Cognex Corporation (CGNX) Earnings Call Transcript & Summary

Good morning, everyone. Welcome to Cognex' 2025 Investor Day. We're thrilled to have you with us whether you're joining us here in Nadi or tuning in via webcast. My name is Greer Aviv, and I'm the new Head of Investor Relations here at Cognex. So just for housekeeping purposes, the full presentation is available on the Investor Relations website and a recording will be posted. A quick note, our expectations, which are subject to risks and uncertainties. Please refer to the safe harbor language regarding forward-looking statements. Today is all about giving you a deeper look into the strategy, innovation and people that power Cognex and sets us apart in the market. To start the day, Rob Willett will take the stage to present. We are Cognex with a focus on who we are, our culture and our 2024 [indiscernible] then Matt Mosher will share our market opportunity, his vision for the future of Cognex and outline our long-term strategic objectives and preview the financial framework that supports it as he steps into the of CEO. From there, [indiscernible] will walk us through the cutting-edge AI technology that drives our innovation. Shiran Salem will follow with an overview of our comprehensive ecosystem, and Carl Gerst will explain how our direct sales model gives us a competitive edge and drives customer experience. After a morning Q&A session with [indiscernible], Shirin and Carl, we'll break for product demos and lunch. Please note that this portion of the event will not be webcast. The webcast will resume at 1:15 p.m. when Dennis Fehr will present the financial framework detail and the capital allocation strategy that supports our growth strategy. We'll wrap up the day with an afternoon Q&A session with Rob, Matt and Dennis, giving you the opportunity to ask additional questions. Thank you again for joining us. We're excited to share our journey with you and to show you how Cognex will continue to lead the way in AI-powered machine vision technology. Before I welcome Rob Willett, CEO to the stage, please take a moment to enjoy the brief video about Cognex. Thank you. [Presentation]

Good morning, everyone. Thank you for joining us. Today, you will hear from Cognoids about progress we are making in our business and with our technology. I'll begin with key messages, which you will hear throughout today's presentations. As a high technology growth company, Cognex is built on a foundation of innovation. Our long-term commitment to R&D is a core strength that sets us apart. We are proud to be recognized as the technology leader in our industry. Our leading-edge software and AI tools, the accuracy and speed of our vision systems, our deep domain expertise and the intense close technical relationships we have with the world's leading manufacturers of discrete products, gives us a strong competitive advantage and creates significant barriers to entry. Today, you'll hear how we're focused on leading in AI-enabled machine vision technology, providing the best customer experience and executing on plans to double our customer base over the next 5 years. You will also hear how our financial strategy will focus on high-margin growth, strong cash flow generation and a disciplined capital allocation approach that supports long-term value creation. And those of you who are here in-person will experience some of our unique motivational culture as Peter Drucker is credited with saying culture eats strategy for breakfast. Our culture allows us to attract, empower and retain the best talent in an industry where innovation and intellectual property are key to success. Many of you are already well acquainted with our company. But for those of you who are just getting to know us, let me provide a brief introduction. Cognex is a technology and growth company. We have an exceptional brand based on our leading technology, deep customer relationships and a direct to sales -- a direct sales approach with more than 30,000 customers. In 2024, we generated more than $900 million in revenue. We have a global footprint with about 2,900 Cognoids around the world, and a revenue mix that reflects our global presence. Over the past decade, Cognex has consistently delivered strong financial performance, achieving an average adjusted EBITDA margin of 28%. You'll hear more from Matt and Dennis about how we're sharpening our focus on bottom line profitability and how this emphasis fits into our broader long-term financial framework. Turning to what we do. Everything we do is based on machine vision, the technology that gives computers and automation equipment, the ability to see. A vision system operates much like human vision, your eye is a sophisticated optical device like a camera. It captures information and sends it to your brain, which makes sense of it. In machine vision, an imager, lights and lenses are used to capture data. That data is sent to a processor where vision tools or algorithms interpret it. Software is at the core of Cognex technology. It is the brain of machine vision, and we are a company of cognition experts from which our name Cognex derived. Replicating vision with a 99.99% accuracy required in manufacturing takes a lot of technology and know-how, which Cognex has spent over 40 years developing. At Cognex, we focus on machine vision for the most challenging applications performed on high-speed production lines in manufacturing and logistics. It's something we do better than anybody else. It is this technology leadership and culture of innovation that have led to a strong track record of growth. It has resulted in nearly 15% annual growth over most multiyear periods throughout my tenure as CEO. As you can see, our business has a cyclical nature, often influenced by major technology transitions and growth has, therefore, not always been in a straight line. Due to COVID era over investment, combined with high interest rates and a more challenging macroeconomic environment in some of our end markets, the past few years, have presented headwinds for Cognex and our competitors. That said, we returned to growth in 2024 driven largely by inorganic expansion. Later today, Dennis will walk you through our growth formula, including the expected contributions from each of our vertical markets. Let's stay with 2024. It was a year marked by strong execution on our three strategic priorities: from advancing our technology to expanding our customer base, and strengthening operational discipline, 2024 was a pivotal step forward. Specifically on those three priorities: one, in 2024, we expanded our portfolio of machine vision products powered by world-class AI, such as the Insight L38, the industry's first AI-enabled 3D smart camera. Our newest products not only provide powerful functionality that allows customers to solve problems in a more human-like way, but also are significantly easier to use, integrate, operate and sell. These products are, as our slogan says, Advanced Machine Vision Made Easy. And because they are easy to use and sell, they allow us to reach less technically proficient customers who have historically been unprofitable for us to serve. So two, we are evolving our sales force to bring our newest technology to a significantly larger universe of customers, one that we estimate is 5 to 10x greater than the 30,000 we serve today. This new structure has already delivered strong results. The original class of entry-level sales noids that we trained and deployed to the field in the start of 2024 completed over 80,000 customer visits, ramped to sell $1 million per week, while also referring nearly $10 million in business to our other sales engineers. This program is significantly expanding our market coverage and unlocking meaningful growth opportunities. The cohort we hired in mid-2023 added more than 3,000 new customers in 2024. These early outcomes validate our strategy and demonstrate the power of aligning talent, technology and structure to drive scalable growth. Building on what we learned, the second class of these sales noids were hired in mid-2024 and entered the field at the start of the year. They are ramping nicely. Three, last year, we successfully integrated Moritex, the largest acquisition in Cognex's history, this milestone enhances our ability to deliver more complete machine vision solutions combining advanced lighting and optics with our industry-leading systems. It has significantly grown our presence in Japan and the scale and competitiveness of our semiconductor business. Importantly, the integration has been smooth and is already contributing positively to our bottom line, reinforcing the strategic and financial value of the acquisition. And now I'm pleased to introduce Matt Moschner. As many of you heard on our Q1 earnings call, Matt will succeed me as CEO effective June 27. This transition is the result of a multiyear succession planning process in close collaboration with our Board of Directors. Since joining Cognex in 2017, Matt has quickly risen through our leadership rank. He was one of several high-potential leaders developed through our succession and leadership development program. Over the years, Matt has successfully navigated both challenges and opportunities demonstrating strategic vision, operational excellence and a deep understanding of Cognex and our markets. The Board and I are confident that he is the right leader to guide Cognex into its next phase of growth. Without further ado, please join me in welcoming Matt Moschner.

I want to begin by first thanking Rob, on a personal note for his mentorship over the last many years and the incredible legacy that he leaves behind at Cognex. Thank you, Rob. I also want to thank all of you, our investors, our shareholders, our partners and other stakeholders. For being here today, for your continued support and interest in Cognex. The last few years, as Rob mentioned, have been challenging. But I'm excited to step into the role of CEO at what I feel like is an incredibly pivotal time for the company. Since I joined Cognex in 2017, I've seen firsthand the power of our technology, the strength of our culture and the passion our teams bring to solving some of the most complex manufacturing and automation challenges in the world. Looking forward, I only see potential. Cognex has always sat at the intersection of breakthrough technology and real-world tangible impact. It's what I find so exciting about working at Cognex. But today's market environment feels different. Technology is changing faster because of AI. The world's supply chains reshaping in ways that maybe we wouldn't have even imagined 12 months ago. And our customers' needs for automation and machine vision are deepening because of rising labor costs and regulations, and our competitive dynamic within machine vision continues to evolve. It's times like this that Cognex and Cognoids are frankly at our best. Today's agenda is designed for you to see that potential up close. And I'm convinced that when you do, you will feel like I feel every day, which is immense excitement for where we are as a business today and where we can get to in the future. Let's get started. What's the most basic question I think about every day? What makes us so unique, but there's many things. The first and foremost, we are the recognized technology leader in our industry. Our reputation is built on decades of domain expertise, our brand, Cognex is synonymous with excellence in machine vision. Now we back this up with a committed investment in R&D, especially in the areas of embedded computing, optics and of course, advanced AI. And for us, it's not just about keeping up with our industry. Our job is to actively shape our industry. Second, we operate within a large growing $7 billion market, one that spans a diverse set of industry verticals, customer types, geographies, from logistics to pharmaceuticals and automotive to consumer electronics. And with a projected 10% to 11% market CAGR through cycle, it gives us a strong base to build from in reaching our own growth ambitions. Third, our direct sales model allows us to connect with end users at every stage of their buying journey. This hands-on consultative sales approach enables us to more deeply understand customer needs and build sticky long-term relationships that drive loyalty and repeat business. For those that joined us at yesterday's pre dinner, you would have gotten a sense from the customer panel that we had. Fourth, we work with some of the world's most sophisticated machine builders and end users. In these partnerships, many of which span decades are a testament to our credibility and technical excellence. As you will hear later today, we see significant potential to expand our customer base even further as much as 2x larger than it is today over the next 5 years. Fifth, our software is embedded directly on device, and those devices are tightly integrated into our customers' operations. The combination of these two things allow us to command software-like margins, which is a powerful driver for our own long-term profitability. And sixth, our capital-light business model enables us to generate consistent, high-quality cash flow, while maintaining a robust and healthy balance sheet. This financial strength gives us the flexibility to invest in growth, return capital to shareholders and navigate uncertainty without compromise. Now Rob mentioned that underpinning all of this is our unique culture. It drives how we collaborate, how we solve problems and how we continue to push the boundaries in an evolving industry. Let's double-click into the market verticals that we serve. At Cognex, our success has been driven on a laser focus on the right industrial sectors. Those sectors that, where our technology delivers the most value and where demand for automation continues to accelerate. Our journey as a company, began in semiconductor, where precision and reliability [indiscernible] we expanded next into automotive, electronics, where automation drives quality and efficiency. And more recently, we've made significant inroads in logistics, a sector undergoing rapid transformation e-com and other supply chain innovation. Later today, Dennis will walk through our growth expectations by each of these market verticals. We'll break down how much of that market growth is driven by underlying market dynamics and how much is expected to come from increased vision penetration, and we'll unpack what that means. Let's start with logistics, which is now our largest and fastest-growing end market. After a brief post-pandemic pause, where the industry took time to absorb a lot of the excess capacity that Rob mentioned, growth in this sector has sharply reaccelerated. Our Q1 results, we reported double-digit year-over-year growth logistics revenue. That marks our fifth consecutive quarter of growth and the highest level we've seen since Q1 of 2022. Now the broader trend towards online order fulfillment is clearly here to stay. And from an automation standpoint, we believe logistics is still very much in the early innings. You'll hear more about our strategy to capture this growth during the logistics product demos later today. Let's move to automotive, which has been historically our largest and most enduring verticals over the last several decades. Now machine vision and automotive is deeply embedded in every stage of vehicle manufacturing for measuring inbound parts to guiding robotic assembly to inspecting fine details like the leather stitching on a new seat. This market, as we've talked about before, has faced significant headwinds last year, and we've seen that softness continue into 2025. We expect a more moderate decline this year, while we remain very optimistic about the long-term outlook for automotive. While the increasing complexity of vehicles, higher inspection requirements, and a transition to electric and autonomous vehicles, all play to our strengths. You'll see this firsthand during our automotive product demo session later this afternoon. Next is packaging, which has emerged as our third largest market vertical. This segment, just as a reminder, includes both fast-moving consumer goods as well as health care-related industries. Growth in packaging has been driven by increasingly stringent regulation, traceability, quality and compliance requirements, making machine vision not just valuable but essential. We also see significant growth opportunities in this market through additional penetration. And it's why we've been investing to transform and expand our direct sales force to reach a broader section of customers in packaging with products that are easier to use and faster to deploy. You'll hear more about our market creation opportunities from Carl and during the packaging demo session over lunch. Let's move on to consumer electronics. While we haven't seen major form factor changes in recent years, we believe the next wave of innovation in this market is on the horizon. The emergence of wearables, foldable devices and other AI-centric consumer hardware could drive outsized growth. These next-generation devices will be produced at massive scale, will be increasingly complex to manufacture, making precision and reliability more critical than ever. At Cognex, we have long-standing relationships with some of the largest and most sophisticated players in consumer electronics. As they bring new technologies to market, we expect to remain their partner of choice. And that brings me to semiconductor, an industry where Cognex has played a critical role for decades. Our acquisition of Moritex in 2023 brought with it even more depth with key semi OEMs. And together, our advanced machine vision technology are essential to modern chip manufacturing. We continue to see strong widespread growth in semi, fueled by demand for high-bandwidth memory chips, which are foundational for next-generation computing and AI infrastructure, which has been built out as we speak. With our proven technology and deep relationships, we think we're well positioned across all of these verticals for growth into the future. Let's turn to our served market. Just as a reminder, we focus at Cognex on our served market, which we define as the total value of business that our products are designed to win. In other words, it's not just the overall market size for machine vision, it's the portion of that market where our products are directly applicable. Today, as I previously mentioned, we sized our served market at approximately $7 billion globally with a balanced split across market verticals that I just described. Cognex holds a strong competitive position in this overall market, and that share position, we think, is in the mid-teens. On the right-hand side of this slide, you can see the key developments, which have led us to revise this estimate since the last time we updated you on Analyst Day 2022. We've added new market segments. We've modified some of the vertical groupings, and we've adjusted for exceptional events like COVID. And there are several key secular growth trends that drive machine vision adoption across each of these verticals. Let's talk about each of them. First, manufacturers are under constant pressure to do more with less. Machine vision delivers the precision and consistency needed to reduce waste, minimize defects, drive down costs without compromising quality, frankly, on products which are increasingly difficult to make. Smaller components and tighter tolerances plays an added emphasis on automation in production. Second, thanks to our investments in AI and other technology advanced machine vision is easier to deploy than ever. Once required complex integration, specialized expertise is now much more accessible and approachable by our customers. This means faster returns on investment, lower project risk, which allows them to think much more ambitiously about where they apply vision. Third, a shrinking labor pool and aging workforce are reshaping global manufacturing. According to a recent Deloitte study, the U.S. manufacturing sector alone is expected to face a shortfall of labor by of 2.1 million unfilled jobs by the end of this decade. As a result, the cost of labor has been increasing at a faster rate than productivity. This gap, this growing gap underscores the need for automation, and it's a powerful tailwind for machine vision growth. And fourth, as companies around the world evaluate more regional and potentially less global supply chains, automation becomes table stakes. Think of this trend as almost an amplifier of the other three, adding only more urgency to customers needs to adopt vision across operations. So in this market context, I'm moving intently to evolve our value proposition. Over the next few years, I will transient Cognex from a traditional provider of machine vision products, to a future-ready AI-driven vision platform, which can serve more customers and deliver the best customer experience in the industry. For decades, Cognex is one because of three things: we have the best vision tools to guide and spec, gauge, identify with unmatched speed and precision. We have financial stability to give customers the confidence that when they work with us, we can support them in the near and over the long-term. And we're a global business, and we have a global presence to enable them to standardize their operations across continents. To be clear, these things are still core to our value proposition and will remain so. But as I mentioned, the world is changing and so must we. There are three areas I will be most focused on. The first, we're taking our nearly 10 years of advanced AI leadership to the next level, on creating new game-changing vision tools to reimagining the product design more holistically to streamlining how customers get support, advanced AI will broadly reshape how customers experience Cognex. A good example is human visual inspection, something we've talked about over the years. Today, we think there are tens of millions of people deployed in manufacturing facilities around visually inspecting products made. In the past, with traditional vision tools replacing these human operators has been very challenging, given the sheer diversity of defects that they aim to avoid. But with today's AI tools, we see a path to addressing these applications and unlocking new applications for Cognex vision. Next, we're going to make machine vision easier to use and easier to deploy than ever before, delivering a more seamless customer experience from pilot to production. This ease of deployment not only enhances the customer ROI, but also lowers the barrier to adoption across a broader cross-section of customers. A good example of how we're already doing this is a product we recently released the DataMan 290 Series which you will hear more about later today. With this product, we have completely reimagined the set of experience, designing a highly intuitive workflow and the ability to auto configure the with a single button press, what has historically taken hours now takes minutes. And with this intense focus on ease of use, I will transform the business. And finally, we're launching a comprehensive product ecosystem with hardware, software, services and support designed to help customers standardize on Cognex globally. This actually is a strategy that I have been leading for several years, while leading our product and engineering teams. Our ability to develop technology in a common way not only helps our customers move more easily between our products, but drive stickiness with them, all while letting us to be much more efficient with R&D spend. So this evolution of our right to win will let Cognex redefine what's possible in machine vision and continue to build the future of automation. At the same time, we will transform our go-to-market and broaden our customer base through targeted investments in our sales force. As we've mentioned before, we think of our market as a [indiscernible] and historically, we've done very well with customers at the top of that pyramid, who are some of the world's most tech savvy and bring some of the most complex manufacturing challenges. They value our technology and they value our highly collaborative working style. Today, as Rob mentioned, we serve approximately 30,000 customers and believe that below that line lies as many as 5 to 10x more who are smaller or regional automation players. Through our investments in our sales channel that we started in 2023, coupled with innovations like edge learning, which make vision easier to deploy, we've added approximately 3,000 new customers across geographies and verticals. We're seeing promising early wins from these investments and over the next 5 years as we mentioned, our goal is to double the number of customers that we serve. I have three strategic objectives for Cognex over the next 5 years, which I already mentioned during our Q1 earnings call. First, we will be the #1 provider of AI technology for industrial vision applications. We will accelerate innovation by continuous investment in AI, product development and platform capabilities to stay ahead of customer needs and lead industry trends. Second, we will provide the best customer experience in the industry, delivering seamless engagements from first interactions full-scale deployments through our direct sales model, a unified product ecosystem and significantly upgraded customer support capabilities. And third, just to repeat myself again, we will double the number of customers we serve by scaling our go-to-market engine and reaching new segments, geographies and verticals. Now if you take these three objectives together, I expect this focus to yield significant results, including us achieving a #1 or #2 position in all major markets that we serve. We've designed today's agenda to clearly outline and support this strategic direction. Each speaker will highlight a key pillar of this growth strategy. Starting with [indiscernible], we will showcase our innovation and leadership in AI technology, emphasizing how differentiation and long-term value for customers in Cognex. [indiscernible] will explore the power of the Cognex ecosystem, illustrating how our integrated solutions deliver measurable benefits to our customers. And [indiscernible] will explain how our direct sales model creates a competitive advantage, enabling us to expand our reach and attract new customers. Now the successful execution of these objectives will sustained growth and ensure expanded profitability, which are both critically important to us. At a high level, our financial framework is designed to deliver consistent long-term value creation through economic cycles. And we focus on 3 core metrics that reflect our discipline and growth, operational efficiency and capital allocation strategy. First, we target a 13% to 14% compound annual growth rate in revenue, driven by innovations and strategic market penetration and an approximate 3% contribution from M&A. Second, we will achieve 20% to 30% adjusted EBITDA margin, which reflects our committed operational excellence and cost discipline. And third, with free cash flow consistently exceeding net income, our greater than 100% conversion rate underscores strong cash generation and working capital efficiency. To provide deeper insight on our financial trajectory later today, Dennis will walk through this financial model in more detail, including the key assumptions that underpin each of these levers. I want to thank you all for your time this morning and throughout the day. I will be available for Q&A, along with Rob and Dennis in the concluding session, and I look forward to answer your questions at that time. It's now my pleasure to welcome to the stage [indiscernible] to talk about our industry-leading AI. Take it away, redo.

Thank you, Matt. Hello. My name is [indiscernible] I lead the AI R&D and Vision tool development at Cognex. I've joined Cognex in 2017 through the acquisition of [indiscernible] an AI startup founded in 2012 in Switzerland. Overall, I've been active in the domain of machine learning, deep learning AI for over 25 years and the ever since I've joined Cognex, I've been working on getting exciting new AI technology into all our products. Today, it's my industry-leading AI technology and how it permits us to compete with open source ready available models. Because that is a question we [indiscernible] how does Cognex compete with open source and specifically 20 years ago, that was with respect to OpenCV. OpenCV is a computer vision library that was originally developed by Intel and was then released in the public domain in the early years. It is an election of basic low-level vision tools that are used for -- do you want to quickly check maybe? Right. So OpenCV is a collection basic low-level vision algorithms. But to this day, it does not provide higher level, optimized tools like Cognex that provide capability, speed and robustness beyond those basic vision algorithms. Over the last couple of decades, Cognex has not only released advanced vision tools that dramatically improved the capability of rule-based machine vision. We have created tools whose name is synonymous for the best-in-class vision technology. In 1997, we released PatMax, a tool that still today is state-of-the-art in fast and accurate part localization. IDMax has set new standards in code reading. Hotbards is a technology that dramatically improves our capability to read 1D codes at very low resolutions. And HR+ improves image quality such that we can also deal better with images with natural scenes that have a large range of contract patients. Now today, we face that same question again, but with a twist. [indiscernible] Cognex compete against open source in the age of AI. It's a fair question. The number of publications and models that have been released into the public domain, ever since the early days of deep learning in the 2010s has the increased dramatically. But the last 2 to 3 years, this number has exploded since we are in our latest AI hype that got started when the world was introduced to ChatGPT and AI generative. But in order to answer the question of how does Cognex compete with open source in the age of AI, we have to better understand what is the difference between generic computer vision and industrial computer vision. ImageNet is a large collection of images and it has been instrumental in advancing AI in vision research. And still today, it's basically the foundation of practically every AI open source model out there. On the right, we see a typical example of a computer an industrial computer vision task. As you can see, these images look nothing like what you would see in ImageNet, it's not a natural image. It's highly task-specific and oftentimes for myself, I suppose [indiscernible] just as well. We don't even really understand what these images show. They manifest complex sectors complex backgrounds. And oftentimes, the visual features and properties that are required to say whether that specific image is a pass or a fail are actually very small and very hard [indiscernible]. And so not surprising that open source off-the-shelf models don't do very well on these kind of tasks. So in the following, I would like to lay out the four main reasons: or four main ingredients that we actually need in order to make AI [indiscernible] It's accuracy. It's ease of use. Its efficiency, speed and its scalability. Let's start with accuracy. In a typical industrial inspection application, we need accuracies of 99% or more. Let's imagine we have a production line that runs at about 600 parts per minute. If we would have only 1% of falls accept, that would mean that within 1 shift or 8 hours we would basically miss more than 2,800 faulty parts. And that's clearly not where we can be. So let us now compare a Cognex model against a state-of-the-art vision language model on two different computer to pass. The first is a generic computation task. It's like imagine classification. As you can see, both models are somewhere in the mid-80s and that is probably good enough of a human interactive chat bot because the human hopefully, is doing some sort of a plausibility check or at least you should be. But for industry, for the factory automation, we strive for 100% full automation. And in that context, as I just laid out before, this is not viable. On the other hand, now let's look at the industrial computer [indiscernible] here to say the same images again. I will now explain to you what we are seeing here. So this is a plug, frontal view of a plug. And basically, what we need to do is we need to inspect these two metallic pins in the center make sure that they are not effective, make sure that they're properly aligned and that they are in their respective slots. So naively, we basically can take that open source station language model and give it the following prompt, are the 2 metallic pins in the center properly aligned within their respective slots. As it turns out, that first prompt did not work out very well. The performance very low just barely above chance. And so after quite a bit of trial and error, prompt engineering, we found out that the model is actually not understanding what we mean with a metallic pin. So it's only once we started to call these metallic pins, metallics fears that the model started to understand what we mean, but we didn't really get it much above the low 90s as you can see here. In contrast, for the Cognex model, we used five samples of good parts, five samples of bad parts, and then that was enough for the model to reach 100% accuracy. Next up is ease of use. So our systems are deployed into challenging environments. And therefore, it's very important that they are easy to train and easy to maintain, In order to train an AI model, you need to collect samples, you have to take images, you have to label those images. And you can imagine that the effort to do that is directly correlated with the number of samples you need. And so Cognex, we've developed a proprietary technology we [indiscernible] Edge Learning that allows our models to train for much fewer samples, whereas reaching a target [indiscernible] so we can learn from tens rather than thousands, as you can see on this illustration that allows us to reach a certain target accuracy much faster. And thus, these models are much easier to train, much easier to deploy, but also much easier to maintain. Another constraint we face when deploying our models into factories is the often harsh and very demanding environmental conditions. [indiscernible] deal with IT, with heat, with vibration. And moreover, our customers would like to deploy these malls into small compact and cost-effective packages. So the ability to run these models on an embedded rugged hardware is not just a nice to have, it's essential. And coming back to our comparison. So here, we see that our model, since it's several hundred times smaller can run at line speeds on [indiscernible] and on that, [indiscernible] hardware using around 8 watts of power. If we want to do the same thing with that open source model, which is built from 7 billion parameters, we would need several large discrete GPUs running in a workstation or in a cluster thereof. Thus, we have optimized our model specifically to be able to keep up with modern production lines while keeping the accuracy and all of that in an efficient, easy to deploy industrial form factor. Moving on to scalability. Even though edge learning allows our customers to train and deploy their models much faster. It's still a fair amount of work. And so once we've trained the model on a specific production line, wouldn't it be great if I could take that same model and use it for the remaining 19 identical production lines that are in my factory. Now the issue is that if you take images from these different production lines, and you see here an example of EV battery cells. Even though those lines are supposed to be identical, the images still look quite a bit different. Now you may say, they don't look different do they. Well, given that we're looking for small defects and we want to be as close as possible to 100% accuracy, these differences actually do matter very much, as you can see on the right, that normal model drops quite a bit in accuracy once we move from Line A to Line B. And so last year, we released a new series of models, so-called robust models that are much better in keeping up that performance. They can deal with these type of environmental changes, like changes in elimination, slight changes in camera position or camera angle, different focal play. They keep up that accuracy while moving from Line A to Line B. Similarly, in mere move more and more towards high-mix, low-volume manufacturing. And so similarly to the ability to move from 1 line to the next, we would like to be able to move from 1 SKU to another, so here you see an example of cosmetic products. It's a different product, but they all share the same issues at the same potential defects. And typically, we're looking at air bubbles under the label we're at wrinkled labels. And so now instead of training for each of those products separately, what we would like to do is to be able to train on 1 and then transfer that from one product to the next. And so we've invented a new technology that allows our customers now to basically learn those defects, air bubbles, wrinkles while not being specifically reacting to the change in the actual appearance of the product itself. And again, as you can see on the right, that allows us to keep the accuracy high when we move from one product A to product B, which is not true for the normal model. So similar to our journey in rules-based machine vision. Cognex has been leading the way in bringing the benefits of AI technology to industrial manufacturing and inspection. We've created value for our customers by addressing the most pressing and most blocking issues. And in 2022, we have released our first edge learning product, the technology, as I mentioned before, that allows us to train from as few as 5 to 10 images. We've then brought that same technology to the 3D world by bringing AI to make easy-to-use robust, but yet very precise measurement applications. Then earlier this year, we've released a transformer-based version of our few shop technology that allows us now to not only train from very few samples, but to actually keep up with the accuracy of models that have been trained on hundreds or thousands of images. And also this year, we have released our first AI-based DataMan barcode reader, the DM-29, where AI helps us to simplify and accelerate the setup process dramatically, but also at the same time, AI allows us to read codes that were previously not readable. Something that I myself would not have expected to be possible just a couple of years ago. So let us now dive into this last example a little deeper. So for an AI reader -- ID reader excuse me, the setup process is key to get highly accurate and fast and reliable reading results. And so in a rules-based traditional reader, I would say. As you can see here on the right, the screen chart, this setup process can be quite cumbersome. And you have to -- specifically, if you're looking at codes like here to the right, at the left, the direct part market or so-called DPM codes. For an experienced user has to explore a high-dimensional configuration space in order to find out what is the ideal camera position, distance, angle, what choice of illumination gives the best contrast, but also how to set up all the different parameters that control the actual reading strategy. So let me now show you how this is done with the new DM-290. In the first step, we set the part in front of the camera of the reader, we make sure that the code in principle is visible, albeit here, it's not readable because we have these specular reflections and pretty poor contrast. And so now in a first step, we instruct the AI to do a rough analysis of the camera position itself in order to provide feedback to the user of how to position the camera in order to move closer, whether to move further away. And as you can see here, we're in about the right spot. And then we instruct the AI to start the tuning process. Now in order to do that, we cannot explore the complete configuration by the high dimensional conjugation space that will take too long. So we have trained an AI model on many, many similar situations such that they can learn of how to find that optimal operating point more efficiently. And it's this process that you see here in action. Also, we've introduced a new AI enhancer, which is a tool that allows us to clean the codes, but also to correct certain defects such that we can read codes that previously were unreadable. And then at the end of the process, the tool offers 3 -- the choice of three different optimal operating points from which an experienced user can choose the one that they like most. And you will get the chance to see this setup process in more detail in our upcoming auto product demo session later. So to conclude, I would like to reiterate the four key ingredients that our customers ask to get AI successfully deployed into factories. We need 99% or more accuracy. The customer also wants to have something that is easy to train, easy to deploy ideally from as few samples as [indiscernible]. Customers don't want their production line to be slowed down by an inspection process. So we absolutely have to be able to keep up with line speeds. And also, customers would like to be able to take that investment they put into 1 training, 1 model and be able to scale that to different sites, different lines, but also different product SKUs. And we at Cognex have invented and released unique technology, tools and products to address each one of these requirements. Nothing that we see in readily available open source software. And now with this, I would like to hand it over to Sharon Selim, and she will be speaking, among other things, how these different tools and technologies I've talked about here tie into the Cognex ecosystem.

All right. Thank you, Reto. So good morning to all of you. I'm Shirin Saleem. I lead the software and applications, engineering organization at Cognex. My teams leverage the cutting-edge AI technology you heard Reto talk about. We went into our products and make it available to our customers. A little about my journey. So I joined Cognex in May of 2023, 2 years ago. After a long career in Amazon in the Alexia AI Group. I worked on far-field speech recognition, national language understanding and building translation powered experiences for millions of customers prior to coming here. Picking up from Reto, I'm going to talk about the foundational role AI plays in our comprehensive ecosystem, raising the bar in terms of how customers interact with our products, how they solve machine vision applications and experience our products. So what is the system, what makes it comprehensive and why does it matter. Our machine vision ecosystem is comprised of a complete lineup of products, serving different personas of customers. They range from the Novus line operator to a sophisticated machine builder. Our products support different types of applications, ranging from 2D to 3D, simple to complex. They are built on a common software and hardware platform, which plays an integral role in standardizing the customer experience and incentivizing our customers to adopt more of our products and not migrate to vendors for new applications. AI technology is an integral part of our portfolio. We offer both deep learning technology that delivers the highest accuracy for complex and data-rich tasks as well as edge learning technology. for simpler tasks that can easily be trained or adapted to a customer's application with just a few images directly on the device. And today, I'm very excited to announce that we have a new alert in our ecosystem, a cloud offering that makes it even easier to incorporate advanced AI models into our product lineup. We issued a press release on that offering after markets closed yesterday in case you haven't already seen it, and I'll talk more about that shortly. But our competitors both established players as well as the newer startups. They may offer one or more of these pillars, but none offers an ecosystem that is as comprehensive and rich in advanced machines. So let's talk a little bit about what makes our ecosystem attractive for our customers. Let's start by imagining a day in the life of a sales engineer visiting a customer. He or she will typically introduce the Insight 2800 series of embedded vision sensors. It's designed to solve common 2D applications. The sales engineer, after talking to the customer may realize that the application requires more speed and more capabilities in the 2800 series can offer. So what does the engineer do? He or she can then offer our advanced Insight 3800 series of vision systems that has the same easy-to-use tools in the same software environment, but with better performance as well as higher resolution and lighting options. This provides a more effective solution for customers that have applications that require a higher level of performance. Now in other cases, a customer may have a new application, one that requires precise 3D measurement, such as inspecting the height of small wins on a PCB. The sales engineer can then recommend the AI-powered L38 on the very same software platform, but offering advanced imaging to capture detailed 3D images and analyze depth information. The customer already being familiar with the vision tools and software can transition more quickly to the new product, transferring all of their prior work. They do not need to invest in extensive retraining or reconfiguration or reintegration with their PLCs. The standardization of cabling and mounting allows them to follow a familiar setup process and Cognex application engineers, whom customers have developed strong relationships with and who have an in-depth understanding of their use cases are still highly effective in providing solutions tailored to their needs, even with a new product. Our journey towards a common platform actually started several years ago with the goal of improving our own internal efficiency. But over time, we found that this approach has become an important selling point for us, saving time and cost for our customers. You will hear more about how our sales force is organized capitalize on the benefits of both the flexibility as well as the commonality of our ecosystem from Carl in the next section. Let's talk now a little bit about the role of AI in our ecosystem. So we offer both the deep learning vision tools and edge learning tools across our products. So let me read again, deep learning tools are designed for complex applications that require high accurate, but also thousands of images to train. Edge learning tools, they're designed to be quickly trained on an embedded platform with just a few images, but they work best for applications that are not too complex. We offer these options across our embedded and vision software products. We allow our customers to make the right choice depending on their applications. But as we talk to our customers, we found that we have room to make the experience even better for them. Customers do not want to be making that trade-off between accuracy and ease of use, they want both. And if they do need to make that transition from edge learning to deep learning, they want to do it seamlessly without having to redo the work they previously did. I am excited to announce OneVision, first fully released cloud-based no-code machine vision AI training platform. With OneVision, our customers can seamlessly integrate state-of-the-art AI models you heard Reto talk about into their vision jobs, and they can access advanced models that offer deep learning performance with the ease of use of edge learning. OneVision is available on the Insight 3,800 and 8,900 series now and will launch on more products in early 2020. With OneVision vision, you can think of our vision systems getting smarter. Customers can train AI models to solve an application, they can then combine it with highly precise rules-based tools of their choice and deploy it across our full family of products. customers could get the benefit of a cloud-based product when they're designing their machine vision system. But then, then they can combine that with all the benefits of edge computing, including low latency infants when they deploy these models on the Insight products. So some of the benefits of the cloud, well, what are they, right, or when you're designing a job. So it offers faster training of AI models on multi-GPU clusters? On the cloud, you have access to advanced AI models and architectures, and we provide built-in tools to distill them to run on Cognex' embedded products. You can do cross-site or cross production line management of projects, which allow for easy collaboration and coordination. OneVision simplifies the entire life cycle of data curation, AI model training, validation, optimization and deployment on our vision systems. Think of the journey starting and ending at the edge. And it integrates with our Insight product portfolio. Let's revisit the PIN example that Reto introduced previously. To recap, the vision task at hand here is to inspect the spins in the center and classify them as good if they align perfectly in the circular hole and bad if they don't. Now the complexity of this task increases when you have lighting and part variations across lines, and it could take hours to configure multiple AI models for each line. Each of them trained on the edge with a few images capturing diversity. Let's see our customer would solve it with OneVision. Step 1, images of the pins collected from one or more lines are uploaded to a common OneVision project. with a push of a button Step 2, using a few labeled images, the customer trains an AI model to locate the pins. Now labeling of the data is fast and efficient, thanks to different modes of AI assistance offered in OneVision, including system in the loop labeling as well as point of labeling. Now once the model to locate the pins is trained, the customer then trains another model to classify the pins as good or bad. Different types of deep learning models are offered. One that works with just a few samples or more advanced models that use more images for training if they are available. At all stages, the customer has access to build an assistance to highlight any corrections or opportunities for further optimization. And finally, once the models have been trained and validated to be robust to cross part variations and lighting conditions, they can be deployed to all cameras across multiple lines of sites. It's easy, it's fast and it's [indiscernible]. So with OneVision, the cycle of the recollection training, validation, deployment and monitoring of AI models, it spins much faster across the entire Cognex ecosystem. OneVision offers benefits for customers in all of our verticals. So our converts in consumer electronics. They typically employ vision engineers with years of experience. That's because they need to design complex vision jobs. With the advanced AI models we have available in OneVision, they can configure the same job with operators who have just days of experience [indiscernible]. In logistics, there is this challenge due to the diversity of different items that are encountered on the conveyor belts, you have to train the models on different types of items for it to be robust. With the powerful compute of the cloud, it takes just hours to train new models on unseen and diverse items, significantly reducing the lead time to adapt to new products. Our automotive customers. They typically need to deploy deep learning models across multiple lines in fact, each with varying production conditions. What previously required hours of repeated effort for each site is now seamless with OneVision's ability to train and deploy across multiple sites on the flight. To reiterate, we are pushing the envelope of AI technology for machine vision. We have a strong foothold in the embedded machine vision market with our comprehensive ecosystem. With OneVision now we can go even faster in embedding these powerful AI tools in the products in our ecosystem. Overall, OneVision strengthens our ecosystem and positions us very well against our strategic objective of being the #1 in AI technology for industrial machine vision. But don't just take my word for it. Why don't you see it in action and hear about it directly from our customers. [Presentation]

All right. And with that, I'm going to pass it on to Carl Gerst to talk about sales as a competitive edge.

Great. Thank you, Shirin. It's wonderful to see so many familiar faces here today. For those of you I haven't met, my name is Carl Gerst, and I've been with Cognex for 25 years. I began my journey at Cognex as the first product manager for our Insight Vision Systems. In 2004, I helped launch our ID products business, which I led for 15 years. What started out as a small initiative grew to represent nearly 40% of our overall business. And a major driver of that growth was our strategic move into logistics. That more recently, I've worked closely with Matt and several others on evolving our product development teams, which has helped build the ecosystem that you just heard about from Shirin. In the middle of last year, I transitioned to lead our sales teams. It's been an exciting change for me. It's bringing me back to what I enjoy most, which is working directly with our customers to understand their unmet needs and finding ways to better serve them. And that's exactly what I want to talk about next. Before we dive into the next section, I'd like to briefly reflect on what we've covered so far with Reto and Shirin. We explored how our industry-leading AI capabilities and our comprehensive product ecosystem are not just nice to have but how they're strategic differentiators for us. These two elements are critical components of our go-to-market strategy and delivering a best-in-class customer experience. As Matt mentioned earlier, we've evolved our go-to-market strategy by making targeted investments in our sales force. This is enabling us to engage more deeply with our largest tech savvy customers and it's also enabling us to unlock new customers with easy-to-use and easy to deploy products. We believe that customer acquisition and customer experience are not separate efforts. We see them as part of a powerful self-reinforcing flywheel. And we take a closer look at that flywheel, you'll see at the center of it is our goal to double the number of customers over the next 5 years. This flywheel is powered by our sales force transformation and our goal of providing the best customer experience in the industry. This helps us build sticky long-term relationships. Surrounding this are three key actions that drive momentum. First is specify your vision. This is where we work with our customers to understand their goals and define the outcomes that they want to achieve. Second is deploy your vision. This is where we bring those life -- those goals to life, and it's tailored through solutions and seamless implementation. Third is support your vision. This is where we ensure long-term success through ongoing support and partnership at every step of the process. A key enabler of this model is our direct sales channel. It allows us to engage with customers across the journey from the initial contact to ongoing support, ensuring consistent high-value experience at every touch point. Let's take a closer look at our direct sales channel. We have two sales teams one that focused on logistics and one that's focused on factory automation. Both of these sales teams engage directly with our customers to understand what their needs are. But the way that our products and solutions are delivered may vary based on the project. So for example, if we're working with a customer and they have an existing line, they may be working directly with us to be able to buy an upgrade to that line with our ID and vision systems. But that same customer may be looking to expand capacity and add a new line. And in that case, it wouldn't be uncommon for that customer to buy those products through one of our partners, such as a machine builder or a systems integrator. The Cognex ecosystem that you just heard about from Shirin plays a critical role in accelerating the success for both our sales teams and our partners. And I'm excited about the launch of OneVision. Most notably the ability to bridge between edge learning and deep learning. Why? Because it enables faster development, it enables faster execution, and it also provides a significantly better customer experience. Additionally, our AI-powered products that you heard earlier about from both Reto and Shirin provide user-friendly guided workflows. And that's empowering both our partners and our customers to move faster. We are focusing our sales team on three themes, each with a dedicated mission. We have a dedicated team that's focused on market creation and expansion. These teams are focusing on acquiring new logos and deepening our reach at existing customers by showcasing products like the DataMan 290. These teams collaborate closely with a more senior sales team who concentrate on market penetration. These customers -- this team is focused on increasing share of wallet within existing accounts by leveraging the full Cognex ecosystem. They also play an important role on supporting new logo accounts, particularly when more sophisticated vision is needed. We also have a team of sales engineers that's focused on supporting value-added partners and helping them move faster. This would include machine builders, systems integrators as well as our automation solution providers. They coordinate efforts between our -- between the partner and the end user, and they capitalize on our unified ecosystem and seamless integration capabilities. Our investment in our sales force has expanded our sales coverage, and it's allowing us to better reach previously underserved customer segments. At the same time, our commitment to AI-enabled innovation has led to the development of market-leading product with feature capabilities such as One Touch AI-powered image formation, AI-guided positioning tuning and decoding. And why are these features so important because it simplifies the qualification and deployment process with our products. You're going to hear more about how we've enhanced our sales reach, combined with these cutting-edge AI capabilities in the upcoming packaging product demonstrations. We see a strong opportunity to grow market share in existing accounts and drive sales by leveraging the power and flexibility of our expanding ecosystem. Tech-savvy enterprise-level customers have long appreciated our ability to solve their most complex applicate. But I wouldn't -- but what that's often required is them to use products that often felt disconnected. Our unified ecosystem changes that, changes streamlines everything, from development to deployment, resulting in better results and a better overall return on investments. This means that customers can start with our 2D systems and seamlessly scale to an AI-powered system when 3D measurement data is needed. And as you heard from Shirin, our [indiscernible] platform now enables customers means that customers can move from using edge learning to deep learning within -- for inspection tasks for more demanding applications and all while staying with inside the same ecosystem. This integrated approach combined with a full Cognex ecosystem is resonating strongly in key markets such as automotive and logistics. And you're going to get a chance to see that after these sessions in our automotive product demonstration. One of the key advantages of the ecosystem that we're building is how it accelerates our sales team and our partners' efforts by offering solutions that are easier to quote, easier to order, easier to install, easier to commission and easier to support. We've long been recognized for our leading-edge technology, but it hasn't always been the most straightforward to implement or to maintain. By transitioning to standardized solutions with guided workflows, it simplified the process for our partners, it's significantly enhancing the customer experience and its improved operational efficiencies. Our focus here has been on logistics and consumer electronics and I can tell you firsthand from spending a lot of time in the field this year, the positive feedback that we're getting from both partners and our customers is incredibly encouraging. And you're going to see this reflected in the upcoming logistics product demonstration. I now want to turn to customer experience and take a closer look at what we mean by specify your vision, deploy your vision and to support your vision. First, specify your vision. We're empowering our customers, providing the tools, guidance and flexibility they need to define their own path forward. We've transitioned from expert-driven setups to self-guided automated workloads. This is enabling our customers to reduce specialized resources and its improved overall scalability and is providing a stronger return on investment. Through a connected product ecosystem, we're beginning to deliver a more personalized experience with features like guided learning and AI-powered agents that can answer application-specific questions. What's this doing for us? It's enabling our customers to work more independently and autonomously, and what that in turn is doing is enabling our teams to engage in more meaningful and consultative interactions with our customers. What excites me most about the evolution of our product ecosystem that was highlighted by Shirin is rather than presenting a disconnected mix of products to our customers, we now can offer a comprehensive integrated ecosystem. This is allowing our customers to more quickly specify our solutions for new applications, it's accelerating market penetration with an existing account, and it's also helping us attract new customers as well. Second, deploy your vision. We've streamlined the deployment of our vision systems. And this is delivering confidence with our sales teams, our partners and our customers. On the software side, we've evolved from delivering custom solutions that were built on legacy architectures to app-based models that are based on scalable software architectures. This shift has enabled the creation of guided workflows that you're going to see in the demonstrations. It's not only efficient, but it's also designed to scale seamlessly. On the hardware side, we've moved from bespoke resource-intensive solutions that were often tailored to individual customers to standardize hardware offerings that address a wide range of market needs. This has led to faster deployments and significantly improved operational efficiencies. Together, these advancements are driving the automation of workflows, which is resulting in streamlining installations, reducing the need for skilled labor, ensuring seamless integration and optimal performance across the board. Third, support your vision. Our investments in a digital platform is transforming the way that we're connecting with our customers. It enables us to deliver seamless integration and drive success through every stage of the customer journey. By being digitally connected, we can now offer proactive real-time support through our My Cognex customer portal. This allows us to accelerate issue resolution and it's helping our customers maximize uptime. These digital capabilities allow us to not only connect with our customers, but it's beginning to enable us to connect directly with our products. And that's enabling us to do things like remote diagnostics, an automated triage when issues arise. And all of this is helping us improve our responsiveness with our customers. These digital services are enabling us to deliver teller support solutions that address a wide range of customer needs. We're still early in our digital journey, but the impact of enabling connected support at every step of the way has already surpassed my expectations. So I'm going to end where I started. We believe that customer acquisition and customer experience are not separate efforts. We believe that our direct sales channel, along with our comprehensive product ecosystem, our strategic differentiators that enable our goal of providing best-in-class customer performance, and ultimately doubling the number of customers that we serve. [indiscernible] Reto and Shirin to join me on stage, where we'll be happy to answer your questions. We're just going to set up some chairs here.

Before we jump into questions with Carl, Reto and Shirin, please note that we have 25 minutes for this Q&A session. [Operator Instructions]

Good morning, everyone. Thanks for the great [indiscernible] held today. We think historically about machine vision and sort of the hurdles to adoption, I guess we think about like a big expensive piece of heart that had to be off to the side of a production line. But is costs no longer the main issue given all the advancements that you've had in the technology and being able to put it into a smaller form factor. Is it related about education and sales coverage? Or is that -- how would you think about what the biggest issues are today for customers in terms of adoption of machine vision more?

So the question is, whether cost is a driver or whether more broadly, there's other elements that are been important to it.

Right. Exactly.

Yes. For those of you that were at the customer session last night, I think you heard quite a bit about this. I mean I think cost is always a driver, right? But what else are they thinking about when they're thinking about implementing a vision system. So they're thinking about the cost of the product, they're thinking about the cost of integration, about the cost of long-term support. And I think more and more for us, what we're looking at, I think we've often in the past, focused on the technology and providing the best technology. But what we see is that we can help [indiscernible] or lower their overall total cost by providing a significantly better customer experience. And I think the ecosystem that you heard about from Shirin as well as the tools that you heard about is helping us really lower the customers' total cost of ownership, total cost of ownership. But often, we think is being beneficial by enabling us to sell products at a higher price.

All right. That's all [indiscernible]. First or and just a quick one on the OneVision cloud offering. I mean is the pricing model different versus selling just a piece of hardware today. And now is there subscription component when you've got a customer that's being plugged into the cloud offering?

Yes. So the question is whether there's going to be a different pricing model with OneVision. What I would say is that we're not going to talk specifically about that today. Really our focus on the second half of this year, if you saw the press release, is we're really going to be focusing on select customers. And the key thing that we is really the customer experience. And I've seen this play out in real time, right, where customers -- some of the -- I was out with customers over this year and the feedback was your edge learning tools that you developed and introduced over the last couple of years is the best thing that they've seen from Cognex in a long, long time.

Right?

But what you see is those customers will hit at some point in some applications will hit a point where they need more performance. And today, they're having to jump often to a different platform. And with OneVision, we're able to keep that. I mean they can stay with an insight. So we're introducing this with the Insight 3800 and the Insight 8900. So that customer can stay with an Insight and update the model on that system. So I would say we're looking at the pricing, right? And we're looking at how it will be priced, but we're going to use what we learned from the second half of this year to influence that as we go into next year.

Joe Ritchie from Goldman Sachs. Thanks for all the details today. Carl, my question is for you. It's a multi-part question. But as you think about the 3,000 customers that you added last year, I'm curious what portion of the customers came from new logos versus share of wallet with existing customers. Part 2, as you look to expand and double your customer base over the next 5 years, how do you envision that shifting? And then I'm curious what is the cost element of this equation look like in terms of trying to penetrate and double your customer base?

All right. So let me try to break that part a little bit.

Three Parts.

So maybe the first part -- and you'll have to maybe help me go through the second and third part. I think your first question is on the 3,000 customers that we added, what percentage of them are new logos versus what percentage maybe would become from existing. I'd say those are new logos customers, right? So we see -- what we're trying to do is with expanding our sales force is the team that I talked about that really focused on market creation and expansion is really focused on calling on new customers and attracting new customers. And then they work very closely with a second team that focused on market penetration. So -- and what we would see is the ecosystem that we're developing, helping us in both cases. So it helps us go deeper for the existing accounts. I think Shirin kind of described really well in her presentation. Oftentimes, we're in there with an Insight 2D system. And then for 3D, we're also competing all from scratch, right, because it often deals even with our competitors, right? It feels like their products are often coming from different companies. Like if you went back a couple of years at Cognex, if I went into a customer, it would feel like our 2D systems, our 3D were all coming from different customers. A common ecosystem, what does that mean, right? They know the software, they know the integration, they built their HMIs, right? And that gives us a big leg up [indiscernible] when new applications [indiscernible] And I would say [indiscernible] your question. Those 3,000 , those are really new logo accounts that we added [indiscernible] and maybe you're seeing [indiscernible] Well, we've -- I think you know we made a big investment over the last couple of years [indiscernible] thjat investment is going to enable us to grow that. [indiscernible] based in the short term without adding any additional cost here in the short term. So I think Dennis and Matt, you're going to hear Dennis on the financial framework, then I think you'll hear from Dennis and Matt in terms of how we're thinking about that in the next section.

Joseph Giordano from TD Cowen. Just curious the unlock was for the One Vision because cloud has been around, has been around, you guys are kind of in those worlds. So like what -- like why now, what was like an impediment to maybe doing this 5 years ago and -- is there a competitive as anyone else doing this right now?

Yes. And maybe I feel like I've been speaking a lot. So maybe I'll let Shirin maybe do you want to take this one?

Yes, yes, yes. So you heard Reto talk about OneVision is not just any AI training platform, right? It's one that's designed for our customers. It's meant for industrial. So you heard Reto talk about all the advanced AI models, what the dimensions that matter in terms of making an application work for our customers. And OneVision vision is catered to that, but combined with the power of edge computing for are all the reasons why somebody may need something embedded on the factory floor, which is latency, reliability and in some cases, confidential as well. So it brings both of these together, and that's what we are looking to capitalize on with the availability of OneVision. So it -- that the cycle of making these models available on the embedded platform with more advanced models, that's what we're connecting the dots with OneVision and embedded solutions.

Reto, do you want to add a couple of comments.

Yes, on the why now? If you look 5 years ago, our AI solutions were all requiring a PC next to the production line. And so in that sense, the need to have a big computer that would allow you to sort of train those models was not as let's say, dire because it was already there in the production line. Now how that we move more and more towards deploying AI on embedded products. That is no longer there that capability. And so basically to offer in the cloud is much more convenient for the integrator.

Damian Karas from UBS. Shirin, you talked about the five pillars of the ecosystem. If you had to rank them, which would you say is most critical to Cognex' differentiation in the future? And you also said that none of your peers can check all five of those boxes. So I'd be curious to hear which you think your largest global competitor out of Japan is lacking.

So for the first part of the question, right? I -- it's hard to give a ranking, but I will say they're all very critical, and they fit together to complete [indiscernible] the ecosystem, right? It's software versus hardware. Do you need both which is better than the other. You need both. If you're trying to solve a machine vision application, you need the optics, you need the processor, you need the software, the ease of use software as well as the advanced AI models and you need all of that to come together to solve an application. So I wouldn't necessarily rank one versus the other. You need all of them. And that was the focus of what I was trying to say, all of the [indiscernible] to come together. Carl, maybe you want to talk about the second half?

I'm not going to talk about competitive [indiscernible] by name. But what I'd say is we look at our competitors, when we introduced Edge learning, I think a lot of the competitors are chasing to try to catch up to that, right? And then we've seen new tools on competitive for things like classifiers or segmentations that are really going after what we've done with Edge learning. What I haven't [indiscernible] is anybody that's been able to bridge edge learning and deep learning, right? And so this is the first. And I can tell you, I couldn't be more excited about. And I'll give you a quick example. I was in Korea earlier this year, and we were working with a noodle manufacturer that's using our Insight 3800 and they bought a lot of them for their lines. overall, very happy, right? So noodle manufacturer, what are they looking at, dry noodles, scrap [indiscernible] they don't want to -- the complement was that you're at, which is great and is very important for our customers that's why our relationships are long and sticky. So I think that's been fantastic, right? But AI is definitely disrupting things, right? And our founder of our company, Dr. Bob right [indiscernible], right, ability to do guidance, inspection, gauging and identification, right? And he often talked about [indiscernible].

James Ricchiuti with Needham. I think we can appreciate the appeal of the new AI tools with respect to the next tier, the smaller customers that you're going after. Wondering how do we think about as we heard last night, a large customer still pursuing internally developed machine vision solutions.

Yes. It's another good question. So I think how do we think about customers that are doing internally I think you heard from that customer last night that they've done it. They developed the AI teams, teams that can solve some of these complex applications. But I think what you also heard was how difficult that is go out, install those systems, maintain those systems over the long-term and scale it, right? And I think what I see is that those internal teams that are using open source and developing those, those are big systems integration efforts, right? And I think what you see from our ecosystem is that it makes the integration significantly right? And having a standardized solutions that they know that they can count on for the next 3 years, for the next 5 years, for the next 10 years, at the end, significantly reduces their overall total cost ownership. So I don't know, Reto, do you want to.

Yes, I think that's something we see quite specifically for bigger customers that they have maybe their internal R&D department and some capability to venture into these kind of analysis. And oftentimes, they run a POC and that may or may not prove positive. But as soon as it comes to then how do we have actually deployed in or how do we maintain that? And what happens 3 years later that specific R&D person is no longer there. I think that's where they're basically bumping against.

Thompson [indiscernible] think you guys have done an excellent job highlighting the road map, how the technology expands the market opportunity. Your customers last night spoke to the ROI when they made the purchase. But historically, technology and pricing as it accelerates pricing down. Maybe just speak to how you think about as we roll out all these new technologies, what happens to pricing on the product? I make it more commoditized over time.

AI accelerates? I don't see that. I see that there's an ability to leverage our N- 1 products for competitive solutions. But I really see with what we're doing with AI as being very unique, right? And it's helping our customers with total cost of ownership, right? And when you think about AI, I think if you go back and look at what Reto and Shirin were talking about, right, AI is a component of it, right? But oftentimes, when we're solving these outpatients or by AI with rules-based vision, with integration with a number of other things. And what we see is that's enabling us to maintain price. And I expect as we move forward and some of these things like with OneVision, believe being to increase that event.

Bobby Eubank from Chevy Chase Trust. Sharon, maybe you can comment on the differences in organization a very large gain have previously versus kind of the nimble work hard, play fast, Cognex, the culture. That will be a nice touch and then kind of differences between audio, AI versus visual. And Reto, I've been following Vidi for 10 years now. It finally feels like we're hitting critical mass and AIs here. But then Cognex compared in valuation to a hugging phase. I mean they could raise money at valuation than the entire Cognex today. So how do you think about that? Do you need to do additional acquisitions? Are you able to get the talent you need? What's kind of the disconnect between some of these models that are out there raising huge money versus Cognex.

Maybe, Shirin, do you want to take that?

Yes, I can start. So look, there are similarities and there are differences, right? From a similarity perspective, I would say that at Cognex, I find myself surrounded by great talent, as I had in prior roles and other places. Very smart engineers, a lot of great talent around -- there is the same work hard, has culture, which again keeps us at the -- always the forefront of innovation. So we're always looking to push ourselves those right, I'd say are very much in the ways of similarities. Differences, of course, there are differences in many dimensions when it comes to the size of the companies. I won't go into that in more detail. But I also will say another big difference is a cultural difference. And talking more about Cognex's culture, I would say that -- what's unique about the culture is it promotes a lot of camaraderie between the employees and it also promotes humility from leadership. And that's a great combination to help you do your best, right, and always keep at the cutting edge. That's what I would say about the differences in.

Great. And then maybe on the second one, maybe I think on the M&A piece of it, we'll leave that for the afternoon. But maybe, Reto, you could maybe talk a little bit about what you're seeing from start-ups and what you're seeing and how that's different from what we're doing.

Right. But I think also with respect to the hogging phase that you mentioned, right, I think one difference really is that hogging phase is very right? It's basically covering every aspect of data processing of analysis of language of vision and so on. And in that sense, it's very broad. And yes, there's a lot potential there. If you look at Cognizant has always been doing a very focus on the specific industrial factory automation market. And that has helped us really sort of to bring in what are the different pieces of technology that we need really get the MAX out of it. And then coming to the talent question, I think to -- in many ways, that's almost parallel to how I just described this, right? If I look for an R&D engineer and they can offer them something specific that basically actually goes into production, it's also specific and creates value for our customer. I think that's very appealing, whereas if, let's say, you're in a much broader space, and it's not so clear where it is going kind of application stands behind. I think that's, in many ways, what I see when we look for talent at that base case, what was the [indiscernible].

Keith Housum from Northcoast Research. Carl, you talked about the direct sales force being very important to the Connect strategy. We get integrators and distributors are also key to some of your sales efforts. Perhaps you can explore a little bit about how that relationship has evolved over the past several years and how the OneVision perhaps will play into the evolution of the relationships with both of those parties?

Yes. I think when we talk about direct, what we really want to be doing is working directly with our customers to understand their needs. It doesn't mean that we're always selling direct. We have OEM partners that I'm quite excited about what we're doing with them. We have systems integrators that would be often providing the solution to the customers. And then in areas where we're underserved from coverage, we have automation solution provided all of those are really important partners for us as we move forward. I think OneVision for all of them for our sales force, for our partners, whether it be a machine builder, whether it be a systems integrator or whether it be our automation solution providers, it really enables a much faster, smoother process in the selling because we believe that the best thing for every customer is to start on the edge, and we believe the best thing to do is start with edge because of that can solve that application, it's going to be the quickest path for the customer and for our partner. But with OneVision, what it's enabling us to do is easily bridge from edge learn -- learning and make that customer experience really good.

I've got one more question.

Tommy Moll from Stephens. We appreciate the insight. -- question for Shirin on the comprehensive ecosystem. So the One Vision announcement yesterday was new news. I think it's safe to say, but putting that to the side for a moment. Would you say that what you're describing today from a customer standpoint looks new? Or is this a strategy that the customers have kind of been aware of for a while and you're more just kind of highlighting something that's already in place for us today. I'm trying to figure out what has changed or will change or is changing?

So I think customers have been exposed to AI and training are we have PC-based solutions, so it's not that they're not exposed to training with AI models. But it's really what's different here is the way the workflows are set up, right, so that they can then take these AI models with all the assistance built into OneVision and deploy it on our embedded platforms, right? They have the options to go from edge learning to deep -- from deep learning to edge learning without having to switch out the type of product that they're using or the interfaces that familiar with. That's one aspect of it, right? And then again, for us, it opens up an opportunity to do more now with the power of the cloud when it comes to the advanced AI models, but again, at design time again, it opens the floor up for us to do more for them and solve new types of applications.

And one interesting anecdote there is also recently, I talked to an early beta test and he was telling that actually what he really likes about this setup is it's not going only going from edge learning to deep learning. We also have PatMax as a rule-based tool in this environment. And now they get to use this tool more in a data-driven process not so much in a tool driven. That means that they can run this tool and get statistics on it, much like they get that for an AI tool. That is a new experience. It really brings the world and that specific user was actually very happy about it.

Yes. Maybe I'll just summarize, Mike. So I think your question like what's new versus what's maybe evolution -- so I think last year, right, if you look at what we introduced with the L38 3D system, right, I'd say we think of a bridge strategy here, right? So what did that enable us to do that enabled us to go on an In-Sight System from 2D to 3D and stay within that ecosystem, right? So a customer could take a job from an Insight 2D system, and they could literally take that drop job and drop it into a 3D system and it would work, and now they could start adding depth data to them, right? So what's new is that those customers that are using Insight and In-Sight 3800 and In-Sight 8900 we're in the future in 3 if they needed to go to deep learning, that transition was not smooth, right? They were often having to move to our vision software and deep learning package, right? And so that they were starting over from scratch. So what's new with one vision is now as you think about the ecosystem, we've got the ability to bridge from 2D to 3D. And now we've got the ability to bridge from edge learning, right? So I would say it's an evolution, and we want to build on that. But it's a really key step in what we're able to do is bridging from edge learning to and keeping them within that insight ecosystem.

Thank you, Carl, Reto and Shirin for an engaging Q&A session. For those on the webcast, this marks the end of the morning session. The webcast will resume at 1:15 p.m. Eastern Time. So please be joined at that time for a discussion of our financial framework. [Break]

Hi, everybody. Welcome back. For those of you joining us on the webcast, please refer to the safe harbor language regarding forward-looking statements available at the beginning of our presentation. To start, we'd like to share a short video that captures the essence of Cognex's unique culture, "Work Hard! Play Hard! Move Fast!" [Presentation]

All right. Thanks for watching. We hope that gave you a glimpse into the vibrant and dynamic culture. We're so proud of here at Cognex. For those of you in the room, we also hope that you enjoyed lunch and the product demos. We'll now shift our focus to the financial foundation that supports our strategic vision. I'd like to welcome Dennis Fehr, CFO, who will walk us through Cognex's financial framework, and how we're positioned to drive long-term value for our shareholders. Dennis?

Thank you, Greer. Hello, everybody. For those of you who don't know me, my name is Dennis Fehr. I'm the Chief Financial Officer at Cognex. I joined just a bit more than a year ago, just celebrated my first birthday here at Cognex with a little cake, so also part of our culture, and had a good time with the team around that. And it has been a great first year, really great collaboration, great trust, Rob, Matt, really fantastic to be here. And I'm very much looking forward to the session to talk you through the financial framework which Matt introduced earlier today. The 13% to 14% revenue CAGR through the cycle and 20% to 30% adjusted EBITDA margin and greater than 100% free cash flow conversion rate are reflective of our commitment to drive long-term value. And this, we will do by focusing on profitable growth at attractive margins combined with strong and consistent cash generation. And when we talk about profitable growth, we really mean bottom line profitability. And to reflect our increased focus on bottom line profitability, we will also update the quarterly guiding metrics, which we are guiding to, and we'll start to guide to following three metrics: first, revenue; second, adjusted EBITDA margin; and third, adjusted earnings per share. I will now talk you through the financial framework in more detail, followed by our capital allocation strategy. Starting with our growth formula. Our growth formula consists of three components. The first component is the underlying industry growth of the diverse set of verticals which we are selling into. Based on independent external market research, we are expecting 4% of growth from this component through the cycle. The second component is the increasing machine vision penetration. Earlier today, you heard from Matt, four secular trends which drive this penetration, continuous cost and quality optimization, the ease of use of machine vision products, which we demonstrated to you in the product demos. Third, demographics, and fourth, the recalibration of global supply chain. Before we got a question from Damian, how about the replacement cycle of products. So we are also including that in this increased machine vision penetration. You heard Carl answering to that question and say like AI will drive customers, the new AI vision tools will drive customers to adopt products at an accelerated rate as they can now solve topics, they haven't been able to solve before. Further, you heard from Carl, how we are driving market creation and market penetration with our sales force transformation and expansion effort, where we are reaching more customers who have not used machine vision in the past. Like some of you have attended the engagement session last night, you heard from the foam customer who they're like, "Hey, we have not used it in the past". Now overall, we believe that this second component can add 6% to 7% of additional growth through the cycle for a total of 10% to 11% total market growth CAGR. Now this 10% to 11% is not just a Cognex number. It's also a number which is backed up by independent third-party market research such as the 2024 interact analysis, machine vision market report. Now moving to the third component of growth. M&A. We believe we can utilize our strong balance sheet and our strong and consistent cash generation to find attractive M&A targets to add 3-plus percent of additional inorganic growth. Now certainly, inorganic growth really depends on deal timing. So therefore, this additional level or this additional component could happen in the near term. It could happen in several steps over time or it could only happen at a one larger acquisition in the midterm. Now let's zoom in a little bit more into each of the three components, starting with the first two. So what you can see on this page is the diverse set of the verticals which we are selling into. With -- for each of the two components, the respective growth rates and then in the total, the total vertical market CAGR through cycle. Starting with the first component of the underlying industrial growth. While we are a bit more cautious about the second half of 2025, third-party market research suggests that semiconductor will have the highest underlying industrial growth, driven by the AI super cycle and the increasing push to reshore semiconductor manufacturing to the United States and the European Union. Considering the ongoing challenges in the auto industry, we believe that this vertical market will have the lowest underlying industrial growth of all the verticals we sell into. However, we believe that it will be more challenging in the near term that they are, however, longer-term investment catalysts such as the transition to EV and autonomous vehicles, and then certainly, that investment levels should normalize in the midterm as well. Now moving to the second component, the increase of machine vision penetration. We have sorted this table to show today's level of machine vision penetration with logistics being the lowest with an estimated 15% of penetration level and semiconductor being the highest level of penetration estimated around 90%. We therefore believe that in logistics, we can see the highest additional growth in the high single digits of increased machine vision penetration for total growth in the mid-teens. Now you've heard from Carl earlier today, how we are helping to move our partners in the space faster. And then some of those of you who have participated here on site and have been participating in the logistics product demo, you have also seen how we are making it easier for our customers to adopt machine vision technology like through our standardized machine vision tunnel and how we are adding vision applications on top of the code reading applications. Moving to packaging. In packaging, you heard from Carl earlier today how we are creating and penetrating this market through our sales force transformation and expansion initiative, combined with ease-of-use products. And again, those of you who have been in the packaging product demo, you saw the firsthand example with this cookies, with the little needles which you could not have inspected in the past with rules-based technology, which we now can inspect with deep learning and one vision and therefore, a great example of how this increasing requirements for traceability, quality and compliance are actually driving the opportunity to bring more machine vision into this industry. We therefore believe that this industry can grow in the high single digits through cycle. Now in auto, here, you have heard from Carl today how we are utilizing the flexibility and full power of our ecosystem to address the increasing needs of our customers for more flexibility and for the increasing complexity of inspection requirements in this industry, which we also showcased to you in the auto product demo. Therefore, we believe we can penetrate this market further and add also here to a growth in the high single digits. Again, this growth may occur a bit later and not in the near term. Consumer electronics is a market today already where you see annual level of refreshments and the kind of an annual level of reinvestments and refurbishments of existing lines, which drives an underlying growth in this industry. And then we have typically seen in the past that it's an industry which delivers outsized growth following form factor changes and the introduction of new electronic devices. We therefore believe that electronics, consumer electronics will be the most cyclical vertical markets of all markets which we serve. Now lastly, semiconductor, as mentioned before, already highly penetrated today. So here only an addition in the low single digit for a total market growth in the low teens. Now let's move on to the third component of growth. When we think about finding the right M&A targets, we are applying a comprehensive framework of strategic and financial priorities. First, we are looking to acquire companies, which help us to achieve our strategic objectives, of being the #1 in AI technology of delivering best-in-class customer experience and to doubling our customer count all resulting in being a major player -- a leading player in all major markets. We are very focused on finding synergistic businesses. This could be smaller bolt-on acquisitions or it could be acquisitions, which exceed the size of our largest acquisition so far, Moritex. We are looking to yield attractive returns from such acquisitions and we will be achieving so by focusing on businesses with attractive growth rates and which are within or on the path to be within our adjusted EBITDA margin target range. Now a great example for such an acquisition is our recent Moritex acquisition. Here, we had the opportunity to close the portfolio gap where we are replacing dilutive third-party lens pull-through with accretive Moritex lenses. I'm pleased to inform you that we are now at about 95% of the non-integrated lenses sold along with our machine vision systems are made by Moritex. Further, we are leveraging the strong sales force of the Moritex channel in Asia and the semiconductor market, which as I just mentioned before, has the highest underlying industrial growth rate, and we are tapping into the strong branch of engineering talent out of this acquisition. Altogether, this has delivered about $0.05 of accretion to our 2024 adjusted earnings per share. Now just before I go and ask about like, oh, do you want to do more hardware type of acquisitions. And on this question, I can tell you, we are very pleased with the Moritex acquisitions on the results, but it was a very unique portfolio gap which we have been addressing. So in that regard, hardware business are not the core focus of our M&A strategy. Now I've talked you through all three components of the revenue growth resulting in the 13% to 14% revenue growth through cycle. Now let's take a look on how our expectations are of revenue and profitability through the cycle. We have analyzed about 50 years of industrial manufacturing data, an analysis which you can find in the appendix to this presentation. And we have basically concluded that a typical cycle length is 5 to 7 years and that such cycles unfold in three phases: an initial phase, where we see a moderate growth followed by a second phase, where we see outsized growth all the way up to the peak of the cycle, and then culminating in the third phase post the peak, where we expect to see flat to high single-digit negative revenue growth. Now as profitability levers and delevers as we go through the cycle, our ambition is to exit the cycle at a higher profitability than we entered the cycle, which is a greater than 25% of adjusted EBITDA margin. Our first milestone on this journey is to reach greater than 20% of adjusted EBITDA margin, which we expect to achieve in 2026. Now let's take a look on how we can get there. The largest levers which we have to drive bottom line profitability, our OpEx efficiency and operating leverage, combined with COGS productivity. I will first focus on the right-hand side of the walk on the OpEx efficiency. Over the last couple of quarters, we have been laser focused on driving organizational efficiencies throughout Cognex. And we have shown strong results in our Q1 2025 numbers. Now going forward, we will continue to look to drive organizational efficiencies. Further, we have been talking about that we are looking to grow OpEx at a slower growth rate than our revenue growth rate. Now let's get a little bit more specific about that. Starting with SG&A. We believe that annual SG&A growth should be a function of annual revenue growth, however, at a substantially lower rate. If we think about RD&E as a technology company, we believe in continuous investment into innovation and therefore, believe RD&E should grow at similar increments on a yearly basis through the cycle. You heard earlier today from Shirin, how we have created a comprehensive ecosystem with -- based on common hardware and software platforms, which enables us to generate scale effects as we continue to grow. We, therefore, believe that this ecosystem enables us to stay the technology leader in the space by investing low teens percent of revenue into RD&E. Now in addition to the OpEx efficiency, we expect to see additional leverage of COGS, SG&A and RD&E as we move through the cycle to -- especially towards the peak of the cycle and then see some level of deleverage as we exit the cycle. Moving now to the other components on the walk on the left-hand side. As logistics is expected to be our fastest vertical market, we also expect continued headwind from mix. At the same time, we are working to drive COGS productivity and we are continuing with our successful pricing strategy where we are upselling our latest product generations and more aggressively price older product generations to defend market share. Now for our internal model, we have assumed a slight accretion from M&A activity. However, the actual value will highly depend on actual M&A activity. Now the basis for M&A, a strong and consistent cash generation to which I'm turning next. At Cognex, we have built a capital-light business model, where we are working with contract manufacturers, which enables us to keep CapEx at about 2% of revenue. Over the last couple of quarters, we had a very clear focus on driving cash generation, and we have now achieved a trailing 12 months free cash flow conversion rate of greater than -- of about 120% of adjusted net income. Going forward, we will continue to actively manage our working capital to achieve greater than 100% of free cash flow conversion continuously through the cycle. Now this is a good moment to talk about capital allocation. As we added inorganic growth to our growth formula, our first priority to allocate available capital is on M&A. Our second priority is to at least offset dilution by buying back shares at times when share prices are at attractive levels. And the third priority is to continue to grow our dividends at increments comparable to prior years. Now over the last 5 years, we have allocated capital towards the Moritex acquisition. We have more than offset dilution through share buybacks by buying back continuously through the cycle. And we allocated the largest share of capital towards dividends, especially driven by the special dividend of $350 million spent in 2020. Now our vision for the future is to allocate a larger share of capital to M&A to support that growth component. At the same time, we are looking to allocate a similar share to share buybacks. However, looking to optimize the approach here by buying back shares at times when share prices are attractive levels, especially at the beginning and the end of the cycle. Further, we are looking to allocate a similar share to dividends if we exclude the special dividend paid. Now at Cognex, we are very proud of our strong and healthy balance sheet. This, however, does not mean that we are not ready to bring on debt as an attractive form of capital to finance M&A activities if such an opportunity may arise. We believe that 1x to 2x of adjusted EBITDA leverage is conservative. Now overall, we believe this disciplined capital allocation will accelerate growth and shareholder value creation. Ladies and gentlemen, throughout the day, you've heard how advanced machine vision is made easier, how our cutting-edge AI technology and our comprehensive ecosystem is solidifying our technology leadership. However, sales force transformation and expansion is driving market creation and penetration in an attractive growth market and how our direct sales approach is a competitive edge. Some of the world's most economic companies partnering with Cognex, and we have the opportunity to substantially increase our customer base to drive profitable growth at attractive margins, combined with strong and consistent cash generation, all rooted in our unique Cognex culture. Thank you for your attention. Rob, Matt and I are now ready to take your questions.

[Operator Instructions]

This is Piyush from Citigroup. On this 20% to 30% adjusted EBITDA margin range, the path to 30% makes sense. Maybe spend some time on the floor that you highlighted the 20%, what are the key assumptions there and the confidence level that if growth is much more muted, you do not return to that 2024 margin range?

Yes.I think -- so first of all, why a range, right? So in the past, maybe we had just -- just one number. I think important is, right, to get this understanding we are a cyclical business and there is some leverage and deleverage happen. So that drove us basically towards, to say like, let's put out a range to reflect on that. And then certainly, we wanted to give some clear target and a clear milestone, to say like, we can achieve within a reasonable time period. So we, therefore, landed and, say like, let's put out the greater than 20% achievables within 2026, which then basically define the 20% to 30% of the overall range. Now, we put a small asterisks in there and say like, we can achieve that if there's no recessionary environment. That means, if revenue growth is more negative, but in general, Matt and I are pretty committed to say, if we would see like a flat revenue growth or moderate growth, we will hit that number, and we will work that number to get there. And certainly, if you think back to the overall margin walk, I think that would be really looking at cost of the OpEx efficiency and that would look at COGS productivity. That would be really the main levers to get to 2026 number.

Got it. Helpful. One quick one on M&A. Like how aggressive do you plan on being like do you have like a target lined up. And I think you mentioned larger acquisitions? Are we thinking more in terms of like the Moritex acquisition you did or it could be like larger than that?

Yes, it could be larger than that. And I would say like, I had a bit in my talk track that I say like, hey, it could be a serious or smaller acquisition. It could be also a larger acquisition, which could happen whatever in 12, 18 months, but it could also only happen in 24 to 36 months. So we're not kind of want to frame and box ourselves into that. Again, I think important here to understand the 13% to 14% is a through-cycle number. It's a long-term number. And it's not like that we are saying like, we will hit this number every year. There will be years where we hope to quite exceed them when we think about the middle of the cycle. But at the beginning and at the end of the cycle, it may look very, very different. So in that regard, take this really not as a straight-line number, but as the through-cycle number.

This is Andrew Buscaglia, with BNP Paribas. Regarding the M&A, I'm wondering if Matt, is this coincidentally you come on board with this new sort of strategic effort? Is this something you've informed others that this is something you want to do? And I guess, what's the impetus for going this route of being maybe a little bit more acquisitive going forward?

Yes, sure. I've been involved with our M&A activities. Actually, my first role at Cognex is working for Rob in Corporate Development. And so as a company, we've thought about how M&A, acquiring people, IP, product lines can add to our growth trajectory. So in that context, I'd say that's not new. I think what's new is us adding that as an official component to our target growth walk. I was deeply involved with the acquisition of Moritex. I've been involved with many of the acquisitions, both in cultivating those relationships as well as executing the integrations, both of the people of the technology and into the broader operation of Cognex. And I think, it's a muscle we've built. I think, we feel really confident whether it be smaller deals that are really going after specific pieces of IP or individual specific talent or larger deals like Moritex that have more mature revenue streams and product lines. I think, what we feel confident is we have the muscle internally to not only find them, right, because that's a big component to this, right? We really have a great view of our market and we network with the key participants. So I think, we have a great view of targets and actionability. We cultivate those relationships. But then on the back end, feeling like we can integrate, right? The integration is key to extracting the value of those deals. And -- and again, I would just reiterate what Dennis said, right? Our focus is really on a strategic fit, right, and strategic fit from a technology, customer, sales style standpoint, and financial -- and then one that fits with our financial strategy that we feel like we have clear visibility to adjusted EBITDA accretion. And when we see that fit, we -- I think you're going to see us move really intently and use the strength of our balance sheet and our strong cash generation to move faster when we see those opportunities.

I really would like to reiterate on that synergy part. At the end, it really, I think, for us, as a leadership team, we really need to be convinced that this is -- Cognex is the right company to own that business, and we really can create an additional Cognex value on top of it. Otherwise, I think it would not be the right thing for us to acquire. So take us that we really will take a disciplined approach towards M&A. And that's why I think, I really want to reemphasize that if needed, we will take the time and maybe 2 years or 2.5 years until you see such an M&A transaction happening, because I don't want to be also haunted by the things which I'm telling to the street, right? So please make note of that.

And maybe just one other thing, on those slides on the bottom, you said, it's a unique Cognex culture, right? And I do think of the acquisitions we've made and one reason we've been so successful is companies love joining Cognex. There's a lot of creative talent. It's a great environment to be a part of. And so that does make our ability to flex the M&A muscle, I think, very powerful in a way that's been very effective for us.

Tommy Moll from Stephens. I wanted to circle back to the top line expectations through the cycle, 10% to 11% is the organic contribution. And if we set that next to the same metric from your Investor Day a few years ago, it's lower now than it was then. And so, I want to think about the two different components there. One would just be, how much has your view of the market or the markets evolved? And then two would be just in terms of the messaging style. I think in the past, you may have used the phrase of stretch goals to characterize some of these metrics. Today's slides read more as a more traditional financial framework. And so there could just be some style evolution here as well.

If you don't mind, I'll start with that, and I'll hand it off. Yes, I think there is a bit of style there. And rest assured, the targets that our internal teams have on each of those metrics are substantially higher than what we're publishing to you. So yes, don't worry, the culture of setting stretch goals at Cognex is very much alive and well and the folks in the back of the room know what I'm talking about, because it's in their bonus goals. But I think the real novelty and maybe if there was a difference, and I have to credit Dennis for this is really thinking about a growth rate through cycle. And I think in the past when we thought particularly about our growth rate, one, yes, maybe it was more ambition. But I would say more specifically, we weren't as nuanced in terms of how that growth would trend over time. And as Dennis mentioned, we fully expect that there will be years as that cycle exercises itself, where we should significantly exceed that growth rate from year-to-year. There may be years though where we might underperform. And so I'd really encourage you to say, if there's anything new in this, it's really around that through cycle notion, which given the nature of our business, which we know is in many ways, tied to the cycles of capital expenditures is a much more prudent and hopefully easier to understand framework for you.

Yes. And maybe, I mean, you summarized it already well, but maybe to add on that, right? At the end, it's always if you put our targets, there's a bit of a balance, right? On the one side, it's like you want to kind of put something out there, which has some aggressiveness to it, at the same time, being realistic about where you are. And if you think back about the three metrics which we put out, right, we're not where we want to be on revenue growth, we're not where we want to be on adjusted EBITDA margin, and we just recently basically came to this greater than 100% of free cash flow conversion. So in that regard, I really want you also to take away like, we're also not sandbagging on the other side, right? So it's maybe not stretch goals anymore, but it's also not a sandbagging here. So we still have to work hard to get there.

Follow-up for you on the margin. In years past, there's been an explicit gross margin component in addition to an operating margin component. Today, we're moving more to an adjusted EBITDA and all-in adjusted EBITDA kind of framework. So just walk us through on the gross margin piece. Has the philosophy evolved there? Is it more tax plus more logistics kind of muddies the water on how you want to message that? What's behind that decision?

I think, first and foremost, we have been thinking very hard about what drives really shareholder value creation. And I think, there's the strong belief that it's really driven by profitable growth, combined with strong and consistent cash generation. And when we say profitable growth, it's really -- it's top line and its bottom line. So if these are really the components which drive basically the value which we create for a lot of the investors which are here and maybe some listening on the webcast, then we feel like that's really where we should focus. So certainly, gross margin components, COGS, OpEx, these are levers which we have been working on, and you saw them in the adjusted EBITDA margin walk, right? Of course, strongest focus on OpEx efficiency, but you also saw in the COGS productivity. I talked a little bit about pricing. So you will find these components. But these are, at the end, for us, levers, which we want to -- or knobs we want to turn to really achieve that bottom line improvement, which we are targeting here. So in that regard, think -- one thing is, is it the right target to drive value creation, and the other thing is what are the knobs we want to turn.

Yes. And maybe I would just add to that. I wouldn't want you to think it's a retreat from gross margin. Very much internally, we hold a very high bar when we launch new technology, and we measure the value of that technology through how it delivers value and how that value is delivered through pricing and gross margin. So we will very much stay focused on gross margins and obviously, healthy gross margins support healthy operating margins. But as Cognex has grown, why do I like an operating -- an EBITDA margin focus? There's a lot of cost below that gross margin line, right? We now have a much larger sales organization. We've diversified our distribution network that brings with it costs. We have a larger engineering organization. We have other fixed cost to the business in OpEx that we want to stay focused on, and we want to prove to you all and to our investors that we can manage both. We can manage both profitability as it relates to gross margins in the product, but also everything that's below that line to drive profitable growth in business.

Damian Karas from UBS. I haven't heard you gentlemen talk much about China today, that was 18% of your sales last year. How are you thinking about the market opportunity in China? Are you anticipating competing as much as you have in the past in the region? And how does it fit within the 10% to 11% organic growth framework?

Yes. I would say we're committed to the China market. Why? Because it's where most of the things in the world are made today. And our prediction will continue to be for the foreseeable future. Obviously, there's a lot of change of foot, right, with global trade and tariff disruptions and companies around the world questioning where and how things will shake out. But I want to be clear, Cognex is committed to our business in China, and we're investing in people and other resources to do that. We actually recently opened an inventory location in Shenzhen so that we could distribute our products with greater speed and reliability to our customers in China. But your question is a good one, because for sure, the Chinese market is a competitive one, and has been for many years. I wouldn't say that's a new phenomenon. Some of our quite impressive emerging competitors are coming out of China. And what started as competitors that really had excellent hardware and really demonstrated a level of speed in hardware development. We've seen them add software capabilities in interesting ways and use AI is really a way to accelerate their entry into vision. And so I'd say we keep a very close eye on that, and we compete today very well with them on a number of dimensions. And so I would really say those two things. We're going to fight to win. We're going to use the full portfolio, both new technology and new products as well as some of our older products to make sure that we can offer customers the best value and keep and/or grow our share in that region.

And maybe just to add maybe more clarifying comment, right? When we publish a number, China, it's really greater China, right? So that includes Taiwan, strong semiconductor. It's really like a global business, which is not driven by what's happening really kind of in Mainland China macroeconomics. And then also included in there is global consumer electronics business, right, which may be manufactured in China, but which is driven from a macroeconomic perspective, more by the consumer electronics cycle. So in that regard, I think, our focus when we talked about the growth framework is really it's about vertical markets and less geographies, because you -- in this global manufacturing environment, we are still in, right? And maybe it perhaps will change a little bit in the future, get a little bit more regionalized, but it's still like a global manufacturing business. Therefore, I think the regional view is always a little bit.

And I think we've said in the past about 3/4, about 2/3 of our business are multinationals operating in China. And so it's -- these are global companies that value a global partner. And so I think there, they still look to Cognex to provide the best technology but also to be a customer that can meet them where they need to be anywhere in the world, if not still in China.

Joe Giordano from TD Cowen. Just one on M&A and one on margins. So maybe on M&A, vision, it's a fairly narrow market, right? $7 billion served of which you're 15%, and in some cases, probably much larger. So like as you embark on this M&A, does it force you to redefine or at least expand the definition of like what Cognex is and what you do and where you play?

I don't think so. As I mentioned, we really have a great understanding of our industry. We've been in it several decades now and who the key players are both established players and maybe some of the newer startups. I think we have a good thesis on how value is created in the product, and we've used that in previous M&A activities. And so -- but on the margin, I think as we've matured and we've thought about how we could create value through M&A, I think that definition has certainly expanded from one that was very rooted in technology to one that adds other components around geographic concentration, customer focus and potentially also a sales channel, how can we use our newly expanded and transformed sales channel to better serve our customers. So I would put it that way. I think in some ways, it's very similar to how we focus on M&A as a growth lever, but we're adapting it as the company adds new capabilities as well.

And maybe really to add, I think, we're really not looking to become like whatever kind of portfolio type of company, right? I made that comment before, needs to be highly synergistic, and we need to have strong conviction that Cognex is the right owner for this business.

Perfect. And then, I'll press you on the margins a little bit like with the understanding that you're setting numbers that you think you can achieve, and I appreciate that. But I think Rob, in the beginning, you mentioned last 10 years, something like 28% EBITDA. And now we're looking at a forward guide in 20% to 30%, effectively, you're telling us it's as good as it's got. You've seen as good as it gets. And I don't think that's the impression you want us to have. So maybe you can frame like how that decade look versus what you're guiding. And maybe in the context of RD&E, we're on a $1 billion base now, talking low teens. We were at like in the hundreds of millions in the mid-teens, but now the growth algorithm is half as fast with a similar RD&E. So maybe you can kind of weave that together.

Yes. I'll start out with that. I mean, I think we were a pretty small company when I joined, I think we were $175 million or so in the first year. And we saw some -- we had years of 65% growth. We had more of that and a very high gross margin. And I think in some cases, we were trying to catch up with the size of company we were. So some of the comparisons may be a little bit difficult in that way. I think, entering logistics, great growth opportunity for us, but it's been a little bit lower gross margin dilutive, which has been an aspect that's been playing out there. But I would say, as I leave the company, I'm optimistic that the gross margins and the EBITDA margin is going to return to beyond what they were there. But I think, the kind of world we're living in today, the market growth we've seen in industrial automation probably has led the team to be a little bit more conservative, and I think rightly so in that way.

I think that's right. And Dennis hinted on it even the 20%, 30% range based on where we've been over the last few years, requires us to do real work to get there. And we didn't want to provide a framework that was so disconnected from where we are today. So I would say, yes, we have ambitions and let's say, even plans to exceed those targets. I think, what we're comfortable with going to market today is that range through cycle. And to the extent we can beat or exceed it, we will certainly do that. But at the same time, I think coming back to RD&E. Yes, we plan to get productivity. We plan to bring it down from mid-teens to low teens. A lot of that is rooted in the year's worth of work we've put into re-architecting our core technology as well as building that into our product strategy. So we're going to continue to do that. But vision is a competitive market, right? We have great margins. There's many customers entering constantly, and we have to stay in our game. And to do that, we have to continue to invest.

Yes, Ken Newman over here at KeyBanc Capital Markets. Maybe another question on M&A. Obviously, with the exception of Moritex, historically, the deals that you guys have done have been pretty small in a lot of cases, pre-revenue. And obviously, Dennis, you mentioned you're not looking to do more hardware where deals suggesting more software deals. I imagine higher revenue, profitable software deals are going to come with a much larger multiples. So just how do you think about being disciplined on what you pay for these new acquisitions and the confidence that you could find deals that kind of meet your hurdle right there?

Yes. No, happy to start. So first of all, I think there's something in between hardware and software, right, as a bad. So in that regard, that's who we are and what we do. So, just think about not only in black and white, perhaps. And I think, again, it comes back to that statement before. What are the synergies? Why is Cognex the right owner? And why can we add more value than others can do? And I think, of course, at the end, we as a leadership team, we need to stay disciplined and really kind of make the right due diligence and get the right conviction that it's really possible. And I think overall, I think we feel very positive that like how the Moritex acquisition went, that we have now established for ourselves that muscle, Matt has been talking about before that we can really do it, right? I think, both Matt and I are aligned that kind of the biggest risk is in the integration, right? It's always kind of post merger. And I think if you look at like how fabulous that worked with Moritex and the value which we are getting from there, we just have the strong conviction that we have built that muscle so that we can do it.

Okay. And then just real quick for a follow-up here. Obviously, a lot of color in concentration on this idea of doubling the customer set here in the next 5 years. When I think about the SG&A expense relative to the sales growth that you're looking to achieve. How do you kind of think about the moving pieces on labor and what you need to add from here from a sales force perspective? And then just any other color on the levers that you can kind of keep to limit that SG&A expense going forward?

Yes. Maybe as we've talked about, I think, in a number of different presentations today, we're very pleased with where we are on the initiative we started 2 years ago to expand and transform the sales force. And we've brought on hundreds of new sales noise. We've trained them. We've integrated them with our traditional sales force, and we're seeing the benefits through new customer acquisition and deeper penetration of existing customers. So I would expect us to continue to go hard at our channel, maybe just to say that. Now we made outsized investments over the last 2 years. Why? To really get that strategy to scale as quickly as we could. Why? Because we saw the opportunity. And that's the company Cognex is. If we see the opportunity we can fiction, we're going to go hard. But I wouldn't expect such an outsized investment going forward, but we will continue to invest in our direct sales channel. Why? It's constantly evolving and it's constantly adapting. Right? A lot of the folks that we've hired over the last 2 years are ready for new roles to be promoted. Some weren't a good fit and have left us. I mean, you need to constantly be replenishing, while at the same time growing that direct sales force and sales model. The second piece, I would say, is also the product and technology. And I hope everyone walks away with a better view on where we're going there. If we can continue down this path of designing a complete product ecosystem coupled and rooted in our edge-based vision technology, but complemented by cloud products like OneVision. It gives a tremendous leg up to our sales force to sell efficiently, to let customers deploy efficiently and as a result, get much more -- but internally, we talk about sales productivity, right? So you're able to get higher sales productivity, much faster through a given sales force. So both of those things, I wouldn't say we're fully penetrated from a sales coverage standpoint. I think, our products are going to let that sales team get much more productive. And I think the benefits of having a direct sales relationship with our customers has proven to be tremendously impactful for us.

Jim Ricchiuti with Needham. I think earlier in the presentation today, you alluded to major technology transitions. And I wonder if you -- those are always difficult to predict. But can you talk to the line of sight you have as you think about the verticals, where do you see the biggest opportunities in terms of these major technologies?

Yes. I mean, it's one of the most exciting things about what we do is, there's major technology transitions in each of our verticals. So maybe we'll step through them. You look at semiconductor, it's the advent of AI, right? And it's the moving to more sophisticated processing nodes to seek out even more efficiency. Think of it as compute per watt. And so as the semi industry tries to keep up with the advancements in AI, I think you're going to see big investments in manufacturing more sophisticated silicon. You go to automotive. That industry is attempting its own transition from traditional internal combustion to whatever the future is, which is likely going to be some mixture of hybrid electric, electric, autonomous, semiautonomous, a car that looks more like a consumer device than it does an automobile. You look at logistics. We went through COVID. What did COVID do? It probably pulled forward 5 years' worth of consumer adoption of buying things online. And by the way, we're not going back to where we came from, right? Consumers now want to buy more on a website. They want to buy more directly from the retailer. And to do that is requiring a level of automation to make those business models viable. And I'm not just talking about the Amazons of the world. You look at packaging, consumer brands are localizing, right? They want to be able to cater to a broader set of more local customer needs. And to do that means you could localize manufacturing to produce for a region or a geography. And to do that economically requires productivity through automation. So I would say it's such a good question, but I see transformation from a technology, from a consumer taste, from a product development across the board. And maybe the one I didn't talk about, of course, is consumer electronics, where we're seeing -- we haven't seen actually a lot of innovation over the years, but where could that come from, right? We see OpenAI thinking about making their own consumer hardware. We see some of the larger players thinking about new form factors of devices. We -- I would say, to the extent AR or VR plays a role in our daily lives is still yet to be seen. So I think there's quite a bit of potential and disruption to be had there. And again, all of those things are going to require a level of precision and scale in manufacturing that are going to drive automation. Hopefully, that answers your question.

Maybe to add on that and maybe also closing with the loop to the SG&A question before. I think, maybe to, in our mind, it's also we are kind of counterbalancing or maybe natural hedging kind of that cyclicality in the underlying markets with some of the investments which we are making, right? At the end, cyclicality is there in the market, but are there -- what are the ways for us to maybe limit cyclicality. And I think the investment in the sales force penetrating more customers, we haven't been there traditionally, bringing ease-of-use products, so that more customers are adopting machine vision. These are not only investments into growth. They are also investments to basically reduce the cyclicality of the business overall. So it's not for us just sitting here. Now let's wait for the next market trend. I think it's coming really back to this view that we think we can really also drive market creation, market penetration, and we control some part of our destiny also by ourselves.

[indiscernible] Your results are showing that your business is cyclical with the degree of operating leverage. And now you're considering adding financial leverage. Could you walk us through your thinking on that and whether that's something that's going to be temporary? Or I mean, just generally, how you think about it?

Yes. No, happy to take that. And yes, when we -- when I talked about adjusted EBITDA margin leverage of 1x to 2x, right? I really want to emphasize that this is really a through cycle number. So I think what does that mean in the statement, right? And we want to be very conscious about where are we in the cycle, right? So if you are at the peak of the cycle where your profitability levels at the highest level from an absolute term, you may think very differently about do you want to go to 2x leverage at that point when you know maybe in 2 or 3 years, you're in a down cycle and your underlying absolute adjusted EBITDA margins are at maybe a couple of percent points lower level. So that's kind of this phase through cycle that we really want to be mindful that like, peak of the cycle is a different number than the trough of the cycle, and that we will manage accordingly. And then certainly notice this maybe to make it also very clear, we think about debt for M&A. We're not thinking about bringing on debt for whatever, let's do funds the business or things like that. So it's really for M&A. And then, of course, we will be looking at like how important is it right now in terms of the capital allocation strategy at that time to repay debt, how fast we want to do it, where exactly are we between the 1x or 2x and so on. So that's maybe a few additional thoughts on that one. I hope it's helpful.

Bobby Eubank with Chevy Chase Trust. Historically, Cognex aimed to outgrow the market. I'm kind of surprised that hopefully, you still have that ambitious target to outgrow the market, but I'm kind of surprised that your messaging to investors is targeting in-line growth with the market. So can you comment on?

Yes, let's talk about it, Bobby. It's a good question. And for sure, again, I hope it goes without saying that the targets we're showing today are internal goals and what we're driving our teams to well exceed them. But -- so what did we lay out? We said we broke our growth story in three legs. Right? We started with underlying market dynamics. We broke out a second component, 6% to 7% of penetration, vision penetration, and that's maybe the piece I'll use to answer your question, then we talked about M&A. Penetration includes many different things. It includes new applications where emerging technology is letting us do things that have never done before. And you should expect us to be leading the charge on those things. So that is Cognex in many respects, growing the market ourselves as the industry leader. The second component, as Dennis mentioned, is a replacement cycle or an upgrade cycle is maybe a better way to put it. Ours -- when do machine visions get replaced? It's often not when they break. It's when the next-generation technology does something that's substantially better that generates a delta ROI to replace it. Again, you would expect us to, in many ways, be leading that charge as well. Now in that market penetration number for us, also implies some level of market share gain as we do one or two of those things, as we innovate and solve problems that have never been solved or as we replace ourselves or others with better technology and applications that have been solved. So we decided to put that together in one number of 6% to 7% and not break out those components separately. Dennis, if you wanted to add anything?

One more question.

You talked in the earlier presentations about the importance of having a full lineup of hardware and the combined ecosystem. So why should that be confined to vision, especially as you're kind of going out into the longer tail of customers? Is your, sort of, narrow focus on vision? Is that a limitation or an advantage?

Oh gosh, I think it's an advantage. And over the years, I think it's proven out to be advantaged that focus. Why? Because it really lets us go deeper in that domain, which is a big one, right? $7 billion growing at 10% to 11%. And so I think you will see us maintain that focus and being the leader, the technology leader in vision. But I wouldn't say we're everywhere in machine vision, right? I think, there is -- there are many product verticals in particular, where we still have room to innovate, room to expand our offerings, both at the high end and at the low end. And then, when it comes to looking at adjacencies, maybe non-vision adjacencies, that's maybe the most interesting. The way that we think about that is really rooted in the vision system itself and what it does it align and then looking at other adjacent high-value automation at that line or at that station, where it would make sense if we were to own or control those adjacent technologies to deliver more value to the customer. And so that's how we think about it, right? And we evaluate what those additional adjacent plays could look like. There are various high-value sensing, non-vision sensing components and technologies that could fall into that definition. And let's just say, we've, in the past looked at those. And then, we ask our customers and we say, would you like us to be the sole supplier of maybe a broader basket of vision and other sensing or other pieces of automation. And so I would say that's very much our framework. But I would expect us to stay very focused on the core vision business.

All right. Thank you, everybody. This concludes our 2025 Investor Day. We hope you enjoyed the sessions this morning and the product demos. For those on the webcast, thank you for tuning in, and we will talk to you at the next quarter's earning call. Thank you.

Thanks very much.