Backblaze, Inc. ($BLZE)

Hi. My name is Frantz Famie, and I cover technology and investment banking for BofA. And today, we have the pleasure to receive Gleb Budman, who is the CEO of Backblaze. And Gleb, I think not that many people know who Backblaze is, right, and especially the story around like being able to the history of you, the way you founded your company and everything.

So can you maybe walk us a little bit through the history and where you are today?

Yes. And thank you, everybody, for coming and joining and chatting. So it is painful to say not that many people have heard, I mean, we have 0.5 million paying customers. But I don't think you're wrong. I think that our opportunity to be better known is quite large. So we started the company almost 20 years ago in 2007. We initially started it in the cloud backup space, but we ended up designing and building our own cloud infrastructure for that purpose. And so today, we are essential infrastructure for AI. And I certainly talk to more of how that's the case. But it started from a need of we needed to build storage infrastructure that was high performance and very efficient for the purposes of providing it to our cloud backup service. And our original plan was to store that on AWS. We did the math, realized we were going to lose money on every single customer, started from first principles, wrote our own file system, built our own infrastructure, built the whole stack and offered that to our cloud backup service. Over time, companies came to us and said, "Love your cloud backup service, but you built this great infrastructure as a service, give me access to that for all of my other storage needs." And so we launched Backblaze B2, and that is now the dominant part of our business and what we offer to the market. We still have the cloud backup service, but the focus is the Infrastructure as a Service.

And what are some of the pain points that the legacy hyperscalers cannot address that bad place is able to like feel?

Yes. So for a long time, one of the key things that people were coming to us for was simple. It was -- it's a 1/5 the price of Amazon S3, and that was simply a compelling value proposition, right? You need storage, it's less expensive, that's easy, right? With AI, there's been some interesting new shifts, right? There's this big replatforming happening. We just heard from one of the neocloud companies. There are a variety of neoclouds that are out there. And they are -- and customers are choosing to use them either because of availability or performance of GPU infrastructure or because of the software stack that those neoclouds are focusing and providing, right? And in order to use any neocloud, your data can't be locked inside of a hyperscaler. And the hyperscalers all try to keep your data locked up inside of them. And for many, many years, the last 2 decades, most customers have felt that, that was fine. Most customers have felt, "I use one of the hyperscalers and I use the services they provide me and it's fine." And what's increasingly happening now is the customers are saying, "Sure, maybe I use one of the hyperscalers for X, Y and Z services. But in order to stay innovative in order to do the AI workloads I need, I also want to use that neocloud, this neocloud and that neocloud. I might want to use this inferencing provider. I also may want to use one of the different CDN providers that are out there. I need to use infrastructure that's not part of that one single hyperscaler. And to do that, I can't have my data locked inside." And we had one customer I remember, they developed their whole own infrastructure and they were using one hyperscaler. That hyperscaler didn't have the availability of the GPUs they needed. So they literally did a whole engineering effort and migrated their entire system over to another hyperscaler. A few months later, that hyperscaler didn't have the most efficient GPUs that they wanted for this. And so then they paused because they were thinking about moving it again, and they paused and said, wait, this can't be the way we operate. We have to free our data so that we can use whoever we want to use. And Backblaze provides you this independent location to put your data efficiently in a high-performance, low-cost way, but one that provides you free egress and good connectivity to all of the places you would want to use. And so that's been a key benefit to the customers that the hyperscalers just don't provide. They can't because they don't want you using all these other services. They want you using their services. So that's been a key part. So that's one. And then the other I would say is for the neoclouds themselves, initially, most of the neoclouds started just renting GPUs. And many of them are trying to go more full stack and offer additional services, but be part of the way that AI gets built. And to be part of the way AI gets built, you have to be part of the customers' workflow. And all AI workflows require data and generate data. And so the neoclouds increasingly realize they need to offer cloud storage as part of their offerings. And so we have a white label version of Backblaze B2 for the neoclouds, which, again, they don't really get from the hyperscalers because they are their competition. So if you think of it as we're serving kind of 2 sides of the market. We're serving the actual builders using AI in order to enable them to use whoever they want. And that's critical for them to innovate. And we're also serving the picks and shovels of AI, the neoclouds and others who have realized they need to offer storage as part of their workflows for their customers.

Okay. Can you maybe expand a little more and go over like a case study of specifically for AI on how you're able to -- what was able to transform a company going through like the AI transition?

Yes. So I mean I'll give you, I guess, examples on both sides of that, right? So on the demand side of things or on the side where the builders are, right, so I was actually talking to a company just a week ago. They are in the GenAI media space, right? So they build a model in order to then use that model for inferencing where the customers can prompt and create video. There are now hundreds of these companies out there, right? And so they are collecting lots and lots of data sets in order to build their models. Those data sets were previously stored on the hyperscaler. They were finding it increasingly painful because not only are they -- was the expense of storing the data becoming prohibitive for them for their business, but they were using multiple neoclouds as well as one of the hyperscalers actually for the model building for the GPUs. But getting the data from to these different places was just crushing them, right? And so they moved all of that data over to Backblaze. So now they're able to have one single large data lake with tens of petabytes of data just for them, just for their model building. And they can use it and send it wherever and however they want, it's free to do. It allows them also to innovate faster. It's not just about the cost. It allows them to innovate faster because in the past, because it was so expensive to get the data to the different GPU locations, they were doing fewer training runs fewer iterations on their model because they have to balance it was too expensive to get the data to the GPUs. Because they were able to send it when they need it, they could do more training, more frequently, innovate faster. So that first part. Then the second part goes to the inferencing part, right? A lot of our customers that came to us in AI came to us for the model building because that's the first part. That's where they have these large data sets to start. But they are a GenAI media company. The whole point is to create videos. So now they're talking to us about the model itself, the inferencing is creating videos and they're storing all these videos out there. Once created, these videos live on at this point forever. Maybe at some point, they'll decide to not, but at this point, they keep them forever. And so that data volume just grows and grows and grows. They need to send those videos to their customers. They want to send them as quickly as possible. It's very important for them to get fast. We've developed something called Sard Stash. It's a patent-pending technology, allows you to ingress the data as quickly as possible. One of the things they told us is that ability to get it out of the GPU and into storage as quickly as possible allows them to free up GPU time. So again, it allows them to be faster and more efficient with their business that way. And then our free egress and connectivity to all the CDNs means they can use the fastest CDN available. So it really is almost an end-to-end workflow that enables their business to not only be much more cost efficient, but actually more innovative and faster. That's on the demand side. On the supply side, on the infrastructure side, we've talked about how we've signed multiple neoclouds. So if you go to neocloud A, B or C at this point and they say they offer storage as part of their product set for a handful of them, it's actually Backblaze underneath white labeled for them, right? And so how has that changed for them? In the cases of 2 of them, they had storage before. What this is enabling them to do is offer storage that is better, faster, higher throughput. It's a better offering that scales more. For one of them, it was a completely new product offering. So they were able to expand the value they provided to their customers and have customers be stickier to their entire workflow. So those are 2 examples of how we're helping the 2 different sides.

Okay. Yes. And I think during your last earnings, you disclosed a lot of traction in AI, right, including, I think, 76% growth AI customer. Can you maybe discuss more your recent traction in AI? And how large you think that can become as a growth vector for the company?

Yes. I think the other thing that we talked about is that 1 in 3 of the new bookings came from AI, right? I mean, it's a material change for the business, right? And as we look at it, I think we are still scratching the surface of it. The urgency that we're seeing from these companies, one of the examples that we gave was that we signed a customer that was roughly $1 million of ARR in 11 days, right? So they clicked on a link and they signed a contract like an ad click on an ad and signed a contract within 11 days for about $1 million of ARR, right? So that is a very fast close cycle, right? And it just speaks to the urgency that these companies are feeling around the Infrastructure as a Service storage need that they have. So I mean, how big can this be? I mean the market is huge. The opportunity is huge. When I think about just taking this one single GenAI media company, right? So this one single GenAI media company that I'm talking about, it's a good sized 6-figure, high 6-figure type deal. That's only the training data, and that's only the training data today. So one of the things that they're doing is they're continually adding more to their training data sets, right? So one of the things they've talked about is, well, now they want to create these videos not only in English, but they want to create them in all the languages that are available around the world. That's more training data, more training data and more training data to improve their model. So the training data grows. But the training data, as far as their business is concerned, is just cost. The inferencing is where they will end up getting all their value. So the inferencing has to be orders of magnitude bigger in data than the training. Otherwise, the model for them doesn't work, right? And so just thinking about is we signed a customer in GenAI media, high 6-figure deal, fairly short sales cycle and that training data is growing. And then the inferencing side has to be orders of magnitude bigger. For that one single customer, there are hundreds of these GenAI media companies today already. That's just on that one single segment. On the neoclouds, we estimate our opportunity for it, right? So neocloud Infrastructure as a Service, just storage, just storage at the data lake layer, right? So not talking about high-performance flash sitting with the GPUs, which is not what we offer, right? There's like half a dozen companies doing that. There's very few choices for large-scale, high-performance data lake. Just that part of it, we estimate about $14 billion, right? So we are leaning in heavily into this AI opportunity because of all the opportunity we see. We've built a business that is growing and steady and great supporting ransomware protection, backup, archiving, media workflows, that continues to be a good, reliable, steady growing business. But on top of that, we're leaning in heavily to the AI side because of all this opportunity.

Yes. And can you maybe go into some of the innovation that you -- like recent product releases or new features or products in the pipeline that you're excited about specifically in that data lake, high-performance data lake market?

Sure. Yes. So I mentioned one, which is shared stash. It's not that new. We released it a little while back. But it's an example of, I think, how you can innovate on the storage layer, right, which is one of the things that we heard from people was that the ability to quickly upload small files was important. And we analyze every single step of the way when you upload a file, what is every single step that it takes to get that file actually uploaded. We found that the slowest part of it was the acknowledgment itself from the hard drive back to the user, and we were able to build technology to optimize that piece to make it both faster and cheaper than other providers, and we have a patent pending on that. So it's an example of technology, not a feature to the customer, but a way that we've built as one of the people said, the bottom part of the full stack, like the part where, how do we optimize the technology stack to make it as efficient as possible using software. On the release side, 2 things that I'm excited about. One is B2 Overdrive. B2 Overdrive was our extremely high throughput offering to the market. And it came from conversations that we actually had around GTC and NVIDIA's GTC last year, not this year, where we talked to customers and they were talking to us about this need of saying, I've got this huge data set, when I've got it all assembled and when I've paid for the GPUs to start being available, I need to get this from here to there as fast as I can because otherwise, those GPUs are sitting idle and it's extremely painful and expensive, right? So I need to move that data quick. But until I'm ready, that data needs to be in a durable and affordable place. And that's an ongoing thing. So we built this B2 Overdrive, which is an extremely high throughput up to terabit per second offering. The other one that we launched more recently is B2 Neo. And B2 Neo is the dedicated white label offering for neoclouds that provides the high throughput, the durability and everything else, but also provides manageability controls for the neoclouds to be able to manage rate limits and users and all that.

Okay. Yes. And as a public company, what do you think investors are missing about like bad place, whether on business model, products, team, like what would you like to highlight to...

I mean I think investors I think one of the things that gets missed is sometimes people go, isn't it just a bunch of hard drives, right? We have 300,000 hard drives. We have 5 exabytes of customer data, right? So I think some of the perception of like what's the value beyond the cost of the hard drives, right? And I look at that a little bit of it's kind of the same as saying, well, AWS is just a bunch of servers. Like sure, they provide infrastructure with a bunch of servers, but it's all the software and infrastructure experience and the technology stack on top of that, right? But I think that, that's often a misperception, right? And I think that the fact that we have been able to -- since we launched B2, it's been about a decade. Our price for B2 has gone up, not down. over the course of a decade. And I think that, that speaks to the fact that we have technology that we have built and customers value above and beyond the cost of the hard drives, which obviously have gone down in cost over the last decade. So that's one thing I think sometimes gets missed. I think another thing that we sometimes hear is, what if AWS just lowered their price, right? And what I would say is that if you look back, it was the same question that we got almost 20 years ago. At the time, we designed our own infrastructure because they were too expensive. We built all the technology and people said, well, but what if AWS lowers price. It has been 20 years. We are still about 1/5 of their price point, right? So I think that it still comes up as a thing, but I would say that, that's -- and I think sometimes it's just the I guess maybe another thing I would say is some of the people don't understand that there's flash and then there's this data lake layer. And there are at least half a dozen companies providing different types of flash storage. And flash storage is great. It's important. It's valuable for a number of use cases, but it doesn't solve all the use cases. And the use cases that it doesn't solve are very big, material and important. And there's a very small number of choices that customers have for that data lake layer that we, in some ways, I would say, got lucky to be in a place where it is incredibly valuable with AI. It's something we started building before AI was a focus, but the technology today that we've built over the last 20 years is just becoming increasingly important.

Okay. Okay. Yes. You can't come to a research conference without us talking numbers. So we saw that Google raised $80 billion to fund the AI infrastructure. So what are your views on the amount of capital that will be needed for you to fund that like the growth in AI?

Yes. I mean there's definitely -- the world is interesting right now with billions being thrown around here and there and everything, right? What I would say is Q4 of 2025, we had said about a year leading up to that, we had said Q4 2025 was going to be the quarter -- our first free cash flow, adjusted free cash flow positive quarter since being a public company. We hit that milestone. The next milestone we said for ourselves was that 2026 is going to be our first adjusted free cash flow positive year, right? And we expect to hit that milestone, right? So we don't intend to need to raise capital. Having said that, we signed -- as we leaned into offering the neocloud storage, we've signed multiple neoclouds. We signed a 6-figure deal, a 7-figure deal and most recently announced an 8-figure deal, right? That requires capital build-out to support those. Again, for all of those, we can do them under our own steam. But we are talking to a broad range of neoclouds. We are talking about large-scale opportunities around those. If some of those materialize at enough scale, it is possible we will want to support those. But we have about $100 million on equipment lease lineup that we have, and we generally fund equipment out of equipment lease lines that align with revenue as opposed to raising capital. So we don't need money to run the business. if the business materially accelerates, that's always a possibility.

Yes. And when you look at long term, next 3, 5, 10 years, given the change that Bay is going through, what would you define as success?

Well, I think that the industry is going through this replatforming. And for the first time in 2 decades, right, we can see that the hyperscalers are not the only game in town. And I think that our opportunity is aligned with that, right? Our opportunity is aligned with the fact that part of the replatforming that's happening is these neo clouds and the semi analysis talks about almost 200 neoclouds out there, right? The part of our opportunity is to be an essential infrastructure provider to a number of those neoclouds, while we, in parallel, directly support the thousands and thousands of AI builders out there with the essential infrastructure that allows them to use all of the providers that they want. So I mean, I think we have a very, very big opportunity here. We built this fairly unique storage platform and outside of the few hyperscalers who've also built impressive storage technology. But if you want a white label offering as a neocloud or you want a provider that provides you independent access to all the things you want to use as an innovative builder, the choices are very few. And so as we look at it, the just the Infrastructure as a Service storage market alone was forecast to be approaching $100 billion, right? That's just the Infrastructure as a Service storage market, and that was not really fully accounting for the AI impact of all of it into the future. So as I look at it, I think success is us being essential infrastructure for the neoclouds for storage, us being the preferred provider for the storage platform for AI builders who want to be the most innovative and use the different services out there and having that be reflected appropriately in the value that we're providing and the value we're receiving.

I think I'll open it to the room for questions. Anyone has a question? All right. So maybe what kind of like message would you like to leave to some of the investors that are here specifically about like that, please?

Yes. I mean I think that for many years, we were providing a service that was call it backup in nature, small business focused in nature. I mean, even when we went public in 2021, our average customer paid us about $500 a year. On our last earnings call, we talked about a customer that paid us -- that signed a contract for over $15 million, right? So as I think that the market perception in some ways, hasn't caught up with the reality and certainly not the opportunity, right? But thinking of the reality of it is, we went from servicing customers paying us $500 a year to ones that are signing $15 million contracts and where that can head from there because, again, that an initial contract. That's not a total opportunity capture. That's going to land before and expand, right? And so I think that the good news about having 0.5 million customers and being around for 20 years is there is a certain level of awareness for the company. The bad news is that, that awareness is -- the perception around that awareness is tied to the rearview mirror, not today and not the future. And I think that today, we already are providing a central infrastructure to a number of the old clouds. We already have 1 out of 3 new customer bookings coming from AI natives. That's today. And I think that, that only scratches the surface of where our opportunity is tomorrow.

And how do you think about managing basically 2 businesses, right, which is the incumbent portion of the business, computer backup and SMB, mid-market cloud storage. At the same time as you're also transitioning to that new cloud storage story, right? How do you manage the way you're positioning the way the Street is going to view the company? And what are your views whether or not you need to keep both?

Yes. So the computer backup business is still a great part of our business. It's a durable cash-generating great part of the business that also provides access for us to go to those people and sell our other services, right? So that's a good solid ongoing part of the business. B2 is the growth engine, right? And so the nice thing is we've got a good predictable business on that part. And frankly, we have a good predictable business on B2 in the use cases that we have served for a long time with ransomware protection, our cloud backup and the like. And then the AI opportunity with B2 is the inflection point and the inflection engine for us to drive business.

Question?

You touched earlier that your inventory that you have and the age of the infrastructure that you're dealing with. I think you recently announced that you extended the useful life of hard drive, I think, from 5 to 7 years. Just generally how you think about if there's a longer runway on this and the memory supply for you straight and all?

Yes. It's a good question. And certainly, the supply side of the business is interesting just globally for anybody in dealing with supply today. One thing that I would say is -- so your first question was just about the ages of the inventory. So we are regularly cycling inventory out, right? So obviously, hard drives that we bought 20 years ago are no longer in our system, right? And we migrate data on a somewhat continuous basis as the drives age out. We did that useful life study where we found that we were depreciating much faster than the actual lifespan of the drives. And in fact, we published these very popular hard drive reliability statistics where we show what the failure rates of drives are over time. So in general, the drives still tend to last longer than what we have as useful life for them. So I think we're being conservative on what the reality there is, but it's more reflective than where we were in the past. In terms of the memory side of things and the hard drive and just supply constraints, so the good news for us is that while supply is constrained across almost everything technology based today for infrastructure, hard drives are not as constrained or the prices are not as significantly skyrocketing as memory and some of the compute prices. And we do buy some of those other components also, but they don't make up the bulk of our CapEx. So in general, it's something we work very hard on to keep good relationships with multiple vendors and have longer purchases and have pre-commitments in the whole bit, but it's not as tight as if we were in some of the other spaces. It's actually been one of the benefits, frankly, for us. Some of our customers have said they were previously buying and intended to buy more flash-based systems as a way of storing data. And because those systems and the underlying components are becoming increasingly expensive and an increasingly short supply, they are looking for ways to offload those systems and only keep what is absolutely necessary to keep on flash, but get a data lake for a layer for what they can, and we're a great offload to that.

Okay. Thank you, Gleb.

Thank you, Frantz. Appreciate it.