Alex Svanevik, CEO of Nansen, on Blockchain Data, AI in Crypto, and Investing for the Future | Ep. 305

 

In an exclusive interview with cryptonews.com, Alex Svanevik, CEO and Co-founder of Nansen, talks about the launch of Nansen query and Nansen 2, the importance of data in blockchain, and the relationship between crypto & AI.

About Svanevik

Alex Svanevik is the CEO and Co-founder of Nansen. He has a background in artificial intelligence, with 10+ years of experience as a data scientist and management consultant before co-founding Nansen in 2019. Alex is also one of the initial DAO members of Lido Finance and PleasrDAO and serves on the board of WalletConnect.With an academic background in artificial intelligence and machine learning, Alex is also an entrepreneur with strong opinions on data-driven insights in cryptocurrency and blockchain. Alex has secured over $88.2 million in funding during his tenure. He has an MSc in Artificial Intelligence from the University of Edinburgh as well as a BSc in Cognitive Science from the University of Bergen (UiB).Alex Svanevik gave a wide-ranging exclusive interview, which you can see below, and we are happy for you to use it for publication, provided there is a credit to www.cryptonews.com.

Highlights Of The Interview

• Nansen is a blockchain analytics platform that enables crypto teams and investors to analyze billions of on-chain data points with essential market signals
• Data is one of the most important pieces of Web3 infrastructure
• How do AI and Blockchain Data mining converge
• Launch of Nansen query and Nansen 2
• The four C’s – Cute, Community, Content, CEO

Full Transcript Of The Interview

Matt Zahab
Ladies and gentlemen, welcome back to the Cryptonews Podcast. We are buzzing as always. Got to start off by apologizing for the lights. We are recording, not super late, but late enough. Normally, we got some nice sunlight on me in Mexico. I’m recording at 7:20 p.m. tonight because we have the one and only Alex Svanevik on the show today. He is a whole frigging day ahead of me in the one and only Singapore. We’re going to get into all this super pumped to have him on. The CEO of Nansen. You guys know what Nansen is. Alex is the CEO and Co-Founder of Nansen and has a background in artificial intelligence with 10 plus years as a data scientist and management consultant before Co-Founding Nansen in 2019. He’s also one of the initial DAO members of Lido Finance and PleasrDAO and serves on the board of Wallet Connect. Super pumped to have you on. Alex, welcome to the show, my friend. How you doing?

Alex Svanevik
Thank you, Matt.

Matt Zahab
Thanks for having me. It’s great to be here. Pumped to have you and it’s always super cool when you’re a whole day ahead of someone, you know, recording.

Alex Svanevik
I’m living in the future.

Matt Zahab
You’re living in the future. You were chowing down on some just a beautiful mackerel breakfast before we got started here. I just finished burritos for dinner. You just finished a good old brekkie. We’d love to see it. Before the show you and I were shooting the shit a little and you had a couple pretty awesome stories. I got to get you to tell those. But before that, we got a touch on your incredible little tweet about Singapore. You have been in Singapore for the last six years. I’ve never been. It’s on my to do list. Seems like one of the sweetest places on the planet. You touched over a couple good points. You can tell them better than I can. I think this would be a great place to start. Tell us why you love Singapore so much and how cool life is there.

Alex Svanevik
Yeah. So I’ve lived, I think in seven different countries. So I feel like you have a relatively good sample to compare, you know, Singapore with, I don’t know where to start. I think to me, it’s actually about values. You know, I, I really like Singapore because I feel like the culture here is very meritocratic first of all. And that’s how the whole society has been, you know, created since Lee Kuan Yew kind of started transforming this place from a swamp to a metropolitan city-state. And that’s probably a bit of an exact duration, but that’s at least how people explain it. So it’s very meritocratic. It’s very efficient, which I think most people know, but when you live it day to day, it makes a big difference. Like if you need to get from A to B, you can get a go check or a grab in two, three minutes, which is the equivalent of Uber, let’s say. And because it’s so small and because the traffic, you know, it’s typically not jammed but on stuff you can get from A to B in like 10 max, 15 minutes. And then if you, if you need to get anything done in the public sector, like if you pick up your employment pass or anything like that, it’s incredibly fast, right? This is something that was unusual for me as a European having lived in, say Spain or Italy, where you want to get like your ID card and you have to show up at 4 AM in the morning, this long queue outside, then you finally make it. And you learn that there’s something wrong with their system. You have to come back like next week or whatever it is. So it’s, I think it’s just very efficient. And then it’s interesting for people who are in crypto because it’s kind of getting that critical mass of a crypto scene here, which is quite exciting. Like I think some people, sorry, some places like Hong Kong where it’s a live is also interesting. And I love Hong Kong, but the crypto scene is a bit one sided and it’s mostly kind of the investors who are based there. Whereas in Singapore, I think you have both investors, you have founders of small protocols, companies. Then you have people who work in the big crypto companies like Coinbase, Binance, and so on. You’re based here. So you have a really kind of rich and diverse crypto scene that I really enjoy. I mean, I could probably spend the whole podcast talking about Singapore, frankly, but yeah, it’s a great place to live. I really like it. The weather is generally quite nice. If you like hot weather and it’s in a great location so you can travel to other great destinations like Thailand, Bali, Vietnam, etc.

Matt Zahab
So cool. Let’s jump right into Nansen here. When I first heard of Nansen, I mean, it was pretty close to when I got in the space not too long ago. I wasn’t as early as you were, but you and your team’s growth has been absolutely incredible. Kudos and massive shout out and well deserved to you guys. Before we jump into the whole thing, did you ever think that like you guys would literally be the behemoth of anything analytics and data related in the whole space? Like, cause again, you know, you had a, you left a good job to come start this in a risky industry. Did you ever have that hunch? Like we’re going to build the shit out of this thing and turn it into a monster. Was that ever a thought?

Alex Svanevik
Yeah, thanks for the kind words. I mean, to be totally honest, when we started Nansen, we kind of thought of it as a potential cashflow business. Like, I think that’s how we didn’t think, let’s go out with the spoil the ocean vision to become like a trillion dollar company. It was more like, hey, we know that there are certain unsolved problems in crypto, and in particular, a lot of the data was kind of either non-existing, the analytics were incorrect in many places. And there were just so many kind of basic analytical questions that you weren’t able to answer back when we started, in particular with regards to what’s happening on-chain. That’s what we are really good at. And so we thought if we just solve those problems, we’re probably going to have paying customers who want to answer those questions. And they’ll want to pay because investors at the end of the day want to make more money. So if we’re helping them make more money, then presumably they will be okay paying a subscription fee for the product. And so it was very much coming from a relatively humble place. But yeah, we did start growing very fast. Like we launched the product April 2020, we had our first paying customers the literal first day that we put up the landing page. And then word spread and we just started growing very organically. And then at the time, I was the only one working full-time on this project. And my other two co-founders were working part-time. And about six months later, we realized like this is turning into a real company. We need to hire people. You guys need to commit to this full-time. And so they did. And we raised a seed round so that we could hire people, even though we were making revenues, actually. But you still want to make sure that you have enough money in the bank, if things change, so that you can pay your employees and so on. So we did a seed round. We started hiring our first people. And then the next year, 2021, was incredible. And we did a Series A with A16C, we had a Series B with Excel and many other great investors later in the year. And yeah, I mean, some VCs we spoke to in 2021 said that we were literally one of the top five fastest growing SaaS companies that I’ve ever seen in terms of the revenue growth. So yeah, that was incredible. But it was also good timing with both DeFi really taking off. And so it was great. But it’s a good feeling for sure. And then you realize, actually, we can aim much higher here. And then you have to calibrate your vision and your aspirations, of course, which is a good thing, obviously. And then yeah, we’ve never looked back since.

Matt Zahab
I love that. Bit of a weird question here. You guys pull a shitload of data from, I mean, all the big boy, big gal chains. You pull data from over 250 million wallet addresses, which is absolutely bonkers. This is strictly my selfish curiosity here. Which chain is the easiest to pull data from and which chain is the hardest to pull data from? Which chain gives you sort of the sexiest and most enrichful and forward-looking, you know, trend esque data and are some you’re just like, oh, this is hogwash. This is nonsense. I’d love if you could sort of give us some gold on the pros and cons of pulling data from certain chains.

Alex Svanevik
I mean, I think those are two slightly separate things. I’ll answer first the version of your question, which is which one is the easiest or which one is the hardest. That’s a pretty straightforward answer. The easiest one for us is Ethereum, because that’s the one we’ve always started with, and we’ve developed the expertise to do that. It doesn’t have an insane amount of data volume, so it’s manageable with the block times and stuff. The one that’s hardest for sure is Solana. So it just has way more data. It’s not EDM, so it’s a totally different paradigm. But that’s why I say the questions you asked are a little bit different. So it doesn’t mean that the content for Hogwarts or that data is dirty or anything like that. It’s just that it’s very hard for us because it’s so different and the volume of data is so much greater. But we still do it because our customers want Solana data, and so you still do that. But I would say we have gotten insanely good at reading data from EDM chains. And of course, that is the dominant paradigm, if you will, of chains, like BNB chain, EVM, Polygon, Avalanche, SeaChain. All these different chains are all EVM chains. And so we’ve kind of sort of industrialized the ingestion of EVM chains to the point where if we decide to onboard a new EVM chain, we can do that in ours, in theory. Of course, there’s more work later with maintenance. You have to do attribution or labeling of the wallets that are active on the chain. That takes time. But the actual getting all the data into our database is pretty straightforward at this point. But it took many years to develop the technology to do it in such a streamlined manner.

Matt Zahab
And present day we have, you know, not crypto related, but semi-crypto related. Everyone’s still on the AI train. It’s left the station. There’s no chance it’s ever coming back. You are one of the few people who can actually chime in and who’s two cents and, you know, hands in the cookie jar we can actually listen to. You have an MSC in artificial intelligence from the University of Edinburgh. So, you know, I’ve asked a lot of people, what is AI going to do to crypto? You actually studied this shit. You know what’s going on. Especially as the CEO of Nansen, you guys are the bread and butter of data. How have you in particular, you and your team used AI to, you know, help pull data from all the different chains to help enrich your data sets, so on and so forth.

Alex Svanevik
Yeah, so we use AI in two primary ways. That’s our AI strategy at Nansen. The first one is that we use it to supercharge our product, right? So it allows us to build certain innovative features and also deepen our data notes in a manner that was not possible just a few years ago, right? So we kind of think of AI as ubiquitous throughout Nansen. It’s not like, here’s the one AI feature. It’s more like it powers our search. It powers the NFT price estimates that our machine learning created. If you want to get an estimate of your Pudgy Penguin, then we have a machine learning model that gives you an estimate, almost like I say, hello, this estimate. And it’s all machine learning power. And so, and then in terms of the attribution, the labeling and so on, that’s an area where we will be using AI much more going forward. But yeah, so the first area is just making the product better. The second area, which I don’t think is unique to us as a company by any means, and certainly not unique to the blockchain industry either, is using AI to increase our organizational productivity and our individual productivity. So this is kind of the, I guess this is where, if you read the newspapers, this is where many people talked about the implications of AI, like AI is going to take our jobs and stuff. I think in my experience, what ends up happening is that you just increase productivity quite dramatically. So if you are working with anything content related, right? It could actually be video, it could be audio, but often it’s text, of course, if you’re writing content marketing, if you’re writing Twitter threads, you’re writing research, we’re basically using AI for all of those different things to shorten down the process and just save time and effectively increase productivity in the sense that you’re getting more output with less input, right, and the input is typically ours. So the way I think about this in a very broad sense is that whenever you’re doing work, there’s sort of three primary things you do. The first one is that there’s a prompt, right? You have something like a drive, hey, I need to do the same, like writing down the name of the task or whatever. Then there’s a long process, which historically has been always from the most time, which is the production, like the completion of that thing, the tasks, and then at the end, there’s an element of quality assurance, like whatever I made, it’s like, it makes sense. Maybe you do that with someone else, you’re quality assurance someone else’s work. With AI, the interesting thing is you end up spending like most of your time only on the first and the last bit, which in a way are the two, that’s where like you spend the least amount of hours. And the thing in the middle, the production, that’s now takes like 10 seconds because the, or it can be like half an hour if you wanna iterate, right? Because typically you quality assure, you go back and then you try again and you kind of give feedback to the AI as you’re working with ChatGPT, for example. And so at Nansen, one of our goals this quarter is to just collectively spend 5,000 hours working with AI. And the reason we set that goal was I realized that a lot of people don’t actually have the gut reflex of trying AI first for a task because you’re not used to that, right? Like you’re used to just doing stuff yourself, but we have to train people to say like, hey, I’m writing a, I’m trying to make a list of strategic accounts that our sales team wants to go after, for example. That’s like, can you use AI to do that? And it turns out absolutely you can, like me and our senior manager of Radley Ops yesterday, we’re spending like two, three hours literally with ChatGPT building out a list of 500 target account lists to go after. And he saved us an insane amount of time just doing that, right? And so the surprising thing is that you can use AI and I would say in particular ChatGPT for so many things. And even now I’ve been using it extremely actively the last six months, even now I’m realizing every day that like, wow, it’s actually pretty good at this thing here. Like if I prompt it in the right way and if I give it constructive and clear feedback if it does deliver on my expectations. Anyway, so I think. If we get the team to spend 5,000 hours, that works out to about four hours a week per person, that’s 10% of their time, right? Then you will have built up a bit of a gut reflex to think like, in my area, this is an area where AI is great and super helpful. It increases my output by like 10x or 100x in some cases. And then once you get the next quarter, because we plan orders through objectives and key results and so on, OKRs. And when you get the next quarter, we can start looking at, let’s look at the outputs and the outcomes we’re creating with AI. But for now, I just want to focus on the input. It’s like, put as many hours as you can into the process of working with AI. And then the best is that good things will come from that. So yeah, so basically like those are the two areas, right? To innovate on the product, make a radically better product. And specifically for us, that’s about kind of creating great interfaces to the data on Linux powered by AI, as well as deepening our data mode. And then there’s the organizational productivity piece where there are many principles. Like one principle is, why AI first? Another principle is make AI a team member. Like you should literally think of AI as team members. Like, hey, did you invite this AI to the meeting? Did you share the documents with the AI, right? Did you give the AI enough context to be helpful, to solve this problem? You kind of have to shift your mental model towards this not being software, but it’s like another team member, which is kind of weird and a bit science fiction, but I think we are actually there where it makes sense to work with AI in this way. So yeah, it doesn’t answer your question on specifically AI for crypto, but that’s at least how we think about it.

Matt Zahab
I absolutely love that. You sort of fired me up there a little. I’m not going to lie too. I feel like you’re the kind of CEO where someone’s like, Hey, Alex, I need X amount of dollars for this AI subscription. You’re just like, you chuck the Amex at him.

Alex Svanevik
Specifically for AI, for sure. I mean, like the reality is it’s more expensive to not have a ChatGPT subscription than it is to have one. It’s like way more expensive not to have it because you’re ending up spending a bunch of time on stuff that the AI could be helping you with and doing a shot.

Matt Zahab
Do you know how many people and clients I talk to who still don’t use it every single day, who don’t have a GPT-4 subscription, where I’m just like, I can barely remember a year ago when this was not, you know, like I almost forget about life before it. And it’s one. Yeah, so you use it yourself. It’s in fact, every, I mean, it’s, it’s bookmarked. I mean, I don’t use the bookmark anymore because it’s just, it’s such a habit of just, you know, Google Chrome, C H A, boom, that just pops, you know what I mean? It’s just wild how it works. That’s a good sign. Yeah, shout out Sam Altman, OpenAI and the team. You guys are incredible. Nansen Query, this was quite the launch. I mean, just enterprise ready blockchain data, doing it all currently supporting Arbitrum, Avalanche Base, Bitcoin, Dash, Doge, Ethereum, Solana, Terra, you name it. You guys are doing, doing it all. I would love to read this and give everyone the lowdown, but you can do a much better elevator pitch than I can, so I’m going to throw the ball over to your end of the court. What exactly is Nansen Query and why is it so powerful? And I’d love you to explain how much help it is giving to big, large enterprises.

Alex Svanevik
Yeah, so the best story here is basically, we built the best on-chain analytics product for investors, right? And in doing that, we realized that, hey, we basically have built the most powerful data platform that powers this product. Why don’t we give access to that underlying data platform directly? It’s a bit like the kind of Amazon and AWS plane, right? Amazon builds a retail store, they have all the infrastructure, and then why don’t we just sell access to the infrastructure? And so that was the thought process behind Nansen Query. And we had many customers asking us to offer programmatic access to your data and so on. And so that’s really what Nansen Query solves. And we also realized that crypto is cool because you can get access to lots of data through APIs, often for free or very cheap. But the problem is that a lot of that stuff is not necessarily enterprise grade, and it’s not something you would want to kind of build your business on top of, whether that’s like products or trading algorithms and things like that. And so we had a real focus of making sure that this was enterprise grade, and we had the highest quality data, that we have unique data sets that you cannot get anywhere else, that we had extremely broad coverage of chains, and then also higher order things like DEXs, NFT marketplaces, and so on. And then overall, the platform itself was very performant with the best uptime and the fastest load time and things like that. So that’s how we ended up building Nansen Query. And I think where we’ve had the most success is surveying the kind of top tier crypto teams in the space, like an OpenSea or Arbitrum or Consensus, Binance, Coinbase, like the kind of really great teams that realize that maybe having like a data platform and having all these data pipelines in house is not a great idea because it just distracts us from our core mission, right? Like Coinbase is not a data company. You know, it wants to increase the economic freedom in the world and primarily, of course, they do that through offering a great exchange. And so instead of them spending a ton of time internally building out stuff, it’s actually much more economical to just buy this from us, right? So that’s the kind of basic premise of why we built Nansen Query and where we’ve had the most success. I also feel like it is a space where, you know, it’s great to have a few different alternatives for customers, right? You do wanna have kind of either free or cheap options for like hobbyists and so on. That’s not quite where we play with this offering. Like we figured let’s just focus on the kind of production grade and sort of enterprise tier customer segment. That’s kind of where we wanna play. And that’s where we think we will succeed the most. And then we will let other companies focus more on kind of the more downstream and broader pool of customers. So that’s where it is today. I think there’s still, and we support like 25 different chains. You mentioned some of them earlier. Like I said, we have unique data sets that are powered by, for example, our wallet label data, which makes it possible for people to create really unique insights that you can’t get anywhere else. And increasingly we are going to be focusing more on like the API endpoints surrounding this. So what we’ve learned is that, you know, we do have a user interface where you can just go in and write SQL queries, announce a query. You can create dashboards, charts, share them with your team, all this stuff. But we realized that many people actually just want to get the data where they are, right? So that’s why we added, well, like we have support for Google BigQuery, which is a data warehouse technology such that if you are already on that same technology, you can literally get all of our data sets in your data warehouse immediately. And so we’re exploring how we can do that with other data warehouse and technologies like Snowflake and so on. And of course, creating better API endpoints. But yeah, that’s basically what Nansen Query is. I think for those who are listening, there might be more investor types. So this is more like if you’re actually, you know, building a company, building a product, then this is a great product to explore.

Matt Zahab
Nansen Query’s for the Big Dogs, and Nansen 2, which we’ll get into is for the investors. And we’ll get into that in one second, but until then, we’ve got to give a huge shout out to our sponsor of the show, PrimeXBT, longtime friends of cryptonews.com and longtime sponsors of the Cryptonews Podcast. We love PrimeXBT as they offer a robust trading system for real beginners and professional traders. It doesn’t matter if you’re a rookie or a vet, you can easily design and customize your layouts and widgets to best fit your trading style. PrimeXBT is also running an exclusive promo for listeners of the Cryptonews Podcast. Use the promo code, CRYPTONEWS50, to receive 50% of your deposit credited to your trading account. Again, that is CRYPTONEWS50 all one word to receive 50% of your deposit credited to your trading account. Back to the show with Alex here. We got to get into Nansen 2. Last year, you guys launched Nansen 2. AI functionalities, which to my knowledge was sort of the big sexy part of the launch. I mean, who doesn’t love that? Just reconstructed from its foundations, smart segments, more signals, you name it. Walk me through Nansen 2 and how you guys launched that because that was pretty spectacular.

Alex Svanevik
Yeah, so I think, again, just to kind of go back to the backstory of why we went Nansen 2, it was actually started because we realized that the tech stack we had were giving us a little bit of headaches, both in terms of being able to shift new features, as well as the performance that I was talking about earlier was kind of giving us some issues. We felt like it wasn’t loading fast enough and things like that. And so what we decided to do was to rebuild the whole product from the ground up. Of course, we could still make use of lots of the great work on the data platform side of things, but even though we had some improvements we wanted to make. So the kind of impetus for why we wanted to create an obstacle was mostly around our own ability to just shift new features fast and also make sure our customers had a really snappy experience when they used the product. It felt a little bit clunky and slow. That was some of the feedback we’ve been getting from users over the years. But then when we decided to do that, we also thought, hey, this is a great chance for us to really level up the user experience more broadly and also to shift some of these innovative features that we had been dreaming of building for a long time that we had been struggling with because of the old tech stack. And so now from the user’s perspective, when you start using Nansen 2, I think especially if you’re familiar with Nansen 1, what you will notice right away is first of all, it’s just way faster and it’s like a hundred times faster in some cases. If you click on either you’re using a profiler, which allows you to look up a wallet or even a cluster of wallets or an entity like a Binance or a three arrows or Alavida or what have you, you can do that and it loads super quickly and it gives you that overview that people expect from Nansen 1 that you get the soothing capabilities that you want and it loads super fast. So that’s the first part. The second part is the user experience, as I said before, is just a lot more streamlined. So in Nansen 1, you needed to know which dashboard to go to if you wanted to do something and that was kind of inhibiting for a lot of people. It’s like, do I use NFT God Mode, NFT Paradise, like what’s the dashboard I need to be using to just answer this question? And we’ve kind of abstracted all of that away to the point where if you go into Nansen 2 today, you just smash command K, which brings us the search bar and you just input whatever it is you need. You paste in a wallet address, you write Pudgy Penguins or an entity collection, you write the symbol of a token, you write the name of an entity like a Binance or Coinbase, whatever, and we just take you to the right screen. So it feels like kind of a trivial thing, but it is actually a huge improvement in the user experience. You don’t have to think too much about how to get from A to B. Maybe there’s an analogy where we’re going back to the Singapore story on like we just want to make things very efficient. You don’t want this bureaucracy and a maze of stuff, you just want to go straight to the point and that’s what we helped users do. And then the last thing is the innovative features that I mentioned and the probably the two most loved features that we have shipped with Nansen 2 are signals, which is kind of like a feed. So if you don’t have a very clear idea of what you’re looking for, you can just go into signals and you get a feed almost like a Twitter feed and it just surfaces anomalous events from the blockchain. So like here’s a token that had 100 times the amount of centralized exchange inflow that it normally has. Maybe you should look at that. Maybe there’s something going on there.

Matt Zahab
So it’s gold nuggets.

Alex Svanevik
It’s like, I don’t know what I should be looking at today. Let me just check out the feed and maybe I’ll just find something interesting. And then you can drill down from there, right? So the mission of our company is to surface the signal and create winners in the future of finance. And so this is literally what that feature does. It just surfaces the signal for you because there’s so much stuff happening on chain, especially with 20 plus different chains that you support. So, and that’s AI powered as well. It’s like the stuff that the AI thinks you should look at because it is anomalous somehow is what’s going to show up in that sheet. So that’s the signal. The second feature is smart segments, which, you know, like I said, like you mentioned before, we have hundreds of millions of wallet labels, right? That’s one of the things that we are known for. But we also realized that we don’t want to be the bottleneck for people to create their own wallet labels and groups of wallets. And so we created this feature called smart segments where you can decide your own criteria of wallets. You can say, hey, I want to look at every wallet that made at least, you know, 10 ETHs and profits trading Board Apes. And you just put that in as your criteria. And now you get a little segment of the, let’s call it, you know, 80 wallets that did that. I support a little more, few hundred wallets that did that. And that segment, you can now profile them collectively in the sense that like, what other things are they doing? Which tokens do they own, NFTs, which transactions have they made in real time as a segment collectively. And you can pull that segment into, you know, the other parts of Nansen. Like you can filter using the segment if you’re looking at a specific token or NFT. And so, yeah, this is another, I think, super powerful feature that we have shipped in a basic form, but it’s going to get a lot more powerful in the next weeks. And of course, yeah, a lot of these things, like I said in the beginning, are AI powered, right? Everything from the search to signals, to of course, a lot of stuff that happens on the backend with regards to the attribution and labeling of addresses. Even I think the congestion of data will over time become more AI supported, because you may not want to have data engineers spend a ton of time writing kind of transformer code and parsing code. It probably makes sense to have AI support for that as well. That’s the summary of what Nansen 2 does. But it’s early days still. And I think if you’ve tried it, you kind of will see a material improvement from Nansen 1, but you should also know that this is early and we have a ton of really exciting features coming out this year for it.

Matt Zahab
Alex, you’ve been on a roll. I wish you had more time here, man. This has been too much fun. A couple more questions and we’ll wrap up. Success story. I don’t know if you can tell me or not. I know the listeners would absolutely love this, but someone along the way must have used Nansen to find a specific signal and made an absolute shit ton of money. And we, on behalf of all the listeners and everyone at Cryptonews, we would love if you could give us just a little tiny, incy story of maybe someone. You don’t need to drop names, but just like the Board Ape example you said, where someone found something, bet a shit ton on it, and made an even bigger shit ton. I’d love you could give us a little nugget of gold here.

Alex Svanevik
Yeah, there are a few different ones. Probably the most famous one is MEDCollector, which is a Twitter account. And he wrote a thread about how he made an insane amount of money flipping NFTs using Nansen. I can’t remember the exact numbers. I think it might’ve been something like 10 ETH to 800 ETH or something ETH flipping NFTs using Nansen. And by the way, just to be very clear, that’s, to his credit, he is the hero. We are just kind of the, like he is Batman. We are the Batmobile, right? Like he is the guy actually doing it. We’re just a tool. But the cool thing was he was not doing that on just one bat, right? He was doing it consistently and just grew the portfolio. So that’s incredible. And I’ve met them in person, which is cool. There’s also another story of one of our customers who I think put 500 bucks on a token that they discovered in Nansen and turned it into one and a half million dollars. There’s also a tweet that’s out there and we have it in some of our marketing material because it is pretty amazing. And then there are of course many other examples. There’s another one where there was a fund that had a lot of money, like hundreds of millions of dollars in anchor when the Terra thing was happening. And they had set up Nansen smart alerts so that they got notifications when liquidity was being drained from the curve pools. And because of those notifications, they also exited the curve pools and basically saved probably like maybe hundreds of miles, at least tens of millions of dollars were saved because they were able to get out fast enough. And they have told me that the smart alerts basically saved them.

Matt Zahab
They owe you a dinner.

Alex Svanevik
Yes, yeah. It’s not only kind of the moonshot shit coins that go 1000X. It can also be used for like defensive purposes to make sure that they don’t lose their money, right? So yeah, and there are a ton of other stories but those are three that come to mind for now.

Matt Zahab
It’s so cool. Alex, absolute treat. Thank you so much for coming on. This was a blast. I can’t wait to have you on for round two. This was too much fun and we barely scratched the surface. You also had some electric stories that you told me before the pod. And folks, we will save those for round two because Alex, I mean, you would be up there for one of the people to have, probably not one, but maybe one dozen pints with and shoot the shit over some crypto stories. But we’ll have to wait until next time. Until then, wishing you and the team all the best. Before you let us go, please let us all know where everyone can find you personally and Nansen online and on socials.

Alex Svanevik
Yeah, so the best is to go to www.nansen.ai to try out our products. You can also find me on Twitter, @ASvanevik, just look for a very cute Pudgy Penguin. You can also find Nansen’s Twitter account @nansen_aiSo thanks for having me, Matt. It was great to be here.

Matt Zahab
Hey, pudgies have been ripping. I know you’ve been calling that for a while, but no free ads on the podcast, but we’re going to give them one. Why do they ripen so much? What’s the deal with pudgies here?

Alex Svanevik
You know, I used to say three Cs, but it’s actually now four Cs, cute community content. For example, they have like 10 billion views on DFC and they have more than one million followers on Instagram. But the fourth C is also the CEO, Luca, right? Luca is a fucking amazing operator and one of the truly great ones in crypto and he’s like 26 years old or something. Really an incredible operator. I’m actually helping on a call with him now in four minutes. So it’s the four Cs. That’s why Pudgy is doing so well, I think.

Matt Zahab
Four C’s, I love it. Alex, thanks again, man. Really appreciate it, and can’t wait for next time.

Alex Svanevik
Thank you so much, Matt.

Matt Zahab
Folks, what an episode with Alex Svanevik, the one and only from Nansen, CEO and Co-Founder. Huge shout out to him and the team for making this happen. If you guys enjoyed this one, and I hope you did, please do subscribe. It would mean the world to my team and I, to the team. Love you guys, thank you for everything. Justas my amazing sound editor, you are the man. And back to listeners, love you guys. Keep on growing those bags, and keep on staying healthy, wealthy, and happy. Bye for now, and we’ll talk soon.