Everpure, Inc. (P) Earnings Call Transcript & Summary

Thank you very much for joining us this afternoon. I am Aaron Rakers. I'm the IT hardware analyst and semiconductor analyst here at Wells Fargo. With us, we've got the Chief Technology Officer of Pure Storage, Rob Lee. Rob and I have known each other for a while now, and we're going to get into some details as we had some news last night. But before we do that, I'm going to do my best to read this safe harbor statement. Statements made in these discussions, which are not statements 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 Storage's most recent SEC filings on Forms 10-Q, 10-K and 8-K. I think I did all right.

You did a pretty good job. Perfect.

Thanks, Rob. So first of all, thanks for joining us. I had a list of questions I mentioned before we got up on stage last night's news is probably going to change a little bit of the path we are going to go down. But you guys announced hyperscale win last night. I want to start at the high level for everybody that's not that familiar with Pure why?

What makes Pure unique in their ability to even get this opportunity to participate in this market -- we've been talking about it for a while, but I think it's great to start there and maybe unpack.

Yes, absolutely. So if we go back to the beginning of Pure, we have always had the vision of replacing all the disk in the data center. And we started our journey in the enterprise. And if we look back over the last couple of decades, the enterprise really has led the way in terms of deployment of flash at scale in mainstream workloads. Hyperscalers to this date have lagged in that mainstream deployment for a number of reasons. And those reasons generally come down to, they have been able to do the engineering. They've been able to get the TCO benefits out of disk that they previously have not been able to get from flash. Flash is all these great properties. But at the end of the day, hyperscalers have been able to make their disk-based systems perform well enough at just cost profile that is significantly advantageous. What we have done and really what led to the design win is frankly, has broken those barriers down, right? And -- let me unpack that a little bit, right? We've been engaged really over the last 1.5 years in discussions with a variety of hyperscalers, touting the benefits of our technology, the same technology that drives our enterprise systems to take the best benefits of flash, deliver unparalleled reliability at scale, deliver much higher performance levels to deliver significant power, space, energy savings, you total all that up, and it translates to significant TCO savings. And what's happened really over the last several years is a couple of things. One is breakthroughs in the technology, right? As we've talked about our direct-to-flash approach really extending that to much higher densities, capacity levels that really start making the TCO equation for hyperscalers in particular, look very compelling. So that's number one. Number 2 is a laser focus from the hyperscaler set on power availability, right? It's no secret. You look at the news. All of these hyperscalers are scrambling to get power. If they look in their data centers today, a large part of where they're spending their power sits on storage, a large part of that sits on near-line disk storage. We can go reduce that significantly. That's become a key critical element. And so when you net all of that out, those are the key drivers. It's still a big hill to climb. And we've been plotting our way up that hill for the last year, working hand in hand with -- well, multiple hyperscalers, but our lead customer, in particular, moving through early assessment of the technology, really deep understanding of how that would fit into their designs, what that would mean in terms of TCO, reliability, operational considerations. And then now with the design win announced becoming part of that plan of record in terms of how they're planning to deploy their next generation of storage architecture.

Yes. So fantastic announcement. I mean I think that it's important to kind of note like -- first of all, I've never seen an enterprise -- there's no other enterprise traditional system vendor that's participated in the hyperscaler cloud. So when you think about it, you've got -- how do you think about the size of this opportunity that it presents. And I've heard you mentioned it a couple of times, multiple, right? It's not -- you got one lead customer, but this lead customer begets maybe the opportunity to participate more quickly at others. Is that fair?

Yes, absolutely. And so a couple of pieces to that. So number one, yes, this is very unique. Certainly, I would say it's first and only of its kind in storage. I would say the next nearest comparable would be what Arista has done in the networking space, as they've moved some of their technology into the hyperscalers. Now if we look at what we're doing in terms of sizing the opportunity, A couple of data points, a couple of things to think about, right? Number 1 is just taking a look at the nearline hard disk estate overall. I think Charlie shared on the call last night, we size the annual , and this is the annual deployment of nearline hard disks in the hyperscaler environments, to be somewhere in the order of 600 to 700 exabytes a year total, all in, right? And so that gives you a sense of just the enormity, right, of disks that are out there that we believe we now have a play forth. If we look at how does that play out over time, that set of disk deployments is very concentrated, right? If you look at really the -- most of that sits in the top 10 right? And so the same conversations, the same technology that we have developed for our lead customer, we believe it's highly applicable. We were talking to multiple other hyperscaler prospects about the same technology, integrations to their environments. We see a lot of commonality in terms of what they're looking for in the space. And so to the last part of your question, yes, we do believe knock on wood, we're not going to make any predictions. But I do believe that being able to come out and announce the design win, certainly, the partnership with our suppliers as well, what we're doing with Kioxia will serve to accelerate our path with other hyperscalers. To some degree, there, I think, has been some doubt in the industry of, "Hey, is this real"? Is now the time can this actually happen and being able to existence is worth a thousand words. And being able to go and prove that out in one hyperscaler, will absolutely help us in the other engagements. Because remember, at the end of the day, storage technology is not an area where these firms are competitive with one another, right? So we believe that will be a tailwind.

Yes. And I'm going to put a little bit of context around what you just said. I mean 600 to 700 exabytes of hard disk drive capacity ship. The company last night alluded to like double-digit exabyte by calendar '26, fiscal '27 for you guys. I mean if my math is right, I think you guys -- even that double digits is significantly more than what you're shipping annualized today, maybe in the -- I think I put in my note 3 to 5 or 3.5 to 5 for exabytes today. I'm guessing that's the right kind of sizing of this -- this opportunity is very large, but at the grand scheme of thing, it's just scratching the surface on the size of the...

Yes, I think that's a good way to think about it. And a couple of items to add to that. So the double-digit exabytes that we're talking about in fiscal '27 absolutely is significantly larger than what we're shipping today. It's also, I think, the first year of scaled ramp that we're expecting, right? So we -- if we step back and we look at, "Hey, where are we in this process for the last year", we've been engaged in really technology assessment, working our way to that design win, getting to part of that plan of record. Really over the next year, right, the way we expect things to play out is as this hyperscaler customer moves closer to production, they've got a set of stages to go through, moving from advanced prototyping to completing their integration and implementation of other parts of their data center design of that generation, doing scale kind of field testing, if you will, more detailed field testing, testing of smaller-scale production deployments all the way to scale ramp. We expect that to largely play out over the next year and for that scale ramp to start beginning to occur in that fiscal '27.

Perfect. And I think the context of the call last night too was like it wraps around a design that they've done for their next-generation data centers, right? You're not naming the customer, but it actually, these customers, these type of customers lay out an architectural design of the data center and then they kind of -- that's the blueprint they follow on multiple data centers. That's how you'd characterize this?

Yes. That's a very good way to characterize it. Again, all of these firms, they drive incredible economies of -- well, hyperscale by standardizing, standardizing on a small set of blueprints that they can go and stamp out multiple times. And so when they think about storage as an example, they absolutely do not think about storage on a workload by workload or project-by-project basis. They might have slightly different designs for their high performance, their mid performance and low performance, but they've got to design for that horizontal tier. That design is going to generally last for some period of time during that period of time. Storage deployments that are put out, whether it's brand new data centers, whether it's completely refreshing older data centers that are kind of coming due, are generally going to be that blueprint just stamped out.

That's perfect. So I maybe should have went down this path a little bit earlier, but talk a little bit about -- I'm going back to the why, right? The why being the architectural attributes of Pure, right? What you do at Purity OS. How that kind of segues itself into what you can do as far as the DFMs and the scaling of the DFMs. Talk a little bit about that, if I compare you guys versus some of the traditional vendors, what makes Pure different?

Yes, absolutely. So if we look at the hyperscalers, one of the questions that we've gotten is, "Hey, so great design win." Who are the other competitors in the space. And we've been emphatic that, "Hey, there were no other outside vendors in consideration and this goes to the why." The why is because there's nobody else in the industry that has the direct-to-flash technology, the IP, really the flash know-how and smarts that we bring to the table. Okay. So then why is that important? Well, that IP, our direct-to-flash approach, the fact that we do not rely on commodity SSDs, it's that IP that allows us to bring out this much higher level of reliability, much greater degree of performance, a much greater degree of efficiency through density, right? to give you some data points. When we talk about reliability, right, our direct flash modules, they're generally -- our annual return rates are generally below 0.2%. right? Industry kind of averages standards for SSDs are north of 1%. Hard disks closer maybe to 2%. So when you think about that, okay, so that means we're 5x more reliable than SSD, but wait, our direct flash modules because they're simpler because we've removed a lot of the complexities that are inherent in SSDs, we can build much denser packaging. We can ship more storage per unit module, then you can get an SSD. So to me, the customers need, if I can deploy 5x fewer of these modules and they're 5x more reliable on a unit basis, while my reliability is 25x higher, right? And so you get these multiplicative effects so that when you step back and you look at it from a system level, you look at it from -- at the scale that these hyperscalers are considering, a 25x improvement in reliability is massive. Right, when you're running a consumer-facing cloud service.

And I would imagine you didn't touch on there, but the power consumption envelope, like we met with Dell yesterday and one of the conversations was, hey, a few years ago, a typical rack server might be 15 kilowatts of power consumption. They're going to ship. They've got a rack now that's 480 kilowatts in a single rack. So the power consumption envelope is a big deal to unpack that a little.

Yes, absolutely. So we generally require power that's about 1/5, sometimes 1/10, the power of competitive solution -- all-flash solutions. And when you look at disk, it's sometimes even a greater difference than that. And a lot of that, again, comes down to the direct-to-flash approach. At the end of the day, the core difference between our approach to delivering flash and everybody else is they rely on SSDs. SSDs do a ton of extra work, a ton of extra translation that introduces a ton of additional inefficiency. You can measure that inefficiency in cost space, in power and reliability and for us, never having had that inefficiency built into our software, well, every step along our road map as we increase our densities as we move to newer generation NAND, the benefits we create out of that IP, the benefits in terms of reliability, performance and efficiency just get magnified each step of the way.

And again, on the DFM today, we're shipping 75, 150, the road map from here is?

So we're expecting in the 300s next year. And we see a path to going beyond that. But look, 300s, even the 150s represent a 4x increase over -- 3 to 4x increase over where we were just 18 months ago. And so it's -- we're in an incredible growth period in terms of improvement of the technology. And again, bringing this back to the hyperscaler, right? I think that's another reason why we were chosen as design partner for this hyperscalers designs is these are highly technically sophisticated organizations. They want to work with bleeding-edge innovators such as ourselves.

And then I'm going to move on after this with the hyperscaler discussion. But clearly, last night, this is a different sales motion, different type of monetization for this opportunity than traditionally sell into an enterprise. So it's a licensing model based on capacity under management. I'm 100% certain you're not going to give me the numbers, but -- just help us understand maybe the mechanics of the monetization piece of this?

Yes, absolutely. So -- and we discussed this on the call last night, -- so first things first, the hardware, while the hyperscalers will be deploying hardware as part of their total solution, hardware will not be part of our sale to the hyperscalers. We'd expect the hyperscalers to source the hardware through there and supply chains, et cetera. What is part of our arrangement of construct with the hyperscalers really, as you alluded to, there are 2 pieces. One is, think of it as a technology license. I would expect that to be on a per capacity deployed basis. And the second piece of that would be more of a support and maintenance agreement and would expect that to be on a time basis. So think of it as not dissimilar to annual maintenance and support type of agreement.

So the hurdle from here is, I mean, the deal is done, right? It's just getting through the processes at that customer to start volume deployment Okay?

Well, so what I'd say is the deal, the design win that was announced is really being selected and being part of the plan of record in terms of how they're going to go build their total end-to-end solution, right, and design for that data center generation. That said, right, there's work ahead, right? And the work ahead really is for the hyperscalers to go through those phases to move to production, go into completing the rest of their integrations implementations, do much more detailed field testing, dotting the eyes, crossing the Ts, building up at smaller scale testing, all the way to the full ramp. And we certainly expect to and will work very closely with a hyperscaler along that process. But in terms of big hurdles across, we don't see any specific ones other than business as usual.

Yes. That's perfect. So I'm going to shift gears. You being the CTO and thinking about there's the perpetual flywheel of like the what's next. As you think about pure, company has done a fantastic job of building out really truly a portfolio company. Now you layer on this hyperscale opportunity, but really broadening the platform strategy, if you will, of the story. You mentioned Arista in an earlier comment. How do you think about the cadence of like what's next on a road map? Are there areas where you're like, hey, this is a feature functionality from here? How do you think about that with CTO perspective.

No rest. We just announced the design win last night and you are....

I'm only thinking about what's next?

No, it's a great question. So I would call it a couple of things. So I think we've matured our sets of capabilities and really put the last puzzle pieces in our portfolio in terms of discrete products and areas of workloads in the market that we want to go cover. I think the couple of areas I'd call out are: Number 1 is really expanding, expanding our platform strategy and building that platform effect. And Pure Fusion has a big part to play in that. When I step back from it, where we were 5, 7 years ago was a point product company, right? We had individual point products. You've got this workload. I've got the best thing for you. Over the last -- the next couple of years was about filling in different point products in that map. I think we've got a pretty good coverage of those key workloads from super high performance all the way down to AI to archives. And we can do it with one consistent software architecture, one consistent hardware technology. I think the next leg forward really is about how do we [ tie ] together in more of a platform effect. How can we make it so that when a customer selects Pure, they're not selecting Pure for just one workload. They're selecting Pure for their entire estate or large portions of their state. Pure Fusion has a big part to play in that by virtualizing how customers manage and have to think about their data states. By moving them from thinking about and configuring and purchasing storage array by array, workload by workload use case by use case, to much more of a horizontal enterprise-wide purchase, right? If you, as a customer, don't have to think about, hey, I need this much storage at this performance level for this database, which is different than this other workload but rather, hey, I need a little bit more of Pure at the high performance level. And I just drop it in there. It's a pool of resources. It automatically goes and gets deployed. That's kind of the next leg forward for us, a lot of technology that has to go into enabling that. We've been working on that vigorously, I should say, over the last couple of years and the recent release of CareFusion 2.0 is a big step forward. The second area I'd highlight is continuing to build on our subscription services, right? And -- it's more than just subscription, I should say, continuing to build on our full as-a-service portfolio. We've made great strides in kind of the first innings of that in terms of Evergreen One. But I think we've still got a room to run there.

Yes. And -- on the Fusion strategy, you said it earlier, like a virtualization layer. So it's like the management layer that allows you to manage depending on your SLA, your workload requirement, how do you kind of click and select certain capabilities, performance-wise or whatever it might be. Version 2, I think at your end user event midyear, you kind of outlined the road map of where that strategy is going. So version 2, what's the next thing there?

Yes. So -- really the big difference, and I think you summarized the capabilities quite well. And we've been working with early customers over the last year with this set of capabilities. But our initial challenge has been that it was net new -- applied to net new deployments. What version 2 brings is a nondisruptive upgrade for existing customers in the installed base to take an upgrade and all of a sudden have all the capabilities of Pure Fusion. So it's really about making that technology much more broadly available to our installed base and across our entire product set. So that's really the big -- the first big step forward. I think the other thing I'd call out, so there's really -- ultimately, at the end of the day, it's about bringing the cloud operating model to customers on their own premises. Right? If we think about some of the lessons we've learned and working closely with our now hyperscaler customers, it's about how they run and operate their storage services beyond just the hardware, right? Hyperscalers, when you as a customer go to a hyperscaler and you sign up for an [indiscernible] service, that doesn't create an IT ticket that causes somebody in the hyperscaler to go and take a physical action to deliver that thing, right? That's all automated. It's all done by software. It's all managed automatically and provision. That's not how the enterprise data center works today. That's what we're solving with Pure Fusion.

And is that a -- remind me, in Pure Fusion when you go in version 2 and you provide that capability is a nondisruptive upgrade. Is that a monetization? Is that actually -- or is it like a seamless upgrade. It's a free optionality to -- that's one thing that Pure has done really...

Yes, it's a great question. So it's a seamless upgrade. We want to drive adoption to this, right? Because, again, we've done a great job, I would argue, as a company of making individual arrays, making enterprise technology that has historically and still our competitive set makes horribly complex. We've done a great job of making that very simple. We're now at a phase where, hey, how do we make somebody who has 100 arrays not have to do something simple 100 times, right? And so a lot of the initial phase of Pure Fusion is really about driving adoption, making it more widely available because it will make it easier and incrementally better for customers who have large installed bases of Pure Technology to add to that pool, if you will.

Yes. So it's a wallet share gain opportunity rather than a monetization. Talk a little bit about in the time we have left, AI, the opportunity in storage is definitely discussed a lot. I think it's for myself and I think a lot of investors, hard to really tangibly see the evidence that is a catalyst on the traditional storage market at this point. I think we can all see -- we see somebody like a WEKA and VAST and some of these guys that are in some of these large-scale AI cloud deployments. But how do you -- how does Pure think about AI as an incremental growth driver. What have you seen to date or what are we looking for over the next 12 months?

Yes. It's a great question. And we really see AI, the impact of AI and data storage falling into a couple, it had 3 high-level categories, right? Certainly, you've got a relatively smaller set of directly connected to GPUs, AI training environments that need high-performance storage. Secondly, you've got a set of I would say, more enterprise-driven AI deployments, folks that are doing inferencing, folks that are trying to deploy RAG type architectures. And then the third set is really, I would say, AI-influenced storage modernization, right? Enterprises that are maybe sitting on massive amounts of very siloed, oftentimes locked away on cold, slow disk data that they want to make available to AI, but if you can't connect the data, how are you going to go do that. And so we see the effect on data storage really falling into these three buckets. And we continue to pursue each one of them, right? We've got some great leading customers in the AI training space, Meta, as we've spoken about over the years, has been a great partner in their research supercluster utilizing our technology. We we're able to expand our partnership with CoreWeave this last month in terms of enabling their environment, their storage environment in the GPU cloud and a whole host of other customers that -- in the AI training space. I would say the enterprise inferencing space is, I would say, earlier innings, to be clear. In my discussions with the enterprise, I see the whole gamut, right, of customers that are -- sorry about that I was odd. I see customers spending the entire gamut of early adopters, folks that are leaning in and heavily experimenting to others that are really just trying to figure out where to get started. I think the enterprise inference opportunity, I think it's going to still take a year or 2 to play out. I don't think the technology has consolidated quite enough yet. I think folks still have a number of things to sort out in terms of security and compliance and also just finding the right use case. So I think that will take some time to play out. I would say, in some ways, the third category, AI driving customers to modernize I would say that's one of the larger categories that we see discretely appear.

You mentioned -- one of the questions I get every once in a while is the Meta AI RSC footprint, there was obviously, news about a competitor getting some opportunity within that deployment inside of Meta. But your engagement with Meta on that footprint is still very much active. Is that a fair assessment?

Yes. No, absolutely. It's -- our engagement with Meta on multiple environments continues on an ongoing basis. I'm personally involved in many of them. We just don't speak of most of the environments. And to be clear, I think the competitor you're speaking of, I think that was a different project that was -- that is a very large company, and we're able to speak of just the RSC environment.

Yes. That's very helpful. And then on the CoreWeave side, just real quickly, that -- that relationship was announced a month or so ago, I lose track of time, but it was the cloud, the large-scale GPU specialized cloud guy that was alluded to a couple of quarters ago. That is an Evergreen One relationship. So walking like CoreWeave's customers are giving the option to use Pure under Evergreen One as a back -- the back that you....

Yes. No. So your recollection is absolutely correct. So I think it was 4Q of last year. We talked about an 8-figure GPU cloud deal. That was -- we can now say that was CoreWeave. That was an Evergreen One deal. And just a few words on that. I think Evergreen One was an ideal construct for CoreWeave because they're effectively a specialized cloud -- GPU cloud provider to their end customers. And so Evergreen One gave them a ton of flexibility and optionality in terms of rate of ramp, rate of actual storage consumption, optionality in terms of mix of performance versus capacity required and just ultimately gave them one less thing to have to go and take risk and have to go think about. And so that deployment has grown quite nicely. And really the expanded partnership we announced, yes, it was about a month ago, is to take the learnings from that, the success from that and make that more broadly available for other customers within the CoreWeave cloud.

So that's how systems sitting in CoreWeave data sets that you guys own?

That's correct. Right? We own as part of the Evergreen One relationship. But that Evergreen One relationship is with CoreWeave. That's not exposed to the end customer. The end customer is buying services from CoreWeave.

Okay. So it's actually -- the consumption is actually coming directly from CoreWeave. It's not -- they're signing up a customer [ cloud ] -- they're all kind of tied together. Okay. With all that said, I'm going to go back to where I started. When you think about the strategy of Pure, you think about this hyperscale deal, when we think about the growth profile going forward, what excites you to move? Maybe let's take the hyperscale and set it to the side, what else excites you about the growth ahead for Pure?

Well, I think we're in a great position to -- look, we play in a huge market. If we just look at core storage stat. We play in a huge market that we're now in a great position to go and expand with them, right? That position is driven by a very complete, but also a very tight set of products and technology, right? One hardware technology, one software technology, 2 basic architectures that can cover the entire span of price performance levels, AI to archive, block file and object. We're now in a position to walk into the enterprise and not just have a conversation about, hey, do you have this workload, I've got the best thing for you, but to be able to go in and say, hey, how would you like to go and modernize your entire data storage estate, get all of these benefits reduce a ton of risk and just make storage something you don't have to think too hard about it anymore. And so there's -- we're in a position to do that against a competitive backdrop where, look, our competitors are not keeping pace. They're not innovating. They're not -- I love my competitive set, [ hear ] it that way. And so I think there's a ton of opportunity there. At the same time, we're continuing to push the boundaries. We're continuing to push the boundaries of what people think are possible. I think we were speaking before this. I think there were a lot in the market, the financial market as well as the industry that had doubts about our prospects in the hyperscalers. Hopefully, we've been able to lay those out, but we're continuing to push boundaries in terms of performance levels that we can deliver. We're continuing to push boundaries in terms of business models, right? This idea of taking a SaaS -- a true SaaS experience and bringing it to customers in their own data center. It is early innings. We talked a little bit about the just kind of quarter-to-quarter dynamics on that, but it's absolutely the way the future is going to go. And then also the cloud operating model. I think we're in early innings of just transforming the way people manage their infrastructure. It's super, super antiquated today, and it doesn't have to be.

Bob, thank you so much for taking the time.

Thank you.

Great discussion.