All right, welcome everybody. For Morgan Stanley Research Disclosures, please check out morganstanley.com/researchdisclosure or talk to your sales representative. I'm also going to read the NetApp safe harbor, which is that NetApp has asked me to read their safe harbor. Today's discussions may include forward-looking statements, including NetApp's performance, which are subject to risk and uncertainty. Actual risks may differ materially from statements made today for a variety of reasons described in NetApp's most recent 10-K and 10-Q, filed with the SEC and available on their website at netapp.com. NetApp disclaims any obligation to update information and any forward-looking statements for any reason. So now that we've gotten the exciting part out of the way, I'm Meta Marshall. I cover hardware here or storage here at Morgan Stanley. We're delighted to have NetApp and NetApp CEO George Kurian here with us today. Thanks so much for being here, George. Thank you. All right, so maybe let's just kick off talking about the fiscal Q results, and then we can jump into the longer-term story. You saw some weakness at the end of the quarter on deal slippage, but also just some kind of weakness out of Europe. Can you just break down how to think about kind of the various areas where you saw weakness and how much was execution versus market? In Q3, we saw some weakness in some of the countries in Europe, U.K., France, and Germany, where their economic outlook was muted, as well as they've had government transitions, and so we saw some weakness there. However, we were on track to meet our Q3 outlook till the last couple of weeks of the quarter when several deals that we had in the pipeline pushed out. These were large deals, seven or eight-figure deals, mostly in the Americas and in Europe, and we have subsequently closed those transactions in Q4, so when I look at the performance relative to our guide in Q3, it was sales execution. Okay, all right, and so just what are some of the, you know, you mentioned a lot of those deals have now closed? What are some of the actions that you're taking around kind of the execution issues? Yeah, these are all fundamentals, right? Better inspection, better closing plans. We have war rooms set up to make sure that we know exactly where customers stand relative to their procurement pipeline with us. And we have taken some people actions as a result of that. I mean, is any of that just a result of your going through a CFO transition, or is this all just kind of execution? This is field execution. Okay, all right, perfect. You, on the fiscal Q4 guide, you had noted that many of these deals had closed, but that you were embedding some level of caution on FX or public sector. You also had a portion just due to the divestiture of Spot. You just gave a sense of kind of fiscal Q3. But in terms of, as we think about the guide, was there any execution embedded into the guide or just kind of how to think about what were the reasons for the guide maybe being a little weaker than expected? We expect Q4, our sales execution to be back on track. With regard to the Q4 outlook that we provided, there were three areas that we provided additional commentary on. The first was FX is about a $17 million headwind in the quarter. Second, we have closed the transaction, the divestiture of Spot, which would impact us for about $15 million in the quarter. And then we had provided some incremental caution with regard to U.S. public sector. Okay. I think one of the questions that investors have had is that we've seen a relatively strong server and networking data center refresh that started over the past couple of quarters. Just where do you think the market is with an appetite for kind of a larger storage upgrade similar to what we've seen on the server or networking side? Storage refreshes typically follow a few quarters after networking and computing refreshes. We have seen some customers do that. Obviously, all customers don't do it at the same time. In general, we see utilization rates of our equipment to be high, which is a precursor to when they have to buy additional equipment and capacity, and we're well positioned. You know, our flash business has performed well. I think if you do the math, even last quarter, if we had met our targets, we would have been up mid-teens in flash, coming off a year on a compare, which was up 21% year on year, so we've got a great portfolio. I feel strongly about our competitive position. You mentioned kind of the third reason on the outlook was U.S. federal. Just can you remind folks of what that exposure is and just if there's any departmental kind of concentration to be mindful of? Yeah, our U.S. public sector business is about 10%-13% of our total business, and Fed is about 70%-80% of that business, the rest being state and local and higher education. So off that 75%-80% of the total U.S. public sector business, we are relatively split evenly across civilian, DOD, and Intel. And so far, we've seen the caution that we've applied to is really around civilian, where some of the changes with the new administration are causing more inspection of deals. We haven't seen cancellations, but we've seen it taking longer to get approvals. Okay, got it. You know, gross margins were also a little bit weaker in fiscal Q3 and into Q4 or from your Q4 outlook, just largely based on kind of the volume of flash. But just how should we be thinking about gross margins of the business kind of after this quarter? Yeah, fiscal Q4, as we said, would be the trough in terms of product gross margins. Fiscal Q4 also historically has, due to our seasonality, a higher mix of product versus service and support, so I think that if you look at the mix of the business, you know, product margins, we should be at the low point in fiscal Q4. Support is pretty stable at north of 90% margins, and then cloud has continued to tick up in terms of both of our business as well as the margin profile of that business. We had 76% margins in the last quarter, and we expect it to tick up towards the higher end of 75%-80% exiting this fiscal year. Okay. You know, just stepping out of the quarter, just how does it make you think about kind of the achievability of the long-term targets you laid out at the Analyst Day of mid- to upper single-digit revenue growth and kind of double-digit EPS growth? Yeah, we feel very good about our long-term model, which is exactly like you said, mid to upper single-digit revenue growth as well as double-digit EPS growth. We have a portfolio that's fully refreshed to address the growth areas of the market. We have four secular drivers that we are driving against: flash and AI being secular, cloud and block being company-specific drivers. Our cloud business, once you remove Spot from the mix, has been growing north of 20%. And so you should see that continuing to be a strong driver of growth at high margins for NetApp. And then we have a disciplined approach to running the business, which allows us to deliver leverage in terms of operating margin profile. Okay. You know, NetApp has seen meaningful share gains over the past year in particular. You know, just how has NetApp's value proposition evolved? I think our value proposition is embedded in the software that we have, you know, running our systems. And we deliver value in three ways. First is we allow customers to simplify their operating environment so that they don't have to learn multiple different system architectures and manage a lot of different environments, which is particularly helpful in times of constrained IT resources. The second is, which is becoming even more apparent with the growth of AI, is the idea that you want to unify your data of all of your different data types, and you want to unify it across on-prem and cloud. And the third is a series of services that allow you to manage your data, protect it, secure it in unique ways to be able to understand how to optimize your environment, as well as to deploy data-intensive workloads much more easily on our infrastructure. That value proposition is resonating with our clients. Got it. You know, C-Series has been a huge success for you guys. You know, you were ahead of the market or kind of ahead of Dell and HPE in introducing that product. Just as that competitive set starts to fill out, you know, right now kind of with Dell in the coming years with HPE, just how do you see kind of that market for C-Series and your ability to continue to differentiate in that? The differentiation is really in the software and our ability to allow clients to unify their data, unify their operating environment, unify on-prem and cloud. Nobody else in the industry has that capability. Okay, got it. And then we've gotten 10 minutes in. We haven't talked about AI yet, so let's dive right in. You know, how are you positioning yourselves to capitalize on enterprise AI adoption? And just can you provide an example of kind of what use cases you're starting to see customers leverage NetApp? Yeah, we've always said that AI is a combination of algorithms, meaning things like large language models and data, where the value or the applicability of AI to an organization's business is really driven by the combination of those two. We are the stewards of data. There's a lot of people working on models, but what we've always believed and what is being proven in the market is that having the ability to unify your data and use your data easily and well with the models is super important to generating better outcomes with AI. We enable clients to do that in three ways. The first is clients need to unify data across multiple types to get better results. You know, you look at models, the more value of the higher fidelity outcomes come from better quality data and wider scope of data, meaning you can unify data across multiple types. We have amazing tools that allow people to do that. The second is people want to be able to apply a variety of mechanisms to both ensure the security of their data, to allow for model versioning and data versioning, to allow for things like traceability of the data so that you can provide assurances that you're applying AI responsibly to your clients. We have an awesome range of tools that allow data scientists and data engineering teams to be able to do that. And then the last and perhaps the most commonly used is hybrid. You know, many clients we have are using public cloud models with their data, and we are able to allow them to use their on-prem data very easily with public cloud, or they want to stand up a private model but take the data that exists on the public cloud and bring it to their private environment. And so those are the three. You know, we have awesome infrastructure to unify your data to allow it to be used with models, to accelerate the use of tools for responsible AI, and then to build hybrid cloud architectures that are very commonly used for AI. I mean, given that you're really at the front lines of seeing what customers are doing, just what are you seeing in terms of trends of customers using public cloud versus on-premise for how they're thinking about AI? I think we've seen, you know, a mix of patterns. I think broadly based public cloud is where clients are starting their experiments. But what we have also seen and what we have coached clients to deal with is it's much easier to bring AI to your data than copy all your data to where your AI model is. It's much more cumbersome to do that. And so our approach allows you to start on cloud and then scale on-prem, which is what a lot of people are doing in regulated industries, which are, for example, healthcare and life sciences, some of the public sector environments, or some parts of financial services where the data is already well established and well, you know, kind of structured. We are seeing the adoption rates be higher, and they are mostly doing stuff in private AI environments. Got it. I mean, what is the timeline? You just mentioned kind of regulated industries maybe moving first, but just what are you seeing as the timeline of AI projects moving from proof of concept to production deployments? And you know, what does that pipeline and revenue opportunity kind of look like for NetApp? With regard to the proof of concepts and things moving into production, we are starting to see the early phases of the enterprise AI opportunity unlock. We've shared that over the last few quarters, we've had, you know, each quarter, you know, in excess of 100 wins of, you know, AI-specific use cases where people are putting together the data infrastructure to enable the use of AI applications. Those continue to be, you know, kind of a steady pipeline, and we're starting to see that, you know, consistently in our business. We are also seeing a growing number of AI-as-a-service providers who are building landscapes to enable enterprises to use their platforms for AI. And, you know, our expectation, as we've said consistently, is the compute build will go first. You know, the data infrastructure gets built out, you know, following compute, and we see these projects going from kind of proof of concepts into production second half of this calendar year to first half of next year. So it'll grow over time. Are there ways, do you think, that you can be, you've mentioned kind of the three buckets that you can help them where you can kind of help them quicker go from proof of concept to deployments? Yeah, I mean, especially if you have your data on a NetApp system, you can run an AI project on there exceptionally quickly. Yeah. Okay. You know, your public cloud business is another differentiator for NetApp. How do you see the relationships evolving, and are there differences between what a public cloud customer for NetApp looks like versus your traditional customers? Yeah, public cloud has been a source of net new customer acquisition, a strong source of that. You know, if you think about our enterprise business, you know, we have a certain percentage of the market, and the majority of the market we don't control. And when you look at public cloud, the fact that we work with the three largest hyperscalers who control probably north of 80% of the public cloud market, it gives us a chance to penetrate a whole range of net new customers, which is what's proven out. Our first-party cloud storage portfolio has grown really strongly for many quarters now. And as we shared, cloud storage is about 80% of the total cloud business, and our first-party storage is about, you know, 70% of the total business. So it's a strong growth trajectory for us. We continue to bring more and more and more innovation every quarter, and not only in the public cloud environment across price points and workloads and capabilities, that's an ever-expanding opportunity for us, but we also, for example, talked about how we are working with Google Cloud on sovereign clouds and private clouds, where the stack that we've built with them in the public cloud now is getting deployed in, you know, various sovereign environments. Got it. Just, you know, you noted kind of the first-place marketplace services are now 70% of the public cloud business, continuing to demonstrate strong growth. Kind of how should we think about what the remainder of that public cloud business, and just how should we think about those pieces as a piece of the portfolio? Yeah, so we have, you know, two or three other elements to our cloud portfolio after having divested Spot. There's operational services called Data Infrastructure Insights, which is complementary to our cloud storage portfolio. It allows a client to see what storage they've deployed, how is it performing, can I optimize the use of that environment, and so on. We also have workload services like Instaclustr that allows customers to deploy more applications faster on that cloud storage, you know, platform. And so those are really kind of value adds to our cloud storage portfolio. And then we've got some subscription, you know, storage, you know, services, which are a very small percentage of the total number, which we are moving, you know, as we said, we continue to move them towards the consumption business, and that's a small part of the total number. Got it. You mentioned just now kind of Google and the opportunity with sovereign clouds. Just can you maybe give a context for the different relationships you have with the different clouds and how you see those kind of evolving? So all of them have their own approach to the customer base in terms of the industries, the applications that they're driving. And so we work with each of them around their priority vertical markets. We work with each of them around their priority application sets. And there are some that are common, right? So VMware is common across all of them. You know, SAP is common across all of them. But there are things that we are working on, for example, with AI that's different, for example, in what we do with Amazon versus Google versus Microsoft. And so our, you know, belief is that by working closely with each of them, we enable them to drive their business by bringing more clients and more workloads to their cloud footprints. But by working with each of them around their priorities, we also cover the market extraordinarily completely. Okay, got it. Another area I wanted to ask about is just the customer adoption of Keystone or your kind of as-a-service offerings. Just what are, where are you seeing these kind of be adopted by customers? We offer clients the ability to buy our technology in a broad range of ways. You know, we want them to be able to have the flexibility to consume it whichever way they want. The as-a-service model actually grew in the cloud first, right, and so our entire cloud portfolio is an as-a-service business, and, you know, when we talk to clients about true as-a-service, we say, "Hey, you should go use the cloud. You can spin up something and spin it down whenever you want." In the on-premises world, we have seen clients get more interested in an as-a-service model. Some of them have learned from the cloud, and they want to use it more on-premises. Our Keystone, which is our storage as-a-service business, has done well. We grew 60% approximately in Q1 and, you know, north of 50, like 55% in Q2 and Q3. It's on a good trajectory. Got it. I wanted to open it up to see if there are any questions from the audience. All right, perfect. I'll continue. You know, a question that we sometimes get from investors is just, you know, clearly you do business with the public clouds. Is there any kind of hyperscale opportunity you see kind of on their own workloads? On their own workloads? Or just on their, within their own environments versus kind of services that they're offering to customers. You know, they have, you know, we work with each of them around their own IT landscapes. And, you know, we have applications that their internal organizations use that run on our footprint. And then we are working with them for better integration with some of their proprietary applications. Like, for example, we announced some of the integrations with, you know, Vertex and with BigQuery from Google. And so you'll see more of those kinds of applications coming over time. Okay, great. Another question that we're just kind of asking frequently at the conference is just how are you guys using AI internally kind of within NetApp? We use AI in three ways. The first is to build, you know, products and solutions for AI. These are all the things that we talked about, right? Data infrastructure, high-performance storage, all of these data services that allow our customers to use AI more efficiently with their data. The second is AI capabilities embedded in our products and services so that you can make it much more easy for a client to use our technologies. These could be advanced security mechanisms like ransomware protection mechanisms, ways for our clients to access, you know, tools that allow them to see how their systems perform and things like that, which are all getting AI smart. And then the third is to use AI to make our operations more efficient. So, you know, we've got a huge percentage of our engineering teams using AI tools to make their, you know, development much more productive. We use it in customer support and in various parts of our back office. Got it. You know, just kind of as a last question, just what are you most excited about for NetApp for the next couple of years? And, you know, just is it AI? Just kind of can you lay out kind of what you're most excited about going forward? You know, maybe I can answer that in a couple of ways, right? I think one is from an external trend perspective, listen, we have two strong things that we bet on a long time ago that are paying off. I think the first was we've always believed that you want to unify your data because having a more unified view of your data gives you more intelligence into how your business operates. That is proving true with AI. And GenAI in particular allows you to analyze and monetize the giant amount of unstructured data in the world, and we hold a huge part of that. So that sets us up really well. The second is, you know, we've said hybrid cloud or public cloud becomes a really integrated part of your architecture. That is proving true, you know, especially with the use of AI, right? I think those two long-term trends we said we've played out, you know, are playing out in our favor. In terms of our portfolio and competitiveness, listen, we've got a fully refreshed portfolio. We are gaining net new logos both with cloud and our on-premises portfolio. I feel like, hey, you know, we're in a really strong position in the market. Great. All right, well, George, thank you so much for being here today. Thank you. Thank you Thank you so much.