Good morning, everyone. My name is Stefan Schwarz. I'm on Andy Nowinski's team here at Wells Fargo, and it's my pleasure to welcome Varonis today. We have Brian Vecci, Field CTO, and Tim Perz, Head of Investor Relations. Welcome.
Thank you.
Thank you for having us.
So, you know, why don't we start off, for those who might be unfamiliar with your story, what do you guys do, what problem are you solving, and where do you fit in the security stack?
So if you think about cybersecurity, you can think about it as layers of an onion. There's the outer layers, firewalls, then you get further in, endpoints and network. We're data security. We protect the data itself, and we do that by identifying what data is sensitive and most important. You can think about PII or PHI and other regulated data, so that's healthcare information. You can think about intellectual property, source code, employee information, things like that. Then we secure it by figuring out all of the ways that somebody could get access to it, which is incredibly complicated. We monitor it all, and then we have automation, robots that'll go through and lock everything down. And if something ever happens, you know about it, because we're monitoring it.
So we lower the time it takes to detect a threat and lower the time it takes to respond to it.
Got it. That's really interesting, and, you know, we've heard at this conference about generative AI and the potential for data loss because of companies adopting that. And Yaki made some comments during the third quarter earnings call about how, you know, AI could be a tailwind for your business because of the risks associated with it, and he talked about two types of risk, one of them being self-inflicted risk. What is that? Can you describe for us what that is?
I met a CISO a couple weeks ago who said what keeps her up at night is if she turns on Microsoft Copilot, which is, if you're not familiar with, is a generative AI-based product that Microsoft is releasing, that's basically ChatGPT for your data. And she said, what keeps her up at night is the idea that she turns this on, and suddenly her users on her trading floor can use Copilot to access employee data or the CEO's email. And we know that that's exactly what is gonna happen, because people have access to way too much data, and they don't know what they have and where it is, and every user has access to far too much. And unless you secure it, you start using generative AI-based tools, you're gonna expose yourself to an absolutely massive amount of risk.
It also makes it very easy for people to create new sensitive data. Summarize all of the information related to this company that I'm doing research on, and it creates a new document that's highly sensitive that didn't exist before. So there's a lot of risk associated with these tools. There's also the risk of building internal training internal LLMs on data sets that include things like employee information. Like, do you want your product that uses ChatGPT to surface information about your employees' 401(k)s? Which is exactly what's gonna happen if you're not careful. So what generative AI does is it creates. It increases the risk of inappropriate or malicious access to data, it increases the risk of exposure, and that's exactly the problem that we solve. And that's what Yaki means by it can be a tailwind for us.
Got it. And so, you know, how does Varonis specifically help enterprises mitigate that risk?
It's the biggest problem you face when it comes to third-party AI risk, like using Copilot, is that all of your users have access to way too much data, and a lot of it is highly sensitive and exposed to people who don't need it. We solve that problem. We find it, we lock it down, we monitor it. If somebody starts accessing a lot of data that they've never accessed before, we alert you, we'll help you investigate, and we'll make sure that what we call the preventive controls, basically the locks on the doors. And these days, with data, every single file needs its own separate lock, every folder, every SharePoint site, every email, every mailbox, every S3 bucket, and Salesforce record. That's exactly the problem that we solve.
We find it, we lock it down, we monitor it, and we make sure it stays locked down.
Got it. And, you know, I wanna ask you about Microsoft Copilot specifically. You know, that takes in a lot of enterprise data-
Yeah
... obviously creates risk. How much more exposure to risk does adoption of Copilot present to enterprises?
Copilot is the, maybe the single most, and this isn't... I'm quoting somebody else, "but the single most powerful productivity tool ever released." It's ChatGPT for your enterprise data. It creates a massive amount of risk, though, because, you know, Microsoft says in the you can, you can all Google the preparing for Copilot page, that oversharing and data governance is a challenge for most enterprises. That's the understatement of the century. They have no way to solve it. So they say if you're going to deploy Copilot, you better make sure that what are called access controls, the permissions, the access to the data itself, is that the data is locked down, because you don't want to expose important, sensitive, valuable information to people who don't need it, right?
I shouldn't be able to Google or basically use Copilot to go find information about, HR data. I shouldn't be able to find, proprietary financial information. I should have no reason to have access to that. But if I do, and we know that I probably do, if we do a risk assessment, because everybody has access to way too much, this is what happens when we do a risk assessment. This is what we see. If you turn on Copilot, you're gonna expose yourself to that kind of risk. It's also a hacker's best friend. If I phish a user, get access to their account, I don't need to be an expert in their, you know, network anymore. I don't need to start moving laterally or finding other data or servers or devices. I can just ask Copilot, "Show me all the customer information.
Give me all the PII." Done.
So Microsoft is warning customers about this, the risks of oversharing data. Surely they have some kind of solution in place, you know, if a customer doesn't use Varonis, what are their options?
You would think so, but they actually don't. So they have a warning against over-sharing. Their solution or the way they address this is really through a perimeter control, what we call data loss prevention. They have technology that's now under the umbrella of Purview. It's incredibly useful. It does things like make sure that when a file has a label on it, basically it's been marked as sensitive, or this is confidential, or this is internal only. When it's got that label on it, then Microsoft Purview will make sure that that data can't be emailed, or it's always encrypted. It doesn't solve the problem of over-sharing, and it requires that the file have a label on it.
This is one of the reasons that we're in the Azure Marketplace and have such a tight partnership with Microsoft, is that you use Varonis to automatically apply those labels, because Microsoft doesn't have a way to do that. So they have technology that requires a massive investment in operations that usually fails unless you use automation, which is exactly what our customers do. So Microsoft themselves will say, "If you want to get the most out of Purview, you should use Varonis.
Got it. So, you're effectively, I guess, using AI to improve the classification of sensitive data? Is that fair?
We classify data. We're not using AI necessarily to do that. We make sure that the data that AI will get your users access to is properly secured. We will make sure that the data that the large language models are learning from is properly secured, and that you don't have anything that shouldn't be in those, what are called corpuses of data. We also have AI built into our product to make the platform easier to use. You can ask... It's called Athena AI. You can ask Varonis, "Show me all of my HR data that's open to every employee." Seconds later, you've got it, and then you can turn on a robot to lock it down. So we built technology to solve the access and the security problems that present so much risk when you start using AI.
Okay. And that's something that just a simple Data Loss Prevention tool couldn't do?
That's exactly right.
Got it. The other risk that Yaki mentioned, in addition to self-inflicted risk, was the risk from external parties. Could you go into that in a little more detail?
Yeah, I touched on it when I mentioned that Copilot is probably a hacker's best friend.
Yeah.
But generative AI, large language models are very good at predictive text. They're also very good at writing code. I have a lot of friends, developers, that don't wanna go back to a world where they didn't have ChatGPT reviewing their code and even writing code snippets for them. That's an incredibly useful tool for productivity for developers, including the developers of malware and ransomware. Also, third-party tools like Copilot are incredibly useful for insider threats and external attackers. So, that's what Yaki means by, you know, externally inflicted risk. Generative AI, large language models make everybody more productive, including the bad guys.
Makes sense. You know, I would think that these extra risks caused by AI would provide you guys an opportunity to monetize this. You know, is that something that you've created a SKU for directly, or, you know, does it just kind of play into tailwinds of the business overall?
It's the latter. What it does is, if it increases the risk to your data, it increases the value of Varonis. So if you want to use Copilot, you need Varonis for Microsoft 365 or GitHub. If you wanna use Salesforce's AI, you need Varonis for Salesforce to make sure that your data is secure. So it's really a tailwind to us. It makes Varonis more valuable. We also. I mentioned Athena AI, which is AI built into our product platform. We do not have a SKU for that. What it does is it makes the platform more useful. It makes it more valuable. It increases customer satisfaction and increases retention rates. It's also brand new, so, you know, we can't measure the impact yet. Signs are customers love it, though, and we're all about our customers.
When our customers love our product, everybody wins.
Got it. And understanding that it's still early for Athena AI and, you know, the work that you're doing protecting customers from-
Mm-hmm.
The risks around generative AI, do you have any thoughts as to when you might expect to see a tailwind from AI? Or I guess from an investor's perspective, when might this show up in quarterly earnings results?
Yeah.
Go ahead.
I think I can take this one. So the right way to think about it is, companies know a problem exists, but they don't know how to solve it necessarily. So we still need to go in, do the risk assessments. What generative AI does is it gives us another reason to get in front of customers and do those risk assessments, to help us kind of explain how we, we fix that problem. So the right way to think about it is, we still have to do the risk assessment. Sales execution is important. Our sales cycles are three-nine months, upwards of 12 months. So I don't want you to plug this in your model for 2024 just yet, but it should serve as a nice tailwind to the business over the next couple years as we execute on this opportunity.
Got it. You know, I'll just take a moment to let the audience know here, if you have any questions, feel free to raise your hands, and I'll, I'll work those questions in. Why don't we switch gears to, you know, your SaaS transition? You know, maybe we can start off just by, you know, reminding everyone of the benefits of the SaaS transition.
Benefits are numerous and of very high value. So SaaS is a much better way to both develop and deploy enterprise software. In the past, in a self-hosted model, just to do a risk assessment, our customers would have to provision hardware. They'd have to go buy you know, hardware to run Varonis. They'd have to go to their database team and license databases to run Varonis. And then, when we're in production, they've got to manage this infrastructure and this environment. We got very, very good at it, and we built a really strong business on it. But transitioning to SaaS has a huge benefit. All of that goes away. We can manage all of the infrastructure on the back end. We see issues in a customer environment before they happen. Everything is fully elastic. One way to think about this is,
We built Varonis as a cloud company before anybody else came along and tried to build Varonis as a cloud company. We took 15 years of all of the technical lessons learned about how hard it is to collect all the information that we collect and do the analysis, rebuilt it as a SaaS platform. And now our customers, it's easier to deploy, it's easier to manage. We've seen an 85% reduction in support tickets. It's more functional. There's more automation built in. It's faster because it scales automatically. We have AI built into it now. Because we don't need to wait for a customer to call us if there's an issue, we offer proactive incident response at no additional cost.
Part of being a Varonis customer is we have a global team of experts that's looking at your environment every day, and when we see somebody, "You know what? It looks like somebody's accessing HR data on your IT team. Is that okay?" Or, "It looks like you have ransomware on this server. Did you know about that? Like, we can help you take care of this right now." Or, "It looks like we see the indications of a nation state actor that are in your systems because we've seen that exact same indication of compromise at three or four other customers. Can we get in and do this investigation right now?" All of those are actual examples that have happened over the last nine months. It is a massive value add.
Turning Varonis on, or just using our SaaS platform, means that you spend less time and energy running Varonis, you get more value more quickly because of the automation and AI, and you get proactive incident response. There's no customer that, given the choice starting from scratch, wouldn't take the SaaS offering.
Got it. And you mentioned that you've built a cloud version of Varonis before anyone else could do so.
Mm-hmm.
Would that imply that your competitive dynamics have necessarily changed with the introduction of SaaS? Or, you know, are there any benefits to Varonis internally from that transition?
You can think about it this way: We had a massive technical moat before.
Mm.
There is a reason that in every one of these conferences and every question that we get from investors is: "Who is your competition, and why didn't you have any competition?" And the answer is, there are multiple ways to answer that question. There are multiple pieces to it. There is no single silver bullet, but the fact is, we solved these problems that you need to solve to secure data before anybody else did. We had a massive technical moat in front of us. With SaaS, that moat is now bigger, and it's getting bigger faster. We've had more press releases for new features and functionality in the last six months than in the last six years, because we can innovate so much more quickly now.
It's a better product than it's ever been, and it's getting better faster, and we're so far ahead of anybody else that wants to try this that, you know, good luck.
What are you hearing from customers? What, what's adoption of SaaS been like?
Absolutely love it. It's, it's night and day, and that's why, and Tim can talk about, you know, the phases of this transition.
Mm-hmm.
We are not actively going to customers and trying to convert them to SaaS yet. But we have customers... We're also not shy about it. We're not, you know, keeping it a secret. And we have customers that are coming to us and saying, "I want the SaaS version of this platform right now.
Yeah, and to put some metrics around that, in the third quarter, we had a 59% SaaS mix, which is selling SaaS to new customers and upsells to existing customers. That compared to our guidance for 45%, so pretty nicely ahead. And then, existing customer conversions came in at $10 million, ahead of our guidance for $8 million, and that's really, self-hosted customers converting over to our SaaS platform. And when you put those two pieces together, we now have approximately 15% of our total company ARR coming from SaaS, and that's just after three quarters of the transition so far. So it's moving ahead pretty nicely, and we're really happy with the progress so far.
Got it. Expanding on that, Tim, you guys have talked about different phases for this transition. Now, what's happening in phase I and phase II, and what's the timing of that?
Yeah. So at our Investor Day back in March, we outlined a five-year transition period, where at the end of that transition, we'd have 70%-90% of total company ARR coming from SaaS, meaning that we're a SaaS company. So that transition is split into two phases. Phase I is focused on selling SaaS to new customers. That'll last one-two years. That's what we're doing right now. Phase II starts after that. That's converting our base of existing customers over to SaaS. So while we haven't started targeting those customers just yet, we've actually guided to approximately $30 million of those conversions this year. And the reason why that's happening ahead of schedule is because of all the benefits that Brian's talked about. Customers want better protection at less effort.
Salespeople want to earn more money on the larger deal sizes of SaaS, and that's really what gives us confidence kind of going into next year as we start to plan for phase II.
Got it. And I think overall, this transition's expected to take about five years, and it seems like a long time, especially given the benefits of SaaS that you've outlined. Why does it take so long?
Yeah. So our previous transition, we went from perpetual licenses to subscription licenses. That took about a year, which is pretty quick. That one was really a financial exercise. This one has a lot more operational components. So we wanna do the transition as quickly as possible, but also in a way that doesn't add any unnecessary risk to the business. So that's really why we're taking our time. As it relates to phase II specifically, there's two things to keep in mind. So one, our average contract length is three years. So a customer might wait until their contract comes up for renewal before moving over to the SaaS platform. The other thing to keep in mind, customers purchase servers, so they might wait to fully depreciate those servers before they switch over to the SaaS platform.
Obviously, we're seeing customers come in kind of ahead of contract renewal or before server depreciation, where they just kind of reprovision those for an alternative use case. There are ways around that, but that might be why a customer would wait three-four years before converting over to our SaaS platform. I also wanted to flag one comment that we've made on the previous two earnings calls. We kinda see that this transition's moving faster than what we outlined back in March. We do plan to address the timeline on our fourth quarter earnings call.
... Thank you. And I guess, have you given any thought, have there been any commentary about the impact of the macro environment on a customer's willingness to move ahead to SaaS or maybe further depreciate the hardware that they have?
Yeah. So the way we've seen the macro environment this year is pretty similar to most other software companies, where we've seen additional deal scrutiny and longer sales cycles as a result of that scrutiny. But if you think about how we've kind of built our guidance this year, it's, it's really been in a way that factored in many things that could go wrong, hoping that they didn't all potentially go wrong. That's what's kind of allowed us to kind of beat and raise our guidance throughout the year. And as it relates to our 4Q, our 4Q guidance, we kind of built that in the same way, where we factored in additional deal scrutiny on top of what we were seeing in the third quarter, which was really stabilization.
I think all of that doesn't necessarily impact the speed of the SaaS transition. If you think about the SaaS transition itself, it actually helps lower the cost of ownership for customers. As a result of that, they're actually more willing to move to SaaS in an environment like this, where if they needed to purchase additional hardware to expand their footprint, that would be pretty expensive. We can save them money on that, so that doesn't impact the speed of the transition.
That makes sense. I think you've mentioned that there's an uplift when customers convert to SaaS. Can you talk about that?
Yeah. So on an apples-to-apples basis, so assuming the same number of users, same features and functionality as our self-hosted platform, there's a 25%-30% pricing uplift for that. But customers are actually saving money on the TCO, because they don't need to purchase hardware, they don't need headcount to manage the product, so they have savings there. And you should think about it as us capturing a bigger piece of the economic pie. And most importantly, customers are getting a product that protects them better. That's what they care about at the end of the day when they're buying a security product.
What are your thoughts on the sustainability of that uplift? Is that what you would expect going forward? Is it possible it could accelerate?
So it's still early, but so far, what we have seen from deals is the price list is holding firm, discount levels are holding firm, so we are recognizing a 25%-30% pricing uplift. And in some cases, the deal sizes are actually getting larger than that because we changed our packaging when we moved to SaaS. Under self-hosted, you used to be able to buy 40 different licenses. You could pick and choose what you wanted. With SaaS, you can only buy platform packages, so basically, the minimum number of licenses that a company would take is approximately six. So that's helping contribute to larger deal sizes. We're also seeing more accurate user counts because we can measure how much data that companies are using, so that's helping us make sure that we're helping customers scale properly as well.
Got it. And, you know, obviously, as a result of your transition, it's created maybe some noise in the financial model, particularly with respect to revenue headwinds. Maybe can you kind of go into what the impact has been specifically and, you know, how you normalize for that?
Yeah. So let's take a simple example to kind of illustrate this.
Mm-hmm.
So if you have a $100,000 deal delivered on the last day of the quarter, under on-prem subscription, we'd recognize approximately $80,000 as revenue in that quarter. With SaaS, it would be less than $1,000. So a big difference there. With ARR, though, both deals would be recognized $100,000. No differences there. From a free cash flow perspective, we're billing and collecting annually in advance for both deals, so there's no free cash flow headwinds. And then the other leading indicator that we talk about is also ARR contribution margin. So what that is, is taking the ARR minus our trailing four quarters, non-GAAP operating expenses. So think cost of goods sold, R&D, sales and marketing, G&A.
What that does, it basically allows us to normalize for the revenue headwinds that you discussed and show our cost structures staying intact, and that we're actually driving operating leverage, even in the early stages of this transition. That's why ARR free cash flow, ARR contribution margin are the three leading indicators for this transition.
Got it. And you've had strong gross margins recently. What's kind of... I would think that the SaaS transition would have a negative impact on the margins. How have you been able to maintain that?
Yeah. So we're very happy with what we're seeing from the SaaS gross margin so far. We still expect those to come down into kind of the high 70s-low 80s% range that we outlined at the Investor Day, but they are tracking ahead of where we thought. And I think part of that is the fact that we invested over $100 million and a couple of years into the SaaS platform. I think a lot of investors were surprised by the magnitude of that investment, and I think you're starting to see the early benefits of those investments. The code is built in a very compute efficient way. It's also resulting in a meaningful reduction in support tickets. And overall, we're really happy with what we're seeing from gross margin so far, but it's still early.
Okay. I wanna go back to some recent announcements you made on the last earnings call. I think there were two new innovations you cited, one of them being natural language search.
Yeah, that's the Athena AI that we were talking about.
Okay.
So that's natural language search. There's two pieces to this. One is basically ask Varonis, and I use the example, "Show me all the HR data that's open to everybody," or, "Show me anybody that's touched any source code in the last seven days that's outside of IT or outside of our development." You basically, you can ask Varonis to show you the things, that you might, be interested in from a security standpoint. Makes the product easier to use. There's also an AI-based assistant. So you get an alert, this person is behaving like ransomware, which is a very common one from us. If somebody gets phished or their, device gets-
... overtaken by an attacker. Suddenly, that device or that user is behaving in a way they've never behaved before. It's a very common alert for us to trigger. We have an incident response team that knows exactly what you should do, and we built a lot of that knowledge into the AI. So now it will walk you through, even if you're not a security expert, here is specifically what you should do: go disable this account here, go check this configuration, go look at this data, go run this report. It basically walks you through the steps that you should take. This is nothing that you couldn't have done with Varonis before. It just makes it easier.
And so I would imagine that has benefits to customers in saving on costs.
It increases customer satisfaction. We believe it'll increase customer retention rates. You know, we know that customers that use the platform more, that do more with Varonis, will buy more. We just know that. We've known that for more than a decade now. That's the whole philosophy of our R&D, is make it so that they can do more and make it easier to do more with Varonis, and that's exactly what Athena AI will do.
Got it. We had a speaker yesterday who was talking about defensive versus the hackers' use of AI, and how that may evolve in the coming months and years. What are your thoughts on how AI can kind of be used to a greater extent on the defensive side, you know, particularly with protecting data?
There's certainly opportunity for AI to make everybody more productive. That's a big reason that we're building it into our product. We do think that there's also risks of, obviously, adversaries leveraging AI. We're looking at from a technology perspective, both angles as much as possible to make sure that Varonis protects as much data as possible, as automatically as possible. A big part of generative AI and large language models is automating things that can take a long time to do, and we're building that into our product because automation is critical. Finding fatigue is a real thing. I can go show a CISO a report of all of their exposed data, but unless I have the answer to what to do next, and it's automatic, they're probably not gonna do it. They're probably not gonna care.
We make sure that not only can we identify risks, but we can fix them automatically, and AI is a big part of that.
Got it. You know, any closing thoughts that, you know, you guys wanna communicate?
I've been talking for 20 minutes.
Tim?
No, I mean, I think one thing that's underappreciated from investors is the fact that we don't have competition, so why you're not growing faster? And I think it comes back to the fact that we're building our market. We have to bring in salespeople. We have to fully train them, enable them to kinda talk about Varonis as well as Brian does. We need to do these risk assessments to educate customers on, on how we help them solve these problems that they previously thought were unsolvable. And I think the fact that we have to make sure our sales execution is so strong in doing all that is really what gets us to a faster growth rate. I think SaaS helps us kind of unlock that a bit more, too, right?
Because it lets us do these risk assessments with less friction, so theoretically, we should be able to do more of these risk assessments with our better sales people, and we hope that helps kind of unlock better growth in the years ahead. I think that's something we're excited about.
I'd put it this way: There's nothing that secures data in the way that Varonis secures it, and it's becoming increasingly important to secure data the way that Varonis secures it. If you're not using Varonis, you absolutely will be exposed, and generative AI, large language models, tools like Copilot, are gonna make that, even more apparent very, very quickly.
Where would you say we are in terms of customer awareness of the importance of protecting data, and specifically with the use of generative AI?
It's really interesting. We used to have to evangelize the problem and evangelize the solution. You know, back to... I joined Varonis in 2010. We would have to just literally walk people through what the heck it was we were talking about and why it's a problem, and they wouldn't even realize they had a problem. That's not true anymore. Everybody knows that they have a data security problem. That is, I mean, everybody knows that they have more data than they can possibly manage, and people have access to way too much. People know this. What they don't know is that necessarily there is a better way, that you don't have to rely on DLP, and endpoint, and perimeter controls that do not solve these problems. So we still have to-- This is why we do the risk assessments.
This is why sales execution is so important. We still have to evangelize what exactly it is Varonis does, why we are not in a Magic Quadrant, why we don't have any competition, that there is a better way. That is absolutely critical for us, but it's becoming more and more important for everybody. To answer your question, everybody knows they have a problem. They don't necessarily know that they have a way to solve it.
So it sounds like, you know, you're fairly under-penetrated in this market. How do you think about how big it is and what the opportunity's like?
Yeah. So the right way that I think about it is we had about 4,400 subscription customers as of the end of last year. If you think about the companies that we're going after, it's typically companies with at least 1,000 employees, because that's typically when they bring in a CISO, and that's who we target in our selling motion. There's about 55,000 of those companies in North America and Europe alone. So if you think about it from a new logo perspective, we're less than 10% penetrated. And then within our existing customer base, we also know that we're under-penetrated there as well. Under self-hosted, our average customer had about five licenses, and we were seeing that our more mature customers had between 10 and 15 licenses on average.
So we know there's an opportunity to basically double the amount of volume that we get from our customers from a license perspective. And on top of that, you kinda have the SaaS uplift of 25%-30%. So really, there's an opportunity to more than double the amount of ARR that we have from existing customers, and that's the right way to think about our TAM.
In terms of sales execution, what kind of investments have you guys made into sales and marketing and, you know, plans for going forward to be able to execute on the opportunity?
Yeah. So we've been investing more heavily in the Varonis Academy over the past few years, which is our in-house sales rep training development. So basically, we'll bring in a territory development rep out of college. They'll work on that for 12-18 months. Best ones from there are promoted out into inside sales roles, so think selling to smaller customers over Zoom. They'll kinda do that for another 12-18 months, and then they'll go out into the field. We've seen reps who go through that training program tend to be more productive than ones that we hire from the outside. That's why we've doubled down on those efforts over the past few years. We hope that'll help our growth in the years ahead.
We've also been hiring from the outside as well, more seasoned reps, so they can kinda get fully productive quicker. It's typically 12 months for a new rep to be fully productive for us. And we've also been expanding internationally. Recently, we've made pretty big investments in Asia specifically. We brought in a new head in Australia a couple years ago, a new head in Singapore, India. So there's plenty of areas that we're kind of investing in sales and marketing, and sales enablement, in general, is always something that's very important to us.
Got it. I guess just following up on that point about international, you know, data sovereignty has become increasingly important. Does Varonis have a role to play in that aspect?
Data sovereignty is about making sure that the different kinds of data are only where they're supposed to be. That's absolutely a great use case for Varonis, and many of our customers are using us for that.
Got it. All right, well, if there's no audience questions, we'll call it there. Thank you, Brian and Tim, for joining us today.
Thank you very much.