Cognex at 2025 Cantor Fitzgerald Conference: AI Drives Growth

On Wednesday, 12 March 2025, Cognex Corporation (NASDAQ: CGNX) presented at the 2025 Cantor Fitzgerald Global Technology Conference. The company outlined its strategic focus on machine vision technology, emphasizing both its growth opportunities and challenges. While Cognex has seen a return to growth, it faces mixed prospects in different market sectors.

Key Takeaways

• Cognex achieved 9% overall growth in 2024, with 1% organic growth.
• The company is investing heavily in AI, with all new products featuring AI components.
• Logistics emerged as a key growth area, contributing 23% of revenue in 2024.
• The automotive sector declined by 14% in 2024, with muted expectations for 2025.
• Cognex is expanding its sales force to target a broader customer base.

Financial Results

• 2024 Performance:

- Achieved 9% year-over-year growth.

- Reported 70% gross margins and 17% adjusted EBITDA margins.

• Market Growth:

- Overall market historically grew at 10-11%.

- Logistics market expected to grow at mid-single digits, with automation and AI potentially adding 10 percentage points.

Operational Updates

• AI Integration:

- All new products in the past 18 months include AI components.

- Focus on deep learning for complex problems and edge learning for localized tasks.

• Sales Force Expansion:

- $23 million invested in 2024, following $28 million in 2023.

- Targeting expansion beyond the top 10% of the market.

Future Outlook

• Market Growth Expectations:

- Anticipates 10-11% overall market growth driven by automation and AI.

- Strong growth in logistics expected to continue in 2025.

• Automotive Sector:

- Continued uncertainty with muted expectations for 2025.

• Semiconductor Sector:

- Strong investment driven by high-bandwidth memory chips and hyperscaler CapEx.

Q&A Highlights

• Competitive Landscape:

- Keyence and SICK are major competitors in factory and logistics automation, respectively.

- Cognex focuses on maintaining technological leadership.

• RFID Competition:

- RFID seen as complementary, not a significant threat.

• 3D Applications:

- Cognex offers AI-enabled 3D machine vision systems, primarily for automotive.

Cognex Corporation’s detailed presentation at the conference highlighted its strategic initiatives and market positioning. For more insights, refer to the full transcript below.

Full transcript - 2025 Cantor Fitzgerald Global Technology Conference:

Troy Jensen, Managing Director, Kantor, Volcan Industrial Tech: All right. Thanks, everybody, for making it. My name is Troy Jensen. I’m Managing Director at Kantor, Volcan Industrial Tech. I recently picked up Cognex.

We’re lucky enough to have Dennis Fier here, the CFO of Cognex. So Dennis, why don’t you just quick start with a background of yourself, and then we’ll kind of open it up and kind of get into a presentation you delivered here.

Dennis Fehr, Chief Financial Officer, Cognex: Yeah. No. Happy to. Good morning, everyone. My name is Dennis Fehr, Chief Financial Officer of Cognex.

I’ve been with the firm for about a year. Worked very long at Siemens originally from Germany, came to The U. S. In 2018 when we spend out a company called Fluence Energy, scaled that, took it public and then had a shorter time at a private company in Boston time. So I’m here.

I will share a bit about Cognex, what we are doing before going into the details. Just quick reminder, may do some forward looking statements that you don’t put undue reliance on such statements. Please, actual results may differ and please consult our latest 10 ks in Q before investing. Who is Cognex? So we are a tech company based out of the Boston area, the town of Natick.

While we ship, let’s say, software embedded on devices, we really see ourselves as a software company, as a true tech leader in the space and that’s also kind of the margins which we command with gross margins in the 70% range and then highly attractive operating margin and leverage. What we do is machine vision. So in other words, we sometimes say is we give machines eyes, but we also give it the brain. Maybe that’s even more important. And it means it’s all about first taking an image, but then it’s all about processing that image.

And we do that in a factory and the warehouse environment. So typically in line manufacturing or in line processing in warehouses and that includes guiding like robotic arm guiding that includes identification that means reading of parts or letters, optical characters on parts or barcode reading. We do gauging, measurements, quality inspections type of things. And what we what we can help with this is basically that there are a lot of workers out there who do these tasks manually still today and we basically can support giving them more meaningful tasks and focusing on other things. As a company, basically, we are riding on, I would say, three megatrends.

I would say one of the oldest megatrends is probably since Henry Ford created assembly line. And since then, engineers have been trying to drive more efficiency and more throughput and better, faster, higher. And that’s what we are there for. But then certainly over the last maybe decade or so there has been also another topic coming into the equation which is demographics that basically there are not so many labor availability out there who want to do such tasks, right? Because at the end, it’s like a task.

Maybe you look at the same thing for eight hours and that’s probably, especially in a developed world, people don’t really want to do that. And then I would say probably since the last maybe five to eight years or maybe since the first Trump administration and certainly much more pronounced also recently near shoring, reshoring has become also a trend which drives basically Cognex demand side. We serve an 8,000,000,000 market. There’s like what we define as like a $6,500,000,000 core vision market, which is like areas like in logistics. So think about like e commerce, distributions, warehouses, certainly then the second largest market is in the automotive space, whereas electronics, so think about manufacturing of all kind of electronics devices and then other areas from medical, fast moving consumer goods as well.

We have entered some adjacencies over the last couple of years like vision sensors that was like organic and then also the optics where we did an acquisition about two years ago. In our more than forty years history, we have a strong growth pattern, so especially from 2011 to 2021 about 14% CAGR Have then seen, especially during the pandemic, quite heavy investment and a bit of a post pandemic slowdown. So I’ve seen the top line going down from 2021 to 2023, but we have returned to growth in 2024 largely driven by inorganic while basically on an organic basis more like started to bottom out and being rather flattish in that year. We work with the most sophisticated customers and let’s say solving the most sophisticated problems in machine vision that’s where we really our core DNA is as a company. So we deliver the highest performance and the solving the most complex problems.

That’s kind of where we originate, but over the last couple of years, we have been also moving into what we call an easy to use and easy to deploy space that has been enabled by some of advancements on the AI side which I will talk about in a minute or so just to broaden our customer base and basically serving also a broader part of the market. As just mentioned, AI is a key theme for Cognex. So we have been embracing AI very early on when a lot of people have not even been talking about AI. So we made an acquisition in 2018. We bought a Swiss company called Vidhi who had kind of an inherit or started to do AI models for machine vision specifically and then we have launched our first AI based product in 2022.

And I would say over the last eighteen months or so every new product which we have been launching has an AI component to it. So there is no machine vision product anymore which we’re launching without AI. And then within the AI, we will have two areas. We call it deep learning. So think about vision software which sits on the cloud, high compute power addressing the most difficult problems to be solved, but we also have what we call edge learning.

That means it’s really a pre trained model which sits on an individual device, is not cloud connected and uses basically the power of that chip in that device and basically has very high speed, high latency and can address some of the, let’s say, kind of medium range problems kind of in terms of difficulty to solve issues. We’ll probably talk a little bit more about the AI space in a bit. To bring some of these products especially the ease of use products to the market, we have worked over the last two years to transform and expand our sales force. So that means we have traditionally have been had a very highly technical and highly consultative selling approach, but we brought on an additional type of sales engineers more like graduate students who are transactional focused and kind of selling these easy to use products. And then lastly or before coming here to the end, we have a very unique culture as Cognex.

So I think within my my close to one year in in Cognix, I’ve been dressing up several times as different characters of different stories and kind of had a lot of fun with our Cognoids as we call them. And if we don’t work hard or play hard, you may see a lot of our Cognoids running around on a turf field in front of our office and playing Ultimate Frisbee. So in that regard, having a nice culture here. And then last but not least, while we certainly will talk more about Cognex in the next twenty five minutes or so, we have an Investor Day coming up on June. So if you would like to learn more about the company, please do visit us.

Thank you.

Troy Jensen, Managing Director, Kantor, Volcan Industrial Tech: Awesome. If you guys could actually keep that up, a couple of my questions are actually addressed in some of your presentations. So I’d love to start with that, the $8,000,000 market served,

Unidentified speaker: if you

Unidentified speaker: want to

Troy Jensen, Managing Director, Kantor, Volcan Industrial Tech: go back to that slide. All right. So 2024 was a good year for Cognex despite the market conditions. You guys grew 9% year over year, about 1% organically if you exclude MoraTechs. Yes.

70% gross margins, 17% adjusted EBITDA margins. So I’d just love to hear your thoughts about the market growth rates for machine learning and how penetrated this market and conveniently got that all displayed right here for us.

Dennis Fehr, Chief Financial Officer, Cognex: Right. So, yes, no, I think as I mentioned initially, I think it’s a highly attractive market in that sense from a traditional growth rate, right? So on the one side or maybe let’s maybe start historically, right? Historically, we have seen the market growing somewhere in like low teens 10% to 11%. And if you look at external analysis just like Interact analysis or others are out there, they’re basically also projecting that forward.

Now you may think like, okay, where is that 10% to 11% market growth coming from? So first of all, there’s typically like an underlying secular market growth. Think about maybe start with logistics, right? Logistics market may grow whatever 6%, five % to 6% somewhere in the mid single digits. But then basically there is kind of that additional automation and AI driven vision penetration in these markets.

As we bring in more AI into machine vision, we basically can solve problems which haven’t been able to be solved in the past without these AI algorithms. And that basically enables additional use cases and therefore drives adoption. And then that, for example, on a logistics market, we would say like while the logistics market itself maybe grows this mid single digits that can add really up to 10 percentage points or somewhere in the mid teens we would expect like a logistics market to grow. So logistics is overall the market we think will grow the fast, which today is one of the least penetrated from an automation and machine vision area. And then we have other markets which may not grow as fast, for example, automotive, right?

We are not very, let’s say, bullish in terms of underlying automotive growth, but you will also have some level of additional automation and machine vision penetration there. So all in, we would see like a 10% to 11% market growth. And back to the beginning, we think we’re in a very attractive market.

Troy Jensen, Managing Director, Kantor, Volcan Industrial Tech: So Dennis, I think of you guys as the market leader in this space, right, and the fact that you guys are only kind of like 15% to 20% share, can you just talk about competition, who are the other big players that you guys see the most?

Dennis Fehr, Chief Financial Officer, Cognex: Right. So we when we talk about the competitive landscape, we basically separate between logistics and warehouse automation and factory automation. So factory automation includes automotive, electronics, medical and all the others. Right? So in that area, our largest competitor is a company called Keyence.

That’s a Japanese company running more a not a very Japanese business model, so they’re very sales coverage and let’s say sales focused, which is I would say, not so typical Japanese style. And they basically, while we traditionally serve the most sophisticated customers with the most sophisticated problems, they are more in the broader market serving basically a large breadth of the market with a very good market or sales coverage. And then on the logistics and warehouse automation, we have a company called SICK, S I C K, that’s a German privately owned company. They are also doing like safety sensors and they’re coming more from the vision sensor area where they have moved into the, let’s say, machine vision space over time and they are basically the leader in the logistics and the warehouse and logistics space and they are more than incumbent there and we are basically have been entering the logistics market probably like about ten years ago.

Troy Jensen, Managing Director, Kantor, Volcan Industrial Tech: Okay. All right. So and you hit on this a little bit too, but 70% gross margin selling cameras, barcode readers implies to me that you have a ton of software in your products. As you said, you’re a software company, but you’re launching all these AI based products. So can you just talk the what’s the difference between AI based products software versus kind of legacy products with all the software?

Dennis Fehr, Chief Financial Officer, Cognex: Yes. No, absolutely. See, I think maybe traditionally, I give you a bit of a journey of the company. So the company started really as a truly software only company. So if you go forty years back, it was software only.

So we provided machine vision software and then our customers would buy some dumb hardware connected to the software and make that work. I think as time progressed more and more customers wanted to have an integrated solution. So basically the next step for us was to embed the software into the devices and then saw like a one stop solution as a as a device. However, that was all what we call today rules based algorithms. So that means some very smart PhDs and software engineers would sit there and think like what’s the problem the customer want to solve and then write like if this then that and then in a very, let’s say, sophisticated way and certainly building a lot of domain expertise over the years.

So that means we have been the leader in this rules based software approach. But then rules based software certainly requires a lot of software engineers writing a lot of code. Right? That’s kind of what it is. Now when we move to AI, we’re basically going away from this rules based approach, but we are building models similar like maybe you think about it at GPT, right?

They’re building large models which then with the models they have created they can address certain specific or universal type of requests and question. And we are basically building very specific for the machine vision industrial and factory automation and warehouse automation specific machine vision models. And with these AI models, we can do two things. A, we can solve problems you could not solve in the past with rules based and I can give one or two examples in a minute. And then the other aspect of AI is that we can make it easier to use.

So for example, in the past, when you bought a machine vision system, when you set it up, you may need to go through some tuning steps. And you you needed to have an an industrial automation engineer to help and basically do this tuning, this initial setup of that vision system. Now we recently launched a new generation of ID readers and they have an AI auto tune. So that means you’re basically removing additional engineering time to set up device. So that means the AI also helps in terms of an easy to use and an easy to plot and deploy approach.

And maybe to have one example for, like, how does AI make it easier? I’ll give you an interesting example. I went a couple of months ago. I went to a big brand name for consumer goods. So they do a lot of different things, but I I walked the line of a simple thing like a dust sheet.

So think about like a piece of paper used to to clean. And in the past, basically, you could use machine vision to inspect to make sure the edge is cut in the right, is the shape right. So that means you basically could do some inspection task of these dust sheets, which are flying by by like 1,500 pieces a minute. Right? So that means extremely fast.

But what you could not do is like to inspect the pattern of the sheet because at the end it was white on white. It’s like can you inspect the structure? Is the sheet structurally intact? You could not do that with a rules based algorithm because it was just too complex to address. But with an AI, you can really train through pictures with good pictures, show and I hate this is good and then a couple of pictures which are bad.

So now with an AI based system, you could really identify and also inspect such kind of structural issues. And that’s kind of one of the examples where you can see that you create additional market adoption and additional use cases for machine vision if you use AI based tools.

Troy Jensen, Managing Director, Kantor, Volcan Industrial Tech: So do the AI based products have better gross margins? So if that becomes a larger percentage of your sales, would you expect to see some gross margin expansion?

Dennis Fehr, Chief Financial Officer, Cognex: I mean, we have typically already commanded very high gross margins. Right? So we think about the AI more like as an market accelerator and part of creating market growth. Right? So in that regard, when we think about our own kind of years forward and we think AI will help to get us to this 10%, eleven % market growth, but we would not necessarily think like that it’s a level for margin expansion as we’re already commanding that level as a software company.

Troy Jensen, Managing Director, Kantor, Volcan Industrial Tech: Okay. Just to stay competitive and kind of lead the competition too.

Dennis Fehr, Chief Financial Officer, Cognex: Yeah.

Troy Jensen, Managing Director, Kantor, Volcan Industrial Tech: All right. So maybe go to the new sales initiative. To me, that was pretty important for you guys. I think you had 80,000 customer visits last year, 3,000 new customers. I think the OpEx grew by $23,000,000 in $24,000,000 because of that.

You can just talk about just the sales efforts here to accelerate growth.

Dennis Fehr, Chief Financial Officer, Cognex: Right. So again, maybe first quickly back to the strategic rationale of the initiative, right. Traditionally, you have been serving customers. That has given us really being the technology leader in that space and we have a very high market share with this group of customers. But they are really sitting at the top of the pyramid and that means there’s a large market beyond that.

Right? So there are traditionally, we have been serving about maybe 25,000 to 30,000 customers, but the total market is maybe 300,000 customers. Right? So we serve maybe like top 10% of the customers. Then, however, when we see like how’s the rest of this market and we looked at companies like Kien’s for example and they are actually commanding also attractive gross margins in that business with these other customers.

So we thought like, hey, here’s a fantastic opportunity that you can expand basically into customer areas, but you’re not right. When you go from the top of the pyramid more down, you would think like you would lose margin, gross margin would come down, but you can actually see that this is not the case, right. So we saw that from competition. We saw that over the last year that actually these sales engineers going to these new customers that they are commanding actually accretive gross margins. Right?

So they are selling easy to use, easy to deploy products. They’re usually a smaller order sizes and it’s part of why we can ask for higher margins because they’re not the largest customers. But it’s a gross margin accretive business. So therefore, we really are focused on this initiative and we have invested quite some money. So you mentioned $23,000,000 and was the incremental dollar value in 2024.

So you already invested about $28,000,000 in 2023. So on total like run rate basis around $50,000,000 run rate. So it’s a significant investment for the company. And so what we are really trying to achieve is like expanding the strategic positioning of Cognex and therefore we are ready to make such investments even though we understand that it creates quite a headwind in terms of the bottom line for the time being.

Troy Jensen, Managing Director, Kantor, Volcan Industrial Tech: Okay, perfect. Just a competitive question, RFID, right, another company that follows Impinj and they’ve had a lot of success recently with logistic customers like FedEx and UPS. Were they previously using barcode scanners? Do you view RFID as a competitive risk to some of your barcode scanning?

Dennis Fehr, Chief Financial Officer, Cognex: Yes. I would say RFID, right, if you think about it, it’s probably a technology which has been around for more than a decade. So in that regard, we have seen that customers in warehouse spaces have been working with RFIDs and very often they have been working it alongside with machine vision systems. So we have not really seen that as a competitive threat in that sense that it would kind of disrupt of what we’re doing and we have also not seen that it has created like a very large market share in the overall identification space in the warehouse and logistics automation space. I would say maybe beside RFID there are other technologies maybe to mention us like for example a lidar technology, right.

So that means some of what we do with measurement for example you could also achieve with the lidar technology. So there’s some adjacency over there as well. And in that regard probably a lidar technology is much more adjacent to what we do and we actually do have on the logistics space some areas where we use some lighter technology ourselves. So there are these type of adjacent kind of technologies, but overall they are more helping with the overall solution than they are kind of competing with each other for market share or tech share.

Troy Jensen, Managing Director, Kantor, Volcan Industrial Tech: Okay. If you could go back to that $8,000,000,000 market share of two, I guess I want to kind of go through the verticals a little bit. So to start out with how about automotive, right? I mean that was a struggle for you guys and now we’re into tariffs. And can you talk about your expectations for the automotive vertical?

Dennis Fehr, Chief Financial Officer, Cognex: Yeah. I know automotive has been probably like the most difficult markets to be in in the last twelve months, maybe eighteen months, right? So traditionally or maybe not traditionally, maybe over the last three to four years automotive has actually been our largest market in terms of revenue. It was now surpassed last year by logistics and warehouse automation. We had had a very nice success there especially in 2023 also with the lot of investments into the EV battery and kind of capacity expansions into this new kind of technology.

But I think the market has seen a lot of uncertainty and a lot of challenges itself, right? So it means the transition from ICE to EV has not gone as fast as maybe many expected. It’s not stalling, right? I mean it’s still happening. I think I read some recent numbers maybe BV results whatever 8% up year over year but people may have thought it would be 30% or 40%, right?

So that means there has been a lot of overcapacity created in that area and therefore not a lot of investment is happening in the EV space. And then at the same time if you look on the eyesight, also there are not a lot of investment happening. And I think talking about specifically North America at the moment, a lot of uncertainty out there in terms of the tariffs and that doesn’t really help with good investment climate. So in that regard, automotive was our weakest market in 2024. Actually, in terms of revenue, it declined by 14% and we still have very muted expectations for 2025 as well.

Troy Jensen, Managing Director, Kantor, Volcan Industrial Tech: How about the more exciting, Marcus, logistics? And I’m assuming that includes e commerce and in semiconductors, you think the growth you’ve seen there is sustainable?

Dennis Fehr, Chief Financial Officer, Cognex: Yeah. No. We’re very positive on both logistics and the semiconductor space. So logistics, maybe first talking about what do we mean with logistics. So there’s e commerce is a big portion on that.

That can be big names like Amazon and then certainly also players like Walmart and Target. But then also think a bit more globally, companies like Shopify, Instacart, Coupang, or some of the Asian names out there. So that’s kind of an area. Then there’s really like warehouse automation, like almost each industrial company does have a warehouse and very often today they use maybe handheld barcode scanners. Something we don’t do that’s really like but like we would consider it maybe low tech, but they may also want to further automize and use what we call machine vision tunnel.

So that means really much more automated type of either incoming or outgoing identification. And then the last the last sub segment of logistics is what we call parcel and post. These are the guys like the UPS, the FedEx and the DHLs of the world. So that’s a market we have traditionally not served very much. We have been starting to entering that maybe over the last two years, but that’s more a market share gaining market, right?

So that means e commerce is a strongly growing market, whereas automation is a strongly growing market where we have been growing with the market and gaining some market share, whereas parcel and post is a very stagnant market where we rather have been focusing on winning share. And then semi. Semi has been actually our in terms of percentage base strongest growth market in 2024. Certainly in part driven that 2023 was a very down year, right? So growing off a low base.

But we have seen a lot of investments into high bandwidth memory chips and that has been driven a lot of demand for capacity expansion. And typically that’s what we see in semi that when capacity is expanding then our business is going very well there. And what we have seen so far, certainly there was the DeepSeq announcement in January and that created a lot of questions around like, hey, is that sustainable? But I think we can clearly say, yes, we see that the market is continuing. And when we looked at some of the, let’s say, hyperscalers on their announcement, what they’re talking about their CapEx, we’re not seeing any stop or any slowdown in terms of investments in the semi market.

Troy Jensen, Managing Director, Kantor, Volcan Industrial Tech: Let me just pause to see if there’s any questions from the audience. Jonathan?

Dennis Fehr, Chief Financial Officer, Cognex: Right. So logistics maybe let’s start there. So logistics as mentioned largest market for us both in market size as well as in revenue size was about 23% of our revenue in 2024. So that means about $200,000,000 or so. Has been growing very strongly in 2024.

It’s about a 20% year over year growth. And what we have said on the most recent earnings call was that we expect a similar strong growth to continue in 2025. And in general, we believe that if we think now further out like maybe three, four, five years the logistics will continue to be the most strongest market in terms of growth percentage, driven by it’s the market which has the lowest automation degree from all the markets which we have been talking about. And therefore, we are very bullish about the logistics market. Now to your second question, three d.

So three d applications you find, for example, very strongly in automotive. So you will not find a lot of three d applications in the logistics space, for example. So it’s really very strongly automotive. I would say we do have a strong three d offering. We last year launched the first three d machine vision system which is AI enabled, call it the L 38.

And certainly on three d, there have been other players as in any of these markets. Right? You can see it’s a it’s a fairly fragmented market with, Cognex having a 15% market share, whereas a lot of gray bar in in each of these markets. And then there are companies they try to enter and sometimes there are companies they try to exit, right, because they have thought that they are not very competitive in the space, right. So I mentioned Intel.

There may be other companies who we feel like may get started to wash out some of the smaller Japanese players, for example. And then Zebra has been in general trying to move from there, let’s say, warehouse logistics maybe a little bit less tech kind of into a more machine vision player and did a couple of acquisitions there like a Fotomeo, for example. And we certainly understand what they’re trying to do, but I would say it overall doesn’t change the competitive dynamics which we see in the space. We haven’t disclosed like how much we do in three d, but you could imagine that it’s a good share. I yes, we haven’t disclosed, so we typically don’t talk about product lines.

Matt? Sorry.

Unidentified speaker: Go ahead. Curious on where the intersection or your adjacency with some of the wearables that are out there that are used in a more commercial setting or smart glasses or things of that nature, is that

Dennis Fehr, Chief Financial Officer, Cognex: Right. Yeah. I would say see there are quite some adjacencies if you think about, like, using kind of image acquisition and processing. I think, you know, you mentioned wearables, for examples, but you could also go into cars, autonomous vehicles. Right?

So you have some some camera tech there. And then the latest, discussions we get is about humanoids, robots, like, would there be so there are a lot of areas where you have some some level of vision tech. I think as a company have been very much focusing on discrete manufacturing and maybe discrete logistics. So I think as we do strategic investments like in sales forces, we are right now really much focused on staying in this broader factory and logistics automation space. Would we have like the base competencies to be active in these areas?

Probably yes, but it’s at the moment not part of the strategy.

Troy Jensen, Managing Director, Kantor, Volcan Industrial Tech: Any other questions from the audience?

Dennis Fehr, Chief Financial Officer, Cognex: Right. I mean, see, we have this very high level four use cases, right? Certainly, they’re becoming much more specific when you talk on Indevo, right? We talk about guide, identify, gauge, and inspect. When you think about innovation and going to the next level, it really happens across all of these four.

Right? So take take something which a lot of people think is a very simple task, which actually it’s not. But let’s start on identify, which is either barcode reading or it is optical character recognitions in part. So when you introduce AI into that, you could, for example, think about it in a in a in a in a distribution center. You want to run parcels and you want to run them as close as you can, right, and as fast as you can.

So that means it’s sometimes very hard to read a barcode which is down here and the next parcel is just side by side. So with AI, you can do, like, enhancing. You can do accelerated finding. You can enhance the the the picture which you’ll get, and then you can do additional filtering. So in that regard, almost in each of these kind of four main categories with AI and with general innovation, you can drive additional use cases and in general come back to that objective that you can do things faster and better and with better quality and basically drive efficiency throughout a factory process or throughout a logistics distribution center.

Troy Jensen, Managing Director, Kantor, Volcan Industrial Tech: And with that, we do need to pause. We’re at the end of our time. So, Dennis, thank you so much and good luck with everything.

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