speaker-0: Hello and welcome to Freight Find Podcast, your source for all things freight transportation. I'm Chris Kapilis, Chief Scientist at DAT Freight and Analytics. And today I'm joined by Peter Schwartz, CEO and co-founder of Altana. And today we're going to dive into the challenges of global commerce. Nine years ago, Peter Schwartz and his co-founders at Altana saw globalization fragmenting and trade friction between countries increasing. They built an AI platform to help businesses survive and thrive in this new reality. In this episode, we explore how Sultan is solving some of the most complex problems facing supply chain professionals today. We'll discuss how a single platform can handle compliance from tariffs and free trade agreements to product passports and rules of origin. We examine how understanding your entire multi-tiered supply chain, not just your director tier one suppliers, unlocks massive efficiency gains and can build genuine resilience. We also discuss how Sultan helped companies navigate the onslaught of tariffs that occurred in 2025 and are still occurring. We learn how Altanite quickly helped them adapt and why the ability to automatically calculate tariffs across geographies and qualify for better rates has become mission critical. And we explore surprising insights from some real-world disruptions. When travel through the Strait of Hermous was restricted, the impact wasn't just on energy prices due to the restriction of oil. We discovered the hidden multiplier effect that cascade through supply chains, affecting everything from plastics to medical supplies to fertilizer. Whether you're shipping goods, managing supply chains, or navigating an increasingly complex global trade environment, this conversation will help you better think about how resilience, compliance, and efficiency can improve your supply chains. Now, following my conversation with Peter, we'll present the truckload market update. So, let's get started. Peter, welcome to the Freight Find Podcast.

speaker-1: Chris, it's great to be here. Thanks for having me.

speaker-0: Yeah. So thanks so much for agreeing to be on this. We met at an MIT event, one of the roundtables we had talking about resilience and that. was great hearing from you. That's where we met. I've always heard of Altana. But can you give me some background, help the listeners here? As you know, the audience is generally transportation executives, mainly from shippers, but carriers as well, but mainly domestic. Can you give a quick overview of what Altana is and what it does?

speaker-1: Absolutely. So Altana is the collaborative AI platform for trusted trade. To make that really concrete, what we're talking about is a system that assists with compliance. So that's like paying the right tariffs, free trade agreement qualification, rules of origin, green lanes, product passports to move goods across borders quickly, expeditiously, and resiliency. So like the ability to understand the multi-tier dependencies in production, bottlenecks, but also transportation. you know, things that could impede the movement of goods. And then of course, more broadly, efficiency. And I think the key insight that I would emphasize is that the same systems can do all of those. And so when we set out to build Altana, we thought to ourselves, we're going to build a system that does as much as possible automatically via AI that unifies all of the needs into one platform. So the same work you do to understand a multi-tier supply chain or a transportation network or you know, to submit for product passport serves all of the other areas of your business. And then you would achieve, you know, your compliance, your resiliency and your efficiency all in one system. And that's why we've got such a broad user base across both, you know, multinational corporates like future electronics, ZF, Boston Scientific, major, I would say the majority of the major logistics companies, you Mirsc, because we're proud to be partners with Mirsc and then a lot of governments as well. Where we're helping both on the regulatory side and then also the economic security side. things like the US.

speaker-0: Yeah, so Peter, prior to this, seems like those are two separate markets to address. One is, you know, resilience. There's a typhoon. How is that affecting my supply chain? You'll hear your bill of materials, your tier end suppliers. The other is products, they're compliant, so therefore they can pass through customs quickly. Was that the vision to bring those together? Because it seems I are. Do you have clients that are one and not the other, or is it both combined?

speaker-1: You know, our vision was that we started the company about eight, nine years ago, and we thought globalization won't last in its current form. The world is going to fragment. And what this fragmentation will look like will be a deep rearrangement of global supply chains and a dramatic increase in both threats to production, you know, just disruption, but also regulation on the multiple tiers of that production. So that might look like, you know, well, let's talk about tariffs. You know, there are tariffs that are specific to the origin of the steel in a given product. Or if you look at like a free trade agreement, know, USMCA already had this, but like, where did the auto body come, where did the engine come from is going to affect the qualification status. And so the same system that that is doing the compliance there that like might satisfy like an EU deforestation regulation in Europe is also satisfying. the resiliency because you had to understand those multiple tiers and now you can analyze that as well. And then it's also doing the efficiency because you're like, ⁓ my gosh, once we understand the multiple tiers of the production or the consumption, now I see there's optimizations to be had. The whole world was very locally optimized because that's all everyone could see. You know, you're just optimizing your relationship with just your direct relationships and there's so much benefit to be had from seeing and acting upon the multiple tiers.

speaker-0: So you started about nine years ago. That's actually quite an insight that you saw greater trade friction coming up at that time. Cause we were still, I think we're over the hangover of global trade forever, but what made you, what was the, was there an aha moment? What made you, Raphael and Evan, your co-founders suddenly say, Hey, this is different. This is going to be changing. Was there a moment or were you guys just out drinking in a pub or something?

speaker-1: think we'd seen it for years. I we'd lived a lot internationally. We'd worked in international businesses for a long time. And it just felt like, you know, without going too deeply into specifics, like the geopolitics of the world and then the realities of the international system were not sustainable. And that this would lead to a rearrangement and and dramatic changes.

speaker-0: Because we did scenario planning back in 2000, gosh, I'm gonna say 2008, that this is one of the scenarios. We called it NAFTA-STEEK, where the world will go into trading blocks. And there's more trade within than between. what you, insight I guess you guys had was that there will be trade between, but at a higher cost, more friction, whether that's tariffs or regulations.

speaker-1: And then to speak positively of it, and this is the, saw two trends, which is one, the fragmentation you speak to, and we thought that was quite likely. And then in fact, it was already happening. And then the second was the rise of modern AI systems that can handle complexity at scale so that you would be able to do, when I talked earlier about the capabilities of Altana, you know, so much of that is from the philosophy of we're going to do as much as possible for you automatically. Cause if you're a major corporation, you might have hundreds of thousands. of relationships that you're managing. you, and a hundred thousands of SKUs, if you're a multi, if you're a logistics company, you might be moving tens of millions, hundreds of millions, even more packages, containers, what have you. And so it's just historically been a very hard problem to deal with. And because of that scale, it's just very hard for humans to deal with. And so it's like, can we do as much as possible that automatically, and you know, we've been using, my whole career has been AI and machine learning. That's changed a lot. And what that means over the two decades I've been in it. But what's really exciting is those capabilities just keep getting stronger and stronger. And then the ability to handle and manage that complexity in a nuanced way at scale gets. And that's the, Kelly, and I'll just say this, that's the countervailing thing. So you see increased friction from the, you know, the world breaking into trading blocks, but now you see the ability to actually much more quickly comply with that regulation and get the efficiency gains and be agile. And so that's the countervailing force, which means, okay, maybe there's more friction, but there's also. more ability to actually move quickly as well.

speaker-0: Do you think that was the barrier to adoption earlier? There just wasn't a technique to automatically do this? Yeah, I don't Cause I know like companies that were doing resilience, you know, notification, they take a bill of material, do it through surveys and try to see what the network is and then monitor real time information. But you're talking about something very different. I want to come to that, but let me step back, back to Altana. If I looked at your, and I did look at your LinkedIn.

speaker-1: I don't think these things were possible.

speaker-0: page, your international studies, you study Chinese, which I'm curious why you went with that engineering political science. don't see, is there looking back, do you see a thread, a common arc that of course you'd be founding Altana to me. looked like you were doing this stuff and all of sudden you're doing this stuff.

speaker-1: I think there is a common thread. So I grew up in DC. I'm from a family of engineers. I was always very interested in technical things, but I also had a lot of international exposure. And so the thread was, I was always very interested in complex systems, whether that was production, transportation, infrastructure, all of those things were really deeply interesting to me. And then sort of the handling of uncertainty. like, probabilities, statistics, all of those things. And then the second thing I had a lot of exposure to was the international system. And so I always thought I would do something international. so, you know, when I talk about international studies or political science, that was also using quantitative methods and studies of like econometrics, that kind of thing. And then I spent study languages as a result. I don't want to claim to you that I had it all seamlessly tied up when I was born, but... I always knew I'd be doing something technical and international. And once I found global trading, global supply chains, was like, oh my gosh, this is such, it's the whole global system. It's so rich. And then like it combines all of my interests. And for me, it's always been so interesting to see like, can I actually like work and operate at a global scale and can my companies. And so like what that means concretely is like, I just, you know, can we provide real value at scale? And the answer has been yes. It's been a pleasure of my life to be like, okay. Yes, we can manage, you we can help manage an entire national economy. Yes, we can help manage a major multi net. We can help a major multinational corporation. I'll be humble, but like, you know, we can have this effect at scale.

speaker-0: And AI, mentioned this before, but AI means different things. was just a Gartner and saw you guys had an awesome booth. but you saw presentations and pretty much AI today means math, right? We use AI it's math, but you know, so when you talk about machine learning and AI, but by that, you mean kind of generative AI that, type of technology, but it seems like it's been a continuum.

speaker-1: I mean the full spectrum. we use whatever's appropriate for the tool and it's far more than just generative AI. We have agentic systems in production to actually assist the user, use the platform. That's in place. We also have a lot of like, you've got generative tools that are not agentic, but then you've also just got classic, more like non-parametric machine learning, parametric stuff. Just what's appropriate for the actual problem being modeled. I don't know how much you want me to get into.

speaker-0: Yeah, I wanna dive a little

speaker-1: We're talking about that, just to say different approaches for different things. Some form of AI is appropriate for some things, it's not appropriate for others. And if you're going to, we're processing billions of transactions, we are working at very large scales across hundreds of millions of companies. Generative AI is not always going to scale to that scale of.

speaker-0: But one of the big challenges here is gathering that information that you talked about. So can you talk about Altana's approach to do this, the mapping? You talked a little bit, can you give a little more detail? Absolutely.

speaker-1: So, you know, we, when we started the company, we were coming out of a previous company, Panjiva, where I was head of data science there. We sold that to S &P Global in 2018. Great outcome, good home for the company. And we, you know, we thought about that, that was commercial data.

speaker-0: Same three companies, three founders?

speaker-1: No, we were not founders of that company. We were leadership. we thought to ourselves, commercial data will not be enough to understand the full global supply chain. You all have commercial data and you want to take it as much as possible. And certainly we do here to understand what's happening. But what you really need is you need to understand a part site specific understanding of the world. By that I mean, it's not enough just to understand corporate relationships. You need to understand the individual facilities, their relationships. And what is the nature of those relationships and how do they relate to the product you're producing? That's what's necessary to actually do. I I talked earlier about like the compliance use case. It's like, okay, I need to understand. I need steel to go into the auto body. And I need to understand that like, where is the steel being made? And that needs to understand the facility level. And, you know, I need to not have a bunch of false positives and blinking red lights. I need to be very specific to what I'm doing for the resiliency. Like I don't want to, you know, if I source from a major corporation and they have a disaster at a factory, It might be completely irrelevant. Right. Because they have so many factories, you know, relevant to my actual needs. And so, you know, that that's very key. And so then that like also that modeling, which we can get to later of like, the, you know, what goes into what at scale, the recursive bill of materials or input output for all physical products has been a deep research agenda of both Altana and you know, over the years, but like, just to speak, speak to that then to achieve that at scale, you need to also have the ability to have. proprietary data and help your user collaborate. And so what we built out was a system that could both benefit from commercial data, but would be deployed out in a federated manner. So it could always respect our clients' data sovereignty, security, and privacy needs and their regulations, things like GDPR, and then allow them to exchange just information without moving sensitive data. And so if they need to share a link or a piece of information, they'd be able to do that. And so when I talk about Altana being a collaborative network and AI being a sort of enabler is like, we're doing as much as possible automatically And then we allow our users to collaborate and exchange just what's needed, what's material. So the distinction between like a survey platform where you're like, you're just trying to send out all these surveys and it's like, you get low compliance rates and it goes out of date immediately and it doesn't scale. It's like, do as much as possible. And then just like, just material, you're just like, okay, I need information on where the steel came from, the labor at this point. Or like where did the semiconductor come from? Cause I'm worried about the resiliency of this production or I want to get this tariff rate and I'm just going to get that piece of information. And so it's not that it's going to be like surveys, you get an email, like everyone collaborates the same platform, you reach out, just get that, or maybe it's already stored and they permission it. And they're like, yep, tack. And they've got that sent over and you're saving a bunch of money on your tariffs or you're more assured of your resiliency and it's all being handled. So long way of saying the augmentation, know, commercial is part of the picture, data is part of the picture, but it's fundamentally that federated system, that ability to collaborate that really allows, that actually makes this feasible.

speaker-0: So I imagine there's an incentive for a supplier or a vendor to be collaborative here because as they, they've got to, I assume they've got to give to get.

speaker-1: Yeah, that's right. It's not even it's it's to. I wouldn't even necessarily frame it that way because it's really like you're in your own private enclave and like it's more like collaborate. If that makes sense. It's not like it's like you're collaborating in a targeted manner with your like with your partner.

speaker-0: We do something on a much smaller scale at DAT. We're trying to collect help benchmarking. It's a standard thing. So we have over 300 shippers provide data, but we just don't provide their data back. You modify it so that it's to your point, you protect their data security, you harmonize it and do all those things. that's, you become the trusted third party for this information. So how were you able to do that from scratch? Cause it seems like getting that flywheel started is very hard. Once it's up and you're accepted, then of course everyone wants to join in. But how did you get the flywheel going?

speaker-1: very much with that commercial data. you we came out of that space where there were, you we were able to purchase very large volumes of that data. And so that meant that even the first participants benefited dramatically from the data. Even from that. And then they were, so there was no, you didn't have the cold star problem that you'd have.

speaker-0: No. What about the issue of changing locations? If I'm a manufacturer, you know, I'm not gonna always manufacture the same product in the same place, right? If I have any kind of resilience, I might have multiple manufacturing plants. How do you track that? Where it changes? Where they have the choice of where they actually produce the goods?

speaker-1: Absolutely. So what we do is for a given product, we produce a value chain and that value chain is an estimate. We take in the private enclave, you take in the bill of materials, the first tier suppliers of that product, and then you build out probabilistically the multiple tiers at the facility level. And when I say probabilistically, those are all confirmed facility to facility links. What's probabilistic is just that recursive estimate of like the bill of materials. So like I'm making a gearbox. Okay, I know I need gears in a box. But I may not, internally, I'm not gonna have the bill of materials for the years. You the supplier does. And if they're not on the platform, then I'm gonna need to like go through and estimate like what are their relevant links for the production of those years. Or rather, I should say not estimate the links, but estimate whether or not those links are relevant. And so, or if there's a missing link that we don't know about. And, but you're like, okay, I need to know where this deal came from. I can't see it. That's fundamentally like the approach there. And then you allow the user to then go through and then like fill in the gaps, collaborate, edit it. But that's really the benefit and the speed.

speaker-0: Got it. And so what's the biggest technical challenge that you have for this? Because having the data seems like then you can do stuff. Is is a challenge collecting the data, validating the data, interpreting the data? Where's the biggest challenge?

speaker-1: It's been a lot of work all around, would say, Chris. It's not a... I want to sugarcoat it. I mean, it's a massive data processing challenge.

speaker-0: mean, if it was easy, everyone would be doing it.

speaker-1: Things of records and like every possible language you're dealing with corporations around the world, you're dealing with, you know, you've got records on hundreds of millions of companies and their relationships, the transportation, the ownership, all of that. And then you need to, on top of that, really triage it down to what's relevant and what's material. Because again, to go back to the previous point, it's not just a question of like, you know, we're not a data company. We're like a, we're a platform for collaboration. And this is all in the service of getting jobs done. and having a triaged workflow on a triage day. Because otherwise, you know, even within your own company, there's a million things happening. It's like, where do you spend your time? Whether you're a CFO, point and minimize tariffs, whether you're like, you know, a supply chain professional trying to like understand where are the bottlenecks and where are the potential issues and the different scenarios, whether you're a compliance professional, you get it. It's just, how do you like go through an order? And so there's also AI systems and analytics to go through and order that, and then really target your collaboration, your outreach. Constructing all of that, mean, some of these questions are fundamental questions of computational economics. Like I've talked earlier about estimating the bill of materials for all physical goods. There's a series of Nobel prizes in the 70s around that subject. We're very proud of the advancements we've made there, which are truly cutting edge and getting increased precision, increased accuracy. And what that really relates to for the user is just less wasted time, less false positives, less red blinking lights, just like concrete action. And then the same thing goes whether it's like assigning the right HS codes. So we have these whole systems. It's not just about estimating the tariffs. It's like at scale, like suppose you were moving like a hundred million shipments worth of low value shipments. You're moving a ton of low value shipments, which used to benefit from de minimis. Now they don't. All of a sudden you're like, oh my God, I need to assign HS codes in all these countries or at least US, EU, all these other places for all these shipments that didn't need them before. I need to actually estimate the value and I need to have the value chain. And maybe they're ever going to be relevant to like. in some cases like UDR, rules of origin, and it's a lot. so fundamentally, the ability to do that automatically and to do that at scale is extremely powerful. And building those systems has been a lot of work and we're very proud of it as well.

speaker-0: But yeah, no, this is great. So, because there's two separate problems. One is how to do it, know, academically and figuring that, then going to scale. And sometimes there are two totally different problems.

speaker-1: 100%. And we invest, we have a large engineering staff very much around that scaling challenge and the scale being able to deliver those insights at scale to serve them up to, we have both the product and then also APIs, which integrate directly with some of our logistics partners. And you have to have very high SLAs on those. It's just, and then just the scaling challenges of processing all of this, everything. no, it's a lot. User interface is all that. Yeah.

speaker-0: So you've been nine years, so a lot has happened in nine years. And so I'm curious for one metric that I find it very hard to get, and I find it very hard to scale to find this, is the average distance traveled for all components for a good. And now I've done the view, I've seen it before and I'm curious if that's something you've done. And if you've seen, if we have less global trade, then you would think the total distance of components travel to make it an item is going down because you have less distant Components is that one two questions one is that something that you even look at or thought about or and two is it? Decreasing is it changing?

speaker-1: So we could measure it. I have not measured it. I mean, we will talk later, I think about like the Strait of Hormuz or these multi-tier impacts on resistance. The same systems that estimate those multi-tier impacts, both at a macro scale at the level of a market or a given product, and then at the micro scale of the individual companies involved also would serve in that estimation of that. We haven't done it. I'm not sure it's decreased because if anything, things are getting more complex, which in some cases means more movement.

speaker-0: Yeah, yeah.

speaker-1: because there's more programs, there's more rules of origin, like there's more work to be done in different locations. I think it's an empirical question. I could see that it's going down, I could see that might be going up, because people are like, okay, if I move this part here and process it in this factory, and just this way, and then I move it to this other factory in this other way, then it's like actually going to generate benefit from a different rate. And so it might actually increase some movement of

speaker-0: So I could see that for like for tariffs to avoid tariffs, not that any company does this, of course, but you move it to different areas. That's interesting. Because I know we talked to some companies or I've talked to some companies who moved things out of China. They want to diversify China plus N or whatever. they moved to Vietnam. But the stuff is now just traveling to Vietnam, the components, and then it's traveling there. So it does make it more circuitous.

speaker-1: Yeah, that if it's illicit trans shipment, is like the non substantive transformation, that's illegal. There's you know, there's like, obviously, that type of behavior occurs. There's also behavior that occurs that's not illegal, which is just like, I'm going to change. the process saying it is substantive transformation, but that doesn't apply more actual movement because you want to do a given process in a given location.

speaker-0: Yeah, I didn't mean for it to be a list. mean, like components are now being shipped and assembly, for example, is done to be. And that's what I, that's what I was meaning. One of the things that I found interesting is the whole idea of the passports, product passports. is something I was not as familiar with until I started looking into some of the stuff that you guys do and the new announcement you have with Maersk. Can you tell us a little bit about the AI powered product passports and what was the idea behind that? What does that do?

speaker-1: Yeah, absolutely. the idea was to, and you see this coming out in various regulatory regimes. You know, you've seen both the US is proud to be actively supporting the deployment of them here, both with CBP, with Merus, with all our other partners. And then, you know, Europe is moving in the same direction. They don't have the same thing will be like around things like UDR, all of that. You see it in a variety of different countries. The digital product passports internally, although in Europe, although they started out. as something around a sort of internal environment and a circular economy are now also there. Those systems require understanding the multiple tiers for the product and really in general, testing different attributes. So in the U S it might be around like labor standards, human rights in Europe. might be around like not, you you deforestation regulation is all about understanding is there any point in a whole or in part an exposure to deforestation? even like multiple tiers back in the US, it's the same thing around human rights. Europe will be expanding that out to cover human rights as well. And so what that implies then, well, know, the same thing, you know, can contain information on tariffs on free trade agreements. It all can be packaged into one, I guess it says it on the label, a passport for the good that has all the relevant attributes. And then the benefit of that is that the goods move through the border much more quickly. And so we see that in the US where basically you're avoiding delays, potential holdups, because they're like, hey, maybe it's non-compliant. It can be denied entry or can be audited later, but like in Europe and the US will often be denied entry. There's been hundreds of billions of dollars of goods that have been denied. And it's like in advance submitting this allows you to attest and show that like a potential link is not actually a problem or that everything's quite in order. It's pre-approved and the stuff just sales to the board.

speaker-0: So it's TSA pre-check for goods.

speaker-1: Clear. Clear for cargo. TSA pre-check for goods.

speaker-0: What's interesting is, so it's checking for certain attributes and we both know there's different types of attributes, right? I can test for certain things or look for visual inspection, but what you're talking about are like credence attributes, things that I can't, if I have the product, I can't tell anything about it for the process, whether there was deforestation for this or another one is sustainability that you haven't mentioned, the sustainable. Do you look at what are the certain attributes that you track for these passports?

speaker-1: Yeah, it's really whatever's required by the regulatory regime in general. And so those are the main things. I was talking earlier about it. Like in the US, it's, you know, might be human rights. In Europe, it might be deforestation. They're also expanding out into also labor standards. It's really what's needed to move it across the border. Of course, our system supports lots of custom fields and lot, you know, whatever's important to a company, can say, I will say whatever, but like we support a large amount of additional things that aren't required by regulators that you might still want. But if you think about what's really key to sail through the border, it's of course complying with the relevant regulation. so- That's really what the focus is. So we see a lot of success that, know, and just, for example, in our work with like the ASF or LL Dean or, know, really across industries, it's just this, you can, ⁓ and to go to your point about AI, it's like you construct as much as possible automatically, you identify material exposure, you go through and show with documentation that it's not a problem, you know, that it's not a problem or you rectify it if it is a problem. It's all attached into that evidentiary submission and you all just package it up and it's just submitted directly to your regulator who can then actually respond to you in some cases in platform and be like, hey, I need a little more info on this and you can clear it in advance. And now you're great. You're just sailing through.

speaker-0: That's great. I imagine a lot of it is the provenance. Where is it coming from? Cause I can give you an interesting example. My wife used to work for a company that does testing at the molecular level. And they had a case where someone was selling honey from a certain place in Australia, claiming it was from something else. And if you didn't have the honey, you know, how do you know the provenance? How do you know it's really from these special bees and they can actually test it at the molecular level and they could do it that way. But the challenge is those things that you're doing. You can't test for you have to have some kind of credibility chain, which is what you're providing. But my question is, go ahead. I'm curious about sustainability. If that's something that you guys track is that seems to be something that would be the carbon footprint or the any emissions generated from a product. Cause you can't test that. If you get a banana, what the carbon footprint is, you need to know how it came in. Yeah.

speaker-1: To return to your earlier point, that's absolutely why we call it a trusted network is because a of this is about only a small subset of the generally regulated attributes or desired information is actually testable in the product. There's some agricultural goods where you can do that. Largely, you just can't. then- there's obviously some cases where it's just like safety. And if it's chemical safety and things like that, yes, again, that can be- Sure. It varies. But when we talk about the trusted network and sort of what the company is set up to do, it really is to allow that creation of credence, that creation of trust. that documentation and that working together. And we really do feel that's one of the things that was really lacking in globalization 1.0 where everything was like, you you just sort of, you buy things, they may have incredibly deleterious effects. And it's just like your supplier, you're intermediated by one supplier and there's really no responsibility. It leads to huge amounts of harm. And so really wanting a system where actually it's understood all the way back to the extraction of raw materials, the whole value chain is understood and acted upon really has huge benefits for the environment.

speaker-0: Yeah.

speaker-1: but also to go back to this point about efficiency, it also makes it more efficient in many cases too, because you actually like, stopped locally optimizing it. Now you understand the whole production system and there's really opportunities to tighten it up. So I'm not like a person that's always like, you can have your cake and eat it too, but I will say our clients have often simultaneously achieved a much more compliant outcomes and saved money on tariffs and actually just like saved hundreds of millions of dollars in operations on a given product line because they're like, oh my gosh, there's all this weird chain of. production happening that we weren't aware of, let's, you know, let's, with transportation, can optimize the transportation when you understand everything. If you don't, you can't. Yeah. So and then go to your point about environment, just to speak to that directly around carbon or just those types of measures. Yeah, we actually do very much support those, you know, we support you default, we support the deforestation analytics, we support a carbon border adjustment mechanism measures like the Europeans are playing the tax around the embodied carbon. And if you don't can't attest to what it actually is.

speaker-0: You shine a light.

speaker-1: then you're stuck with these onerous default rates, which you're getting tariffed upon. you know, you could of course measure other things like water stress and everything there and what that looks like multiple tiers back in the platform. You know, we'll have the emissions profile for a given steel plan or wherever we can have it in advance. We'll have the emissions profile from the transportation, estimated transportation networks. ⁓ And then that will then allow you to go through and be like, this is material and like not to get too specific on it, but like In some regulatory regimes, you have to go get the documentation that it's exactly those emissions at that steel plant or at that fertilizer plant to get those benefits. And this will allow you to identify who do you reach out to get the most information with the least effort.

speaker-0: Yeah. One of the challenges for like a commodity supply chain at some point you might have in formales, you have a smelter or for palm oil. did a lot of work in palm oil in Malaysia and at some point it gets aggregated. And so how do you track that? Or is there only a certain point that you can go in certain supply chains where there is a consolidator of some sort where things get combined and you don't know the ultimate original provenance.

speaker-1: We can often see what goes into the consolidator, but if it's all mixed together and it's 10 % deforestation palm oil, then the answer is 10 % deforestation palm oil. And then the answer is you got to go collaborate with your refiner and say, hey guys, you got to either not put, my batch needs to be different, or you got to stop working with this other company or they've got to fix their practices.

speaker-0: I'm curious. So when you go with a company with this, do you find that first response is people go, ⁓ my God, I didn't know where you're showing them their supply chain and they suddenly realize it? Because sometimes, you know, you're doing your job. You don't realize the whole supply chain. Do find that you're uncovering and shining light on things that they then didn't know operationally?

speaker-1: ⁓ for sure. Generally are, we find that most corporations and nations only know one tier out. can only see that's all they've ever known. then I don't begrudge them that. mean, just the technology to do this at scale hasn't lifted. It's been, you know, sort of you're stuck, you've been stuck before these systems with the choice of either going with incredibly expensive consulting projects that go on forever, or just sort of dealing with what's available in the market. And so it's just been pretty impossible. Now it is possible and it's feasible to do this at scale. in a cost-effective manner and really benefit from it. And so that's really changed the dynamic. And so of course, when we first deploy with a customer, they see a lot of things they haven't seen before. And there's a lot of opportunity and often, there may be things to address, but we go through it in triage.

speaker-0: But you raise a really good point with the consultancies. You used to be able to do this, but what they were lacking is the scalability, right? Because you don't want to, you know, hire a huge thing for each product. You do it as a one-off. That's interesting. Let me switch topics if that's okay.

speaker-1: I think that the important reason to do it as well though is that like, you know, sort of pretending that there are, you know, saying I don't want to map it because I don't want to see the risks is actually quite problematic because now the regulations and the regulator is really assessing for those risks. And so what in the past, you know, like maybe there wasn't a really enforcement of a reasonable standard of care there now is at scale. And so that's also another thing that's really changed.

speaker-0: Is that that's very recent because sometimes ignorance was bliss, right? I didn't know. I didn't know we're deforesting. Is that by geography? Is that mainly Europe versus different areas? then the EU tends to be much more regulatory heavy and we're more market focused here in the US.

speaker-1: Yeah, no, it's changed dramatically over the US is the US actually was the first mover here and you really yeah around you know, I was talking earlier about sort of like human rights and then actually movement around the tariffs as well, which are really pretty strong incentives. That's where station regulation coming to effect this December and all that. So it's like, if anything, it's been faster here in the US, really other countries.

speaker-0: I wanted to go to. That's interesting. You brought up tariffs. So how happy were you in 2025 when all of a sudden tariffs got released? And I looked at the numbers, the first half of 2025, new tariffs were released every nine days, either changes or new ones. So I assume that was good for business.

speaker-1: describe us as happy. I don't take pleasure in my clients having issues that need to be solved, of course, by business. your business is to help with those things. And so we very quickly released systems there, by which I mean the ability to calculate the tariffs at scale across multiple geographies, all of the geographies, free trade agreements, the ability to collaborate and get the information there to qualify for those different tariff rates.

speaker-0: You could solve them.

speaker-1: which can often be 50 or 100 % of the value of the good in some cases, and then really like be able to act upon it. And so we've continued to really develop that very strong suite there. And then the same system that was doing, you know, all those rules of origin stuff that I talked about earlier, all of a sudden is also doing the tariff.

speaker-0: And when you started nine years ago, nine years ago, were tariffs in mind as being part of it or did this something that was more not a happy accident, but ⁓ wow, we didn't focus on that. We That wasn't the initial. But yes, it can be used that way. Was it more resilience first and then tariffs came in? Or were you thinking of them both as similar?

speaker-1: You know, what really happened was the resiliency really pulled us in during COVID. Sure. You you saw all the disruption of people's supply chains. We were working in like medical supplies for obvious reasons. And we were very proud to support a variety of different companies in that space there. The Boston Scientific being an example for it. We then as there became more and compliance regulation around those multiple tiers in the US, we then moved into that year, there are hundreds of millions of dollars of goods being detained. the border, we were helping people actually like show that they were, their goods should not be detained, we're helping clear goods through the border. And then when tariffs came into effect, of course, you know, the whole system changed, where all of a sudden, you know, in the past, people might be like, I don't, you know, it's fine, I'll just pay the slightly higher rate or, you know, I'm not, you know, it's whatever, I don't need to spend the time to qualify for USMCA or really understand this that much. And it's like, oh, my gosh, now it's 100 % or 150 % of the value of the good. I really do want to understand it very quickly. And I want to actually calculate it correctly. And we found, just to go even to the point of calculation, we found there was a huge need for systems that could just calculate it correctly at scale. was being done manually at most companies, like a lot of logistics companies. so we could then actually do this for our clients. And then all of a sudden you're ending de minimis, and now you've got to actually also just assign the right HS codes or tariff categories as well at scale. we've seen a lot of demand, a lot of need.

speaker-0: and most.

speaker-1: We're proud of the work we've done there, and often it's actually reducing costs.

speaker-0: Yeah, lot of the hidden costs of these changing in tariffs isn't the cost of the tariff, but the processing of it. And now with the refunds coming back, that, I was talking to someone just the other day and how that process is going. And it's amazing how much effort that's taking.

speaker-1: Totally. so like our ability to go through and automate that and then like really do the full audit in advance. So it's like, okay, what is the audit actually going to look like that's going to come along with this refund and able to submit it. That's a huge value added to platform for obvious reasons. Cause it's a lot of money.

speaker-0: So let's talk about current challenges, straight of her moose. So we all see it, you know, everyone's even, guess, who's, you know, the, who's the provider where you can see all the ships are and everyone's watching where ships are. What are some of the unexpected things that are coming out of the closure of the straight her moves or the restriction of the straight of her moves that you're seeing that surprised you? Or that would surprise other people, maybe not you, but other people.

speaker-1: I guess I'll go through multiple stages of surprise and answer that question. The first thing that I think is probably obvious to your audience, but isn't as broadly reported upon necessarily is that it's more than just energy supplies. so, energy people talk about like, of course it's impacted energy prices and the price of the pump, but there's other sources. That is a somewhat fungible thing and you can swap in other sources of power generation and there's ways to deal with it. Price goes up, the ways to deal with it. There's also fundamental questions of availability. And when you start to look at things like, for example, that are specific production profiles that are coming from the Gulf, so I'm thinking things like jet fuel or petrochemicals, like, I mean, the inputs into plastics, the primary and the intermediates. It's like, you can't make plastics out of nuclear energy. You can make energy out of uranium, but you can't make plastics out of uranium. And so all of a sudden you might be looking at medical supply. You are looking at medical supply shortages out in Asia because you can't get your gloves. And so, because you literally can't make your plastics. so fertilizer is a similar example. It's like, I need, you know, I need my fertilizer inputs to make my fertilizer. I can't like translate coal into fertilizer. I need to my natural gas. And so what you see is this multiple tier impact that becomes questions, both production and availability. So if you look at like, for example, primary petrochemicals and intermediates, you look at our systems and you'll see about 19 billion in immediate disruption from the Gulf. But this has a 200 X multiplier as you go through the second, you know, the consumption of that and the production of the goods that go into the second tier and the production are moving on to the third tier. So you're looking at those 16 or 16, 18.69 billion night, sorry, 18.6, 19 billion in primary export impact translates right. 2 trillion in first downstream impact. Another 2.7 trillion in second tier downstream impact of goods that are being impacted. And so that's a massive multiple tiers. you're looking at like, that's the macro level and you're looking at 500 companies that their facilities are being impacted coming out of the Gulf. But then that's going to thousands that are being impacted through those multiple tiers. talking about the major companies, I'm leaving aside even the small SM.

speaker-0: Yeah, energy is fungible, but also some plastics are. Is there a reason why it's all concentrated there? There are other sources for some of these, but they're probably not used to the same demand.

speaker-1: different levels of, as you're correctly getting at there, there's different levels of fungibility, availability, and different things. What's happened is that there's all sorts of bottlenecks that have become apparent that aren't allowing the market to flow as easily there so people can get what they need. And what that means is like export, you know, for example, export of natural gas in the US is limited by fundamental infrastructure constraints. There are fundamental port limitations, and there's just locked up in contracts. You know what I mean? It's like, it's spoken for. We talk about price being bid up, it's When it gets bit up, it's coming from someone else who's not gonna get it. And then there's also just like, sometimes it's just locked. The contract is locked up and you're not gonna, can't, they're not gonna break it for you. And that's where you end up with shortage. It's very much the revenge of the real is the experience over the last, I know, maybe six years now where it's like, COVID is a good example where it's like, where things physically are is mattering. And like sometimes you just can't get it. It's like there's not this, you know, getting vaccines wasn't a question of like money in some places. It was like there's just not enough vaccines being produced. And so there was a rationing in their allocation. The same thing is happening this.

speaker-0: So Peter, wonder if, so if generally for chemical plants and things like that, a scale is more efficient, right? Scale economics. And so that naturally drives it. If everything's functioning normally, you'll consolidate and you'll have large plants and because that's efficiency until you get smacked by a disruption, then resilience suddenly comes. There's a, seems to be a trade off. There is a trade off between efficiency tends to be fragile because you're concentrating versus resilience. Do you think this is yet another wake up call to companies where we need to diversify these commodities from multiple locations? Because you'll pay the efficiency price.

speaker-1: Yeah, I would say it is. And I would also say people have woken up is our experience. So there is a lot of, you know, I think resiliency, historically, people were like, okay, the global system is fairly stable. It's like a cost center. Why don't we go with the more efficient thing? I think post COVID and then post effect, you know, post Ukraine, post Hormuz, where you're just seeing repeated disasters. And it's not just, know, conflict, you also see natural catastrophes have increased. You're just seeing like bottlenecks, just everything is becoming more, the fragility is becoming more more apparent as the whole system is being shaken. so resiliency is now a C-suite concern.

speaker-0: Yeah. And I think it takes, there's a lot of corporate forgetting sometimes after, know, if things are smooth for a while. I see this in transportation. The last four years, truckload rates have been just flat or decreasing. And some people are thinking it's going to go on forever like that. And then, you you got to get smacked once in a while and then you wake back up. But there is a lot of corporate forgetting if they're not constantly reminded of this stuff. But do you think that this is changing things or is this just another disruption? I to change things.

speaker-1: We see a lot of demand for this. Yeah. Okay. But I mean, I'll just say this, it helps that it's all married together. So the same system that does compliance and gets your, you you've got your green lane, you're moving your goods quickly, you got your clear for cargo. The same thing that's doing that is also getting you the resiliency is also getting you the efficiency. And that's the fundamental reason that we've unified these all into one platform is because look, sometimes things will be more stable, sometimes they'll be less, but these are just different lenses. Like Altana isn't a resiliency platform. It's not a tariff platform. fundamental platform for global trade. And when new things happen, we'll add the new functionality and everything will be unified and be able to collaborate. And it's that agility that will really characterize organizational success.

speaker-0: And that's the distinction that I'm discovering as I look more into this segment. There are, that's why in the beginning, it seemed like there was more resilience kind of companies versus what you're doing is for trade efficiency, more effectiveness. bringing those together. Peter, thanks a lot. I always learned a lot. So I appreciate it. This is kind of not typical topics that I do in this podcast because we're a bunch of truck guys, but this is impacts what they do. So I appreciate it. Thanks so much for joining me.

speaker-1: No Chris, it was such a pleasure. really enjoyed this and I enjoyed seeing you at MIT. I want to... ...get out again.

speaker-0: I'll buy you cup of coffee. Alright, everyone stay tuned for the truckload market updates. This is the truckload market update for 14 May, 2026. In the drive-in market, we saw the change in active contract rates increased 2.1%. Spot rates also increased 1.4%. And the current level of replacement rates for drive-in is 7.5%, which means new contract rates coming in are about 7.5 % higher on average than the rates they're replacing. We see the market gap between spot and contract being $0.08 a mile, where spot is above contract. And the year-over-year change in spot rates for Drive-In is 31%, while change year-over-year for contract rates is about 5.6%. Okay, on Temp Control, again, we saw the contract rates increase a little lighter than previously, 0.9%. Spot rates jumped 1.6%. Current level of replacement rates for Temp Control is about 4.2%. So, still increasing quite a bit. Market gaps about nine cents a mile, spot above contract. Year-over-year change in spot rates is 24 % and 4.5 % for contract. Kind of similar to what we saw for drive-in. Intermodal, we saw contract rates jump 5.4%. Spot rates jumped 6.7%, although there's very little spot in intermodal. We see the current level of replacement rates essentially flat, like positive 0.1%. It's a rounding error. So pretty flat with a market gap between spot and contract, negative one, where spots technically a little below contract, but really it's right on par. Year-over-year change in spot rates for intermodal is about 10 % increase and about 9 % increase for contract rates. Finally, flatbed. We saw that contract rates jumped 0.5%. Spot rates also increased 1.8%. And the current level of replacement rates for flatbed is positive 6 % with a gap between spot and contract of 21 cents a mile, which is pretty high. Year-over-year change in spot rates, about 20 % for flatbed and about a 2.6 % change in contract rates. Flatbed is just different. Its spot is behaving very differently from the contract side of things. Alright, so contract spot rates up across all the modes. That doesn't happen that often to be honest. Usually there's one that doesn't quite do that. Comparing year over year, all the modes are between 10 and 30 % up for spot rates and about 3 to 10 % for contract. Replacement rates are all in the positive 4 to 8 % except for intermodal which is flat and that's kind of reflecting what we hear anecdotally as well. RFPs are bringing in or increases of around that four to eight percent. And somewhere the gap between spot and contract is flat to positive across the board. So we're in a new cycle. The market's tightened, been tight since December. We see it continuing throughout the spring and into the summer. And that's it for the truckload market update for 14 May, 2026. And that's a wrap for this episode of The Freight Fine. The Freight Fine podcast is hosted by myself, Chris Kapless, and is produced and edited by DAT Freight and Analytics. For more information or to catch up on previous episodes, swing by our website at www.dat.com slash resources slash Freightvine. And don't forget to hit that subscribe button wherever you listen to podcasts. And hey, why not drop us a review while you're at it? If you have any feedback or questions about what you've heard or suggestions for what you'd like to hear in the future, please send an email to me at chris.capless at dat.com. That's C-H-R-I-S. ⁓ And finally, a big thanks from all of us at DAT for tuning in. We hope you learned something new and you come back again.