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00:00:13.279Please welcome Kiet Tran, CEO of Lukka, in conversation with Stablecons, Dante Reminik, for a special Stable Pulse recording, sponsored by Lukka.
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00:00:17.120Hey everyone, welcome to Stable Pulse.
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00:00:19.519We have a really fun conversation here today.
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00:00:26.559We're gonna dive into data, how data interweaves itself into pretty much anything that digital assets touch.
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00:00:32.560It's gonna be very difficult for me to keep this to an allotted time Kiet, because I feel like we can go on for ever and ever.
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00:00:37.920There's a lot of rabbit holes to go down, but let's just kick things off with an introduction.
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00:00:40.159You have a very, very impressive background.
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00:00:42.640You've already done some very impressive things at Lukka.
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00:00:44.560Brag about yourself.
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00:00:49.359Well, bragging is not something I like to do, but I'll do my best.
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00:00:54.799Look, so I you know, I started my career at BlackRock Aladdin.
00:00:54.799 -->
00:00:59.759You know, one of the things I tell people is sometimes you better be lucky than to be good.
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00:01:02.640In my instance, I was lucky, right place, right time.
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00:01:10.239Um and then in early 05, I joined a startup called Market, which became IHS Market, right, which was acquired by S ⁇ P Global for $44 billion.
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00:01:18.959But during my journey there, I spent a lot of time around market infrastructure, market structure, especially around the OTC marketplace.
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00:01:23.840And one of the things we talked about was, you know, I was the team that actually built the ability to short mortgages.
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00:01:28.959So you read the big short, I dealt with all those cast of characters on a daily basis.
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00:01:36.079And I do think, you know, when we talk about digital assets in general, I think it's really part of market transformation.
00:01:36.079 -->
00:01:45.920I think overall global markets, we started with analog to, I would say, electronic in the 70s with NASDAQ, TTCC.
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00:01:52.480And I think the industry's gone digital in the 2000s with web APIs, mobile, et cetera.
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00:01:58.319And now my view is we're in the next phase, which I called programmable markets.
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00:02:07.439Imagine having assets and investments that have programmable logic, but also leveraging agents to transact and trade, right?
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00:02:09.919Which we've seen with Robert Hood and other platforms.
00:02:09.919 -->
00:02:14.560So I think that's the phase that we're in right now, which is quite exciting.
00:02:14.560 -->
00:02:23.759And what's exciting about Lukka is we think about Lukka at a macro level, look, Lukka is a global data and software infrastructure provider for digital assets.
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00:02:35.680We help institutions understand, value, reconcile, govern, and report digital assets with the same rigor that you need for traditional finance.
00:02:35.680 -->
00:02:48.560And the one thing people don't talk about is if I buy a stable coin or buy a digital asset, well, you still need to reconcile it back to your ERP system, your treasury system, your investor book record system, your accountable book record system.
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00:02:49.919That doesn't go away.
00:02:49.919 -->
00:02:53.520And that's the superpower that Lukka provides.
00:02:53.520 -->
00:02:59.680And we do this for a lot of infrastructure providers, fund administrators, exchanges, asset managers, banks.
00:02:59.680 -->
00:03:04.719And so for us, like we're the plumbers in suits that people don't talk about, right?
00:03:04.719 -->
00:03:05.759But that's what we do.
00:03:06.000 -->
00:03:06.879But everyone needs.
00:03:06.879 -->
00:03:07.680Exactly.
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00:03:08.240Exactly.
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00:03:08.960I love that.
00:03:08.960 -->
00:03:12.159And let's talk about what that data actually looks like.
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00:03:15.680To your point, you know, we've moved from an analog world to a digital world.
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00:03:22.479Now this is, you know, the second coming of progress of financialization online.
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00:03:33.520How is the data that people need to know when interacting with these digital assets, how has that changed since you know the first wave of innovation that's come through Wall Street?
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00:03:44.639I think you know there's the decentralization aspect, which on the opposite side means this lack of standard.
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00:03:44.960Yeah.
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00:03:49.120Something as simple as a Bitcoin, there's 30 plus tickers for Bitcoin, right?
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00:03:59.919And so when you think about like if I want to buy or sell a bond, if I want to buy a sell a stock, there's only a certain amount of exchange of venues I can do that with.
00:03:59.919 -->
00:04:05.840But if I want to buy crypto, there's a lot of C5, DeFi exchange, right?
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00:04:08.240We're connected to hundreds of venues.
00:04:08.240 -->
00:04:11.599And so how do you normalize all of that?
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00:04:12.080Right?
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00:04:13.520That's just the off-chain stuff.
00:04:13.520 -->
00:04:16.800And then you also then have to all the on-chain stuff.
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00:04:29.120And when you think about the on-chain stuff, let's say Solana, if I want to pull every single transaction for Solana down to the Genesis level, that's before indexing.
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00:04:32.480That's four to five hundred terabytes worth of data.
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00:04:35.040Massive amounts.
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00:04:54.319And so what Lukka has come to be in, and what we realize is because of our ability to understand and normalize both off and on-chain data, it helps us give institutions the ability to understand what asset are you holding, right?
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00:04:56.160What's backing this asset?
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00:04:58.319How do you reconcile your position?
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00:05:01.199How do you understand the counterpart you're dealing with?
00:05:01.199 -->
00:05:05.279And so to me, it's a big data challenge, right?
00:05:05.279 -->
00:05:08.160And that's something that we've focused a lot of our energy on.
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00:05:19.360Yeah, I think that there's this really interesting sort of dichotomy that happens with on-chain digital assets, because on one hand, you have the transparency of a blockchain, right?
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00:05:21.680Everything is recorded on that chain.
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00:05:27.839And on the other hand, it's almost so much data that it's hard to understand the actual actions behind that data.
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00:05:38.000How do you go about collecting terabytes and terabytes and terabytes of information and producing something that's workable, that's usable, that's actionable for your clients?
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00:05:46.879Yeah, I think a lot of it is our ability to triangulate and normalize.
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00:06:00.720And we're able to do that because a lot of the global fund administrators, so you know, you think about like hundreds of hedge funds or asset managers that buy and sell these things, they need a fund administrator.
00:06:00.720 -->
00:06:03.279Well, we're the ones that service the fund administrator.
00:06:03.279 -->
00:06:08.639So, because of that, you know, we understand all the assets, we understand the reconciliation of positions.
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00:06:10.800So that gives us an edge.
00:06:10.800 -->
00:06:20.639And because we also run our own blockchain nodes and we also do our own indexing, when you pull this together, it gives you a view that no other can have, right?
00:06:20.639 -->
00:06:24.560So you think about, for example, we're talking about, hey, everything's on a blockchain.
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00:06:30.399It is, let's say I have a Solana wallet, and on this wallet, there's six assets with a smart contract.
00:06:30.399 -->
00:06:32.399Like, well, what asset is that?
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00:06:33.279How do you link back?
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00:06:34.800Is this tokenized NVIDIA?
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00:06:35.040Yeah.
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00:06:36.079Is this a Bitcoin?
00:06:36.079 -->
00:06:36.720Like, what is this?
00:06:36.720 -->
00:06:37.839You have to follow the trail.
00:06:37.839 -->
00:06:38.720You have to follow the trail.
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00:06:44.240So we provide the linking and mapping of these trails to make everyone's lives a lot easier.
00:06:44.560 -->
00:06:52.879And there's one thing that you mentioned that I want to circle back on, which is the connection between the on-chain system and the off-chain system.
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00:06:53.360Right?
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00:06:56.480Anyone who's working with digital assets has to have both.
00:06:56.480 -->
00:06:59.759There's no fully on-chain solution, there's no fully off-chain solution.
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00:07:07.519Tell me about the challenges that most people face when dealing with mirroring the on-chain and off-chain solution and how you guys go about solving that.
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00:07:23.360I think a lot of it is it's really about reconciliation and understanding one, realizing that issuing a smart contract and tokenizing is the first of many steps.
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00:07:27.439You think about a bank, well, you gotta connect back to the 30 systems the bank's sitting on.
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00:07:27.759Yeah.
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00:07:28.480Right.
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00:07:35.439And so it's really about building that connectivity on what it means on-chain, what it means off-chain.
00:07:35.439 -->
00:07:37.759Let's use NVIDIA as an example, right?
00:07:37.759 -->
00:07:39.680Nvidia is a stock.
00:07:39.680 -->
00:07:47.360Well, NVIDIA has a stock taker, it trades on these exchanges, it has an ISIN, it has a QCIP, it has a CETO.
00:07:47.360 -->
00:07:53.199And what we do is we then map that to then all the tokenized versions of NVIDIA, right?
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00:07:54.319That's on-chain.
00:07:54.319 -->
00:07:58.079We map it to all the prediction markets that are related to NVIDIA.
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00:08:02.800We map all the perpetual futures that are in NVIDIA to then give you a 360 view.
00:08:02.800 -->
00:08:07.759So when you're doing the reconciliation, you now have an apples to apples linkage.
00:08:07.759 -->
00:08:10.879But then there's more to that.
00:08:10.879 -->
00:08:21.680And what I mean by that is in the traditional world of how we deal with, like a stock has a corporate actions, etc., on the blockchain, location matters.
00:08:21.680 -->
00:08:30.720And so I do think it's the decision of how we build our data model where we would have an identifier for an asset.
00:08:30.720 -->
00:08:33.679Let's look at Bitcoin, we have a global identifier.
00:08:33.679 -->
00:08:37.360But Bitcoin on Ethereum, we also have an identifier.
00:08:37.360 -->
00:08:39.919So we have an identifier at the asset location level.
00:08:39.919 -->
00:08:44.240So then that gives us this deep linkage back to all the breadthcrumbs.
00:08:44.240 -->
00:08:49.679And so anyone that wants to reconcile on and off chain, they can use all these breadthcrumbs to reconcile.
00:08:49.679 -->
00:08:51.519And that's going to be important, right?
00:08:51.519 -->
00:08:57.360Because look, your accountant book record system, your investment booker record system, your P it's not going away.
00:08:57.360 -->
00:08:58.639You're not changing that overnight.
00:08:58.799 -->
00:08:58.960Yeah.
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00:08:59.279Right?
00:08:59.279 -->
00:09:08.320In fact, it'll probably get more complicated as more assets come on chain, more issuance, more money moving on a blockchain, on blockchains.
00:09:08.320 -->
00:09:11.600I imagine this, there's just compounding complexity to what you're doing.
00:09:12.000 -->
00:09:16.480So the the way I put this is um, and you you're too young, or maybe I'm too old.
00:09:16.480 -->
00:09:19.279You think about like the early internet days, right?
00:09:19.279 -->
00:09:24.320In the early internet days, you know, people have a store and then they sell online.
00:09:24.320 -->
00:09:32.159But they have an online system, inventory system, they have a store inventory system, they don't talk to each other, which means they don't have an inventory system.
00:09:32.159 -->
00:09:40.480So in today you have your C5, your D5, your TRAF Fi, and they don't reconcile, you don't have a ledger, right?
00:09:40.480 -->
00:09:42.639So that needs to be reconciled.
00:09:42.639 -->
00:09:46.399And that's really a big part of where Lukkas sees our value in the future.
00:09:46.799 -->
00:09:47.840So let's talk about this.
00:09:47.840 -->
00:09:54.000And honestly, there is probably a more tactful way to ask you this question, but who cares?
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00:09:54.559Right?
00:09:54.559 -->
00:10:03.919Like when it comes to digital assets and data, what are the negative externalities of not working with someone like Lukka?
00:10:03.919 -->
00:10:16.320Like if you know I have a hedge fund or I have a financial institution and I want to go trade, what can happen if I don't maniacally focus on this level of reconciliation and building out this comprehensive data layer?
00:10:16.720 -->
00:10:22.559I mean, you don't understand your risk profile, you don't understand your positions, how are you reporting back to your regulators, right?
00:10:22.559 -->
00:10:32.799And one of the things we know is there's more and more regulatory clarity, which means you need to report this back to all your global regulators, right?
00:10:32.799 -->
00:10:40.720Whether it's Cough, 1098, Mika, there's all these regulations you need to align back to.
00:10:40.720 -->
00:10:43.759But also just a smart way of running your own business.
00:10:43.759 -->
00:10:44.080Yes.
00:10:44.080 -->
00:10:48.080Like why would you run a business and not be able to reconcile all your inventories?
00:10:48.080 -->
00:10:48.639Absolutely.
00:10:48.639 -->
00:10:49.120Right.
00:10:49.120 -->
00:10:56.480And so to me, any institutions, and look, this this is really the premise of Lukka's founding, right?
00:10:56.480 -->
00:10:56.799Yeah.
00:10:56.799 -->
00:11:01.120Um, Lukka was originally known as a Bitcoin tax calculator.
00:11:01.120 -->
00:11:02.559We found in 2014.
00:11:02.879 -->
00:11:03.440Interesting.
00:11:03.679 -->
00:11:10.159And then we realized that institutions will step into this space.
00:11:10.720 -->
00:11:10.960Right.
00:11:11.039 -->
00:11:13.759And that's how my focus is really more around crypto, right?
00:11:13.759 -->
00:11:25.120And so what we did, we say, well, if institutions were to participate in this asset class and this marketplace, they would need to be familiar with how they operate in other markets.
00:11:25.120 -->
00:11:34.080You need a reference data layer, you need a corporate actions layer, you need a pricing evaluation layer that's actually RFS Gap compliant.
00:11:34.080 -->
00:11:34.960That's key.
00:11:34.960 -->
00:11:41.840So what's interesting is all these digital asset startups that are going public, the first thing that ought to have them do is call Lukka.
00:11:41.840 -->
00:11:45.279Because we're still the only RFS Gap compliant valuation service out there.
00:11:45.279 -->
00:11:46.399That's amazing.
00:11:46.399 -->
00:11:52.879And then how do you build your ledger system on tracking your investment book or record, your account book record?
00:11:52.879 -->
00:11:57.360So we built a full stack with the view that institutions will come in.
00:11:57.360 -->
00:12:07.200And what we realize is the opportunity is not in crypto because crypto is the first asset class tested on the blockchain and tested on digital asset.
00:12:07.200 -->
00:12:10.000We think the future rail is digital asset.
00:12:10.879 -->
00:12:14.159And and so Can you tell me more about that?
00:12:14.159 -->
00:12:17.759Why you say the future rail is digital assets themselves?
00:12:18.240 -->
00:12:31.279I I think, look, I I think the reality is the biggest unlock is really around 24-7, collateral unlock, the efficiencies that it brings, right?
00:12:31.279 -->
00:12:34.639But let's not confuse that as an asset class.
00:12:34.639 -->
00:12:45.360It's not an asset class because you will have tokenized versions of fixed income, tokenized versions of equities, which you see in the Nasdaq, DTC, NICE are running through.
00:12:45.360 -->
00:12:50.000You know, as my point is, you know, market's gonna be programmable.
00:12:50.000 -->
00:12:53.360But not every asset class remove the same speed of direction.
00:12:53.360 -->
00:12:56.159But it's quite timely that we're at stablecoin today.
00:12:56.159 -->
00:13:07.120I think stable coin is what's driving a lot of these innovations because what is a stablecoin at a very macro level is an atomically settled liability.
00:13:07.120 -->
00:13:14.399You still need the assets back in it, which is short-term treasuries, repoils, money market funds, that's still T plus one, T plus two.
00:13:14.399 -->
00:13:16.159So what you gotta tokenize that, right?
00:13:16.159 -->
00:13:22.320So I think these drivers are really showcasing the value of digital asset as a rail.
00:13:22.639 -->
00:13:31.679I I really like that mental model and something you and I were talking about backstage of stable coins as a connection layer between disparate systems, right?
00:13:31.679 -->
00:13:38.080You might have an RWA issuer over here, an exchange over there, a different RWA issuer over on the other end.
00:13:38.080 -->
00:13:42.320And the way to connect all of these disparate systems is with stablecoins.
00:13:42.320 -->
00:13:45.200So I'm a I'm a really, really big fan of that mental model.
00:13:45.200 -->
00:13:51.279We've talked a lot about using data retroactively for reconciliation.
00:13:51.279 -->
00:14:02.639Are people also using the data that you're collecting for future actions to inform what moves they should be taking in the future, not just reconciling what's happened in the past?
00:14:03.279 -->
00:14:03.840It varies.
00:14:03.840 -->
00:14:10.320Look, so we we also power a lot of uh hedge funds and opdesks that it's also not widely known.
00:14:10.320 -->
00:14:13.360I think part of the challenge is we do great work behind the scenes.
00:14:13.360 -->
00:14:18.559We don't go around bragging because that's not what we do best at, but maybe we need to do a better job bragging.
00:14:18.559 -->
00:14:22.480Um a lot of opdesks do use us, right?
00:14:22.480 -->
00:14:27.279And because we have a diverse type of data set that allows them to triangulate.
00:14:27.279 -->
00:14:36.240Imagine understanding what's happening in the prediction market, perpetual market, or tokenizer real-world assets, it gives them an edge that they otherwise wouldn't have.
00:14:36.639 -->
00:14:36.960Interesting.
00:14:36.960 -->
00:14:43.360I imagine that having all this data is not only a performance advantage, but there's also a risk and regulatory advantage.
00:14:43.360 -->
00:15:02.080We've talked a little bit off the stage about market structure, what's happening in the United States, what's happening around the world, just in terms of forcing financial institutions to comply with various different laws around, you know, you're able to use this issuer, not this issuer, you know, this is what a good digital asset practice looks like.
00:15:02.080 -->
00:15:12.559How have you guys needed to adapt with the market structure that's coming up around the world in terms of the type of data that you collect or the type of data that your clients want?
00:15:13.200 -->
00:15:20.080Yeah, I think a big part of that is you know, one of the things our team has harnessed over the last year.
00:15:20.080 -->
00:15:25.919So, since taking over Lukka, you know, my view is if you're not an AI company, you're not a company.
00:15:25.919 -->
00:15:32.960And so we've invested heavily in our AI infrastructure and really give us that flexibility to operate.
00:15:32.960 -->
00:15:38.399And so behind the scenes and what runs everything is is a platform called Lukka Intelligence.
00:15:38.399 -->
00:15:46.159So think of it as you know, Claude Cowork or OpenAI Codex, but for capital markets workflow.
00:15:46.159 -->
00:15:47.440And our team runs on it.
00:15:47.440 -->
00:15:53.279You know, we have our Okidomo agent that goes and really uh spin up nodes.
00:15:53.279 -->
00:15:55.600Uh we have a recon agent.
00:15:55.600 -->
00:16:02.799And so a lot of these tech advancements has allowed us to really accelerate what we do.
00:16:02.799 -->
00:16:09.039And if you think about it's not just about the AI, it's about the data power in the AI.
00:16:09.039 -->
00:16:13.440So because we send in so much data, it gives us that tremendous advantage.
00:16:13.840 -->
00:16:16.080Can we go down this agent rabbit hole for a little bit?
00:16:16.080 -->
00:16:22.720I want to get a better understanding of how you guys are using agents to collect, decipher all this data.
00:16:22.720 -->
00:16:24.559But also on the other side, right?
00:16:24.559 -->
00:16:27.039Are your are your clients using agents?
00:16:27.039 -->
00:16:31.200Are those agents being informed by the data that that you're collecting?
00:16:31.200 -->
00:16:32.639Walk me through all of it.
00:16:33.120 -->
00:16:36.399Well, what's interesting is we we haven't exposed this to our clients yet.
00:16:36.399 -->
00:16:36.720Oh.
00:16:36.720 -->
00:16:39.039But uh but we've demoed them and they want it.
00:16:39.039 -->
00:16:39.759Of course.
00:16:39.759 -->
00:16:50.559Look, for us, it's really about how do you harness deterministic workflow and probabilistic workflow?
00:16:50.559 -->
00:16:53.360The LM itself is a probabilistic workflow, right?
00:16:53.360 -->
00:16:56.240Give me the next word, give me the next context, right?
00:16:56.240 -->
00:17:02.879But when you're reconciling, you know, you can't run a financial model and say, well, the answer could be this or that or that.
00:17:02.879 -->
00:17:03.519Right?
00:17:03.519 -->
00:17:05.440It needs to be deterministic.
00:17:05.440 -->
00:17:10.240And for an AI workflow to be functional, you need what I DMS the ACES.
00:17:10.240 -->
00:17:11.599What does that mean?
00:17:11.599 -->
00:17:18.640It needs to be accurate, it needs to be consistent, it needs to be explainable, and it needs to be secure.
00:17:18.640 -->
00:17:26.880And our view is there's no better way to prove it than to run this ourselves with the workflow we run on.
00:17:26.880 -->
00:17:32.640And we're now at a stage where we're so confident we're in the process of rolling this out to our client base.
00:17:32.640 -->
00:17:33.359Amazing.
00:17:33.359 -->
00:17:42.160And that's the that's the power really about leveraging and harnessing the technology with the deep insights the team bring.
00:17:42.160 -->
00:17:50.960And one of the things you know people don't realize is the way I use LM versus the way someone else uses may be different because I have different contexts.
00:17:50.960 -->
00:17:57.519And I do think the next phase of theta, it's about context on how to do something.
00:17:57.519 -->
00:17:57.839Right?
00:17:58.480 -->
00:18:02.160Do you see your job as my job is to get the best context for my clients?
00:18:02.160 -->
00:18:03.599That's exactly it.
00:18:03.599 -->
00:18:04.640I love that.
00:18:04.640 -->
00:18:06.480What context engineers?
00:18:06.480 -->
00:18:07.279That's what we are.
00:18:07.279 -->
00:18:11.839So it's a really interesting way of looking at what what Lukka does.
00:18:11.839 -->
00:18:14.400Does it stop at context?
00:18:14.400 -->
00:18:20.640Or do you guys take that context and and turn that into insights?
00:18:20.640 -->
00:18:23.759Or do you just give your clients the tools to do that themselves?
00:18:23.759 -->
00:18:25.519It's it's both.
00:18:25.759 -->
00:18:29.920Look, I I I I think the the future is going to be headless in a way, right?
00:18:29.920 -->
00:18:32.160So all solutions, we have all the MCPs.
00:18:32.160 -->
00:18:35.119MCPs is available on anthropic marketplace.
00:18:35.119 -->
00:18:35.440Yep.
00:18:35.440 -->
00:18:37.200The Lukka MCPs are?
00:18:37.200 -->
00:18:37.519Yeah.
00:18:37.519 -->
00:18:37.680Yeah.
00:18:37.680 -->
00:18:38.240Amazing.
00:18:38.240 -->
00:18:41.759Um again, we need to do a better job marketing that, but we do have that, right?
00:18:41.759 -->
00:18:47.039Um But we've also harnessed our own LM and run our own stack internally.
00:18:47.039 -->
00:18:58.240And one of the things we realize is that the more we run our workflow on, the more we're giving it context, right?
00:18:58.240 -->
00:19:05.119And so we've been hosting our own open weight model, and we've been building what I call the lucka brain.
00:19:05.119 -->
00:19:12.880And the more we inject context into the brain, what it does is really put guardrails to make sure it doesn't go heywhy, right?
00:19:12.880 -->
00:19:24.799And to make sure that the output is deterministic, even though the workflow combines deterministic tooling with probabilistic solutions in the mix.
00:19:25.599 -->
00:19:32.640I imagine, though, that the complexity of this context is something that you have seen grown tremendously.
00:19:32.640 -->
00:19:42.000Again, always more chains, always more assets on chain, always more issuers coming and issuing 17 versions of SpaceX stock.
00:19:42.000 -->
00:19:50.480How has that challenged your team to build out these contextual models differently as just the snowball of complexity?
00:19:50.960 -->
00:19:52.480Well, well, to add to that, right?
00:19:52.480 -->
00:19:56.400So it's funny, one of my good friends, you know, they launched a stablecoin uh last year.
00:19:56.400 -->
00:19:58.559It's like the same day, 10 fixed stable coins came out.
00:19:58.559 -->
00:19:58.880Of course.
00:19:58.880 -->
00:20:00.079Trying to pretend to be us, right?
00:20:00.079 -->
00:20:00.400Of course.
00:20:00.400 -->
00:20:03.119So that's the other level of complexity you need to solve.
00:20:03.119 -->
00:20:11.599I I think the advantage we have is because of the reference data and a lot of the work we put in place, it gives us that edge.
00:20:11.599 -->
00:20:24.480So we have a massive deterministic set of tooling and database, and marrying that with these probabilistic tools and hosting our open weight models allow us to triangulate that we otherwise couldn't.
00:20:24.720 -->
00:20:24.880Right?
00:20:25.039 -->
00:20:40.400So you think about tracking and tracing and being able to have a deep understanding on the 1.2 billion wallets that we're tracking trades, marrying that with this AI tooling will give you superpower you otherwise didn't have.
00:20:40.400 -->
00:20:46.799And so for us, it's really about embracing this new tooling and going all in on it.
00:20:47.200 -->
00:20:47.920I like that.
00:20:47.920 -->
00:20:59.039So that's, I imagine, what most of your team spends its time on is you know, you advertise yourselves as, hey, we're we're a tool for people who are working with digital assets.
00:20:59.039 -->
00:21:03.519But on the back end, you guys are entirely focused on how to optimize with agents and everything like that.
00:21:03.519 -->
00:21:04.319Exactly.
00:21:04.319 -->
00:21:11.039Do you see your clients being as aggressive on the AI front and on the agent front as you guys are?
00:21:12.400 -->
00:21:16.160It I think it varies on the types of accounts.
00:21:16.160 -->
00:21:21.359Look, I I think everyone went from token maxing to now value maxing.
00:21:21.359 -->
00:21:22.160As it should be.
00:21:22.160 -->
00:21:22.799As it should be.
00:21:22.799 -->
00:21:23.039Yeah.
00:21:23.039 -->
00:21:31.599Look, the issue is this, why would you give your data, give your context to frontier models and pay them at the same time?
00:21:31.599 -->
00:21:34.640There's nothing worse than the Toys Rust moment, right?
00:21:34.640 -->
00:21:39.039When Toys of Rust taught Amazon how to be in a toy business, and Amazon, well, thank you very much.
00:21:39.039 -->
00:21:40.480We're now in the toy business.
00:21:40.480 -->
00:21:41.119Yeah.
00:21:41.119 -->
00:21:47.440And so the the next phase is really around AI sovereignty.
00:21:47.440 -->
00:22:02.799But the reality is, I I think part of the challenge we're seeing, look for very large institutions, and I may get in trouble for saying this, but you know, the executive level to the person that knows what they're doing, It's like probably six to eight levels in between of middle management.
00:22:02.799 -->
00:22:05.920And so every company's going through a different journey.
00:22:05.920 -->
00:22:09.519I've seen some firms that shut off all AI access because they freaked out.
00:22:09.519 -->
00:22:11.759To other firms say, you know what?
00:22:11.759 -->
00:22:15.119Let's play with it, let's figure out.
00:22:15.119 -->
00:22:19.039And so there's no one size fit all.
00:22:19.039 -->
00:22:26.799But the reality is in today's world with all these models, it's like keeping up with the Joneses.
00:22:26.960 -->
00:22:27.200Yeah.
00:22:27.440 -->
00:22:28.799So Astra just came out, right?
00:22:28.799 -->
00:22:32.160Astra, the open I version 6, whatever the case is.
00:22:32.160 -->
00:22:38.240Um, you know, you have a new version of an LR model everywhere with all these open models.
00:22:38.240 -->
00:22:40.319So how do you know which one to use?
00:22:40.319 -->
00:22:45.359Like it's intimidating, it's confusing, which is similar than all this blockchain, right?
00:22:45.359 -->
00:22:47.039All these different chains, all these different access.
00:22:47.039 -->
00:22:49.920There's two incredibly complex systems that are coming together.
00:22:49.920 -->
00:22:50.960That's exactly it.
00:22:50.960 -->
00:22:56.160So our view is we just help harness this on behalf of our clients.
00:22:56.160 -->
00:22:59.920So they don't need to worry about which arm to use, which system to harness.
00:22:59.920 -->
00:23:07.119Look, put it this way: if I need to know who's the first president of the United States, I don't need fable.
00:23:07.119 -->
00:23:10.400The dumbest model will, in theory, know the answer.
00:23:10.400 -->
00:23:10.880Yes.
00:23:10.880 -->
00:23:14.880So how do you harness that orchestration across workflow?
00:23:14.880 -->
00:23:24.960And our view is, you know, we're we're using this for our own cooking deeply internally, so that we'll offer this out to our customers.
00:23:24.960 -->
00:23:32.640And that's really been the advantage, is you know, everyone is an AI expert across Lukka, right, from that perspective.
00:23:33.039 -->
00:23:33.519I love that.
00:23:33.519 -->
00:23:39.519And again, backstage, you and I were talking about how it's still the very, very early days of Lukka.
00:23:39.519 -->
00:23:46.079You've gone out, you've built this incredible system that marries the complexity of digital assets and the complexity of AI.
00:23:46.079 -->
00:23:51.680You're actively delivering value to some of the world's largest financial institutions, but it's still the early days.
00:23:51.680 -->
00:23:53.359What's next?
00:23:54.960 -->
00:23:59.680Look, I I think financial institutions are getting the joke.
00:23:59.680 -->
00:24:04.480You think about this whole stablecoin today, how many banks you see here, right?
00:24:04.480 -->
00:24:14.079And so if you're a financial institution and you don't treat digital asset or stablecoin seriously, then you're sleeping under a rock.
00:24:14.079 -->
00:24:19.200And I think that leads to a lot of opportunities for Luke and what we built, right?
00:24:19.200 -->
00:24:23.440We've been building to waiting for this moment, and the moment is here.
00:24:23.440 -->
00:24:24.880So it's quite exciting for us.
00:24:24.880 -->
00:24:26.720You know, the team is super busy.
00:24:26.720 -->
00:24:31.279Um, and I I do think this tailwind continue to be an opportunity for us.
00:24:31.519 -->
00:24:39.599Yeah, I mean, to your point, you and I have spent the last 48 hours straight talking to people who are building out stablecoin programs or in one way or another.
00:24:39.599 -->
00:24:54.880But whether they're uh a hedge fund that wants to R between stable coins, whether they're a B2B stablecoin orchestration company, I think that where the Venn diagram converges is that every single one of those companies needs data.
00:24:54.880 -->
00:25:02.480Like you cannot unequivocally run any type of digital asset program without having the data to back that up.
00:25:02.480 -->
00:25:12.640Have you found that the type of data that is needed across these variety of different clients changes, or does everyone need roughly the same type of data?
00:25:12.960 -->
00:25:16.079So it's not just about data, but I would say data infrastructure.
00:25:16.079 -->
00:25:16.640Okay.
00:25:16.640 -->
00:25:17.200Right?
00:25:17.200 -->
00:25:23.839Because you need to map back to all the on-chain data, and there's a massive amount of data.
00:25:23.839 -->
00:25:24.079Right?
00:25:24.079 -->
00:25:26.559It's Lukka sitting on 10 plus pay to bytes worth of data.
00:25:26.559 -->
00:25:29.039So it's a massive data set.
00:25:29.039 -->
00:25:36.240But it's also a massive exercise of mapping all the breadcrumbs.
00:25:36.240 -->
00:25:44.480And so I think that's the advantage that Lukka brings to the table is all the breadcrumbs that we map to give you that end-to-end linkage.
00:25:44.480 -->
00:25:48.880And so think of us as not just data, but data infrastructure.
00:25:49.039 -->
00:25:49.279Yeah.
00:25:49.519 -->
00:26:00.559And I I do think that's something that everyone's gonna need if you want to be able to reconcile back and report back to your investors and regulators, you know, your positions, your risk, exposure, etc.
00:26:00.559 -->
00:26:01.599That's going to be important.
00:26:01.839 -->
00:26:02.079Yeah.
00:26:02.079 -->
00:26:09.039I mean, I talk about we we talk about the stablecoin stack, and oftentimes that stack is made out of various different infrastructure components.
00:26:09.039 -->
00:26:16.000You have, you know, your wallets over here, you have your ramps over here, you have a custody provider, an issuer, whatever that might be.
00:26:16.000 -->
00:26:25.440Do you find that people are coming to the data layer in the stack at the right time, or is this often something that they realize, you know, after the fact, uh-oh.
00:26:25.440 -->
00:26:30.079You know, now that I need to do all this reporting, I need to go after the data, the right data.
00:26:30.160 -->
00:26:30.640Aaron Powell Yeah.
00:26:30.640 -->
00:26:35.440In in a lot of cases, what they end up doing, because they need to set up right, they end up doing a lot of bodies at it.
00:26:35.440 -->
00:26:35.599Yeah.
00:26:35.599 -->
00:26:35.920Right.
00:26:35.920 -->
00:26:38.000Things end up being super manual.
00:26:38.000 -->
00:26:38.640Yes.
00:26:38.640 -->
00:26:46.720And I do think that's the advantage we provide is you leverage Lukka, you no longer need that many people in that process you've got to put in place, right?
00:26:46.720 -->
00:26:49.359On this reconciliation nightmare you gotta run.
00:26:49.519 -->
00:27:05.759Aaron Powell I I always find it funny when you know the the some of the most advanced financial organizations in the world, people who are working with agents, people who are working on the frontier of trading or whatever it might be, still have a team of 10 working off of a shared spreadsheet to reconcile all their dates.
00:27:05.759 -->
00:27:06.000Trevor Burrus, Jr.
00:27:06.000 -->
00:27:08.079Funny, I was talking about someone earlier today.
00:27:08.079 -->
00:27:08.880It's ridiculous.
00:27:08.880 -->
00:27:09.839But it's over the place.
00:27:09.839 -->
00:27:10.400But it's true.
00:27:10.559 -->
00:27:10.640It's true.
00:27:10.640 -->
00:27:11.119It's true.
00:27:11.759 -->
00:27:20.400You know, I see people using the most advanced technology still running off of an Excel sheet and still doing OTC trades by texting their banker and whatever.
00:27:20.400 -->
00:27:21.680That's right, that's right.
00:27:21.680 -->
00:27:24.240Signal WhatsApp, telegram.
00:27:24.240 -->
00:27:38.480Trevor Burrus, Jr.: It's the dark duopoly of innovation in this space, is that there are people who push and push and push the frontier, but also still still operate on really old human-centric uh actions, I would say.
00:27:38.480 -->
00:27:46.319So hopefully you can do a lot to eradicate that and just say, hey, run the most advanced system in the world, and we'll handle the rest.
00:27:46.319 -->
00:27:47.599Exactly.
00:27:47.599 -->
00:27:48.799I love it.
00:27:48.799 -->
00:27:58.480So there's going to be a lot of people who are listening to this, who are building out these programs, who are at financial institutions, who are at B2B payment companies, whatever it might be.
00:27:58.480 -->
00:28:02.240How should they get a hold of your team if they want to learn more?
00:28:02.240 -->
00:28:03.039What do they do?
00:28:03.039 -->
00:28:04.559What's the next step for everyone here?
00:28:04.880 -->
00:28:06.160Yeah, look, look at that tech.
00:28:06.160 -->
00:28:07.759We also have a LinkedIn page.
00:28:07.759 -->
00:28:09.680Uh definitely hit up our team.
00:28:09.680 -->
00:28:17.519I I do think once you get to know us as a team, once you get to see our platform, you're gonna find out you've been missing out.
00:28:17.839 -->
00:28:18.880I can confirm that.
00:28:18.880 -->
00:28:20.000Their team is great.
00:28:20.000 -->
00:28:24.799Uh and I also, the one thing that I really like about your team is that you recognize that every data problem is different.
00:28:24.799 -->
00:28:28.160And so you customize a lot of the work to the individual clients.
00:28:28.160 -->
00:28:30.799And I think that that's something that's really, really special with space.
00:28:30.799 -->
00:28:32.880But Kit, I really appreciate you coming up here.
00:28:32.880 -->
00:28:35.759Like I said, you and I could do this for three more hours.
00:28:35.759 -->
00:28:42.960So we're gonna have to have you back and you know dive into the nuances of market structure and and home mortgages and everything like that.
00:28:42.960 -->
00:28:44.160But that's for another time.
00:28:44.160 -->
00:28:46.559I appreciate you coming up, and uh, we'll see you soon.
00:28:46.559 -->
00:28:47.359Thank you for having me.
00:28:47.359 -->
00:28:48.640Have a good one.
