SentinelOne, Inc. (S) Earnings Call Transcript & Summary

If I just go down this tried for a second. If we solve the alignment problem the way that you're suggesting, then you get the trust and then you get the unlock from a productivity and adoption.

I believe so. But I also think that it's -- that's a deeply rooted architectural problem because to do that in a way that is known circumventable by the model or the software itself. You can't have security running at the same level or the same layer, the same ring that the model is running -- and just in terms of compute, even today, if you take normal cybersecurity. If you're running a user space, I don't care what you do. Your toast. Your toast. -- everything can bias -- so the story is about like user space becoming the thing and in the wake of the CrowdStrike outage and blue screening, 8 million devices across the world. People are like, "Hey, get out the kernel, you have to get out, everybody is going to get out Nobody is out, what are we like 2 years, 3 years from that event. Nobody is getting out. And the reason you're not getting out is because the moment you're out, you're a host, like you are in the same level the attackers are when you got no shot, no shot to prevent any type of an attack. So the need to be as low as it can be in the operating system is a dire need in the question of rare alignment. And I would say that it's even more acute, you likely need at this point to even have either a new chip design where you can separate compute for whatever security you put inside versus whatever is running the actual software in the model or you need some form of a better security on clay. -- even the security on claves we've seen today, Apple as an example, I think they got really great security unclaimed capabilities. They offer your protection, you can load your software and then they protect it via hardware. That got compromised also. So it seems like we would at some point need to really think about how we separate hardware in a manner that allows for security that cannot be bypassed by what it's supposed to be securing with sounds pretty obvious, but it's really not the case today.

Yes, super interesting. Let me ask you about this concept of taking the proprietary data set that's in Sentinel-1 and applying it to some sort of LM technology, such that you're able to get maybe it's purple or maybe it's a continuous penetration testing loop where you can run offense and defense with agents to level up the scalability of the existing architecture. What are your thoughts on how that makes sense to SentinelOne?

Yes. I don't know. I mean, it's going to be a jagged answer. I think that there is a lot of focus on vulnerabilities, maybe too much focus on vulnerabilities right now. This entire notion that you're going to have the red agent and the blue agent, and they're going to hand shake each other and 1 is going to find 1 is going to fix and everything is going to be miraculously pristine after that. I haven't seen it. I haven't seen it. And we've been retaining our environments in an automated manner for years. And obviously, once we got access to more and more frontier models over time, we've used frontier models to do that as well. You find a lot of stuff still need humans in the loop. You need to prioritize stuff. You still need to understand what's real and what's not real. And the fixing element, I mean, it's not just finding in fix. It's finding it's fixing, it's putting temporary controls, it's rolling deployment for production systems. Who is going to let AI roll out a production system completely automatically. Nobody is doing that today. That's the 1 place I would not exercise AI. So to solve cybersecurity in this miraculous one's going to see them, 1 is going to find them, and we're good. Haven't seen that happen. And look, again, we're a glass wing program participants. We're part of Daybreak we got access to every model that you can dream of, like everything that's previewed. We already have it. We've had it for a while. Obviously, all the open source out there. I think the other realization is that -- there is no like supreme intelligence out there. These are largely in terms of the level of reasoning and intelligence -- these motors are not very different from 1 another. Some are better at keeping course. Some are better at scale. Some have better speed, better cost perspectives, better specialties -- but in general, the reason in quality is dramatically different. But even when you take 1 of these models and you say, "Okay, I'm going to pick a model and I'm going to start fine-tuning it. or doing some stuff post training. And just to ground everybody, like doing stuff post training is very, very limited. Like you're not changing the true innate behavior of the model. You're trying to kind of keep it in track. It's all done post training. To think that you have done something post training that is so dramatically better that is going to win against adversarial AI. Again, I haven't seen that in our research. And especially, I mean, at some point, it also becomes like a very like linear and binary question. Like let's say you're taking what's it called Nvidia and Numoto, that thing -- that stuff is not like even top 10 in reasoning performance by any benchmark, honestly. And then you're saying, okay, I'm going to use that as my basis. Just an example, I'm going to use that as my basis. And I'm going to sprinkle some fine-tuning in my data from years of doing cybersecurity and the Chinese open-source models are probably like by a factor of 5 better than these models today. I haven't seen them lag. Moreover, I've seen them add incredibly, incredibly sophisticated ways to scale their models. That I think a lot of the frontier companies are hoping today. That's the -- I think the benefit they have when they're seeing something open source. But all in all, to just kind of pick 1 model and say, "I'm going to train this to be the best thing of all models, I think that's like total wishful thinking. No matter if you're -- America, Jensen or not, I don't think that, that changes stuff, right? I mean, at the end of the day, you have to be agnostic. You have to understand where the limits are -- and I think in many ways, I think what we're trying to do more than anything, this has nothing to do with technology to stop confusing customers to stop making Pompes claims to stop thinking that you can develop something that is completely unprecedented is going to win. That's the solution. Here you go. It's right here. Let me open my jacket and give you the solution. None of that exists today, and that's part of the issue. -- and we're all trying to think around corners and understand, okay, where this is going? I think it's proven very elusive. -- not because we don't know exactly what the potential of damage here is, but more because these motors are unpredicted unpredictable. They kind of not only improve in an unpredictable manner. -- but they also lack precision in an unpredictable manner. So it's very interesting to obviously kind of go about and try and solve it. But then I always go back in cybersecurity, it has to be fundamentals. -- people have not gotten their fundamentals together yet. So don't rush to deploy the AI security, a genetic space ship, red, whatever, on or whatever, that's all going to help you. Spoiler alert, not going to get more secure. You really have to start the fundamentals. And I think that's why also we're seeing this amazing traction around runtime protection and around endpoint protection because it's very -- it's very obvious, right? You're running AI workloads in some place. You need to monitor that workload. That's it. We don't need to talk too much about AI at that point. I mean you need the visibility, seen the visibility seeing immediate alert. You're seeing amazing signal coming from all these new found workloads. To me, that has to remain the focus for at least the next year or so, the speed in which people are doing it, that has to change. So if anything, this day and needs to give us this wake-up call, which I think it's I don't know how many more wake-up calls this world needs to have about cybersecurity for things to move faster. But right now, we also have to recognize the limits of what the infrastructure can absorb. You can't just deploy overnight across the world. You can't fix this globally in 2 days. It's going to take time naturally. I think it is moving faster, but it's moving faster incrementally. And I think just the level of confusion right now is also somewhat, I think, throwing customers into kind of a loop of what do they need to do? Who do you need to talk to? Who's going to solve it? There's almost like they're sitting there and they're waiting for their vendor that already kind of is preexisting to come and descend from the top and say, okay, now the problem is sold. Now to be honest, we're all trying to do it. We're absolutely trying to do it. I mean we're also getting to the point that we understand that the fastest way to deploy is actually not by talking to us, just by clicking a button on your console and starting to do things in a much more automated way. So a lot of what we're investing in today is this ability for our customers to just click a button and get it on with and not go to those protracted sales cycles that we're seeing in cybersecurity and deployment. We want to automate everything for you. We believe that's the real power in AI right now they can really automate stuff. It's a great search engine. It's a great automation tool. Everything else will be really careful with.

Sonalee, this is a perfect to have you opine on the feature of the transformer architecture. Temis just talking about, look, it doesn't happen otenight. And you had this language in your scripts that I thought was actually very CFO ask, which is appropriate.

Yes, you are separate. Yes, architectural changes are multi-quarter and multi-year in nature. Now you have a really clean July quarter. So I think 2 things might be happening once 1 determines point, things are happening a little bit faster. And two, you have a little bit more of a handle on 701 forecasting and having been in the seat for a couple more quarters.

So talk to us about both of those things. What are you seeing in terms of pattern recognition or rather what's changing on the pattern recognition for deals in the pipeline conversion rate, salespeople productivity, all that good stuff.

So you're right, it was my second quarter. as fast we don't just think it was a clean quarter. We think it was a great quarter. We're really proud of what we achieved. And for those of you who didn't go through our earnings, we actually beat on the quarter and raised our full year revenue guidance. And I think it was the magnitude is important because I actually was 1 of the larger SP-14 In a number of quarters. So thank you for noticing that. It was, and we actually raised by significantly more than the beat just showing our confidence in the outlook in the business. So you asked a couple of questions there. So in terms of how customer conversations are going and this -- I think you're alluding to the Metis moment, how is that impacting our pipeline and our deal cycles and conversion rates. So we see a really strong demand environment and that is very, very clear in our pipeline. But my comment around this being a multi-quarter, multiyear tailwind for us and the industry still holds true because boring from what Tomer just said, we need to focus on the fundamentals. We need to focus on how quickly customers can actually absorb all this new technology. And I think from our perspective, 1 of the areas where we're seeing a lot of strength and traction is in our AI security products. And that was 1 of the things that really drove the strength in our net new ARR, and we'll continue to drive that. And those are great conversation openers with our customers. But just to give you an example, I was on a customer call this week. It was a very, very large infrastructure provider, a global infrastructure provider. And the CIO was saying, look, we need to clean sheet our stack and specifically our security stack because we don't want security to just be something that we do to protect ourselves and protect our customers. We want it to become strategic for us and for our business. but that is a multi-quarter conversation. And that is something that I want to bring all of the team across this company into. And yes, we want SentinelOne to be part of that journey and please tell us what products you think we need. And again, this is where the power of the platform comes in. The reason they want us to speak to us is because we bring a true platform approach, but it's something that is going to take place over many quarters. And whilst we're definitely seeing it in the pipeline, like when you actually see that hit the revenue numbers, that's going to be over time. And I think that's great actually because it's a cumulative impact. The other question you asked was around kind of sales productivity and efficiency. And Tomer talked about like where we are seeing the benefits of AI and One thing that's very dear to my heart and a metric that my team focuses on all the time is net retention because we all know that it is way better business to keep and expand the customer and SaaS to go out and acquire a new one. And you've seen really strong net retention metrics from us in the last 2 quarters, particularly in that cohort of $100,000 customers and above which tend to be our stickier customers. And again, I think that's validation of the platform strategy. They are buying more and more products from us. And guess what, when you buy several products from us and you're adopting our platform, you're much less likely to churn. And I think that is 1 of the things that's driving that productivity and retention. And then the other thing is just amongst our sellers, we are seeing improved productivity, and we are seeing lower and faster deal cycles. So again, these conversations that do take 6 to 9 months or sometimes 9 to 12 months in the case of enterprises, large enterprises, we are seeing a slight contraction in that sales cycle, which is starting to come through in the numbers. And then finally, on the renewals process, we started automating our renewal process, particularly for that really long tail. And we can touch way more customers, and we can actually reach out to them earlier in the cycle, and that's giving us a lot better predictability -- and 1 of the things that I'm really going to be focused on as we go into fiscal '20, Tomer and I are planning for the first time together is how do we bring that number that as we think about net retention, how do we improve that number and really work on that churn and downgrade, particularly with all these new products to like just drive it higher and better.

One of the debates in cybersecurity for some time now and especially over the last couple of years has been the importance of scale. And in some ways, you have well scaled relative to some of the new entrants in the space. On the other hand, you've got 2 or 3 really large competitors that sometimes have a larger microphone and throw more dollars at the problem. So from a CFO perspective, if you're trying to reduce churn and grow NRR, how do you do that in a way in which you can use your sort of middle-of-the-road size as an advantage and maybe there's a better expression for that relative to the companies that just have much bigger R&D in and budget.

Yes. So I'll answer that, and then I'll let Tomer comment on R&D as well. So look, I think a couple of points I would make there. We feel like we are able to make the investments we want to make and look, you can see for yourself how well some of those emerging products are doing, like we've seen record growth and in some cases, like in the case of AI security, so prompt and purple AI, like meteoric growth. We tripled our ARR year-over-year in that product. So we feel like we are able to make those investments that we need to make in the products where we see real outsized opportunity to grow. And that's notwithstanding the competitors. And yes, they are formidable competitors. We feel like we're formidable. And our win rates continue to improve year-over-year. we're seeing those competitors and our win rates are like we're getting better over time. The second thing I would say is we also invest in our go-to-market and 1 of the things that I just touched on earlier, automating renewals, that's something where actually we're seeing better productivity from our sellers, and we're able to take some of those savings and reinvest in areas again where we see the ability to deliver outsized growth. So I feel like from where I'm sitting right now, we really have the potential to take advantage of the time in this opportunity in this space to make the kind of investments we need to make to continue growing and hopefully accelerate our growth.

Yes. I would say R&D and our technology, I mean, versus the competition, that is not my #1 concern. It's far from being my #1 concern. Honestly, I mean we -- you would say, with our size, with our position, we like all the stuff we still have the best technology in the market. Like we will show up every day to POCs with the world's leading companies and we win time and time again, regardless of the size of Microsoft or Palo Alto Networks or CrowdStrike. So I would say size is just not a good reflection of the quality of technology. bigger microphones, for sure, more confusion for sure, controlling a narrative or weaving a narrative for sure. I think that's our challenges as a company at that size, which, to me, by the way, is quite for, and I'm a technologist because like I just want to build the best stuff ever and make sure the customers are protected. Instead, we need to kind of come up with all kinds of counterfeiters for what these other people are telling in saying and trying to promote. It's part of the game. We all get it. I wish that in this day and age, people would actually focus on what's important and what matters and not the ferrite stories about how identity is going to solve regenetic protection today because I just bought a company. But 3 months later, identity is just going to be 1 sliver and just bought another company that's going to solve it for you. And we all need it. Like customers eat it, analysts eat it, everybody is eating it. And I kind of look at it kind of sometimes with like deep, deep frustration on like why do people continue believing in those stores. I mean these stores change, if you just go back 3 months, 4 months, 6 months, it no longer holds what they've said, what this market has been saying Six months ago doesn't hold today anymore. The brilliant acquisition that you've done 9 months ago, nobody cares about it today. But we all have like very like distinct short-term memory, I would say, and we kind of move and move and the human brain works in a very susceptible way sadly. And I think that a lot of folks have learned how to manipulate that, to be honest. And I think that's the main thing we're dealing with, right? It's dealing with confusion. It's dealing with the kind of fear, uncertainty and doubt that people are fueling into the space is sort of really being like almost like in a very dry way, technical about the problem and technical about the solution, and let's just go and solve it. Let's not tell stories all day long. Let's just focus on how this thing is getting risk from here. to hear in a quantifiable, measurable way. Those stories that you're telling on earnings calls, they're not doing it. I'm saying it also about myself. Like to me, it feels like a cybersecurity theater that's completely disconnected from what's actually happening in environments. Sorry to be so blunt today, but...

No, that's why we love you because you're a direct in blunt. So hey, please Join me in thanking Tomer and Sonalee.

Thank you. Appreciate it.