Vision Podcast #30 – Succeeding with Edge AI with Macnica Europe

Succeeding with Edge AI

MVPro Media – The Vision Podcast #30

Guests – Josselin Vilpoux, Director of Solutions Sales, and Sascha Zimmermann, Senior Manager of Business Development | Macnica ATD Europe

Josselin Vilpoux and Sascha Zimmermann of Macnica ATD Europe join Josh Eastburn to explore how edge AI, advanced imaging and new sensing technologies are moving from promising concepts into practical industrial applications.

In this episode, Josselin and Sascha discuss the shift from cloud-based AI towards edge processing, including the importance of real-time performance, data sovereignty and the growing need to match AI workloads with the right hardware.

The conversation also explores purpose-built AI accelerators, machine vision and image sensor technologies, predictive maintenance, event-based vision, robotics and emerging applications including drones and industrial systems. They also explain Macnica’s component-to-solution approach and why involving technology partners before a system architecture is fixed can make the journey from proof of concept to production significantly easier.

On this page:

• Podcast player
• Sponsor information
• Guest information
• Useful links
• Episode chapters
• Episode transcript

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Listen to the Episode

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About our Guests

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Useful Links

Macnica ATD Europe: macnica.eu

Sascha Zimmermann: LinkedIn profile

Josselin Vilpoux: Linkedin profile

Macnica ATD Europe: LinkedIn page

Axelera AI / Metis AI Platform: Available through Macnica ATD Europe

Ambarella: Edge AI and video processing solutions through Macnica ATD Europe

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Episode Chapters

Click onto the chapters to access the relevant sections of the transcript below.

1. From Components to Complete Solutions
How Macnica is evolving beyond component distribution to support customers from hardware selection through integration and deployment.

2. Why AI Is Moving from the Cloud to the Edge
What is driving the shift towards edge AI, from real-time performance and data sovereignty to security and the realities of deployment.

3. Matching AI Workloads to the Right Hardware
How purpose-built AI hardware can offer an alternative to general-purpose GPUs when inference performance, power consumption and cost matter.

4. Beyond Traditional Machine Vision
Exploring predictive maintenance, alternative sensing technologies and event-based vision, and where these approaches can complement conventional imaging.

5. Taking Edge AI from Proof of Concept to Production
Why early technology decisions matter when moving AI systems from demonstrations and proof of concepts towards real-world production.

“Come to us before the architecture is locked. The earlier we are into the discussion, the more we can make the workload-to-silicon match easier from POC to mass production.”

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Episode Transcript

[00:00:00.000] – Josselin Vilpoux (Macnica Europe)

When you are buying an NVIDIA GPU, you buy it because it can do several things. Once you are focusing really on the inference phase of the AI model, then you can scrap it and integrate an accelerant chip and you have performances really, really similar, but for a fraction of the cost in terms of consumption per watt. And this is where it gets very interesting. The more consuming your application is, the more interesting it gets.

[00:00:28.980] – Josh Eastburn (Host)

Welcome to the MVPRO Podcast. Today I’m joined by two guests from Macnica Europe, Josselin Vilpoux and Sascha Zimmermann. Macnica ATD Europe is the EMEA division of Macnica Holdings, an €8.5 billion global technology leader headquartered in Yokohama, Japan, delivering semiconductor distribution and engineering services across Europe, the Middle East, and Africa. Their component-to-solution approach spans machine vision, robotics, medical, industrial IoT, and embedded computing. Supporting customers from chip selection through full system implementation with a presence across France, Germany, the UK, and Northern Europe. Josselin is Director of Solutions Sales. After 5 years as a project and product manager in the French Army, he joined Macnica 3.5 years ago and now manages the company’s entire EMEA division. Sascha is Senior Manager of Business Development. He spent more than 30 years selling image sensors and imaging components, and since 2025 has led business development at at Macnica ATD Europe, focusing on growing the image sensor business and opening new vertical markets. Joss, Sascha, welcome to the show.

[00:01:33.130] – Josselin Vilpoux

Thank you.

[00:01:33.550] – Josh Eastburn

So maybe you can tell me about a machine vision project or a wow moment that has really stuck with you, right, that you still remember when you think of machine vision.

[00:01:43.230] – Sascha Zimmermann (Macnica Europe)

In the past, after 30 years of this business, there were many stories and I’ve seen many small companies growing enormously. One example is a camera manufacturing in the northern part of Germany. When I met those guys first time, I think in ’94, there were just a few people at the time. We sold them CCD sensors and it was a very small company. No one knew where it was going to. And I saw it a few years ago, it was one of the biggest ones in Europe and still they are. So this business and this market is still very interesting. There are many things that still don’t see. 30 years ago, there was the saying, okay, in 10 years, the market for image sensors will be saturated. 20 years ago, and it’s still not. And we see so many new applications now in robotics. So this is amazing. It’s not a particular example, but this is how I see looking 30 years ago and now. It’s still very exciting market.

[00:02:37.190] – Josh Eastburn

Yeah, I agree. Joss, anything coming to mind for you?

[00:02:40.240] – Josselin Vilpoux

I will take something very specific and quite recent. Something that stuck with my mind recently was Deployment of one of our solutions that we are supporting called Icetana. It’s a video analytics AI-based solution, basically just identifying unusual behavior in CCTV networks and pulling the feed real-time in the security operation room. Something happened at one of our customers’ place, 25th of December. This is why it’s stuck in my mind because it was Christmas Day. And we saw someone break in throughout the CCTV network. You could see the person approaching the mall, breaking in, and getting away with just the trash. But still, it stuck, and I was impressed on how we could follow the journey, so to speak, of the person within the video stream. That was crazy.

[00:03:33.910] – Sascha Zimmermann

Yeah.

[00:03:34.320] – Josh Eastburn

Well, okay, that’s a different application than we’ve had before too. CCTV. Interesting. So maybe that leads into a question then about what does Macnica do, let’s say in one sentence.

[00:03:43.610] – Sascha Zimmermann

I think one of the DNA from Macnica in Europe is the image processing. So we provide imaging components. This is what we did for many years already. And now we’re adding more and more services and solutions which fit into customer demands and customer needs. And so we’re not trying only to be a hardware provider or supplier, more want to provide part of ecosystems and also the engineering, the solutions. So software is getting more and more important, and if you wanna survive in the future, you need to be able to provide more out of the ecosystem than just a component, a hardware. And on top, of course, we have our components and solutions that fits very well into this imaging market. And of course, beside, we have the technology solutions business. I think that Joss can say A little bit about it?

[00:04:34.640] – Josselin Vilpoux

You, you ask one sentence, I will describe it in very few words.

[00:04:38.690] – Josh Eastburn

Sure.

[00:04:38.930] – Josselin Vilpoux

If we want to capture in an essence what is Macnica Europe is about, we are a solution provider, right? Usually what I say is that where most distributors stop at catalog supply, right? So you give a part number and then distributor is shipping the product. Our component-to-solution approach really means that we stay through design-in firmware, software integration, some cases turnkey manufacturing, right? So the whole point is to let the customer know that it’s not about us disappearing from the moment they receive the components on their desk, right? But we’re gonna walk with them through all the process from hardware selection until the full deployment of the solution they’re looking for.

[00:05:23.650] – Josselin Vilpoux

Hmm. And you’re part of a larger network, right? So there’s Macnica in Americas, the company’s headquartered in Japan. How does that structure change what you’re able to offer to your customers in Europe?

[00:05:36.820] – Josselin Vilpoux

Yeah, so we see where we see the really the value lying in is, is not really on which region is bringing what to another region. In practice, we are using this platform or this Atlantic approach as a way of accelerating our partnership relationship management. So whoever has built the stronger relationship with a given supplier, we’re gonna leverage that and be able to replicate it in another region. So for example, Sasha is, is much more knowledgeable than me about that, but we have a long-lasting relationship with Sony, uh, right? Thanks to this long and, and, and trusted relationship that we have with Sony here in Europe. We managed to extend that relationship to Macnica US and we enabled them to meet Sony high-end supply chain requirements. So it’s, it’s really not a, a one-way street. It’s really whoever has a, a competitive advantage, let’s call it that way, with a specific supplier, global suppliers, we use this relationship, we harness it to another region and we make it a win over there as well. It’s really cross-collaboration approach, right? That’s, that’s the whole—

[00:06:50.020] – Josh Eastburn

Yeah. And then, so I guess the point here too is that you’re working with global companies, right? And you have a presence where they are as well, wherever they are in the world. Yeah.

[00:06:57.780] – Speaker 4

Yeah.

[00:06:57.890] – Josh Eastburn

Sascha, do you want to add anything to that?

[00:07:01.190] – Sascha Zimmermann

No, I think it is absolutely what you’re saying. And we have many examples in both directions and we’re getting partners and suppliers that is coming from North America or the link is coming from North America, just as an example in WiseBrews. So I think the network within Macnica is very good and very strong, so it allows a lot of cross-selling options.

[00:07:20.280] – Josh Eastburn

How do you decide which suppliers become part of your catalog and are there particular trends that you’re seeing across vision or AI or sensing to help to shape some of those decisions?

[00:07:33.690] – Josselin Vilpoux

So, the first thing first, we make sure that these partners are global enough., right? They don’t need to be mega corporation or to have established offices in every single countries of the world, but because we are adopting this quite large regional approach, what we want to make sure is that our suppliers are able to follow up with the pace, right?

[00:07:56.910] – Josh Eastburn

Mm-hmm.

[00:07:56.930] – Josselin Vilpoux

So that will be the first requirement. And then definitely, at least on the AI side of things, we see quite a strong trend right now from, from cloud to edge AI. So we definitely shape our partnership strategy around this kind of big movements that we are witnessing currently.

[00:08:16.140] – Josh Eastburn

Sascha, what does that look like on the business development side? What kinds of requests do you hear people coming to Macnica with?

[00:08:24.620] – Sascha Zimmermann

This is a good point because from the business development side, we need to listen very strong to what the market is asking for. What is the customer asking for at the end of the day? So this is also part of, according to me, partner network would be which partner to add or not, which technology. It should be according to the market needs and each territory, of course, it’s slightly different. So we see slightly different customer and market behavior in North America than in Europe. There are a lot of similarities and I think you need to listen to the market and this is why business development is traveling a lot, visiting a lot, and trying to get a very good overview on what is going on in the market. Because this helps to decide on the partner network.

[00:09:04.580] – Sascha Zimmermann

Joss already mentioned we have a strong demand on the edge AI. So from a web-based or cloud-based to edge AI, and then also we see a lot in the robotics. And if we go a little bit deeper, at the moment we have a lot of requests on the drone market, civil drones, but also drones for industrial, and last but not least, also drones for defense.

[00:09:27.660] – Josselin Vilpoux

Sure.

[00:09:28.460] – Sascha Zimmermann

This is a very strong market and we see a lot of demand here.

[00:09:32.150] – Josh Eastburn

Yeah, that’s a pattern that I’ve heard from other guests as well. I think world conditions kind of explain that to some degree, but I’m interested to dive into what you both have mentioned now about the different forms of AI that you’re seeing applied in the field. I think especially the shift we’re seeing from cloud-dependent AI to edge-based AI, what do you think is driving that shift?

[00:09:54.180] – Josselin Vilpoux

Yeah, so there are a lot of things going on and obviously customers are sensitive to different topics, but if we should isolate or identify trends or big things, I think that requirements cloud compared to edge is a big point because when it’s almost impossible as of now, maybe the situation will be different in a couple of years, but as of now, having real-time detection while you run your solution in the cloud is very, very challenging. At the moment. So this is where we see quite a strong advantage on the edge side of things. Without getting too political, data sovereignty pressure is definitely a key topic. We have European-based suppliers in our portfolio and we see, especially in the defense industry, as you can imagine, we see it as a concrete criteria the customer will raise very early in the discussion, which is something quite recent, not completely new, but also inference cost and practicality is also something like we’ve been talking a lot about AI inference for a while. Now what we see is what happens beyond testing things in a lab and deploying into the fields. And this is where you can have a real gap sometimes between what some suppliers can claim and the field reality.

[00:11:15.930] – Josselin Vilpoux

So this is also something customers are very eager to tackle quite quickly is how benchmarks and claimed performances are compared, or at least how they crystallize themselves in a real environment, which is not ideal lab-based.

[00:11:32.540] – Josh Eastburn

Sasha, do you have anything you want to add to that? I think that’s an interesting point. Just, I mean, obviously we’re all familiar with that of like, hey, I ordered this, it said it was going to do this, and this is actually what I got instead, right?

[00:11:44.630] – Sascha Zimmermann

The edge AI is a reason why people come to Matnica and we have, especially in Germany, but I guess France is similar and maybe in all of Europe is that we were a little bit hesitating on the AI because of security reasons and safety reasons. But with the edge AI, I think this makes things easier and especially in countries like Germany, it gives more trust and confidence to people to use also this technology. And this is where we see then. Customers and potential customers are interested.

[00:12:13.220] – Josh Eastburn

Why do you say especially Germany?

[00:12:17.180] – Sascha Zimmermann

I think Germany has always had— Germans always want to be confident about what they’re doing. So they want to ensure that what they’re doing is the right way. They want to be ensured that there is— they’re secure. And this is why AI was— many countries were already using ChatGPT quite a while when Germans were saying, no, I don’t want to use it. And because there’s always kind of this because it’s going to the cloud, no one knows what’s happening with this information. And in the industry, it’s even more tough. And knowing that you have an edge AI that gives the kind of security to use the technology, but also to have a certain kind of security at the same time.

[00:12:53.070] – Josh Eastburn

Mm-hmm.So they’re not as eager as Americans are to sell their identities online, huh? That’s a problem here.

[00:12:59.590] – Sascha Zimmermann

Maybe.

[00:13:01.740] – Josh Eastburn

Is there one particular partner or product in your catalog right now that you are especially excited about? Any particular technology you’re bringing to market that you like or that you feel like is getting a lot of attention?

[00:13:15.010] – Sascha Zimmermann

I think we have two of them. I’ll talk about one of them, which is Amberella They’re in AI since quite a while, and the advantage is that they’re offering edge AI also since a while, where at the beginning maybe it was quite difficult to find customers for I’d say more difficult to find customers, but now as the industry is looking at this technology, we have a lot of products that we are introducing to the market. We see a lot of demand, especially in the last 6 months. The inquiries we get from Amberella products is really increasing. And there are also a lot of new products that are high-end, especially from iENSO, the N1-655, which is really incredibly performant. And this really suits this technology perfectly. They are both American-based and they are in the market for many, many years, very well known for high-quality video SoCs. Adding AI to this makes it so interesting, and we’re seeing really a lot of demand at the moment for this in different kind of technology. Comes from even in the embedded market, also even in robotics. It’s interesting because you can add so much functionality and options due to the AI.

[00:14:22.830] – Sascha Zimmermann

We have also another one, which is because Ambarella is actually a system-on-chip, especially for video, or let’s say tailor-made for video. They also have a bit of what is their core business, but we also have a very good AI engine. I think Josselin knows much more about Synthetan than me.

[00:14:43.060] – Josselin Vilpoux

Yeah.

[00:14:43.250] – Josh Eastburn

Yeah.

[00:14:43.640] – Josselin Vilpoux

I guess Sascha, you’re referring to Axelera right?

[00:14:46.470] – Sascha Zimmermann

Yes, of course.

[00:14:47.130] – Josselin Vilpoux

Yeah. So that’s funny because thinking exactly the same answer than Sasha when you ask like, what are you excited about? And so on. We have a very interesting split in our portfolio. And what is really good is that both Amberella and Accelera, they don’t compete on the same axis. Where I see Axelera  shining with their product called Metis. So it comes in different form factors. So we have M.2 PCIes and it’s inference chips or NPUs as we call them nowadays. Axelera is calling them AI PU. You get the idea. Right. I see really Axelera, it is shining is on classical vision with, let’s say, high stream density per watt. So this is really where the product takes off. And yeah, it’s really a trend right now because when you buy a standard GPU, you buy it for flexibility, correct? When you are buying an NVIDIA GPU, you buy it because it can do several things. Once you are focusing really on the inference phase of the AI model, then you can scrap it and integrate an Axelera chip and you have performances really, really similar, but for a fraction of the cost in terms of consumption per watt.

[00:15:57.450] – Josselin Vilpoux

And this is where it gets very interesting. The more consuming your application is, the more interesting it gets. So yes, it’s quite a recent product and recent partnership that we established with Axelera AI, but one we are really excited about and really proud of being one of their trusted distributors.

[00:16:15.670] – Josh Eastburn

Excellent. So you work with the chip makers to help design or to create these kinds of purpose-built chipsets?

[00:16:23.830] – Josselin Vilpoux

Absolutely. And this is also through these kind of lines, this is also where we can really apply our mantra from components to solution because, Excelera is basically hardware. It’s a chip, right? An NPU. But you can’t just go to customers and say like, okay, You are running AI models, correct? Yes. So you are in the inference phase? Okay. Of course not. You need to understand the use case. You need to walk them through the pipeline. Sometimes you also need to help them moving from the NVIDIA environment to Excelera’s one, and it’s much easier than what customers first anticipate. So this is really where we can apply our components-to-solution approach and this is also where we see customers being the most satisfied working with us. It’s because we are able to walk with them throughout the journey and not just shipping boxes.

[00:17:16.860] – Josh Eastburn

Can you think of an example of a type of application where the difference between what’s now become your sort of standard NVIDIA GPU and Excelera NPU, where that difference really shines or is noticeable?

[00:17:29.760] – Josselin Vilpoux

There is like so many use cases possible. So I will not take a typical one. I will take a—

[00:17:35.370] – Josh Eastburn

Sure.

[00:17:35.850] – Josselin Vilpoux

One that we don’t really think of. We are working with this company and they are specialized in industrial printing. So they print very, very large images on big printers machines. So definitely not the kind of printer you will find at the corner if you go down in your street and looking for some papers to print, absolutely not. And they have a need for AI models running on these printers. The issue is that standard GPUs either don’t match their requests or are too expensive to integrate and to run because it’s, as I mentioned, the consumption per watt is, is where Excelera really shines. So in this case, we started discussion 2 years ago and we are seeing this project coming to life. So it’s also really exciting when you start a discussion a few years back to see it taking shape eventually.

[00:18:32.240] – Josh Eastburn

Yeah.

[00:18:32.540] – Josselin Vilpoux

Industrial printing, absolutely not something in my radar 2 years ago, but yeah. Yeah.

[00:18:38.070] – Josh Eastburn

And so we’ve kind of been talking a lot about vision in different forms, but that’s not the only part of Macnica’s catalog, right? So what are some other modes of sensing that are becoming essential and what does Macnica have going in that space as well? Maybe that’s a good question for you, Sascha. What kinds of conversations are you having outside of maybe what we consider classical machine vision?

[00:19:04.140] – Sascha Zimmermann

You know, my expertise is like 30 years in imaging and, um, but maybe it’s real.

[00:19:09.190] – Josselin Vilpoux

Yes.

[00:19:09.530] – Josh Eastburn

Okay.

[00:19:09.680] – Sascha Zimmermann

I don’t know what it is. So, you know, you can use it for motors to measure tension and to measure torque.

[00:19:16.300] – Josselin Vilpoux

Gauge and torque. Yeah.

[00:19:17.670] – Sascha Zimmermann

Like, yeah, Brose and Bosch can use this also for the e-bikes. Electric bike can be very useful, but also if you wanna measure tension on any metals or for example in turbines of, should also be suitable for plane turbines to measure the tension on the metal that’s appearing. This is what I can say and it’s a pretty new technology that kind of allows predictive maintenance. So you can analyze a machine, a tool, an engine, if there is any unusual tension or friction to a material. That allows to maybe change something in the setting before something gets damaged, especially on high-priced material like engines and turbines and whatever. But I’m not really the specialist to go into details.

[00:20:01.010] – Josh Eastburn

That was a pretty good description for somebody who says they’re not too familiar with it. Joss, do you want to add anything to that, or are you pretty happy with that?

[00:20:08.090] – Josselin Vilpoux

No, I think it’s a good one. We can elaborate also very quickly on ADI OtoSense™, which is not exactly addressing the same market than STREAL. So STREAL is really, as Sascha mentioned, for robotics and e-bikes. That’s the two main focus. ADI SmartMotor Otosense™ is smart sensor for predictive maintenance of motors, most specifically single load motors running 24/7. So with this sensor, we are enabling maintenance team to have a precise view on the overall health of their critical assets. Critical motors running into factories. Where we see the real value of this sensor is when we are addressing food and beverage industry or paper industry, wherever you have a motor running 24/7 and you can’t afford this motor to break down. This is where this sensor comes to play.

[00:20:59.900] – Josh Eastburn

Are you seeing, Sascha, are you seeing any interesting crossover between these different modes of sensing? Are you seeing projects that combine these? I know that’s something that’s come up for robotics in the past, for example, right? But yeah, let me answer that for you.

[00:21:13.920] – Sascha Zimmermann

There is a very interesting technology that Sony launched a few years ago, which is the event-based sensors, which is very interesting also for different kinds of applications. And it can combine machine vision and predictive maintenance because with these event-based sensors, you only actually capture and measure the difference pictures from one to the other pictures. You don’t have a moving picture where you see like here now this video. You would just see changes in a picture. So for example, if you would, for an object that is moving on, has vibration, then the standard vibration, you would just not see it. But if there’s any change in the standard, this would, you would immediately, would immediately see there is an unusual vibration or movement, and you can also see where it is, which of course can somehow combine predictive maintenance and machine vision. Um, it’s a very particular technology. That is now also apparently very interesting for avionics, so for drones, because you can see things. So especially also on the security side, if you are monitoring something from the air and you could see on the ground, for example, you won’t see any moving objects, but if something is moving, you will immediately see, okay, something is moving.

[00:22:33.460] – Sascha Zimmermann

And nowadays you can calibrate drones that they are not moving. They will be able to calculate this. And this is also an application where you kind of mix both technologies, even for a security, is not predictive maintenance, but also is hard. Maybe it is predictive maintenance, I don’t know.

[00:22:48.710] – Josh Eastburn

Yeah, it’s a type of analytics. I’m wondering what the output of that looks like if it’s not a traditional image. How is that delta expressed?

[00:22:59.700] – Sascha Zimmermann

You would just see it’s a black screen and you would So for example, if my head would move like this, you would just see the pixels that moved. So it’s more a meta picture, a real picture that you will see like here. So it’s more a meta picture where you would just see the pixel information of the pixels that have really been affected due to the movement.

[00:23:20.650] – Josh Eastburn

Yeah, that would be really interesting. That’s a tricky part of a podcast. It’s only audio, so hard to describe visual things sometimes for an imaging podcast.

[00:23:29.390] – Sascha Zimmermann

And if you have those spots, you can of course also do measurement with that because if you go from one spot to the other, you have an optics and then you can merely say, okay, this object moves by, I don’t know, 1 millimeter, which would also allow a 3D measurement. Not exactly, but you could simulate the kind of 3D vision.

[00:23:48.700] – Josh Eastburn

Oh, okay.

[00:23:49.420] – Sascha Zimmermann

Yeah.

[00:23:49.970] – Josh Eastburn

And I guess how does that, what’s the benefit to doing it with this approach versus the traditional approach? I think you mentioned. Maybe there are some applications that wouldn’t be detectable by traditional methods.

[00:24:02.390] – Sascha Zimmermann

You only need one system because you only need one camera with one processor and that’s it. Because normally if you do 3D, you need more sources and more equipment. You need a second camera, then you need different kind of illumination. You see, you need only one ecosystem to make this analysis.

[00:24:19.740] – Josh Eastburn

Mm-hmm. Mm-hmm. Mm-hmm. Okay.

[00:24:21.460] – Sascha Zimmermann

So it kind of facilitates this technology. And in the past, if we look at 20 years ago, there was a trend of only analyzing changes in a picture, but this was very complex and it required a lot of computer processing to do that. And now this kind of sensor, you don’t need a lot of computer processing because you just analyze a few bits of a picture. So it’s very fast and you don’t need a lot of processing.

[00:24:45.950] – Josh Eastburn

Okay, that was a great answer. We’ve talked about already a pretty diverse array of different types of applications and technologies that Macnica is working with on a day-to-day basis. Looking ahead, where middle of 2026 and probably into 2027. So as you think about the next year, what’s coming that we might look out for?

[00:25:04.610] – Josselin Vilpoux

So I will say like, let’s call it more of the same discipline. So going deeper into fewer technologies instead of spreading thin across every new accelerators here and there. So my message to the world outside will be more like, come to us before the architecture is locked. That will be the key message. The earlier we are into the discussion and the more we can take the workload-to-silicon match easier from POC to mass production, right? So always the key thing when we are trying to move from a demo environment to something that runs in the real world. That will be my key message here.

[00:25:49.190] – Josh Eastburn

What’s the best way to get started? With Macnica, where should they find you and how do they get your help?

[00:25:54.990] – Josselin Vilpoux

We are everywhere, but you just type Macnica Europe in Google or on LinkedIn and you will find us for sure.

[00:26:00.620] – Josh Eastburn

All over the place. I know Vision Stuttgart is coming up, the big trade show in Europe. Will Macnica be there?

[00:26:09.120] – Sascha Zimmermann

Yes, of course. We’ll have a booth there as usual and we will be showing off our current and new technologies and also We’re going to show a little bit more kind of examples what is feasible with our tech boundaries. And I think it’ll be again, a very exciting show. We’ll have key players down because trailers will be shown more in value. Of course, Pika will be there also.

[00:26:33.340] – Josh Eastburn

You both have been great. I hope you feel like that was a good conversation. We got into a lot of different topics, which I hope expresses what’s Macnica’s capable of. I think that’s certainly a goal here. To help people understand all the different types of problems that you’re able to solve. Thank you for your time. I’ll let you guys go. Thank you.

[00:26:50.920] – Josselin Vilpoux

Great. Thank you very much, Josh.

[00:26:52.370] – Sascha Zimmermann

Very interesting.

[00:26:53.330] – Josh Eastburn

Okay.

[00:26:53.440] – Sascha Zimmermann

And good luck. Great. Thank you.

[00:26:56.260] – Josh Eastburn

That was Josselin Vilpoux and Sascha Zimmermann of Macnica Europe. Look out for Macnica at the Vision trade show next month and check out the show notes for links to all the products mentioned in the show today. If you have a game-changing product, technology, or service to share with the industry, Please find me on LinkedIn or contact me at josh.eastburn@mvpromedia.com. And for all the latest machine vision news, head over to mvpromedia.com and click subscribe. This episode was produced by Big Robo. For MVPro Media, I’m Josh Eastburn. Be well.