NEAR Top Or Supercycle?🚨SVRN CEO Sal Ternullo INTERVIEW

0:00Right now at Subway, try the $4.99 sub of the day. Get a different 6-inch sub every day for just $4.99 each, like Meatball Marinera on Mondays, tuna on Tuesdays, and the BMT on Saturdays. It's a different 6-inch sub every day, packed with protein and your choice of chopped veggies for just $4.99 each. Or make it a meal with chips and a drink for just $2 more. But hurry, it's only for a limited time, and only at Subway. At participating restaurants, prices higher in Washington, Alaska, and Hawaii, and on third party delivery, add on taxes and fees for delivery additional. Is near protocol the only crypto AI play that is worth anything today? Well, we're going to break it down for you guys and get into it a little bit deeper. Before we get started, I do want to thank our sponsor today, and that is Proton Mail. You guys should be getting into security. And the reason is because Proton Mail is doing a fantastic job at protecting your privacy. This is the go-to place to get privacy set up for yourself, and you can do that starting with email. So, begin there if you want to do this for your business or your personal account, very

1:02easy to do. And one of the biggest things you can get into is, of course, Proton Unlimited. Proton Unlimited gives you a whole slew of things you can use, including mail, calendar, VPN, also getting drive. It's almost like a Google replacement. And the best thing here is you get sheets and also password protection. This is one of the best tools out there for security, especially in times like this, when there is so much junk and scams coming through your mail right now, use Proton Unlimited, use our link down below to get a little bit of a discount. A little bit of no, we sent you. If you look at the charts, I'll kind of start with that before we bring on our guest. And as you can see near protocol on the weekly, this has had a pretty good run all the way down here from training around 94 cents up to a little bit over 480 right now. And after this last week of a retracement that we've seen in pretty much everything. And if you look at one of the biggest players in near, especially in reference to holders,

2:02this is SVRN holding near. And when you look at digital asset treasuries like this, this, of course, is one of the ones that we're going to be talking about today. And we'll have one of their representatives on to break this down. Some of the things that you have to consider is if you're trying to look at a near or an AI play and near might be the one one thing to consider is this. And that is how it is positioned is one of the only tokens that really position in all three of these major macro trends that are now overlapping. And that, of course, is AI privacy and then revenue share near sets in the center of all of those things. So quite a bit. We wanted to bring on Sal Ternolo, who is a managing partner over at, of course, SVRN. Great to have you. Thanks, Sal. How are you? Thanks for having me. I appreciate it. All right. So we've got to get into a lot around near in general. And we're going to, we will address some of the most recent news today in, in today's video. But I want to talk a little bit on the sense of an AI play in crypto.

3:05When you think about near, obviously you guys believe a lot in this project. Would you say that it is the only AI play in crypto right now? I mean, there's a diverse market of, of players that are looking at how decentralization can play into solving some of the problems that we see across different AI workflows, whether that's in the process of training models on a distributed basis, in the idea of, how do we imbue ownership of weights in models to users? And where near really plays in this is, how do we bring some of the principles around privacy and confidentiality that they've pioneered on the layer one blockchain side into the AI space? And so, what they're doing on the private infrancide right now is, is extremely exciting and look forward to getting into it. To your point, let's get into it. I want to go into the first thing and that, of course, is intense. And this is something that I think, maybe some of our viewers don't completely understand what near-intense are. Can you explain it to us?

4:05Give us a rundown on this. Yeah, I mean, near-intense has been the most exciting product in the near ecosystem over the past 18 months, clear product market fit and scale now, processing more than 32 billion in volume. But I would think of near-intense as the easiest mechanism to facilitate an intent-based outcome. And so, a user says, I want Bitcoin. I want to swap my USDC for Bitcoin. How do I actually facilitate that behind the scenes is how intense architecture works. And so, it basically abstracts from the user all of the technical complexity. They just express their intent and that intent is fulfilled by a network of solvers who offer the best execution and price. And so, abstraction of all the complexity of bridging, swapping, et cetera, and give me the outcome that I want. All right. So, with that being the case, when you think about, I guess in general, an average user of this, do you feel like this is something that they themselves,

5:06are going to understand versus what does it really do for me? Is this translating to the average buyer of near today? Yeah. I mean, the average buyer of near today, how they experience intents is whatever app they're using, whatever wallet they're using. If they're swapping within that application, they're likely using their intents. And it's behind the scenes intentionally what the objective is to get the best user experience behind that. I want Bitcoin or I would like to swap my USTC for ETH. Yeah. I want, okay, so that's good. I want to go over to IronClaw because this is something also that I think needs a little bit more explanation. Give me a rundown on how this works and how it benefits the ecosystem. Yeah. So, IronClaw, you're probably familiar with your audience is familiar with OpenClaw and kind of the rush towards the harness space that played out in the beginning of 1926. Ilya and the team looked at OpenClaw and said, this is riddled with security issues that will ultimately compromise users' privacy.

6:08They're credentials to different types of apps and surfaces. And so IronClaw is effectively a blown up and re-architected OpenClaw harness that allows you to have security over your credentials and privacy and your interactions. And I think we've seen this kind of secure harness space take off. There's a number of players in the category. But that is very much what IronClaw was aimed to do was to re-architect OpenClaw and design it in a manner that gives users better security. How functional is this right now? I'm looking at just all of the elements that it can go into. You can kind of see the full layout here in BoxTria, monitoring, prep assistant, team chat operations. How usable is this today? Yeah, it's live and usable right now. I think what you see is that the user segment that actually adopted OpenClaw or me is these different types of harnesses. In many ways, we're kind of prosumers. They were users that were pretty hands on and sophisticated in AI.

7:10And what I think you'll start to see over the next several months is components and parts of IronClaw being delivered in a seamless user experience behind apps like Ndeer.com. We're similarly too intense. You don't need to understand anything about intense. You just have to have a great user experience. So I may in natural language say, I want to swap my USDC for ETH when ETH hits 2500 bucks. And IronClaw behind the scenes facilitates that alongside intense. This could be big then. If this gets role, I mean, if you get some adoption here, this could be a major because we're seeing more use case, especially on personal LLM or AI in general language models. Do you think that that is going to pick up and compete with things like news or some of these other platforms that are rolling out these AI computers in the cloud? Yeah, I do very much so. And I think it's really about the convergence of these different product pillars. So we talked about intense IronClaw.

8:10And what's actually powering the privacy behind IronClaw is private inference. And so the technology stack focused on confidential computing where you can interact with open models and have your prompts be fully protected and confidential, have the outputs be fully protected and confidential. And as a user, be able to prove those things. And so even with Muse moving in the direction of kind of user privacy and security, you still have transparency of what's happening to Facebook employees. Near is designing in such a manner where even the people that are building in the engineers and the operators can't see what's happening in those interactions. So that's a good point. I think it's super powerful. Yeah, for sure. I want to go over to near revenue when you look at overall intense and TVL on this, been climbing. But on the daily change, this had a bit of a retracement here. What happened to TVL? Why did we see this reversal? Yeah, this morning, I'm not sure if you were tracking it, but there was a security event

9:13on intense, which I think likely was the driver of TVL dropping this morning. And so there was a compromise of an underlying infrastructure component. It resulted in that $3.8 million estimated loss. I think the incident response process around that from the team was great. Communication was very clear. And ultimately, a commitment to make all users whole in a very, very timely fashion. These types of events are inevitable in a public system. And so I think it's really about how do you control them, how do you respond, and what do you do to make sure that users are always made whole? And I think they covered all those bases today. When you, okay, so obviously we see damage control with projects a lot when they're trying to deal with something of this nature. The other area that I'm always concerned with is exposure. Obviously, you could see intense right here and just the relationship in terms of Z-Cash. Is, do you feel like, I'm sure you don't feel this way, but I'm sure the market is looking at it and they say, hey, is near a little bit too exposed here in reference to Z-Cash?

10:16I think Z-Cash has been a great partner over the past year. But if you've noticed over the last several weeks, we just announced a partnership on the intent side with OnDote to support more than 400 tokenized assets. And so the dependency and kind of volume that we've realized on Z-Cash trading pairs is going to scale beyond that into not just digital crypto assets, but also tokenized assets as well. And so I think that dependency or kind of like single supplier relationship risk at pointing to is naturally going to all the way. But I do refer, you know, in terms of Z-Cash interactions in exchange, near intense is a great solution. And so I expect it will continue to have high volumes, but I do expect the volume mixed to diverse by over time. Yeah. I want to jump back to the AI hack side of things. In terms of the market in general, I'm not just talking about near. We've seen a lot of exploits over those last six months. The likelihood is this could accelerate, or maybe it's just social media that it amplifies these exploits.

11:16But do you think that the market is really prepared for the kind of potential exploits, especially if you look at the agentic issue that's being faced around all sorts of deployments out there, whether it's anthropic or open AI or many others that could get into this, are you prepared? Do you feel like near is prepared for this? Yeah. I mean, in terms of the market near is one of the most well prepared projects and has been thinking about the future risks from a cybersecurity perspective to public blockchains and smart contracts all the way back to 2019, 2020. And Ilya's co-founder Alex Skidnaf has been focused on formal verification as a potential solution to have basically math proofs over security properties of different types of applications. And I think inevitably you will see the market move in this direction where the advancements in AI pose additional cyber risks. And then we start to build new tools and technology that give greater assurance over security

12:18posture. And yours been at the front edge of that curve in the Web 3 space, but also candidly across the Web 2 cyber landscape as well. I want to go into another area. And that is where we're seeing platforms. In some cases, DeFi, we've seen all sorts of apps that have moved into bank-like activities. And it's not that it is a bank, but it's looking more and more like a bank every day. You guys of course have launched a very similar component right here. And I want to scan down here on the page and notice your money. Now, it seems that you've got where you can swap. You can do SINs, invest in RWAs, earn on the assets, and then eventually act almost as if it is a bank. How soon is that before we see those kind of things coming in terms of features? Yeah, so if you look at near.com as an application right now, it effectively offers the types of features that you experience in a bank to your point, but in a non-custodial manner, where the user controls their assets with no centralized third party involved.

13:20And so today you can swap assets, you can earn on assets, you can trade perpetual futures contracts on hyperliquid, for example. And very soon to the point that you're alluding to, there will be a card that goes in pairs with this account. And so you can actually spend from that non-custodial surface into any traditional kind of point of commerce. What about partnerships? Because this is typically the on ramp for most of these platforms to go in this direction. I know you guys are partnered with Venice. We had the Venice founder on not too long ago talking about that. You guys can go back and watch that video. It's an interesting view of, I guess, privacy-based AI usage. Are there other partners out there that are helping you kind of ramp this up? Yeah, I alluded to this before on the tokenized asset side, but just last week a partnership was announced with Ondo, which will present through this same experience in near.com and through near intense the ability to hold one of 400 tokenized equities inside of this

14:21account. By swapping anything, it's not just digital assets. It's swapping tokenized equities, tokenized money market funds. All of those products are available. And I think the ondo partnership is going to be kind of a flagship moment for the year. All right. So a couple of things I want to showcase here. One is this is on your website. This is a breakdown of revenue share. This was something I was looking at and trying to understand it. Can you explain how this works? And for many of you guys can go out to SVRN.net. You can kind of zone in on to what I'm looking at here on screen. But it shows the universal swap fees, distribution channel, et cetera. Explain this to me a little bit. Yeah. So effectively, there's a revenue mix. And depending on where a transaction is processed through, if it's through near.com, which is kind of the first party application built by a few slabs, there is a 20-bit take rates that cruise 100% to the protocol, meaning through buybacks of near tokens, all of that

15:23value of cruise there. OK. I was alluding to as well. Many users may use near-intense and not actually know that they're touching it. So for example, you pointed to ZCASH. A number of the ZCASH retail wallets have integrated near-intense as a distribution partner. And in the context of those distribution partners like Zodal or like Ledger as a hardware wallet provider, there are fee share arrangements set up where the basis points on the transactions are split between the distribution partner and the near-bidac system. And so depending on the channel that the transaction occurs, there's a different monetization and value-cruel mechanic to near. You think a lot of other projects are going to get to this phase where they really start to do revenue shares to amp up their market and some of their own communities and kind of go in this direction. And here's been somewhat of a leader here. Yeah, yeah, I totally agree. I was just on a conversation with Matt Hogan from Bitwise prior to this. And over the last six months, we've kind of seen this revenue meta where hyper-liquid,

16:25in particular, inspired a number of projects to really think hard about value of cruel to the native token. And near was right behind them with intense proving product market fit, scaling in volumes and monetizing for the token holders benefit. And so I think the market will continue moving in that direction. Projects that are focused on value of cruel to token holders are outperforming noticeably in the top 20, but also beyond that. And I think that trend will continue as this bull market ensues. I want to look at liquid staking because this is another issue that we obviously have seen with linear LNR. You can kind of see it. Where is the best place right now to liquid stake near? Yeah, there's three different liquid staking protocols that have achieved scale in the ecosystem. There's linear. There's metapool, ST near. And then there is R near from Rhea Finance, which is effectively an aggregation of the different defy Legos between exchange liquidity pools and lending.

17:26And so those are the three kind of dominant liquid staking tokens in the ecosystem today. I'm kind of curious for our audience that are watching this right now. How many of you guys are liquid staking today and you don't have to give me the ass to just let me know if you are down in the comments. Do you think this is going to be something that investors start to really act on in the future? Yeah, I mean, liquid staking tokens are an interesting way that allows you to get protocol and yield, but also use the asset at the same time. And so oftentimes you see users who want the yield, but also want to use that asset as collateral to potentially take leverage and buy more of the underlying or use the dollars or stable coins that they're borrowing in a tax optimized way to pay for things in their daily life. And so those are generally the two kind of directions of travel I see with LSTs is I want the yield, but I also want that collateral asset either to take leverage or to think about tax planning around utilization of the stable coins I borrow against it.

18:30Yeah, well, and I think the point you're getting at is that the opportunity for this getting into mainstream is probably much bigger than I think a lot of people really understand. You're sitting at right now, what are we at? 6.3 billion in market cap on near protocol. What do you think this potential is for this project right now? Yeah, I mean, I think today when you look at the valuation 6.3 billion, the majority of investors, both retail and institutions are underwriting near intense volume, revenue and buybacks to near token. And they're looking at the entire AI products suite as effectively a free call option where you can underwrite the network at this valuation today on this one product vertical that we know well. And then you have the upside asymmetry for that call option if private inference or one of the AI products takes a similar trajectory in terms of growth and product market fit. And then finally monetization to the token, you have a significant upside event.

19:31And so my view is that as the user adoption and kind of consumption of the AI products suite scales, we will see a fee switch come on that side. And that will very likely be the next reprising event where we see the market cap expand materially. Okay, you're danced around it. How much of a growth potential are we talking about here? Yeah, I think we're we're we're going to see near in the top 10 by the end of the cycle. And so we can put benchmarks that's 25 billion. I think we're somewhere between the three to five X assuming we prove product market fit and scale on the near AI side, right? We're 17 today. I think the top 10 is what? All right. Hyper liquid at. Yeah, hyper liquid at 22, yeah, 22 billion right now. So you're at seven near is at 17 billion at 636, 6. And Zcash right above that at number nine at 22 almost 23 billion. And then you move into Toronto, Salana land, which is significant. So that's a big move overall.

20:33I'm going to take that one and take a look at this. So is there anything that you look at on the roadmap or anything within the AI trade? Because this is always something that I think traditional finance is worried about right now. And that is a potential unwind. Are you at all concerned about some sort of grace one or an impact on the market that could affect this in the near term? And I'm talking about next 12 months. Yeah, I mean, I'm generally concerned about kind of the grace one event on the centralized frontier lab side. It's going to be very interesting to see how these IPOs go over. But I think the trend and direction of travel that really started without car fun, C and VC talking about AI sovereignty in the context of enterprises is a massive tailwind to all of the products that MIR is building on the AI stack. They're designed to enable both user and business sovereignty, privacy, confidentiality around their data and information and edge. And so I do think it's possible that we have some type of shock events on the centralized

21:35AI side. But I think ultimately, despite whatever short term impact that may have on AI related tokens in the kind of crypto space, that would be a driver of adoption and then ultimately repricing on the near side. Interesting. Well, I mean, if you look at just the interest by region right now, I'm looking at privacy, flock and data and data privacy, all, of course, on significant up trends right now here on Google trends over the last 25 years. It's been a spike specifically here right around 2025 and started to move specifically toward this direction, which NIR has been focused on for quite some time. So you may be exactly right here as there could be some big benefits to the upside here. Hey, Sal, thank you so much for coming in today. We appreciate the breakdown learning a little bit more about it and where NIR is heading. So thanks for stopping in. Of course, thanks for having me.