stylist tool, saved retail teams over 30 hours in their product digitization and catalog management process with our automated product tagging and metadata creation solution. Showing proof of how we’ve helped businesses grow while simultaneously helping them get leaner and efficient has been central to this growth.
A huge portion of it has just been showing that the company can grow and that we can use this kind of AI to grow an actual business. Computer Vision-based applications are not easy to scale. At the beginning, it was all about proving that the technology could even be built and then if there was a place it could be applied. Because we’re very specific to fashion and home, at this stage, the minute many investors looked at it, they said, “It’s over. Retail is dead. Change your vertical”. Thankfully, we had wonderful investors and partners from the get-go that stayed the course with us and believed that creating a category takes experimentation and time. Today, there’s so much talk about how markets often look tiny in the beginning but it’s not always the case. This has certainly been true for us.
Q: What are some lessons you learned from your fundraise?
My biggest lessons have been around not underestimating how hard the journey can be. It’s hard. It doesn’t get easier. It’s exactly like raising children. It just changes with time. It’s up and down and sideways and it crushes you and makes you happy all at once. But you won’t do it any other way. Despite all the bias that no one wants to talk about, despite having to punch 10x more than your male peer, every day is worth it. I’m privileged and thankful to have had the opportunity to raise all these children with my husband/co-founder, both at home and at work.
Q: Why did you decide to focus your company on a retail application?
A: Until recently, most of the examples of AI-in-use you’ve been hearing about, have been experimental. I love to say that AI has been a technology looking for a problem to solve. Scaling systems built using computer vision is not easy. It is not flawless and is very specific to specific types of conditions. Our take was that the only way to make the AI we were building succeed was to take a vertical approach to a specific industry. We are now solving very specific problems for the retail industry in a way that’s actually adding value to them. We’re helping them move 10x faster at a fraction of the cost, while simultaneously helping them deliver superior experiences to their customers. We are essentially a vertically integrated AI stack for the Retail Industry.
It’s an understatement to talk about how retail is undergoing change. You have Amazon on one side, real estate prices going up, activism and a fundamental shift in cultural values everywhere, the rise of sustainable living, minimalism and awareness, Marie Kondo on TV, co-working spaces like ReStore becoming storefronts for brands you’ve never heard of that Rihanna discovers on Instagram — everything is different. We, along with our customers, believe AI will be at the center of this story, and will help in the reimagination and rearchitecting of this industry.
Q: How does vue.ai use data to make retail companies more efficient?
We do end to end retail automation. From the point where merchandise gets to a company’s warehouse, they’ve got a lot of people taking pictures and writing metadata of all the different types of clothing, apparel and accessories and no two people are writing the same thing. You type in “umbrella skirt, ” and you get an umbrella and not a skirt. With computer vision, it’s like giving your machines the ability to see all your merchandise and create all that data in a moment. You upload a million images of your merchandise and everything is automatically tagged and described in a few minutes. It takes a few hours to do what is today a month-long process.
From there, we move to the photography side, you have companies paying a lot for mannequin studios and photography and taking over three months to digitize and get products ready for their online platforms. And there’s no way for us to envision how these clothes are actually going to look on ourselves. Enter our model generator. It generates human models of different sizes, skin tones, geographies, body type. I’ve never understood why I’ve had to use size 0 white models as the only option to visualize the clothing I see on most sites. Vue.ai fixes that.
Once all your merchandise is digitized and is ready to go online or in a subscription box or in email, our AI stylist tools kick-in. They’re tools for stylists, for product managers, marketers to help make merchandising decisions across different channels. We combine inventory data, trends and forecasts with individual style preferences of each and every shopper to create a real-time, intent-based personalization across the entire customer journey. We are the only AI solution out there that spans the entire spectrum of applications that are used by merchandisers, stylists, and consumers.
Q: Where do you think AI is headed in the future?
A: I think the future of AI is in the hands of product people. If we don’t make sense of where and how we’re going to put AI to use, we’re going to be in a very bad state not too far from now. So much is getting built today in this space without absolutely any idea about how it’s going to be used and a deliberate process of thinking through value. There’s a lot of money that’s been raised on AI just purely because of people’s technical qualifications but no sense of what the product or use cases are going to be. If I had a dollar for every time I’ve had a VC tell me “oh we funded this AI startup but they’re not sure of the use cases just yet, and are now doing facial recognition”. We’ve somehow ended up in this deep fakes, deep celebrity faces world, with not a lot of thought to the outcomes. I think having the key is having the right kind of product team to help you figure out how to harness the tech and deliver value in a genuinely meaningful way. Essentially, AI needs to go back to basics like everyone else and start with the problem.
Q: What are some of your favorite founders or brands you admire?
I admire my fellow Sequoia-backed founders Ankiti Bose of Zilingo, a recent unicorn and one of the fastest growing retail companies in the world built out of Singapore; Selene Cruz of ReStore, from right here in the valley, whose changing the very definition of a retail experience; Vidit of Meesho, a marketplace built on Whatsapp for the India market are some examples of my favorite brands that come to mind. If anything, their businesses are so unique and they’ve been able to build strong moats and go at the same problems in a very novel way, precisely because of their diverse backgrounds. Their stories are absolutely fascinating and I’m a big fan. Building a category like ours requires working closely with such leaders, who are quietly pulling at the legacy systems and unproductive ways of the old retail world and building the foundations of an entirely new industry.