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The Hidden Data Problem Behind Institutional Crypto w/ Kiet Tran · The Stable Pulse

• 0:00
  Intro: Please welcome Kiet Tran, CEO of Lukka, in conversation with Stablecons, Dante Reminik, for a special Stable Pulse recording, sponsored by Lukka.
• 0:14
  Dante Reminick: Hey everyone, welcome to Stable Pulse.
• 0:17
  Dante Reminick: We have a really fun conversation here today.
• 0:19
  Dante Reminick: We're gonna dive into data, how data interweaves itself into pretty much anything that digital assets touch.
• 0:26
  Dante Reminick: It'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.
• 0:32
  Dante Reminick: There's a lot of rabbit holes to go down, but let's just kick things off with an introduction.
• 0:37
  Dante Reminick: You have a very, very impressive background.
• 0:40
  Dante Reminick: You've already done some very impressive things at Lukka.
• 0:42
  Dante Reminick: Brag about yourself.
• 0:46
  Kiet Tran: Well, bragging is not something I like to do, but I'll do my best.
• 0:49
  Kiet Tran: Look, so I you know, I started my career at BlackRock Aladdin.
• 0:54
  Kiet Tran: You know, one of the things I tell people is sometimes you better be lucky than to be good.
• 0:59
  Kiet Tran: In my instance, I was lucky, right place, right time.
• 1:02
  Kiet Tran: Um 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.
• 1:10
  Kiet Tran: But during my journey there, I spent a lot of time around market infrastructure, market structure, especially around the OTC marketplace.
• 1:18
  Kiet Tran: And one of the things we talked about was, you know, I was the team that actually built the ability to short mortgages.
• 1:23
  Kiet Tran: So you read the big short, I dealt with all those cast of characters on a daily basis.
• 1:28
  Kiet Tran: And I do think, you know, when we talk about digital assets in general, I think it's really part of market transformation.
• 1:36
  Kiet Tran: I think overall global markets, we started with analog to, I would say, electronic in the 70s with NASDAQ, TTCC.
• 1:45
  Kiet Tran: And I think the industry's gone digital in the 2000s with web APIs, mobile, et cetera.
• 1:52
  Kiet Tran: And now my view is we're in the next phase, which I called programmable markets.
• 1:58
  Kiet Tran: Imagine having assets and investments that have programmable logic, but also leveraging agents to transact and trade, right?
• 2:07
  Kiet Tran: Which we've seen with Robert Hood and other platforms.
• 2:09
  Kiet Tran: So I think that's the phase that we're in right now, which is quite exciting.
• 2:14
  Kiet Tran: And 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.
• 2:23
  Kiet Tran: We help institutions understand, value, reconcile, govern, and report digital assets with the same rigor that you need for traditional finance.
• 2:35
  Kiet Tran: And 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.
• 2:48
  Kiet Tran: That doesn't go away.
• 2:49
  Kiet Tran: And that's the superpower that Lukka provides.
• 2:53
  Kiet Tran: And we do this for a lot of infrastructure providers, fund administrators, exchanges, asset managers, banks.
• 2:59
  Kiet Tran: And so for us, like we're the plumbers in suits that people don't talk about, right?
• 3:04
  Kiet Tran: But that's what we do.
• 3:06
  Dante Reminick: But everyone needs.
• 3:06
  Dante Reminick: Exactly.
• 3:07
  Dante Reminick: Exactly.
• 3:08
  Dante Reminick: I love that.
• 3:08
  Dante Reminick: And let's talk about what that data actually looks like.
• 3:12
  Dante Reminick: To your point, you know, we've moved from an analog world to a digital world.
• 3:15
  Dante Reminick: Now this is, you know, the second coming of progress of financialization online.
• 3:22
  Dante Reminick: How 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?
• 3:34
  Kiet Tran: I think you know there's the decentralization aspect, which on the opposite side means this lack of standard.
• 3:44
  Dante Reminick: Yeah.
• 3:45
  Kiet Tran: Something as simple as a Bitcoin, there's 30 plus tickers for Bitcoin, right?
• 3:49
  Kiet Tran: And 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.
• 3:59
  Kiet Tran: But if I want to buy crypto, there's a lot of C5, DeFi exchange, right?
• 4:05
  Kiet Tran: We're connected to hundreds of venues.
• 4:08
  Kiet Tran: And so how do you normalize all of that?
• 4:11
  Kiet Tran: Right?
• 4:12
  Kiet Tran: That's just the off-chain stuff.
• 4:13
  Kiet Tran: And then you also then have to all the on-chain stuff.
• 4:16
  Kiet Tran: And 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.
• 4:29
  Kiet Tran: That's four to five hundred terabytes worth of data.
• 4:32
  Kiet Tran: Massive amounts.
• 4:35
  Kiet Tran: And 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?
• 4:54
  Kiet Tran: What's backing this asset?
• 4:56
  Kiet Tran: How do you reconcile your position?
• 4:58
  Kiet Tran: How do you understand the counterpart you're dealing with?
• 5:01
  Kiet Tran: And so to me, it's a big data challenge, right?
• 5:05
  Kiet Tran: And that's something that we've focused a lot of our energy on.
• 5:08
  Dante Reminick: Yeah, 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?
• 5:19
  Dante Reminick: Everything is recorded on that chain.
• 5:21
  Dante Reminick: And on the other hand, it's almost so much data that it's hard to understand the actual actions behind that data.
• 5:27
  Dante Reminick: How 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?
• 5:39
  Kiet Tran: Yeah, I think a lot of it is our ability to triangulate and normalize.
• 5:46
  Kiet Tran: And 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.
• 6:00
  Kiet Tran: Well, we're the ones that service the fund administrator.
• 6:03
  Kiet Tran: So, because of that, you know, we understand all the assets, we understand the reconciliation of positions.
• 6:08
  Kiet Tran: So that gives us an edge.
• 6:10
  Kiet Tran: And 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?
• 6:20
  Kiet Tran: So you think about, for example, we're talking about, hey, everything's on a blockchain.
• 6:24
  Kiet Tran: It is, let's say I have a Solana wallet, and on this wallet, there's six assets with a smart contract.
• 6:30
  Kiet Tran: Like, well, what asset is that?
• 6:32
  Kiet Tran: How do you link back?
• 6:33
  Kiet Tran: Is this tokenized NVIDIA?
• 6:34
  Dante Reminick: Yeah.
• 6:35
  Kiet Tran: Is this a Bitcoin?
• 6:36
  Kiet Tran: Like, what is this?
• 6:36
  Kiet Tran: You have to follow the trail.
• 6:37
  Kiet Tran: You have to follow the trail.
• 6:38
  Kiet Tran: So we provide the linking and mapping of these trails to make everyone's lives a lot easier.
• 6:44
  Dante Reminick: And 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.
• 6:52
  Dante Reminick: Right?
• 6:53
  Dante Reminick: Anyone who's working with digital assets has to have both.
• 6:56
  Dante Reminick: There's no fully on-chain solution, there's no fully off-chain solution.
• 6:59
  Dante Reminick: Tell 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.
• 7:09
  Kiet Tran: I 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.
• 7:23
  Kiet Tran: You think about a bank, well, you gotta connect back to the 30 systems the bank's sitting on.
• 7:27
  Dante Reminick: Yeah.
• 7:28
  Kiet Tran: Right.
• 7:28
  Kiet Tran: And so it's really about building that connectivity on what it means on-chain, what it means off-chain.
• 7:35
  Kiet Tran: Let's use NVIDIA as an example, right?
• 7:37
  Kiet Tran: Nvidia is a stock.
• 7:39
  Kiet Tran: Well, NVIDIA has a stock taker, it trades on these exchanges, it has an ISIN, it has a QCIP, it has a CETO.
• 7:47
  Kiet Tran: And what we do is we then map that to then all the tokenized versions of NVIDIA, right?
• 7:53
  Kiet Tran: That's on-chain.
• 7:54
  Kiet Tran: We map it to all the prediction markets that are related to NVIDIA.
• 7:58
  Kiet Tran: We map all the perpetual futures that are in NVIDIA to then give you a 360 view.
• 8:02
  Kiet Tran: So when you're doing the reconciliation, you now have an apples to apples linkage.
• 8:07
  Kiet Tran: But then there's more to that.
• 8:10
  Kiet Tran: And 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.
• 8:21
  Kiet Tran: And so I do think it's the decision of how we build our data model where we would have an identifier for an asset.
• 8:30
  Kiet Tran: Let's look at Bitcoin, we have a global identifier.
• 8:33
  Kiet Tran: But Bitcoin on Ethereum, we also have an identifier.
• 8:37
  Kiet Tran: So we have an identifier at the asset location level.
• 8:39
  Kiet Tran: So then that gives us this deep linkage back to all the breadthcrumbs.
• 8:44
  Kiet Tran: And so anyone that wants to reconcile on and off chain, they can use all these breadthcrumbs to reconcile.
• 8:49
  Kiet Tran: And that's going to be important, right?
• 8:51
  Kiet Tran: Because look, your accountant book record system, your investment booker record system, your P it's not going away.
• 8:57
  Kiet Tran: You're not changing that overnight.
• 8:58
  Dante Reminick: Yeah.
• 8:58
  Dante Reminick: Right?
• 8:59
  Dante Reminick: In fact, it'll probably get more complicated as more assets come on chain, more issuance, more money moving on a blockchain, on blockchains.
• 9:08
  Dante Reminick: I imagine this, there's just compounding complexity to what you're doing.
• 9:12
  Kiet Tran: So the the way I put this is um, and you you're too young, or maybe I'm too old.
• 9:16
  Kiet Tran: You think about like the early internet days, right?
• 9:19
  Kiet Tran: In the early internet days, you know, people have a store and then they sell online.
• 9:24
  Kiet Tran: But 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.
• 9:32
  Kiet Tran: So in today you have your C5, your D5, your TRAF Fi, and they don't reconcile, you don't have a ledger, right?
• 9:40
  Kiet Tran: So that needs to be reconciled.
• 9:42
  Kiet Tran: And that's really a big part of where Lukkas sees our value in the future.
• 9:46
  Dante Reminick: So let's talk about this.
• 9:47
  Dante Reminick: And honestly, there is probably a more tactful way to ask you this question, but who cares?
• 9:54
  Dante Reminick: Right?
• 9:54
  Dante Reminick: Like when it comes to digital assets and data, what are the negative externalities of not working with someone like Lukka?
• 10:03
  Dante Reminick: Like 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?
• 10:16
  Kiet Tran: I mean, you don't understand your risk profile, you don't understand your positions, how are you reporting back to your regulators, right?
• 10:22
  Kiet Tran: And 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?
• 10:32
  Kiet Tran: Whether it's Cough, 1098, Mika, there's all these regulations you need to align back to.
• 10:40
  Kiet Tran: But also just a smart way of running your own business.
• 10:43
  Kiet Tran: Yes.
• 10:44
  Kiet Tran: Like why would you run a business and not be able to reconcile all your inventories?
• 10:48
  Kiet Tran: Absolutely.
• 10:48
  Kiet Tran: Right.
• 10:49
  Kiet Tran: And so to me, any institutions, and look, this this is really the premise of Lukka's founding, right?
• 10:56
  Kiet Tran: Yeah.
• 10:56
  Kiet Tran: Um, Lukka was originally known as a Bitcoin tax calculator.
• 11:01
  Kiet Tran: We found in 2014.
• 11:02
  Dante Reminick: Interesting.
• 11:03
  Kiet Tran: And then we realized that institutions will step into this space.
• 11:10
  Dante Reminick: Right.
• 11:11
  Kiet Tran: And that's how my focus is really more around crypto, right?
• 11:13
  Kiet Tran: And 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.
• 11:25
  Kiet Tran: You need a reference data layer, you need a corporate actions layer, you need a pricing evaluation layer that's actually RFS Gap compliant.
• 11:34
  Kiet Tran: That's key.
• 11:34
  Kiet Tran: So 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.
• 11:41
  Kiet Tran: Because we're still the only RFS Gap compliant valuation service out there.
• 11:45
  Kiet Tran: That's amazing.
• 11:46
  Kiet Tran: And then how do you build your ledger system on tracking your investment book or record, your account book record?
• 11:52
  Kiet Tran: So we built a full stack with the view that institutions will come in.
• 11:57
  Kiet Tran: And 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.
• 12:07
  Kiet Tran: We think the future rail is digital asset.
• 12:10
  Dante Reminick: And and so Can you tell me more about that?
• 12:14
  Dante Reminick: Why you say the future rail is digital assets themselves?
• 12:18
  Kiet Tran: I 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?
• 12:31
  Kiet Tran: But let's not confuse that as an asset class.
• 12:34
  Kiet Tran: It'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.
• 12:45
  Kiet Tran: You know, as my point is, you know, market's gonna be programmable.
• 12:50
  Kiet Tran: But not every asset class remove the same speed of direction.
• 12:53
  Kiet Tran: But it's quite timely that we're at stablecoin today.
• 12:56
  Kiet Tran: I 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.
• 13:07
  Kiet Tran: You 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.
• 13:14
  Kiet Tran: So what you gotta tokenize that, right?
• 13:16
  Kiet Tran: So I think these drivers are really showcasing the value of digital asset as a rail.
• 13:22
  Dante Reminick: I 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?
• 13:31
  Dante Reminick: You might have an RWA issuer over here, an exchange over there, a different RWA issuer over on the other end.
• 13:38
  Dante Reminick: And the way to connect all of these disparate systems is with stablecoins.
• 13:42
  Dante Reminick: So I'm a I'm a really, really big fan of that mental model.
• 13:45
  Dante Reminick: We've talked a lot about using data retroactively for reconciliation.
• 13:51
  Dante Reminick: Are 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?
• 14:03
  Kiet Tran: It varies.
• 14:03
  Kiet Tran: Look, so we we also power a lot of uh hedge funds and opdesks that it's also not widely known.
• 14:10
  Kiet Tran: I think part of the challenge is we do great work behind the scenes.
• 14:13
  Kiet Tran: We don't go around bragging because that's not what we do best at, but maybe we need to do a better job bragging.
• 14:18
  Kiet Tran: Um a lot of opdesks do use us, right?
• 14:22
  Kiet Tran: And because we have a diverse type of data set that allows them to triangulate.
• 14:27
  Kiet Tran: Imagine 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.
• 14:36
  Dante Reminick: Interesting.
• 14:36
  Dante Reminick: I imagine that having all this data is not only a performance advantage, but there's also a risk and regulatory advantage.
• 14:43
  Dante Reminick: We'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.
• 15:02
  Dante Reminick: How 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?
• 15:13
  Kiet Tran: Yeah, I think a big part of that is you know, one of the things our team has harnessed over the last year.
• 15:20
  Kiet Tran: So, since taking over Lukka, you know, my view is if you're not an AI company, you're not a company.
• 15:25
  Kiet Tran: And so we've invested heavily in our AI infrastructure and really give us that flexibility to operate.
• 15:32
  Kiet Tran: And so behind the scenes and what runs everything is is a platform called Lukka Intelligence.
• 15:38
  Kiet Tran: So think of it as you know, Claude Cowork or OpenAI Codex, but for capital markets workflow.
• 15:46
  Kiet Tran: And our team runs on it.
• 15:47
  Kiet Tran: You know, we have our Okidomo agent that goes and really uh spin up nodes.
• 15:53
  Kiet Tran: Uh we have a recon agent.
• 15:55
  Kiet Tran: And so a lot of these tech advancements has allowed us to really accelerate what we do.
• 16:02
  Kiet Tran: And if you think about it's not just about the AI, it's about the data power in the AI.
• 16:09
  Kiet Tran: So because we send in so much data, it gives us that tremendous advantage.
• 16:13
  Dante Reminick: Can we go down this agent rabbit hole for a little bit?
• 16:16
  Dante Reminick: I want to get a better understanding of how you guys are using agents to collect, decipher all this data.
• 16:22
  Dante Reminick: But also on the other side, right?
• 16:24
  Dante Reminick: Are your are your clients using agents?
• 16:27
  Dante Reminick: Are those agents being informed by the data that that you're collecting?
• 16:31
  Dante Reminick: Walk me through all of it.
• 16:33
  Kiet Tran: Well, what's interesting is we we haven't exposed this to our clients yet.
• 16:36
  Kiet Tran: Oh.
• 16:36
  Kiet Tran: But uh but we've demoed them and they want it.
• 16:39
  Kiet Tran: Of course.
• 16:39
  Kiet Tran: Look, for us, it's really about how do you harness deterministic workflow and probabilistic workflow?
• 16:50
  Kiet Tran: The LM itself is a probabilistic workflow, right?
• 16:53
  Kiet Tran: Give me the next word, give me the next context, right?
• 16:56
  Kiet Tran: But 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.
• 17:02
  Kiet Tran: Right?
• 17:03
  Kiet Tran: It needs to be deterministic.
• 17:05
  Kiet Tran: And for an AI workflow to be functional, you need what I DMS the ACES.
• 17:10
  Kiet Tran: What does that mean?
• 17:11
  Kiet Tran: It needs to be accurate, it needs to be consistent, it needs to be explainable, and it needs to be secure.
• 17:18
  Kiet Tran: And our view is there's no better way to prove it than to run this ourselves with the workflow we run on.
• 17:26
  Kiet Tran: And we're now at a stage where we're so confident we're in the process of rolling this out to our client base.
• 17:32
  Kiet Tran: Amazing.
• 17:33
  Kiet Tran: And that's the that's the power really about leveraging and harnessing the technology with the deep insights the team bring.
• 17:42
  Kiet Tran: And 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.
• 17:50
  Kiet Tran: And I do think the next phase of theta, it's about context on how to do something.
• 17:57
  Kiet Tran: Right?
• 17:58
  Dante Reminick: Do you see your job as my job is to get the best context for my clients?
• 18:02
  Dante Reminick: That's exactly it.
• 18:03
  Dante Reminick: I love that.
• 18:04
  Dante Reminick: What context engineers?
• 18:06
  Dante Reminick: That's what we are.
• 18:07
  Dante Reminick: So it's a really interesting way of looking at what what Lukka does.
• 18:11
  Dante Reminick: Does it stop at context?
• 18:14
  Dante Reminick: Or do you guys take that context and and turn that into insights?
• 18:20
  Dante Reminick: Or do you just give your clients the tools to do that themselves?
• 18:23
  Dante Reminick: It's it's both.
• 18:25
  Kiet Tran: Look, I I I I think the the future is going to be headless in a way, right?
• 18:29
  Kiet Tran: So all solutions, we have all the MCPs.
• 18:32
  Kiet Tran: MCPs is available on anthropic marketplace.
• 18:35
  Kiet Tran: Yep.
• 18:35
  Kiet Tran: The Lukka MCPs are?
• 18:37
  Kiet Tran: Yeah.
• 18:37
  Kiet Tran: Yeah.
• 18:37
  Kiet Tran: Amazing.
• 18:38
  Kiet Tran: Um again, we need to do a better job marketing that, but we do have that, right?
• 18:41
  Kiet Tran: Um But we've also harnessed our own LM and run our own stack internally.
• 18:47
  Kiet Tran: And one of the things we realize is that the more we run our workflow on, the more we're giving it context, right?
• 18:58
  Kiet Tran: And so we've been hosting our own open weight model, and we've been building what I call the lucka brain.
• 19:05
  Kiet Tran: And the more we inject context into the brain, what it does is really put guardrails to make sure it doesn't go heywhy, right?
• 19:12
  Kiet Tran: And to make sure that the output is deterministic, even though the workflow combines deterministic tooling with probabilistic solutions in the mix.
• 19:25
  Dante Reminick: I imagine, though, that the complexity of this context is something that you have seen grown tremendously.
• 19:32
  Dante Reminick: Again, always more chains, always more assets on chain, always more issuers coming and issuing 17 versions of SpaceX stock.
• 19:42
  Dante Reminick: How has that challenged your team to build out these contextual models differently as just the snowball of complexity?
• 19:50
  Kiet Tran: Well, well, to add to that, right?
• 19:52
  Kiet Tran: So it's funny, one of my good friends, you know, they launched a stablecoin uh last year.
• 19:56
  Kiet Tran: It's like the same day, 10 fixed stable coins came out.
• 19:58
  Kiet Tran: Of course.
• 19:58
  Kiet Tran: Trying to pretend to be us, right?
• 20:00
  Kiet Tran: Of course.
• 20:00
  Kiet Tran: So that's the other level of complexity you need to solve.
• 20:03
  Kiet Tran: I 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.
• 20:11
  Kiet Tran: So 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.
• 20:24
  Dante Reminick: Right?
• 20:25
  Kiet Tran: So 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.
• 20:40
  Kiet Tran: And so for us, it's really about embracing this new tooling and going all in on it.
• 20:47
  Dante Reminick: I like that.
• 20:47
  Dante Reminick: So 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.
• 20:59
  Dante Reminick: But on the back end, you guys are entirely focused on how to optimize with agents and everything like that.
• 21:03
  Dante Reminick: Exactly.
• 21:04
  Dante Reminick: Do you see your clients being as aggressive on the AI front and on the agent front as you guys are?
• 21:12
  Kiet Tran: It I think it varies on the types of accounts.
• 21:16
  Kiet Tran: Look, I I think everyone went from token maxing to now value maxing.
• 21:21
  Kiet Tran: As it should be.
• 21:22
  Kiet Tran: As it should be.
• 21:22
  Kiet Tran: Yeah.
• 21:23
  Kiet Tran: Look, the issue is this, why would you give your data, give your context to frontier models and pay them at the same time?
• 21:31
  Kiet Tran: There's nothing worse than the Toys Rust moment, right?
• 21:34
  Kiet Tran: When Toys of Rust taught Amazon how to be in a toy business, and Amazon, well, thank you very much.
• 21:39
  Kiet Tran: We're now in the toy business.
• 21:40
  Kiet Tran: Yeah.
• 21:41
  Kiet Tran: And so the the next phase is really around AI sovereignty.
• 21:47
  Kiet Tran: But 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.
• 22:02
  Kiet Tran: And so every company's going through a different journey.
• 22:05
  Kiet Tran: I've seen some firms that shut off all AI access because they freaked out.
• 22:09
  Kiet Tran: To other firms say, you know what?
• 22:11
  Kiet Tran: Let's play with it, let's figure out.
• 22:15
  Kiet Tran: And so there's no one size fit all.
• 22:19
  Kiet Tran: But the reality is in today's world with all these models, it's like keeping up with the Joneses.
• 22:26
  Dante Reminick: Yeah.
• 22:27
  Kiet Tran: So Astra just came out, right?
• 22:28
  Kiet Tran: Astra, the open I version 6, whatever the case is.
• 22:32
  Kiet Tran: Um, you know, you have a new version of an LR model everywhere with all these open models.
• 22:38
  Kiet Tran: So how do you know which one to use?
• 22:40
  Kiet Tran: Like it's intimidating, it's confusing, which is similar than all this blockchain, right?
• 22:45
  Kiet Tran: All these different chains, all these different access.
• 22:47
  Kiet Tran: There's two incredibly complex systems that are coming together.
• 22:49
  Kiet Tran: That's exactly it.
• 22:50
  Kiet Tran: So our view is we just help harness this on behalf of our clients.
• 22:56
  Kiet Tran: So they don't need to worry about which arm to use, which system to harness.
• 22:59
  Kiet Tran: Look, put it this way: if I need to know who's the first president of the United States, I don't need fable.
• 23:07
  Kiet Tran: The dumbest model will, in theory, know the answer.
• 23:10
  Kiet Tran: Yes.
• 23:10
  Kiet Tran: So how do you harness that orchestration across workflow?
• 23:14
  Kiet Tran: And 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.
• 23:24
  Kiet Tran: And that's really been the advantage, is you know, everyone is an AI expert across Lukka, right, from that perspective.
• 23:33
  Dante Reminick: I love that.
• 23:33
  Dante Reminick: And again, backstage, you and I were talking about how it's still the very, very early days of Lukka.
• 23:39
  Dante Reminick: You've gone out, you've built this incredible system that marries the complexity of digital assets and the complexity of AI.
• 23:46
  Dante Reminick: You're actively delivering value to some of the world's largest financial institutions, but it's still the early days.
• 23:51
  Dante Reminick: What's next?
• 23:54
  Kiet Tran: Look, I I think financial institutions are getting the joke.
• 23:59
  Kiet Tran: You think about this whole stablecoin today, how many banks you see here, right?
• 24:04
  Kiet Tran: And so if you're a financial institution and you don't treat digital asset or stablecoin seriously, then you're sleeping under a rock.
• 24:14
  Kiet Tran: And I think that leads to a lot of opportunities for Luke and what we built, right?
• 24:19
  Kiet Tran: We've been building to waiting for this moment, and the moment is here.
• 24:23
  Kiet Tran: So it's quite exciting for us.
• 24:24
  Kiet Tran: You know, the team is super busy.
• 24:26
  Kiet Tran: Um, and I I do think this tailwind continue to be an opportunity for us.
• 24:31
  Dante Reminick: Yeah, 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.
• 24:39
  Dante Reminick: But 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.
• 24:54
  Dante Reminick: Like you cannot unequivocally run any type of digital asset program without having the data to back that up.
• 25:02
  Dante Reminick: Have 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?
• 25:12
  Kiet Tran: So it's not just about data, but I would say data infrastructure.
• 25:16
  Kiet Tran: Okay.
• 25:16
  Kiet Tran: Right?
• 25:17
  Kiet Tran: Because you need to map back to all the on-chain data, and there's a massive amount of data.
• 25:23
  Kiet Tran: Right?
• 25:24
  Kiet Tran: It's Lukka sitting on 10 plus pay to bytes worth of data.
• 25:26
  Kiet Tran: So it's a massive data set.
• 25:29
  Kiet Tran: But it's also a massive exercise of mapping all the breadcrumbs.
• 25:36
  Kiet Tran: And 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.
• 25:44
  Kiet Tran: And so think of us as not just data, but data infrastructure.
• 25:49
  Dante Reminick: Yeah.
• 25:49
  Kiet Tran: And 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.
• 26:00
  Kiet Tran: That's going to be important.
• 26:01
  Dante Reminick: Yeah.
• 26:02
  Dante Reminick: I mean, I talk about we we talk about the stablecoin stack, and oftentimes that stack is made out of various different infrastructure components.
• 26:09
  Dante Reminick: You have, you know, your wallets over here, you have your ramps over here, you have a custody provider, an issuer, whatever that might be.
• 26:16
  Dante Reminick: Do 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.
• 26:25
  Dante Reminick: You know, now that I need to do all this reporting, I need to go after the data, the right data.
• 26:30
  Kiet Tran: Aaron Powell Yeah.
• 26:30
  Kiet Tran: In 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.
• 26:35
  Kiet Tran: Yeah.
• 26:35
  Kiet Tran: Right.
• 26:35
  Kiet Tran: Things end up being super manual.
• 26:38
  Kiet Tran: Yes.
• 26:38
  Kiet Tran: And 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?
• 26:46
  Kiet Tran: On this reconciliation nightmare you gotta run.
• 26:49
  Dante Reminick: Aaron 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.
• 27:05
  Dante Reminick: Trevor Burrus, Jr.
• 27:06
  Dante Reminick: Funny, I was talking about someone earlier today.
• 27:08
  Dante Reminick: It's ridiculous.
• 27:08
  Dante Reminick: But it's over the place.
• 27:09
  Dante Reminick: But it's true.
• 27:10
  Kiet Tran: It's true.
• 27:10
  Kiet Tran: It's true.
• 27:11
  Dante Reminick: You 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.
• 27:20
  Dante Reminick: That's right, that's right.
• 27:21
  Dante Reminick: Signal WhatsApp, telegram.
• 27:24
  Dante Reminick: Trevor 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.
• 27:38
  Dante Reminick: So 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.
• 27:46
  Dante Reminick: Exactly.
• 27:47
  Dante Reminick: I love it.
• 27:48
  Dante Reminick: So 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.
• 27:58
  Dante Reminick: How should they get a hold of your team if they want to learn more?
• 28:02
  Dante Reminick: What do they do?
• 28:03
  Dante Reminick: What's the next step for everyone here?
• 28:04
  Kiet Tran: Yeah, look, look at that tech.
• 28:06
  Kiet Tran: We also have a LinkedIn page.
• 28:07
  Kiet Tran: Uh definitely hit up our team.
• 28:09
  Kiet Tran: I 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.
• 28:17
  Dante Reminick: I can confirm that.
• 28:18
  Dante Reminick: Their team is great.
• 28:20
  Dante Reminick: Uh and I also, the one thing that I really like about your team is that you recognize that every data problem is different.
• 28:24
  Dante Reminick: And so you customize a lot of the work to the individual clients.
• 28:28
  Dante Reminick: And I think that that's something that's really, really special with space.
• 28:30
  Dante Reminick: But Kit, I really appreciate you coming up here.
• 28:32
  Dante Reminick: Like I said, you and I could do this for three more hours.
• 28:35
  Dante Reminick: So 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.
• 28:42
  Dante Reminick: But that's for another time.
• 28:44
  Dante Reminick: I appreciate you coming up, and uh, we'll see you soon.
• 28:46
  Dante Reminick: Thank you for having me.
• 28:47
  Dante Reminick: Have a good one.