EP28: Covalent: Fueling AI & DA with Our Specialty
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Hey everyone, welcome back to Web3 Founders World Talk, where we dive into real unfiltered conversations with the true game changers in industries. Today, we're thrilled to have Ganesh, CEO of Covalent, joining us. Welcome aboard. Blair, so happy to have us on the show. Excited to chat further with the community.

Thank you so much for coming. Can you just briefly introduce yourself? Like how did you land in crypto industries? How did you get to start your project? And also, please tell us a little bit about Covalent as well. Absolutely. So I'm Ganesh Swamy. I'm one of the founders of Covalent.

And so Covalent has been around for like over five years. So it's one of those like OG projects. And my journey into crypto has been quite accidental. So it was just a chance that I entered. So I was not in crypto. I actually come from a database world. So building data infrastructure. And prior to that, I used to do cancer research. So-

I was doing physical chemistry, building antibodies for drug design. I was on the founding team of a company that is Canada's biggest biotech company. It's listed on the NASDAQ, and there are a couple of drugs in clinical trials.

So that's my background. I pivoted out because pharmaceuticals takes like 10 years to build an MVP. It just takes a while. And I wanted, my friends in like IT were like, you know, just shipping MVPs and going to market, raising capital and going through M&A in like two years. And I was missing that pace. So I pivoted to data infrastructure. And this is when, uh,

cloud data warehouses were becoming popular like snowflake. So a lot of the on-prem workloads were moving to the cloud and the cloud is like a new kind of like infrastructure piece. And I was helping a lot of these companies move to the cloud. So I did that for about a decade. And I was working out of a coworking space and a mentor of mine said, "Hey, you should check out this decentralized database project hackathon." This was during the bull market in 2017.

And I'm like, okay, I'm in Vancouver. It rains a lot in Vancouver. So I don't have anything else to do on a Saturday. Let me go check this out. So I know that in a database world, ultimately, it doesn't matter what your database is. People still want to do the analysis in Excel. That's like really the front end for all databases. It doesn't matter what Oracle or SAP or Microsoft is.

And so what I built in this hackathon is a way to pull blockchain transactions directly into Excel. So that was the idea, right? And so it's like a search engine, Google for the blockchain, whatever you want to call it. And back then in 2017, it was just ICOs. It was just simple like ERC20s and transfers. That's it. No DeFi, no NFT, none of the complicated stuff.

So we ended up winning that hackathon. And then we were saying, hey, this is a cool idea. You know, this could open up a lot of things. What I got wrong was the market timing because the next like two years was just the bear market and it was brutal. So please don't get my advice on market timing. I have the worst...

track record. Anyways, we started this company Covalent. So Covalent comes from the chemical word covalent bonds. If you remember your high school chemistry. So here we're binding centralized systems and decentralized systems, databases and blockchains, uh, you know, things of that nature. So that's the analogy. And so that was the Genesis story for Covalent. And so we started this company essentially. It's like looking at, uh,

blockchains like a database. So you can query it, you can index it, you can do all kinds of things from that blockchain.

And yeah, the first couple of years were a struggle and then DeFi summer hit and right time, right product. They say like overnight success, right? But we've been working on this for like two, two and a half years by then. There's a little bit of like a detour here and there, but that is generally the Genesis story. So it's like, if it didn't rain that Saturday in Vancouver, there would be no point. So super simple. But the core crux idea here is that

It doesn't matter what kind of infrastructure or change happens under the hood. People are not going to retrain or retool. They're not going to throw away Excel. They're not going to retrain your existing workflow. Your existing business process have to adapt. You need this bridging agent. You need this middleware. That's really what Covalent offers from day one. We've never really pivoted or anything of that nature.

So that's what it is. It's called by different names today. Some people call it indexes. Some people call it like a data availability layer and so on. But that's fundamentally what we do. We just make blockchain data more accessible in a decentralized fashion.

Wow. That's like the most interesting story that I've ever heard. It's all about the weather. And then it's all about the weather. So I'm so glad that, you know, Vancouver rains a lot. So that's why you get to, you know, establish. Maybe you're the only person who rains more in Vancouver. But yeah, that's the, you know, it's just like...

Luck, I would say. Yeah. But you get to establish this really fantastic project with pretty substantial pain points because you identify that's the thing. And now you're doing a great job. And I just want to know that if you guys have encountered any sort of challenges or resistance during the journey, like you said, timing...

especially due to the whole crypto industry thing, that could be a really pivotal indicator. So did you guys encounter any other technical challenges or any other kind of micro environment kind of challenges along the way? So I'm a CEO entrepreneur, right? So this is my fourth startup. And any kind of mission, journey, startup that you do,

has risk and it comes in risk bundles. There's like market risk, which is where we failed that first like two, three years, right? There's like product risk. There's technology risk. There's financing risk. There's like team risk. So all of these like bundles, right? I would say we had definitely financing risk because nobody was writing checks during the bear market. There was market risk because, yeah,

the market just wasn't there. Like there was no, no applications. We bought the product. So there's no, like, we are like pretty good engineers, the founding team. My other co-founder, Levi, has databases his entire life. So he knows more, way more than I do by, by, by no stretch of the word there. So, so there's definitely financing risks. There was like technology risk. We got lucky in another different way in the sense that EVM won out and

and everything basically become EVM. And there are teams that bet on like EOS and, you know, like Cardano and like, you know, Solana, it's done well, but anyone who's bet on a non-EVM like XRP and Elrond, all those guys are like dead now. Right. So I think, you know, definitely we got lucky on that, like choosing EVM, the technical, the thing.

So I would say those are some of the rest and but the biggest brutal thing is the financing and the market risk. So after spending two years on Covalent working day in and day out, we had bootstrapped no outside capital. I got really disillusioned with with like just the whole space.

not just me, there's a lot of people who exited during that bear market, just like you saw in the previous bear market, how people exit, right? Yeah. So a mentor of mine said, you should just take some time off and just go get some perspective, you know, to see if this is right for you or not. So I went and did Mount Everest. So the base camp, I climbed Mount Everest. It was like a pretty like hard journey, but I was spending a lot of time by myself. I was spending like eight, nine, 10 hours, just like, you know, walking, walking just by myself. There was a whole group at

I was just like in my own thoughts and I had a lot of time to just think about it. And I had some brilliant insights in the Himalayas. And one of the insights I had is that you scraped all this blockchain data. Why don't you just use it to see if there's any traction and then just do an outbound and reach out and see if they want your product.

So we came back, I sat down, I came back in October, now we're December, January, February. I just grinded through like those like four months. I didn't take a Christmas break.

and we got product market fit, and we started making revenue, and then we closed consensus. And then it's just like, that's a flywheel, right? So again, another chance, just like a different perspective. We had all the data. So you can literally see what protocols have what fraction. So why don't you go and just reach out to them? So I would say those are the big kind of like resistance challenges. And then after that, there's always a challenge that

People don't understand the value of an indexer because all data is public. People are like, "What's the difference between Etherscan and Covalent? What is the difference between RAAF and the Covalent?" But those are ongoing. That's part of the journey. But initially, I would say the biggest challenge was just getting this off the ground was so hard. And it took almost three years before we could see light at the end of the tunnel. So yeah, those days were long and hard.

Yeah, but that's also very impressive because, you know, in this space, it's still very nascent. So we are still seeing entrepreneurs struggling with product market fit. And sometimes I feel like entrepreneurs need to be really selective on things that they've been doing, not just for, I mean, for their interests or, you know, just for like personal, maybe some sort of like perceptions. There's something called product founder mindset.

- Market fit. - Oh yeah, that's the thing I wanna talk about. - Just like product market fit, right? - Yeah, yeah. So can you also provide us with a brief overview of your product scope?

Because I do see you have unified API, like Go Rush. And also, additionally, in comparison to developers manually handling data retrievals and processing through RPC, what kind of cost reductions or efficiency improvements can developers expect

with your product? Well, I'm not a really technical person, but I guess that could be a question that people, yeah, like you said, they are just wondering what's the difference between those two. And also, how does it differ from other blockchain data solutions like the Graph?

Got it. This is a great question. Maybe before even talking about the differences between different data solutions, the crux of the problem is that

blockchains are billboards, they're not databases. So what happens in a billboard, you post something and then after that week is gone, you take down the posting and then you put another post. So that is what blockchains are. The whole point of a blockchain is to get it in for the challenge window, see if there's any kind of challenge. And after the challenge window, you evict that

you eject it and then you go on to the next so you evolve the state machine right so that is the core thing about a blockchain and a lot of people like misunderstand this they you know they really don't understand that you know blockchains are meant for state propagation not for storing any kind of like historical data so that is one gotcha the second thing is that

Every blockchain has its own nuances, right? Some of it does POS, some of it is proof of stake, proof of work. You have new kinds of roll-ups. You have different DA solutions. You have some people using call data, some people using blob storage. But from a developer perspective, they just want to see token balances. They want to see NFTs. They want to see what is your cost basis. They want to see...

you know, standard stuff and they don't really care about, you know, what the technology is, doesn't matter. And so the way the unification makes sense, right? So this is very novel to Covalent where we've built a unified interface to all blockchains that we index. And we index about 200 blockchains today, including test nets. So if you integrate with Ethereum,

You change one character and then you have Solana. No, sorry. You have like any other like Polygon, Arbitrum, Phantom, Optimism, Base, and the list goes on, right? Mantle. So any EVM chain, just one character change. So you build your UI and then everything just works. So this is very popular with developers because they don't want to rebuild the stack again and again for all the different chains.

Then some of the other aspects is that it's important to understand the data stack itself. So you have data products like CoinGecko, which is more for a retail audience, right? So they give you like high level stats and market gap and circling supply and stuff. It's not truly on-chain data because some of that data is also off-chain, but that's a retail audience. Then you have like infrastructure layer indexers like Covalent and the Graph that offer like essentially structured data.

And then you have RPC, which is a layer below, like Alchemy and QuickNode that offer raw data.

So this is the layer. So our specialty is in the center, which is structured data, because the RPC gives you unstructured and messy data. So that is a key difference. So the value of an indexer is to take all this raw unstructured data from RPCs or the blockchain and then make it structured so it's usable and consumable and human readable.

So that's how the stack is organized. Then I would say with the graph, I think they're just two different philosophies in building indexers. And so the graph has something called subgraphs. Covalent has a unified API. In the subgraph, you create DAP-specific kind of endpoints, but each DAP has its own schema, has its own structure.

In Covalent's approach, it's a unified schema. So it's not specific to a DAP or something, right? So the use cases and the traction and the kinds of customers, they're all completely different. But they both kind of solve the same problems. And what is so interesting is after about five years, the graph is becoming more like Covalent and Covalent is becoming more like the graph because everyone tries to expand their scope.

Yeah, that's very interesting. I noticed that you guys have highlighted a lot of actionable items in your Covalent Vision 2024. It's been a quarter and I just want to know...

Because you guys mentioned like you say, I run way back machines. Those are pretty pivotal. I can get that. But how was all those items determined by your team? Because it's a lot. And can you also provide an overview of your current progress? Also, which one will be your primary focus among all those items? So,

I think there is a method to this madness. It looks like it's a lot, but it's actually like a jigsaw puzzle and it's a holistic kind of like program. So let's take a step back and understand this flywheel, right? So Covalent goes and indexes blockchains, right? We index the blockchain. And so the developers and the dApps on those blockchains use Covalent.

And when they use this, when they use the product, now these dApps want to go multi-chain. So they consume more data from Covalent, which means it unlocks more use cases. When it unlocks more developers and more use cases, more blockchains want to come and tap into the use cases and the developers. So the last, I would say, 50, 60, 70 blockchains we've indexed, it's all been inbound.

So we've never like, we don't do like any kind of outbound. They want to say, come, they have all of this like products, they have all of the traction. And so an example is like if a wallet like Rainbow Wallet, right? Rainbow Wallet is a very popular wallet. All of the data is Covalent. They will not go to a new chain unless Covalent supports it. So we get a lot of requests from the dApps

For example, we just got, we announced blast indexing, right? But that's not because the blast team asked us or we went to blast or whatever. It's because Rainbow asked us that you don't support blast because on Rainbow's side, it's one character change. They just changed one character and suddenly blast is supported. Everything is supported on blast. So they don't have to rebuild anything. It's so easy to use. So that's the flywheel, right? So everything around this is how it's just like a flywheel that's spinning around and around and around.

The key thing here is where the token comes in. All of the revenue that the demand side, the developers, it's a pay-as-you-go API. It's free to start and then you start paying revenue. That revenue flows back to the operators who run the nodes and therefore the CQD stakers. That's really how this whole flywheel spins.

So that's how the decentralized economy also starts to develop. So it may seem like it's a lot, but everything about our community program, the fee buyback and the switch,

The Ethereum Wayback Machine, the list of products we have on the demand side, the developer grants programs we have, the more indexing we have for all the roll-ups and roll-up as a service, it's all part of this giant flywheel. It just spins faster and faster and faster. So yeah, it's all part of the same program. It just looks like it's disjoint.

Yeah, it looks like it's all over the places, but I would say everything ties together, like you said. Like, how is it going? I guess we just want to see if there's, you know, any sort of...

like product developments that we are we can we we're expecting to see in the future like can you give us a sneak peek of that absolutely so the key thing here is uh one of the things that we had highlighted in our review from last year is the fee switch mechanism which is the revenue that is coming from an exogenous source basically you know customers paying revenue

That's used to buy back CKT and distribute it to the operators. So that switch went live about 45 days ago, and it's buying $1,000 worth of CKT every day.

uh so perhaps uh you know maybe the show notes or something i can uh share the wallet address and it's just like every day buying thousand dollars sometimes ckt is 20 cents sometimes it's like 40 cents it doesn't matter buying and buying and buying and as the demand side revenue increases it's going to essentially establish the floor for ckt because it is buying anyone who is trying to sell right it's just that floor yeah so that's live now so that's uh an exciting kind of update that's like the the final like picture going in

The other thing is the staking migration moving back to Ethereum. So far, we've been using Moonbeam for our settlement and so on. And I think generally the Polkadot ecosystem is kind of like not really where it needs to be. So we're moving staking back to Ethereum. So all the audits have been done for that. And then what's next is just the EWM like testnet, the incentivized testnet. So that is almost ready.

And then doubling down on the AI and the DA narratives and, you know, just building more products and getting involved with those communities. So, yeah, everything is going according to the plan.

Wow. Hope everything pulls off because it sounds like a lot of work. I captured that from your social media that covalence also strikes in advancing AI with very extensive historical and real-time Web3 datasets. How does this process work? And can you also name some specific use cases for AI models?

I know there's been Web3 and AI crossover for a long time, but we are debating on some sort of real, legit use cases currently. So can you maybe name a few? Absolutely. So the key aspect of these language models, the large language models, the LLMs, is structured data.

So that is the input to all of this. It's the reservoir of data that is required to train these LLMs. And the whole point of Covalent is having all of the structured data.

So you can go and feed all of the structured data into these language models, and then you can fine-tune existing foundational models, whatever you want, and then you can start to do inference on it. So that's really how the pipeline is. So it's very similar to getting the structured data and then running a query node and then querying the structured data. So that's a database product. So you're just moving from big data to big models. So that's like a transition.

It's a very natural extension for us. We were quite surprised when the market started to use Covalent for these use cases. It makes sense. Structured data is like clean formatted, normalized data. Who would not want that? We started seeing a lot of use cases. We put out a post recently on all of the AI use cases that are being built today.

So, you know, we could perhaps put it in our show notes or something. But an example is SmartWales. So SmartWales is a platform that does, you know, on-chain copy trading. So you can follow any kind of wallet and then they like do a summary of like multiple wallets. And then they use AI to figure out if it's like a trap or if it's a scam or not. And so SmartWales is an example of an excellent project that's doing, you know, really fun stuff there.

Another example is Leica. Leica.ai uses AI for analytics. You see a lot of projects here. Again, we're not on the analytics layer, we're not on the retail side, but they're using all this data to train and then they can do really sophisticated analytics on tokens if you want to do your research and so on. Leica is a really cool program.

product for this. Another really cool thing I recently heard about is Ntendray Finance. And so this is offering anomaly detection predictive analytics, and this has a lot of traction for financial management. So in the back office, they're looking at your payroll, they're looking at your expenses and all that stuff. They can use AI to do fraud detection essentially.

Another example is Bitscrunch. So Bitscrunch is a project that recently went public. They did a coinless sale. They have Animoca and Coinbase as investors. And so they use Covalent's data for fraud analytics and all that stuff. So the base foundation data there, the data is Covalent behind all of these projects, right?

So those are some of the use cases, just like how we started Covalent before there was DeFi, before there was NFT, before there was GameFi. You know, the market evolves in different ways, but that's on the application layer. So we're on the infrastructure layer. So we empower all of these use cases. Wow, that's very impressive. I mean, it's good to see that you're empowering those innovations and

Those people out there are really just moving the needle and making a difference because of Covalent. Well, also you mentioned CQT several times.

in our talk today, can you also elaborate on the specific role that your token plays within the ecosystem? I guess that could be another unique differentiator, compare your tokenomics with other products. And also recently you have launched a token buyback program to bring off-chain revenue on-chain. Can you just share more insights?

Absolutely. So CQT stands for the Covalent Query Token. So it's a staking and governance token that belies this entire covalent economy. So...

Just from our experience of being in the market, your developers and your consumers of your product don't want to use your token for payments. It's kind of like friction, right? So these tokens are like a 2017 era relic. There's no point. So everything on the demand side, all of the revenue that customers are charged is all in US dollars.

So it's fixed, right? So there's no challenges, forecasting or budgeting or whatever. It's fixed. So that US dollar is then used as an on-chain mechanism to buy CKT. So when I mentioned that $1,000 a day, that revenue, that $1,000 is coming from customers. And then the CKT that is bought based on just like a market buy is distributed to the decentralized operators who actually do the work.

They earn in CQT. Think of it, maybe a close analogy is that I'm hiring some contractors in the Philippines, and I'm paying in the Philippines local currency because that's what they use to spend. I could pay them US dollars, but they'll sell it for their local economy. That's how it is. The whole covalent economy is based on CQT.

So now there's like, you know, other utilities, like we're going to be introducing a liquid staking kind of program. And so the delegation program is another utility here. So you can go as a token holder, go delegate against one of these operators. There's about 14 operators and we're just going to put out a post to recruit more operators.

And so they run the actual infrastructure, so you can delegate against their infrastructure. And so we have a whole tokenomics program there. And everything about the incentive for long-term data availability, even in the AI use case, if you see there's lawsuits against the New York Times,

which sued OpenAI because they're using all these New York Times articles to train their data. So if there's any kind of bias or any kind of revenue, then the royalties have to flow back, which means you need the entire track record of all of the mutations that have happened on the base model. All of that, like blockchain is a perfect use case for stuff like that. So back to the token.

It's a regular ERC-20 token. It's available on OKEx and Uniswap and SushiSwap and KuCoin and Gate. And you can hold the token or you can participate in the economy, which is as a delegator, you can stake your token and earn a yield. Or if you have enough technical know-how in running the infrastructure, you can become an operator.

But besides that, I think that's generally how the system works on the backend. Besides the DeFi utilities like providing LP and so on. Yeah, it is a very well-designed mechanism, I would say, especially all of the stakeholders in this game. They are incentivized. Well...

Given your very ambitious revenue generation goal, can you please just outline some sort of your strategic plan that, considering your steady growth with institutional users, do you foresee the unified API significantly driving that growth? Because there are two big pillars in your product line right now, right? One is Golden Rush, another one is unified API. So which one will be...

the secret recipe. So I think we've taken a different approach with revenue generation. And on the demand side, we actually have three products. We have the unified API, we have increment, Gold Rush. So these are like three products. And the way we design these products is think of it as multiple ingredients

or the same set of ingredients, multiple recipes. So you have this structured data, you have this database of structured data, and then you have Unified API, you have Gold Rush, which is a block explorer, a model of block explorer. You have Increment, which is like a Dune-like dashboarding product, but they're all based on the same data. So that's been our approach to having multiple use cases and personas based on the same indexed data.

So with regards to revenue generation, yes, we have pretty ambitious targets and we've been growing consistently month after month after month. Now, in terms of the unlocks, there's a couple of unique opportunities that are down the pipe. The first is the RPC stuff. So what is happening in the space is that all the RPC vendors are not storing historical archival data.

So now the whole industry is kind of like consolidating on Covalent because the whole point of Covalent and the long-term like Ethereum Wayback Machine and all that stuff is to hold the entire history of the blockchain. And we have the very custom architecture to enable that.

Because, you know, so we signed a deal with Infura. So Infura is now starting to like spill that traffic to us. We're seeing other kinds of like, I can't name these players, but they're all starting to like migrate their backend to Covalent as a stack. And so we should see significant revenue growth from that initiative, for example. Yeah.

Besides that, we have some gaps. We outlined this in our Covalent Vision, and we are very upfront with some of the shortcomings that we have in our data stack. So one of the biggest gaps is trace data. So for the most

toughest forensics and accounting cases, the trace data is a gap that we have. We're making strides on that and we'll plug that gap. The whole team is organized in a way where whatever actions they do is going to drive revenue down the line. That's a completely different part of Covalent where they're incentivized and they're motivated by different reasons. I'm pretty confident that we'll hit all of our targets.

It's a matter of product delivery and product pipeline and go-to-market and sales and stuff, right? Which is quite distinct. I think it's not a lot of companies have that kind of machine built for product and building outside of the token side of things.

Yeah, well, thank you for sharing all those insights and like backstage stories, because it sounds like you guys have pretty sophisticated, very well-designed mechanisms in all aspects. So looking forward to seeing more innovations happening on Covalent.

Let's just see the bigger picture of the whole like data indexing or whatever they've been calling. Well, how would you assess the current state of the on-chain data market, specifically focusing on the decentralized data indexing? Because there are like also centralized data indexing available in the market. Yeah. So, you know, I'm just going to be transparent here. I think

The centralized data indexers come and go. So they're not... I mean, we saw dozens of indexers come in last cycle, and they're all mostly dead today. We're seeing a lot of indexers enter the market now, right? And I don't know what's going to happen to them. I think the centralized indexers...

are not really within the ethos of decentralized technologies, especially if you want to feed this index data back into spot contracts.

So the trust assumptions in your data needs to be the same level as how the data got to the blockchain in the first place. So if you break that trust assumption, it has a limited total addressable market. That's really how this works, right? So your DA layer, for example, if you look at a Celestia or your EigenDA or Avail, right?

The trust of Celestia needs to be the exact as the L1 that it's securing. Otherwise people will hack Celestia and put fraud on the L1. So it's the same kind of like setup here. So it really matters, right? And so I think the centralized indexers can, you know, go get some customers, maybe a couple of million dollars of revenue, maybe for like some simple use cases, but for the toughest of the toughest use cases, right?

which is the whole point of crypto, you need the trust and the security guarantees. So we never think of like,

centralized indexes as competition ever, right? Because we know we've seen, like we've been around for a while. We see these guys come and go, they make a lot of noise. There was another project that Paradigm invested in last year called NXYZ. They raised $40 million and after a year they shut down. So, you know, it happens all the time. We see this like centralized indexes is not just, just not going to work in this space.

With decentralized indexers, there's a lot of claims about decentralization. But if you look closely behind the scenes, there's some points of centralization, including Covalent. We've been very transparent on how we are going on this progressive decentralization story. But if you think about the vision of who's trying to introduce something brand new, Covalent is the only indexer that has cryptographic security.

So every mutation on the data has a cryptographic proof that is submitted that anyone can audit. And this has been running at scale for multiple years. The network, the first role of the network launched summer of 2022. So almost a year and almost two years now.

So it was April, actually, it's exactly two years. So April, 2022. So for two years, even through the Nomad hack, even through all of this, like changes and stuff, the network itself has been like, has never stopped. So I think, you know, they say that a lot of projects, they die, you know,

because of lack of focus and not because their core stuff works. So we don't really think about other projects, what they're doing and so on. We are laser focused on what the industry needs, what our customers say they want, what are the toughest problems to solve that will forward the industry. So everything about the cryptographic security, no one really asked for this like two years ago when we built this, right? Two years ago is when we shipped. We've been working on this for like four or five years now.

But this is what we need. This is how you push the space forward, right? We are pioneers in this journey. So it's important for us to get that out. Yeah. I mean, I really admire that your mindset. And also, I'm feeling the same because those centralized players, sometimes they've made a lot of noises. But one day it would backfire them in a way. Well, what kind of notable trends have you observed recently?

in this market cycle. I know you don't want me to ask you about any sort of a timing thing, but is there any sort of like notable trends on your radar that you want to share with everyone, like regarding your, let me, maybe like business metrics in terms of your data indexing volume from like layer ones or any other kind of metrics that if there, yeah, because there are like a lot of speculations around, right? In this cycle, like-

So I would say what is real in terms of Covalent, like what is like absolutely, you know, real is the revenue is real. These are actual customers paying money to use protocol and the data.

That's a testament to the quality of data and the quality of service, right? No other index out there has revenue of this scale. We have fidelity, Ernst & Young as customers. So that just tells you how trustworthy the data is. The second thing is in terms of the impact, we did a calculation a few weeks ago. There's over 250 million wallets that consume or enriched by covalence data.

So this is all of the wallets, all of the custodians. So if you look at like jumps, custody products, they're all like covalent, um, things like, uh, ambient finance, which is a big, uh, project on scroll, uh, swap, uh,

SushiSwap. So all of those wallets, they use covalent data to get enriched structured data. So that's 250 million wallets in this space. So that's real, right? That's like the number of unique wallets we've seen use covalent data.

I would say the proofs that are submitted on-chain, anyone can download these proofs and rebuild the entire Ethereum state from the Genesis block. That is real. It's like you don't even have to talk to us. You can just go download the proofs and rebuild the stack. So that is real. So I would say these are the things that are real on Cobain. In terms of trends,

In ETH Denver, I was on a couple of panels. So definitely, I think this cycle is the DA cycle, the data availability cycle. I would say there's a big push on the AI stuff as well. That's a macro trend that's very, very, very exciting. And I would say the LSD, LRT seems to be top of mind for a lot of people. So-

I'm not a financial guy, so I don't understand the intricacies of how these liquid restaking tokens work and what the risk factors are. But there just seems to be a lot of attention on those tokens. So perhaps with EigenLayer and restaking and all that stuff, there's going to be a big move

you know, this year. But we only stick to things that we have expertise in and what is our sweet spot, which is data, data, data availability and AI. Yeah. Well, big thanks for sharing your expertise today because of the nascency of the web industry. So it's still pretty, there are a lot of like, you know, tweets and turns.

of the space, right? So we're already seeing all those like massive, like fresh, new, like capitals or, you know, like innovations flowing into our world with all those kind of like different kinds of experiments. Well, let's see how it goes. I want to leave you with two thoughts for your audience. Just to show you how we are. First point is that

Covalent has about 60,000 developers. Infuro has probably half a million developers. So Covalent has like 10% of what Infuro has. GitHub has 30 million developers. So Infuro has 1% of GitHub and Covalent has 0.1% of GitHub.

So that's how early we are. We haven't really done anything. And the second thing is that the bull market, you know, it's like, should I invest in these meme coins? Should I invest in like LLT, LST? I would say the biggest investment you can make is in yourself, in your knowledge, in your research, you know, your conviction. And if you believe in yourself, you know, you should double down on yourself.

And for people who've done that in just in my like limited history is they've done really well for themselves. So I want to just leave that message to our community and our audience here. Wow, that's very authentic. Well, thank you so much for everything. It's very fulfilling.

Blair, thank you so much for this excellent service that you do because I think we need more genuine builders and people with strong conviction. So if the listeners haven't had a chance, please read both the English and the Mandarin translation.

uh research reports quite extensive quite detailed and you know it goes really really deep uh so thank you so much for everything that uh you guys do for for the industry