Name: From Sprawl to Control: Regaining Control Over Data in a GenAI World
Uploaded: 2025-10-08T14:56:08.249Z
Duration: 40 min 8 s
Description: From Sprawl to Control: Regaining Control Over Data in a GenAI World

Transcript for "From Sprawl to Control: Regaining Control Over Data in a GenAI World": Hi, everyone. I'm Tuan Nguyen, product marketing manager for data security here at Forcepoint. And I'm joined by Nick Savides, field CTO and head of strategic business. This session is about one of the biggest challenges facing businesses today, data sprawl. So what used to be files living in SharePoint or email is now quickly moving across new channels and Gen AI tools. Right? So our discussion today is about how to go from sprawl to control. Regaining control over data in the Gen AI world and really do it in a way that empowers innovation instead of blocking it. So I like to start with the reality we're all living in. The data landscape is evolving. Right? Data is no longer contained. It's everywhere. It's across endpoints, web, emails, SaaS applications, different cloud services, and GenAI tools now. Right? And with all of this data traversing these different channels, we're hearing from customers and analysts really a convergence of pressure points on both CISOs and security teams. So the first is data sprawl and fragmentation. So the modern workplace is a mix of, you know, remote users, right, contractors, BYOD, bring your own devices, and different services. And, you know, we've heard it before. You know, businesses, they just don't know where their data starts or ends anymore. It's in Google Drive, Teams, Copilot, third party apps. Right? So data is fragmented across these different systems. And traditional tools, they struggle to keep up. Right? And you see that quote there from Gartner. You know, 85% of organizations just don't know where their sensitive data lives. And, of course, you know, the next one is the GenAI explosion. So there's a huge wave of adoption of GenAI tools, but that comes with real risk to data. Right? So employees, they're pasting sensitive customer data, source codes, even entire projects into ChatTBT or Copilot, Gemini. You name it. Right? Often without knowing that they're creating exposure. You know? And one of my favorite stories is from a company who recently implemented Copilot. Right? And an employee decided to, during review time, ask Copilot, am I getting a promotion? Right? And it, in fact, responded with you're actually on the termination list. So they found out that they're being let go that quarter versus getting their promotion. So GenAI is an incredibly pervasive technology that's meant to consume data. Right? But you need the guardrails around that and how employees are interacting with that sensitive data. And then all of this is happening in the face of increasing regulations and mandates that we have to abide by as businesses. Right? So compliance is really catching up with all of this data sprawl. So now we have an, you know, growing number of countries with privacy regulations, and most of the world's population is covered by some form of data protection laws. So, you know, regulations, they move fast. So we need a shift from reactive compliance to proactive data governance as, rightly quoted there from one of our customers. And lastly, you know, there's the human cost. Right? Security stack fatigue. So security teams, you know, they're overwhelmed by siloed point solutions and alert fatigue. Right? And there are many organizations out there that have five or many more different tools for data security. Right? And none of them talk to each other. So there's a real need for consolidation because, you know, stand alone solutions, they create inefficiencies, right, and drain resources. Alright. So let's let's ground this conversation in what's actually happening out there with DataSprawl. So first, you know, an organization potentially has over 800,000 files at risk from oversharing. Right? And that's not just from careless forwarding. It's actually from misclassification of data as well. Right? So you might think that a a file is safe, but when it's not properly classified or labeled, then it's suddenly open to way more people than it should be. Right? Then, of course, there's GenAI. You know, 72% of organizations, they don't yet have GenAI data security policies in place yet, which means employees are uploading sensitive data to these AI tools without the appropriate guardrails. Right? And over 80% of enterprise data is, you know, unstructured data. Think about emails, documents, source codes, while the rest, structured data, like databases, CRM, metrics, Oracle, MongoDB, you name it. And what happens is with structured data, it often gets less investment in security tools and resources. Right? But what's really required is coverage for both data types. Right? To really bridge that gap for a holistic picture across both structured and unstructured data to to see and understand risk. Right? And and close that blind spot. So, you know, this ties into that last data point there, which is 85% of organizations, again, do not know where their sensitive data lives. Right? So when we talk about data sprawl, this is it. Right? Data is everywhere and often without visibility and control. And so a new data security approach is required. Right? A full life cycle strategy. One that starts with discovery and classification of both structure and unstructured data. Right? And from there, we need to contextualize and prioritize that data. Right? Understanding ownership, location, identifying risky behavior, you know, so we can adapt and coach users in real time applying dynamic policies that responds to risk. Right? So we can remediate issues like over permission data, misconfigurations, exposure. Right? And finally, you need pro protection that's proactive. Right? So enforced through a single policy that prevents data loss across all the different channels, whether it be endpoints, SaaS applications, email, web, GenAI tools, and and beyond. Right? And this really hap needs to happen not, you know, once in a year compliance exercise, but it has to be continuous across every channel your data flows. Right? And when you take this modern approach, it can really deliver on three key results, right, which is visibility, control, and everywhere. So that's the foundation, but I don't want you to, you know, just hearing it from me. With me is Nick. He's out there every day with customers seeing how these challenges play out. Right? So I wanna bring in Nick, our field CTO, for his insights. Hi, Nick. Welcome. Thanks, Juan. It's good to be here with you today. Absolutely. Thank you for being here. So if we may, let's start with visibility. Right? So data sprawl, it was already a challenge as we just saw. Now GenEI is adding to it. So how has this shifted what visibility means for security teams? Great. It's a great question, Twad. And, I think that, you know, the complexity, around visibility and data sprawl has only got worse. You know, we we we know that this was a problem from the the dawn of computing as data started to to to shift out into different spots. It got a lot worse during the cloud era. And where we are today, we have these generative AI tools and really for us to understand what data we have is critically important. Because if we don't know what we have, we can't have a real understanding of our risk. So the ultimate goal from visibility is to get really meaningful cyber data risk quantification. This is absolutely critical. So you have to know what you've got so that you can measure and quantify your risk because otherwise, you don't know what to do. And if we think about the problem, most people have started with the the the thinking about generative AI as as an issue itself. Right? It's creating this new data. I don't know what to do. I don't know what data is going into it. I'm not really sure about what's coming out. And then it it it actually has got worse than most people think, and it moved into this, era of, you know, AI as a copilot, where your users are interacting with the with the with the copilot itself. It they're they're giving it information. It's creating new information back. Where is it? Is that in the tool? Has it been fed back into the tool? Is it in the chat? The data is actually sprawled out of the traditional locations of where but it's no longer in a file. It's no longer database. It's moving in and out of this tool with my user. And then finally, we've we've now moved in 2025 into this autonomous, agentic AI era where the agents themselves are creating data. And our tools, and sharing it. And our tools are instrumented, in general to, approach this. So what we have is existing data being accessed by AI. We've got AI generating new data, and now we have AI deciding which data it should share and where and to what other AI tools. So it's creating new data and it's sending it to other, AgenTic AI, tools. And our traditional data security tools haven't caught up with that, in enterprises. And that's what I'm very excited about here at Forcepoint is that we are tackling all three, of these these problems. So to understand what what thing the the these things are doing. I'll give you a really good example. You might have visibility today over a file sitting on some of these endpoint. But what happens, you know, you've got you you you you see what's on there. But what what happens when that file no longer exists and it's a piece of data inside an a a a, an AI agent that takes it, manipulates it, creates a new piece of data, and then sends that to another agent to do something else with it. And you don't know which agent it's going to pick at any point in time because it's acting autonomously. The visibility problem is absolutely critical to solve. Otherwise, we won't get that meaningful cyber data risk quantification quantification that we need, in order to understand what risk all of these things present to us. Yeah. That that's exactly right, Nick. And I love how you said, at Forcepoint, we're addressing every single one of these things. Right? Because what's really exciting about our AI mesh technology, which is integrated to our DSPM solution, is that you're able to classify with high accuracy across these data types, you know, across multiple data sources. Right? If it's being ingested to GenAI tools, and you're what what what, you know, customers are getting is that unified risk lens across their environment, right, where they can really understand their data risk posture. Right? We we can service, you know, you know, surface the the biggest exposure. Who has access? How sensitive is that data? How risky is that data? Does it, you know, contain PCI, PHI, PII, IP, all all these fun acronyms. Right? And and so we we have visibility in into all of this. We understand the risk. And then, well, most importantly, we we shine a light on what we call a ROT data. So ROT is a acronym. It stands for redundant, outdated, and trivial data, you know, and that's a key step in tightening, you know, governance and reducing, data risk and exposure. Right? Yeah. Alright. So that that's visibility. But, you know, knowing where data, is doesn't solve the whole problem. Right? We have to control it. So so, Nick, on on control, you know, too many security tools, they they create these silos. Right? So making consistent control enforcement more complex. So when you introduce this idea of unified policy management and data discovery across different sources, is there a light bulb moment for customers? Yeah. Absolutely. And and this is a really critical piece here. You know, we we just spoke about, you know, that visibility piece and being able to understand what we've got. And the next follow on from there is the control piece Because we have if we understand what we've got, we've got this meaningful understanding of our cyber data, our cyber data risk. Right? So we've quantified that. The next step is to try and control that. What we really wanna get to is this sort of meaningful cyber data risk, reduction. Right? So, we've got the visibility and the next step is to control. It's very nice to know what you've got, where it is, and what's happening to it. Now I wanna control it so that I can, actually reduce the the the the risk that I'm that I'm faced with. And the way I imagine this, it's like a very complicated machine. Right? In the old days, we had a desk and a filing cabinet and people coming in and out, swapping files in and out, and we could see everything that they're doing. And it was easy. Now this complicated machine has all these moving parts. It's it's dealing with other machines. It's creating stuff and feeding it back into itself and and into other people. Now we've instrumented it with the visibility piece. And importantly, I wanna touch on something you you said there that that unified policy. It is absolutely critical that your visibility is universal in its application. And what I mean by that is that the the the visibility is the same. So when I look at a piece of data, no matter where it is, I get the same classification. I get the same result. I get the same understanding of it. Now that I've got all of that, I can I've instrumented this complicated machine. Well, I wanna control the pieces. Now I want to control where the data is going. I wanna be able to control what is happening to it. And this is where I think Forcepoint really excels at because it's what we've been doing for a very long time with our traditional, data loss prevention technologies. These have been built over twenty years to effectively apply controls to the movement of data, but from a very user centric point of view. Now now that we have this ability to have visibility across everything, with the same level of accuracy, the same classification across all of these different things, we now have the ability to marry those those pieces of control, to that and we get real meaningful cyber data risk reduction. Because now I I'm able to control what the machine is doing with the data, what data it is producing, who it's giving it to, which other machines it's sharing it with, and how my users are interacting with that. And I think this is what really differentiates Forcepoint as a vendor in the rest of the industry. Because, you know, other people do might do do bits and pieces, but unless it's universal in its application, and that that that that that question the way you phrase that question in that, you know, the the, around the universal applicability and, you know, a unified policy is critical. Because otherwise, I end up with these patches, these silos, where my efficacy of understanding, my classification, my visibility is different, and my control is different. So what will happen is, I I I actually might control my risk really well on one side, but then I don't I'm not controlling it really well on on another piece. So this is absolutely when I talk to customers, they love this idea that I can create a policy and I am assured my level of control and my level of understanding is the same. So that when I see a piece of data on a file server or I see a piece of data going via an email or I see a piece of data between one agent and another AI agent, I get the same visibility, class vacation, and understanding of what it is, and then I get a piece of, a a a policy driven control aspect that tells me what to do in that that tells the the protection tool what to do in that specific scenario. It is unbelievably powerful. And customers really like that idea, because it it does give them that meaningful cyber data risk reduction, and they can report on that. And the and the more they apply those policies, the more they spread them out, they can actually track their their risk reduction and present that to their executive and say, we are in a much healthier position than we were last month and the month before that and the month before that. Absolutely. And and if I may add on to that, you know, it's all about that consistent enforcement and control. Right? But but at FourthPoint, we we don't have blanket rules that slows down everyone. Right? We have adaptive policies that takes into, context, you know, the sensitivity of the data, the user, the the risky behavior, that situation in real time. Right? So when we talk about safely enabling, let's say, Gen AI, for example, the key is enforcement that adapts without getting in the way of daily work. Right? You know? And and with Forcepoint data security everywhere, we were able to monitor, you know, user activity in real time where it it continuously adjusts, you know, risk scores and applies controls based on the context in that individual. Right? So so very important is this precise enforcement that that we're able to do with our with our holistic approach. Right? And and really really the the result is, you know, data security that works in the background. Right? You know, protect protecting sense of information and streamline compliance and really helping keep your people being productive, but but in a secure way. Right? Yeah. And that's very, very exciting. And what I find, is that this is one of the most unique things about Forcepoint because we've now instrumented our systems, our people, our tools, and all of the data flows. We've got this consistent view around what data is, what risk it presents, what classification and categorization is, and its context. We now have the ability to control the movement, of that data with the tools that we have. Well, let's look at the actual user now. Now, typically, what will happen is if I'm going to to to send a a file to someone, the the policy decision making is, relatively simple. It says, is is the recipient an authorized recipient of this data that Nick is trying to send? And it will stop that from happening or allow it from happening based on that policy. But what ends up happening in this scenario is that you have to have rules for every possible combination, and we know that's not the way real life works. And what what you end up happening is what I call the policy spiral. And, you know, organizations and customers will tend to to to write policies for every possible scenario. It gets that that policy list becomes longer and longer and longer. And what you've just described is probably the most, unique and interesting thing that I've worked on since joining Forcepoint, and that is the ability to have that adaptive response. A response that is determined at the time of transaction based on the risk that that transaction presents. And what we do here is we have an understanding of all of the precursor events that typically lead up to a breach or lead to a data loss event. And if I'm observing what a user is doing, I've instrumented that well, I can then say, when a low level of risk is presented, these are the acceptable actions that that can occur. When an elevated risk of, is present, that list of acceptable actions becomes shorter and shorter and shorter until I reach a high level of risk where now I I'm I'm actually gonna stop things. So we we're applying an appropriate level of friction at the right time, getting out of the way of the majority of the business so that when your users are low risk with low risk transactions, we are just observing and we let things happen. We let the business continue as it should, and only when there is a higher elevated level of risk do we apply an appropriate level of friction. Demonstrating this and talking through this with a customer, is actually one of the best experiences, because once people see this, you know, they actually don't believe that it's possible, because this was this was impossible just a few years ago, and we've made the impossible possible here at Forcepoint. It really, really is exciting stuff. I mean, just having a different action plan tailored for that individual in that moment in time. You know, I'm taking into context his risky behavior that day, that week, that moment. It's it's just really, really exciting stuff. So finally, you know, it's not just about one channel at a time. Right? Nick, you know, data security really has to extend everywhere. You know? So as new apps and tools are introduced, sees those, they they worry about gaps, right, that that that show. So how does Forcepoint's approach, you know, resonate when they see that they can secure SaaS, web, endpoints, email, and GenAI altogether? Yeah. It's a it's a great question. And I I think that it is it is really good if you've got control and visibility and protection across, you know, one channel. But that's the one channel. It's the one thing. It really doesn't give you the meaningful risk reduction we're trying to achieve unless it's applied everywhere. Because what will happen is you leave those weak spots and your data will flow through those weak spots. Your organization will be put at risk through those weak spots. So from our perspective, our approach is to apply this in every possible scenario, in every possible way that the user will be interacting. It gives us this idea that our data protection is self aware. We know what's happening across all of the different channels. We have the instrumentation, so we have the visibility, and we have the the the the ability to control, all across all of those different channels. So we don't leave those weak spots because they will become the high risk areas. So you wanna reduce your risk overall. And when we think about this from a force point perspective, are those five key areas that you mentioned earlier, the discovery, classification, prioritization, remediation, protection? We have to apply them everywhere. We have to apply them to all the different channels. We have to apply that to data at risk, at rest. We have to apply that to data in use. We have to apply it to data in motion. And what the way we achieve that is by having that behavioral analysis and the adaptive risk scoring that we, you know, we just spoke about. The posture controls. So this is this is a bad thing. This is a bad configuration. This is a a bad setting. You are oversharing this information. We have to have an understanding of that. We have to have the high accuracy discovery and classification that says, this data that I haven't seen before, this document that I haven't seen before, it is of this type. It is of this risk. It is of this classification. We have to have that. It has to apply to all of those things. And then, of course, what happens is once we've got all this instrumentation and you've got all of this control, typically, like any security tool, you increase as you increase your level of awareness, you've got more incidents that you need to deal with. And this is something that we we haven't forgotten about here at Forcepoint. A lot of, security tools will create this alert fatigue Because what they do is they they might improve your visibility in in an area, and, they will create all these alerts, but then it's up to you to deal with that. And that's why that prioritize piece for me is absolutely critical, because what it does is we are able to say these are the highest priority things that you need to deal with because these are the ones that present the most meaningful risk to you that you need to go deal with. And I'm going to do my best to automate the response of that. I'm gonna kick off an automated workflow. I'm going to work with your incident response plan. I'm going to work with your other tooling to either remediate that risk as quickly as possible, in an automated fashion, or allow you to be the most efficient in you in the way in the the most efficient that you possibly can be in responding to it with a person. And, of course, we don't forget about our people. In general, what I found, is that in an organization, most people mean well. And when they have an incident that they they would have inadvertently caused a piece of, data loss event or some other risky action, well, we want to be able to turn those users from a risk into a a risk reducer. And while we're dealing with the response side on when an incident occurs, we wanna prevent them from happening in the first place. So if we can coach our users and say, the action you are about to perform presents a risk. Maybe you should think about that. Ask the user to slow down a bit. That reduces the the the the number of incidents that actually get to the response stage. And this, I I really like this approach because, you know, if you I used to run a SOC, you know, you and you when you design your security processes, they're all the same. They all start with a funnel. Oh, I've got all my incidents come here, and I, you know, I filter them out, I deal with my high priority ones and then someone has to investigate. Yeah. Great. What we wanna do is optimize at each step. What we are doing here at Forcepoint, using those risk risk adaptive pieces and the user coaching, we're actually reducing the number of incidents that ever get to the funnel in the first place. By saying, these users are presenting the risks. I'm not gonna let them get into the funnel because I'm gonna stop these actions. Right? And these users might be doing something that is going to present a risk to the organization. I'm gonna stop them, slow them down, and say, hey. Are you sure you are doing the right thing? And that, typically, when you stop people just for a second and make them think about what they're doing, they'll take the safer course of action. So we're we're not only are we optimizing the funnel, we are actually optimizing the number of events that go into the funnel by by dealing directly with the users themselves. And this is what I like about our approach here at Forcepoint. It it truly is everywhere, not just across the different channels like, you know, air, email, web, and, SaaS applications and generate, Gen AI apps. It's across the people as well. Both the incident responders and the SOC and the actual users themselves. The technology operates across all of those to give us the most efficient, data security program that you can have. And that's why we call it self aware because it's it it's trying to deal with as many of the problems itself before they they hit your operation teams. Yeah. That that great, great points, Nick, because you touched on so many good points, but, you know, all not, not all users are malicious. Right? And data, you know, it doesn't stand these neat boundaries. So, you know, what's really needed is a solution that secures data in the way it's actually being used. Right? And by people working everywhere with data that's that's everywhere. Right? So this is really the shift that that we're talking about. Right? A complete data security solution that's really a business accelerator. Right? So it can drive better outcomes, whether that's compliance, innovation, or operational efficiency like we just talked about. But at the center of it is one unified policy. Right? It protects across data across the full life cycle, whether it's at rest, in use, in motion, and it does this, you know, as we talk with a consistent framework that discovers, classifies, prioritize, remediate, and protects. Right? So I I wanna take a moment to break down some of the outcomes you'll you'll actually feel customers actually experience. Right? So first is, you know, you see and protect data everywhere. Right? So customers, they're actually consolidating policies by as much as 90% by automating classification across every channel. Right? So that's that's a huge simplifier. Okay? The next one is safely enabling, Gen AI. Right? So so, so, you know, people can innovate with AI, but but while still governing how users are interacting with it. So they don't expose sensitive data in the process. Right? And the next one is is is huge. Right? Streamlining compliance and governance efforts. Right? Because when you have consistent and reportable visibility across data and channels, you know, let's be honest. What whatever makes an audit easier is is is a a total win. Right? And the last one there is consolidating fragmented infrastructure. So customers, they're they're reducing operational cost by by up to 31%, right, by by replacing silo tools with with one platform. So so this is really what we mean when we say data security everywhere. It's about simplifying protection while giving businesses the freedom to innovate securely. Right? Now to bring this to life, I'll have our TME, Aditya. He'll walk us through a short demo, so you can actually see how this works in action. Right? Having visibility and control across data everywhere. Hello, everyone. I'm Aditya Sahoo from the Forcepoint technical marketing team. In this video, we will explore the journey of sensitive data and see how Forcepoint keeps it secure at every step. To bring this to life, we will follow Tom, a banker working on a client portfolio. Before we follow Tom on his data handling journey, let's first log in to the Forcepoint DLP and check his risk adaptive protection score or RAP score. RAP is a capability within the Forcepoint DLP that helps organizations identify, assess, and respond to risky behavior, especially insider threats and potential data loss through real time risk scoring and automated policy enforcement. At the moment, Tom's RAP score looks quite healthy. Now let's see what happens when Tom attempts to download a a file containing client text records and Social Security numbers from his official Google Drive. Forcepoint CASB immediately steps in, intercepting the traffic and presenting a warning banner. This alert cautions Tom that the document contains sensitive PII information, helping prevent accidental or unauthorized data exposure. Now that Tom has already downloaded the sensitive document to his laptop, he attempts to copy it to a USB drive so he can continue working at home. However, copying sensitive data to a removable drive violates the policies enforced by Forcepoint's TLP engine. The result, Forcepoint immediately blocks the action and presents an on screen prompt stopping the file transfer. This ensures that sensitive information is protected from both intentional misuse and accidental data exfiltration. Next, Tom uploads the same sensitive file to his personal OneDrive to collaborate with colleagues who do not have access to Google Drive. Normally, this is where data sprawl accelerates with files being copied, reshared, and quickly slipping out of control with Forcepoint. However, the file is automatically encrypted in the background, and access is restricted to the approved project team only. Collaboration remains seamless while sensitive data stays fully protected at every step. Later in the day, Tom copies part of the financial data into ChatGPT, seeking a quick summary. At that moment, the information is on verge of leaving the organization, one of the riskiest points in its journey. However, Forcepoint reacts instantly. It detects the sensitive information in real time and warns Tom to provide a business justification to continue. The alert is clear, timely, and actionable, stopping exposure before it happens. With Forcepoint, even the risks posed by GenAI platforms are contained, and sensitive data stays protected always. Let's take a look at Tom's elevated wrap score. Because of his recent actions, Forcepoint DLP has raised his score into the critical category. From this point on, every move Tom makes is watched more closely. Every file he accesses, every attempt to copy or share data is evaluated against his recent behavior. This way, Forcepoint doesn't just block a single risky action. It continuously adapts tightening, protection as risk increases, and easing controls when behavior improves. And finally, here's the Forcepoint TLP dashboard, a signal pane of glass for your entire data security ecosystem. It brings together incidents from endpoints, SaaS applications, Gen AI tools, and email. So security teams don't have to jump between consoles from this unified view. They can instantly spot where sensitive data is at risk, drill into incident details, understand user behavior, and take immediate action. Whether it's blocking risky moves, tightening permissions, or launching investigations, everything can be managed right here all in one place. In just a matter of minutes, Tom's client's data moved across endpoints, SaaS applications, and GenAI tools. At every point, Forcepoint's data security approach enforced a single unified policy. Risky actions were blocked instantly. Tom's risk score was elevated, and adaptive controls stepped in requiring approvals and coaching him in real time, providing visibility and control across how data is stored, how it moves, and how it is used. This is what we mean when we say data security everywhere. It stops data sprawl from turning into a data breach, all while keeping business moving at full speed. One of the things that I I I've learned out of my five years here, at Forcepoint is that we are a company that continues to innovate. We have got twenty years of experience in this, data security space. We've got a proven foundation with proven technologies, that are trusted by millions of users across the world to protect their most sensitive assets. Now that doesn't mean that we can rest on our walls, and, we continue to, evolve as the market evolves. You know, we have adapted our technologies to deal with the the cloud transformation. We we took them from on premises into the cloud and then back down again. And we've adapted what we do to the modern threats that organizations face. And now we're entering the generative AI era, where Forcepoint is looking towards the future, and we continue to innovate our platforms and our data security everywhere, our our data security cloud. These are true innovations that set our customers up, not just for today, but for tomorrow and well into horizon too. You don't have to take my word for it. You know, we've got wide industry recognition by analysts and customers alike, for this. And it's one of the reasons I I quite enjoy working here here at Forcepoint is that we are constantly pushing the boundaries of what is possible, with data security. Absolutely. Absolutely. So let me wrap this up to where we started, right, with the idea of data sprawl. So Forcepoint's data security everywhere approach is really about giving you visibility, control, and protection across the data life cycle no matter where it goes. Right? At rest, in use, in motion, one platform. Right? Unified policies integrated with the tools you are already rely on. Right? And and really built to secure data on any device, any app, any location. So, you know, we hope we were able to give you some inspiration today and maybe a few ideas, right, to take back to your teams. But, really, this is just the beginning. So we we'd love to continue the conversation with you, whether that's diving deeper into your specific use cases, right, or exploring how GenAI fits into your security strategy or or looking how to, simplify policies across channels. So please reach out to us. Right? We also have our free DRA. So that's a data risk assessment, which we encourage you to try if you haven't already. Right? Which where, you know, in minutes, you can do a free scan of your OneDrive and get a report back of your data risk. Right? So so please take advantage of that. It's a fourteen day free trial, and you can find it there on on, forcepoint.com/dra. Right? So thank you for joining myself and Nick, and thank you for being a part of this journey from sprawl to control. Thanks, everyone.