Good morning. This is the conference operator. Welcome to the Schneider Electric call for analysts and investors with Olivier Blum, Chief Executive Officer, Nathan Fast, Chief Financial Officer, Caspar Herzberg, Chief Executive Officer of AVEVA, and Antoine Sage, Head of Investor Relations. Thank you for standing by. All participants are in a listen-only mode, and you may register for a question at any time by pressing star and one on your touch-tone telephone. I would like to inform all parties that today's conference is being recorded. If you have any objections, you may disconnect at this time. At this time, I will hand you over to Mr. Antoine Sage. Hello, good morning, good afternoon, and thank you for connecting at short notice. As an intro and as a reminder, we are currently in a quiet period, accordingly, today's discussion will be strictly limited to the agreement reached by Schneider Electric to acquire Cognite, and we will not be commenting on our 2026 performance. Joining this call, we will have Olivier Blum, Schneider Electric's CEO. We have our CFO, Nathan Fast, and we have Caspar Herzberg, the Chief Executive Officer at AVEVA. For this call, we will present you a couple of strategic slides that you will be able to retrieve on our website after the call, as well as the press release that we issued yesterday. I'm going now to hand over the floor to Olivier and Nathan and Caspar, who will elaborate on the definitive agreement reached to acquire Cognite. After which we will open for question and answers. Olivier, over to you. Thank you very much, Antoine, good morning, good afternoon to all of you, thank you again for joining in such short notice. We are excited to be with you today, of course to make an important announcement, which is the acquisition of Cognite. If I just go back to what we told you last year, in 2025, we've decided to refresh our strategy and to enter in the new cycle. This new cycle has one simple goal, which is really to advance energy tech to the next level. It means really bringing this company in the market which will be able to connect the physical and to the digital world by electrifying, automating, and digitalizing every industry, business, and home with a goal to drive efficiency and sustainability everywhere. I told you in our Capital Markets Day in December that we were entering in a new era, a new era where we believe intelligence is key, a new era where AI will require more compute, more compute will require more energy, and energy and industrial agents will sit at the center of everything we do at Schneider Electric. Not only because it is important for Schneider Electric, but it is important really for everything we do our customer. For us, it is extremely important that we create a company that is able to connect this physical and digital world, a company where we can capture data, structure data, contextualize data, and deliver those data across the lifecycle. We believe that the company which will be able to structure this data on top of physical assets will be the company that will win in the market. We believe this acquisition transcends our belief that Schneider is really in the position to be able, by leveraging our data cube, powered by AVEVA technology, to deliver that unique value to our customers. If we go to the history of how we have built this industrial stack industrial world, you remember we started in 2008 by combining AVEVA and Schneider Electric industrial software to start really to create the first industrial digital twin in our company. Later on in 2021, we enhanced, we amplified everything we were doing with AVEVA by adding OSIsoft, the world's leading source of industrial time series data. And now, of course, we are entering in this new era, in this new era of embedded intelligence, where we want to build an AI industrial champion by combining the historical capability of AVEVA and everything that Cognite has been able to build. We are building a foundation really that brings data to the next level and that can create true intelligence in the industrial world. If I just tell you briefly about Cognite. Cognite is a company that has been created in 2017 in Norway. It is a company which has 800 people globally. A large number of R&D tech product people being located in Norway. Great people. I had the privilege during the process to meet the historical founder who are still in the company and will continue to stay with us in the future. Their vision about the industrial world and how AI is going to impact the industrial world is excellent. They are benefiting to a very, very strong pool of talent in AI, and they have been able really to do a remarkable performance, to deliver remarkable performance over the past years. And beyond the performances, with every single customer that I have met in the past three years, I can testify that customer love the platform and really love the value. Let me briefly walk you through Cognite core technology stack, which is designed to transform industrial data into actionable intelligence at scale. The first layer is what we call Cognite Data Fusion, which somehow is a core foundational piece. It provides a cloud-native industrial data foundation. It ingests and textualizes, if you want, data across IT, OT, engineering system, creating a unified knowledge graph. All together, this is what enables customers to unlock significantly greater value from their industrial data within a fully open ecosystem. The second layer that you see on the slide is really Atlas AI. That brings an industrial AI agent layer, a unique one in its industry. Through a low-code workbench, customers can deploy AI agents on top of this data foundation to automate workflows and accelerate decision-making, which drive real tangible business impact and generate efficiency for customers. If you go to the upper part of the stack, you have Cognite Flows, which act as the execution layer. It allows customers, people on site to rapidly build and scale production-ready AI-native workflows, which empower really the frontline team, as I said, to translate expertise into enterprise-wide value. Altogether, you can see that those three layers create already standalone a powerful end-to-end industrial platform that turns data into intelligence and intelligence into action, which is really aligned with the long-term vision and strategy we have at Schneider Electric. I remind you that we have started a journey at Schneider and AVEVA over the past year to start to create something unique in industry, which is called CONNECT, where we combine really from design to build, to operate, to optimize, as I said, a unique set of application and analytics across the life cycle. We are, as I said in my introduction, what we do in industry now today, we want to do it, of course, in data center, we want to do it in infrastructure, we want to do it in building, not always with the same technology, but always with this idea that the company that will win will be the company that can connect the physical and the digital world. Of course, Schneider Electric historically has a very strong positioning, a strong legacy in the physical world, in all the segments, including in the industrial segment. Going to the next layer of intelligence is absolutely essential, and that's why I repeat myself. We have created this unique combination, first of AVEVA and Schneider Electric software, then amplified with OSIsoft, then now we amplify with Cognite. All of that, we want that ecosystem to be enabled, to be amplified by developers and partners everywhere in the world. This platform has to be extremely open to welcome any kind of technology partner that we onboard on a regular basis. That's what we have done so far, at Schneider Electric with AVEVA. I would like to hand over to you, Caspar, to explain a bit more in detail how Cognite and CONNECT are going to work together. Thank you, Olivier. When you look at the design, build, operate, and optimize life cycle of an industry, and you translate this life cycle into data, you will see on the design side, models, assets. These assets are at times very large, millions of data points if they are a large process plant. On the operational side, you have the time series data that Olivier talked to that comes from how machines fare when they produce something. This is vibration data. This is the experience of the machine, if you like. Then, of course, you have optimization data, which is what you do with all of this data, asset and operational data, and other IT and enterprise data. All of this together, we bring to the market in CONNECT. Most of this data today still sits on-prem and is then usually copied to the cloud for analytics and for AI. We've introduced a no-copy capability, meaning that only the data you need to work with in the cloud is taken. The challenge, of course, with these enormous amounts of data is how to scale this while then dynamically maintaining the context of that data to each other, the context of plant- to- machine, of time series data like a certain temperature on a certain day 10 years back. All of this, how to maintain that, and how to dynamically model that in the cloud. What Cognite does for its customers is to take this fragmented, complex industrial data and integrate it into a single unified data model, and most critically, a knowledge graph supported by, as Olivier said, the agentic AI workbench, where you can use algorithms to dynamically model this, without a lot of coding. That gives us now as AVEVA, Cognite, and of course, as Schneider, the ability to have the full life cycle of design- build- operate fully working in the cloud for our customers for analytics. Of course, because of the dynamic modeling, as a way of feeding into what the AI models of robotics, the AI models of any type of industrial AI need. This is at the heart of this acquisition. In summary, it gives us the ability to ingest, to contextualize data, not just from the Schneider and AVEVA systems, but across, because we have open software, all of our customers' broad pre-existing data ecosystems, as I said, third-party data, and so on. Let's go to the next slide. Let me talk about how AVEVA significantly accelerates Cognite, because what we bring them is immediate scale across all of the large industrial segments that AVEVA and Schneider are currently supporting. Of course, the global footprint on top of that Schneider Electric has with its countries and its strong go-to-market engine. In addition, we have an install base of more than 23,000 customers with the comprehensive portfolio I described earlier. That gives, in summary, Cognite a reach, a depth, and a scale to accelerate adoption and to bring the innovation they have to, very often, our joint customers, and increasingly, as they move towards life sciences out of the pure process industries, to new customers. Cognite in turn, as I described earlier, accelerates AVEVA. It accelerates by bringing a modern cloud-native SaaS architecture with the focus on industrial data and AI I described. It brings advanced capabilities in industrial data management, the data graph, et cetera, that I just mentioned. A rich library of industrial extractors that will be added to the huge library of connectors and extractors that AVEVA already has. We would then be able to do any type of industrial data extraction for our customers, more than probably anyone in this industry. Of course, together we will form a unified platform for the next phase of industrial AI, because what Cognite bring neatly fits into what CONNECT has. Lastly, of course, they bring a significant level of innovation and of a dynamic go-to-market focus on growing new customers, winning new logos. You have to imagine this is like a locomotive that pulls the larger AVEVA with it to significantly more growth. Next slide, please. What you see here is just a very small extract of the different segments in which AVEVA operates today, and some of the customers. Some of them, many of them, Cognite customers today, often with a small land presence. Of course, the combination of the two companies is going to create a scaling effect across that customer base of, as I mentioned, 23,000 customers. That is going to be hugely powerful. With that, I'd like to hand over to Nathan for the next steps on transaction. Perfect. Thank you, Caspar, and good morning, good afternoon. Let me take a brief moment to cover the key terms of the acquisition, which you'll see are fully aligned with our disciplined capital allocation framework and priorities. Starting first with Cognite's financial profile. In 2025, the company reported an excess of $170 million of revenue, with strong momentum reflected in 36% growth in ARR bookings. I turn to valuation, we have reached a definitive agreement to acquire Cognite at an enterprise value of $3.1 billion, with the transaction to be fully funded in cash. In terms of timing, the completion of the transaction remains, of course, subject to customary closing conditions, with closing expected over the coming quarters. Once completed, Cognite will be integrated with AVEVA and will be fully consolidated and financially reported within Schneider Electric's industrial automation business. To conclude, overall, of course, this transaction, again, is fully consistent with our strategy-tied, process-defined M&A discipline, combining a strong strategic fit first, a compelling financial profile, strong growth and gross margin, and a high degree of integration readiness. Olivier, maybe before we go to Q&A, I'll hand over to you for any closing comments. Thank you, Nathan, and thank you, Caspar. As we said many times from our Capital Markets Day to the different conferences and meetings we had together, we said we would be always really open for M&A in a very targeted and selective manner. Cognite is really in this category. I mentioned as an example that in the past we have acquired, for instance, Motivair to accelerate really our technology stack in liquid cooling to go faster in capturing the growth supporting in data center. That's very similar when we talk about Cognite today. The goal is really to accelerate the execution of our strategy, becoming a worldwide champion in the industrial world by taking AI to the next level is part of our ambition. It's a strong element of differentiation. What we found in Cognite is great technology stack, great product, high quality people, and as I said in my introduction, a leadership team, which is made of the historical founders, who are committed to stay with us after the transaction, and also many other people on the technology, on the commercial side that really understand the industry. They understand technology, they understand AI, but more important or equally important, they really understand the industrial world. There was a strong technology fit, but there was, as well, a very strong cultural fit, which is always extremely important for me. This is a capacity on not only acquiring great product, but how it will fit with our culture. I'm really excited, and of course, we will have a period, as Nathan mentioned, until closing. Preparing the next step where we will combine forces and we will ask really Cognite to lead this AI industrial platform is super exciting for us. You can imagine that a strong attention will be put in place on retaining the people, developing those people, and make sure we do a great integration culture in order to retain the key talent. It's time for me to conclude. Cognite accelerates the AI journey. You understood. If I step back a little bit on the big picture for us, it's really executing our strategy, going to the next level of AVEVA story. I would amplify even more that what we found in Cognite will help also to enhance all our energy management technology stack on the software side, because as we said multiple times, our goal is to bring industrial intelligence to our customers, but also to bring energy intelligence. We are extremely excited and, of course, the focus will be on really delivering strong results and being able to grow fast that business with high level, of course, of profitability. On that, I will stop, Antoine, and over to you for the Q&A. Thank you, Olivier. Thank you, Nathan. Thank you, Caspar. Look, we've covered a number of areas, and I think luckily addressed some of the key questions that you may have. We just have 10 minutes remaining, so let's move to the Q&A quite fast. As usual, in the interest of fairness, please limit yourself to one question, and we'll come back to you if time allows. With that, operator, can we please open the line for the first question? Certainly, sir. The first question is from Alasdair Leslie of Bernstein. Thank you. Good morning. One of your opening lines yesterday in the press release, you talked about industrial AI shifting from supporting analytics to acting on and kind of executing operations. I guess that's really interesting and quite exciting. Obviously could unlock a lot of potential productivity and growth. I was just wondering maybe if you could just help us understand how much Cognite might help you kind of leap forward to that point now. How close might you be with Cognite to kind of AI autonomously taking command of real operations? Thank you. No, sure. That's a good question. Caspar, do you want maybe to give a concrete example because we have already some customers who are using our own AVEVA platform and Cognite. Maybe it would be good that you give one customer example or one application where we've been able already to demonstrate. Absolutely. We have a large customer in the Middle East that is using the combination of Cognite platform with the data from the PI System and the data from our both process simulation capabilities to model and autonomously make decisions for their large petrochem assets today. Maybe further than that, to the question, because when we look at robotics and when we look at the growth in robotics in factories, the more autonomous that is going to become, the more the core data infrastructure needs to be dynamically modeled. This is where the combination of knowledge graph and agentic AI capabilities, their AI workbench, are incredibly important because you will be able to dynamically model the changing data, the changing operations data, the sometimes changing asset data for your robots, basically. I think it's going to be a key enabler of the accelerated use of robotics in factories. Back to you. Thank you, Caspar. Thank you, Alasdair. Operator, next question, please. The next question is from Andre Kukhnin of UBS. Yes, good morning. Thank you very much for taking my question. I just wanted to see if you could help us to understand better the kind of market positioning of Cognite versus its peers and who they would be. Could you help us to assess the kind of technological position of Cognite as well? How can we track that in the future? Caspar, please go ahead. Yeah. In industrial software, it is the largest and probably quite unique company in that space, which is why we've been after it frankly for many years, right? Because it complements us so well. If you're looking at the more analytical level, I would look at companies like Databricks, Snowflake, and some of the hyperscalers as comparative. Basically, what you do with industrial data in the cloud, in an AI agentic way, is a new area where a lot of people are interested, including some recent announcements by Prometheus and others. With this type of customer base and this proven way of doing things, both the combination AVEVA and Cognite, and Cognite itself, are pretty much peerless, I believe, at this point in time. Okay. Thank you, Caspar. Thank you, operator. I propose that we move to the next question. Yes. The next question is from Phil Buller at JP Morgan. Hi. Good morning. Thank you for the question. Perhaps to Olivier and Caspar. I can see the strategic fit of Cognite. The questions I'm getting today are more along the lines of, are there more gaps to fill? Does the deal complete the IA software portfolio, or are there more to come that perhaps you've been looking at for several years as you have with Cognite? Is this the multiple we should get used to, really? Thanks. No, thank you. I will take that one. Look, as I just said, and I repeated multiple time, we are not obsessed with inorganic. We are obsessed by delivering our technology stack to our customer, to integrate properly, to deliver great customer value proposition. This step is an important one. It comes at a time when AVEVA and OSIsoft have been digested, have been integrated. Definitely the team now has the bandwidth, the possibility really to go to the next level. It doesn't mean that we will come back tomorrow morning with another acquisition. I think we want to do step by step. Again, to continue to be very, very selective only if it makes sense. As I said multiple times, the focus of Schneider Electric is to deliver our equity story organically mainly, and by exception, when there are great technology, great companies that help us definitely to accelerate the strategic execution, we will do it. My short answer is do not expect us to come back to you with many, many deals. This one is an important one. Now it's time for Caspar to integrate, to deliver the synergies, we'll continue to monitor the market whenever there is great opportunity. The next question, gentlemen, is from James Moore of Rothschild & Co. Morning, everyone. I just want to come back to the primary rationale. I don't know, Olivier, if it's for you or Caspar. Is it that the white space and the thing that you really needed was the knowledge graph? As we shift towards agentic AI, the knowledge graph understanding without having to search through millions of data records in order to come up with the answer. Is that not somewhat similar to the ontology of Palantir? Is it something that is similar to the sort of Altair RapidMiner of Siemens or Altair? Is that the space that we're talking about, and is that the rationale and what you were missing and why you really bought the business? That's a great question. Caspar, you want to take it? In the industrial space, it's the only one, we believe, that has the combination of knowledge graph that you have very well described and agentic workbench that works with the data, and puts it into the knowledge graph. In that respect, it's fairly unique. Okay. Thank you, Caspar. Thank you, James. Look, all right. I think that now it's time for us to wrap up. Thanks everyone for your time. Thanks, Olivier. Thanks, Nathan. Thanks, Caspar, for your participation. Next time we will reconnect together will be for our H1 results release. In the meantime, let me thank you again and wish you all a very good day. Thank you. Bye. Thank you all. Have a good day. Ladies and gentlemen, thank you for joining. The conference is now over, and you may disconnect your telephones.