How Vue CEO Ashwini Asokan grew 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 than anything else so from a churn perspective you know it's interesting our turn started happening when we immediately said you know what let's also start going behind people with like no volume at all or like you know really small young startups that were coming up in the fashion space and that is when we started to see a little bit of churn but it shouldn't be it shouldn't be a ton of turn though because they should be paying like like such little amount relative to your enterprise deals the revenue turns should still be really low if you're turning small small startups fundamentally different strategies right and that is probably the biggest lesson that we learned that we can't handle both segments at the same time very early in the day and i think we went head-on by going through all segments at the same time and so enterprise is still definitely one of those verticals that works like it's it's we figured enterprise out and now we're at that point where you know sorry what just because we're short on time i don't want me to cut you off but so when you look at the past 12 months revenue churn are you talking like 10 or more no we're talking about like two percent okay two percent and then it's and that's monthly or annually annually all our contracts are annual so if we don't do we don't have monthly charm yeah and then when you when you look at you've had two three four years of business history now when you look at expansion revenue on these accounts year over year doesn't more than make up the two percent loss absolutely absolutely right so do you think that's like 30 40 range or what would you put that in so at least uh 30 to 40 of our growth year year-over-year comes from uh our expansion revenue so just to repeat that back to you if someone signs up with you today with a certain number of skus on a hundred thousand dollar acv you're saying they're gonna use you they're gonna add more excuse they're gonna up they're gonna have more head count they'll expand at least a hundred and forty hundred fifty thousand in a year two absolutely and and even more like i can't tell you exactly the numbers at this point but for us with like i would argue like six or seven of these 30 customers that we've had have more than tripled in the three years that we've in the two and a half years that we worked with them right so a huge course of it has been really growth growth growth um and since it is an end-to-end promise it allows us to actually continue to build and grow with our customers how aggressive are you being to get them in the door in the first place so if they're gonna pay you 100 grand in a year one will you spend the full first year acb to get the customer for a 12 month payback period oh not at all we're talking about cac for this segment today being something more like 10 of that so cac is not which is very counterintuitive a lot of people go that makes no sense at all but but you know it's basically a couple of flight tickets at the end of the day because enterprise sales is all about being in front of the customer showing them how this works and doing it what's the sales person commission um about seven to ten percent okay so yeah if you have so again seven to ten percent 100 grand is 10 grand right there and then you're basically saying there's no other cost to close the deal it's mostly in the form like i said it's mostly in the form of a couple of flight tickets but that's pretty much it okay what's your team size today how many people today we have uh almost hundred okay hundred folks is spread out all over 102 actually yes spread all over now obviously you're on the vc path which means you're trying to figure out smart ways to burn capital to drive growth i always like to get the heads of ceos and figure out how aggressive you're choosing to be so when you look at burn that you can actually sleep with at night right are you talking like a hundred grand a month a million a month ten million a month what are you comfortable burning well you you know for me at the end of the day the burn is not so much a number as much as it's um i tend to look at every milestone that i've i've kind of taken from a fundraiser's perspective for me i've noticed that it's roughly about like 18 months for the most part um i'm somewhere between 18 and 24 months and we've been incredibly cash efficient right sorry what do you mean by 18 to 24 months you're talking but you're talking in terms of cash in the bank in terms of any time like your run rate basically yes that's exactly right and so with recycle you know we plan for a minimum of like 24 months and we've been pretty on the dot and which means my fundraise cycle has kind of coincided with that kind of ability to stick to that dot from a budget perspective so the churn is a lot less a number for me and more in terms of looking at the revenue we're making look at looking at the growth we're making and how are we how am i able to plan the fundraise cycle according to that is largely the story of burn for me um and of course at the end of the day you know it's important to look at gross margins we are a sas enterprise company so you know our eyes are constantly on the margins i mean hopefully that's like 85 to 90 percent correct almost i would say remember we are a computer vision company in the cloud so heavy software image and video in the cloud is what we do and it's already time with like you know very very little lag because our customers are hitting our apis and we're serving back images and videos and analyzed real time what sorry just to round out the funding story so what when was the last round two months ago oh you just closed it oh it's great how much was it 17 million in series b oh got it okay got it so you had about what it sounds like uh 12 million in before that across seed in series a and then the 17 million or sorry did you was it was it 12 million before that it was uh so we did 17 this time around and yes we did do 10.5 so it's like 27.5 prior to that okay and you're saying when you're doing the 17 in your head what you're thinking is you want to buy yourself at least 18 months of runway oh of course yeah absolutely so that means burn today would be something like 900 grand a month less than a million um way less than a million you forget like we are um we are a huge portion of the teams based out of india um a small portion of the team is based out of san francisco and then we have other folks out of japan and latin america but a huge portion of our uh team is based out of india okay i get the reason i'm asking just because you said you raised for eight you like to raise for 18 months of runway so 17 million by 18 months is a million that's about yeah but that's over and above the revenue right so i'm not gonna live off of my um um of just the fundraise alone so the fundraise is like a combination of the 17 million plus the revenue that run rate that i am in right now yeah that's 18 plus when i think my cash is going to run up yeah okay very good and then um going back right so you said 35 customers north of 10 000 bucks a month each that puts you north of 350 000 a month right now in revenue is it accurate i'm not sure i'm ready to pause that unfortunately i'm not i'm not trying to get you in a gotcha i'm taking numbers you already gave me you said everyone paid more than 100 grand some up to a million and you said 35 customers yeah someone some up to a million yes yeah but you said everyone i'm again i'm not trying to get you to gotcha these are your numbers you said north of 100 grand and some up to a million so if i assume the minimum of 100 grand a year across 35 customers that's north of 350 grand a month that's right but we do have um increasingly over the last like say six months folks in the mid market category as well as part of the experiments we're doing so but it is fair to say that we're looking at somewhere between 75-100 in terms of the average okay when do you think you'll hit 350 a month do you think you do that this year or is it more like next year it's a stretch goal oh god no like now okay got it fair enough um good and then where were you a year ago double in your every year or more or less we did 4x last year um we went from zero to twelve zero to one in about 12 months a little over 12 and then we have been we did a forex right after that and this year we're looking at roughly about 3x so so just be clear if you're doing like 300 a grand a month right now and you're saying you like basically that's 4x year over year you're saying you're only like 75 grand a month a year ago uh no so we're on year three right now so we we did 4x last year in 2018 and this year we're on our path to doing about 3x oh got it so you're doing about 100 a month a year ago a little more than that that's great that's i mean that's look that's healthy growth and is most the growth coming from expanding into the same customers or adding new logos all together it's it's it's even it's both and being an end-to-end customer uh kind of a platform it's really important for us to kind of invest back in our customers and so the land and expand strategy for us you know comes up to like 30 to 40 percent of our revenue and then there's a lot of new growth as well very good all right let's wrap up here uh ashwini with the famous five number one what's your favorite business book you have something sitting there right behind you um now chaos monkeys is a fun one but i'm i'm very recently reading um um uh ben horowitz's hard things about how things like the 40th time i'm reading that book that's definitely an all-time favorite of mine and number two is there a ceo you're following or studying a not a single one but you know katrina lake is a is a pretty fantastic one to um follow number three what's your favorite online tool for building your company online tool for building my company um from an hr perspective or from in in what way you pay okay um twitter i hire 15 to 20 of my employees on twitter number four how many hours i sleep to get every night oh my god this is a total shaming moment isn't it um not a lot probably about um four to five hours i've gotten better this year i'm i'm i'm gonna be at seven by the end can i can i ask you like your situation like married single kiddos i'm married my co-founder is my um husband okay um any kids two yeah all right two kids and then can i ask to ashwini how old you are [Music] uh 37. take me back 17 years what do you wish your 20 year old self knew what what was that question again what what's something you wish you knew when you were 20. now you know what it's almost the exact other way round i would say my 20 year old self was a professional dancer and a professional musician and so full of confidence and uh completely flying and i would look back and go oh my god i hope my 20 year old self tells my 37 year old uh self today it's all gonna be okay it's the other way around guys it'll all be okay she's helping online retailers better manage their skus their inventory for accuracy whether it's licensing issues imaging issues or just scale issues serving 35 customers paying north of seven grand a month to call 300 a month right now in total revenue that's up from just 100 grand a month a year ago so nice growth rates they've got about two percent uh gross churn annually on thirty percent expansion so 128 net revenue retention spending call like 10 grand i need to get a new customer so pretty healthy payback period they've raised about 29 million bucks just closed a 17 million around here two months ago as they look to continue to scale sweeney thank you for taking us to the top thanks nathan