Okay, hopefully I counted three to one correctly. I want to welcome everyone for our fireside chat with the team from Pure Storage. Before we get started, I would like to read the disclosure. Statements made in these discussions which are not a statement of historical fact are forward-looking statements based upon current expectations. Actual results could differ materially from those projected due to a number of factors, including those referenced in Pure's most recent SEC filing, on Forms 10-Q, 10-K and 8-K. To that end, wanna thank everyone for joining us. A perfect timing, given for Pure's recent earnings call. I do have some questions, kind of follow up, and I'm just gonna start. Rob, you guys talked about hyperscaler revenue that is embedded in your fiscal year guide, especially for the second half. What I wanna better understand is the diversity of a customer. Is that just a one hyperscaler customer to— The mix, does it include both hardware and software? Yeah, thanks for the question, Mehdi, and thanks for having us. As you mentioned, coming off of a great 4Q prints and had a lot of discussions with the financial community over the last couple of days. Let me hit your first question, which is, I think just seeking to better understand the hyperscaler revenue expectations. Where is that coming from? How does that look? And then a couple elements in what we introduced as the new, more standardized hyperscaler business model. As you mentioned, we discussed on the call on Wednesday, you know, our increased expectations for the year relative to our prior commentary, in terms of hyperscaler shipments. That's, you know, as we have tried to share in qualitative color, that relationship continues to go very well and is ramping quickly and, you know, has surpassed our prior expectations. We do expect most of those shipments in FY2027 to occur in the back half, so in the fiscal 3Q and 4Q, just due to the schedule of the hyperscaler build-outs. To your question about, you know, customer mix and concentration. Yes, at this point we are still shipping to our, you know, our lead customer in the space. We are engaged with, continue to be engaged with and advancing engineering discussions and, I would say exploration and testing with additional future prospects. You know, really just one primary customer in the scaled part of the hyperscaler business at this point. I think the other part of your question, and I know I'm going long here, but you had three questions baked in. I think the other part of your question is seeking to better understand the mix of that revenue in terms of, "Hey, how much is software? How much is hardware? What does that exactly look like?" You know, I want to take you back to and take your listeners back to our original business model, which we articulated in fiscal 2026. In our 3Q call, we had kind of foreshadowed and indicated, "Hey, we're going to be evolving this business model," and then take you to what that looks like and our expectation moving forward and what would cover most of the FY2027 shipments. The original business model, if you recall, was really centered around, think of it as a software royalty or license fee for the DirectFlash software. That is really the heart of the IP. That's the heart of what the hyperscalers are interested in. In FY2026, that made up the bulk of, you know, the revenue. Smaller piece in terms of maintenance and support, but we can set that aside. Really, the bulk of that was in software royalties. The hyperscaler supply chains would then in order to take advantage of that software, hyperscaler supply chain would be procuring the servers, the DRAM, the NAND itself, all the components to make the NAND into the DirectFlash Modules, et cetera. What we learned, you know, as we've grown the relationship and have talked to additional hyperscalers is, hyperscaler supply chains are quite adept at, you know, at procuring servers and DRAM, quite adept at, you know, at procuring NAND and NAND Flash. For all of the other components to finish out the DirectFlash Module, our PCBs, our designs on, flash controllers, et cetera, it just made sense for all involved. It was a lot operationally simpler, for our supply chain to go, help procure those components. To be very clear, and we discussed this in Tarek's prepared remarks, we would not be procuring the NAND, for the hyperscalers or the servers. Really, the rest of the components to make that solution. When you consider that in the overall shipment, you know, that is That change or that shift to that standardized business model is what is now bringing the gross margin expectations associated with the hyperscaler business into that range of 75-85 points. Depending on the configuration or the performance tier or the drive sizes, you may have some variation within that range, but that would be our expectation for that hyperscaler business. That's pretty, I would say, clever. Let your customers and their scale be involved with NAND procurement, which hasn't really happened in the past. I guess perhaps in the past, most of the demand was driven by enterprise. The AI has enabled you to penetrate hyperscalers, and now they are helping you with procuring the required NAND. Would you agree with that? Well, so yeah, let me, let me maybe unpack that. Obviously there's a lot of complexity that goes into sharing and coordinating supply chains. As you mentioned, we, you know, for our enterprise customers, for our core business, you know, our customers are just looking for the best solution, finished product, et cetera. It really doesn't make sense, and they don't have the infrastructure in place to go run these types of, you know, quite sophisticated supply chains. Hyperscalers on the other hand, you know, makes sense to for us to work together with them, you know, to apply the best capabilities they have in their supply chain, the best capabilities we have, and that's really what led to this evolution and standardization of the business model. Yes. Now, I wanna step out of the queue I have with my questions on the topic and actually go to the demand side. There are evolving demand drivers. How do you see KV caching impacting the demand, especially as we migrate to inferencing? What are the key products in Pure's portfolio that will be applicable to that, which I would phrase as a new kind of a demand driver, the KV caching? If I step back and look at the-- Now shifting gears to the core business, if I look at the demand drivers on the core business, you know, I think we see a number of demand drivers we talked about on the call, and, you know, reflected in our guidance and outlook for the year. We see robust demand across the board in exiting, you know, fiscal 2026 with a ton of momentum. You know, and I think there's a number of demand drivers across the industry. And then I'll answer your question specific to AI, which, of course, is still a smaller part of our overall book of business. You know, I think that, you know, certainly, if I look across the industry, what we saw in, you know, throughout the back half of fiscal 2026, you saw, you know, us raise and subsequently beat the guidance, several times through our fiscal 2026. What we saw was a couple of things. One was, pretty robust demand, you know, across the board, across segments, whether that was, enterprise, commercial, U.S., international. It was pretty broad-based. I can't identify, you know, a specific application driver or a specific, you know, vertical or area. We saw pretty broad-based demand, and you saw that come through in terms of our, you know, in terms of our sales and our revenues, you know, as well. I think I suspect part of this may also be, you know, Last year, right, we had a little bit of call it a headwind to IT budgets across the board, perhaps exacerbated by the Broadcom VMware action. A lot of folks were, you know, pretty stretched, and you see some of that, you know, either pressure relieving, if you will, or maybe folks that had sweat assets a little bit longer. You see some of that starting to kind of relieve. You know, I think the other thing is, as folks now turning more, in the direction of AI, I think as folks are progressing in their thinking and plans about, "Hey, how do I go, you know, get more value out of my data?" You know, modernization, infrastructure modernization projects overall, we're seeing those move forward. You know, we see that both in the core, array business, array and, blade business, as well as, what we're seeing in Portworx, you know, in terms of, modernizing, not just container applications, but virtualization as well. If I look specifically at AI, coming to your question about KV cache, you know, we're engaged in conversations across the board, everywhere from, you know, folks that are just looking to connect their data to ChatGPT, all the way to folks that are doing some small scale, you know, maybe fine-tuning, maybe folks that are doing, you know, really focused on inference and RAG and to large scale GPU clouds or, you know, foundation, you know, AI natives that are really down the training path. I think we have a robust portfolio of solutions for that. You know, on the inference side, we do see, you know, more of a focus on KV cache. I think it's very early days. We have a number of customers on our FlashBlade solution, that are making use of, you know, object capabilities and our KV cache accelerator, there to really make that whole process a lot faster. I do think as inference grows to scale, that will become more and more important. You know, as a portion of the market and, you know, just overall, segment of, you know, kind of a share of our book of business, it's still relatively small compared to everything else that we do. Yeah, yeah. Especially your NAND suppliers are having a hard time sizing the market, the size of the market for KV caching. Everybody's trying to figure this out. It's very fascinating because you have the enterprise finally beginning to utilize AI, and then you have the native data, the hyperscalers wanting to own everything. They have already invested billions or hundreds of billions in training, and now they wanna extend their services to inferencing. In that context, how do you see Neocloud service providers that are telling enterprises, "Hey, I could be your edge compute," evolving? When you say enterprise demand is strengthening, is that traditional enterprise or does that also include Neocloud service providers? Yeah. A couple pieces to the question there. You know, when we talk about demand strengthening and just being robust across the board, really talking about traditional enterprises, traditional commercial public sector are really our core business. Again, just highlight that we do see that pretty robust across all workloads, of which AI is just one of many. You know, in terms of where do Neoclouds fit into the equation? You know, it's interesting. They, you know, I think we work with many Neoclouds. You know, we, you know, work with them on behalf of both call it large scale tech titan types who are, you know, utilizing their capabilities as well as smaller enterprises and commercial customers that are utilizing them to provide the GPU infrastructure. You know, I think the Neoclouds are really focused on, you know, they're focused on providing infrastructure that can meet the wide range of demands. Think about it this way, if you're, you know, GPU as a service provider at Neocloud, you know, you might have one customer who's doing super large scale foundation model training. You might have a couple other customers that are just doing inferencing. You might have a couple other customers that are actually working with images and video instead of text. The range and variety of different needs that you have to go satisfy is quite large. I think that is, you know, I think that presents an opportunity for us because, you know, unlike most of the storage competition in the AI space, we've purposely not taken a laser-focused view, right. We've leveraged, we've really leaned into the power of our core technology, which is to be, you know, very flexible, very adaptable, very deployable for multiple different needs. I think we're seeing that, you know, that value proposition resonate as we engage with more Neoclouds. Yes. Agreed. I'm gonna ask you one more open-ended question. I think there are still some details to be worked out, data sovereignty, data security, and I think your 1touch acquisition announced the other night fits into that narrative. Ultimately, I'm looking for an inflection point. We love inflection point, where one earning report you come out with a big revenue growth exceeding 20%. How should I think about that context? Are we setting up to the over the next couple of quarters where you're gonna see a scaling of your products, where you're finally transitioning into deploying AI among enterprises? Is this gonna be just a slow train moving forward, but it's just not the slow Choo Choo Train is not gonna turn into a bullet train? Hopefully, that makes sense to you, the question. Well, I mean, I would just point out that, you know, the revenue guidance and outlook we provided for FY2027, you know, almost doubled our initial outlook coming into, growth coming into, FY2026. You know, I would argue that we are driving significant acceleration across both the core business as well as our newer markets, whether that's the hyperscalers, whether, it's AI. Look, you know, we're focused on continuing to drive growth, continuing to accelerate. You know, we have multiple levers that we're pulling on and, you know, just to reiterate for your audience, certainly the core business, focused on completing the portfolio, focused on, layering on top of that the intelligent control plane, data management capabilities, things that will allow us to reach, into, and hire into larger accounts, compete for larger wallet share. You see, the results of that, already starting to pay, you know, bear fruit with, I think, Tarek, shared a number. You know, the number of deals that we track and, have booked over, $5 million growing 80% year-over-year. That again gives you a data point in terms of the leverage we're driving in, the core enterprise. Hyperscalers, we've talked a lot about that in terms of the tremendous opportunity there and, you know, notwithstanding, we're in a bit of a tough position to give too much disclosure because of the customer concentration. Needless to say, that business is growing ahead of our expectations and we've tried to share some color on that. Certainly, you know, you and I have had a lot of discussion around, you know, AI and the number of different, you know, angles that Pure, you know, I guess Everpure, I should say, is playing in AI, whether that's in the enterprise space with KV cache and Inference, whether that's really reaching deeper into the Neoclouds with FlashBlade//EXA. So we've got a number of levers. You know, we're focused on sustainable growth and accelerating that over time more so than individual, inflection points. Yes. Yeah, I think your execution over the past several years is a proving point where how well you're situated with enterprises. Perhaps it's the hyperscalers that if I were to use a scenario analysis could provide the growth acceleration. Would you agree? I think that, I think that any of those levers, you know, could provide, growth acceleration. You know, we're looking to drive acceleration out of all of those. Yeah, I mean, just by, you know, kind of the size of the market and so on, you know, I mean, the hyperscalers, it has dominated our conversations. It's a huge focus area for us and, you know, it's one of the, one of the big drivers that we're really leaning into. Do you feel like you're in a situation where you wanna drive operating growth profit? Do you wanna drive operating margin expansion, but you also have all of these opportunities. How do you manage the OpEx? Right? Because you can allocate more OpEx to drive growth acceleration, but then you do give up some margin. Am I thinking about this right? You have to deal with a delicate balance, right? Yeah. So yeah, let me, let me share kind of our views on where we're focused. You know, I outlined and we discussed, you know, all of the exciting kind of areas that we see as capable of driving growth, the levers that we're pulling on, you know, to get there. So how do we then think about, you know, a resource allocation, and how do we think about driving growth versus profitability? You know, and the short answer is our thoughts and philosophy in that, you know, really haven't shifted. Charlie and Tarek, myself, the entire management team, you know, we are, make no mistake, we are focused on driving growth. We're focused on leaning into those levers, but at the same time, continuing to, you know, drive moderate leverage over time. Where we've tried to quantify that, just to kind of, roughly, for the street is we wanna drive top-line growth while, you know, every year creating, you know, roughly speaking, a point to the OM. You know, that said, and I think, you know, what Charlie, what Tarek has articulated, as he's joined is, you know, the better metric and where we're really more focused on is, you know, driving OP, or operating profit dollar, growth. Now obviously you can do the math and back into what the implied OM is, you know, that's kind of how we're thinking about the balance of investments, growth opportunities, also, continuing to drive incremental improvements to profitability. Does the 1touch acquisition help you with hyperscaler opportunity, enterprise or both? That was very interesting. My interpretation of 1touch acquisition is that, yeah, it does help you with streamlining the data sovereignty, data security. Maybe you could just quickly explain what the 1touch acquisition is all about and how is it gonna impact enterprise, hyperscalers or both? Yeah, happy to. Let me hit the first thing, the second thing first. We see it primarily targeted towards the enterprise and the parts of our portfolio that exists today, but also we will build in the future, targeted at the enterprise customer base. You know, what is 1touch? What is the strategic fit? I talked a little bit about this, or we did on the conference call. If I step back from it, you know, they really provide a couple critical capabilities that we will both continue to sell in their existing offering, but also integrate into our core technology over time. Those critical capabilities or the ones that come to the top of the list are data discovery, being able to automate data source discovery, data classification, right? Being able to look at different pools of data and then generate from that an understanding of, okay, what is this? Is this PII? Is this customer data? Is this, you know, health records, et cetera, et cetera. And then, the third is the ability to contextualize that. The ability to represent and capture semantic meaning of the data. If you net all of that out and you look at what we have been articulating as our enterprise data cloud vision, our intent is to integrate those components into Purity, into Fusion, into the enterprise data cloud over time, so that we can go help customers better understand the meaning of their data across multiple different sources, multiple different silos, and work with their data much more seamlessly. Charlie's talked about, you know, enterprise data is still trapped, still subservient to applications. We do a great job of providing the infrastructure for that today. Where 1touch and the integration of those capabilities will come in and help is it will help customers actually be able to integrate data across multiple sources without having to do the old school thing of ETL and copying data all over the place. You know, that said, we just announced the intent to acquire. We have yet to close the transaction. We expect that to happen at the beginning of our Q2. You know, as I was telling somebody the other day, then the work begins. You know, then we begin to do with the technology integration. Yeah, very excited about it. I think, you know, the strategic fit is quite exceptional. This goes back to what Charlie referenced earlier in the call, the new unified control plane, and I'm not sure how many people picked that up. When we think about unified control plane, and given where the data lakes are located in various places, the 1touch helps consolidate and actually make the unified control plane more effective, right? Yes. I think it complements it very nicely. You know, think of it as the unified control plane helps customers consolidate infrastructure. Where 1touch integration will help is they'll help customers consolidate the logical data and the use of data. It's very complementary. What's also fascinating, I'm just making an observation here, enterprises wanting to do inferencing or deploy the infrastructure for inferencing on their own, given data security and everything that you already mentioned. I do get a sense that maybe Pure is also strategizing to capitalize on this. How do you deal with the actual deployment of necessary server rack? You are still a point solution, but you offer a comprehensive storage portfolio. Is that your enterprise customer that has to think about deploying the compute and storage together, or is there like a third party that is involved? Am I thinking what is right? Feel free to correct me what I just laid out. Yeah. I think the essence of your question is, "Hey, we're a great data storage infrastructure provider. I'm talking a lot about additional software. How does the customer go and deploy that? We don't ship servers. What does that look like? You know, look, I, we work very closely with, you know, say, converged infrastructure partners, Cisco, you know, being probably the strongest one, where we do have converged, you know, everything from converged solutions and offerings to strong reference architectures with multiple server vendors. Of course our strong, you know, partner and GSI and systems integrator community, works to help with deployment for customers. You know, what I'd say is that with, especially with modern applications, the shift to cloud native, really Kubernetes and container-based deployment of applications, in some ways has made, you know, this part of the puzzle a lot easier to fill in. You know, frankly, the value and where customers are focused is, how do I deploy containers in Kubernetes quickly? In most enterprise customers, you know, they're getting to the point where, you know, if you can walk in and say, "Hey, I've got this software offering, it's container in Kubernetes deployable," they've got a Kubernetes team somewhere that, you know, knows how to go do that. You know, in some sense, the specific servers and, you know, racking and stacking that really has become commodity. It's not an area that we're particularly focused on. Do you have any efforts to work with different CPU architecture? There's also competition on which kind of a compute architecture would do the inferencing, the XPUs and CPU and so forth. There's a diverse set of technologies out there, right? Yeah. There's a diverse set of technologies. You know, we work with, and our, really, our customers deploy solutions on, you know, just about all the major CPU vendors, major and less, I would say, smaller, GPU providers as well and, you know, everything in between. Clearly in the, you know, GPU space, the bulk majority of our customers, whether it's training or inference, you know, are running on NVIDIA, whether it's, you know, NVIDIA GPUs in third-party servers or, NVIDIA-provided servers. NVIDIA continues to be, you know, an incredibly strong, you know, partner, for us and a focus, you know, really the focal point of our, AI solutions development, as you might imagine. Sorry. There's a fire drill going on. Apologies for background noise. A literal fire drill. Want to pivot back to this supply chain and focusing on the enterprise side, because on the hyperscalers, they're helping you with procurement. On the enterprise side, how much of a visibility do you have with the demand? Like is there like a backlog? Because you have to turn around and think about procuring the NAND, especially the tightness that may not go away. Help us understand the contracts you have with the NAND suppliers for enterprise application and how are— Is there any flexibility to adjust the shipment, and how does the pricing kick in here? How often does the pricing is negotiated? I mean, what I'd say is that, you know, our supply chain team, you know, for years, has been top-notch. You saw, you know, you saw the incredible work that, you know, they did to position us well through to weather the post-COVID supply chain tightness, you know, in calendar 2021. The nature, you know, I'm not gonna get into specific contracts and kind of numbers, but the nature of our, you know, strategic agreements and long-term agreements, You know, with our critical suppliers, hasn't changed. If anything, that's, you know, really strengthened over time. We, as you might imagine, have multifaceted, you know, sets of agreements that at the end of the day give us, you know, very good visibility into our enterprise supply. You know, I will say, and Charlie touched on this on the call as well, you know, there are many components that go into, you know, a finished solution. I would say the tightness on the overall supply chain situation right now is not just constrained to NAND as you would know, you know, covering the industry. It stretches everything from NAND to hard disk drives to HBM, high- bandwidth memory, to DRAM, to CPUs, to networking cards. Our teams are, you know, very hard at work and busy ensuring that we have the supply we need to meet the, you know, enterprise demand that, as I mentioned before, is quite robust. You know, we do benefit from the same structural advantages that I think helped us through the post-COVID tightness. For your audience, just as a reminder, because of our software efficiencies, we're able to use far less components, to the order of 20%-30% than a lot of our enterprise competition. The fact that we have one unified hardware technology means that our overall BOM or bill of materials is a lot lower. There's fewer different parts to go chase. I have a lot more flexibility in steering mix in terms of, you know, a lot of shared parts means that for whatever I source, I have more flexibility to build all the things in my portfolio. You know, these are things that, you know, I think, we're also leaning into. Got it. Two quick follow-ups. Can you update us on the mix of the QLC NAND that you're using, and how does that mix changes into the second half of the year? Yeah. I mean, we've been shipping more QLC than TLC, you know, as a business, in the enterprise, so setting aside the hyperscalers, you know, for quite some time. You know, I think that mix continues to shift more and more towards QLC, but it's been over 50/50 for quite some time. I haven't looked specifically first half, second half, but the mid to long-term trend is pretty clear. It, you know, it's kind of the QLC portion is growing. Yeah. To what extent are you able to pass on the incremental cost increase to your enterprise, customers? You know, I think the best way to look at that is the commentary we gave on gross margin implications, you know, which is that which is to say we do expect, you know, we do expect near term pressure in Q1 gross margins on the product side, specifically because the input costs grew very, very rapidly in the back half of Q4 faster than the ability for the market pricing to adjust. We've since taken pricing action. We do expect the effects of that pricing action to really help us recover those gross margins starting in Q2 and then throughout the year. All of that said, you know, we don't, you know, to be very clear and to restate, we don't, you know, we don't think of our pricing philosophy and our pricing actions as being gross margin driven. We look to the market. We price in a competitive space. We command a premium for our solutions that's reflected in our long-term gross margin benefits over the competition. What happened here was that again, the rate of input cost increases was almost unprecedented, faster than the market could adjust pricing. What we've done in those pricing actions is we've reevaluated, reassessed where market pricing has moved to accommodate the new higher level of input costs. We've adjusted our pricing. That's really what you're gonna see, starting to flow through Q2, Q3, Q4, so that the gross margins, you know, recover back into a healthy part of that long-term range of where we wanna be at the product side, 65 to 70 points. Great. Okay, we're a minute over the time. Wanna thank you for giving us opportunity to catch up with you post-earning. I wanna thank everyone on this call for participating. If there's any follow-up from investors, feel free to send me an email, mehdi.hosseini@srg.com. I wish everyone a great weekend. Thank you, Rob, and the rest of the IR team. Thanks, Mehdi. Bye.