Shael Khan (2:47)

I'm Shael Khan. I lead the early stage venture strategy at Energy Impact Partners. Welcome. All right, so here's a cycle that I have seen play out many, many times. Developer X of project Y wants to go build a big new project and somewhere in the development process they engage in epc. EPC being an engineering procurement, construction firm. There are many of them, many of them are very, very large and they're kind of ubiquitous. If you're going to build a big capital project, they engage the EPC and then there's like a fairly painful process from there on where it's slower than they want it, they have to go through multiple cycles of iteration. There's value engineering, the cost comes in higher than they expect, and then at the end of the day, there are a bunch of change orders anyway and there are cost overruns, there are time overruns. It's not necessarily the fault of the epc. Right. Lots of things can happen in the world, but the process of actually getting big projects constructed is notoriously hard. And some folks have been wondering whether there is a way to leverage modern technology, AI included, to do it better. Certainly that is the opinion of Alex Modan, who is our guest today. Alex is the CEO and co founder of Unlimited Industries, which is a startup that recently unstealthed to basically be a modern epc. They're trying to start from scratch to build a company that will do engineering procurement and construction with new technology, with a different business model to try to get projects built faster, more on budget, potentially cheaper. It's an interesting question and it applies to everything from data centers to power generation projects, battery storage projects, new chemical plants, anything that we might build that's a big capital project. So it's relevant to basically everything else that we talk about here. Anyway, here's Alex. Alex, welcome.

Host/Announcer (4:36)

Hello.

Alex Modan (4:36)

Thanks for having me.

Shael Khan (4:37)

Thanks for being here. Let's talk about epc, Engineering, procurement, construction. You founded a company based on the premise that it could be done better. So I want to start with what's, what's wrong with it today, as you've observed, EPCs and how they work, fundamentally, what is the problem that you see?

Alex Modan (4:56)

Yeah, well, it might be first contextualizing, like the what is EPC and where does it play in the value chain? So to start this, let's just imagine we're going to build.

Alex Modan (5:09)

I don't know, let's just say a data center project. So if we want to go build a data center project as an owner of a project or a developer of a project, the first thing that we do is we kind of find the land and we contract that and we start to figure out what permits we need, we figure out what power we need to buy. And then you know, you typically go find an off taker or some sort of tenant for that, for that actual data center project, or again, whatever the product is that comes out of the facility. And the last like big contract that you're trying to do is go find the third party that's going to design and build the thing. EPC engineering procurement construction is basically the vertically integrated or all three of the kind of design, manage the supply chain, actually manage the build of the project. All three of those in one contractor. And for all intents and purposes, they are the people who design and build the thing, that EPC piece. And so I think when I got into it, I was actually really excited the first time we went to go work with an epc, thinking that there's going to be all these different kind of disciplines and institutional knowledge under one shingle. I think the biggest thing that's challenged with the industry today is that the incentives between the developer, the person who actually wants to build the thing better, faster, cheaper, or some sort of metric like that, versus the third party.

Alex Modan (6:25)

The incentives are so fundamentally misaligned because of how these contracts get produced. And so you either have the vast majority of these contracts have some element of cost plus where.

Alex Modan (6:38)

We'Ll give some sort of guidance about how much the project's going to cost. But as a third party contractor, your incentive is really, we only make money when the project costs more and takes longer. Or there's sometimes these contracts that run on a fixed firm basis where that third party will actually say, hey, we'll build it for this much. But they define the contract so tightly that inevitably what happens is when you learn something through the design process or when things change, which inevitably they always do, you get issued these like massive change orders. And that's at that point, that's where that kind of third party EPC typically makes all their margins. Just because you're, you're, you're already working together and you can't really easily leave. So yeah, high level. What's broken is, is it's the incentive structure, the incentives between that third party or the, the actual developer who wants to build better, faster, cheaper and the third party who's in control of making all the decisions about what gets designed and what actually gets built.

Shael Khan (7:32)

If I'm being charitable to EPCs and you know, and I ask the question of like, why is it cost plus typically or fixed firm, but where change orders are the norm? Um, I would imagine in part it is because there's the one, there's this like time lag, right? Like they're signing the contract on day one, but they're actually procuring the commodity materials six months later, a year later, 18 months later, whatever it might be. Those prices are volatile. They would have to hedge them every single time if they weren't going to do that. Like, and not to mention labor availability, labor costs and all this other stuff. So is it because they just can't wear that kind of a risk, the like time risk, or is your experience that there's a different reason why it ended up being cost plus or fixed firm with all sorts of change orders?

Alex Modan (8:23)

No, it's, I mean, definitely to Steelman, it's because it's ultra complex to build these projects. There is hundreds of people that'll be involved in how the thing gets designed, that manages the entire supply chain to get it built, and then manages all the like boots on the ground of the project that's actually doing the building. So there is tons of complexity. And the reason that these contracts are structured in this.

Alex Modan (8:46)

Inherently flexible way is because it's really hard to know up front how much exactly is the thing going to cost. So yeah, I mean, it certainly has evolved this way because when you think about these projects, and I mean the small version of these are like $100 million. The more normal version of these is many hundreds of millions. And then the bigger ones are certainly in the meaty billions of costs. So because you have all that r risk, the contracts effectively are this big risk mitigation strategy.

Alex Modan (9:20)

And the easy way for the EPC not to take any risk is just to say we're going to get a margin on top of what it costs us to build the thing. But the problem is.

Alex Modan (9:30)

There'S no motivation then to make the thing cost less. If anything, there's a motivation the other way to make it cost more.

Shael Khan (9:35)

Yeah, you mentioned there's a lot of people and a lot of uncertainty. I guess one way I think about it is that there's a spectrum of different types of projects. On one end of the spectrum is a thing that looks the same every time you build it, more or less. I mean, maybe a version of this would be, I don't know, utility scale battery projects or utility scale solar or something like that where like, you know, we've built hundreds of them. They generally look the same wherever you go. You would imagine that on those types of projects it would be pretty well known. Maybe there is some commodity risk, maybe there's some labor risk, but like broadly speaking, the designs are going to be similar and the experience is high. And then on the other end of the spectrum, there's like a first of a kind thing that's never been built before. And they're obviously your error bars on the cost and the time, the labor and all that is going to be highest. And then there's a bunch of stuff in between. I imagine data centers are in between actually, because in some ways they look the same. There's like a powered shell. The shell is a building. But then inside the data center, right, like there's all sorts of innovation. Like is this one liquid cool? Is this one using which Nvidia chips is it using? How is it designed? There's so much innovation in that space that it's changing all the time, which.

Alex Modan (10:48)

Also changes the facility too, right? Like, like it's. These changes trickle out for sure.

Shael Khan (10:53)

Right. So I guess as you think about this, like the incentive structure being misaligned, do you view it as being more misaligned on the, I guess relatively speaking, easier stuff to build because there you should be able to have high level of certainty on what the cost should be a priori. Or is it more misaligned on the, on the esoteric stuff because the error bars are even higher and so the risk aversion of the EPC leads them to like way overpriced, for example.

Alex Modan (11:21)

Yeah, yeah, I mean, definitely, definitely. It's like the contingencies or the egregiousness of this like cost misalignment is certainly true with the more custom the project gets. So the first of a kinds are a great example of that. Or you know, like you even mentioned, data centers that are shifting in their requirements, of course have more and more, more of this baked in. It's basically just correlated to risk. Like how much risk is there in this? Solar has less and less risk as we deploy more and more the exact same way. Same thing with utility storage. But I do think that like where you see. So you definitely get misaligned contracts or misaligned incentives, which, which kind of balloon costs. And that is the, the kind of status quo for how you contract these things anyways.

Alex Modan (12:05)

But the other, other thing that kind of falls into this is how projects broadly are approached. And so if you think about how we build products, like we have a metric for it, right? We say, hey, we're going to make this widget, it's going to come out of A factory, we'll have some sort of cost per widget metric and that allows us to kind of approach these projects with this continuous improvement type approach.

Alex Modan (12:27)

And drive cost down. That's like our learning rate. I think arguably, like that's why solar has fallen so aggressively is because we keep kind of making, or at least I should say the module costs, which is even different than this is maybe a side tangent, but it's like different than the actual installed costs.

Shael Khan (12:41)

Yeah, well, it's actually the problem with solar is that the module costs have fallen much faster than the installed costs have.

Alex Modan (12:46)

Right.

Shael Khan (12:47)

Like we haven't solved it on the construction and all the other commodity materials and stuff.

Alex Modan (12:52)

Yeah. And that's because all progress happens with this highly iterative process and this continuum improvement process that we get out of manufacturing a thing. But when we move into projects world, everything's a snowflake. It's like everything's n of 1. Even a project that we're building, we built lots of refineries. That next refinery that we build is still an N of one project. And because it's approached in that way, you don't really get any sort of benefits of learning through that process. And you know, by definition each project's going to be unique. It's a different piece of land. But.

Alex Modan (13:25)

Yeah, and again, maybe this is a tangent, but that's like another big problem in the industry is everything's done from scratch. So even if you're going to go design a new, you know, a slightly different data center or solar project or something else of that sort.

Alex Modan (13:42)

Every tweak or change that you make effectively reintroduces the entire redesign of the process. And so yes, there's some stuff that gets lifted, but the overall amount of work that happens is not the kind of delta of the change. It is like a significant rehaul of work. And it just keeps us from like learning and iterating to improve how something gets designed. Not just in terms of saving the engineering costs, which is actually a pretty small piece of the cost anyways, but actually like kind of having a better design that improves the overall cost or performance of the facility.

Shael Khan (14:14)

I guess. One thing I wonder is, okay, so let's take epc, right? Like engineering, procurement and construction. Just taking it at the simplest base layer of what the work entails. Let's just say you could dramatically improve because what you're describing is like the learning, I think, I guess maybe is on all three, but predominantly on engineering. Can you design this thing so that it's fast and Easy to design and is definitely going to work up front. My guess is that in most of these big capital projects, the E out of EPC is the smallest slice of the pie in terms of total cost. And the bulk of the cost probably comes from a combination of procurement, the actual physical materials, much of which are going to be steel and cement and aluminum and commodities that, that have prices that vary, and then construction, which is sort of a function. It's an outcropping of how the engineering occurs, but certainly is also just driven by.

Shael Khan (15:13)

Construction process and labor and so on. So as you think about where is there an opportunity to deliver cost reduction and also cost certainty, how much of it is the E versus the P versus the C?

Alex Modan (15:26)

Yeah, totally. Okay, so those are two separate things, right? So let's say cost certainty versus an overall reduction in cost. On the certainty side.

Alex Modan (15:36)

Everything gets really kind of planned out or teased out in the engineering portion, right? And so generally, again, life cycle of these projects are, you know, you start with some conceptual design, you understand maybe plus or minus 50% how much the thing's going to cost. Then for the most part you dig into this like front end engineering design and you will get to totally changes per project. But say you get to like plus or minus 10% of cost and that gives you enough confidence to go to a lender, an actual bank, and say, hey, let's underwrite this project. We think you're going to get the IRR you need and then we move forward. But in the vast majority of projects, when you go to final investment decision and you have plus or minus 10% estimates, you're only maybe 30% of the way through your engineering 70% you still have to go do. And you just, it doesn't make sense to do it up front because it takes a lot of time and it costs a lot of money. And it's a lot easier to finance that with the actual lender's money rather than the development capital. So the certainty that you have going into a project before you actually take the money from the bank to go build it is actually pretty low. There's so much more work to go do and you just don't do it because there's a high marginal cost of the engineering. So one way that you really reduce all the risk, if you will, or all this uncertainty from how the project's going to work is if you could instead just take these projects further through the design process so that by the time you're doing your Earthworks or you're moving some sort of ground, you're actually 100% done. You have your issued for construction package which doesn't happen today. And so there's that big piece on how do you remove uncertainty, how do you remove costs? I mean, yeah, you're totally right. The engineering cost is anywhere from 3 to 10% or 15% of the project costs. So it's not a huge lever in itself. But if you think about the way these projects are designed today, because again, such a high marginal cost to engineering, what you end up doing is you only really design something one pass through. There's no sort of iteration, there's no optimization of design. And that leads you to a spot where you kind of make early decisions, you freeze those design decisions, you kind of do the next stage gate of your design process and you eventually get stuck in these very low local optimums rather than ever understanding what the global optimum of that design process is. So yeah, I mean I can get more into how we approach this problem, but.

Alex Modan (17:55)

There'S huge gains in opportunities to use the E to rapidly reduce the P and the C.

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Shael Khan (20:12)

Okay, let's talk about how to use technology, which is I think what you're alluding to here, right? Like this is an area where my suspicion is generally it's not the first category of AI adoption, or at least it hasn't been historically. Where do you see the biggest opportunity? Like where are the step function improvements that one can achieve by leveraging modern technology, be it AI or something else?

Alex Modan (20:36)

Yeah.

Alex Modan (20:39)

So we have built a lot of technology to help accelerate that pre construction phase. So this is basically the E in a lots of the procurement, management side of things. And we have a software and kind of like an AI native version of this that helps accelerate the chemical design, mechanical, electrical, civil, structural controls. And in doing that, we basically are building a platform that allows us to remove that risk, but at a very, very low marginal cost. So that helps you accelerate through the design process, not just saving time, but exploring a much wider search base and getting to much greater levels of definition before you actually have to freeze designs. And that has a big impact to the previous point. Right. Is just like removing uncertainty, reducing costs through optimization.

Shael Khan (21:28)

Can you go a level deeper on that? What does that actually mean to reduce uncertainty using software? Like what are you actually doing?

Alex Modan (21:36)

Yeah, it's just, you know, if you start a project today at like zero, you know, it's like completely uncertain, right. And as you start specifying or defining the bringing definition to that project, which is the process of engineering it, you start to see more. You, you start to remove risk, right? You say, hey, you know, we can actually size a pump that will solve that, you know, moving the fluid from, from point A to point B. Or actually we can design a tank like this to hold this amount of volume. And once you start providing that level of definition, you remove a lot of the kind of ambiguity. But there's still tons and tons that goes into the thousands of documents that you'll generate to design a plant fully.

Alex Modan (22:20)

So this is what we have built. It is a platform that our engineers use. I think the important distinction here is this is not like a software technology that we sell. It's like we use this as an internal tool ourself. So our engineers have this kind of AI platform that has all of their data in one place, all the kind of requirements about the project, all of the potential vendors that could be used, and they use it to basically accelerate that design process really significantly. We haven't redefined how you're engineering these projects. We've kind of significantly augmented the people that are doing that work so that they're able to just with the same amount of time and capital, they're able to define way more and provide way more kind of engineering definition as well as like time to optimize those designs so you can remove kind of suboptimal design.

Shael Khan (23:10)

Can you articulate a little bit like, what is distinct about this from the. You know, that EPCs have been using engineering software that is super mature for. For a long time. Maybe that's the problem. But like, what's distinct about what you just described from what you could just get off the shelf to design a project?

Alex Modan (23:28)

Most of the software in this industry really hasn't changed much in the last maybe 20 years. And I again, kind of always come back to the incentive structure. There's no real incentive structure for an EPC to want better software. It's the same reason your law firm doesn't necessarily want AI software to help them accelerate and reduce their billables. So the way these softwares work now is that there's a bunch of kind of distributed software solutions or maybe decentralized solutions. So you'll have a CAD tool that you use to actually do the designs. You'll do almost all of your kind of rough engineering or hand calcs and Excel. You'll use dedicated simulation software for some sort of fluid design or structural analysis or whatever that might be.

Alex Modan (24:08)

And then you use another tool to review those PDFs with a tool to put red lines on them and go through design cycles and then push to drafters and then other tools to manage how do you reach out to your vendors? And anyways, there's all these different software solutions that you're using in order to do engineering. And what we built kind of from day one was just a modern version of this software. So we put all those different disparate tools into one underlying platform and we gave modern software to them, which is like, you know, automatically doing version control and collaboration and everything that you would expect out of just like a modern tool. And what that allows us to do is not just kind of have much more streamlined workflows, but it allows us to kind of build AI in as a core primitive to the solution. So now sometimes our engineers will do some sort of work manually within one of our softwares, but often they will dedicate a, or kind of delegate a task to an AI that knows how to use all those tools in our software so that it can do that design task and then surface that back to the engineer who delegated it.

Shael Khan (25:15)

So it's at least in significant part, it's like integration of a bunch of what otherwise are kind of disparate workflows to allow for faster iteration and more automated iteration. Like, you do a change somewhere in one piece of software right now, you'd have to go to another piece of software, like, make the change in that software, see how it changes the other thing, do that over and over again. And so it's like building everything into a single comprehensive suite, basically.

Alex Modan (25:39)

Yeah, totally. There's like one underlying data model. There's not the same piece of data that shows up in 10 different softwares. And that's really helpful, not just again, for streamlining your own workflows, but it's so that an AI can do it and it doesn't have to manage all these different tools and interfaces, that the same information is repeated but out of date or edited by the wrong person who didn't have permission or something of that sort of.

Shael Khan (26:02)

When you say AI in this context, what do you, what do you mean? Like, is it LLM type AI where you're like, I want to be able to, in my single pane of glass, be able to ask, you know, like, what would happen if I changed all the screws in this entire project from X to Y or something like that. Like, is it LLM AI? Is it what is the AI? Yeah, because there's also a version of what you're describing that's like enterprise software for sure, but doesn't necessarily. And like there's a big data component to it, but it's not inherently AI.

Alex Modan (26:33)

Yeah, no, it's like an exact use case, the one that you gave, that you would do. So we'll record all of our meetings, and that meeting you're having with a handful of different disciplines of engineers or people understand the commercial, the agreement and what that'll trigger through that recording is a bunch of tasks for AIs to go do. And you just basically mentioned a trade there, right? It's like what if we had, I don't know, one type of material over another type of material, one type of conveyance over another type of conveyance. For this project or this material, our AI will go explore that different design path. And that's a trade that you would give to an engineer and you'd say, hey, go spend a week, assess the trade off between using belt conveyance or pneumatic conveyance for some sort of material handling problem and then tell me back what do we feel like is the right kind of total cost of ownership trade. And it'll just explore that. And so that's an LLM who's doing a lot of that work. And importantly, you're not just kind of asking a chatgpt or something of that sort to go explore that and produce something which it'll do and honestly it'll do in a pretty impressive way. But the way that we've built it is that it's grounded both inside of our, inside of the data for the project because it has all that in one place and then inside of the tools that we've fed it. So it knows how to use.

Alex Modan (27:43)

How to down select actual vendors, or how to read spec sheets that we fed it, or how to use simulation software that we fed it in order to derive these answers.

Shael Khan (27:54)

You mentioned data centers and I think you guys put that in as one of the categories you're most interested in in, in your announcement when you guys unveiled. Is that because we're building a lot of data centers or is that because there's like something specific to data centers, data center construction and engineering that makes it especially attractive here or is there something else that you would describe as like the perfect prototypical use case for this in the early days is X.

Alex Modan (28:22)

So these projects have, you know, a handful of different, a handful of different reasons of why you would apply this technology in the data center use case Specifically speed is really an important lever for them. And so you can take, you know, instead of the design portion taking, call it six to nine months of your critical path, we can massively collapse that period of time. And that's really, that's really important for, for these data center projects to kind of accelerate how quickly we can actually build them. The same piece though, with the fact that, you know, if you right now budget six to nine months for, for your design portion, almost none of that, you're going to start to figure out, well, how do we optimize that design or do some sort of value engineering to save costs or to design for long lead items or to design for constructability. So really strong value prop in these data center projects.

Alex Modan (29:12)

As we end up kind of increasing the capacity that we have on our team though, it'll make sense to pick up basically many of these types of large industrial projects of which we've already pushed the kind of technology to be able to demonstrate. And, and it'll end up being really applicable across all types of construction.

Shael Khan (29:30)

So if you can deliver more certainty upfront, then that presumably is the thing that unlocks a different kind of business model that hopefully solves the incentive problem. Is that just a fixed price contract with no change orders allowed or what does that look like?

Alex Modan (29:48)

That's exactly it. We literally put no change orders in our contracts. So you wear the contractors to make.

Shael Khan (29:53)

It explicit, like you wear all the risk. Basically if there's a cost overrun, you're going to go negative on the project. And the premise here is that because EPCs notoriously don't have huge margins. Right. Construction firms are like high volume, low margin type businesses. And so I guess the thinking on your side has got to be because we are reducing the cost of everything along the way, we naturally have higher margins which would allow us a little bit of a buffer if, if things do become a little more expensive than we expected. At least we're not like in the red. Do I have that concept right?

Alex Modan (30:29)

Yeah, I mean, we definitely will have a different margin profile than the industry. But it's not that because even when you think about it, the engineering margin, it's like, it's pretty small because the spend of the engineering is actually really small relative to the larger construction scope of the project. The important part of what allows us to absorb that risk without the kind of risk that we go into the red, or at least in a risk adjusted way, is because we've been able to do so much design up front and we've been able to not only.

Alex Modan (30:58)

Kind of like remove all that extra risk by taking the definition instead of, you know, doing that at 30%, we can take that definition all the way through 100%. It's, you just remove all this ambiguity of how much the thing should actually cost. So when you, you know, again, traditionally when someone gives a contract to go build a project because they have such little core definition, they don't, they don't know all the vendors that they're going to buy from. They have, you know, you even mentioned, I think this example earlier of like there's like a tariff risk by the time that you, you know, you fund the project and you Commit to a cost tariff can change in the, you know, six more months you need to finish the design in order to order the parts.

Alex Modan (31:36)

That doesn't exist in our world because we've been able to just very, very quickly remove all this risk before we actually commit to a price that's very unique.

Shael Khan (31:43)

Wait, how does that work? So, so that's a very, it's a good specific example. So I guess what you would do is issue the purchase order for all of the material before you commit to a price to the customer. Like, how do you avoid the terror?

Alex Modan (31:57)

Yeah, exactly. It's timing it all out. So when.

Alex Modan (32:02)

Just to compare this again to how it works today is you'd only when you, when you say, hey, we're the epc, we're going to give you a performance guarantee or some sort of fixed firm price when you go to buy this or fund this project with like a notice to proceed or final investment decision. At that point you just, you literally don't even know all your bulks. Like so you're all your commodity equipment, equipment, the steel that you need, the wire that you need, et cetera. We will know all that at this point in time because we're not 30% definition, we're 100% engineering definition. And because we have this entire equipment list at this point in time, we know either how to say, hey, let's purchase everything at the same day that the project gets funded. Let's go either purchase everything, or let's design hedges from a cost perspective so that we're not exposed to some sort of volatility or risk.

Shael Khan (32:48)

That's complex. Right. I'm thinking of these big construction projects, right. And you're either on, on the, on the day that you sign the contract, you're either buying all of the steel just as a random specific example, or you're hedging steel prices at the project by project level to make sure that you don't overpay for steel. That's kind of what you need to do.

Alex Modan (33:09)

Yeah, that's what allows you to, to truly like having kind of a, a very different risk assessment for how these projects get built. And that what gives you a ability to do a fixed firm and actually mean it. Most of these fixed firms aren't really like industry themselves. I mean, we've seen time and time again where it's like a fixed firm doesn't really mean a fixed firm because there's inevitably some way that in the thousand page contract that you assigned with your epc, you went out of scope and invalidated that price. Hence the kind of change order trickery.

Shael Khan (33:39)

I guess the other thing that I wonder how you manage is, is subcontractors. Right. Like it's another area where change orders come from, not just the general contractor or the EPC having to make a change order, but also because some subcontractor made a change order. So do you have to flow this all? First of all, are you going to use subcontractors? You're just going to do everything in house and have a ton of people on staff. And if you are going to use subcontractors, do you have to then flow this change in a structure down through all of them where they can't issue any change orders to you either there?

Alex Modan (34:11)

Yeah. Certainly long term we will do everything in house. We will vertically integrate as much as possible because that's where you can fix the incentives all the way through. Yes. For these initial projects as we take we are working friendly with like the local GC or even the trades, even the actual folks that we will subcontract a lot of this work out to. For that it is making sure that we prior to entering into a contract you have the kind of the same thing where often those contracts are not as.

Alex Modan (34:42)

The level of definition that you have when you're asking someone to actually give you a fixed price on what a scope of work is, is very hard. We don't have that same problem because we take things way deeper through definition and we have a much better understanding of what should this actually cost to go build.

Alex Modan (35:00)

There's a handful of different ways that we kind of approach working with the actual subcontractors as we do this to hit our performance goals. But it is this kind of like a.

Alex Modan (35:12)

Continuing loop of how do you remove more and more risk through design?

Shael Khan (35:16)

All right, so wrap it up. You don't have to give me exact numbers, but like when. When should we expect to see the first cod? When should we expect to see the first project constructed by you guys?

Alex Modan (35:28)

I love it. Yeah, we'll hopefully see next year. Year. So hopefully by end of next year.

Host/Announcer (35:33)

Yeah.

Shael Khan (35:33)

Fast is the rule. Alex, thank you so much for the time. Really appreciate it.

Alex Modan (35:37)

I appreciate it. Thanks Joe.

Shael Khan (35:40)

Alex Modon is the CEO and co founder of Unlimited Industries. This show is a production of Latitude Media. You can head over to latitudemedia.com for links to today's topics. Latitude is supported by Prelude Ventures. This episode was produced by Daniel Waldorf Mixing and theme song by Sean Marquand. Stephen Lacy is our executive editor. I'm sheil Khan. And this is Catalyst.