 Hello everyone, welcome to special Cube Conversation exclusive content here in Palo Alto Studios. I'm John Furrier, the co-founder of SiliconANGLE Media and co-host of the Cube. We have exclusive news with Vectra Networks announcing new funding, new R&D facility. I'm here with the president and CEO, Hitesh Seth, who's the president and CEO. Welcome to the Cube Conversation. Congratulations. Thank you, John. Let's be here. So you guys have some big news, okay? Vectra Networks, you guys doing some pretty cool stuff with AI and cyber, but it's not just software. It's really kind of changing the game with IT operations, the entire cloud movement, DevOps, automations, all impacting the enterprise and other companies. Yes. Before we dig into some of the exclusive news you guys have, take a minute to talk about what is Vectra? What is Vectra Networks? Maybe it'd be useful to give you context of the way we see the security industry evolving, right? And if you think about the last 20 years, and if you were to speak to the security person in an enterprise, their primary concern would be around access management. Who gets in, who gets out, right? The firewall industry was born to solve this problem. And in many ways it's been a gift that's kept on giving. You've got companies with multi-billion dollar valuations, Palo Alto, Checkpoint, Fortnet, you know, a piece of Cisco, et cetera, right? There's roughly about $40 billion of the market cap sitting in this industry today. Now, if you go back to the same enterprise today and you look at the next five, 10 years and you ask them what is the number one issue that you care about, right? It's no longer who is getting in and out from an access policies standpoint. It's all about threat management and mitigation. So the threat signal, the threat signal is now the most important commodity inside the enterprise. And the pervasive challenge for the customer, the enterprise customer is how do I get my hands on this threat signal in the most efficient way possible? And we at Vectra are all about automating and helping our customers hunt for advanced cyber attacks using artificial intelligence. Where did you get the idea of AI? I mean, obviously AI is about automation. I've always said in the queue, well, AI is a bunch of BS because real true AI is there. But again, AI is really kind of grown out of machine learning, automating. And so there's kind of a loose definition, but certainly it's very sexy right now. People love AI, I mean AI is awesome. But as a practical matter, it seems to be very important for good things, also for the enterprise. Where did you get the idea for using AI for cyber? Well, you know, I would go back to, in my journey and intersection with the notion of using AI for cyber security. Back in about say 2010, there are major cyber events reported in the press. And at that time, I was in the networking sector. And in the networking sector, we all looked at this and said, you know, we can do something about this. And being good networking companies, we thought we would build chips, they would do DPI and do packet inspection. And it was to be blunt, old school thinking, okay? Fast forward to 2012, and I was sitting with Vinod Kosla at Kosla Ventures, and we were talking about the notion of security and how can you transform security dramatically? And this is when we started talking about using artificial intelligence. It was very nascent. And frankly, if you went up and down Sand Hill at that time, most of the venture companies would have, and they did because we were raising money at that time. They looked at us and said, you guys are nuts. This is just not going to happen. It's very experimental. It'll take forever to come to pass. But that's usually the best time to go and build a new business and take a risk, right? And we said, you know what? AI has matured enough. By the way, at that time, they were also poo-pooing the cloud. Oh, the cloud, Amazon will be nothing. Yeah, yeah, yeah. Exactly, right? So generally a good time. A good time to go and do something revolutionary. But here are the other things to note. Not only had the technology around AI and its applicability had advanced enough, but two other things that happened at the same time. The cost of compute had changed dramatically. The cost of storage had changed dramatically. And ultimately, if AI is going to be efficient, not only has the software got to be good, but the computer's got to be available as well. Storage got to be available as well. These three things were really coming together around the time frame. Well, it's interesting. I want to just dig into that for a second, because knowing what the scene was of the networking at the time, you said old thinking, but the state of the art in the 90s and in 2000s was, hardware got advanced, so you had higher speed capability. So you can do some cool things, like still move the throughput through the network and do some inspection. And you say, de-package, but that's the concept of looking at the data. That's correct. So now, okay, now there might have been narrow view. So now you take it back with AI. You're taking a, is that, am I getting it right? You're taking zooming out and saying, okay. Well, a couple of. You combine that notion of inspection of data with more storage, more compute. But it comes down to also, what data you're looking at, right? When you had wire speed capabilities, you would apply your classic signature-based approaches. So you could deal with known attacks. What is really happening, sort of like 2011, 2012 and onwards, the attack landscape is more so dramatically. It changes so fast that the approach of just dealing with the known was never going to be enough. So how do you deal with the unknown? You need software that can learn. You need software that can adapt on the fly. And this is where machine learning comes into play. You got to assume everyone's a bad actor at that point. You got to assume that everybody has been infiltrated in some way or fashion. Well, the cloud, certainly you guys were on the front end kind of probably thought were crazy way all the VCs you mentioned that. But at the time, I do remember when cloud was kind of like looked at as just nonsense. But if you then go look at what that impact has been, you're on the right side of history, congratulations. How did, what really happened? Where was the sea change for you? You mentioned 2012. Was that because of the overall threat landscape change? Was that because of open source? Was that because of new state-sponsored threats? What was the key flash point? A couple of things, right? We saw at the time that there was a emerging class of threats in the marketplace being sponsored by either state actors. But we also saw that there was significant funding going into creating organized entities that were going to go and hack large enterprises. There were enough- Not state-sponsored directly, state-sponsored kind of, you know- On the side, on the side, yeah. Let's call them for-profit entities, okay? Sounds like equifax to me. Yeah, that's a good point. And we saw that happening. Trend two was there were enough public, on the record, hacks are getting reported, right? Sony would be a really good example at the time. But just as fundamentally, it's not just enough that there's a market, the technology has got to be sufficiently ready to be transformative. And this is the whole point around what we saw with compute and storage and the fact that there was enough advancements in machining itself that it was worth taking a risk and experimenting to see what's going to happen. And in our journey, I can tell you, it took us about 18 months, really, to kind of tune what we were doing because we tried and we failed for about 18 months before we kind of came to an answer that was actually going to gel and work for the customers. And what's interesting is that having a pattern oriented to look for the unknown, because it's, you know, the old days was, hey, here's a bunch of threats, look for them and be prepared and deploy. You got to deal with a completely unknown potentially attack. But also I would say that we've observed the surface areas increased. So you mentioned checkpoint and these firewalls. Those are perimeter-based security rules. So you got a perimeter-less environment. Correct. Every day. And you've got IoT. IoT, so it's a hacker's dream. It's absolutely, you've got to, is the way I like to think about it is you've got an end-by-end permutational issue, right? You've got an infinite possibility. If you're a hacker, you're absolutely right. It's Nirvana. You've got endless opportunities to break into the enterprise today. It's just going to get better. It's absolutely going to get better for them. Well, let's get to the hard news. You guys have an announcement. So you've got new funding. And an R&D facility, in your words, what is the announcement? Share the data. Fantastic, yeah. So we are really excited to announce that we have raised, or we have closed around $36 million, serious defunding. It's being led by Atlantic Bridge. And they're a growth fund and they've got significant European roots. And in addition to Atlantic Bridge, we're bringing on board two new investors, two additional investors. The Ireland Strategic Investment Fund, number one, effectively the sovereign fund of Ireland. And then secondly, initial electronics out of Japan. And this is going to bring our total funding to $123 million today. What we're going to be using this funds for are the following things. One is the classic expansion of sales and marketing. I think we've had very significant success in our business. From 2016 to 2017, our business grew 181% year-in-year. Subscription-based. So all subscription revenue. So we're going to use this new fuel to drive business growth. But just as important, we're going to drive R&D growth significantly. And as part of this new funding, we are opening up a brand new R&D center in Dublin, Ireland. This is our fourth R&D center. We've got one here in San Jose, California. We've got one in Austin, Texas, Cambridge, Massachusetts. And so this is number four. So you're hiring some really smart people. How many engineers do you guys have? So we have, you know, we are about 140 person company, roughly half the company is in R&D. Got you, a lot of engineering going on. And you need it too. So about competitors, Dark Trace is out there, heavily funded company. Yes. They're a competitor. How do you compare against the competition and why do you think you'll be winning? Yeah, I can tell you, you know, statistically, whether it is Dark Trace or, you know, we are running directly into Cisco as well. We win in the large enterprise. We win 90% of the time. And I'll describe to you, it is, and factually correct. And I'll describe to you why is it that we win. So, you know, we look at people like Dark Trace and there are other smaller players in the marketplace as well. And I'll tell you one thing fundamentally true about the competitive landscape and that differentiates us. AI is on everybody's lips nowadays, right? As you pointed out. But what is generally true for most companies doing AI and I think that's true for our competition as well, it tends to be human augmented AI. There's not really AI, right? This is sort of like the Wizard of Oz. You know, there's somebody behind the curtain actually doing the work. And that ultimately does not deliver on the promise of AI and automation to the customer. The one thing that we have been very... They're using AI to cover up essentially manual business models throwing people at it. Other, is that what you're saying? That's correct. They're throwing, you know, effectively it's still a people oriented answer for the customer, right? And if AI is really true, then automation has got to be at the forefront. And if automation is really going to be true, then the user experience of the software has got to be second to none. So I know it's Michael Lynch is on the board of that company, Dark Trace. The autonomy he was indicted or charged with fraud. Correct. To fraud HP for billions of dollars. Correct. So is he involved? Is he a figurehead? How does he relate to me? I mean, I think you should talk to Mike. You should put him in this chair and have this conversation. I would recommend. I don't think he'll come on. Yeah. He'll get grilled big time. But my understanding is that, he has a very heavy hand in the reign of Dark Trace. Dark Trace, I think, if you go to the website, so this is all public data, if you look at the management chain, these are all autonomy people. What that means with respect to how autonomy was run and how Dark Trace has been run, it's for them to speak about. What I can tell you is that when we meet them competitively, we meet other competitors. I mean, if I'm a customer, I would have a lot of fear and certainty and doubt to work with an autonomy led because they had such a head fake with the HP deal and how they handled that software. The software stack wasn't that great either. So, I mean, I'd be concerned about that. You hear that? History may be repeating itself. Do you hear that in your account? History may be repeating itself. Okay, so you want to answer the question. Okay. All right, well, let's get back to Vectra. Some interesting notable things I discovered was you guys have been observing what's been reported in the press with the Olympics. Correct. You have information and insight onto what's going on with the Olympics. Apparently, they were hacked. Obviously, we're in Korea, so it's age or so, assuming there's no DNS that doesn't have certificates that have been hacked or whatever. I mean, what's going on in South Korea with the Olympics? What's the impact? What's the data? Yeah. Well, I mean, I think what is really remarkable is that despite the history of different kinds of attacks, aquifacts, what have you, nation-state events, political elections getting impacted and so forth, once again, a very public event, we've had a massive breach. And they've been able to infiltrate their systems. And the remarkable thing is that they've been- There's proof on this. There's proof on this. This is in the press. So this is nothing, there's no secret data you're on our part, which is this is very much out there in the public arena. They've been sitting in the infrastructure of the Olympics in Korea for months. And the remarkable thing is that why were they able to get in? Well, I can tell you, I'm pretty sure that the approach to security that these people took is no different than the approach to security that most of the enterprises take. The thing that should really concern us all is that they chose to attack, they chose to infiltrate, but they actually paused before really fundamentally damaging the infrastructure. It just, it goes to show you that they were basically demonstrating control. That I can come in, I can do what I want for as long as I want, I can stop when I want. So they were undetected. They were undetected. And they realized that their tactics reflected that. Absolutely. And given the fact that there seems to be a recent trend of going after public events, we have many other such public events coming to bear. How would you guys have helped them? The way we would help them most fundamentally is that, look, here's a fundamental reality. There are, as we discussed just a second ago, there are infinite opportunities to break in into the infrastructure. But once you're in, right? For people like you and I who are networking people, you're an art turf. And the things you can do inside the network are actually very visible. They are very visible, right? So it's like somebody breaking through your door. Once they get in, the footprints are everywhere, right? And if you have the ability to get your hands on those footprints, right? You can actually contain the attack as close to real time as possible before any real damage is done. The network is where the action is, no doubt about it. Yes. So you can actually roll that data up. Correct. And that's where the compute- And this is where you apply machine learning. You can extract the data. You look at the network. You can extract the right data out of it. Apply machine learning or AI. And you can get your hands on the attack well before it does any real damage. And so to your point, if I get this right, if I hear you properly, the compute is much stronger now. Correct. And with software and AI techniques, you can move on this data quickly. Correct, but you've got to have a fundamental mindset shift, which is I'm not in the business of stopping attacks anymore. I should try, but I recognize I will be breached every single time. So then I better have the mechanisms and the means to catch the attack once it's in my environment. And that mindset shift is not pervasive. I am a thousand percent sure at the Olympics that people designing the security infrastructure said, we can stop this stuff. Don't worry about it. Okay, you had that thought differently that would not be in this position today. This is the problem in all society, whether it's a shooting at a school or an Olympic-hacked event, the role of data is super critical. That's the focus. Hitesh, thanks for coming on and sharing the exclusive news. It's a key with exclusive coverage of the breaking news or the new round of funding for Vectra Networks. I'm John Furrier, thanks for watching. Thank you, John.