OK, welcome everybody, and thanks for joining us on the third day of Oppenheimer's Virtual Conference. Good afternoon, I guess, at this point. My name is Ittai Kidron, and I'm a Security Software Analyst here at Oppenheimer. I've got the pleasure of hosting Cognyte, more specifically Elad, the CEO, and David, the CFO. The guys; Elad and David, are going to give us a presentation about the company. Needless to say, we'd like to get all of you involved as well. Feel free to post your questions, and I'll be making sure to watch for the site and look for your questions and incorporate them in the discussion as we go. With that, Elad, David, thanks for joining us today. The floor is yours. Looking forward to it. Thank you, Itay. Good morning. Good afternoon, everyone. Thank you for joining us today. Before I start presenting Cognyte, I may make some forward-looking statements that are subject to risks, as outlined in our filings with the SEC. Maybe I'll start with the big picture. The global security environment our customers face is more complex and fast-moving than ever. Crime and terror are accelerating. We do see that it's becoming more global. Actually, more than 70% of organized crime groups are operating in more than three countries. We do see that the borders between terror and crime are blurring. They use the same smuggling routes. They do have similar funding resources. Actually, some of them are cooperating, and the stake is high. We do see that the potential damage, actually the actual damage, is over $2 trillion a year. This presents a high risk going forward, and the threats for the security and the safety of our societies are growing. This is exactly where Cognyte comes in. Our solutions deliver faster, more accurate decision-making capabilities. We help organizations, primarily security agencies, to generate actionable intelligence in order to accelerate and enhance the investigation and operations. What it means is that we help them, actually, to be able to accelerate the speed, accuracy, and success rate of investigations and uncover insights in order for them to take the right decisions on time and neutralize threats. We deliver our solutions to customers globally, and primarily security agencies, such as law enforcement. Law enforcement is the blue police. Actually, they're fighting crime. They have to get a warrant from court and investigate and put their hands on the bad guys. We also have military intelligence customers. Those customers need real-time intelligence on the field during missions. This has to be robust and real-time analytics of data they have in order for them, first of all, to keep themselves safe, but also understand the environment around them. We have customers in the national intelligence segment. National intelligence are usually those intelligence guys that are looking for potential threats that are coming from outside of the country. Those threats may become significant threats for the safety of the citizens and the forces and the assets of the country. National security agencies, those agencies are actually focusing on threats, primarily terror threats, that are coming from inside the countries. All those organizations need technology in order for them to be able to accelerate investigations and make sure that they are successful in the missions. Our customers actually are challenged on three fronts at the same time. First is data. In order to generate intelligence, you need to analyze data. We all know that data is growing in volumes and diversity and very fast. This presents actually a challenge for our customers that needs, first, to be able to analyze lots of data and do it very efficiently in real time with strong analytics. The second one is the adversaries themselves. Actually, they are becoming more sophisticated. They are well-funded. They are well-organized. They know how to hide better. It is becoming harder and harder for security agencies to put their hands on the bad guys. The technology is running fast. This presents opportunity, but also risk, to our customers. Opportunity because if they are ahead of the curve and utilize the new technology faster than the bad guys, of course, they will be in an advantage position in order for them to be able to find the bad guys and put their hands on them. On the other side, if they are lagging behind, the bad guys are also using technology, for example, AI, in order to generate fake identities, fake entities, and hide better. This is actually a race between the security agencies and the adversaries. We offer solutions that enable agencies to investigate, identify, mitigate, and prevent threats. If you look at the overall threat environment, there are many, many different use cases, and you have only a few examples here, that our customers have to address. It is counter-terror. It is organized crime. It is financial crime that is also in the cryptocurrency environment, which is anonymized. It is violence. It is cyber threats. It is military threats, border control, illegal immigration, drug smuggling, trafficking, human smuggling. Many, many different use cases our customers have to deal with. All of them need to be able to analyze data in a very sophisticated manner in order to investigate what already happened and actually understand and put their hands on the bad guys, but more importantly, sometimes to identify potential threats and mitigate them before they unfold. This allows them also to prevent threats. We all hear in the news the threats that happened, OK, that materialized and created damage. Unfortunately, lives are lost because of that, and also financial damage is significant. We don't hear many, many threats that have been identified and prevented before they unfold. When customers have technology, they have the advantage, and they can do a lot in order to keep the societies and also the assets safe. Now let's look at the three layers that form the backbone of our solutions. We start with signal processing. Actually, we take chaotic, sometimes encrypted signals and turn them into organized data. Then we convert the data into insights and the insights into actionable intelligence. It's becoming more and more complicated. If 20 years ago, each person or each bad guy had one identity, which is his phone, a wire phone, today they have many different identities, many virtual identities, sometimes fake. The funding sources are anonymized. Actually, customers have lots of data that has no meaning unless you use a sophisticated technology in order to uncover insights out of it. Another challenge was that lots of data converted and became encrypted. Encryption actually helps the bad guys better hide. Today, with sophisticated analytics and AI, you can generate actually or unhide hidden connections, hidden relations, hidden identities in order to convert this signal processing later on to data and actionable intelligence. When we say actionable intelligence, eventually, those security agencies have to take the right decisions on time in order to secure their societies. If they get the insights on time, and we'll discuss immediately what I mean by insights, they can save lots of lives and actually mitigate financial damage. Together, those three layers I just showed you give our customers the ability to conduct complex, mission-critical investigations with speed and confidence. We see data differently. Before, I just mentioned that actually customers have to get actionable insights in order for them to do the job or be successful in the missions. What they need to do, the W and the H questions. Who is going to do what, when, with whom, where, and why? What's the rationale behind it? What are the motivations? What are their funding sources? They have to answer many, many different questions in order to be able to mitigate risks and uncover threats and actually neutralize it before it unfolds. The ability of sophisticated technology to take signals that have no meaning and convert it into organized data and convert the data later on to actionable insights gives the customers, our customers, security agencies, the ability to answer those questions. If they have the answers for those questions, they can mitigate risks. Maybe a bit about Cognyte, the company itself. We are in this market for over three decades. We are operating in nearly 100 countries. We have hundreds of customers. Overall, we have about 1,500 + employees. A significant amount of them are R&D experts. Actually, 800 employees are in R&D. We are located in 13 global offices, out of which 6 are global R&D centers. As you can see, we are global, and we have a long track record in this market. What really sets us apart is our real-world experience. Our solutions have saved many lives over the years. You can see that it's not just about technology. It's also three decades of breakthrough technology, but we also have veterans coming from different security agencies, from law enforcement, national security, employees that know how investigation looks like, what are the pains of our customers, what they need today, what they may need potentially in the future. This combination of domain expertise and technology is very important. In addition to that, we are working with many customers, including tier one customers, very sophisticated and vast customers. We have the luxury to have our customers as our partners, design partners, share with them our roadmap, get the feedback, and purify and focus the technology development and evolvement to exactly what customers need. We are also implementing new technologies frequently, including, of course, the AI, machine learning, in order to gain two things. The first advantage that is generated by using AI is to make the utilization of our technology much more efficient, which means that simple users can query the solution with natural language rather than being required to understand the data exactly and to have to query the solution in a very sophisticated manner. Many simple users can do a lot of work much more efficiently and faster and get into conclusive outcomes successfully. The other side of AI is helping us to uncover more hidden insights. I mentioned before that some of the signals are encrypted, and we cannot decrypt, but we can run analytics on top of it to find hidden relations and connections. This is done by AI. Another example is the anonymization of entities that are running transactions in the cryptocurrency environment. This is also done using AI. We are partnering with our hundreds of customers around the globe, delivering to them very advanced technology, but also learning from them continuously what they need in order to be able to maintain our leadership position. When I say partner with our customers, it includes also being able to engage with them frequently. We also have an intelligence summit that we invite all our customers. There are usually industry conferences that many different vendors and many different customers are coming to the same place to see what's new. In addition to that, we have our own Global Intelligence Summit, where we, Cognyte, only invite our customers globally to join us in order first to get the idea of what's new, the latest and greatest releases that we have, but also learn from them. The recent one was back in November 2024, when 300 guests joined us from nearly 70 countries. This kind of event keeps us highly engaged with customers, but also gives us the ability to really understand their current and future needs. Back in April this year, 8th of April, we conducted our Investor Day. This was an Investor Day in which we were able to present the market, the technology, and also the long-term targets. Our fiscal 2028 financial target is to become a half a billion-dollar revenue company with a gross margin of 73% and adjusted EBITDA close to 20%. As you can see, this reflects actually continuous top-line growth, but also margin expansion. We have financial leverage in our model, and we are going to grow to $500 million in top-line, but the profitability will grow much faster. This is the target for fiscal 2028. Closing on what matters most, our customers on the front line, keeping the world safe. The testimonial speaks volume about our impact. You can read it. Actually, our customers are saving lives every day. They are preventing financial damage and damage to critical assets every day. They do a lot of it using our technology. We are really happy to be in this market and to help our customers to achieve successful outcomes. This is actually summarizing our purpose. Our purpose, Cognyte's purpose, is to help our customers make the world a safer place. We have a proven track record of impact. Longstanding customers, some of them I know personally for over two decades, are with us for many years. They continue to expand with us in addition to acquiring new logos that we have. We actually have a relentless drive for innovation. It is a combination of understanding the market, engaging with customers, delivering high value, continuing to evolve and innovate, and making sure that the customers are successful in their mission. That's what we do at Cognyte. With that, I conclude the presentation, and we can move to Q&A. Thank you all. Elad, if you can keep the slides on, can you go back to the third or the fourth slide that shows the product, the three layers of your product? I want to make sure I understand the stack more accurately. Specifically, can you elaborate a little bit about the technology that you're using? What are the types of signals that you're collecting? Is your architecture some sort of a data lake architecture that collects and creates some baselines of behaviors? Try to help me understand the fundamental technologies that are used in each and every one of these layers. Sure. Actually, our customers, different customers have different data sources. Some of them are regulated. Some of them are less regulated. Generally speaking, customers have many different data sources. I can give you examples. They have data coming from the dark web. They have data coming from social media. They have data coming from their own databases, criminal records, vehicle records, weapon holders' records, etc. They have data coming from historical investigations they've done. They have forensics data that they have, actually devices that they put their hands on and actually took data out of it. They have communication, telcos data. There are many, many different data sources that our customers have. Some of the data sources are structured, like databases. Criminal records are a database with structured forms. Some other data sources are unstructured. It's video. It's images. It's a type of data that is unstructured, and you have to run engines in order to understand what's inside. When we say signal processing, signal could be data coming from telcos, for example, OK? It's signals that some of them, the metadata is encrypted. Actually, customers need to know who is talking to whom, who is part of an organized criminal group. They have to connect the dots. They have to take those data sources that they have, the structured ones and the unstructured ones. In addition to that, they have to analyze what's inside and be able to understand that one piece of data here is connected to one piece of data there. Then they get the intelligence picture in order for them to be able to take actions. Got it. Signals could be telcos, could be pieces of data that have no meaning. There are data sources that are structured. The combination of those is fused in a very smart manner. Actually, we have a fusion layer that takes all data sources and makes sense out of it. The analytics layer is running on the data that was structured in a certain way. Customers can make sense out of it and get the real insights that they need. Is this deployed in the cloud, or can this be deployed in a private data center that those customers have? We offer flexible deployments. Actually, today, given that most of our customers are security agencies, they prefer to host their data given the sensitivity on-prem. I do believe that over time, the cloud vendors will provide cloud space that is secured enough for governments to feel comfortable with and to move. For now, it's on-prem. The technology itself is cloud-ready. If the customer has a private cloud in his premises, we can deploy it on private cloud. If it's standard hardware, you can deploy it on standard hardware. Public cloud will be relevant, secure public cloud. The platform is ready for that as well. Got it. How much of the solution that you provide to customers is, how shall I call it, a cookie cutter? Every customer gets the same thing versus there's a need for a lot of customization. Like, for example, a weapon database, right, that you mentioned. I'm sure for every country, it just looks very different, that database, no matter what, right? I'm trying to think, how easy is it to implement this quickly within one customer to another? It requires a certain amount of services and integration and customization to make this useful? Yes, the technology is productized. The layer of the data and the data connections is very flexible and configurable. The vast majority of the solution is generic and productized. If you look at our revenue streams, you'll see software services and professional services. Actually, the professional services, which is deployment, training, is about 15%. You can imagine that most of it is productized and not customized. We do have some customizations for key customers when it's required in order to keep them with us for many years. They are with us for many years and continue to buy from us. The repeat business is very strong. Generally speaking, it's productized, and the gross margin is also reflecting it. The gross margin is over 70%. It's not a customized one-time project for each customer. It's a product. Got it. Can you talk about the go-to-market? One of the questions I'm getting here is around go-to-market motion. Can you explain the go-to-market motion and how long sales cycles are in this market? Yes, so first of all, we do have the flexibility to allow customers to start with point solutions, which means a small solution by capacity that actually addresses one, two use cases and starts with a deal that is about a few hundreds of dollars, OK? It goes up to tens of millions of dollars. If you look at our earnings calls, I shared very large deals, but also very small deals that are coming from new logos that start small and expand over time. The deal size varies between a few hundreds of dollars to tens of millions of dollars. The sales cycle is between two quarters to 6-8 quarters when it comes to a very large solution that involves lots of data. The customer needs to prepare himself for that. Usually, the customer needs to prepare the IT environment and also to get the data available for us, and then we can deploy. It takes time in the sales process to define everything to better understand what they need exactly. Then the deal comes. It's between two quarters to six to eight quarters. That's the more or less sales cycle timeline. When I think about the space that you're kind of stepping into, how often are you walking into a situation where your customers have tried to make something by themselves, just couldn't get that going, versus there's a complete lack of knowledge, don't know how to do it, we just need someone to please help and stand it up for us because we don't know where to start? Yes, so actually, some customers, advanced customers, had their own R&D centers or used their own IT capabilities in order to try and build solutions that help them in some way. It doesn't work anymore. The reason it doesn't work anymore is because the technology is running so fast. The data is growing so fast. It's very difficult for one customer to invest in order to keep pace with the technology and with the data that are evolving very fast. They need to come to companies like us and get the technology that is proven with hundreds of customers, that is ready, that has all the governance and security, that has the entire investigation layer. It's very difficult to, OK, if it's NSA, they can do it on their own, I assume, OK? If it's usual customer, global customers that are coming from standard countries, national security, national agency, it's very difficult for them to do what we do. We have the luxury to talk to many customers, to build a very strong roadmap, to predict what will be the changes in the environment, in the technology environment, in the data environment, and to be ready ahead of time. For one customer to do it for himself, unless he is very huge with very deep pockets, it's also almost impossible. For that reason, we see customers with homegrown solutions moving to us. Interesting. I'm just wondering if there's, have you thought about more, how shall I call it, commercial applicability of your technology with commercial customers and not necessarily national defense agencies, state nations, and police-like type of agencies? Is there a commercial angle to this as well? The product itself was initially designed to be IT-ready, cloud-ready, also for enterprises. Technically speaking, we designed it in a flexible manner in order for us to be able to support other segments outside of the security market over time. For now, today, our focus is security agencies, as I mentioned before, globally. Having said that, we do explore other use cases outside of the security market that our product can fit. We are checking what are the potential markets, whether they have the budgets to pay for this kind of technology, and whether we have the access of domain expertise, either inside or maybe outside, in order to address it. There is no concrete plan for now, but the exploration is in process. Got it. OK, TBD on that. David, can you talk about the business model? When you deploy with a customer, you charge them by what? Our offering itself is mainly perpetual. The reason that it's perpetual is because in most of the cases, we're talking about an on-prem solution, given the sensitivity of the solution and the security organization needs. Although we do see a trend that more and more agencies are considering to move to the cloud and move also this type of solution, currently, most of the deployments are on-prem, and the model is a perpetual model. We do have an offering in subscription, in which we also incentivize our sales organization. This type of transition may take place, but it will take a long time. The pace, we don't know what will be the pace, but it may take a long period. The offering itself, the way that we generate revenue, we have three types or three streams of revenue. We have our software revenue, which is mainly software and some templates. Usually, it's recognized based on delivery, acceptance, or percentage of completion. The other revenue is our software services, which is the vast majority support contract, which recognize over time. We have a small portion of less than 15% of professional services and others, which recognize upon the service we provide. Got it. Is the professional component set by the amount of data that gets processed by your system? What decides if I pay $1 million or $10 million to you? Pricing mainly depends on data capacity and functionality. This is the major impact on the pricing. You can see that the customer may do expansion of a few million dollars. It could be even above $10 million. The size of the deals may be a few hundreds of thousands of dollars to even a few millions of dollars, depending on the deployment itself, what portion of the platform they hold, and how much they would like to process within our solution. Got it. Elad, if you and I talk, say, three years down the road, in what way would you think the company would look differently than it does today? First of all, we have an initiative to expand presence in the U.S. Historically, as part of Verint, we didn't focus on the U.S. We've decided as a standalone company to focus on the U.S. We hired our own team in the U.S. We're working on acquiring partners' network in the U.S. We already started installing local law enforcement agencies. We want to move forward also with federal agencies. We already engage with some of them. The U.S. is one vector. Another vector is technology-wise to maintain leadership in a way that we are able to uncover more hidden insights out of the same data sets of our customers. This will give us the opportunity to come up with a very strong upgrade path for the entire customer base. This is the second one, so product and technology. The last one is we are in exploration of other market segments. I don't know to predict how long it will take, but it might be that in this time frame, we'll be able to serve more segments that are not necessarily the ones that we serve today. In the U.S. market, maintain market leadership and acquire more new customers globally, and maybe other segments that we can serve. Got it. Makes sense. Maybe we'll wrap up with the competitive front. What's out there, really? I mean, I understand that some try to do it themselves and fail, but are there other solutions available from similar competitors out there in the world? How does that look like? Given that we are global and we address many different use cases, we also support many different departments within the units, which is the operational units, the special forces, the intelligence headquarters. We do see in certain territories and in certain use cases different competitors. We can see global competitors like Rohde & Schwarz, like Elbit from time to time, like L3Harris, like Octasic in certain cases, like JSI. The market is very fragmented because there are different use cases and there are different geographies. Given that we do global operations and many use cases, it is changing from one territory to the other. As you mentioned before, homegrown solution is also a kind of competition that we are converting customers from in-house solutions to solutions of ours. Fantastic. That's great. Guys, I appreciate it. It's super interesting. I really appreciate your time. Thanks for presenting the company here today. Good luck. I'm looking forward to working with you and connecting with you in the future. Thank you. Thank you. Thanks, guys. Have a good one. Thank you.