He pivoted at $1M ARR—then raised $120M. | Kevin Tian, Co-Founder of Doppel

Pablo Srugo (00:00:00) :
What was your ARR when you decided to pivot from NFTs to this world?

Kevin Tian (00:00:04) :
At that point, I’d say we just broke seven figures. So it’s not an easy decision, right? Because you had a business growing, but at the same time you had to accept the reality that, look with the way that market was heading and the ambition that we had about how do we really serve the whole world. We had to do something. We 10x’d our revenue that year and we had a big, big focus and pipeline on the new pivot, and the new market we were going after. Product market fit’s not a one moment thing and I know other folks have said this, but we’ve truly experienced this at Doppel. We got initial product market fit with our first products pivoted, right? And then it had to go get product market fit with our other products. Even to this day, we’re constantly expanding our platform, right? So we have to actually go get product market fit on the new products we ship and so you’re constantly actually evolving your product and constantly getting product market fit.

Previous Guests (00:00:56) :
That’s product market fit. Product market fit. Product market fit. I called it the product market fit question. Product market fit. Product market fit. Product market fit. Product market fit. I mean, the name of the show is Product Market Fit.

Pablo Srugo (00:01:09) :
Do you think the Product Market Fit show, has product market fit? Because if you do, then there’s something you just have to do. You have to take out your phone. You have to leave the show five stars. It lets us reach more founders, and it lets us get better guests, thank you. Kevin, welcome to the show, man.

Kevin Tian (00:01:24) :
Thank you for having me, Pablo.

Pablo Srugo (00:01:26) :
Excited for this one, man. I mean, you’ve been at it for just four years. You’ve raised over $120 million from some of the, frankly, most well known VCs in the world. Bessemer, a16z, SV Angel, and a bunch of others. And you’re doing something that is intrinsically interesting. Because if you talk to everyday people, not in tech, not in startup, about AI, I think one of the most recognized fears is this idea that you could impersonate anyone these days. I mean, you can create a video, it looks like anybody, sounds like anybody and what stems from that is this huge concern. And you’re building a product that uses AI to solve at least some of the problems that come from impersonating others. So we’ll get into all of that. Maybe as a first question, take me back a little bit in your history. I know you met your cofounder at Uber. What was it like in those early days? How did you guys meet?

Kevin Tian (00:02:17) :
Yeah, no, great question. I mean, it’s funny, we met at Uber both straight out of college. We were actually in the same cohort, July of 2016, and we hit it off pretty quickly. Because we both like basketball, actually. So we played, yeah, we actually played basketball at what is, I think, now called the KD Court in Hayes Valley and spent a lot of time together with those infamous 8:15 p.m. late night dinners at Uber. Just chatting about life and chatting about our vision for starting a company.

Pablo Srugo (00:02:45) :
And this was still the Travis days, right? This was before, right before Dara came in?

Kevin Tian (00:02:48) :
Yeah, this was still the Travis days. So certainly got to see, you know, that whole arc right from Travis to Dara and, certainly a lot of interesting years at Uber.

Pablo Srugo (00:02:56) :
What was actually, I’m actually curious about this complete tangent but I’m curious because I’ve spoken to people who were there after, maybe before. You were there, right at the peak end and through the transition. What was that like? And maybe the more precise question is, as one of the many thousands of people that worked there at that time. How did the change at the very top impact you? Was it night and day in terms of, not better or worse but just in terms of differences? What did it feel like day to day?

Kevin Tian (00:03:21) :
Yeah, I mean, so at the time I was an engineer on the dispatch team, right? And so, you know, to a degree, it was certainly several layers above me, right? In terms of that leadership change, but you certainly did notice a big change in terms of a couple things. I’d say one, the PR. When I had just joined Uber, you know, we were fresh out of college. Just constant PR articles and stories, for better or for worse.

Pablo Srugo (00:03:47) :
This is probably right when that, taxi video came out, no?

Kevin Tian (00:03:49) :
Exactly, the taxi video. Multiple stories just coming out constantly and then second, I do think, yeah, there’s a little bit of a change in tone of leadership, right? Because Travis, what he’s known for is being so hard charging, and certainly I’ve learned a lot of great things from him, and apply that to what we do today at Doppel. But I think Dara brought a different tone. Someone who’s an experienced CEO, right? And maybe a little more calmer.

Pablo Srugo (00:04:17) :
So you're there till 2020, you work at Lyft for a year, and then shortly thereafter you start Doppel. What leads to starting Doppel? How did that happen?

Kevin Tian (00:04:26) :
Yeah, it was a great question. So I think Rahul and I had always talked about starting a company and at the time this was 2021, right? So this was the depths of COVID, where everyone’s working remotely and everyone’s separated from each other distance wise, things like that. A lot of existential questions come up, right? Around, all right, what are you going to do in your life? And so 2021, I’d say, was perfect from a time perspective where everyone’s having those thoughts and conversations. And with Rahul, he had actually been pitching me on doing a startup together for a while. So I think it got to the point where it’s like, yeah, why am I not going out there building something with Rahul? And that’s really when the company started happening.

Pablo Srugo (00:05:08) :
Was it a specific idea that made you cross? What was the catalyst for you saying, okay, enough's enough. Now's the time.

Kevin Tian (00:05:14) :
Right, it wasn’t actually. I actually left Lyft without a specific idea at the time. I actually, at the time, Rahul was still working on a startup idea for mass consumer e-commerce stuff.

Pablo Srugo (00:05:27) :
Oh, so was he? So Rahul took the leap before you, like he didn't, he wasn't at Uber still?

Kevin Tian (00:05:32) :
Rahul's the OG, right? He left Uber 2018, and he had been eating glass for several years at that point.

Pablo Srugo (00:05:40) :
Oh shit, okay. So he was at it for like four years trying different things.

Kevin Tian (00:05:43) :
Exactly, exactly and then for myself. I left, I actually initially started in the real estate space helping just because I was so frust. It’s funny because my mother’s actually a realtor, but I have this thesis still very much that I don’t think that a buyer’s agent necessarily adds a ton of value to the process and so that was the first idea that I worked on called Ferry Home. So yeah, I left Lyft without necessarily having a clear plan and of course, again, Rahul had been doing it for years, just eating glass.

Pablo Srugo (00:06:12) :
And you started this company, the real estate company. You started right after you left Lyft? This is your first idea?

Kevin Tian (00:06:17) :
Yep, exactly and so spent time building that out, iterating with users. So that’s why I didn’t join Rahul at first and then I’d say by the end of 2021. Rahul and I had a good sit down together out in Vernal Heights. Just saying, hey, could we do something together? And what would that idea really be, given that we weren’t very successful beforehand?

Pablo Srugo (00:06:38) :
Let’s go deep on this phase because it’s one thing when you hear the stories of the serendipity idea, right? Like, you take Shopify as a classic one, right? He builds a snowboard store, and all of a sudden he has to build this infrastructure for e-commerce. People start pulling it out of his hands. It happens, or Facebook, you know, is totally different but a similar kind of serendipitous story. When you have two founders that come together for the express purpose of building a company, in a way it’s more interesting. Because it’s more like playbookie, or it feels like something that you could learn more from than just, yeah, this idea came to us and it exploded, right? What happens after that? Take us through the details of going from that conversation, yeah, let’s work together, to coming up with an idea.

Kevin Tian (00:07:21) :
There’s a great question. Well, so a couple things were happening at the time, right? One, he was actually roommates with one of the heads of research at OpenAI. So he got a good sneak preview of this thing called ChatGPT, right? And how large language models were rapidly accelerating. I’d say second, at the same time, there was a lot, a lot of momentum in the crypto markets, specifically NFTs. At this time period, OpenSea, for example, was the hottest company at the time, right? And so I think there were a couple of things that were happening there. We asked, all right, what are going to be the biggest problems to solve for? And very quickly, we anticipated, and that’s what we’re seeing today with AI. The biggest threat is really how easy it is to impersonate anyone or anything. And so whether you call that problem phishing, whether you call that problem fraud, whether you call that problem deepfakes, whether you call that problem counterfeiting, it’s just the idea that digital authenticity and digital integrity was at risk. And so that’s where we were like, OK, so then what does that mean in terms of maybe applying it to the NFT and crypto space? And that’s really where Doppel's start is, we spent a lot of time chatting with a lot of our ex-Uber colleagues. Who are at these hot Web3 companies and realized, they quickly told us, yeah, we have a problem with maybe fake NFTs, or we have a problem with certain impersonations happening. Things like that and that’s really where Doppel was born.

Pablo Srugo (00:08:47) :
So it sounds like you didn’t start with a specific problem or even a specific market or customer type. You went really high level, right? You looked at the trends and the big things at that time. I remember the first half of 2022, and crypto was still on the up and up for sure. And then AI was the other big piece. I mean, walk me through, you went kind of to the conclusion, which was, okay, phishing and impersonating others is going to be big. Do you just get there by just talking? How do you get to that subset of the problems that AI is going to create? Did you have a list of all these things that could be, and this is the one that’s interesting?

Kevin Tian (00:09:18) :
So I think it was the idea around, hey, look, digital authenticity and digital integrity is really what’s at stake. So we actually didn’t jump straight to phishing or fraud or something like that, right? It’s just the general idea of, okay, if AI gets really good, what does that mean? Well, we’ve seen The Matrix. We’ve seen the latest Mission Impossible movie where AI is a bad guy, things like that and it’s like, if AI is going to destroy the world. Maybe they just put us in this virtual environment, right? Or maybe they’ll just be able to manipulate us in whatever way through digital interactions. So I think that was the guiding vision and it very much continues to be our mission today, right? Is to protect the world from social engineering attacks every day. The formulation of phishing, social engineering, and deepfakes, that came over time, right? Because initially, alright, with that whole premise around digital authenticity, oh, let’s focus on the NFT crypto market because it’s so hot. There are a lot of new companies, which means a lot of early adopters that don’t have incumbent solutions yet and we had a lot of people from our network from Uber and Lyft right at those companies. So we could very quickly have those conversations with people and say, hey, how are you thinking about this problem? That’s how we discovered that there are deep problems around, in particular, the trust and safety teams for those companies and what they’re trying to solve. So we weren’t even initially selling to cybersecurity at first. We were selling to trust and safety. We then sold to legal and intellectual property teams.

Pablo Srugo (00:10:52) :
Yeah, tell me more about those early conversations that are super important because they’re very formative. I mean, you’re at a stage of your company where you could do anything. Because you haven’t done anything yet, right? What did you ask, and what did you start hearing? What were some of the threads that you pulled on?

Kevin Tian (00:11:04) :
Yeah, I mean, one of the ideas we had with VCs that became our initial direction was, you know, we chatted with some of the NFT marketplaces, like, how are you guys solving for digital authenticity? How are you solving for the fact that, hey, I could probably take one of your Bored Apes, mint my own token, and try to sell that? And a lot of regular people wouldn’t be able to tell the difference. And very quickly, one of those initial conversations was like, yeah, we’re trying to solve that problem. And, yeah, it’s not our core business, right? Our core business right now is just scaling up our marketplace. So yes, we’d pay for something if you did this, right? And that basically became our very first initial direction, was building this API.

Pablo Srugo (00:11:52) :
And was that your question? Was that your ultimate question? Because if you ask people about problems, they’ll tell you just about everything. Were you asking these guys, hey, would you pay? How much would you pay? What was the bar?

Kevin Tian (00:12:02) :
Yeah, we would ask, would you pay? We probably should have asked, how much would you pay, right? But we certainly asked, would you pay? And I think that’s a very, very important question to really be able to measure the value of what you would really be delivering for that particular customer.

Pablo Srugo (00:12:18) :
Did you raise money at this point or is just the two of you kind of bootstrapping?

Kevin Tian (00:12:23) :
That’s a good question. So at this point, we were actually applying to different incubator, accelerator, or whatever you want to call it, programs, right? And we were deciding between South Park Commons, Y Combinator, Pear Ventures, and a couple more as well. And so, I forget the exact timing of when the check arrived, but at that point we were committed to South Park Commons. And as part of that program, the Founders Fellowship, you do get some funding up front. It’s essentially a pre-seed.

Pablo Srugo (00:12:57) :
Did you get into YC as well?

Kevin Tian (00:12:59) :
So funnily enough, we didn’t because we ended up wanting to move faster in the timing of the summer cycle versus the winter cycle, things like that, right? We ended up just not waiting for that cycle to finish. We had two offers already for programs that would start end of January, early February, which is when Doppel was incorporated.

Pablo Srugo (00:13:20) :
What was the investment size from South Park?

Kevin Tian (00:13:22) :
Investment size at the time was $400k.

Pablo Srugo (00:13:24) :
How do you? Once you start hearing that this is a problem and they'll pay for it, do you, like, sign purchase agreements, do you take checks, or do you just start building first?

Kevin Tian (00:13:33) :
Yeah, so the very first conversation we had, we started building. We actually created a basic prototype API, sent an email saying, hey, we’re ready to show you what it is, and of course got ghosted. And the reality was he was just so busy at the time.

Pablo Srugo (00:13:55) :
And this is when, by the way? This is like summer '22?

Kevin Tian (00:13:57) :
No, this was still. In terms of the duration or the timeline here, I'm still talking January, February, right? So we moved fast.

Pablo Srugo (00:14:05) :
Okay.

Kevin Tian (00:14:05) :
We worked to get stuff done within just the order of a number of days and followed up. Things like that and so, that was a mistake. Compared to the very first contract we signed. For the very first contract we signed, we had the conversation with the customer. We talked about getting something commercially and, we actually asked the question, how much are you willing to pay? And we got to work on actually getting that contract together even before we built something.

Pablo Srugo (00:14:34) :
This is still for the same product?

Kevin Tian (00:14:35) :
We thought it was the same product. We discovered it wasn’t. But we thought it was the same product at the time. Same area, right? It was still NFTs, and it was still very much verifying, and looking for fake NFTs. But it was actually more from a lawyer’s perspective, who wanted to take down fake NFTs on another marketplace than, you know, a marketplace internally policing their own NFTs.

Pablo Srugo (00:14:57) :
And what's the time? When was this?

Kevin Tian (00:14:59) :
So that started happening already in, it was either February or March. So the timescale of all these conversations was basically multiple conversations per week, reaching out to everyone we knew in our network who were at these different NFT companies and getting intros one way in or another.

Pablo Srugo (00:15:16) :
How much was that first contract?

Kevin Tian (00:15:18) :
The very first contract we had at Doppel was for $5k a month.

Pablo Srugo (00:15:21) :
That's very big, especially with no credibility in terms of the brand and in terms of even a product out there. How do you make that happen?

Kevin Tian (00:15:29) :
So I do feel that we got very lucky and very blessed to meet someone who was a quick believer in us, right? Hey, okay, this group of founders, ex-Uber, they know how to code, they know how to build, would like a solution in this space and they’re a company that liked being an early adopter for stuff, right? Because they were a very new company as well. They were committed to investing in the ecosystem around NFTs and Web3. And I guess they liked us on the first call.

Pablo Srugo (00:15:57) :
Well, I guess my question is more, how do you stop them from saying, and I’m thinking about this from the perspective of a founder trying to do something similar. Which is, well, yeah, I’m super interested. I’m a hundred percent down to pay $60k a year, but show me a product and I’ll pay you. Why pay ahead of it? What’s the incentive for me? How do you make that? Or was it just that they were willing to do it, and you kind of got lucky and it happened?

Kevin Tian (00:16:17) :
Yeah, the latter. We kind of got lucky and happy. But it actually makes a lot of sense for the buyer as well, right? Because from the buyer’s perspective, no one had built this yet. No one had built solutions for NFTs yet, because it was such a new market. You want to pay so that someone invests the time and money into it, right? And it was a month to month contract, which is also a mistake, but it was a month to month contract. So there’s low risk on their part.

Pablo Srugo (00:16:42) :
What happens, fast forward a few months, like crypto starts to really tank the second half of 2022. What stage is a company at, at that point and what happens?

Kevin Tian (00:16:52) :
So I would say it still hadn’t really tanked significantly yet in the second half of 2022. Certainly some headwinds started happening, but we still very much had a large, and just to be clear, we still love our crypto customers today. We still very much have crypto customers today, but our product today is very different than what it was then. So we actually were still very, very heavy in serving our crypto customers. I think by late 2022, though something we had done well was realize, hey, we can expand the product beyond just crypto and NFT use cases, right? Because this problem around digital authenticity, even for the crypto customers, involves social media impersonations and fake websites. And we realized that because some of our early customers were like, yeah, we use you all for the NFT stuff, and we use this other solution for all the other digital channels. They said, well, if we could go for that, would it be valuable to not have to use two solutions? So yeah, if you could do it well, sure and that’s how we expanded the product at the end of 2022.

Pablo Srugo (00:17:53) :
And at that point, had you raised a seed round already? By the time you expanded?

Kevin Tian (00:17:57) :
Yeah, so we actually raised the seed round summer of 2022.

Pablo Srugo (00:18:01) :
How big was it?

Kevin Tian (00:18:02) :
It was a $5 million seed round with FTX and we wanted FTX because they were such a big name, right? At the time.

Pablo Srugo (00:18:09) :
Did you deal with SBF directly or how does that happen?

Kevin Tian (00:18:12) :
I did not, did not. So I never got to meet him directly, but had the fundraising happen, right? Same sort of thing, right? You work your network, and of course, South Park Commons is so incredibly helpful for connecting us to a lot of great firms and teaching us how to run a process, right? So we did the seed round in the summer of 2022, and by that point, that meant we were already hiring engineers. And so late 2022, that’s how we could accelerate a lot of that product development.

Pablo Srugo (00:18:40) :
How many people were you by late 2022?

Kevin Tian (00:18:43) :
We were five people. So two co-founders and three engineers.

Pablo Srugo (00:18:47) :
And why with $5 million did you not hire a lot more people? What was your thinking?

Kevin Tian (00:18:51) :
So the thinking at the time, right? Was, it wasn’t hiring that was our bottleneck, right? It was just doing more sales and very much at that stage, we were doing founder-led sales. In retrospect, I think that was absolutely critical, right? To get a feel for how to expand the product and how to pivot the company at some point in 2023. And so it wasn’t, hey, we need ten more engineers. It was more that we were still really establishing ourselves, figuring out product market fit, and figuring out what’s the vision for the product.

Pablo Srugo (00:19:22) :
We have tens of thousands of people who have followed the show. Are you one of those people? You want to be part of the group? You want to be a part of those tens of thousands of followers? So hit the follow button. What was the strategy for raising $5 million then? Why not raise, or just raise a lot less and minimize dilution?

Kevin Tian (00:19:39) :
Right, a couple of things. The strategy there was really, how much money do you really need to get to your Series A goals? What are other people doing for their seed rounds? And let’s add a little buffer because I felt like things were frothy at the time in 2022, and it was very possible that a winter was coming.

Pablo Srugo (00:19:56) :
So tell me, we're going to get into the pivot soon but tell me a bit more about what the product was in '22. Let's take a little deep dive there, without getting too technical, but how did it solve the problem that it solved?

Kevin Tian (00:20:07) :
So we basically built infrastructure that could scan for and ingest all the different blockchain transactions, right? And scan for potential fake tokens, and fraudulent activities going on. By the end of 2022, we had also expanded that to looking at websites, social media accounts, and things like that. That was really the final form at the end of 2022, and how we were serving a lot of these NFT and crypto customers who were dealing with impersonation, fraud, and social engineering.

Pablo Srugo (00:20:35) :
Maybe walk me through an example. I mean, you talked about the Bored Ape NFT before and somebody copying it, putting it on a different blockchain, whatever. How would that play out using your product? How would it find it?

Kevin Tian (00:20:45) :
Yeah so, for example, we’re consuming all these different blockchain APIs, right? And we suddenly see a token come in. We pass it to our AI agent, right? To say, hey, is this an impersonation? Is this a copycat? And it would say, if it said yes, then great, we’re going to go take that down. We’re going to issue a takedown request to OpenSea or MagicEden to, hey, shut down this NFT campaign.
campaign.

Pablo Srugo (00:21:12) :
And it would do that by just, actually looking at the image? Because this is still pretty early in the kind of AI evolution.

Kevin Tian (00:21:18) :
Yeah, so there's actually, 2022, there were already foundational AI capabilities, specifically with the CLIP model and how that could represent images as embeddings. Where it would represent an image with semantic meaning. So it’s not just, hey, it’s red here, yellow here, but it could say, hey, this is a tree, or hey, this is a person walking, right? And that’s really how all the image generation AI models were built, like MidJourney at the time and DALL·E. They were really just reversals of that same model. So with MidJourney, you give it a prompt and it generates images. Well the reverse is you give it an image, and it tells you the semantic meaning of that image.

Pablo Srugo (00:21:59) :
And this was like the first version of your product. You mentioned you started expanding to other use cases. What was the next use case that you expanded to?

Kevin Tian (00:22:06) :
So I’d say the next big pivot was really 2023, right? Because, basically we had initially focused on positioning the product for trust and safety teams and legal teams. You know, beginning of 2023, we actually shut down that very first API prototype we built, right? That we talked about. We actually shut down that API that could just tell you, hey, is this NFT real or not. We actually, we're still selling to legal, but we quickly realized that a lot of the people who were really pulling for Doppel and really willing to spend a lot of money on Doppel were the cybersecurity folks. And they were cybersecurity folks who faced this problem not just in the crypto and NFT industry, but in every single business in the world, right? Like, Pablo, I don’t know if you’ve ever seen anyone try to impersonate you or someone in your orbit get impersonated via email, SMS, or fake websites, things like that. But almost every company we’ve gone to has experienced that sort of problem and that’s when we made a critical strategic decision to say, all right, let’s actually focus on solving cybersecurity problems. Which means we had to change the product sum, right? Now we’re pulling in dark web threat intelligence, and we’ve really amped up the ability to automate fast takedowns of all these threats. And that’s really the evolution that happened in 2023.

Pablo Srugo (00:23:26) :
So that's the what? Which is good but I want to get to the how and the why. The first one is you said you shut down that API. I mean, what leads you to shut down that API?

Kevin Tian (00:23:35) :
Basically, conversations with me and Rahul saying like, hey, we actually have one customer using this API. We’ve been trying to get another customer to use this API, and they’re not willing to pay us that much for it. And how many NFT marketplaces are there in the world that would really pay for this, right? Because we’ve actually chatted with almost all the biggest ones.

Pablo Srugo (00:23:58) :
And why would you say that it wasn't a priority? Because on the face of it, it sounds like, you know, they should all pay for it. It's an obvious thing.

Kevin Tian (00:24:03) :
Well, if it was a big priority, right? You would see them spend a lot more money on it, and we’d have a lot more customers on it, right? And the reality was a lot of them were shifting towards in-house solutions because it was so custom as well, right? Every marketplace operates so differently. It’s hard to build a solution that works as well for Amazon as it does for Etsy, right? Because their internal databases are so different, things like that and that’s why we realized, hey, this actually isn’t a great market, and this actually isn’t a great product for growing a venture-scale business.

Pablo Srugo (00:24:37) :
And then you end up going down the cybersecurity route. Because you feel pulled from there. How did that pull happen? Where do you start seeing that at first?

Kevin Tian (00:24:47) :
Yeah, a couple of things, like existing customers realizing that, you know, those were the power users. Those are people who are referring us to other people and then there's also some top-down analysis as well, right? If you look at how many big companies there are and what industries they're in, cyber's always been one of the best in terms of, you know, really being able to scale a company to venture outcomes.

Pablo Srugo (00:25:10) :
It's actually crazy how many like, we have a lot of cybersecurity companies come on this show and it's always surprising to me how well they're all doing and seemingly yours is actually social engineering. Which is not an area I've seen that many in but you think about threat detection or what whatever it's like they all seem to say the same thing and yet they're all getting crazy traction. So it's an area that it almost seems like there's infinite spend infinite need.

Kevin Tian (00:25:31) :
Right, and that's just the reality, right? It's like cyber never goes away. Bear market, bull market and especially for us being a unique twist on the space, right? Focusing on social engineering when so many people are focused on maybe identity security, right? Or data security or cloud security. That's what really gives us our leg up today.

Pablo Srugo (00:25:49) :
When you mentioned that the bottoms up piece of that, which is that cyber teams were the power users. What part of your product were they mainly using and what value were they getting at that time?

Kevin Tian (00:26:00) :
Yeah, so the key piece of the product that they were using is they were really concerned around phishing and social engineering attacks, right? And so in particular, they really were leveraging the piece of the product to shut down domains, shut down things that were trying to steal money, right? Or steal data. So that's really what we ended up deciding the pivot towards, like, hey, let's actually really focus on that use case, right? Let's focus on that use case. Let's focus on pulling in more data sources to solve that use case and building more automated workflows to handle it at scale.

Pablo Srugo (00:26:34) :
So you told me about the original product around like, you know, finding fake NFTs, but how did this part of the product work? How are you finding fake domains or phishing attacks or whatever?

Kevin Tian (00:26:43) :
Yeah, I mean, so it takes a lot of the same infrastructure, funnily enough, actually, right? So large-scale distributed systems that could process a ton of data, use AI, right? Have AI agents actually be the, instead of asking the AI agent, hey, is this a fake token? You're now asking the AI agent, hey, is this a phishing website, right? And so, you know, there's a lot of product work, right? To integrate that data, to shape what it's looking at. But the underlying platform infrastructure is actually pretty similar. You got to be able to process a ton of data in real time, ask an LLM, what do you think about it? And then, you know, make decisions based off that.

Pablo Srugo (00:27:20) :
But just maybe fundamentally, it seems like intuitively, and I'm not saying a vibe. But it's one thing to find where all of the NFTs are being sold and just monitor them, and monitor all those blockchain transactions. But how do you find every single website in the world that might be spinning up somewhere? You know what I mean? And just check every single one against a potential, you know, scam.

Kevin Tian (00:27:40) :
Yeah, yeah, we can go very, very technical on this but the quick answer is you look at a lot of the DNS registrations, right? Every time someone spins up a new website, doppel.com, that's being broadcasted out to the registrars. Second is we do a lot of interesting stuff around our threat graph, right? Finding the websites because we pulled them in from search engine queries. If you go search JPMorgan, Bank of America, TD Bank, right? On Google search, what comes up there as potential phishing sites and scams, you know, we, the big power of our platform today is that we are multi-channel, multi-module, so we'll pull in, you know, we'll pull in Facebook accounts, too. And maybe the Facebook account actually links to a malicious phishing site, or maybe an X account was tweeting out a scam campaign, and so that's a lot of our techniques for discovering malicious campaigns.

Pablo Srugo (00:28:30) :
What was your ARR when you decide to pivot from NFTs to this world?

Kevin Tian (00:28:34) :
At that point, I'd say we just broke seven figures, low seven figures. So it's not an easy decision, right? Because, you know, you had a business growing, but at the same time you had to accept the reality of that, look, with the way that market was heading and the ambition that we had about how do we, you know, really serve the whole world. We had to do something but yeah, that's when we made that critical business decision.

Pablo Srugo (00:28:57) :
But fortunately, at least my understanding is you didn't have to churn those customers. You kept them, you just started adding customers that weren't crypto.

Kevin Tian (00:29:04) :
Yeah, so we still very much have a lot of great crypto customers today. I'd say some churned because maybe they bought us more for the original use case, first not and so we ended up aligning much better with the much larger customers that were more enterprise-focused and more enterprise-oriented. And that was an intentional decision, like, yeah, we are going to be a better fit for these customers that are really seeing scale, really seeing volume, and really want a premium solution in the space.

Pablo Srugo (00:29:30) :
Let's go deep on go to market, go to market tactics. You're selling to cybersecurity enterprise. They're probably bombarded with different solutions that they could buy. What do you do? How do you make that happen as you make this pivot?

Kevin Tian (00:29:43) :
I mean, I think it's still very much what it is in the early days, it's network selling. So you're selling, you're looking for connections through past co-workers. You're looking for connections through your investors. Maybe you throw on some advisors who can help. Maybe your existing customers actually, you know, before they joined this crypto company, they were at this tech company, or maybe they were at this bank, right? And so you're able to leverage that network as well. But it's a lot of network selling. You do some outbound as well, cold outbound to folks that you think are a good profile for you, given, hey, I've got existing customers that do something very similar to you. But that's really how you start bootstrapping that go to market motion.

Pablo Srugo (00:30:22) :
Maybe as a specific example, tell me about like the first customer, enterprise customer you landed for this new product and kind of how it all happened.

Kevin Tian (00:30:29) :
So our very first like big, big enterprise customer that came through working with Andreessen Horowitz.

Pablo Srugo (00:30:35) :
This is after they funded your Series A or before?

Kevin Tian (00:30:38) :
This is after they funded the Series A. So I guess enterprise, we did have some customers that were, you know, maybe smaller enterprise customers. So we could talk about that as well, but for the big one. Where we're talking about Fortune 500, that was through Andreessen Horowitz.

Pablo Srugo (00:30:54) :
So maybe, yeah. Let's talk about the ones, because they funded you. If I have this right, beginning of 2024, $18 million A, is that right?

Kevin Tian (00:31:01) :
Yeah, yeah, so they funded us. We announced it, I think, beginning of 2024, but it closed end of 2023.

Pablo Srugo (00:31:07) :
And at that point, you're already made this pivot and had a few million ARRs, is that right?

Kevin Tian (00:31:11) :
Yeah, we're in the middle of making that pivot. So we started getting some smaller enterprise customers. So, thinking about some of those initial ones. They came from essentially interest from our current customers, right? So, for example, a lot of our current customers, again, you work in the crypto space but the crypto space is so new. So that means you came from most likely another tech company or most likely another financial services company. So they would say, hey, Doppel's a great company, great team, would have liked this at my old company. So I'm going to recommend you to my ex-colleague, right? And so that's how we got our initial smaller enterprise customers late 2023.

Pablo Srugo (00:31:47) :
And then how do you raise? It's not that normal to raise a Series A, especially from a Tier 1, while you're going through a pivot. I mean, the normal thing would have been, you do the pivot, you prove it out. You get to like two to three million ARR, and it's all up to the riot, and you go and raise. How does a Series A happen?

Kevin Tian (00:32:03) :
I think it's a couple things, right? One, the reality is that the Series A, you still are very much betting on the team and the vision. And so, again, we were very fortunate to hit it off with the a16z team.

Pablo Srugo (00:32:16) :
But was it an outbound process or was it kind of like inbound, that became in preempted?

Kevin Tian (00:32:20) :
So it was an outbound process. So we actually decided to run a process for Series A. Again, South Park Commons was super helpful with that. They introduced us to folks that they thought could be a good fit for us and we were already in the middle of the pivot. We were already starting to get some customers that were going beyond the crypto space and were much more security-oriented. And so we were able to start referencing that as part of our Series A pitch.

Pablo Srugo (00:32:43) :
But yeah, maybe let's go deeper on that. First of all, why did you decide to do it then versus wait literally three to six months and just get more points on the board?

Kevin Tian (00:32:52) :
Yeah, great question. I'd say momentum, right? We were really starting to feel it from the pivot that, hey, there's actually a much bigger opportunity here. We felt like we had a good amount of traction from the ARR numbers and our growth numbers, things like that. It's strike while the iron's hot, right? And so that's why we decided to do it then.

Pablo Srugo (00:33:10) :
How fast were you growing at that time?

Kevin Tian (00:33:12) :
We 10x'd our revenue that year and we had a big, big focus and pipeline on the new pivot and the new market we were going after. And so I'd say this combination of those two things is what really drove our Series A narrative.

Pablo Srugo (00:33:25) :
Perfect. Well, let me, actually stop it there and let me end with the three questions that we always end on. When was the moment when you felt that you'd found true product market fit?

Kevin Tian (00:33:36) :
My answer to that would be, product market fit's not a one moment thing. I mean, I know other folks have said this, but we've truly experienced this at Doppel, right? We got initial product market fit with our first products. We pivoted, right? And then it had to go get product market fit with our other products. Even to this day, we're constantly expanding our platform, right? So we have to actually go get product market fit on the new products we ship and I think in cyber in particular. Well, really, I'd say all of SaaS now, right? People want platforms, not just point solutions and so you're constantly actually evolving your product and constantly getting product market fit. So I'd say there's like individual moments of product market fit for maybe individual products. But you actually have to go earn product market fit every day, like even from a go to market perspective, right? So like, hey, let's go get that brand recognition in Europe now. Or let's go get that brand recognition in Asia and so I think that's one of the probably most interesting things about being a founder is that, like, it's not just one moment, you actually have to keep innovating and keep iterating and keep pushing the pace, even as you scale.

Pablo Srugo (00:34:37) :
And was there any time, especially in those first few years where you thought maybe things wouldn't work out and maybe Doppel would just fail?

Kevin Tian (00:34:44) :
Probably like subconsciously, but you just don't think about it that much, right? Because the focus is, hey, how do I just get that next deal, right? And how do I build that next feature? And you're so busy in that existential battle, you're not thinking about, oh, we're going to die or we're going to fail. You're just thinking about, how do I just get that next step done?

Pablo Srugo (00:35:03) :
Perfect, and then last question, what would be your number one piece of advice for an early stage founder that's looking for product market fit?

Kevin Tian (00:35:10) :
I think it's, you know, actually one of our cultural values, but it's moved really, really fast. Even if you don't know what you're doing, even if you don't have the market yet that you want to go after. I truly do believe, and I know Brian Armstrong has a phrase around this, right? Action produces insights. So focus on that next step, right? Like, hey, if you don't have any conversations going with customers, go figure out how to get that next customer conversation, you know, whoever through your network. If you need to go build something, get to coding that day. Or of course, if you're doing a non-software product, like, get to building that day. But I do think, you know, it's important to do a lot of reflection and exploration, but you got to move and you got to move with high urgency.

Pablo Srugo (00:35:54) :
Perfect. Well, Kevin, it was great having you on the show, man.

Kevin Tian (00:35:56) :
Thank you.

Pablo Srugo (00:35:57) :
Wow, what an episode. You're probably in awe. You're in absolute shock. You're like, that helped me so much. So guess what? Now it's your turn to help someone else. Share the episode in the WhatsApp group you have with founders. Share it on that Slack channel. Send it to your founder friends and help them out. Trust me, they will love you for it.