How Vue CEO Ashwini Asokan grew Vue to $19M revenue and 35 customers in 2024.

hello everyone my guest today is ashwini ahsokan she is the ceo and co-founder of vue.ai a computer vision artificial intelligence company for the fashion retail industry at the company her and our team of 100 give the power of sight and learning to machines teaching them to see and experience the world like humans do working across san francisco india and seattle her team has been known to build some of the most cutting edge ai tech and products all right ashwini ready to take us to the top there we go yes all right so tell us tell us what customers are using this technology right now who are you selling to um fashion retailers for the most part so think macy's thread up in the us uh diesel valentino across europe tata group of industries in india so we've got a variety of fashion focused retailers across the globe um that use your ai okay and how might one of these you know a target or online until specifically how would they use you um so there's kind of three ways in which most of these guys use the ai that we provide um the first one is in automating their product digitization process so the minute all their merchandise comes into their company someone's gonna have to be today sitting down and writing and creating all this data about that merchandise right uh black t-shirt round neck long sleeves um and attributing different kinds of styles to it is it casual wear is it you know official wear and there's actually people from across the globe that are that are crowdsourcing a lot of this data um most of this data is incorrect it's inaccurate um and in a lot of cases people are not even creating that data right so for us this whole process of uh using computers to create that merchandise and inventory data for retailers is one of the three primary value propositions that we have the second one is actually around modeling and photography um so we've got algorithms that basically generate human like images in human in human form to model clothing right so today most of these companies that we work with use mannequin studios um or you know they take pictures with models and most of them actually take the head off because they don't want to pay licenses and there's a lot of misuse of model imagery out there in the industry and so increasingly we're beginning to realize that ai generated human models is actually a very appropriate kind of um use case so model models love you you're putting them out of business that's not true so most of the models are being used for marketing purposes our use cases have nothing to do with marketing purposes they're more site merchandising so you've got these millions and millions of images on these product pages with just you know mostly photo generated or photoshopped images without heads in there and for us we're actually generating ai-based models so customers just give us their clothing and we produce different types of models in different body types different skin types different race now almost everybody across the world for for most of these brands they see the standard six feet you know the classic model kind of body and most of the world doesn't even fit that image right got it so how are you when you package all this into your platform right give me a general sense of how you're pricing this is it per number of skus is it a pure play sas play how do you price we are a sas enterprise company so it's largely based on the catalog sizes for these companies it's based on um usage in some in some ways but measured by what so catalog size is a huge portion right what's the usage metric though you said it's usage based as well what's the usage portion so the usage based part of it is largely things like traffic so our ai stylist which is another product um is based on like how many people come and interact with the ai stylist right so again we style and curate outfits for people across the globe for different brands and retailers as well and so some of it is catalog size based and some of it is like web traffic and app traffic okay and then i want to capture more of your backstreet before we do though i mean give me a general sense of average here right so the average customer or the retailer's gonna pay you what per year to use your technology anywhere between a hundred thousand and a million dollars okay so it's very it's very much an enterprise sales motion it absolutely okay timeline when did you launch what year 2016. okay when do you write the first line of code that actually started around 2014. so my question is how much money did you and your co-founder sink into the mvp before your first dollar revenue well you know we were completely bootstrapped um uh we had saved up i had saved up from having worked um at intel for over 10 years um in the bay area and it gave us an opportunity to bootstrap our own company um and uh we raised we have raised almost 28 29 million dollars to date in seed series a and series b since we started the company well yeah but go back just because your bootstrap doesn't you didn't spend money build the mvp it just means you spent your own money to keep you know so you don't get diluted right so how much are your own money did you guys think you spend to build the mvp hundred thousand dollars okay and did you feel like you did that pretty efficiently or you could have done it cheaper looking back oh a lot cheaper looking back um and i think it's interesting right because we did not start off with uh we actually started off with the underlying technology platform so one of the reasons we actually started the company is we wanted to build our own computer vision and ai proprietary platform so much of the first two years of the work that we did ourselves was actually building out the underlying platform before we actually started view.ai so it was a bit of a you know the other way that we went about it um fast forward to 2019 there are still not a lot of sas and enterprise companies out there that are pure play ai so we in a way you know we believe that we've actually broken ground here in this category um being an ai first task company and so you 2014 2016 you're building your building and get your first customers that you're how many customers are now serving today um almost about 35. okay 35. and do you remember how you got your first can you tell us that story yes i do um so i i can't name names unfortunately but um i was actually at a talk um uh called mind the product is a fantastic product community um across the world and there was a mind the product conference and i was actually speaking at it in 2016 in san francisco and i had visited there and also ended up cold calling a uh top-notch retailer out there in san francisco an online retailer um they let us in the cpo gave us a chat they let you in the conference basically you were trying to get in for free no i was a speaker at the conference sorry so i was out in san francisco i was a speaker at this conference buying the product and um around the exact same time i ended up meeting somebody um from this online retail fashion company um at the conference and ended up also like you know calling her getting in touch with her and and got a meeting with her and um uh started pitching her um the promise of ai and how it can truly change the way what was her title uh she was the vp of product actually not the cpo she was a vp okay interesting and and it was at that time this this was one of those few companies that was already ahead of the curve they were already thinking about um replacing kind of their existing practices in the warehouses um they were spending almost like a minute two minutes on just just the tagging activity and a lot of their site search and discovery was broken and they wanted to kind of they saw the use of computer vision in that context and said okay you know let's start putting millions of these products through um you know the computer vision tech that we had and the product i think the audience my audience totally understands the product i totally get the need for this i'm curious though volume wise so 35 customers how many skus have you now processed across all your base altogether we have tagged about 450 million products today 450 million okay over the last what to two and a half years over the last two okay and how much over the past 12 months um more than so so a large portion of that almost 300 million in the last uh 12 months okay good so obviously good growth there now turns critical in any sas company right so so how do you measure your churn have you had any customers downgrade or cancel since you started yeah so this has been an incredibly i would still argue we're still in a bit of a of an of a early adopter market we're just moving from early adopted early majority it's very evident and so for us our strategy right from day one has been going after the biggest names in ego so we went after the largest companies and the largest brands in the us in europe and south america and india in japan and it was very counter to almost any investor i was pitching to or most of like my peers other founders that i've been talking to saying you know it's really hard to kind of build an enterprise startup by ground up by only pitching to the top tier but it was very evident to us that we had to build this category out right from day one and our strategy was to go after the biggest names in the industry and build credibility and trust and that was more important to us...