Rob Viglione, CEO of Horizen Labs. Welcome to the show. Thank you for having me, Peter. Very happy to be here. I want to talk a lot about ZK today and the cool things that you and the team are doing. Before we do so, I'd love to hear about your background, how you got into crypto. I believe from some of the research I've done, you've been in it quite a while. And so I'd like to hear from an OG and how you got into it. It's funny to think in OG terms because I think whenever any of us get in, like we always think we're late. So I got in myself back in 2012 and 2013 in Bitcoin. And really it was Bitcoin back then. And I got involved really from the idea of I loved economics and I love the idea of experimenting with money. But then where it took me, I was actually living and working in Afghanistan at the time. And I started evangelizing Bitcoin in Afghanistan. I think I was probably the first person to do that. I regret buying some things with Bitcoin back then. But in any case, it made me realize it sort of shaped my worldview on where crypto is transformational for humanity, really in places where we don't have very well-developed capital markets or financial systems. And it kind of went from there, rolled into my PhD, I did my PhD in finance, dissertation in crypto finance, taught a couple of courses on blockchain and crypto finance. I then launched my first project back in 2017 called ZenCash with Zen, cryptocurrency that's out there on markets, actually very well traded. It was a privacy coin. It was actually the third ZK project in the world, on chain, I mean. So really proud of that and actually resurrecting that project in some really interesting ways. But I think in terms of ZK, I think it's a technology whose time has finally come. That's awesome. You bring up two things I want to go a little bit deeper into. You mentioned Afghanistan. Were you in the military at the time? So I was supporting the military at the time. I was an Air Force officer prior to that as a physicist and mathematician, which is kind of strange to think of the military hiring scientists like that active duty. But I worked in what is today called the Space Force. Back then it was Air Force Space Command. That's awesome. In the last couple of months, I've met with a number of folks that were veterans, two, from the IDF, Israeli Defense Force. And I love asking questions around what they learned from the military that helped them in their journey as an entrepreneur. And I'd love to ask you the same thing. It's a great question. would say probably the thing that I personally take out of it and what I love hiring veterans for is resilience, especially when you look at these crypto markets and the insane ups and downs, it's actually really important to be able to keep a cool head under fire and be able to just operate towards an overall mission. I think that's the biggest lesson that I got out of it. And it's actually, can't count how many bear... variable cycles I've been through at this time, but with the recent market volatility, it's a little reassuring that we have people who can actually just operate under fire. It sure teaches you something about perspective, doesn't it? Sure does, exactly. mean, as much as our emotions run high here, you put it in perspective on where are we in life, how lucky and fortunate we are to have this opportunity to build in this amazing new industry. It's kind of humbling. Yeah. You mentioned you feel you kind of regret buying some things during that time with Bitcoin. I don't want to go into it, but that makes me, you know, it's a curious thing to say. But would love to go into, you know, some of the, what are you focused on now in the ZK space? Yeah, just to quickly touch on that point, because we actually had an amazing conversation before we started recording. I we might as well just hit record. I was lamenting that I bought some things with Bitcoin back in the day. This was like 2013. I remember buying cigars like in Afghanistan. There's not much to do after work. So we're sitting around campfires smoking. I bought a watch. It's a nice watch, like with or without Bitcoin, but it's actually like way too expensive of a watch now that I ended up back, this is 2014, Bitcoin prices by nothing. These are things, I mean, the house that I live in, they're partially subsidized with crypto. was, you know, sold to buy it. You know, these are those things where you have to make a decision. Are you going to be kind of an active community member where you want to see these kind of like virtual economies evolve and you want to like actively participate? Or do you just want to hodl for the long term? And I've always straddled that in the sense where like I want to be actively participating and using the cryptocurrencies to actually create this like, you know, you know, a virtual economy that we are. Yeah. No, I've kind of gone through the same kind of like buyer's remorse kind of, you we bought a family van and of course we bought it with, you know, I sold crypto to do it. And it's like the most expensive family van in the world. you know, but you know, the kids are comfortable, they're safe, my wife's happy. And so I guess that's what matters. And I have to think about that versus the, man, I could have, you know, that could have bought something else way more. But. So let's focus on, let's kind of transition to what you're up to now. ZK is a very hot area. It's been around for a while, but has kind of struggled to find use cases. But I'm seeing, at least in the last several months, like lots of projects are now really, really kind of ramping up in the ZK space. Do you think now is the right time for it? It sure is. Yeah, I think one of those things we were talking about before we hit record was it feels like it's a technology whose time has come. And I think in the early days, so for me, like when we got into ZK, know, with Horizen Labs today, we launched Zencash, the third ZK project out there on chain. And it was really kind of like we were enamored with the technology. And then we spent years like more deeply enamored with the technology post-launch and building out this team of cryptographers, cryptographic engineers. We've done research and invented proof systems, built them, deployed them, kind of dabbled in the platform and app space in ZK. And I could say just from all of that experience, we were probably a little bit too early from a commercialization of the technology perspective. But you've actually interviewed some rock stars in the ZK space who are building this enabling technology. So it's not for me to necessarily plug their projects. But now we can actually see a value chain evolving for this class of tech. And think we have to think about the tech as what's the utility that we bring to the market for users that they can't get without it. And that's where we are right now as a company and how we're thinking about it. How are you guys thinking about it? It's challenging, actually. So we're still early days, I would say, in terms of the commercialization of the tech. mean, there's some phenomenal projects out there in the way that we're tackling it is we think about the value chain as such. You've got applications that are generating proofs, and then there's a whole bunch of different types of application logic that you could provide things like on-chain privacy, making use of information that's stored privately or locally and still posting know, proofs of that information on chain, they're making use of it, you know, in application environments and so forth. So we look at that as kind of like the proof generation application environment market. And at Horizen Labs, we're core builders for the Horizen Protocol, which now we're actually launching on Base as the privacy segment of the Base ecosystem. So we're super excited about that. And that's an amazing project. This kind of revitalizing this old original project with Zen, a cryptocurrency that we've had, you know, for years on now. a very relevant modern platform that's tackling a very specific set of use cases. So that's kind of execution layer. And then we have another project called zkVerify down at the ZK verification layer. So what we realized is if we're successful and we have a trillion plus proofs generated a year across range of different applications, there's no way in the world that current web-threading infrastructure can handle them. It just can't. mean, don't quote me on Ethereum's capacity for verifying proofs, but we're dealing with something like, I don't know, 50 or so per block, 50 to 100 per block, right? So you're just not gonna hit scale of billions and then trillions, and that's if Ethereum were used only for proof verification, which is not by any means. So what we realized was we need dedicated infrastructure, and we need to scale that, we need to do it fast. So now we're launching a project called zkVerify, which does nothing but verify ZKProves as fast and efficiently as possible. How does that work? I envision kind of, you know, there's a set of applications that need their their chain or their transaction verified or ZK verified. And then you've got a set of provers, I'm guessing, that kind of act as validators on those. But all they do is they proof. Is that about right? Peter, that's exactly it. So basically, whenever you generate a proof, regardless of whatever application it is, on-chain, off-chain, or whatever, that proof needs to be sent to a verifier to actually complete that circuit. In verifiers, like in kind of like the earliest stages of ZK and Web3, those verifiers were embedded as smart contracts on the L1 you want to verify on. Now they're on L2s, can put them on L3s, it doesn't matter. But what we're doing is actually we have a dedicated space where we've been all with the relevant verifiers and we optimize them. And we basically have that piece of infrastructure does nothing but verify proofs. But then the result of the proofs needs to go somewhere that's useful for the applications. And like that depends on the app, right? So like the way that we do it is we plug into all of the major chains like Ethereum as an example. And the way we plug in with zkVerify is we have a smart contract on Ethereum like a zkVerify smart contract. that takes the result of the verification action that was done off chain, bundles it into our Merkle tree so it can condense the footprint of all of those proofs, and those proofs can be referenced on the smart, zkVerify smart contract on Ethereum, on any other EVM chain as it stands right now, and then your application can make use of that. Is it a decentralized network approvers? Tell us about that side of the market. under the hood, the way we did it, and like to me, the architecture and the infrastructure, like the infrastructure itself, how we implemented it, it doesn't matter as much as the point of the architecture. The point of the architecture. is we want a decentralized network that actually manages this verifier set. That's the important thing. The way we implemented this particular instance was we used Substrate and we baked in as modules within the Substrate framework, all of the verifiers. It's just a very efficient, elegant engineering system that we can actually now have a decentralized verifier network. got it. Can anyone become a verifier? Yeah, so right now we're in testnet. The goal is we want anyone to become a verifier to be able to run the software and to be able to do that. I think that's key. So we are going to launch, at least the idea is we want to launch with a trusted set of just professional infrastructure providers so we can note that there's high performance infrastructure that's the core of the network. So we know it's actually very effective and works, and then open it up to the world. And I think the whole value of this Web3 stuff is that anyone in the world can actually verify and participate in the infrastructure. to make sure that it's actually, that you didn't leave being operated. Let's maybe back up a little bit, because I do want to go into the test net and how that's going. I guess when you think about the Web3 space, what led you to think that maybe now is the right time for ZK and that these chains and applications, there needs to be some, ZK is like the solution to some kind of problem. Maybe help us understand what the problem is. Yeah, so the problem is twofold. One, I think is super important and going to be increasingly important now with kind of regulatory shifts in the US, privacy, on-chain privacy. And I think that this has been a barrier. for institutional adoption and barrier for user adoption for certain types of applications is like we can all talk about, and we've been talking about it for a really long time, what if we had things like a decentralized Uber? Pick your favorite application, talk about decentralizing it, launching it on chain. And do we want the entire world to be able to see everything done, every single Uber ride that you've taken, where you live, where your destinations are, where your pattern of life is and so forth? No, absolutely not. We don't want that. So we know that we need this obfuscating layer of privacy for lots of very important operations if they're going go on change. Add financial data and the problem becomes 1000X more important, right? So I think that that's category number one. And we're really like deep in the privacy space and like massive advocates for it. In the regulatory environment, finding became fair before that, which we were kind of betting that it always would. It just kind of took some time to get there. The second is scalability. The Web3 architecture that we have out there now works completely fine for the range of applications that we have, but there's such a small subset of a subset of a subset of the world's economic activity. And if we're going to actually get this stuff, like our vision is Web3 may not take over everything in the world, like of Web2 and so forth, but Web3 absolutely will intersect with all of Web2 going forward. Web2 will become Web3, but like what we're seeing on like the on-chain world will intersect with many, like most of the other types of digital activities that we have. And I say intersect. I don't mean like take over because it could be something like corporations still have their private databases, but they're just generating Ziki proofs from the databases like space and time technology allows us to do so they can just have automated regulatory compliance real time, know, at like, you know, 1 % of 1 % of the cost because literally all the data is and it's automated. Right? So there's just so many instances where like the off-chain world will intersect with the on-chain world and you need like massive scale and privacy to make that happen. Yeah, so privacy and scalability. Now, ZK still is quite an esoteric topic for a lot of developers. But they have an idea of what they want their end product to look like and the kind of features and offerings that they have for their users. Tell us about developer education, because most developers, they have no idea what ZK is, how to build a circuit. What types of things are you guys doing to help educate the developer and help them kind of along, kind of help them on their way? Yeah, I mean, it's absolutely critical. it's not just us, but the way we structure things. And maybe this could just be illustrative for how a company like us thinks about it is. So we have kind of like a clustering of know, ecosystem entities in our ecosystem. We've got Horizen Labs as the builder for multiple ecosystems, like Horizens that you verify. We built in others as well. And then you've got foundations that are really core to these ecosystems. And the foundations, I think their key role is doing developer growth and innovation from developers. So the way that we look at things is within Horizen Labs, operate like, or increasingly sophisticated, not quite there yet, but we're getting way better ourselves, like business development operation, where everything is just basically, our BD teams is very systematic about thinking through product market fit, what are the use cases that we actually add like extraordinary, like incremental value on. that people couldn't live without us, right? And then what are those in between? And we assign teams with like a typical CRM approach to systematically go out there and like, you know, acquire customers to ultimately like get our NorthStore KPI, which is the number of proofs for our network up. But that's on like our systematic business side. There's a parallel effort run out of the foundation, which is on the developer growth and innovation side of. We want thousands of developers across hundreds of projects that are experimenting with lots of different use cases and actually building this developer community that's very rich and robust. It's just like much more dynamic than we could ever do or be as a centralized company, right? So it's that parallel effort that's absolutely critical. The way we operate that, know, kind of like parallel sister, like CRM type of approach where like, just think about like, top of funnel is getting developers in there with like hackathons, university programs, in life, virtual events, whatever it is to get people to actually build grant programs and things like that. The whole point is to just get as diverse and rich of an experimental environment as we can, but not one offs. We actually kind of cycled them productively through a funnel so that they've been increasing value out of our platforms as they go through. You said a lot of things I want to go into there. You mentioned your North Star is like the number of proofs. How do you, do you make a judgment on the quality of like what's being proved? So for example, I think, you know, right now there's kind of a crisis of, you know, the image that I'm looking at, like I don't know if it's AI driven, for example. And. to be able to show that it is, whether or not it's AI driven, you want to look at how many permutations this image had. And maybe each of those has its own proof. Something like that, the sum of that is very interesting, right? Because it shows you that the image was actually altered. It's manipulated, and it could be held up in court. It's all of that. But any single permutation may not you know, maybe change the color here, change the color there. Do you make a judgment on the proof at all or anything? OK, so I'd say this is such an awesome question because you also, I was kicking myself for not mentioning the third category, where ZK is useful, which is unverifiability. So you've got privacy scalability and verifiability. In fact, we already have some really interesting use cases and customers in the AI domain. So I think the intersection of ZK and AI is absolutely critical, just as an aside because you brought that up as an example. as of today, so the way that we differentiate in terms of like, know, quality of proofs being sent out, we don't go under the hood. In fact, we can't really go under the hood to understand like what's inside of a proof necessarily, but we do absolutely differentiate type of proof. And there's multiple proof systems that are out there and proof systems can kind of form, depending on function. And We have differential pricing on proof systems because they require different computation on the verifiers. So as of right now, our first order kind of naive approach, just like our goal, our nurse star is like bulk volume, because that's where we were differentiated from, say, Ethereum or verifiers elsewhere, because we do nothing but verification. So we want to just first hit scale. And then we are differentiating across proof types in terms of pricing. But once we're at scale, then it's going to be kind of a matter of like, What are we verifying? Why are we verifying it? Why does it matter? And I highly suspect that we will have use cases that are just like hands down way more valuable economically than other use cases. So totally agree with you, but the only way that we capture that currently is via computation. And to the extent that you're gonna have multiple steps of verification and some process like to do, like your provenance of information or authenticity of information, those steps each have computational elements to them. So in aggregate, they should be more expensive than like, say, just verifying a simple abroad 16 proof of, you know, are you over a teen to buy this cigarette? You know, so I suspect we capture that like in first order effect. But over time, I think it's gonna be very interesting to get a little bit deeper under the hood if we can. So we've established that zkVerify excels in privacy, scalability, and verifiability. Going back to the target customer, mean, almost anyone can be a customer of this type of offering. What exactly is the focus? I guess the target customer may be a secondary customer. Maybe tell us a little bit about that and the kind of positioning that you are employing to reach them. Yeah, so again, a phenomenal question because we think about this very deeply every day. And what we're trying to do, just to be clear, is we're still pre-PMF, right? Like we probably, like most of Web3 needs to be honest about the fact that we're still pre-PMF on most of the things that we're doing. But the way that we're tackling that is initially, like our goal is, so how do we differentiate from a developer's perspective? So our customer would be a developer. we're sort of agnostic on any developer that operates in ZK is kind of our first order, your target, and then we go deeper at the second level. But to first order effect, what we want to do is we want to get a one-stop shop for verification. So we want to simplify everything, whether you're kind of a new developer to ZK or you're a professional developer in ZK or you're a corporation using ZK and you have a whole team of developers. Our idea and our differentiation is we're one-stop shop. You work with us, we are the professionals at building verifiers and deploying them and maintaining them and security audits and all that. And you have an amazing simple interface you just RPC into. Instead of deploying a verifier on every single piece of infrastructure or chain that you want your product to operate on, you just send a proof once to us and that's it. And we make it as easy as possible. You don't have to worry about building your own verifier, copying another verifier from someone else, but not doing security audits or keeping it updated and maintained over time. We do all that. So that's kind of our first thing. The next step is we think more deeply about now, which are the use cases where this really matters? We have categories of use cases as of right now that we're actually hunting down very aggressively on PMF fit. Or that's redundant, not with the F there, but on PMF. And those three categories right now are, there's a ZK AI use case category, which is super interesting because I think that that's where the next trillion proofs are going to come from. which is like authenticity of information. Is this real? Was this video content edited? Is this a deep fake? Is the data feeding an algorithm actually retaining privacy for its users? Is it compensating its users for value added to the data? Is the algorithm itself being kind of, is its integrity kept private? Are we verifying the output of some algorithm or LLM is actually the correct output relative to it, right? So it's like, there's lots of kind of subcategories within AI that are super interesting. We have an awesome. customer there, partner that we're building those out with. That's where I'm super bullish. Category two, I would call it like the private DeFi stuff. So I think private DeFi is absolutely kind of foundational. And this is where it kind of like with us as a company, you can see our strategy. We have this execution environment on Base called Horizen, which is like the place where all of those privacy apps can cluster and get kind of synergies from clustering there. I think that's huge. I think when the world comes on to you with finance, especially institutions, they're going to be using like privacy tooling there. So we're actually really big on that as a category. And then I'm getting older in age. what was the third category? mean, we have so many on the business side as well. yeah, sorry. We have so many customers in terms of like from the proof generators to those that are actually making use of proofs. But I'll just stop there and I'm sure it'll come. Come back to me as we go further. Well, there's a, you know, with a lot of the AI, a lot of the ZK projects that I'm speaking with, I mean, one of their target, the target customer for them or the target category is really kind of the AI space. And it goes into everything that you just mentioned. And maybe we can spend some time there because that's quite interesting. Especially since, you know, AI is has really taken up the bulk of the mind share for both, not just crypto, but like outside of crypto and And then there's so many opportunities for verifiability. Tell us kind of like what are, you mentioned several use cases. What's one that I guess excites you the most in terms of like usefulness and what zkVerify is doing in that space? Yeah, totally. And I just remembered the other major category, which is verifying off-chain stuff. So verifying off-chain stuff like an SQL database and bringing that on-chain is super, super critical. And that's also AI related since a lot of data is kind of off chain. Exactly. And I think the probably the technical implementation that we're extremely excited about Horizen Labs is what we're calling like ZKTLS use cases, which is basically you can generate proofs off of web content where you verify kind of the server source of the content and the content itself, package that into a proof. And you can actually have that proof go on chain to verify information. And the classic case here would be, for instance, I could pull up my bank portal. You know with my bank and I can actually use that information, snap, is it key proof that actually verifies that it was the bank's server, an IP address that serving that information. And then I could, in a privacy preserving way, go and apply for credit on chain with actual detailed financial information that I'm not disclosing to the world, but verifying that, yes, I have more than a certain amount in my bank account. I've executed a certain number of transactions, whatever information you want. I think this is absolutely critical. blend of how do we get off-chain information on-chain that is going to just be kind of like that major catalyst for really just kick-starting our industry. it. Tell us more because that's just a really curious space to how ZK Verify is playing in the AI space because I just see that you mentioned your business development team. I imagine that probably they could probably do several things, right? But I'm guessing that the most demand or seemingly the most demand is going to come from the AI space. But you also have a lot of B2B partners that are in the Web2 space, I'm guessing also. But with those types of partners, they probably need a lot of education. And so the sale cycles in those are quite long and also resource intensive. And for a little startup, that might not be feasible. But in the Web3 space, especially if it's crypto and AI, they're more familiar with ZK and its potential and its benefits. And so there's probably less education that you need to do. So maybe tell us kind of, I've kind of said a lot there, but maybe tell us your thoughts on, you know, how, zkVerify is finding product market fit, especially kind of maybe lean into the AI space. Yeah, no, totally. And just to kind of put it in context, we're still on, you know, just testnet. So we're not in production yet. So just want to clarify for everyone out there. We're running through this exercise real time, kind of as we're talking right now. Now, the way that we have it is we have one big anchor customer in the AI space, which we're super excited about. And we're kind of using them for product iterations to understand why this is incrementally so much more valuable. And then we have multiple other AI companies that we're working with to really figure out, does this make sense for them? Is this actually a competitive differentiator for them? And what I can just say from my observations thus far, at least for these companies. And these are crypto AI companies. So you're right, the education is way different than if we went to just like a raw AI company that's outside of our industry. But for these guys, they all acknowledge that ZK actually should be on the roadmap. They want it to be on the roadmaps, but they're also in their own PMF, kind of like startup phases. So they're focusing on what matters most to them, like their core functionality and then how they bring that to the market and serve their customers is like the next iteration. until they themselves at PMF. Like ZK for them has been like, we know we need it, especially when we actually get anything related to customer privacy, inputs to the models that we don't want shared with the rest of the world, or for ingesting information that has sensitive information like my bank information and so forth. Or for model developers, do they want, and kind of an example here could be, if you develop like an on-chain, like DeFi algorithm or trading algorithm, right? want that algorithm, the output of the algorithm to be verifiable because you probably want to sell your services in a way or get reputation for actually building an amazing trading algorithm. But that's literally your differentiation as a product. You don't want that to be copy pasted by the next guy, right? So to the extent that you can have verifiability of the output of something. So if you were to build like an AI agent that's out there trading, you don't want the details of that AI agent to be leaked to the world. Like even in terms of its operations, because you could potentially reverse engineer the algorithm that's operating under based on its trading behavior. So there's multiple levels here where obfuscation becomes really important, depending on use case. But the reality is there's probably plenty of early, low-hanging fruit AI use cases where they're not even thinking about privacy, verifiability. They're just sort taking it for granted, where they need to push the application, their core product, more. or work on algorithm development and so forth. That's at least what we're seeing, but it starts with an anchor customer that we go from there. And right now we're just knee deep in again, like customer discovery as a use case. And having the of the blanket of Horizen Labs, which is well established and respected, and then zkVerify as one of the products that you're focused on now. mean, that's quite, I'm sure that's quite helpful in terms of funneling potential customers to use zkVerify offerings. You mentioned Testnet. Let's talk about Testnet. Like how are you structuring that and how's it going so far? Yeah, so TestNet is, we have a phase rollout approach. We're actually in TestNet phase two right now, or season two, as we're calling it. Now keep in mind, we basically have a BDB product and a highly technical product, right? So like our audience are highly technical developers and we've had... Hundreds of them so far that we've funneled in from hackathons. I think at this point, maybe more like 500 or so developers from hackathons and various events where we're actually getting them to build POCs and use cases, which is awesome. It's amazing to see and surprises us all the time the types of use cases that come about from these events. But then like it just goes from there. So we need to be really careful about how we're getting out there and not wasting our resources early. Because with test nets, and I think in our industry, people are really heavy on incentives to make it look like they have a lot of traction and usage. For us, it literally comes down to proofs. like, We're not going to go out there and buy proofs in the sense we're going to incentivize people to take proofs and networks and get our metrics up. And I think we have a luxury of that, kind of like what you alluded to before, Peter, with we're incubating this out of Horizen Labs, which is a mature stable company that has resources. So we don't have to go out there and fabricate numbers to try to get our metrics up. And I think that would be a disservice long term and hurt our brand credibility. So the way we have it is we have we literally every day we have in our slack we have a bot that aggregates our proof throughput on chain via the explorer. So like our entire team every single day just right in our faces how many proofs we have on the network from what key customers so we can see like breadth and depth of proof volume in the network. Again, I look at it as we want the big B2B customers to be, you know, call it like the depth of volume that's in our work. It's super important. We have some awesome anchor customers there, but the breadth really matters as well because ultimately this is an innovation game and we want to be able to serve and learn as fast as we can and get our learning cycles really tight so that we can incrementally improve and modify our platform, our product, to just make it the best in the world. Yeah. You mentioned you use hackathons as a funnel to introduce people into the test net. What exactly, tell us what that looks like and what these developers are building such that it creates proofs. Because creating a proof is not, it's not trivial. And so I'm curious about what that, what, you know, the compression of, know, from entering into the test net to building something to the thing starting to generate proofs. Yeah, so I think there's multiple angles here. So first of all, we do real world hackathons, like we couple them with like Heath Denver and other events or like DevCon and so forth. Then we do virtual events. And think having a good mix of those is really important because you'll get different participants. But the next big piece, though, is you have to properly screen the right type of developers to come because you can get a lot of developers to sign up and then just kind of garbage and garbage out type of thing and you've wasted your time. resources. So we try to screen effectively for those devs that have ZK experience, or at least enough related experience, where they can just kind of take the tooling and the RPC interface with zkVerify to be effective. Now, there's more tools that are on the market as well these days. So you have SDKs that are out there from companies like Sindri, which are partners of ours as well. They just make it easy to actually construct the ZK circuit, or just kind of out of the box with their SDK. Because it used to be very difficult. Like we were early ZKs. ZK devs and like, it's painful to me every time I would hear our CTO talking about building a ZK circuit. It sounds very inefficient. Now there's ZKs that make it easier, but even better, like longer term now, we have ZK VMs out there. Like, zkLink put out a phenomenal ZK VM, they've got Risc Zero with their ZK VM, and you're getting others now that are out there. And that's just making it way easier because you have developers just code in Rust or whatever language depending on the VM, and that just compiles under the hood, down to a circuit, and generates a proof. So now, just because the tooling is so much more mature, maybe linking back to that early part of our conversation, I just think that time's there. And we make heavy use of partners and tools in our hackathon events and screening to be effective. Now, you mentioned RISC0 and Sysync. Do you view them as competitors to zkVerify or potential partners? No, I view them more as partners. So those are enabling execution environments that just make proof generation way simpler. And I think that's better. So for ZKVM, what we care about, we want to be that massively scalable infrastructure under the hood so that the outputs of those types of environments hit our network. Now, the way they go to market, a little, it's idiosyncratic to them, but a lot of these guys will go to market in that they're trying to make money on, the proof generation side. So to the extent that you have a ZKVM, coupled with their proprietary or their preferred proof gen network, all we care about is like the proof at the end of the day, it can easily verify. So in terms of like where zkVerify fits in the stack, let's say that zkVerify is working with Succinct. And Sysynced is kind of top of mind, because I just met with Uma last week. Where would zkVerify sit? Yeah, so where the verification layer there. So if you think about the layers, you first need the generator proof, and that's where these proof gen networks come in. And then you have these services that do aggregation, by way, like zkVerify will do aggregation in the very near future. And then you need to ultimately verify the proof somewhere. So we sit squarely in the verification camp. Now we will add aggregation just so we can handle way higher volumes ultimately, but that's going to be kind of a product market trade-off between like time and, you know, time and throughput. So, you know, but that's how we look at it. So there's a stack out there in kind of a value chain for ZK. So in terms of like user journey, so I do a thing and then I generate the proof that I did the thing and then it's verified and then it's posted on chain. Is that kind of the journey roughly? Yeah, so your application executes some logic, and then that logic needs to be converted into a ZK proof. And that proof can happen in multiple ways depending on your application and what makes sense. These days, just to give a plug to one of our partners, Forma, it's a network of decentralized proof generator, a set of nodes that generates ZK proofs for customers. So these days, you don't even need to build your own infrastructure to do that, which is phenomenal. like the dev experience like should be as simple as pull in kind of like an RPC interface to a proof generation network, connect that with your app logic, and then output goes to another RPC interface on the verification side. And it's kind of like one very seamless cycle. Yeah. Okay. This is pretty fascinating because I came into this conversation thinking of potential competitors to zkVerify, but it sounds like zkVerify could be a partner to the projects that I was thinking of as potential competitors. And so that's actually quite interesting because now it opens up the possibilities of where zkVerify could fit. Yeah, exactly. And then it comes down to proof flows and how they're being generated and how we're adding value to actually just make the entire process very seamless for people. Yes, that's the thing. And how we look at our customers is we just want to make their lives way easier. Yeah. Going back to Testnet, because you mentioned you're in the middle of phase two, what types of things are, as I imagine you've got big customers in there, but also maybe independent developers building things and generating proofs, what are some interesting applications you're seeing that you could talk about in Testnet? And to what extent are they helping in generating proofs? Yeah, so there's, first of all, like one of the tasks that we have, our testnet developers do, is you literally generate or creating proof verifiers and submitting them to the network to be integrated as palettes. That's a whole beast in itself. And this is why I kind of initially caveat with, we have a very technical testnet because we're not one of those testnets where we have an incentive program that brings a million users to grab an NFT and hope that it converts to monetary value one day. have very technical people building real pieces of infrastructure to make the network better, which is great. But that aside, I'll highlight, again, one of our flagship partners here, which is on the private DeFi side. They're called Singularity. And Singularity actually provides a privacy wrapper around public liquidity pools and public AMs and DEXs so that you can actually obfuscate user flow there. And the product that they're rolling out right now is a private dark pool, they're calling it, which is, again, is designed for institutions to come on chain, which I think was always a blocker. No institutions can come on chain, start trading at scale without proper and effective privacy. So that's one use case that I think is phenomenal for the world, and great for us as well. And where we have our differential value is if they were to deploy directly on Ethereum and verify that proofs with Ethereum, They use Ulster-Planck's Noir language and the proof system Ulster-Planck. And it cost them hundreds of dollars. Yeah, exactly. Developed by Aztec, exactly right. But it cost them hundreds of dollars to verify proof. So right away, if you think about demand curve for usage there, it chops off any type of retail trading ability, or even for institutions to trade lower value assets, or maybe HFT, it's high frequency trading, which you probably wouldn't want to do it on chain. But just the whole point is with multiple hundred dollar like verification costs it really impacts the products utility So with us like we collapse out to pennies, right? So it goes from hundreds of dollars to pennies and we're in enabling function there where they can actually deploy The product on Ethereum where they just couldn't do it previously Yeah. So much of crypto involves retail folks that are not necessarily technical, they believe in the mission and the vision of the project and they want to be part of it. Do you envision involving non-technical folks in the testnet in maybe phase two, end of phase two or phase three? Absolutely, we will. guess, and this is kind of like, you know, touching on some philosophy of how this industry has been operating. I think we have new opportunities now with changing regulatory environments in the US. I think having mature companies like Corresum Labs to plug ourselves, right? We're here for the long run. I want to maybe IPO as a company, right? As a business, right? So like we're not going to be like, we're in a completely different class or category than an anonymous founder who launches a product and you're gonna get robbed one day, right? And I think that that's really important. The way that that's relevant here is that we take more of a conservative approach to how anything that touches real money, we take a more conservative approach to. I would rather hit PMF and focus on platform and like UX and make sure that we're actually adding incremental value to customers and use cases before we do anything on the token side. And of course, these systems by their very nature to be decentralized have to have tokens. And absolutely, Zikki Verify will have a token that we will TGE and launch. But we're just focusing way more on the technical and like the product aspects of it before we even think about bringing retail in. Now retail would be more on the way we look at it because we're sort of like a B2B platform. It'll be more engaging the customers and audience of the projects that are using zkVerify and working in partnership with those customers of zkVerify to bring their customers inside joint campaigns. That's the way that we look at it because it's not like zkVerify is not an EVM where we're gonna have a whole bunch of random, know, NFT projects and things like that to engage with customers. literally a piece of super critical infrastructure that's going to be a major enabling force for the entire industry. So we'll work with our partners and their customers to actually get them engaged productively in joint campaigns. No, this has been really, really helpful. And the ZK projects that I've met with, they focus on different parts of the stack, different kind of target customers. And what's really cool about ZK Verify and the parent company, Horizen Labs, that Horizen is established. It's respected. It's very regulatory compliant. And all of that really matters, especially to really all customers, but especially in this environment where things are becoming more regulatory relaxed. Hopefully more B2B established Web2 projects will be looking at potentially using ZK offerings as part of their product offering, especially in healthcare, maybe defense and other areas too. When you're speaking with folks that are not you know, don't know a ton about zero knowledge. Like how do you make zero knowledge relatable to them? Yeah, the best thing is to not even mention zero knowledge. The way we typically pitch it is security technology or privacy technology. And to me, security and privacy have a really important intersection. And I think that's the best way to sell to a non-native Web3 audience. In fact, it's even my preferred way, because I think that we're guilty of this as well. We've been overly enamored with classes of technology and not focusing so much over the years on the actual end user value, the point of it. These are enabling technologies to do something valuable for customers. So I think I would prefer not to even focus on the technology and really just focus on what you get from the tech. Yeah. One of my favorite examples comes from Ogilvy. Ogilvy was a master at copywriting. And he gives this example, which I often refer to. And I've shared this with lots of folks within a crypto space because you're exactly right. know, most crypto people get, are really technical. They're overly enamored with, you know, complexity, right? And they feel like speaking, you know, in jargon is, you know, impressive. It's actually not. But the example, yeah, the example. the way, agrees with that. Like our CTO is amazing at actually just selling things like very simple to understand, but like there's deep complexity behind it. No, I love that. And we need more of that. Ogilvy's example, he shares, he says that, you know, when you see like a weight loss product, I'm probably attributing it wrongly to Ogilvy. It's someone within the Ogilvy organization. But the example goes as such. He goes, when you see a weight loss product, you often see, you know, copy like this, you know, I lost 10 pounds by using XYZ. And then they kind of end there. And the Ogilvy he takes it a step further because you want to, you what is the emotional anchor and what is the actual benefit? And he says, I lost 10 pounds using XYZ comma. Now my wife finds me attractive again. Like that, that little piece of like, you know, five to, five to six extra words after the comma is really what matters. And so when I speak with folks within the crypto space, And I share that example. I often see like a light just shine in there, like a light bulb turns on. It's like, my gosh. And so I wonder if there's, as you explained ZK, if there's those types of examples we could share to make ZK more relatable, because it is such breakthrough technology and it can enable so much. But we also have such a hard time explaining exactly what it is. And that's kind of the bottleneck. Yeah, I completely agree. I wish I could say I have some. amazing and interesting examples like that here. I mean, for me, it's kind of, you can go on one side or the other of the on-chain world is scary. Like you hear about hacks and all these things happening all the time. I just don't like negative messages. I don't want to frame something in a negative way. But the reality is like the on-chain world is scary. You've got the Lazarus group out there constantly hacking exchanges and stealing people's money and all that. You've got scams constantly. Well, ZK can actually help protect you. So there's definitely an angle there. And then there's more virtuous stuff, there's a whole enabling side of the technology where you just wouldn't do things on chain without that type of cryptography and security. You know, you mentioned the Lazarus, this is totally aside, but I, so I led growth at Harmony when Harmony, the Harmony bridge was hacked by over a hundred million dollars by the Lazarus group, which then led to just hours and hours with the FBI and all of these. was, it was a mess. Anyway, Lazarus group, no bueno. Yeah, no, exactly. Well, Rob, this has been really such an enlightening conversation. What I guess what are some parting words you'd love to leave with the audience? And keep in mind, the audience are primarily developers that are in either the Ethereum space or Solana space, some Bitcoiners, but really a lot of marketers, lot of marketers and biz dev folks listen to this show because they want to learn more about how to actually market crypto products better. Yep. I think the way that we approach it is, we've talked a lot about product market fit. Ultimately, though, it's community market fit. community does represent a very important core constituency of users for these products in Web3. So as we think about that, it's this blend of community and customer. that is sometimes challenging to get right. One kind of heuristic that we have there is instead of building in isolation, and we've been guilty of this as well, I can tell you lots of ways to do things by examples of how we did them wrong historically. One is go to where the users are. Don't think about building in isolation and getting users. Go to where the users are and then think about carefully and deeply what it means to add value into that environment. And this is just one little example there. Horizen, the project we've talked about a bunch here, has been a dedicated L1 since 2017. We're actually migrating out over to Base now because we realize Base is where they have amazing users, amazing organizations participating in that ecosystem. It's more about ecosystem and community, and we can bring the tech there. We don't need to do the tech in isolation and hope that people come to us. So that's a big lesson for us in how we're thinking about everything that we do going forward. So go to the customer, actually do some customer development, help them learn about their needs and then allow them to kind of help you build a product that actually meets their needs. Perfect summary. Totally agree with that. Awesome. Well, Rob, thank you so much. It's been so fun to talk with you and to learn about zkVerify. Peter, I appreciate it. Thank you for the opportunity.