theCUBEd Awards | Deep Instinct Data Security X by Deep Instinct (Top AI Innovation for Security)

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Carl Froggett

Incubator Advisor

Loughborough University

Lane Bess

Chairperson of the Board

Blaize Holdings Inc.

play_circle_outline Deep Instinct's prevention-first approach to cybersecurity focusing on AI and deep learning science.

play_circle_outline DSX Product: Solving Legacy System Issues, Reducing SOC Fatigue, and Preventing Zero-Day Threats for Measurable Improvements

play_circle_outline DSX praised for its predictive prevention capabilities and impact on data security.

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Deep Instinct Data Security X by Deep Instinct (Top AI Innovation for Security)

Carl Froggett

Incubator Advisor Loughborough University

Lane Bess

Chairperson of the Board Blaize Holdings Inc.

Join Lane Bess, CEO, and Carl Froggett, CIO and Chief Information Security Officer at Deep Instinct, as they discuss their pioneering work in Artificial Intelligence innovation for cybersecurity in this special segment of theCUBE’s Tech Innovation CUBEd Awards. With theCUBE Research analysts guiding the conversation, Bess and Froggett share insights into Deep Instinct’s prevention-first approach, emphasizing the deployment of Deep Learning Science and Neural Network Science to preemptively combat potential threats before they materialize.

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What technology did the speaker focus on in their cybersecurity journey, specifically aiming to prevent threats before they happen? add

What impact does DSX have on advancing cyber security measures, particularly in terms of reducing operational load and total cost of ownership? add

What are some key insights Lane has gathered from his conversations with CEOs and CIOs regarding data security and the importance of prevention in preventing threats? add

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Deep Instinct Data Security X by Deep Instinct (Top AI Innovation for Security)

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Rebecca Knight

>> Hello everyone and welcome to theCUBE's Tech Innovation CUBEd Awards. I'm your host, Rebecca Knight, where we are celebrating the winners of our inaugural program that showcases the incredible creativity and innovation that's taking place across the technology landscape. Today we are joined by Lane Bess, the CEO of Deep Instinct, and Carl Froggett, the CIO CISO of Deep Instinct. They have won for the top AI innovation for security. Lane and Carl, welcome and congrats.

>> Thank you very much. It's an honor actually.

Rebecca Knight

>> Lane, I want to start with you tell our viewers a little bit about Deep Instinct, the company and its prevention first approach to cybersecurity.

>> Sure. Happy to do that. As many know, I've been in cybersecurity for 25 years, and the challenge I always faced with even my last few companies was the ability to actually prevent threats before they actually happen. A lot of technology layers of defense and great technology, but the real challenge that we had to face was how do we get the AI science, in particular the tech is called Deep Learning Science and Neural Network Science, to really put ourselves in a position of prevention first. And that's really what we focused on. That's what brought me to the company after having done so many other cyber journeys before. The goal then was to figure out how we took this core technology and applied it towards many solutions that were needed for customers. The recognition you gave us recently around our DSX platform was ultimately where we see the market really focusing, and that is on the very big threat of data breach and data security threats.

Rebecca Knight

>> Carl, the winner here, as Lane just said, is Deep Instincts' Data Security X DSX product. Why don't you talk a little bit, before we get into the nuts and bolts of DSX, about the problem that you are setting out to solve in terms of how legacy systems dealt with threats and malware, or perhaps didn't deal with them.

>> I think the threat landscape continues to evolve. Having been in cyber security for 30 years, there's constant evolution, especially from the bad actors. As Lane pointed out and the award, thank you so much, our unique value proposition is built off deep learning. And with DSX, we're able to take that core differentiator, that unique value we have, and apply it into different areas of an enterprise's security stack, be it storage, be it cloud, be it applications, obviously end point. And that flexibility of being able to bring that deep learning core and that prevention first approach makes it very unique in the market.

Rebecca Knight

>> Lane, as cyber attacks become more sophisticated and malicious, and this is obviously not your first rodeo, you've been in this industry for a long time, the demand for solutions that protect businesses is at an all-time high. Who is the target audience for DSX?

>> Well, the truth is, it's all enterprises and also governments. Everybody needs the prevention capability. The biggest challenge that a lot of the enterprises and governments are facing is that their team's abilities to react to attacks is limited, number one, from the sophistication and acceleration of attacks, and AI is only going to bring greater attacks. Things such as DeepSeek, we test all the time, attacks being created with AI technology, and we can defend entirely 100% against them. The big challenge that most companies are facing is that their SOC, their analysts, the people who have to react to this don't have the tool sets to react to the accelerated pace of this. And so we not only through the prevention-first approach, address this resource challenge, but we also impact and protect against the fact that one breach is all it takes to either cost a company dearly or cause a business continuity interruption.

Rebecca Knight

>> Carl, if you want to get into more of the nuts and bolts, how does DSX advance cyber security measures?

>> From the nuts and bolts perspective, I deployed Deep Instinct at my previous company. So number one, it really replaces some of the legacy solutions that are out there. One thing that Lane mentioned was SOC fatigue and just the overwhelming number of threats and alerts that a SOC has to deal with. Deep learning is very accurate. So just naturally we reduce the load, number one. But as companies have adopted multiple of our products, they usually start with one because they want to address a risk. But we have companies with two or three of our different products in their environment now, and what they see is that overall operational load come down, number one. They see a total cost of ownership come down, because we're displacing legacy systems, be it signature, be it machine learning. And one of our core things is not just a prevention-first approach, but making it easy for enterprises to plug their gaps in their risk posture. So we have a very flexible kind of deployment model that plays well, especially into some of the more modern shift-left agile development as we move to cloud and software stacks. Not a problem for us. You can take the same fundamental deep learning core that we have and apply it in many different use cases.

Rebecca Knight

>> I want to ask you both about the impact that DSX is having. Carl, I want to start with you. What are some of the measurable security improvements that your customers have achieved by adopting DSX? I know you said you already drank the Kool-Aid before going to work for Deep Instinct.

>> Yeah, and one of the reasons I joined Deep Instinct, not just Lane here I've known for many years, but was the uniqueness and the disruption of deep learning versus machine learning and other AI. To answer your question bluntly, everything is becoming a zero-day. So historically we have known somebody gets attacked, we create a signature or a hash or machine learning learns from it. That's nice when you have that time. But as we've demonstrated time and time again using open source, readily available LLMs, you can easily generate unique malware on the fly. Now the intent there from the bad actor is it's really cheap and easy to do now. You don't need expertise. You don't need to be really knowledgeable because the LLMs are doing it for you. And obviously we're moving from an instruction-based expertise to an intent-based, I need a malware that's going to breach this so I can steal the data or I can hold a company for ransom. And that capability is a seismic shift in the threat landscape that we've never seen before. And deep learning is the only AI that can prevent a zero-day without a detect and response that I've deployed. I deployed that for the last 20 years. So as the threat landscape has changed, we as the good actors, we as the good guys need to change with it, and that prevention of zero-day threats is the value proposition. And obviously we prevent the things that are known that everybody else prevents as well, but that is our big value proposition.

Rebecca Knight

>> Lane, what about the feedback that you're hearing? The company has grown tremendously and our judges note that customers praise Deep DSX for its predictive prevention capabilities. What are you hearing when you go out and talk to customers?

>> I spend a lot of time with CEOs and CIOs, and there's now becoming a board level mandate to get out ahead and prevent threats. I actually make the call to action. For many of the people watching this today, I would suggest that you really have to put aside your fatigue. A lot of CISOs have fatigue. They've spent a lot of money. Quite frankly, they would like to go for a platformization approach where they could do a one-stop shop, but that isn't sufficient. While many of the platform and various solution sets they can get are helpful, you have to step it up to the next level. And that's really where we come into play. I encourage the board level mandate, the CISOs, CIOs to really step up and take on this extra step of prevention. When it comes to data security, let's face it, the biggest breaches and the biggest cost to companies are in data. You see a lot of companies, even companies like Rubrik in the backup and restore starting to focus on the integrity of data. So much risk exists in data and applications, the transfer files, that has to date really not been the focus of attention. That's what DSX does.

Rebecca Knight

>> Innovation is central to these awards. Carl, I wonder if you could tell our viewers about a specific example of how you and your team approached a challenge in an innovative way and the impact that it had.

>> From that perspective, as we work in other customers, for example, or prospective customers, we'll go in and we will leveraging our core, again, on the DSX side. We go in, we help the prospective customer and existing customers re-architect. There are some things that are very innovative that we're able to do that I would argue no one else is able to do. So for example, we have three or four customers right now. We operate in an air-gapped environment. So what that means is these really sensitive kind of ministry of defense and other environments where the existing tech stack cannot work. Why? Because it requires connectivity to do that detect and respond that we talk about. There's a lag, but they require connectivity. So one of the unique things that we can provide to those environments is that we operate in an air-gapped environment, number one. And number two, our core, this deep learning core that I talk about, we only update that once or twice a year because it's so resilient in the new and unknown. I know for the listeners out there, I was skeptical too when I first came across Deep Instinct six or seven years ago. But that is one of the fundamental differences between what we have in the industry and the disruptive and innovative nature that deep learning brings to the table. We are able to address data security and zero-day issues that literally other technologies cannot address today, and then we backdrop that. Because we don't have to be connected, we also bring some nice business benefits, one of them been privacy. We never see customers' data. We don't need to see it. We never see their files. You don't have to send us things for us to do analytics. Everything is hosted and contained in the customer's premise. So when you look at regulatory and GDPR and other data privacy regulations that are only getting more strict, our innovations enable us to really bring value to those customers.

Rebecca Knight

>> Technology is always evolving. Lane, as you said, the bad guys are only getting more creative and more wily. Meanwhile, you're also combating SOC fatigue. A lot of organizations are sort of feeling, maybe not demoralized, but certainly frustrated that this is a huge problem and could cause a lot of damage to their companies. How do you, as the leader, make sure that you are staying ahead of these trends, while ensuring that you're also creating a meaningful solution? How do you think about that and how do you approach that, Lane?

>> The reality is that Deep Instinct has been around for eight years, and the technology that we developed was way ahead of the generative AI craze we've seen. In fact, I feel very good about the fact that this company, made up of some of the best threat researchers and cyber people out of our Tel Aviv organization, developed for the last eight years the only cyber capability with AI of this nature. And so when all of the euphoria and excitement came around when ChatGPT, OpenAI over the last few years, this company was already well ahead in terms of development of this technology. We had the core team being able to develop this for the last eight years. And now having that experience, we're well ahead of anybody else in terms of being able to further this, and more importantly, combat the new threats that we're seeing.

Rebecca Knight

>> Lane and Carl, congratulations again, and thank you both for coming on the show.

>> Thank you.

>> Thank you.

Rebecca Knight

>> And thank you for tuning into this special segment on theCUBE's Tech Innovation CUBEd Awards. I'm Rebecca Knight. Stay tuned for more.