How Vue.ai Reached About 35 Customers at a $75K to $100K Average Annual Contract (Interview with CEO Ashwini Asokan)

Introduction to Vue.ai and Ashwini Asokan

Nathan Latka

00:00Hello, everyone. My guest today is Ashwini Asokan. She's the CEO and cofounder of Vue.ai, a computer vision and artificial intelligence company for the fashion retail industry. At the company, her and her team of a 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

00:19tech and products. Alright. Ashwini, are ready to take us to the top?

Ashwini Asokan

00:23There we go. Yes.

Nathan Latka

00:24Alright. So tell us tell us what customers are using this technology right now. Who are you selling to?

Customer Base and Target Market

Ashwini Asokan

00:31Fashion retailers for the most part. So think Macy's, ThredUp in The US, Diesel, Valentino across Europe, Tata Group of Industries in India. So we've got a variety of fashion focused retailers across the globe that use Vue.ai.

Nathan Latka

00:46Okay. And how might one of these, a target or online retail, specifically, would they use you?

Ashwini Asokan

00:52So there's kind of three ways in which most of these guys use the AI that we provide. The first one is in automating their product digitization process. So the minute all their merchandise comes into their company, someone's going to have to be today sitting down and writing and creating all this data about that merchandise, right? Black t shirt, brown neck, long sleeves, and then attributing different kinds of styles to it. Is it casual wear? Is it

01:21official wear? And there's actually people from across the globe that are crowdsourcing a lot of this data. Most of this data is incorrect. It's inaccurate. And in a lot of cases, people are not even creating that data. So for us, this whole process of 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. So we've got

01:51algorithms that basically generate images in human form to model clothing. Right? So today, most of these companies that we work with use mannequin studios, or 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,

02:22use case.

Nathan Latka

02:22So models love you. You're putting them out of business.

Ashwini Asokan

02:25That'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 and different

02:50body types, different skin types, different race. Now, almost everybody across the world, 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?

Nathan Latka

03:06Got 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 SaaS play? How do you price?

Pricing Model and Usage Metrics

Ashwini Asokan

03:15We are a SaaS enterprise company. So it's largely based on the catalog sizes for these companies. It's based on usage in some ways,

03:25but

Nathan Latka

03:25Measured by what?

Ashwini Asokan

03:27So catalog size is a huge portion.

Nathan Latka

03:29What's the usage metric though? You said it's usage based as well. What's the usage portion?

Ashwini Asokan

03:35So the usage based part of it is largely things like traffic. So our AI stylist, which is another product 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.

Nathan Latka

03:54Okay. And then I wanna capture more of your backstory before we do though. Mean, give me a general sense of average here, right? So the average customer or the retailer is gonna pay you what per year to use your technology?

Ashwini Asokan

04:03Anywhere between a 100,000 and a million dollars.

Nathan Latka

04:06Okay. So it's very much an enterprise sales motion.

Ashwini Asokan

04:08It absolutely is.

Company Timeline and Bootstrapping the MVP

Nathan Latka

04:10Okay. Timeline, when did you launch? What year?

Ashwini Asokan

04:132016.

Nathan Latka

04:14Okay. When did you write the first line of code?

Ashwini Asokan

04:17That actually started around 2014.

Nathan Latka

04:20So my question is how much money did you and your co founder sink into the MVP before your first dollar of revenue?

Ashwini Asokan

04:26Well, we were completely bootstrapped. Had saved up. I had saved up from having worked at Intel for over ten years in the Bay Area, and it gave us an opportunity to bootstrap our own company. And we have raised almost 28 to $29,000,000 to date in seed series A and series B since we started the company.

Nathan Latka

04:47Well, but go back just because you're bootstrap doesn't mean you didn't spend money to build MVP. It just means you spent your own money to keep, you know, so you don't get diluted. Right? So how much of your own money did you guys think you spent to build the MVP?

Ashwini Asokan

04:56A $100,000.

Nathan Latka

04:58Okay. And did you feel like you do that pretty efficiently or you could have done it cheaper looking back?

Ashwini Asokan

05:02Oh, a lot cheaper looking back. And I think it's interesting, right? Because we did not start off with Vue.ai. 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 Vue

05:25dot ai. So it was a bit of a, the other way that we went about it. Fast forward to 2019, there are still not a lot of SaaS and enterprise companies out there that are pure play AI. So we sort of in a way, we believe that we've actually broken ground here in this category being an AI first SaaS company.

Nathan Latka

05:43And so you be at 2014, 2016, you're building your building, you get your first customers that year. How many customers are you now serving today?

Ashwini Asokan

05:51Almost about 35.

Nathan Latka

05:53Okay, 35. And do you remember how you got your first? Can you tell us that story?

First Customer Story and Cold Outreach

Ashwini Asokan

05:57Yes, I do. So I can't name names unfortunately, but I was actually at a talk called Mind the Product is a fantastic product community 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 visited there and also ended up cold calling a top notch retailer out there in San Francisco, an online retailer. They let us in, the CPO gave us a chance

06:28to

Nathan Latka

06:28Hold on, hold on. Let you in the conference, basically you were trying to get in for free?

Ashwini Asokan

06:32No, I was a speaker at the conference. Sorry. So I was out in San Francisco. I was a speaker at this conference, Mind the Product. And around the exact same time, I ended up meeting somebody from this online retail fashion company at the conference.

Nathan Latka

06:47Oh, I see.

Ashwini Asokan

06:47And ended up also like, you know, cold calling her, getting in touch with her and got a meeting with her and, started pitching her, the promise of AI and how it can truly change the way.

Nathan Latka

06:59What was her title?

Ashwini Asokan

07:01She was the VP of Product, actually, not the CPO. Was a VP

Nathan Latka

07:01Interesting.

Ashwini Asokan

07:01Of

Nathan Latka

07:06Interesting.

Ashwini Asokan

07:06And it was at that time, this was one of those few companies that was already ahead of the curve. They were already thinking about replacing kind of their existing practices in the warehouses. They were spending almost like a minute, two minutes on 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, let's putting

07:31millions of these products through the computer vision tech that we have and

07:37dragging

Nathan Latka

07:37Yeah, the 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?

SKUs Tagged and Product Volume

Ashwini Asokan

07:47We have tagged about 450 million products today.

Nathan Latka

07:51450 million.

07:53Over the last what?

Ashwini Asokan

07:55Two, two and a half years.

Nathan Latka

07:56Over the last two.

07:57Okay. And how much over the past twelve months?

Ashwini Asokan

08:00More than so, so a large portion of that, almost 300,000,000 in the last twelve months.

Nathan Latka

08:06Okay, good. So obviously good growth there. Now, churn's critical in any SaaS company, right? So, so how do you measure your churn? Have you had any customers downgrade or cancel since you started?

Churn, Retention, and Expansion Revenue

Ashwini Asokan

08:16Yeah, so this has been an incredibly, I would still argue we're still in a bit of a early adopter market. We're just moving from early adopter to early majority. It's very evident. And so for us, our strategy right from day one has been going after the biggest names in each geo. So we went after the largest companies and the largest brands in The US, in Europe, in South America, in India, Japan. And it was very counter

08:43to almost any investor I was pitching to or most of my peers, other founders that I've been talking to saying, 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

09:05was more important to us than anything else. So from a churn perspective, it's interesting. Our churn started happening when we immediately said, you know what? Let's also start going behind people with no volume at all, or 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.

Nathan Latka

09:24But it shouldn't be it shouldn't be a ton of churn, though, because they should be paying like, such little amount relative to your enterprise deals, the revenue churn should still be really low. If you're turning small, small startups,

Ashwini Asokan

09:33Fundamentally different strategies, right? And that is probably the biggest lesson that we've 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 we figured enterprise out. And now we're at that point where,

09:53you know-

Nathan Latka

09:53Ashwini, sorry, just because we're short on time, I mean to cut you off. But so when you look at the past twelve months revenue churn, are you talking like 10% or more?

Ashwini Asokan

10:01No, we're talking about like 2%.

Nathan Latka

10:03Okay, 2%. And that's monthly or annually?

Ashwini Asokan

10:07Annually, all our contracts are annual. So we don't have monthly churn

10:11for the most

Nathan Latka

10:11And then 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, does it more than make up the 2% loss?

Ashwini Asokan

10:21Absolutely, absolutely. Right.

Nathan Latka

10:23So like you think that's like 30, 40% range or what would you put that in?

Ashwini Asokan

10:27So at least 30 to 40% of our growth year over year comes from our expansion revenue.

Nathan Latka

10:33So just to repeat that back to you, if someone signs up with you today with a certain number of SKUs on $100,000 ACV, you're saying they're going to use you, they're going to add more SKUs, they're going to update, they're gonna have more headcount, they'll expand at least 140,000, 150,000 in a year too.

Ashwini Asokan

10:45Absolutely. 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 been the two and a half years that we worked with them. Right?

Nathan Latka

10:45That's great.

Ashwini Asokan

10:45So a huge force of it has been really growth, growth, growth. And since it is an end to end promise,

11:05it allows us to actually continue to build and grow with our customers.

Nathan Latka

11:09How aggressive are you being to get them in the door in the first place? So if they're gonna pay you $100,000 in year one, you spend the full first year ACV to get the customer for a twelve month payback period?

CAC and Sales Motion

Ashwini Asokan

11:16Oh, 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 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

11:35for corporate

Nathan Latka

11:35What's the salesperson commission?

Ashwini Asokan

11:38About seven to 10%.

Nathan Latka

11:40Okay. So yeah, if you have... So again, seven to 10% of $100,000 is $10,000 right there. And then you're basically saying there's no other cost to close the deal?

Ashwini Asokan

11:48It'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.

Nathan Latka

11:53Okay. What's your team size today? How many people?

Team Size, Burn, and Runway

Ashwini Asokan

11:55Today, we have, almost 100.

Nathan Latka

11:57Okay. 100 folks spread out all over.

Ashwini Asokan

11:59102, actually.

12:00Yes. Spread all over.

Nathan Latka

12:02Now, 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 in 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 $100,000 a month, 1,000,000 a month, 10,000,000 a month? What are you comfortable burning?

Ashwini Asokan

12:20Well, know, for me at the end of the day, the burn is not so much a number as much as it's, I tend to look at every milestone that I've kind of taken from a fundraise perspective. For me, I've noticed that it's roughly about like eighteen months for the most part. Somewhere between eighteen and twenty four months, and we've been incredibly cash efficient.

Nathan Latka

12:40Sorry, what you mean by eighteen to twenty four months? You're talking in terms of cash in the bank, terms of anytime you like your run rate basically?

Ashwini Asokan

12:47Yes, that's exactly right. And so with recycle, we plan for a minimum of like twenty four 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 burn is a lot less a number for me and more in terms of looking at the revenue we're making, looking at the growth we're making and how am

13:10I able to plan the fund raise cycle according to that is largely the story of burn for me. And of course at the end of the day, you know, it's important to look at gross margins. We are a SaaS enterprise company. So, you know, our eyes are constantly on the margins

13:22and

Nathan Latka

13:22Hopefully it's like 85 to 90%, correct?

Ashwini Asokan

13:26Almost, I would say, remember, we are a computer vision company in the cloud.

Nathan Latka

13:31We have a software.

Ashwini Asokan

13:33Image and video in the cloud is what we do. And it's all risk timed 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.

Funding History and Series B Close

Nathan Latka

13:46So what was your... Sorry, just to round up the funding story. So what when was the last round?

Ashwini Asokan

13:52Two months ago.

Nathan Latka

13:53Oh, you just closed it. Oh, it's great. How much was it?

Ashwini Asokan

13:5517,000,000 in series b.

Nathan Latka

13:56Oh, got it. Okay. Got it. So you had about what? It sounds like, 12,000,000 in before that across seed and series a and then the 17,000,000... Or sorry. Did you... Was it was it 12,000,000 before that?

Ashwini Asokan

14:06It was... So we did 17 this time around and yes, we did do 10.5. So it's like 27.5.

14:13Prior to that.

Nathan Latka

14:13Okay. And you're saying when you're doing the 17 in your head, what you're thinking is you wanna buy yourself at least eighteen months of runway?

Ashwini Asokan

14:20Oh, of course. Yeah, absolutely.

Nathan Latka

14:22So that means burn today would be something like $900,000 a month, less than 1,000,000.

Ashwini Asokan

14:27Way less than 1,000,000 you forget. Like we are a huge portion of the team is based out of India. 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 teams is based out of India.

Nathan Latka

14:44Okay. I get the reason I'm asking you just because you said you raised for eight, you like to raise for eighteen months of runway. So $17,000,000 18 is a million.

Ashwini Asokan

14:50That's about... Yeah. But that's over and above the revenue. Right? So I'm not gonna live off of my... Of just the fundraise alone. So the fundraise is like a combination of the 17,000,000 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 out.

Nathan Latka

15:06Yeah. Okay. Very good. And then, going back, right? So you said 35 customers north of $10,000 a month each that puts you north of $350,000 a month right now in revenue. Is that accurate?

Revenue Discussion and Growth Rates

Ashwini Asokan

15:19I'm not sure I'm ready to talk that. Unfortunately,

Nathan Latka

15:19Well,

15:22I'm not not trying to get you in a gotcha. I'm taking numbers you already gave me. You said everyone paid more than $100,000, some up to a million and you said 35 customers.

Ashwini Asokan

15:31Yeah. Some are some up to a million. Yes.

Nathan Latka

15:33Yeah. But you said everyone, again, I'm not trying to get you to gotcha. These are your numbers. You said north of $100,000 and some up to a million. So if I assume the minimum of $100,000 a year across 35 customers, that's north of $350,000 a month.

Ashwini Asokan

15:44That's right. But we do have, increasingly over the last, like say six months, folks in the mid market category as well as part of the experiments we're doing. But it is fair to say that we're looking at somewhere between 75,000 to 100,000 in terms of the average.

Nathan Latka

15:58Okay. When do you think you'll hit $350,000 a month? Do you think you do that this year or is it more like next year? It's a stretch goal.

Ashwini Asokan

16:04God. No. Like now.

Nathan Latka

16:05Okay. Got it. Fair enough. Good. And then where were you a year ago? Doubling year over year or more or less?

Ashwini Asokan

16:11We did four x last year. We went from zero to 12... Zero to one in about twelve months, a little over 12. And then we have been, we did a 4x right after that. And this year we're looking at roughly about three X.

Nathan Latka

16:23Just be clear, if you're doing like $300,000 a month right now, and you're saying you like, basically that's 4x year over year, you're saying you're only doing like $75,000 a month a year ago?

Ashwini Asokan

16:35No. So we're on year three right now. So we did four X last year in 2018 and this year we're on our path to doing about three X.

Nathan Latka

16:44Oh, got it. So you're doing about $100,000 a month a year ago?

Ashwini Asokan

16:48A little more than that.

Nathan Latka

16:49That's great. That's, I mean, look, that's healthy growth. And is most of the growth coming from expanding into the same customers or adding new logos altogether?

Ashwini Asokan

16:55It's even, it's both. And being an end to end customer, 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 comes up to like 30 to 40% of our revenue. Then there's a lot of new growth as well.

Famous Five: Books, Tools, and Habits

Nathan Latka

17:11Very good. All right. Let's wrap up here, Ashwini with the famous five. Number one, what's your favorite business book?

Ashwini Asokan

17:18You have something sitting there right behind you. No, Chaos Monkeys is a fun one, but I'm very recently reading,

17:27Ben Horowitz's The Hard Thing About Hard Things, like the fortieth time I'm reading that book, that's definitely an all time favorite of mine.

Nathan Latka

17:33And number two, is there a CEO you're following or studying?

Ashwini Asokan

17:36A, not a single one, but Katrina Lake is a pretty fantastic one to follow.

Nathan Latka

17:43Number three, what's your favorite online tool for building your company?

Ashwini Asokan

17:47Online tool for building my company. From an HR perspective or from...

Nathan Latka

17:52In in what way?

Ashwini Asokan

17:53Pay. Okay. Twitter. I hire 15 to 20% of my employees on Twitter.

Nathan Latka

17:59Number four. How many hours of sleep do get every night?

Ashwini Asokan

18:03Oh my god. This is a total shaming moment, isn't it?

18:08Not a lot. Probably about

18:12four to five hours. I've gotten better this year. I'm gonna be at seven by

18:16the

Nathan Latka

18:16Can

Ashwini Asokan

18:16end of

Nathan Latka

18:16I ask you like your situation, like married, single, kiddos?

Personal Background and Closing Reflections

Ashwini Asokan

18:21I'm married. My co founder is my husband.

Nathan Latka

18:25Okay. Any kids?

Ashwini Asokan

18:26Two.

18:27Five and nine. Yeah.

Nathan Latka

18:28All right. Two kids.

18:29And then can I ask Ashwini how old you are?

Ashwini Asokan

18:3237.

Nathan Latka

18:33Take me back seventeen years. What do wish your 20 year old self knew?

Ashwini Asokan

18:38What was that question again?

Nathan Latka

18:39What's something you wish you knew when you were 20?

Ashwini Asokan

18:43No. You know what? It's almost the exact other way around. I would say my 20 year old self was a professional dancer and a professional musician and so full of confidence and completely flying. And I would look back and go, oh my god. I hope my 20 year old self tells my 37 year old self today. It's it's all gonna be okay. It's the other way around.

Nathan Latka

19:07Guys, 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 $7 a month. So call it $300,000 a month right now in total revenue. That's up from just $100,000 a month a year ago. So nice growth rates. They've got about 2% gross churn annually on 30% expansion. So 128% net revenue retention spending call it

19:30like $10,000 and you get a new customer. So pretty healthy payback period. They've raised about $29,000,000, just closed a $17,000,000 round here two months ago as they look to continue to scale. Ashwini, thank you for taking us to the top.

Ashwini Asokan

19:42Thanks, Nathan.