Think Customs Is Still Randomly Checking Cargo? Think Again (Podcast)

AI in Customs Enforcement: Inside CargoSeer with David Smason

Artificial intelligence is already reshaping global trade compliance. But what happens when that same technology moves into the hands of customs and border agencies? In this episode of Simply Trade, Lalo Solorzano and Andy Shiles sit down with David Smason, co-founder of CargoSeer. His technology was recently acquired by BigBear.ai. Together, they explore how AI is modernizing cargo inspections, customs enforcement, and border operations.

From X-Ray Analysis to Decision-Support Platform

CargoSeer started with a focused challenge: helping operators analyze cargo X-ray images faster and more effectively. However, that concept evolved into something bigger. Today, it’s an AI-powered decision-support platform. It brings together imaging, trade documentation, supply-chain information, and other data. As a result, frontline operators can identify higher-risk shipments and make better-informed decisions.

Consistency, Customization, and What’s Next

AI also creates an opportunity to improve consistency across ports and inspection teams. Experienced customs officers often develop sharp instincts after decades on the job. So, AI can help capture patterns from effective inspection methodologies and apply them more broadly across an agency. David also discusses CargoSeer’s work in El Salvador, where highly customizable AI helps customs administrations address their specific enforcement, revenue, and operational goals.

Ready to Go Deeper?

Whether you’re new to trade compliance or sharpening your team’s expertise, GTC offers courses built for real-world skills. So, explore GTC’s Importing Procedures to find the training.

Transcript

Andy Shiles (00:06)
there’s so much artificial intelligence in with systems and different things. Now we’re getting into a scenario where it’s been out there for a while.

And actual different places, you know, private companies are actually applying it, governments are applying the use of it and all that. So we’re gonna get into talking about I think how we’re gonna see some springboarding of certain customs agencies around the world as well as the US that AI is helping them

I think there was a Lila, I think we had a another show that said this, and I think it’s so apropos to this discussion. The government usually is a day late and dollar short. They’re usually behind the industry. And now they are getting ahead of industry and on things. They know more about what somebody’s importing and exporting

especially on the import side, probably more so in their supply chain than the company themselves. So I’m looking forward to this discussion and and all that. But that’s the the development of AI technology is phenomenal. So we’re gonna get to talk about some folks that we know in the industry and some the latest, greatest news I think.

Lalo (01:33)
So here we’ve had like you said, several guests that talk about AI. but what they do is that they they address the trade professional side of the of of the of the equation, you

Andy Shiles (01:44)
Mm-hmm. Yep.

Lalo (01:46)
know. So this one is very different in which

their business. and we’re talking to David Smason here, by the way, from Big Bear. and and we’ll we’ll talk a little bit more about that here as he comes in. But what what we’re looking at is that his technology is mostly to modernize like you said, Andy, customs agencies or border operations throughout the world. And it’s very interesting just to see how his technology has

been adapted to help those those agencies deal with you know just the different things that are going on in the border and and operations in and out of you know crossing borders. But anyway, so we have David who who will be joining us. his company was just recently acquired. We’ll we’ll hear a little bit more about that here as he explains a little bit, but for the

Full information for David, you’ll find it on our show notes here down below in the in the description. And or if you’re watching this on video, check out the description on YouTube and you’ll find more information. But it this is pretty interesting only because we get to see the flip side

Andy Shiles (03:01)
All right. David Wake w welcome to our show. I’m I’m looking forward to this. So won’t you tell everybody a little bit about what has been going on with your company? It’s it’s just some breaking news here, if you will.

David Smason (03:14)
Yeah. Well, yeah,

I mean, it’s pretty cool. we’re excited. been excited for a while. first of all, thanks guys for having me. Good morning to everyone. I mean, to understand what we do, we gotta go back a couple years ago when I had my aha moment, right? so I’ve been working in this industry for a while. and about four or five years ago, I started realizing that massive amounts of data are coming online.

Right. and at the time I thought it was just the physical data, just the x-ray images. I mean it very, very focused on looking at an x-ray machine. I couldn’t understand for the life of me why we can’t have technology that would help the operator adjudicate the image, you know, better, faster, more efficiently, whatever it is. so I got this crazy idea in my mind that, hey, why don’t we create AI?

That can solve all these scenarios. and it again at the beginning I thought it was only going to be just for x-ray images and hey, let’s find narcotics, let’s find contraband, let’s find cigarettes, whatever, in this specific image. so we founded cargo seer together with my partner, and as we got into it, we started realizing that while x-ray images are important, the real special sauce or the holy grail.

Of what we can do is to take all of the data, all of the trade data, right? Including the documentation, including the supply chain data, including external data, internal data, whatever it is, stuff that a customs agency would be looking at anyway, and more importantly, stuff that an operator would be tasked with looking at and putting that into a system that

analyzes everything and allows the operator to have the right information to make the right decision in a timely manner. So that was kind of the origin story of CargoSerum. As I said, it started really with solving one small problem. How can we analyze, how can we adjudicate X-ray images better? Or how can we support the operator in adjudicating X-ray images better? And then it ballooned into this massive artificial intelligence infrastructure that’s capable of taking all of the information, right?

and not only taking all the information and analyzing it, but taking all the information, analyzing it, and presenting it in a manner that an operator can understand. Now, how do we get there? a lot of times when technology is developed, so

really, really smart people will sit in a room and develop technology and then try to take it out and find use cases for it. we kind of did the opposite. We observed operators for tens of thousands of hours and we said, show us exactly what you do. And we replicated exactly what the operator did because we understood that it was so important that we not introduce something that’s foreign to the operator, but that we introduce something that looks familiar for the operator.

Right? Something that they know. They wake up in the morning and they’ll say, hey, this looks this looks, you know, similar to how I’ve been trained. So we did all that, we built the company, and about a year and a half ago,

We started engaging with Big Bear primarily with Kevin McAleenan right? And everybody knows Kevin’s background. He’s kind of the guru of this industry in the last 20, 25 years, right? Been in all the right positions, both on the operator side, right? I mean, the man ran LAX, right? But also

Lalo (06:28)
Right.

David Smason (06:29)
on the policy side, you know, serving in in the first Trump administration and so on and so forth. So I was really, really, really excited by the fact that we would be able to join forces with a company like Big Burn, more specifically.

Specifically with an individual like Kevin McAleenan right? And match this technology with the deep operational expertise. Because if you remember at the beginning, what we set out to do was give the operators tools that they can actually use, not create technology that nobody’s gonna be able to use. So when we met Kevin, right, and said, Hey, this is something cool, let’s start talking. And as time went on and we started collaborating, we said, Hey, wouldn’t it be interesting if we really joined forces? And then, you know, Big Bear acquired us at the beginning of January this year, and the rest as they say

history and we’re we’re really off to the races here, had a great start of the year, and we look forward to doing really, really great things over the next five, ten years.

Andy Shiles (07:21)
let’s let me jump in and just say this for a minute is that for those that may not know, Kevin McAleenan used to be the commissioner of customs.

has worked up like you just said, he ran LA. He he’s gone from the front lines all the way up through the organization, has been an outstanding executive for CBP and now he’s the CEO of

David Smason (07:51)
Big Bear AI. Yeah.

Andy Shiles (07:52)
Big

Bear AI. And with that, your company has been acquired just recently by Big Bear, which says a lot because I I personally met Kevin and and and I’ve worked with a lot of his executive team over the years and he had surrounded himself with some good, good, good people. That is one smart guy. In addition, I’m sure now that if you’re

well not yeah, if you are part of his executive leadership team, that is something. So that speaks volumes about your products. So you you called a cargo seer is that right?

David Smason (08:37)
seer like somebody you can kind of see into the future. That was the origin. Yeah.

Andy Shiles (08:42)
from my I I I will also say this from my background. I had over thirty years with FedEx, but I have been in other positions where I’ve actually gotten to see the clearance operations

I have seen them select a lot of shipments and they’ll go through and they’ll inspect them.

I guess the red flags come up on shipments that they need to apply their expertise to to say, hey, we really do need to look at this, but then it’s it’s a more efficient process.

David Smason (09:17)
when we started to kind of get into the nitty-gritty of okay, how is this technology assessed, right? What are the KPIs? What what kind of performance do we need to to bring?

The initial thing or the biggest thing that, you know, agencies were telling us is can you help us reduce our time to release, right? We have the exact problem that you just described, Andy. They had that problem. They said, hey, w we might have some systems, but it’s pretty much randomized. Check. I I don’t know what what you saw, what you were observing, but most places it’s pretty randomized, right? Just like when you go through the airport and the metal detector beeps and like, you got selected for a random check, right? And next to you there’s like 98-year-old grandmother in a wheelchair also got selected, right?

Kind of the same thing.

Lalo (09:59)
Mm-hmm.

David Smason (10:01)
so I mean they said, hey, we we want to get things faster, we want to be able to release more cargo, but we cannot compromise on the integrity of the inspections. And one of the biggest areas that we were able to address initially was empty containers, right? I was flabbergasted, literally, to see that an operator was expending the same time, the same resources, cognitive resources, on adjudicating an empty container, right? And the container’s empty, they’re supposed to be empty.

There’s not supposed to be anything in there. A lot of times there is stuff in there because it’s a great avenue for smuggling, right? But the operators looking at said, hey, this is a use case we can solve very, very quickly with AI, right? you can hit 99 100% accuracy relatively quickly, and that’s what we did. So that was the first use case, and and really adjudicating the empty containers. Now, in every port it’s different, export, import, but they make up between 10 to 30 percent of the containers going in and out of the port, right? And we immediately reduced.

full automated analysis and now when I say full automated analysis it means that the operator is quickly able to look at it and make the decision. And we’re very proud of the fact that our analysis happens in under five seconds, right? So if you think about it previously an operator gets an empty container spending between three to seven minutes on adjudicating that container. Now with our technology, right, they can do the same thing with the same amount of accuracy and the same level of confidence in under five seconds. That’s kind of the increase that we were initially looking for

Right, and once we got into it, we started to understand there’s other areas, what we call low-hanging fruit, right? So when we look at our country, the United States, where there’s a lot of produce coming in, right? And these are relatively easy

loads

Andy Shiles (11:42)
Right.

David Smason (11:43)
to adjudicate because they’re homogeneous, right? So we have algorithms that can look at that and say, hey, there’s an anomaly here, or this entire load looks like bananas, right? And this is okay, this is legitimate. obviously, the second thing that that a customs agency is interested in worldwide, right, doesn’t matter where they’re at.

revenue they’re looking at increasing the amount of revenue while making sure that their inspections are in as point as possible and what we’re seeing the technology able to achieve is exactly what you described.

Lalo (12:13)
Yeah.

David Smason (12:13)
So let’s say you have a randomized system

flagging 10% of cargo because that’s the amount of cargo that can be efficiently inspected, right? They sent their benchmarks, say we need to release it within whatever it is, 10 minutes, we need to make 70 million dollars a year just throwing out numbers. So in order to do that we have an equation that says we need to analyze 10% of cargo, right? So even if we’re not increasing the level the amount of cargo, the quantity of cargo, we’re able to ensure that those 10% that’s being that 10% that’s being inspected is

the high value are the high value targets. I’m sorry. So instead of looking at something and kind of guessing, we might be able to get some revenue collection here, or we might be able to to recover some revenue or the tariff is wrong or classification, whatever it is, we’re saying with a much higher degree of confidence that that 10%, whatever the numbers are, when we go into a customer, we say, okay, first of all, what do you want to achieve? Because you can’t walk in and say, hey, we’re going to give you technology and nobody really knows what it is and nobody really knows how to assess it, right? We say, what do you want to achieve, right?

You want to hit a TRL of three minutes, just as an example. You want to increase your overall revenue collection by 72% year over year, whatever it is, right? And then we can go ahead and calibrate the technology for that. So that’s really what something really, really cool that is happening with the advance, with the advancement of AI is the level of customization that we are able to achieve with each and every use case. I mean, crazy things like when I was in the front lines 10 years ago, I wouldn’t have even imagined that we could cover so many threat vectors, right?

Right? So I mean you can cover 10, 15. A great operator can cover 30,

Lalo (13:48)
Yeah.

David Smason (13:49)
40 by themselves, right? But AI is able to look at so many different scenarios, game out all of these different probabilities, and say this is the one I want you to focus on. Right? So that’s kind of where we’re going with the ability to

Maybe inspect more cargo, maybe not inspect more cargo. At the end of the day, it depends on what the customer wants or what the agency wants. But what we will always ensure is that the cargo that we’re flagging for inspection will necessarily be a high value target, right? And their probability of achieving their goals from that inspection will be much higher, right? So they’re not wasting time on

empty containers, right? They’re not wasting time on small collection amounts. I mean we we have a customer right now who said, look guys, anything over fifty thousand dollars in revenue collection, in recovery, I’m sorry, we don’t care about. It’ll cost us more money to go ahead and get that from the importer, right? We only want things over fifty thousand dollars, just as an example. So we have the ability to kind of move that around and customize it and fine-tune it for the for for the operator and at the small scale and for the

For the whole agency at the larger scale. And again, going back to our previous comment about Kevin and Big Bear, this is really where that kind of operational expertise comes in, right? Because they can go in, they were on the inside for 20, 30 years. These folks know exactly, exactly what the operators want. And the last thing I’m going to say is something that’s important for any AI technology company selling into these spaces, one of the biggest pitfalls is bringing something to market or giving something to

the operator that they won’t want to use, right? And it’s like they can smell it. They know if it’s not real, right? They know if you’re if you’re faking it, right? So you gotta be 100% certain that the operators are gonna. That’s why we started operator first, and that’s why we’re continuing together with Big Bear with that operational expertise to make sure that we’re always serving the operator first. So again, apologize for the long answer. Just get passionate when we talk about the performance matrix and the outcomes for customs.

Lalo (15:55)
No, that’s

fine. I I I I think that I think that’s fine. But I I I was gonna also ask you, be in the research that I was doing leading on to this episode and from other information that I found, I mean, aside from the fact that you’re obviously now vice president over at Big Bear as compared to how you were CEO previously from CargoSeer. But aside from that I did see

That you all had a 12-month pilot with country of El Salvador and you recently got the win, and so you’re you’re actually now fully implementing. So now you have an actual case study that you may be actually be able to explain and talk to. Like how how does that, what is it that they were looking for that that 12-month pilot maybe helped you to get that win and come in? And and how did Big Bear maybe even help?

Maybe push it a little further and along and and

David Smason (16:45)
a hundred percent.

Lalo (16:46)
and and and come come through with that with that deal.

David Smason (16:50)
No no no ifs ands about ifs ands buts about it, right? Big Bear definitely helped us cross the finish line there. We’re you know, that that’s exactly why we joined forces to, you know, kind of convert those pilot opportunities into real operational technology. yeah, El Salvador, we announced it, I think it must have been two, three weeks ago. very, very exciting for us. and as in any customer, right? We’ve obviously had multiple customers that you know we’re not really supposed to talk.

About really not a lot to talk about previous to the acquisition and ongoing. but the lines are the same. The reason they came to us is because they wanted, on the one hand, technology that could be very, very, very specialized for their use cases. El Salvador is no different from any other country, right, with a high level of technical and technological proficiency. They know exactly what they want, right? And what they don’t want is a standard off-the-shelf AI solution that is scalable.

for hundreds of countries, right?

But when you come and use and you say to that provider, when you say to that vendor, okay, well, we want this change, or we need this, or we need to update this, or we need do that, it’s gonna take them three years and they’ll charge you $10 million to do it, right? That’s the old model, right? That’s the old model. what countries like El Salvador are looking for is highly customizable technology, fine-tuned to their specific use cases. And obviously, I can’t get into the nitty-gritty of exactly what they’re looking for, or whatever any any of our other customers are looking for, but I can say that we’ve developed

thousands and thousands of very very very operationally specific models specifically for what countries like El Salvador are looking for. And that’s the real edge, right? And that’s the competitive edge that any AI technology is gonna have to find if they want to really thrive in this new environment. you know aside from that like any country like I mentioned all of our customers are interested in money right

You know, so that everybody is interested in how can we increase revenue because it it it’s like seeing this massive it’s like buying a lottery ticket, knowing that you won, going to the store.

And saying, hey, you can’t redeem this, right? You see the money there, you want to grab it, but you just don’t have the ability to do it. Right? So what if I came to you at that moment when you’re leaving the store dejected, and I said, Hey, I have a solution for you that can help you redeem this lottery ticket? Those are literally the conversations we’re having with these folks, right? When they see this type of technology and they see the impact of this technology. So we’re very, very, very excited about our

deployment in El Salvador, but we’re even more excited about the potential that it opens for us in Central and South America because those are our neighbors to the South, right? Very, very, very important for the economic prosperity, not only of that region, but for the United States itself, right? And we look forward to supporting everybody in achieving the same level of technological, I don’t want to say superiority, because that’s not right, but the the right level of technological proficiency that we’re able to bring to customers like El Salvador.

Lalo (19:59)
Mm-hmm.

Andy Shiles (20:01)
I would say that that’s one of the things that it it it again, it makes things more efficient for, you know, the agency and the the thing of saying, you know, they want to increase revenue. Well, I I would say it this way is that you want to make sure that everybody’s playing by the same rules. In other words, everybody that’s importing isn’t is not circumventing something. So from a competitive

standpoint, it it’s it’s actually a i it evens or levels the is what I’m trying to get at levels the playing field for all the importers or the business community or something. Somebody’s not circumventing something, getting something through where they should should be paying more in duties and taxes, because of the way they’ve declared it or whatever. This is your system

gives the ability to catch that, I guess, and and and make sure everybody crosses the Ts and dots the I’s. So that’s that sounds

David Smason (21:04)
Yeah.

Andy Shiles (21:05)
phenomenal in that. The other is is that

is impressive. I’m sure that it’s customizable even down to the operator level at each port. Each port may have a has a different personality or demographics is maybe a better way of putting it of what cargo is going through there based on the mode, based on who’s using that or whatever. So in the end, would you say, David, that this gives the ability to be

for the agency to be more consistent across the country.

David Smason (21:43)
Yeah, a hundred percent. I I do I do wanna

Give a shorter a short answer to your previous comment about leveling the playing field. One of the things that we’ve seen across the board is everybody’s interested in counterfeits, right? Everybody’s interested in understanding how they can really make sure that everybody has a fair crack. And what’s interesting about in the counterfeits use case is industry is getting so involved. So I’m not gonna dive down that rabbit hole, right? But the big brands are

Andy Shiles (22:08)
Right.

David Smason (22:08)
very, very invested in that. with regards to your set your second comment, yes, it’s making things more consistent.

100%

enforcement is more consistent. the ability to track enforcement and interceptions is far more consistent. And one of the nice things about AI and our our solution in general is it can track everything that an operator is doing.

but really really to the nanosecond level we call it, right? Where their eyes go, where they click, what they look at. And we’re not doing that to track to try to find people who are, you know, doing things that they shouldn’t be, shouldn’t be doing. We’re doing it to improve the system. We’re doing it to improve the efficiency. And what was, you know, previously missing was an operator might be doing something really, really good in one port and this guy’s been there for 40 years and he knows everything. He knows everybody. You know, you know how they say it. I can smell the fraud, right? I’ve heard that so many times, right?

Andy Shiles (23:05)
Yeah.

Yeah.

David Smason (23:05)
I can smell the narcotics,

right? but how do you take that knowledge, expertise, and experience of that operator’s been there for 40 years and apply it across the board, right? You have him come in, you teach a workshop, but he doesn’t really know what he’s doing, how he does it, right? He’s like, you know, instincts, right? And that’s true. But we can now look at what those kinds of people are doing and say, okay, how do we take those methodologies and those approaches to adjudication and how do we train an algorithm so

Instead of just having one really effective Andy, we have 10,000 really effective Andes because those are the algorithms that are operating just as Andy would have operated, right? And we’re seeing massive increases in efficiency, but also consistency. And if you look at it from the importer side, you know.

I I don’t know if we have any of this in the US. I’m not really on that side, but in a lot of countries we have selective enforcement, right? And it makes it a lot fairer for the importer, right? And it it allows them to understand exactly what’s gonna happen, right? It’s not their shipment is getting stopped because of some non-existent issue. They know that if they do something wrong, they’re gonna get stopped, but they know also know that if they play by all the rules and pay everything that they’re supposed to play and fill out all the forms properly and documents and submit and so on and so forth, then they’re gonna be let through, right? So it

Also gives a level of predictability, and in supply chain, the number one thing that you always want to go for is predictability, right? So if we can give the importers and the economy that predictability, then in some indirect way we’re also, you know, supporting economic prosperity, which is our overreaching goal, right? So economic prosperity, national security, and so on and so forth. So yeah, you’re 100% right. it provides consistency, but where we’re taking it is trying to take that consistency and run.

replicate it across every single every single use case. Now I will say, you know, air is not like sea, sea is not like land, planes are not like ships, containers that come off a ship is not like, you know, a container that comes off of a plane, whatever

Andy Shiles (25:07)
Right.

David Smason (25:08)
it is. And that’s really our biggest challenge. And that’s what we really look forward to cracking in the next three years.

Andy Shiles (25:14)
Well, it’s you’re hitting the nail on the head is that each mode of transportation has different nuances that again, the the the ports are different, the the operations themselves are different, there’s a significant difference.

with the express operators and the and what I call the express mode of clearance versus air cargo versus truck versus you know royal and and ocean. So I I I do have a question though is in this is that we’ve been focusing a lot on the customs. What about the other agencies and in particular here in the US like FDA? I I I’m telling you some of these agencies when in their process they’re so far behind they think they’re ahead because they’re

It’s what I call the Charmaine method of of clearance. You remember the old Mr. Whipple and the Charmin toilet paper commercials? Don’t squeeze the Charmin kind of a thing?

David Smason (26:13)
I d I don’t remember, but I can imagine. No, I

Lalo (26:16)
I was gonna say he’s probably

David Smason (26:19)
get it.

Lalo (26:17)
too young for that, Andy.

Andy Shiles (26:19)
Boy, did I date myself. But that was the the whole point of that is that

they want to see the the paper. They want to hold the paper, they want to look at it, and you can go through it. And it’s like, Lord

David Smason (26:32)
Right.

Andy Shiles (26:32)
have mercy, come on and and get into the twenty-first century. What about the other agencies, David?

David Smason (26:40)
The other agencies love it.

They love it because it gives them a level of confidence, right? I mean, if you look at you’re talking about documents and holding the paper, one of the one of the first things that we started solving in documents, similar, you know, I told the story about x-rays, is the very simple operation of extracting the information from the document, right? If there’s one thing that people hate the most, anybody who’s in these government inspection jobs, operators, doesn’t matter where they are, it’s reading 50 documents that are probably badly scanned, right? Sometimes they can come on a clipboard, right? We’ve seen that even in the United States.

States.

Andy Shiles (27:12)
Yep.

David Smason (27:13)
and the first thing we developed was the ability to extract that and put it in a digital manner that they can understand, right? Not changing the data at all, not analyzing it, not doing anything different, just putting it in a screen, right? And having it readily accessible to them on their iPad, on their terminal, even sometimes on their phone, right? So they love these technologies. Now you’re right, there’s a big challenge.

you know, when you talk about the OGAs, other government agencies that are heavily invested in the customs enforcement process, you know, both from health, safety, and all the way down to national security. at the end of the day, we believe that algorithms are going to be the great equalizer, right? An algorithm does not treat things differently, right? It doesn’t matter if somebody’s looking for, you know, the phytosanitary certificate to make sure it’s compliant, or they’re looking at the tariff, right? The algorithms can do all of that. And

At the end of the day, where we believe that the future is going is there’s going to be one system. So if you you guys remember 25-30 years ago, concept of single window, right? And I’m supposed to bring all the information together, it just made things worse, in my opinion. I’m sorry, that might

Lalo (28:16)
Yes.

Andy Shiles (28:16)
Yes. Yeah.

David Smason (28:18)
be a little controversial, right? but the more information that’s in there, the harder it is to look at it. So what we’re doing is looking at the next generation of single window, AI gen AI-enabled single window, right, and saying all this information is coming together, but that’s all in the back end, right? All you need to do.

Is look at your specific use case and the screens that we present, you can look at the health concerns, you can look at the safety concerns, you can look at the national security concerns, you can look at the revenue concerns, right? And the end of the day, these interfaces are going to serve all of the government agencies. Now I will say we have a long, long way to go before policy gets there, right? I don’t even want to get into the complexities and you you guys know this better than I do, but you know, getting FDA to give budget to C B P to support, you know, all these things without

You know, get getting them all to agree on a single interface, that’s probably gonna be the biggest challenge. But what I can say is that the technology is moving in that direction rapidly, and that’s what we talk about when we talk about consistency over the operators. It’s not only an operator who has to look at an extra image in the right way in the in a similar manner across ports, it’s inspectors all over the world even, right? And again, I don’t want to go down this rabbit hole of global trade and stuff like that. Maybe that’s for another episode. but yes, it’s definitely

making everybody happier. Well no. It’s making a lot of people happier. There are some people, as in any situation, who don’t like progress for multiple reasons, right? But yes, the short answer is yes. They’re happy about it.

Andy Shiles (30:00)
Well, with all that to say, I it sounds like it’s you’re making the front line much more effective as they’re dealing and protecting our ports, our borders, if you will, and our ports with the cargo that’s coming through as well as other country frontline folks. So not only is it more effective, it has to be much more productive and

when you’re effective that means that it’s a cost savings to the in the end to the to the taxpayer, but also that i i it it gives the incentive do things right, cross the T’s, dot the I’s and you’re gonna be able to get your stuff through and and the bad guys are gonna get caught. So

David, I I appreciate your d discussion. I I definitely we wanna come back and hear some more, especially as you’re developing more products with this or or implementing more situations and see what’s going on in the industry. But do the sake of time, we need to wrap this up. But thank you again for being on our show. Lalo, any last words from you?

David Smason (31:09)
Absolutely.

Lalo (31:10)
No, just just thank you to David because the this was this was a good conversation. something we’ve never really had in our show, which is other than I guess when we have Alan on the show, Alan Bersin you know, but but he doesn’t really dig this

this much into it as well. But you know, it’s this was a good a good conversation and thank you, David, for joining us for this.

David Smason (31:35)
Absolutely. Thank you guys anytime.

Andy Shiles (31:36)
Folks, I will say

David Smason (31:36)
Perfect. Thank you guys.

Andy Shiles (31:37)
thank you again for your listenership. we yeah I continue to get more and more listeners around the world. like us, share us, subscribe to us, follow us, whatever the button says. we greatly appreciate that. And with that, hope everybody has a great day.

Lalo (31:55)
Thank you, David.

David Smason (31:58)
Thank you.

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