provider of integrated technology-enabled asset protection solutions. Industries served include oil and gas, aerospace and defense, renewable and non-renewable power, civil infrastructure, and manufacturing. MISTRAS shares are listed on the New York Stock Exchange under the symbol MG. Welcome, Ed.
Thank you, Mark, and thank you, Noble Capital Markets, for sponsoring today's meeting with you. I appreciate your time and interest in the MISTRAS Group . Before I go too far into the presentation, I'll just give you a fair warning here. I will be making forward-looking statements. I will be using non-GAAP measures. All of those are governed by, obviously, provisions, whichever read to you, but this entire presentation is found on our website, including reconciliations of the non-GAAP information. As Mark said, MISTRAS Group is a asset protection company, tangible asset protection. We are there to keep uptime and safety for our customers' most mission-critical assets. We were founded and went public back in 2009. Founded actually before then.
Based in Princeton, New Jersey today. Our Founder, Sotirios Zachariadis , is currently Chair Emeritus. Manny Stamatakis is acting as Interim CEO at the moment. I am CFO plus. John Smith heads up our services portfolio. Gerry Del Terrio is all things commercial, and Hani Hammad is our Chief Transformation Officer, and I'll touch on those roles as we go forward in the presentation, but essentially, MISTRAS is an ESG enabler. We are there for safety, job one, two, and three for our customers. We're there to keep assets in their intended state, condition, good working order, maximizing uptime, minimizing unplanned outages, and safety, again, is a primary reason why we are there.
We offer a one-source solution to our customer, and I'll explain to you exactly what that is and what that means, and that's a newer and developing part of our portfolio. But first and foremost, let me just define for you very simply what non-destructive testing is, NDT. I'll also use the term NDE, non-destructive evaluation. What it essentially is, is a method, a technique that I use to identify something you cannot see with your naked eye. So corrosion, cracks, leaking, some integrity issue, that's happening to the asset now. I wanna find it early on before it propagates into a bigger problem, and along the way, obviously, I'm there for efficiency, effectiveness of the operations of my customer, as well as safety being, as I said earlier, job one, two, and three. What are these techniques?
Ultrasonic would be a technique, an RT, an X-ray, a radiographic technique. I'll just draw your attention to one thing on the page here. It's the middle box on the left side. Acoustic emission is something that our Founder Sotirios started, put us on the map for. That's basically listening to what's happening. And VPAC is a piece of equipment that I manufacture. It's hardware that can basically listen to an open valve, hear the damage, hear the problem, hear the waste, call it out very quickly, fix the seal, fix the valve, and then, as an example, I might not need to vent off and flare that methane gas, as an example. Lots of ways to work way upstream to prevent an issue that has to be corrected on the back end.
So now I'll walk you through in a little more detail, that AE on some other examples, but it's one of many, many techniques. Again, it's a non-invasive way of assessing what's happening on the customer's mission-critical assets. That's what NDT is all about. So who do we help? Well, as Mark mentioned, oil and gas obviously is a big group for us, upstream, downstream, and midstream. Anything industrial, power generation, infrastructure, bridges, you name it. Aerospace and defense is also a critical market for us, wherein we're actually testing component parts, whereas on the other industries, we can be in the field testing the actual asset in service along the various stages of its life cycle. And that's an important distinction, not just who we help, but how do we do it.
Again, field is where we go visit the asset. That's a picture of a technician on the far left there in the middle of the page, up at height, testing, you know, a apparatus. On the far right would be in my shop laboratory, a part coming to me for testing, such as a titanium part going into a new aircraft, and I'll walk you through in a little more detail what we do and why that's important. But in the middle, there's data that ties it all together, and that's the piece I'm gonna spend most of today's conversation on. Why is data important? We're not new to it.
We've been selling software and sensors for quite some time, using our AE technology as a core there, and I'll walk you through why that's, you know, a very compelling argument for the customer to tie this together in this bundled one-source solution that, we feel is very proprietary. It's unique, and our competition does not offer such a breadth of, capabilities. First and foremost, though, the technician is critical here, whether it's collecting data, assessing data, giving the customer information. Technicians are with the customer every day of the year, helping them work through their asset integrity issues. We believe we have one of the largest, workforces in the United States, very highly trained NDT technicians, skilled to collect data. They're skilled to work at height in many cases.
They're there to, you know, call out what they see in front of their eyes, as well as use all these advanced techniques that we've employed over time. Critical, critical element. You know, these are assets that are under, you know, tough working conditions. What's happened before might happen again, but there's always new facts and new circumstances, new variables, so the technician, the human, is a very important aspect here of all the work we do, particularly in the field. Now, they're not alone, though. I would say in the field, we're looking to automate what happens and speed up the collection, improve the quality. As an example, on the page here, are two examples of how I do that.
On the top left is a robotic crawling device, an ART crawler, automated RT radiographic techniques, taking an X-ray, basically. So that little device, which we built in-house and have patented, basically walks along the pipe, insulated pipe, or in this case, it's exposed pipe, and it's taking an image, almost 360 imagery of what's inside the pipe that I can't see, a weld, a crack, a pinhole, you name it. In the past, technicians would have carried the equipment and taken an X-ray shot at different intervals. Now, I can do it along the whole length of the pipe, so it's faster than I could have done it before, taking intermittent shots. So that's a very critical piece. On the right is an inverse of that to a certain extent.
This is a buried pipe PIG, as I affectionately call them, pipeline inspection gauges, PIG, which is running through buried pipe, doing a similar thing, taking an image of what's happening inside there. Again, looking for pinholes, looking for the assessment of the crack, the ovality of the pipe, et cetera, et cetera. Why is this important? Well, much of this is regulatory. The U.S. Department of Transportation and its PHMSA rules require that this testing be done to a certain standard, hence, you know, why this is an important part for us. Much of this is on the midstream. Inline inspection testing is very critical, and again, this speeds up what the technician does.
In the end, there's data being collected here, data being analyzed, and that's the most important piece of the puzzle, the most important thing that I offer to my customer, and I'll come back to you in a minute on how we pull that together. Shop labs are sort of a little different sort of location, basically, but same work happening. In this case, at my shop laboratories, the parts come to me for testing. It's not a fully assembled piece of equipment in service, but a component part. This example here is of, you know, a fan blade on a jet motor. It's the final output here, but it starts with a forging, a casting. A raw piece of titanium comes to my shop, so we're going to test it.
We're going to inspect it, make sure there's not a void in that metal as it was initially fabricated. Along the way, it's going to go through various fabrication steps. We like to do all those steps in-house. If you've listened to our last couple of earnings calls, we're doing a lot of CapEx investment here, expanding our service offering to help, you know, speed that part to its finished final assembly stage by doing more steps. In the past, all these steps were done by different vendors. Each time a step was done, the part had to be tested again. Now, we can keep the part in our shop, send it back for testing each time a step happens. There's CNC machining here. It's light, you know, additive manufacturing, and this is a real good place to grow our business.
It's commercial, it's private space, as well as defense going, so lots of good business here, and we are expanding this piece of our sector along the way, but as I said initially, data is the real key here, so whether it's in the field, working at height, or in my shop lab, it is about data, so as you kind of come across the spectrum there, but then you get into, "Okay, well, what do I analyze with the data?" Maybe there's something consulting I would do here. You know, there is, you know, maintenance that I might obtain here. There is real testing has to happen, and of course, I use some of my own proprietary equipment and sensors to make all this happen.
The core of this, though, the starting point of data, is really, knowing what's happening over the long haul to assess and analyze, create trend lines and algorithms of what, you know, what is happening. We filter that through something called PCMS software, Plant Condition Management Software. This is a core piece of our data story. We've had this piece of software for quite some time. We bought it from BP years and years ago, and it's in a, you know, a large number of U.S. refineries today, dictating how they analyze things, how they risk-based things. Basically, looking on the chart here is a way of assessing, what's the probability of something going wrong, and what's the consequence of that? So the green assets, I probably don't need to worry about very much, very often.
They're in good working order, low risk, low consequence. The red assets are ones I should really focus on because they're, you know, going to have something of interest on a frequent basis and/or of severe consequence. The amber and yellow are different stages, but generally, you would work to prevent the asset from moving into a red by better managing the risk. More recent, it's more common, you know, in more frequent way or of a touch point there, would be one way of working through there. But risk-based, how I look at life, how I manage these assets, is really what I want to do, and it is a software story, it is a data story. But it's only a piece of the puzzle. So PCMS here is on the flywheel to the, on the nine o'clock position there.
It's only one piece of the puzzle, and this is that bigger bundled solution that I referred to earlier, so PCMS is only one piece of software. Onstream uses separate software. New Century is another geolocation software that I acquired along the way, and I tie this together in a sort of a bundled suite of applications. So if you start with PCMS, for the sake of the argument, at the nine o'clock position there, that's a snapshot. That's a point in time, but it drives actions, it drives insights that you know into what we call our OneSuite portal. But OneSuite, again, is all my applications. There's calculations, there's reports, there's risks that I want to manage, but it doesn't stop there.
I really need to feed data in through the robotic crawler and the PIG that I just mentioned, let alone a sensor. Technicians grab more data, I warehouse it, I assess it through my software, and then it kind of tells me what I learn over time, how I can do the work more efficiently. So really, what it's moving from is a time-based testing type of approach, where maybe I showed up my technicians every thirty-six months. Now, I can risk-based when I show up. Maybe it should be a lot less frequent than 36 months, or perhaps more frequently. I wanna risk-base what I'm doing based on the condition of the assets, based on other relative factors and variables, and what's going on.
So the more I'm there, the more I'm connected, the more I'm validating algorithms, the better, and I could get in advance of this for my customer, and just give them more value add. It creates a higher retention factor here. None of my competitions has quite the entire holistic solution here that I'm offering to the customer. So this is my data solutions offering, which we're really leaning into for the customer to really expand the connectivity. And, it's real, it's here, we've done it for some time, and it's also only in a few of my key end markets, oil and gas, other process industries. The two bolded on the bottom there are where my data solutions is strong right now.
My other key end markets here have not been exposed as much to my data offerings, so that's where we really want to expand it. But it is real. There's over two million assets being analyzed now. It's about 10% of my revenue, and it is expanding globally across the end markets I serve now. So we believe this is a very logical way to expand our business. Data can lead service, service can lead data, vice versa, and we're gonna really lean into this part of our business. And it is worth it. There's a huge value add here for the customer. These two examples illustrate that. The names had to be masked here just for the sake of confidentiality, but on the left side there, this is a real example.
This is a PCMS customer who does an expensive shutdown, a $50 million downtime over the course of a two-year cycle. We came in with PCMS, risk-based what was going on, how they did the testing, assessing the risk. For a $500,000 charge, $500,000, we were able to save 10% of that activity for the customer, 10% of the $50 million, that's a $5 million savings. That's a 10-for-1 payback simply in year one, and that benefit's gonna accrue to the customer going forward, year after year. You might say, "Well, Ed, why are you doing that? Aren't you doing some of that work yourself in that turnaround?
Aren't you cannibalizing some of your own labor model there?" Well, yeah, I might be doing that, and that's okay because I'll pick up other work there, maybe light mechanical work, maybe I'll calibrate a sensor and do some other value-add work there. The industry will be disrupted, is being disrupted. I'd rather cause that disruption, in a way, versus be exposed to that from the competition or somebody else. So real value here adds to meaningful cost savings for the customer. It's a win-win, though. For me, there's higher margins here on the data side, obviously, but it creates that barrier to entry and that robust relationship with, you know, with the customer.
The left example, or right example on the right there, I won't go through that one, but very similarly, an example leading to lots of, you know, work being avoided down the road that would've been adverse CapEx. Premature CapEx wear can be avoided with this data analysis up front, seeing things earlier on, and taking, you know, an action in advance goes a long way. So with that, I think we're about halfway through time. I will stop right there and throw it back to Mark, and leave a little time for some questions here. Mark, back to you.
Thank you, Ed. So the first question I have is, in terms of what is your marketing and sales strategy to penetrate existing markets and also expanding into new markets?
Great, great question, Mark. Yeah, we... A couple of things. One thing we did was we started a new commercial function last year around this time, that's had a good year of runtime now, to really lever up with customers, to ladder up, to manage relationships on a broader sense. That, that's a huge way, that we've had a lot of gains. We've had very good, good organic growth since, that time last year, and it's really comes down to understanding your customer. We have long-term MSAs, master service agreements, that dictate much of the work, so we wanna really leverage into that, pick up additional sites of, of our current customers, where they haven't seen our service offering before.
You know, the same things that happen in these industrial sites repeat themselves in different related industries, but, you know, this non-destructive testing world, it is a big, giant data set of what you've seen before. PCMS has a lot of that data, so we really wanna leverage up and sell, again, data to our service customers, and then service to our data customers, as a real way to expand out and, you know, leverage the relationships we have. It is a relationship business, and, you know, we pride ourselves on a high level of retention, and we've been expanding into adjacent markets throughout the year to leverage what we can do in the field, what we can do in the shop.
Data kind of cuts across all of that and can really get us into a different new adjacent markets, but it really comes from the commercial presence we have, and leaning into that function, to just expand that knowledge out to other locations.
Now, revenue from North America was, I think, roughly $156 million versus $34 million for international in the second quarter. Are you making an active effort internationally, or are these just kind of an extension of your North American clients? For example, maybe a refinery, you know, that has refineries in Europe. How are you kind of positioning yourself for international versus North America?
Good question. Yeah, our home base is North America, US and Canada, and Western Europe. The markets are, yeah, there is global customers, absolutely, that we share across the globe, but generally, it's more of a localized scope of work, where the customer manages their locations on a local basis, not so much globally. But we do like Western Europe. We have been expanding. It's very similar work across the board. They're a little more shop and aerospace-centric than we are in North America, but very similar end markets, very, very similar capabilities. But again, it's a localized, you know, market in terms of how you serve. Generally, there is some uniqueness.
You know, again, we're testing infrastructure, parts are coming to us, so there is that geographical presence, and that bricks and mortar is important when it comes to the shop in the field. Again, data is more universal. Our data guys are more global. Selling a software, you know, tracking with a sensor can be in a data center, which I have in multiple locations right now across continents. That's truly a global business, hence why that one's one I can leverage and expand across the board. But yeah, we like the end markets we're in, and they're all, you know, pivotal to us. And we are moving up to go more global with our customers, but historically they've approached things on a more multinational level versus being truly global.
You know, it sounds like in terms of, you mentioned the regulatory requirements for some of your customers, you know, that those probably aren't gonna be the highest margin services. But you're really trying to differentiate yourself with all of these other products and services that you can provide, to really kind of become an extension or a part of your customer's business. Can you just talk a little bit about the revenue model in terms of recurring revenue versus ad hoc, and bundled versus unbundled?
Sure, and you're right, we are seeking to be a outsourced or co-sourced asset integrity manager with my customer. That's really why we're there. We're managing the risk of their asset base in a sort of a co-sourced relationship. We're embedded with them in a good way, managing the risk for them. And much of my work is recurring, where my technicians show up at the same account every day of the year. So that recurring piece of my business model is significant. Some of the lines are gray a little bit there, it's a little bit fuzzy, but it's probably close to 60% of my work is recurring, run and maintained at these evergreen sites, as they call them, dictated by these master service agreements.
I would put, you know, another kind of 30% of the work or so, is more what I would call call-out work, where it's much more, you know, campaign-driven. Where it's some of the same customers, but, you know, maybe they need, want something done once a year or once every second or third year. That's call-out work, a unique test happening, sort of in a vacuum on a fixed basis, but not on a recurring matter, and then the final 10% is a little more contract work, maybe it's new construction work happening. It is recurring in a way, but under a fixed period of time under a contract. Maybe that's a five or 10-year cycle, new construction build.
There's actually a fair amount of work going on there today with EV and battery, and LNG work, and new construction throughout North America, and we are bidding on and winning work there. That's also another interesting piece of our business here. But we really seek to connect at multiple points there throughout the year with our customer. Again, it's the technician showing up, it's a sensor maybe that we would leave behind to track rudimentary things. We like to be connected as frequently as we can with a customer to move the entire business to this recurring model. We've moved it up over the past, you know, three to five years, and plan to continue that, where, you know, it creates a barrier to entry, it creates retention, and it just creates more value for the customer.
The more data points we can give them, all the better. The more they can stay ahead of a condition that's propagating into a bigger problem, we see it sooner in time, and then they can take evasive measures to prevent, you know, off-cycle repairs, downtime, premature capital wear and tear. That's the value they get by having us connect with them. That's why we love this risk-based inspection, and really having that connectivity, you know, on a much more frequent basis with the customer.
How scalable is this business? In other words, I mean, you've been growing your bottom line faster than the top line, at least in the second quarter. I mean, do you have- is there a lot of R&D or expense, you know, as you enter into new industries? Or is there some transferability between industries in terms of your product offering?
Yeah, no, great question, Mark. I mean, actually, it's very scalable, and much of it is sort of repurposed. As an example, we've been on bridges for quite some time using acoustic emission, listening to the damage on a road deck, on the cable stays up top, support pylons down below. Listening to damage from afar that you can't see, and then giving the customer readouts of what that means, so they can take corrective, you know, actions. That same technology was repurposed on windmills. You know, fiberglass blades deal with similar dynamics, similar stress, and we're using AE technology there, as well as in many other, you know, applications. So it is. You know, the technology we built is tried and true, and does get repurposed. And I would say in our shop laboratories, they're infinitely scalable.
That's more of a machine hours type of proposition. Yes, there's technicians involved in my shop laboratories as well, but I can leverage up the equipment hours into second and third shifts, and really expand the number of parts coming in. That's per part, per pound, per piece, per square foot of the testing there. So that's a model that's infinitely scalable within my shop labs. In the field with a labor model, a little tougher to scale up there. I need another technician with the equipment to go in the field to do the work. So that's a little tougher to scale. But data, obviously infinitely scalable. Software licenses, once they're implemented, they're up and running, and monitoring is easy to do. A technician can monitor, you know, a significant number of assets, and we can automate some of that monitoring as well.
So that piece is infinitely scalable. So yeah, there's a little bit of CapEx on some of our shop business, but, you know, that's fairly modest. We're definitely asset light from that standpoint. So all of our, you know, technology can be repurposed, and it is, into adjacent markets. We're agnostic, we're not tied to oil and gas. We'll float into whatever end markets fuel up the energy grid going forward. And, you know, we'll migrate over time to where the market needs us to support them.
Ed, thank you so much for joining us today.
Thank you, Mark. Thank you for hosting the conference, and I appreciate your time as well, and appreciate the listeners learning a little more about the MISTRAS Group today. Thank you.
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