Siemens | Live from Hannover Messe 2026

Hey. Hey. Hey. Heat. Heat. N. Heat. Hey, heat. Hey, heat. Hey, hey, hey. Let's go. Hey. Hey. Hey. The rain. Grab that. Hey. Hey. Hey. Heat. Heat. Heat. Heat. Heat. Hey. Hey. Heat. Heat. Feel the best. Hey, hey, hey.

A wonderful good morning ladies and gentlemen. This is day five live from Hanover Mass Hall 27, the living room of innovation. Max and Christine are back.

Good morning. And Christine's already taken her shoes off and I'm glad you took yours off and not me because otherwise everyone in here would need a gas mask.

We wouldn't have had visitors at our booth for the whole day if it was you.

So, as a matter of fact, I'll do that now. What goes to most favorite in their daily activities? Think of new shoes. And as a matter of fact, we have this analysis tool here at our fair booth. And now I will unveil to the world that I have a flat foot on my left side. Thanks, Dad. I'm a platform Indiana on the left. Max, what would your foot sole look like?

Um, I think it just be red everywhere.

Yeah, you got the hot feet. Now I have Joseph Flynn, one of our colleagues who has been working hard and heavily here making girls happy with new shoe soles. Flynn, uh, Joseph, what are we doing here? What are we actually providing?

So, we're showing that when you have lots of products and each of them are unique, we can still manufacture those efficiently. We're telling that story with shoes here today. And what we can do is take the data from the pressure sensor and we use that to change things about the areas of this sole. Some will be softer for cushioning, some will be harder for support. And each one is unique to the person who steps on the sensor.

So we will get a very very unique sole for me very very soft and make data work for you. This is the motto of this year's fair. You still have six hours to come to Hanover. So give it a go or you watch the recordings of our presentations from the previous days where we unveil what we have to show in regards of technology and innovation. Max, what's on schedule today?

Well, we have Miki coming up in just a second, our running reporter. He's got another session today. I'll be on stage in a talk about the ERA initiative cloud edge. Quite exciting for Europe especially. So, I'll be hosting that and we have a special thing for partner country as well later on, but I'm not going to give it away. Brazil is this year's partner country and we had great presentations. We had great customer success stories on stage already. So don't miss that one. That's going to be five to 12. That's what we're going to unveil. Who's next year's partner country and what the recommendation of this year's partner country Brazil is to those who have the honor to jump in next year in regards of customer storytelling and bringing a large delegation to our fair booth?

Exactly. Should I go and make my way around the booth quickly and then hand over to Miki while you...

I'll optimize my shoe printed and then I'll have a soft and easy day at the fair with perfectly fitted shoe soles.

And then you'll get some nice blue shoes like our colleague over there. They do look exciting. We still have to get our hands on them. The hardest thing to get here. I'm going to throw my flitter boots away and I'm going to go for the perfectly individualized super cushioned shoes.

All right, we will see you later and we're going to take a short walk. This is our innovation hub. We are showing what the future of industry might look like here. Everything is going to be orchestrated by AI: entire designs, operation workflows, the whole thing for more autonomy and more flexibility. We have the shoe sole example here in the center. We have physical AI with robots and AGVs that can think and act autonomously. On the far side, that is our digital enterprise for consumer packaged goods, an end-to-end showcase showing how core technologies can help from design to the supermarket shelf. We have three exciting customer examples: Pringles, Natura, and PepsiCo. Over here is our technology deep dive with four customer islands: advanced machine engineering, smart manufacturing, electrification and buildings, and systems engineering. We have various highlights like ECGPD for switching and protecting, serious controls, industrial controls. Also integrated into the booth are our partners because we believe a collaborative approach is the only way to achieve true digital transformation. And with that, I'm going to hand it over now to our running reporter Miki.

Thank you very much Max and welcome to our last day here at Hanover. Next to me is Gamza and she's a marketing manager here at Siemens and together we are standing on a LED glass floor, right? And I want to know we have a lot of products here. What exactly are we seeing?

Good morning, Michael. Here at our exhibit, we are showcasing three new product innovations with a groundbreaking technology. The first one is our Centron ECBD, an electronic circuit protection device, now a three-phase version. The second is a SIRIUS ET200 SP starter for fully electronic motor starting with safety functions. The third is a semiconductor circuit breaker, the Centron 3QD2 for DC power distribution.

That sounds big. What are these innovations and what makes the technology special?

We combine semiconductors, microcontrollers, and intelligent algorithms to ensure super fast switching. These devices are up to 1,000 times faster than conventional devices and are super fast for short circuit protection. This is important for DC applications. There are three main reasons: DC short circuits rise extremely fast, DC has no zero crossing, and electronic loads are extremely sensitive to voltage drops. To wrap up, we have these three new innovations with semiconductor technology. If you want to learn more, come to our booth.

All right. So you've been here a couple of days as well. What's been your favorite and your impressions about the fair so far?

It's really full. It's busy. We had great talks with our customers. It's really nice to be at such a fair to get the feedback from our customers live.

We now head back to the stage. Thank you very much and back to the stage.

Thank you Miki. Thank you Gam. Great way to kick things off here. Now, up next here on the stage on our LED in the stream, we want to show you some highlights from day one when the chancellor of Germany came to our booth. So, please enjoy the show.

A video montage showing highlights from the fair, including the chancellor's visit, scenes from Brazil, and glimpses of the exhibits.

I'm on the floor here and I'm joined by Salma Khn, head of marketing for sustainable services at Siemens. Hi Salma, it's great to have you here at Hanover. So I'm going to dive straight in. When we talk about industrial business today, sustainability plays a huge role. What are you showing here under industrial sustainability services?

Hi, it's great to be here as well. For me, sustainability services help our industrial customers to stay resilient and competitive over long term. We enable them to use existing resources more efficiently, extend lifetime of assets, and reduce operating cost. Today we show three key offerings: circularity with circular repairs and spare services, retrofit and modernization services, and energy efficiency services. The exhibit behind me shows energy efficiency in action.

Amazing. It sounds really interesting. I've already had the chance to look at the circular repair services. Can you tell us a little bit more about how these services work in practice?

Let me start with circularity. The demand for natural resources is getting less, so we need to change from linear to circular economy. We help customers with refurbished and remanufactured automation products, extending lifetime with high quality and fast delivery. Retrofit and modernization upgrade automation and control systems, improving productivity while saving initial investments. Energy efficiency services provide data-driven transparency into energy resources, helping identify improvement potential, reduce carbon emissions, eliminate energy waste, and reduce operating cost while staying compliant. Examples include DCS modernization for Munich wastewater management and urban waste management in Portugal, and a steel industry customer Sitenor in Greece saved 46% more energy after an energy audit.

Yeah, if you're not sold already, I don't know what else will. Highly encourage everyone to come to 183 where you can learn about the sustainability services we have to offer. I think I'm going to hand it back to the gallery studio now. Thank you, Salma.

Thank you.

I've got Dr. Matias Opel from Siemens. He will show us what's happening today in the world out there and live. Let's move on to you. Good morning.

Good morning. Thank you for having me and it's a real pleasure to be this year at Hanover again to talk about how dreams become reality. Looking at autonomous production and industrial AI, it's fascinating. AI is almost everywhere. I'm Matias Opel and I have the privilege to lead many years to help people, organizations, and technology come to their full potential. In industrial contexts, we face headwinds: scarcity of resources, fragility in supply chains, shortage of labor. We need to be adaptable, flexible, fast, and resilient. Siemens has its own factories, like the lighthouse factory in Langan, which has the ambition to become the first AI powered autonomous factory. We drink our own champagne. To master the transformation, we need industrial AI, not just general AI. Industrial AI must be rock solid, safe, reliable. We need an industrial foundation model that understands engineering languages and modalities. We also need IT and OT convergence, software-defined automation, and collaboration. Our vision is to build an open ecosystem, partnering with companies like Nvidia and startups, via the Siemens Xcelerator platform. Data is key. We need to turn data into valuable insights. The most important moment is now. Let's shape the future together.

Thank you. I like the together. What makes that so important? What changes it for us?

What makes it so important is that the challenges we are all facing are so strong that nobody has the 100% answer. We need data centers, AI models, compute power, but also industrial domain expertise. No single company has it all. If we combine our strengths, we can build a better future together.

That's really cool. I took away from our discussion with partners that you know that was the point. It was really talking to your customers about what's working, what's not. Do you have an example with one of your customers where this is really working and flowing for you?

The example is our own factory in Langan. We walk the shop floor, identify where the highest potential is for increasing autonomy and productivity. We are also discussing this with many customers. It's not an office conversation; we go down on the shop floor, combine IT and OT, identify use cases, and implement against the biggest problems or potentials.

This is what we need. I remember walking through the gateway, it felt like stepping into a portal. That alone was impressive. What has changed the most in the last 5 years from your perspective?

The most change is the people, the mindset, the openness to adapt new technology. When we explore humanoid technology in the shop floor, workers are interested and say they would welcome help. The mindset of exploring what becomes possible and moving the envelope further out with our technology and expertise. In the AI space, the last five months or weeks have been fascinating with rapid model evolution.

If we look at the next 5 years, what do we really need to do to move the needle? What needs to be done Monday morning?

Start sharing data. Data is important to train models on industrial grade, to understand further use cases, and enrich the validity of models. It starts with the first step and leaning in on data. We all sit on our data pots, but we need to share to realize the full potential.

I love that sharing is caring. I had a great chat with you. This was very spontaneous and that's the moments we love. Matias, great having you here. Thanks for being with us.

Thank you.

With me is Miriam, one of our tour guides, and she can tell you more about what you can see in the electrification and buildings area. Miriam, thank you very much. I will hand over to you.

Okay. Thank you. Also a warm welcome from my side. My name is Miriam. I'm a business developer and during fair time I work as a tour guide. Our electrical infrastructure is under pressure. Electrification and digitalization are accelerating while we face aging assets. I'll take you on a tour. We have medium voltage switchgear, blue GIS, NX plus C, F-gas free. We have Zroek relay for monitoring and protection, and Zprotect Wii virtualized protection server. Next, the 8DJH 24 secondary distribution switchgear, smart with C bushing collecting current and voltage values. Data is collected and used in a digital monitoring system. Electrification X dashboard shows contextualized data from a solar power plant. Finally, the Sivacon low voltage switchboard with withdrawable functions, smart motor control, busbar trunking system for flexibility, and arc fault detection. I invite you to come to Hanover and check out our DC solution.

So, I'm just going to say 90%. We spend 90% of our human life in buildings. Buildings are the spaces where we live, learn, work, and heal. They are a huge lever for energy savings and reducing carbon emissions. 40% of all energy is used by buildings, and 75% of EU buildings are not energy efficient. By 2050, the world population will be 9.7 billion, with 68% in urban areas. Every building needs to operate more efficiently. Our technology enables the path from smart to human centric autonomous buildings. Autonomous buildings are intelligent and self-optimizing, powered by AI and integrated systems. They learn, prescript, and act with minimal human intervention. Performance: daily operations are self-managed, issues identified before they occur. Energy savings: data-driven systems optimize complex energy flows across assets, grids, environments. Safety and security: fire safety systems self-test, security systems recognize authorized individuals. Flexibility: spaces and operations adapt. AI is used for pattern recognition and forecasting. Digital agents orchestrate responses across building systems. I'll show you our AI-based HVAC closed loop optimization live at the booth. It combines real-time sensor data, weather forecasts, and thermal building models to calculate optimal heating and cooling in advance. Also, energy load optimization reduces overall energy costs by 15% by automatically reducing peaks and shifting loads with AI, reacting to price signals and forecasts. This results in lower energy spend, CO2 reduction, and stabilized operations. To learn more, visit our booth.

Now let's also talk about our energy load optimization live at the show here. We can show you how to reduce overall energy costs by 15% thanks to our energy load optimization. Energy costs are rising due to grid fees, volatile prices, and electrification pressure. Operations struggle to react fast enough. Renewables and electric loads increase fluctuation. Manual energy operations leave flexibility unused. With energy load optimization, we automatically reduce peaks and shift loads across the building with AI optimization, reacting in real time to price signals and forecasted data. This results in lower energy spend, cutting CO2 emissions, and stabilized operations. Our customer can flexibly manage energy demand and collaborate with the grid. If you want to learn more about human centric autonomous buildings, visit us at Hanover Messe at the booth. You can also find the Building X system on our Siemens Xcelerator platform.

Thank you. Welcome back to the floor. I'm joined by Christina Mersburgger, marketing manager for sustainable services. So, welcome Christina. We're here at the Siemens booth to talk about circular repair services and how shifting to a circular economy is no longer a nice to have, but a catalyst for business growth. Why is it important to shift to this circular economy?

Yes, thank you very much. Where the linear economy was based on the model of take, make and waste and this has served us now for more than 40 years but it's reaching its limits now. So we can see that with resources, supply chain disruptions and with the global volatility that it's really important to do more with less resources and shifting to a circular economy is not just a nice to have anymore for our customers. It's really a business opportunity.

Great. And one business opportunity is circular repair services. What are they about?

Yes. So if we take a look at our exhibit here, you can see what it looks like when we get products back from our customers. So take for example the simatic HMI panel or sinamics. So you can see the scratches, you can see that they're nonfunctioning anymore, that they are dirty. And then with the Siemens magic, our customers with circular repair premium, they get it back in a condition that is as new in performance and appearance. So this is the remanufacturing from Siemens. And what's also really great is that our customers benefit from the high quality of the original manufacturer. And this is why we also give our customers a warranty of 24 months. And there is also circular repair advance. This is the second option of our offering and this is basically about putting it back to full performance but with a more cost effective way. So also at the very high quality.

Wow. Okay. I mean it's such a great concept to bring back your products and revamp them so we're not wasting. How do our customers benefit from these services and why should they buy only from Siemens?

Yes. So they benefit basically because they extend the lifetime of their products and their machines. And they also increase their planned availability thanks to our global network of more than 160 repair centers. And what's also very best is that they save resources and costs because they shift their investments to operational expenses. And this is how they stay competitive and also gain a huge business advantage. And why should they buy from Siemens? I mean the answer is pretty clear because who could you trust more than the people who originally built the products. So you get the highest possible quality from our service experts when it comes to testing, when it comes to updates. And what's also best is that we ensure that the products come back in compliance with safety and industry standards. So, if you would like to find out more, please visit us here on the fairground at station 120 or tune in later at 1:50 p.m. when we talk with our customers, spare parts now, how we can take circularity to the next level.

Yeah, brilliant. You've summed it up really well there. So, we've got a brilliant concept and a really useful thing for all of our customers. So, as Christina said, get yourself down here if you'd like to learn a little bit more or tune into the talk later on. And with that, we're gonna hand it back to the gallery studio. Thanks, Christina.

Thank you very much.

Hi. So we are at the CPG area here with showcases and our cooperations with our partners like PepsiCo, like Pringles and Nura and many more. We have to keep it a little bit short, but Tyler, you are an industry development lead for CPG and you will tell us which role all of our products have in the industrial metaverse that Siemens is promoting and pushing and what it does to help our customers. Tell us, please.

Yeah. So, full transparency, I used to think of the industrial metaverse initially as a photorealistic environment to take pretty pictures. I then evolved my thinking to be a bit more of a collaborative engineering environment. And now I think I've really figured out it's a multifaceted collaboration environment. Yes, you typically start making engineering decisions, gaining quick consensus, doing virtual validation and commissioning, making sure that lines and optimizations are going to be appropriate, but it has such a long life cycle associated with it where you can get into maintenance planning, operator training, safety training, closing the loop and democratizing models.

So digital twins do also play a role in that. Can you please explain a little bit what they do?

Yeah, that's a great question. So, actually last week I was working on a presentation for a customer and they came to me and said, 'Please do not talk with us about how to build a digital twin. We get it. We have to make decisions on how we're going to move forward with that.' And I looked at them and I said, 'Has anybody really talked with you about how to use a digital twin?' And they kind of perked up and got excited about that. So, that's a story that I've been relaying here both with our internal leadership and with customers and it seems to be resonating quite well. We talk a lot about building these models and constructing them appropriately, but how do you actually utilize them? How do you create a closed loop system to make these engineering decisions? And that's where the digital twin really comes into play.

All right, one last question also regarding the industrial metaverse. How is Siemens supporting making it real? What are we doing there?

So, first and foremost, we're working with key partners and key customers to really bring this to life, right? So through the PepsiCo product project, we birthed the new product that was announced at CES in January, the digital twin composer. So that's one example of how we're making it easier to go from this industrial foundation of these different 3D models and geometries into the industrial metaverse, building these global scenes, making it much easier for customers to take that leap and move forward.

All right, thank you very much for the insights. If you want to learn more about what we are doing with PepsiCo here and our other customers, head over to the CPG area, talk to our colleagues like Tyler and learn more. Thank you.

How can CPG companies turn data into value and accelerate the journey from idea to consumer with maximum efficiency? Our digital enterprise expert will explain. The digital enterprise combines industrial software and automation to create a seamless data flow from design to optimize. With a digital twin, data fabric, and industrial AI, companies can achieve faster, more sustainable product design and production. Examples: Pringles used industrial AI to boost capacity by 10% without new lines. Nua reduced water and energy consumption by up to 50% with digital twin technology. PepsiCo identified 90% of issues before implementation and achieved 20% higher throughput. Siemens is leading the industrial AI revolution, providing AI built for the real world. The time to act is now. Thank you.

Thank you very much for the very tangible examples. It's not just a theory behind it, but you also showed us where we help our customers. But you also brought something else with you. Those cups, I've seen them. What are they? And how do I get one? Now, these cups are something that you can win. If you go right over there or you see it also on the screen where the digital enterprise for consumer packaged goods showcase is. If you go there, talk to our experts, get through the entire end-to-end story, you can collect some stickers and win this coffee mug. So go ahead, enjoy your time, talk to our experts, and have a good coffee time later.

Thank you very much. And that's a very good reason to go over there. Now I hand over to Max and he's going to tell us what's up next.

Thanks very much, Mickey. Great job. So, welcome to Hall 27 everybody. In case you have not yet taken a seat on our excellent stage area here, then please do so. We have many free seats for you. There's no need to stand around at the back. Come closer. We have a great talk lined up for you next. So grab a seat and enjoy the show because next up we are going to be talking about the global challenges and long-term vision of the European cloud edge initiative called Aura and our guests will share their views on the anticipated demands and expected benefits. So please welcome with me here on stage from SAP Thomas Klingbal and from Siemens Sirinel. Welcome gentlemen.

Hi. Take a seat.

Thank you for inviting me.

Hi. Thanks for having us. Take a seat.

So, gentlemen, the final day of handover. Thank you so much for joining us here on stage. Um, Thomas, you are the director of innovation enablement at SAP and Sir, you're a principal key expert for edge and cloud computing. I would like to briefly explain the Aura initiative: it drives the development of a sovereign, interoperable, secure multi-provider cloud edge continuum, with over 120 partners from 12 EU member states. It fosters open collaboration for a resilient digital infrastructure. And now, Thomas, can you explain the main challenge you wanted to address with Aura?

Yeah, the biggest challenge in cloud computing is the plethora of possibilities, but you have to adapt your software for each platform. Scaling across multiple providers is complicated. SAP has always aimed to support multiple providers, and Aura provides a reference architecture that enables workloads to run on any infrastructure and scale across them, making the cloud work better.

Sir, how about you? What was your motivation to join?

We see the same situation on the industrial operation side: a plethora of non-interoperable edge platforms with high vendor lock-in. When we saw the ambition on the multicloud side, it matched our vision of industrial edge computing. We wanted to bring Siemens' expertise to make a multicloud edge continuum.

Now, we've spoken about security concerns. Aura is open source. How does that contribute to digital sovereignty and security?

Open source means the software is free and anyone can review the source code, make changes, and ensure compliance. There are no hidden parts. It's future-proof because no single company has full governance, and you can continue using it. It even enables smaller contributors to participate, benefiting from distributed development.

I see you nodding. Do you agree?

Yes, it's a perfect match. Customers want to avoid vendor lock-in. Open source creates trust and allows them to continue their business even if a vendor disappears. The same principles that create trust and sovereignty in the cloud apply to the edge.

Now you mentioned vendor lock-in. What strategies ensure interoperability?

We have to accept many vendors providing edge technology. Common standards and federation mechanisms allow interoperability. For example, identity access management must be agreed. These strategies, including federation, make the setup future-proof.

Let's move to practical use cases. How do you contribute to smart production?

We've been contributing to Kubernetes and cloud workloads with Gardener to orchestrate workloads, and Garden Linux for bare metal. The data fabric ensures data flows from production to data centers, and the ability to shift workloads closer to data sources depending on requirements like sustainability.

Sir, what about you? Any progress?

Yes, we recently concluded a proof of concept showing that the multicloud approach from SAP can extend the edge to create a real edge-to-cloud continuum. For example, in machinery-as-a-service, an OEM can now choose different edge and cloud providers, gaining resilience based on the foundations of the Aura initiative.

I'd like to shift to market opportunities. How will edge computing and AI evolve over the next 5 to 10 years, and how will initiatives like Aura benefit the market?

The vision is to extend the cloud-edge continuum to AI, lowering the burden for scale in OT-IT convergence. This will boost use cases, more edge platforms, and edge-to-cloud. New business models like subscription services will become feasible, and AI will act as an accelerator, forcing us to do the homework to make AI scalable in the next one or two years.

Do you agree, Thomas?

I agree. AI will change how we process data. It will become more important to process data closer to where it is needed to avoid transporting huge amounts, using open software stacks.

Sir, how will the manufacturing market develop as a result of Aura?

Use cases that are not feasible today will become feasible. For example, everything related to subscription models requires reliable edge-to-cloud communication. AI shows the bottlenecks we have, and we must now do in one or two years what we've tried for 10 years to not lose track. We need to enable customers.

What are the next steps for Aura?

We have achieved a reference architecture that will be finalized in the coming months. Two foundations, NEON and SILVA, channel the software for telecom. It's all about adoption and scale, creating a developer community. The project will be extended with a 2.5 billion euro funding for AI at edge. If interested, visit us in hall 13.

How long are you going to be there today? It's the final day.

Until end of day.

Me too. Ladies and gentlemen, make the most of that opportunity to speak with Sir and Thomas. We look forward to seeing you again. Thanks, Sir and Thomas. A round of applause, please. Thanks again.

Enjoy the rest of the day here in Hanover. See you soon.

And with that, we're now going to catch up with another one of our experts who's been in an interview with our running reporter, Izzy. Over to you.

You've joined me at the accelerated product development station. We're going to dive into VR headsets and see how digital twin technology can help build something like this plane. Let's move over to Mario Desperara, a technical account manager at Siemens, who's virtually building a plane. Hi, Mario.

Hi.

First question: what is this VR headset used for?

The main focus is collaboration. For example, with a large ship, you can put on a VR headset and review it from anywhere. You can take measurements, do design collaboration, and see photorealistic textures. It's useful for marketing and engineering, allowing real-time design changes.

So it sounds like you can build anything anywhere. What is the most special thing about this tech?

Because you feel it. With a model, you can sit inside and see how reachable things are. It's like being in a video game. That's special.

Great. Thank you, Mario. So we're going to move over to a drone. I'm joined by working student Yanick and PhD student Jerry Schul. Hi guys. How are you?

Yeah, very good. So what are we looking at here? What's it used for?

So we are seeing here a drone. It's a rescue drone developed in collaboration with the Austrian mountain rescue team. It's intended for injured hikers, enabling quick and efficient rescue. I'll move over to Yanick. Can you tell us what is special about the drone?

What's special is not only what it does, but how it was developed. It was developed in our research center at the Technical University of Graz. We integrated many Siemens software products in one room to show the power of the portfolio. For example, an overheating issue was identified and the drone was redesigned within a week.

That's fascinating. You and Jerry are students. How does it feel to be here at Hanover Messe and see the real world?

It's an honor. I work for Siemens DISW for about two and a half years. It's amazing to bring our knowledge to customers and talk about real problems.

Brilliant. Thanks so much guys. Okay, with that we're going to move over to the mighty innovation hub.

You can see the hustle and bustle. We can't get through. We're trying.

There we go.

Excuse me. Sorry. Still with me.

Velia, would you mind joining us for a quick chat?

Hi. So,

Great. So, we're here at the innovation hub and I'd love you to tell us about the sensory development of the robotics at Heirlang and factory.

Yeah, for sure. So, obviously we can see here kind of an end-to-end innovation showcase, right, of a highly flexible adaptive production. And I come from our own Siemens's own electronics factory in Alangan. And one of the challenges that we have is that we have a lot of different products that we need to manufacture and we kind of have low to mid volume. So we don't have a lot of a certain product that we can manufacture. So traditional automation doesn't really work for us because it's just too expensive a lot of the time. So cases like these that bring intelligence actually down to the hardware that helps us be more flexible and adaptive is exactly what we need to continue making our factory more productive. And this is kind of an application use case for physical AI where robotics start to learn doing their own task and obviously this is also a lot of part of the future outlook of where robotics are headed. But in our factory also started a couple of years ago even bringing intelligence into the robots. We started teaching them how to feel for example where they had like very fuzzy assembly tasks that they needed to complete without damaging the product. We had also the cases where we needed to teach our robots how to see, identify different parts that needed to be picked up and put into package for example using semantic pack pick-and-place also. And now obviously we're excited for the next step also with partners like Nvidia to see how we can bring more and more flexibility and intelligence down to the robotics level.

Yeah. Amazing. So we can see how reactive the robot arm is here. What would you say is the most special thing about getting to work with kind of at the forefront of this tech and yeah, what's exciting about it for you?

I think the excitement mainly comes from not being in the lab environment but having a process that needs to adapt that new technology right for our real production. There's real customers waiting on our products. So this shift I think is really special from in theory it's possible or in a lab it's possible to then actually translate it into real production environment and have that proof point that we can also demonstrate to customers that it works reliable in a process. So that is a cool interface between those two worlds, innovation, but then when it hits reality, what do you need to do to make it work?

Yeah. Okay. And with this technology, what would you say was kind of the biggest challenge to getting it to where it is now? Is that obvious for you?

I mean the colleagues obviously are doing an amazing amazing job and a lot of the research partners are on the forefront of that technology development but you do need to give it a reality check sometimes and you need to talk about the complete systems life runtime life cycle management service. So all of this is kind of the maybe the unsexy bit that still needs to be talked about and figured out. Yeah.

Yeah. Right. Okay. And so in the factories, obviously we're not making trainers as we can see here today, but it's more hardware technology.

Okay, cool. And when you've had people visiting you today, has there been any questions that have kept rising up? Have you had similar questions?

Well, so far we're pretty much in the beginning of the fair. So not a lot of repeat offenders, let's say. But I think it's cool for us as a factory to be here represented on the fair, right? Because we serve as our own kind of proof point. So people don't expect to be talking with factory people and then they kind of perk up when they realize, oh, you're doing it or you're actually using it. So that's always amazing coming here.

Okay, brilliant. So I think are we almost at time? Two minutes. Well, should we have a little walk around and see what else we can find in the innovation hub? Let's follow. Let's have a look.

So, as you can see, the robots that Via was talking about, we can see them in action here. And it's so amazing to see how adaptable they are and how quick they react to what's around them. Let's see if we can get a good shot here. Okay. Wow. So, you've seen it here live in action. You've got a POV of the innovation hub and I hope you've enjoyed our chats with our guests today. I'm going to throw it back to Max in the gallery studio.

In the age of AI, energy is getting more important. But what is also more important is sustainability and merging those two topics. We are here at the Siemens booth looking at our Ecotech sustainable control cabinets and next to me are Vira and Johan and they will be telling us much more about what you can see here. So my first question goes to you Vira. What is this cabinet and what is so special about it?

Hi. So this cabinet is a strong example of how Siemens walks the talk when it comes to sustainability and also demonstrating how products with the Siemens Ecotech framework help reduce the customers' carbon footprint overall efficiency and so on. And what is so special about this cabinet is that this is the world's first cabinet produced with sustainably produced steel. And what this means is that there is a massive reduction of 70% carbon dioxide with the help of this cabinet. So which means that around 300 kilograms of CO2 saved per cabinet. And it's not only about the cabinet, it's also about the products inside. So these products are designed with the eco-design framework which means they are energy efficient, low carbon footprint and produced from sustainably sourced materials. Yeah. So this is an example.

Okay. My next question goes to you Johan. Can you give us a concrete example of a product from the Siemens Ecotech framework within the cabinet?

Yeah, sure. Maybe you have also seen yesterday's panel presentation about our Ecotech framework and just like Vira also mentioned it's about 13 eco-design criteria and we improve a lot of them in order to make our products more sustainable. And my example is here a S7 1500 CPU. I have here an old version and a newer version. You don't really see the difference but you feel it in the weight because taking the example of minimum material use, we were able to reduce the plastics, we were able to reduce the amount of metals and also make the PCB smaller. So in the end, depending on the variant of the CPU, 14 to 45% less weight compared to the previous product. And less weight, less material means then also less CO2 footprint for our customers.

All right, this sounds like a huge development and change to what we had in the past. Vira, what are the benefits of a product within the Siemens Ecotech profile framework for our customers besides what we already heard?

Yeah. So that's a great question. So first of all, sustainability is making business sense. Yeah. So the first benefit is that it really boils down to the cost because by using products with the Siemens Ecotech framework, it's not about only the costs which are reduced at the initial purchase but it's also during the lifetime because these products are more energy efficient, less carbon dioxide used and produced with more sustainable materials. Second is the topic of reputation. So by using products with the Siemens Ecotech framework, you are also giving a positive impact to your customers and partners and setting an example of how you are serious about the environmental footprint. So this is also a great example. And third but not least is that you know that the regulations are getting stricter day by day. So by using products with the Siemens Ecotech framework, you are also getting closer to your goals. So this is also a big huge benefit. And most important is by using Siemens Ecotech products with the framework, you're getting the same quality and durability as what is popular for Siemens. So this is also the big highlight with us. Yeah.

All right then, one of our last questions. Will it be available on the booth and where can we find more sustainable information about Siemens products?

What also is important for me to say is that you will find sustainability and sustainability offerings from Siemens not just in our booth but everywhere around. We have services around energy efficiency when you take the Energy Manager Pro. You have services around making production more efficient, make your products more efficient. Taking the example of the Siemens digital twin, also services offerings for decarbonization, helping our customers to decarbonize. Why I say this? It's important to know that sustainability is really on the heart of a lot we are doing. But if you really want to see our products, how we make them more sustainable, then come to our booth 180 and 175. They're just here close to each other. Let's talk about our cabinet and let's talk about our concrete products. Yeah, see some examples of how we make sustainability happen.

Okay, so you mentioned both exhibits here. What is the difference between 175 and 180?

So on the one we have the cabinet like Vira mentioned, it's possible for our customers to order a whole cabinet with CO2 reduced steel with Siemens Ecotech product inside. At the other booth we show concretely on the ecolabel what is the framework, what are the concrete eco-design criteria we're improving. So we could look at distinct products, look into the Siemens ecolabel profiles and see the sustainability of our products itself.

All right. So if you have one thing to take away for our visitors here, what would you say is that?

So as you know what the situation is happening around the globe, AI definitely is the hot topic but it's also important to also catch up on the regulation sustainability because things will also change in the future. So it's always good to start preparing for this journey right away. So with products from Siemens Ecotech framework, you are rest assured that you are way ahead of this journey. So I would ask our customers to visit here and also get some more information about the products.

We are going to discover next how Siemens and AWS are accelerating industrial AI at scale using real-world vision AI deployments in the Siemens electronics plant in Langen. And by standardizing this joint Siemens industrial edge and AWS architecture, deployment times have been able to drop from months all the way down to days. And here to tell us more, I'm glad to be joined now by our two guests -- from Siemens, advanced optical inspection and closed loop manufacturing expert Marvin Herbach, and from AWS, principal partner development manager for industrial Dr. Henning Hudov. Gentlemen, thanks for being here. The stage is all yours.

Perfect. Thank you very much, Max, for the warm introduction. We are very happy to be here for this presentation. And before we go into the details of the great things that we've been doing together in the electronics factory in Alangan, let me tell you a little bit about the origin, the history of our partnership which originated roughly around 2015. And for those of you who remember 2015, 11 years ago, that was the year where Apple brought out the new Apple Watch. 1 million devices sold within the first 6 hours and ambiguous computing was everywhere. People got connected. Here at Hannover, it was the beginning of industrial 4.0. The promise of connected devices bringing productivity gains. Siemens of course, Marvin was already here. AWS was not yet here on the stage. We waited for another two years until we released our first product actually together with Siemens. And what we already started building out there is what you see on this presentation, bringing together AWS and Siemens. Siemens mostly comes with the deep history of hardware in the field. What you see on the slide in the lower left corner is the connectivity, the data integration and this cannot be overexaggerated. It's crucial that you as an end customer and also a machine provider have access to the data and typically it's a lot of brownfield. So you need to have the knowledge over decades how to connect to a variety of machines out in the field. But what do you then do with the data? The data as such is the base. But you need to bring it up to a compute layer. That's why our two companies together innovated in the area of edge computing, Siemens industrial edge as the platform, and together we developed applications that run on top of this platform, feed up data to the cloud. You can think of it similar to an Apple Watch that you can measure the heartbeat at the person at the machine and this then goes up to the cloud for analytics and further use cases, feeding data to other sources and also back to the device. So this in a nutshell is what we've been working on. The partnership has been running for 11 years. We were here already last year 2024 showing you the first case of the application of what we've been doing together and today is the time that we take you to the next level. Last time we talked about the first uses implemented and now we are all about scaling. Cloud computing is about scale and together we worked on the concepts how to also scale the use cases in the factory environment. And I'm really happy to be here with Marvin today as the factory in Alangan is only 50 minutes drive away from my place. So Marvin, take us through the great use cases you've been implementing.

Yeah, thanks Henning already for the introduction of AWS. So let's start with our factory introduction. Electronics factory Alangan was established around 50 years ago and is really already a brownfield factory. So we are now optimizing a lot of different production lines to get all our productivity gains all the entire chain. So you can see we have here motion control as a business portfolio element. So we produce so-called inverters. This is a cinematics portfolio element and we also have the cinematic which is the control. All in all it's the intelligent setup to drive the motor. So we have the intelligence and we have also here the inverters who do the power electronics. So it's all about translation and logic signal to the drive. And by also having so much different product types, we have different product variants to produce. So we have here a mid volume to high mix production. So it's a lot of different products which can be configured by the customer itself. That means we have also a heterogeneous production. So it's a lot of challenges to optimize to get it further smooth running. And we implemented also in the last several years over 100 AI models which are running on the shop floor now. And this was also already awarded last year with the World Economic Forum as a lighthouse factory. So we are also proud member here. And now we want to show you a few examples of how we improve our production daily basis. So here you can see a so-called THT assembly line. THT is a through-hole technology process. So you can see here typical product of us. So we have here different components of different size. It's like solving a puzzle but just in a bigger size I would say. And the first step is putting all the components in a place which is here the assembly process. So it can be done by humans or robot depending on our vision here. And then we have to check if everything is there and this is the first use case. So we have here an AOI, an automatic optical inspection, to inspect all the quality of our placement. Afterwards if everything is placed then we have the soldering process. And for the soldering we have now here a new vision use case which is all about checking the quality of so-called flux. And this is a transparent fluid which can now be inspected by using a thermal based camera to check the quality if everything is straight, everything is more or less glued together. And here we also introduced a new function for our industrial edge. So in the past there were only normal cameras supported. Now we can use also thermal based cameras. After gluing everything together and having the soldering done, we do a so-called AOI again which is an optical inspection that inspects the quality of the soldering. And here typically AOIs have static rule-based inspection. And by further optimizing this, we use digital tools after having it improved by lean philosophy, we can use digitality tools to further reduce your so-called false positives. That means if the AI says it's a fail, typically a human has to inspect this if it's a real error or not. So we have a manual touchup and now the AI takes over this role automatically. We have a reduction in productivity or increase in our productivity, reduction in our manual efforts. And finally we also have a so-called coating process. You can see shiny surfaces here which is the coating of our process. And we have here as well a low cost inspection made together with smart algorithms, which is low cost but using also cloud for scaling it across the factories and cells. So all in all you can see four different use cases using exactly same stack on all, made together with AWS.

Right and Marvin, what really impressed me a lot is we saw here also what we at AWS call a flywheel. The typical Amazon flywheel is that if you're reducing cost, you're attracting more customers. With more attracted customers, you increase the number of sellers on AWS, and with more sellers, more variety comes, and again you get more customers in. Then the next round of this flywheel starts. I think what we're seeing here in practice is you also putting in or us together putting in a flywheel. The first use case that was the heavy lifting building in security as job zero initially. So can you talk us a little bit through how long did the first use case take, how long the second, how much could we then spin up this flywheel?

Yeah. So indeed the first use case here number one was all about five to six months. So we did all the customizing and also all the setting up the architecture once together with AWS with all the partners here. And then we used this blueprint for all the other use cases. So in less than two to three days we have already implemented this on our production cells. And the last use case which is the coating was running on day one already. Really impressive.

And also here if you look what is now the target also for our future, this is so-called future automatic manufacturing. We have here again the production line and we have AWS as a cloud system but we want to also run further algorithms, further optimization. And you can see here all running typically on AWS but to get everything connected, we use here our industrial edge ecosystem as a clue as an intermediate layer between IT and OT. And we have running now the different use cases but also it enables us in future to work here much closer together enabling closed loop by using an AI model to control the other one. Typically approaches to Agentic AI, I think also AWS is working on this topic as well. What is your vision as well?

Yes, I mean what we are seeing is more and more the promise of Industry 4.0 now also gets delivered with the use of generative AI. There's so much routine work you can offload and simply have an AI running in the background doing for you, and you can check results again with simulation. So I think we will see a lot of improvements in the years to come. We're just at the beginning, that's for sure.

Now let's have a look how we together set up our solution which we mentioned here. You can see here the typical build to run cycle which is the MLOps, the machine learning operation cycle, and it goes hand to hand from edge to cloud together with Siemens and AWS. And we want to show now the entire cycle how it's working here with our product portfolios. So it's starting all about here the industrial edge on the shop floor level. That means on field level we have everything connected with our edge. So we collect the data from machines like image data, we collect it from cameras. Here you can use so-called vision connectors from Industrial AI suite which is a product portfolio from ourselves. Then we have a lot of different other data sources and it's all together in our edge ecosystem available. Now here is also the running process of the AI model. That means the AI model consumes all the data, image data, machine data, and can do the prediction itself. So this is the optimization of the process here. And the results are then sent either to a machine to control it closed loop or we also send it out to the cloud. And here also AWS comes into place that we have a closed loop as well for the entire training and deployment.

Yeah. And Marvin, maybe before I jump into what we do on the left side of the circle, let's maybe also contrast how you worked in the past. My understanding was before leveraging cloud, you had to buy local compute and it could take you months until you had procured new hardware that you could use for these topics. Is that the case?

Definitely the case. So in the past, our data center collected the data manually on on-premise systems or we also had different so-called pipelines. That means every use case was more or less a silo itself and it was not scaling across the different cells across the factories. For this we needed a repeatable standardized approach and came together with our solution here. Yeah.

Awesome. And I think what we now build together is as you see the swoosh to go to the left side of the picture. The data that's collected on the shop floor with the pictures and the machine data is then fed into the storage. On AWS side, it's with Amazon S3. That's our storage that has virtually unlimited storage capacity and it also brings life cycle data. Data that is not used anymore gets into very deep archives, very cost efficient, and it only needs to be recalled once or twice a year. But the data that's super fresh, you get it in a way that with latency you can draw it out in a fraction of a moment. That's on the storage side. On the compute side, we use together Lambda functions. This is again a computeless computing. That means you don't need to run the compute infrastructure yourself. You simply have an endpoint that you can trigger with APIs and it just works as an infrastructure. And the same is also true for what you see on this picture with EKS. This is our container platform and you can think of it that compute power as container is only spun up if you need it for your next job. So for example, next job comes, you need a graphical compute power so-called GPU, but these things are very costly. So instead of having them all the time on premises, you just as a container spin them up when you need them, you run the job, and once the job is done, then you redeploy it and you're saving cost as you are using the scalability of the cloud itself. Once this has been processed, then the data gets fed back based on the template approach that we invented together into the packaging. And with the packaging, I think it's back to you, Marvin, it goes back down to the shop floor.

Yeah, but maybe let's have a look first on the template approach. So this is a new one here. So in the past as mentioned, we have different silos for every AI use case. That means you have expert for this AI model, expert for this AI model. But the future is that for example the operator from the factory can itself operate all the AI models at once. That means we have a unified user interface which is doable or operable for every AI use case. And therefore we have so-called templates. You can take as analogy for example cooking in private life. In the past, everybody had for example an oven and fryer and mix depending on the food which you want to prepare. And nowadays everybody has maybe a mixer or an air fryer with a lot of different recipes and programs. You have a platform here and you select only the recipe which you want to eat. And the recipe is your exact template. So the data scientist who is creating the model is doing it always in the same way. Therefore we reduce the engineering but the operation is always the same platform. And the domain expert, the operator itself, can do now the operation from every AI model, vision AI model here, by themselves. And after getting the model which is then also packaged from this platform, we have as well here our Siemens SDK included ready for industrial edge. We have the deployment also automatically to the edge device itself. So here we have the so-called AI Asset Manager. It's like a hub system for the different edge devices which are running all around the factory. So it's like a factory-wide control system. And you can deploy the AI models but you can also monitor them. That means for example if one machine is not working well, you can directly see here drift and can react here either manually or automatically in future as well. And then we close the loop and have now the possibility to do this again for further optimization or for new use cases because it's scaling across the entire loop. So it's going hand to hand and we reduce reuse by using this kind of modular pieces in our engineering as well as in our operation due to platform here.

That means now with all these recipes, you don't need to be a star cook anymore to have something that tastes really well. The layman so to speak can do it. You don't need IT experts to run this. Correct.

Yeah, that's right. So you only have once here the recipe creation I would say, but you can now use the star cook's recipe and can also enjoy it in every factory. So you can benefit in a factory network as well here. Yeah.

So you're now even sharing the recipe book across the different factories.

Yes, indeed. Yeah. Yeah.

Super impressive.

So, and now let's have a look on the numbers itself. So as mentioned, we're using here really this template-based approach which is here the platform which gives us a lot of engineering potential. So we talk about 60% here because as mentioned the data scientists can now focus only on the AI model and use the template-based approach. This is one of the first approaches here which we now implemented in our lighthouse factory. Secondly, as mentioned in our title, we can deploy it much faster now because we have the engineering, we have also the operation goes hand in hand, and we have an automatic deployment mechanism. So it's already in days available on the shop floor. If you have the PC already done on this kind of modular approach. And finally, you have then here the service cost because you have only one solution, one platform, you have only one service, you have not a lot of silos going on here, and you have a reduction in operation which is also beneficial for us as a factory.

No, super impressive. And Marvin, can you tell me a little bit your experience? How are you now scaling this from one factory to the other? Are they coming? Do they see the benefits? Do they want to have your recipes or how do you actually do this in practice?

Yeah, so first after implementing this on one cell, we want to scale it internally at the factory itself. So we have a lot of parallel production here. So we scale it at a lot of different production machines. But we also scale it in our factory network depending on the other setup of the factory. They are interested maybe in the coating, maybe interested in our soldering use case. It's like a recipe. Not everybody likes the same food. So it's also a pull from the other factory. We have here a market internal market more and everybody can then share only the recipe because they're following the same platform. It's also scaling here across the factory because we are following the same language, the same platform idea, and only give here the recipe to the other ones.

No, that's really impressive and I also love that you're not scaling just let's say in Europe, you're scaling globally. And I think again that shows hand in hand our partnership that we have this in different regions giving you also the latency for the compute that you need for these advanced use cases. So again super impressive that Siemens brings the global scale of how you bring this to production. And I think together we are able to serve you with the topics and the services globally so that you're able to execute this way.

Yeah. No. Nice. Then let's maybe have a look at the outlook. So today first day of Hannover Fair. We have plenty of opportunities to meet Marvin and myself. Either come to the AWS Pavilion in hall number 15 where we have a huge demonstration also of how small language models for production runs on AWS. And at the same time, you have the opportunity to also see Marvin here in Hall 27 at the Siemens booth to see all the other impressive things that we bring to market.

Gentlemen, thank you so much for joining us, Marvin, for coming here, for showing this great little exhibit here, and also to you for making your way over from the AWS booth. We wish you all the best for the fair and all your colleagues, and again, thank you so much for joining us.

Great. So, I'll get started off and then I'll hand over to Emmod. So one of the things I think that's important is Siemens is really in a large transformation to change from an industrial company to an AI-based company where we're really transforming into a data and AI-driven company. And that's a big change for us. So part of what we're trying to do there is if you look across Siemens, there's more than 700 product teams that deliver software to the market, and historically those things had different licensing, different foundations, different capabilities. And what we're trying to do with foundational services that I lead is to be able to have a common foundation for all of the Siemens accelerator products. So we want to build and deliver building blocks to the product teams. Those building blocks are for the whole suite of Siemens accelerator products. And then what we're also trying to do is to have an outstanding customer experience. If you have to log in to every product separately, if you have different licensing for every product, that's not a great customer experience. And so this is all part of what Roland leads us on on the transformation to one tech company. So foundational services is here to support that transformation. Now if I break down some of the things that we were just talking about there on the left, you'll see Siemens accelerator. So Siemens accelerator is our whole suite of products and how they work together. It's common identity, common licensing, it's a common customer experience, and being able to enable a land and expand sales motion so that once you buy something from Siemens, it's just an obvious choice to buy the second and third thing because it just works together on top of that common foundation. Then in the middle, you'll see capabilities that we deliver: SaaS services like identity and data services, edge services and edge application management, and on the right developer services. One of the things that we have tended to do is many of the products in Siemens had a separate tool chain for its path to production. How source code was managed, how quality was validated. It was many different systems. And one of the things that Roland has chartered us to do is to deliver what's called OSIS, one software engineering system, which would be a tool chain for all software products in the whole company. So that's a big transformation that we're just starting on but is that third leg of the stool. So when you think about what we do with FDS, we're enabling the businesses to focus on their business value so that we can do the undifferentiated heavy lifting below the covers. Now when it comes to Envoy, one of the things that we see is in our customer base, when we go talk to their CTOs or their CIOs, they have a very disparate system where the silos of applications don't work together as well as they would like to move data across the value flow. It too often takes human intervention where humans have to manually move data from system A to system B. And then there can be unplanned outages because maybe if somebody's off that knows how to do these things, you can't do the job, or maybe IT systems go up and down because they're different backends. So change that you might think should take a day or two can take weeks because of that manual flow of information. So we're introducing Envoy as a way to shepherd that data across these systems and to be able to have human-oriented interactions but as part of a controlled flow. So if you look at agentic workflow today, you can see great promise and lots of proof of concepts. There's great things out there where somebody will take a small problem and prove what an agentic workflow can do. But what we're trying to do with Envoy, which is based on top of AWS agent core, is to have a performant, scalable, secure system with governance where you can have that agentic workflow and deliver it as successful enterprise scalable agents that work with the products that you know in Siemens accelerator. So Envoy works, it connects to the data sources that you have, it connects to the applications that you know, and enables customers to deploy those workflows. And if you look at the right hand side here, we want to make sure there's a focus on configuration over coding. You can of course code, there's nothing wrong with coding, we love coding, but as much as possible, we like to enable configuration. Also, there's modularity, there's ability to maximize the customer's return on that. And the customer is free to choose their LLM of choice. We don't force that on anybody. So it's all about leveraging what Microsoft, leveraging what Amazon brings to the forefront of these capabilities, and we build on top of that. So with Envoy, what we're trying to do is if you look at example product engineering and manufacturing engineering products, we're really focused on four initial offerings: design center, sim center, team center, and opcenter. What we're trying to do is make sure that we can have workflows that span across those four different applications with a common foundation and the ability to have that agent workflow that moves data between the products as appropriate in a way that enables that workflow. All built on top of that scalable interface. So on the bottom you have our foundational services that we deliver, which are built on top of Amazon, which Emmod will explain next. And of course we're built to support DI SI and mobility in that capability so they can work on their application differentiation while we work on the non-differentiated heavy lifting. Emmod, do you want to talk about what we've done together?

Sure. Yeah. So we started our journey like a year ago and during this time, we actually started to introduce to Siemens the new agent core services. Agent core helps accelerate the agent development with a multi-agent orchestration. So we planned for a workshop with Siemens in Pune and the first week of that workshop was actually focused to let the team experiment with agent core and learn about agent core capabilities. The week after that, we bring the ISW, we learn about their use cases and we start developing agents. So within one week, we developed nine agents including an agent orchestration layer as well with agent core. During that time in the workshop, we also identified some gaps in our service. We helped bring the AWS service team to learn about those gaps and identify how we're going to move forward on the next step. In addition to that, we bring ProServe, we have a program called resident architect. So this will help to actually move along with Siemens to make it in a production level. So that architect works almost on a daily basis with your team to identify any kind of development bottlenecks so that we can elevate this. So during that design phase, we have a few design principles. We start with configurability. We don't need the Siemens developer to actually update their code every time there is a new large language model or a new kind of configuration. So based on that, the developer doesn't have to update their code but update their configuration. That configuration could be swapping large language model or could be adding a configuration for bedrock guardrail based on their use cases. And then if we look back on AI agents, AI agent is composed of a brain which is the large language model, also include memory, and in addition to that also include tools. So for memory, agent core provide you with short-term and long-term memory, and there is a lot of work under the hood to transfer short-term memory to long-term memory and consolidate this into a long-term memory. So we leverage agent core memory for memory interactions. In addition to that, Siemens FDS built their own solution with S3 and OpenSearch as well. And then with the extendability, those agents require to have some tools. Think about it as your hands and feet. We have the NCP integration to integrate with data sources, with API, and with any other tools. And then we also have Amazon EventBridge to integrate with other services as well. And then for security and governance, we have the agent core guardrail or bedrock guardrail. We also have the agent core evaluation to evaluate the performance of the agent, and then we have observability which provides you with all traceability from invoking the large language model to the interaction with large language model and reasoning. So all of this is actually available as blocks for the team to look at it and see how we're going to improve the agent.

So I'd like to make a comment on that too because when you look at all of those capabilities from Amazon with Envoy, we're trying to unleash those capabilities into the Siemens products. We're not trying to protect the products from Amazon services. We're not trying to isolate them. We're trying to make it even easier to adopt and even easier to leverage. So in no way, shape or form is Envoy trying to protect the Siemens developer from these. We're really trying to unleash them, which is our attitude across all the foundational services. We use a ton of Amazon calls in our product offering. And we're not trying to protect the product teams from them, but we're just trying to make sure that we leverage all of that to deliver a multi-tenant, highly scalable, cloud-scalable offering to support all of the Siemens accelerator offerings.

Right. And it's all configurable. So through your API interface, you can select what language model, you can configure it the way that you like, what guardrails and so on, so very simple to use.

So with agent orchestration service, your team stops building infrastructure and focuses more on building intelligence. And that's actually the main role of Envoy platform. So with that foundation and AI services, it makes it reliable, scalable, and secure. Now we're not talking about a roadmap, we're talking about a solution and a service already in production today and already adopted by many business units.

Yeah, we've got at least four examples where products are using it in production and we will continue to make it available to all the rest of the Siemens Corporation because we don't want every product team to have to be making this investment time and again. We'd like to make it once and then leverage that investment across the Siemens accelerator portfolio.

Right. And we're looking in the future to actually innovate more with Siemens, right?

Not just on AI but on other services as well.

Yeah, absolutely. Yep. And if you want to learn more about our capabilities and our services, we have Siemens booth in hall 27, that's our booth here, and we have another booth in AWS in hall 15.

Thanks very much. And yeah, another great example of our ever-expanding partner ecosystem. Our partners are with us across our entire booth because we believe that true digital transformation is only possible through a collaborative approach. No more solo efforts. That's why we are teaming up with the likes of, as you just saw there, AWS, but also Accenture, Capgemini, Microsoft, Deloitte, and many, many more. Plus a broad network of system integrators and distributors who are helping us create an environment for industry that is flexible, resilient, but also future ready. Now in addition to partners and also customers who are with us here at the booth, we also have the partner country. So every year the Deutsche Messe, the organizers of the event here in Hanover, they have a partner country and that partner country has its own area at our booth. And this year the country is...

Brazil. And Brazil was in fact the first ever partner country of Deutsche 45 years ago. And we at Siemens have been active in Brazil for 158 years. That is when we established the first telegraph line in Brazil. And that historic commitment to data, to connectivity and to technological advancement has evolved rapidly over the past few years. That is why we are incredibly proud and excited to showcase what we are doing for both the people and the country of Brazil. So, let's take a look.

We're here in the Brazilian corner of our fair booth in Hall 27. Brazil is partner country of this year's Hannover Messe. And with me is Pablo Fava, the CEO of Siemens in Brazil. Pablo, how was your experience here being partner country and the overall impression of Hannover Messe?

So, thank you Christine. It's a very nice experience actually. We have been working for years in order to become partner country. Brazil was the first one in 1980, the first country that has been partnered in this fair. It is a big job but it's a big opportunity also to showcase everything that we are doing in Brazil with our partners, with our customers, and to bring a huge delegation here, not only customers and partners but also institutions and government. It's a good opportunity to connect with people. So I would say very proud of everything that we have achieved here.

And we had a lot of customers on stage talking about Siemens solutions. So definitely that was very impressive and also what you have achieved here in the booth with the setup, inviting customers coming here talking about it. So great experience and there is one gentleman already eagerly waiting to get a chance like this. We have Fernando Silva, the CEO of Spain, the next partner country next year Hannover Messe 27. Fernando, could you share some insights on Spain?

Yes, first of all, congratulations Pablo and the Brazilian team for the outstanding work you did. We will learn from you certainly, but let's talk about Spain. Let me frame it in five topics in terms of the dynamics of the Spanish economy. The first one is our geostrategical location. We are connecting Europe with Americas, with Africa, with Middle East and this is a unique asset that we have in Spain. Second, we already have a very dynamic industrial framework. We are very strong on machine building, on defense, on the automotive sector. So we need to build on top of this. And how can we build on top of this? Adding the digital layer. So connecting the digital and the real world, putting AI, putting connectivity on top of everything. And finally, two very important topics. Spain has a very competitive energy environment. Our energy is mostly renewable and very competitive. And I think we also have a unique capacity to attract and retain talent. Our people from engineering are very strong. So I think we have all the factors to make it a success also in Hannover 27.

Sounds promising and we're curious what's going to happen next year. So we're happy to have you hosting and being the partner country 2027 at Hannover Messe. Thanks Fernando. So Pablo, why is Hannover Messe so important to Siemens as a whole?

So Hannover is a moment in the year where we have the chance, Siemens as a whole worldwide, to bring customers, to bring partners, to showcase everything that we are doing in terms of innovation. And we have to transfer this somehow and it's not only through digital ways or doing in our countries in our regions, we are normally doing this kind of road shows with customers, but coming here to our home to Germany, particularly Hanover, where we also can see other competitors and the strength of Siemens compared to other competitors. That's a very strong point to point out why we are the enablers of the technical transformation of the regions where we're acting. For us in Brazil, Brazil is also a country with nice resources, huge resources, with sustainable energies. 90% of our electric matrix is already sustainable, so Brazil can be an answer also for the future. It has a nice opportunity to participate now.

Great, great feedback and it's big footsteps actually which you're stepping in, Fernando, with being the partner country next year because Brazil definitely showcased a lot of great solutions, happy customers. So we're looking forward to have you here but now is the moment that we hand over the baton. Are you looking forward to that, Fernando?

Yes, absolutely. And again I think Pablo already mentioned the most important is that we work as an ecosystem with our partners, with our customers, with universities to make the best out of the technology. So we are really looking forward to showcase the Spanish industry, the Spanish infrastructures and how we apply technology, but also to reinforce the connection between Germany and Spain to really make a more competitive Europe and a more sustainable and fair Europe. So I think the learnings from Pablo and the team will be great and again we have to work as an ecosystem to make the world a better place to be.

Wonderfully said and I think now really is the moment to officially hand the baton over from Brazil to Spain.

Sure.

Fernando, as an Argentinian living in Brazil, it is my great honor to transfer to you the baton to a Portuguese living in Spain. Right.

Yes, exactly. And I wish you a lot of success for next year. Be prepared. It's a big job but it's a big also realization.

Yes. Thank you Pablo. It's a great honor to receive it from you. In addition, we have all these connections Brazil, Portugal, Spain, South America and so I look forward to also work together with your team to learn on your experience and build a very strong Hannover 27. Thank you very much.

And see you soon.

See you soon.

Thank you.

That's a wonderful experience here. I love Hannover Messe because the proud to be Siemens moment definitely comes true. Thank you.

Thank you very much. And we're going to be handing back over to Christine and Miki in just a second. But first, I want to make a few final comments here on the stage. I just want to give a brief overview again of what you've been experiencing here at our booth from an event experience perspective. You heard just then the partner country. Brazil, every partner country gets their own representation here at our booth. But of course, there is much more going on as well. We have our customers represented here throughout the entire area. I want to pick out three in particular who are in our digital enterprise showcase for the consumer packaged goods industry: PepsiCo, Natura and Pringles. PepsiCo is using our simulation technology to optimize their warehousing and intralogistics operations. Natura, a Brazilian cosmetics company, is using our digital twin technology to optimize the way they extract essential oils. And Pringles uses our simulation technology to simulate the dough and can filling process. In that digital enterprise showcase, we are demonstrating how with our core company technologies - the comprehensive digital twin, software-defined systems, and industrial-grade AI - we can help get the product from design all the way through the supply chain to when the product hits the supermarket shelf. In the middle we have our technology deep dive area with four islands representing our digital thread approach: advanced machine engineering, smart manufacturing, systems engineering, and electrification and buildings. On the far side, we have an animation showing how we envision the future of industry dominated by AI, making everything more autonomous, flexible, and orchestrated. This area is split into three sections: a shoe sole exhibit using additive manufacturing, physical AI with robots and humanoids, and smart infrastructure where AI takes care of maintenance, operations, and sustainability. That is our booth here in Hall 27, our new home with a focus on industrial-grade AI. I'm going to say goodbye for now and hand over to Christine and Miki.

This co-pilot of mine called Max definitely did his homework as I always say and I wonder who is going to tell all these stories from tomorrow onwards. Probably his friends and family and Julia his girlfriend is going to get all that information now firsthand from tomorrow onwards. How was your Hannover Messe experience?

It was amazing. I'm completely positively overwhelmed from all the things that I've seen here, all the amazing people I've talked to and generally the amazing vibe we had here. How about you? What did you think about it?

I mean to me Hannover Messe is very special. I'm 25 years within the company and 12 years definitely we have been working on that stage program which evolved year after year and the whole crew here who is working on that program grew to a family. At this place is the time to really say a big thank you to everybody who involved to create this, to produce this, to edit this, to bring it to your tables, to your devices wherever you are watching. It's a great honor to really work in that team, to trust in everybody who is involved, and this is actually my best Hannover Messe experience in regards of what we achieved in this 12 years time. Hannover Messe is a crazy time and if you have the virus for a fair you definitely live and breathe Hannover Messe, innovation, exploration and all these great things we're showcasing here. The team on site especially is also so cool because without our experts, with our partners, with our customers, we could not host a program like this with 250 plus speakers with 180 topics over the course of the week. And Max, you're joining us now. Great you're back. I mean, I don't know if you heard it, but I wonder whom you're going to tell all these stories, what you have developed and worked on and learned from tomorrow onwards. Port Julia.

Yeah, I think I'll just tell my girlfriend Julia every night. I mean, as you do as well, when we practice and rehearse for these things, you've told me as well, you walk around your neighborhood at night speaking to yourself. I do that, too. I think I'm just going to continue talking about partner countries, about partner ecosystem, and customers. They're used to it. So, I'm just going to keep on doing that.

Okay, keep on doing that. I keep on doing to say thank you to our partner country, Brazil, which was really a great experience. And we prepared a little song here which is kind of like in Hannover at the fairground. We've had fun. We've had partners and customers. We explored our exhibits at the fair booth. Always a pleasure to host these sessions for you all. Now we're traveling to the Copacabana. Something like this. We're going to prepare on that. Big thanks to you, Miki. To Izzy, who's probably watching us at the airport right now. She's flying back home to Manchester. Izzy, great that you've been supporting. Also to Tina in the office, to Carsten backstage, to Cedric, to team Comp team, to the GBS Dream Boys, and to many more who have been involved. And as always, Christine, to the lady without whom this stage program wouldn't be here, the queen of the show, you yourself. You've put together another amazing program. This time with a jam-packed gallery studio as well, Monday to Wednesday.

We forgot Militia. Militia, great host on stage in our gallery studio.

It's an absolute jam-packed thing. Once again, you made it work. We coordinated ourselves. We rotated and it was an absolute dream. So, thank you once again. Without you, this wouldn't be the same.

Well, my co-pilot, I have trust and faith in you, dear Max. So, dream team once more. I hope you all enjoyed watching this great show. And we just have a highlight video now to kind of take impressions from all week long. Get the highlights. And if you want to see more of our sessions, they are still available on demand. Enjoy. Stay safe, stay curious, stay innovative, and come back latest on this channel for SPS 2026. Goodbye.

Bye-bye.

Now, we have to innovate. We have to push the boundaries of what is being able to be done. We're basically unveiling the future. You have to first prove that it works. And I think we proved it, right? Welcome to Hanover Method 2026.

When it comes to AI. No company can do this alone. We really need strong partners to make this happen.

This is where people exchange, where ideas are born. Possibility basically takes shape.

Now think about how many products we already used today. Yogurts, toothpaste, shampoo, coffee. Consumer packaged goods companies must handle rising demands for diverse and sustainable products. How can they manage this complexity? With the power of data, seamlessly combining the real and digital worlds. Siemens' leading industrial software and automation portfolios enable the digital enterprise, where everything is connected by fully integrated and digitalized workflows. This end-to-end approach enables a horizontal flow of data from design to realize to optimize. Digital threads guide you through the most efficient way on your digital journey. Siemens Accelerator provides access to the entire portfolio, ecosystem, and marketplace, powered by industrial AI. AI makes sense of vast data, transforming it into actionable insights. With the right data fabric and knowledge graph, companies can accelerate product development, optimize production, and achieve results like Pringles' 10% higher capacity, Natura's 50% lower energy and water consumption, and PepsiCo's 20% higher throughput. The digital twin composer brings the industrial metaverse to life. Next time you go to the supermarket, think about whether that product was empowered with Siemens technology. Come to Hall 27 to explore the end-to-end story.

So welcome everyone. Good afternoon. I have the luxury of presenting this next panel and with me and in order I have Cedric. I sure you know everybody knows Cedric is the CEO of Siemens Digital Industries. In the center I have the luxury of having Ali Perroi. Ali is the VP of supply chain and manufacturing. And in the far end I have Stuart Makuchin. Stu is VP of industrial metaverse, been in the company for few months.

29 years.

29 years only and is responsible of the industrial metaverse strategy. So, first of all, I'd like to start with Ali. Ali, first of all, welcome to Hannover Messe. Welcome to the Siemens booth. So, thanks for having me. Really happy of having you here. So, tell us a little bit about this project. What is this project interesting for PepsiCo? Why what do you want to get from this project that we were presenting at CES this year and now today at Hannover Messe?

Yeah. So the demand for our product is growing but our footprint isn't. So the goal was to do it in digital first to make sure that we can expand manufacturing into the warehouse, make sure the lines that we were planning to add fits, figure out all the flow, figure out all the inefficiency if you will before we actually spend any money, any capital doing the actual work. So that was the main reason and we had food beverage feeding into the same mix instead of a large warehouse. So we wanted to do it digitally first to reduce risk. The main reason that was the project.

Yeah. I think it's an interesting thing that of course you can see in our booth. But this is not just a digital twin of a line or a machine. I think this is something more than that. Why do we think that this is a milestone in our industrial metaverse strategy?

First, let me say thank you to Ali because I mean if we think of PepsiCo, we have a long-standing relationship but the great thing is we're in deep admiration of what you do. I mean you serve billions of customers. You have billions of data touch points and the key question was how can we make that better, right? How do you find somebody you partner with to rethink the fast-moving consumer goods or packaged goods industry? And that's why thank you for letting us work with you. And what is actually very interesting is we always envisaged to say if we want to do something digitally it should be simple, it should not be difficult. So we built the digital twin composer together with Nvidia and Pepsi world premier the first one which is using it and you have to imagine it is that you can sort of simulate and build scenarios extremely fast and extremely quickly. And because you have that opportunity to do this, this is what we wanted to actually drive forward with.

I think we have a video here.

Yeah, we have a video, but we have better than a video. We have a video and we have a voice over and Stuart, which is sort of with this only 29 years old. Exactly. Background has built it forward. So let's roll the video and then tell us a bit what we've done with PepsiCo, which technologies there's a lot of technologies coming together and why this is super different.

So this is the application we developed for the showcase for PepsiCo. It's what we call a single pane of glass. So we can look at different plants. We can actually look at the supply chain flow between those plants and the goods in and out. We can look at different aspects and what's happening behind the scenes. It's pulling data from all different systems. So this is Teamcenter. All the information needs to be managed in a secure manner. You can fly through the current state of the plant. Now, this is leveraging our NVIDIA partnership that's embedded. This is the current state, but one of the things you want to look at future states. So, I look change the date and in the future state I've dropped a Gatorade line into this plant. So, I have this concept of effectivity. I can look at different things, but this is a single pane of glass. There's information coming from 20 different systems behind us and every aspect. There's a digital twin. So this is a digital twin of actually the mixing tank. So it's a single experience that you're pulling all this information in a very seamless way. And this is just part of it. The full demo is available on the stand.

Yes, Stuart. Thanks so much.

That's fascinating. Ali, let's roll back a little bit on time. What were the operational challenges you're trying to solve with these models that this industrial metaverse project you did with us?

The biggest challenge was we were going to make a lot of decisions in a very fast way and we wanted to get it right the first time and minimize our investment and mistakes. So the best way to do it is the digital first approach. Do it all in digital. Technology is there. The main reason we partner with Nvidia and Siemens to do it in a scaled way because we plan to not only do it in this region, we have many regions that we want to do this in. So we wanted to do it fast. I would say what it allowed us to do is make better decisions faster and that was the main reason.

Yeah, a good reason.

Good reason. Yes. And I know that we're still a little bit early in the process, early on in the journey with we're starting with you, but can you advance us a little bit of the advantages and the gains we've got so far with us?

We were able to identify where we had bottlenecks as we add the new line. We realized we didn't have enough docks. So we ended up using an auto truck loading system that allowed us to speed up the pallet that's coming off the line. Get it out the dock. We were able to optimize it because we didn't have a lot of space. All of this inside the 12 weeks. So we were able to prove that everything fits and flows digitally first. So now I'm happy to report that that project is actually expanding. They're asking us to look at can we add two more lines in this same facility. So that's phase two that's coming up.

That's coming up. Stuart, you've been in this project since day one. You're one of the sponsor executives of this project. So which are the main challenges we had to face so far.

So I think the biggest challenge was data. You know Ali was very good. They gave us three simple plants. They're 50 years old. There was no 3D data. Data was in different silos. Some of it wasn't even electronic. So pulling all that data, we scanned the plants. We converted those to 3D models. We then use those to simulate physics-based simulation and optimization of as-is and to-be state. And this all had to be in a managed environment. And then just on top of that, we gave us 10 weeks to do it. It's a lot of technology just working together seamlessly from physical to digital, from digital to physical again as many times as needed.

That's fascinating and Cedric, but PepsiCo is not a small company, they have more than one plant, more than...

So, what are the challenges we had to face to scale this?

Man, Ali, I don't know if you want to if I said everything correctly or if you want to correct me.

Digital composer allows us to streamline the workflow. So we are one of the first ones I understand to use it and yeah, you can kind of see the physically see the decisions you make and how they materialize all in digital world before you actually go to physical. So that's a big advantage.

Ali, just one for you. We know that you are very aggressive in the way you want to deploy this technology across the different sites but what's going to be the next plans for you, what do you have in mind?

So our goal this year is to scale this capability across not only North America but LATAM, EMEA and Asia. Ever since the announcement at CES, all of our country GMs are asking for this capability because they have plants and they want to test it in digital first. So our goal is to not only scale it, but to show value right away. I would say show value and do it often.

Absolutely.

And Stuart, you've been in the industrial metaverse since the beginning. So you're one of the executives that have been pushing for this technology, one of the visionaries. We have a lot of visionaries inside Siemens. But we have been one of the ones that we're visionaries and we're executioners and you have both. So you actually make things happen which is quite important. What's next? What's the next thing that we should expect in the industrial metaverse from?

Well, I think this world is accelerating, right? I think digital twins are going to get more comprehensive. You're going to be able to do physics-based simulation of every aspect to give you insights into products. AI, we're scratching the surface of what AI does. AI is really going to help us deliver this at scale and really accelerate it, right? And so there's all these multitude of new use cases. I could go on. There's around humanoid robots, virtual commissioning. We're envisaging all these new use cases that we haven't even thought about because once you bring all this information together using our digital twin fabric, AI fabric into a single pane of glass, it enables so many new things.

Yeah. And the last one for Cedric, I'd like you to use your crystal ball and not just for this industry. We're explaining how this industrial metaverse can change the food and beverage industry. But how do you see industrial metaverse impacting the industry in two, three years?

The digital twin accelerate them with AI and really have a bottom line impact is something which is super powerful and I have to say we couldn't have done it without you guys Stuart and definitely a customer which is pushing us but this is the new standard and you should have a look at it because I think it's super impressive.

Mhm.

Thank you very much. Uh gentlemen just to close this panel. It's been a luxury having you three. I would like to encourage you just to step by the CPG booth. We have an amazing demonstration of a pop-up factory also done in partnership with PepsiCo that shows how can we do a fully automated lights factory running with AI. So that's a really interesting thing to watch but also you have all the projects that we done with PepsiCo. Just thanks so much. We love having customers like PepsiCo that they push us that they let us show all our technology and I wish the rest of the audience an amazing Hana Vermesa.

Thanks so much.

Thank you. More to come.

Thanks.

Thank you very much. Well done.