Palo Alto Networks Inc ($PANW) Q3 2026 Earnings Call

Thank you, Hamza, and good afternoon everyone for joining us today for our earnings call. As you can see, our Q3 performance was exceptional as we delivered a record quarter. Our results surpassed every guided metric fueled by an acceleration in organic bookings momentum, the sustained tailwinds from our platformization strategy, and surging cybersecurity needs as AI transitions from experimental stages to enterprise-wide production. Within our core portfolio, we achieved significant traction in network security and SIEM, while Prisma SASE continues to establish itself as the fastest-scaling product in our history. Altogether, we delivered $8.1 billion in NGSAAR during the third quarter, representing 60% year-over-year growth. This is our most significant quarterly outperformance to date and surpassed our guidance. Our RPO reached $18.4 billion, up 36% compared to last year when adjusting for recent CyberArk and CloudGenix acquisitions, both of which are exceeding expectations in their first quarter post-close. Our organic NGSAAR and RPO rose 28% and 22% respectively. This is also materializing as AI fundamentally redefines the enterprise tech stack, elevating cybersecurity to a mission-critical priority for every organization. Much has been said about Minos over the last many months. Over the past quarter, frontier AI development reached a critical inflection point. We have entered the era of truly cyber-capable systems where models like Minos possess the autonomous capability to execute comprehensive attack campaigns from start to finish. This represents a fundamental paradigm shift for the cybersecurity industry. The most critical factor in this transition is speed. When weaponized by adversaries, these frontier models can identify and weaponize vulnerabilities in mere minutes, a process that previously required months of manual effort. Earlier this year, our Unit 42 researchers demonstrated the acceleration by simulating a comprehensive ransomware campaign from initial entry to data exploitation in just 25 minutes. In contrast, the typical enterprise still requires days to identify a breach. These existing latency gaps are already a concern, but the emergence of these latest models makes them completely unsustainable. We believe this is merely the opening act. As frontier AI development continues to accelerate, we anticipate a 3-6 month window before these systems evolve into more sophisticated hacking entities globally. Within a few years, we expect generative AI to reach a level of autonomous execution that is truly unprecedented, scanning environments, generating bespoke exploits, and orchestrating end-to-end campaigns at machine speed without human intervention. That is the trajectory of the modern threat landscape. However, this same technological leap provides a powerful defensive advantage. We validated this potential during the quarter. Leveraging our strategic partnerships with leading frontier labs, we utilized early access to their most advanced models to complete the equivalent of years' worth of fantastic in less than 3 weeks. This unique vantage point allowed us to introduce Unit 42 frontier AI defense, enabling our customers to fortify their environments against AI-driven attacks. Market reception has been exceptional. With north of 1,200 customers asking to meet us, we have already completed 800 meetings in the last 6 weeks to help our customers think through their cybersecurity future. These meetings are driving conversations across the platform. In fact, we're already seeing strong interest in our agentic endpoint security offering since the acquisition of Coy and have already generated interest for over 150 customers. This is critical for securing rights in the AI coating tools agents as they proliferate our endpoints. While identifying vulnerabilities is a critical first step, true mission-critical production is achieved at runtime. Real-time inline defense is the only way to shield even unpatched infrastructure as an attack sequence unfolds. This is where the cybersecurity battle will be won or lost. Countering the next generation of adversaries requires a comprehensive architectural vision that goes far beyond simple large language models. While the capabilities of these frontier systems are impressive, they're not a silver bullet for cybersecurity. We currently see two major structural challenges. First, the prevalence of false positives with error rates often reaching 25% forcing manual intervention that destroys the speed advantage of automation. Second, these models always fail at the last mile of complexity, leaving critical gaps in remediation and vulnerability management. In today's threat landscape, the most subtle 1% of novel attack techniques are what lead to the most devastating breaches. For every enterprise, the defensive bar must be perfect while the attacker only needs to succeed once. The probabilistic nature of even the most advanced systems leads to inaccuracies. In a mission-critical environment, the cost of a false positive is simply too high. One wrong enforcement decision can take down a global production network. Just as autonomous vehicles require constant real-time validation, an automated defense must be built on high-fidelity telemetry and battle-tested against every edge case to be mission ready. An AI model is only as effective as the data it can see. As frontier models become available to everyone, the real competitive advantage shifts from model to the data you have. That is why having sensors that sit in line with live traffic is so vital. They provide the telemetry and context needed to outmaneuver bad actors while serving as a critical enforcement point. The logic is simple. The more you integrate, the more you see, the more data you unify. The better the AI performs, the more you inspect the runtime, the faster you can stop an attack. Our global footprint now exceeds 125 million sensors across network, endpoint, and cloud, ingesting over 17 petabytes of daily telemetry. This scale creates a powerful flywheel. Every new sensor makes our entire platform more intelligent, which leads to more deployments, more data, and even stronger real-time protection. This reality is why platformization is the only sustainable answer. The legacy approach of query-based tools that wait for human reaction cannot keep up with machine-speed threats. We're transforming the industry by consolidating data onto a single platform, reducing breach response times from days to minutes through AI-driven pre-analysis. Point products that silo data and increase latency are becoming obsolete. As the battle moves to fighting AI with AI, we believe Palo Alto Networks is in pole position, and our Q3 results prove that momentum. As AI compresses attack timelines, only a platform that gets smarter with scale can respond fast enough. In the third quarter, we received 110 net new platformizations. This figure includes 20 from our CyberArk console integration. These strategic additions expand our reach into large addressable markets within data and observability. Given the fragmented nature of these sectors, they're perfectly aligned with our overarching platformization vision. We concluded Q3 with roughly 2,280 total platformized customers, bolstered by the inclusion of our latest acquisitions. These engagements represent deep architectural commitments rather than simple transactions. When organizations reach this integration milestone, they standardize their infrastructure on our platform, yielding superior long-term retention and expansion. This is reflected in 120% net retention and single-digit churn rates amongst this cohort. Moving forward, we remain confident in surpassing 4,000 platformizations by fiscal 2030, providing the primary momentum towards our $20 billion target for NGSAR. The scale and quality of our customer business this quarter reflect how strategic these platform commitments have become, and how customers are increasingly bringing us in to secure production AI deployments at scale. Let me share a few examples. In Q3, we surpassed $200 million in ARR with a leading frontier AI lab that relies on us for observability across its most demanding training and inference clusters. We expect that to continue to grow again next quarter as they complete their migration to Cortex XDR. One of our largest Q3 deals was an $80 million transaction with a leading power producer in the United States, an organization at the center of the AI infrastructure expansion. They selected our next-generation firewalls and also adopted SASE to secure a distributed workforce of over 25,000 employees. A global consulting leader signed a deal for over $20 million, selecting Prisma AI, our AI security platform, to secure its rapidly growing fleet of AI assets and agents that are running more than 2 trillion tokens per month on our platform. This was an existing platformized customer who spent several months working closely with us to secure this entirely new frontier. It was also a record Prisma AI win and speaks to our customers partnering with us for the AI transformation journey. As AI redefines the stack, these deals further validate our position as the cybersecurity partner of choice. That was particularly notable in our network security business, where we had our strongest Q3 in several years. Our largest business unit, network security, delivered its most robust third quarter performance in years. This momentum underscores the mission-critical role of real-time network traffic inspection as enterprise-wide AI initiatives continue to transition to production. This Q3, we saw strong growth in hardware, SASE, and software firewalls during the period. Following the earnings, we anticipate that AI will serve as a structural catalyst for deeper traffic inspection requirements. The initial phase of AI adoption was primarily conversational, but the shift towards agentic AI represents a fundamental change. Unlike simple chatbots, autonomous agents trigger a massive volume of secondary machine-to-machine interactions, consistently accessing tools and data to complete complex workflows. This creates a surge in nonstop, high-volume traffic that must be secured at runtime. This evolution directly translates into heightened demand for high-throughput hardware, expanded cloud-based software capacity, and the necessity for unified policy enforcement across the entire platform. Our Q3 results featured the strongest hardware performance in a decade, with next-generation firewall bookings rising nearly 40% year over year. This was supported by our latest Gen 5 appliances in early access and AI data center build-outs. We're seeing early adoption from a new class of buyers, including sovereign infrastructure providers and AI labs, representing a significant new market as deployments move beyond traditional hyperscalers. A key differentiator for our hardware portfolio remains the strength of our subscription attach, illustrating how customers are standardizing their security stack on our platform. Within our installed base, we currently average more than four subscriptions per device. Our innovation engine continues to expand this opportunity, and we now provide 11 advanced subscriptions, including our next-generation trust security, which utilizes Fiber Arc certificate management to address emerging compliance standards for shorter certificate lifespans. Palo Alto Networks remains the fastest growing provider in the SASE market. In Q3, SASE ARR reached $1.6 billion, growing 40% year over year as customers prioritize unified protection across hybrid workforces and AI applications. Competitive momentum remains high, with nearly 50 displacement wins totaling $200 million in contract value year to date. Secure browser also achieved a major milestone, scaling to 11 million licenses, a fourfold increase that cements its status as a critical control point in the AI enterprise. Furthermore, software firewalls remain a high growth pillar of our strategy. ARR was up 25% in Q3, accelerating as organizations expand their capacity to inspect growing traffic between cloud and AI workloads. As these environments scale, the requirements for high-fidelity telemetry only increase. The common architecture approach is also driving increased customer growth in Prisma SASE, which continues to be the fastest growing product in our history. Organizations are aggressively moving beyond the experimental phase, deploying AI agents and applications to production. This transition creates entirely new mission-critical security demands. We believe we are the first in the industry to embrace AI security platformization. Yes, AI security platformization, capable of securing and monitoring AI end-to-end. We have effectively doubled our capabilities in this space in just over 9 months. Our journey began with securing models and runtime defense. We then integrated identity security to govern agent access and observability to trace agent behavior across complex infrastructure. Most recently, we expanded agent endpoint security as AI tools proliferate across the edge. Our recent acquisition of Portshift marks yet another strategic milestone. As a leading AI gateway processing trillions of tokens monthly, Portshift provides a critical enforcement point to monitor every request, apply real-time policy to agent-to-agent interactions at scale. This relentless innovation has established Prisma SASE as our fastest growing product ever. We reached over 300 customers in Q3, tripling our Q2 count, and have clear visibility towards $100 million ARR within the next couple of quarters for a product that was not in the market 1 year ago. Ultimately, securing the AI enterprise generates a massive volume of runtime telemetry. Data is only actionable if processed at machine speed, which is a core mission of our Cortex platform. XSIAM remains our primary response to the emerging frontier model threat. As attack cycles compress to machine speed, organizations can no longer rely on legacy query-based architectures or manual dashboards. Effectively countering AI necessitates a defensive strategy powered by AI. Upon the introduction of XSIAM 42 months ago, we entered the sector as a disruptive innovator, engineering our platform from the ground up to redefine security operations. Today, our platform processes more than 17 petabytes of daily telemetry, a volume unmatched by any other pure-play security vendor. We ended the third quarter with more than $600 million in ARR, representing a 100% year-over-year increase across a growing base of 740 customers. The most significant metric, however, is the outcome. The majority of our customers are now responding to threats in under 10 minutes. This is a dramatic reduction from the days or weeks previously required, and serves as a blueprint for the modern SOC. In observability, our Q3 performance was well above our initial expectations. As AI initiatives generate a surge in telemetry, Cortex XDR is a purpose-built capability to scale alongside these workloads. Our observability ARR surpassed $300 million this quarter, nearly doubling since our acquisition announcement last autumn. Furthermore, 80% of our net new customer acquisitions this year adopted multiple products, reinforcing our platformization momentum. The world's leading AI natives, including two of the top five frontier labs, have adopted Cortex XDR, validating our ability to provide observability at AI scale. Beyond our early investments in markets where AI would drive a positive inflection, we also recognized early where AI would overhaul existing security capabilities. Consider posture management. Traditional periodic scanning is insufficient when attack timelines are measured in minutes. As a result, we proactively transitioned our cloud portfolio from static posture to real-time detection with Cortex XDR. We're making steady progress and anticipate most Prisma customers will be migrated to Cortex Cloud by the end of the fiscal year. Now, as these agents proliferate, every autonomous entity represents a new identity that must be managed, which leads directly to our progress with CyberArk. In our inaugural quarter post-close, CyberArk has surpassed our internal benchmarks as we move to execute our unified vision for identity security. Last month, we launched Ideara, our next-generation identity platform for the AI-driven enterprise. For years, the industry operated under the IAM fallacy, the belief that you only needed to secure a handful of privileged administrators. In the era of agentic AI, that distinction has vanished. Every identity, whether human, machine, or software agent, now possesses the potential to access a sensitive system at machine speed. Ideara addresses this shift by democratizing modern PAM controls across all users, extending protection to agentic identities, which represent the primary attack vectors of the future. Our execution in Q3 was strong. Joint go-to-market efforts have already initiated approximately 1,000 cross-organizational engagements. This has sustained CyberArk's growth trajectory while improving its profitability profile through our integration initiatives. Given our rapid progress, we're now 3 to 6 months ahead of our original timeline for converging CyberArk's profitability with our own, a milestone we expect to reach within the next 12 to 18 months. This acceleration reinforces our path towards a 40% free cash flow margin in fiscal 2028, which Deepak will talk about more. The events of the third quarter represent a watershed moment for cybersecurity and have elevated our category even higher on the CIO priority list. Mark my words, this all has increased the terminal value of the entire cybersecurity industry. We're identifying several structural catalysts for the AI cycle driving growth across our platform. First, AI creates a massive surge in traffic and connection points requiring real-time inspection as agents trigger hundreds of secondary actions. Network security becomes an indispensable foundation for SASE adoption. Second, countering machine-speed adversaries requires real-time automated defense. This is the core mission of XSIAM, consolidating data onto a single platform so AI can respond to threats in minutes rather than days. And third, in an environment populated by both humans and agents, identity serves as a primary defensive layer. When autonomous entities can execute actions independently, securing access to identity becomes mission critical. The convergence of these trends validates our platformization strategy. Managing fragmented data and siloed point products is no longer viable in an AI-driven landscape. A unified platform that gains intelligence with scale is the only path forward. While we're still in the early stages of this shift, we remain committed to innovating ahead of the threat landscape and earning our customers' trust every day. I will now turn the call over to Deepak to discuss our financial results in greater detail.

Yes, we can hear you.

Thanks, I guess first of all, I thought you were asking me about the 40% free cash flow question you mentioned on CNBC, but anyway, we can save that one for the...

Yeah, okay. Look, you saw across the board, we've always maintained that as more traffic traverses networks, more inspection is needed. When more inspection is needed, hardware is the cheapest and fastest throughput mechanism to inspect the data. I think the multi-year tailwind will come from the fact that more and more data needs to be stored both by organizations, needs to be used for training all these frontier labs out there, and you can see the explosion of data centers being built, whether it's by hyperscalers, frontier labs, or neo cloud labs out there. And you're seeing that demand fall through to some of the hardware vendors in the space. I think couple that with the scarcity and component pricing, you've seen some pricing increases, you've seen some of that mixture of price uplift as well as demand uplift, but I think, you know, maybe the number's gone from 5% to 8% to 10% to 12%, so that's a 50% increase in demand for the industry, I think. I think you'll see that. I think you'll tell me before I can tell you when you see when data center growth starts to taper off or plateau, you know, this thing is going to come to roost, but I expect that this trend should continue for the next few quarters, if not few years. Lee, did you want to ask? Hopefully you think I gave a good answer.

So, let's do a double team with this. I'm going to start off and I'll have Lee talk about some of the capabilities that we'll need in the AI future. But one of the things which we have done, as many of you know, over the last many years, we actually built native VM capability in many of the hyperscalers. Now you're seeing that is where a lot of the models are being hosted, a lot of the AI artifacts are sitting for customers because AI is not an on-prem event. It's typically a cloud event, hyperscaler event. And the fact that we have native firewalls sitting in those hyperscalers allow us to inspect traffic, not just regular cloud traffic, but also AI traffic. And I'll have Lee talk about all the capabilities we've built in Prisma Access over the last 12 months, which have allowed us to provide all the security capabilities that AI needs.

Well, look, each of the models has a different approach in terms of how they do the observability. Some have their own approach on a DIY basis. Some of them are using third-party vendors like us. So, I don't think it's one-size-fits-all. What we are seeing is that Chronosphere is particularly good at AI native platforms, whether it's frontier AI labs, or whether it's SaaS software, I call them modern SaaS software companies, and not older SaaS software companies. Typically, what's happening is the observability market is maturing. Companies are beginning to realize as volume scales, it's not okay to be DIY. I think the general reluctance in the observability industry historically has been cost. I mean, even at Palo Alto, when we were deploying a third-party vendor, we chose to turn it off because it was prohibitively expensive. And what Chronosphere has done has been able to deliver that same capability at approximately half the cost of what the industry charges. So, it starts to meet the number at which you're better off not building your own or using open source with some enterprise capabilities; you're better off using platforms like Chronosphere. So, it's early days. At least they said we have a roadmap that requires us to bolster a few more capabilities in the platform to make sure it's competitive in its space, but the advanced practitioners already see the capability and the ability and are happy to use it, and we continue to make progress on the roadmap to make sure that becomes a full comprehensive platform and hopefully it becomes another mainstay platform for us in the future.

Well, Fatima, thank you for the question. Look, we have repurposed our Unit 42 team to focus primarily on frontier AI defense. As I mentioned, we've had north of 1,200 outreaches from customers both in both directions where we reached out to our customers and they to us. Both Lee and I and a lot of people in my team have personally done tons of meetings. You know, I've done close to 100, Lee's done close to 100. We're doing these meetings to talk to our customers about how they want to strategize, not just about how to react to models like Me Too's because we believe it's real, but also to prepare for something that can get better and better and how does the infrastructure need to change in the next 6 to 12 months from now? We are firmly of the belief that people will have to deploy the new endpoint capability like Coy, go to Prisma Access browser or secure browsers. They will have to put virtual patching capability in the firewalls and fundamentally reimagine their SOC and use XDR. So, all of that is true, but the conversation usually starts with Unit 42 trying to help them test their code, make sure their code is safe, their code is robust, test their configurations and help them with some form of managed patching for their environment because every vendor is going to show up with lots of patches that need to be done this time. So, that's primarily where Unit 42's focus is short-term. Long-term, they're focused on transforming architectures where again, all of Palo Alto is focused on delivering that capability. As it relates to agentic dog fooding or champagne drinking or dogs drinking champagne, I think, yeah, we have, and I don't want to say, you know, this is sometimes better to be lucky than good. We did design XSIAM with the idea of pre-analyzing everything before we ingest the data. So, XSIAM is turning out to be a great tool in this regard in terms of reducing the mean time to detect and remediate for customers. And it has agents running in it to give you that capability. I think that capability will increase. And you know, we can have a long conversation about what exactly an agent is. I think there's a lot of deterministic workflows that run to reduce the task of a SOC analyst. A lot of automation that exists in XSIAM and over time perhaps our customers will trust those agents to act independently. For now, the customers want to sort of see, observe, and approve, which is where it's set up. And then as customers get comfortable with deployment, we'll get to give it agency. So, we're not seeing the rush demanding agency. I think right now customers are in phase zero where they're saying, "I better collect all my data because if I don't have all the data, I don't have all the context. If I don't have all the context, I can't actually react to any attack."

So, Michael, I don't want to make sure all of you understand. Six months ago, cybersecurity stocks were doomed because AI was going to protect every one of us and we were all out of a job, right? And suddenly, we're hiring more people. AI is not taking jobs away. And suddenly, you can't execute a cyber protection scenario without using a platform subject to a vendor. And think about it, right? I think the part which you must pay attention to, Michael, is I said there's a 25% false positive rate. It means an AI model can say, "Oh my god, I see a vulnerability." And one time out of four, it's not seeing the right vulnerability, which means if you let AI do the job, it could try and patch something that's working perfectly fine. And if you let AI go protect that, you might have screwed up something else. So, I think you got to take this with a grain of salt to understand that the three big takeaways, if I was in your shoes I would take from this is if you thought that the terminal value of cybersecurity was gone, like many SaaS companies, this terminal value is here to stay. You actually just created a longer-term G in your model for long-term growth rate for cybersecurity. I think to the extent you felt the demand was going to get weak in Q4 or Q1 or Q2 for someone, it's not going to get weak. Now, I wouldn't get ahead of my skis and start throwing the kitchen sink at numbers for cybersecurity companies because there is still a process, a mechanism, a cycle that people buy in, and there's execution and deployment. So, to the extent that do I see good demand? Yes. To the extent that I believe that the demand will continue for longer? Yes. To the extent do I expect a windfall next quarter, the holiday quarter? No, I expect robust growth.

Look, I think, Adam, we are what I'd like to call the second wave of SASE. The first wave of SASE was internet access or VPNs. And that's what you could call them SASE, but they were effectively feature capabilities in that market. And you saw the VPN people, like the firewall guys, win the VPN battles. You saw the internet access companies, which were the early SASE players, win the SASE battle. I think as we evolve from there, what we're seeing is the desire for a comprehensive network stack. Only what I mean by desire for a comprehensive network stack, people call it zero trust, people call it a single policy across multiple network capabilities, people call it a network for the architecture. People are figuring out that if you want to secure your traffic, you want to dynamically route your traffic, you know, there's a lot of contention between SD-WAN and security, you need to have a common platform. Now, we got SD-WAN many years ago, and we only sell it as part of this SASE platform because we don't believe we should be in the solo SD-WAN business for the most part. And that was the strategy. Now, we're seeing network architecture projects show up where people are saying, "My god, I really understand Palo Alto's security framework because we use Palo Alto firewalls. Amazing. You're telling me I can just replicate those policies across my entire network stack and not have to go learn a new stack, write a new set of policies. That's cool. Oh, wait, I can do that in software firewalls and Prisma Access as well." So, I think what we're seeing is the benefit of consolidation. Now, I think one more thing has changed in the mind of the customer. This is my eighth year, the eighth week anniversary in 4 days I'll hit 8 years at Palo Alto, surprise, surprise. And I'll tell you, there was a lot more willingness to take best of breed 8 years ago. I think that willingness has slowly subsided where the customers see the value. Perhaps the products have normalized, perhaps the companies have matured, but customers are much more comfortable talking about a consolidated strategy with hardware, software, and SASE. And I think what you're seeing is our ability to present that capability to the platform. We are taking share from some of the SASE-only customers, and unfortunately, to their chagrin, firewalls are not dead. Just the way hardware is not dead, and PCs aren't dead, and storage isn't dead, firewalls aren't dead, either. So, having a firewall leader who has the ability to deploy world-class SASE is helping in the market, and that's what you're seeing.

You just don't trust me, John.

Okay.

Do you have a selling point?

So, the one which I think we've talked about fleetingly, John, and I'll tell you, you know, a lot of things are going well, and we continue to toil through migrating our Prisma Cloud customers to Cortex Cloud. I wish that was behind us, but that is still ahead of us for the next 6 months, so we'll keep grinding through that. That was not contributing as well as some of the other products are. So, that's fine. You know, that's why you have a portfolio of platforms and some do amazingly well and they cover up for their slightly slower brethren, and the slower brethren come from behind and go win after that. So, I think we feel not everything's perfect, John, but a lot of things are doing well. So, thank you for that part. As far as CyberArk is concerned, I think we have a very, very measured strategy around CyberArk. Remember, this is our first large acquisition. The biggest fear in large acquisitions people think is that we will break it. I think the most important part is we did not break it. Look, I didn't break it. It's working. Okay? We worked with the company. We made sure that we talked to every one of the leaders. In fact, the entire CyberArk product team is in Palo Alto right now in our offices. We spent most of yesterday and this morning with them and we'll continue to spend the next 2 days with them. The plan was, just the way when I found Palo Alto 8 years ago, it was a great company, it is a great company, so CyberArk, we have to make sure that that product gets more modern and more innovative. And that's what the team's very focused on. I've been seeing commitments where I'm going out to customers, showing them the roadmap, promising them that the PAM product is going to even get better than compared to what it already is, and we're going to show them great outcomes. There are Palo Alto customers who are asking to meet CyberArk. There are CyberArk customers asking to meet Palo Alto. We have 1,000 meetings where Palo Alto and CyberArk people are talking to each other and going to the customer together. Two independent sales teams, but they are connected in 1,000 different places, which is already creating some degree of momentum. So, you know, our plan is don't hurt the top line. Make sure that the existing customers still love us, want to buy, want to upgrade, and they're going to see better product. That's phase zero. Take out all the places that could be friction or overlap, which allowed us to streamline and get better operating margins. You know, I just got an email this morning. We have migrated one of our critical systems from CyberArk independent system to Palo Alto and CyberArk on the same system. We have four more major systems to get through in the next 4 months. We think we'll get there before the end of this calendar year. If we can integrate their back-end systems to common systems, we're using AI to write a whole bunch of new coding capabilities, sales capabilities. So, topic number one, trim the fat or trim the overlap and don't break the top line. We think we're on track not to break the top line. Improve the profitability, which we've done. As we said, we think we're going to be six months ahead on profitability because we found ways to get there faster. Our job is then to make sure that if we can deliver the next capability of products which is incremental to what they already had, that allows us to look at the whole fiscal year and say, "How do we go out and hit the ground running in the following fiscal year to deliver better top line?" So, CyberArk is our chance to prove that we are capable of doing amazing large acquisitions. We're capable of integrating large teams. And if I can prove that, the market will give me the license to go win again. So, this is existential for me. It's existential for my team, and they know it. So, we're going to work hard to make sure that CyberArk succeeds, allowing us to do more and more of that in the future. So, the bottom line is, thank you for the question, John.

Well, I just want to say thank you. Officially declare Cylance and ClearSky Cyber Security dead. I want to thank our partners and employees and all of you guys for supporting us. I'll see you guys next quarter.