A.I. is certainly having a moment in 2023—but there are plenty of companies that have been working on the technology for nearly a decade.
Tomer Weingarten, who founded and now runs cybersecurity giant SentinelOne, developed seminal machine learning technology that’s able to survey devices and find security breaches. The Mountain View, Calif.-based company was founded in 2013 along with Almog Cohen and Ehud Shamir.
“Many people didn’t completely understand what we’re doing when we started,” explained Weingarten. “My background was in engineering and machine learning, you know I always loved playing with statistical analysis,” he added.
While VCs and founders explain that the conventional mark of success for many cybersecurity startups is to be acquired, Weingarten and his team decided to stay private even though they received about 20 acquisition prospects over the years, according to Weingarten. In June 2021, the company went public in the highest-valued IPO ever for a cybersecurity company at a $10 billion market cap on its first day of trading. Since the company has gone public (NYSE:S), shares are down 57%. Yet the stock has seen significant gains in the past year as it climbed 31% in 2023 as of today.
SentinelOne has acquired two cyber startups—Scalyr for $155 million in February 2021 and Attivo Network last summer for $617 million. The company also launched a $100 million venture fund, S Ventures, in September 2022. Yet Weingarten acknowledged that beyond the market environment, the pace of A.I. innovation has actually contributed to a recent pause in the company’s M&A activity because they’ve realized they can do a lot more in-house.
I spoke to Weingarten about how cyberattackers and cybersecurity companies are leveraging A.I. and how A.I. has changed the M&A landscape in cybersecurity.
Termsheet: How does your company leverage A.I.? What exactly does the technology do in layman’s terms?
Weingarten: We started the company about 10 years ago because we were trying to revolutionize how people think about detecting all these malicious activities in a given network, whether it’s the machines, the users, or the data itself. We built a machine learning-driven platform that first and foremost monitors everything. So basically, think about a wide range of telemetry that is beaming from all of these devices from all of our activities. Everything that we do is logged in one system or the other. All of that data and activity is then cross-correlated in one platform that applies A.I. to highlight all these small anomalies that happen by looking at the aggregate of all of these activities.
Our system finds all these anomalies. Now, the system is accurate and often autonomous enough to actually take action in real-time to automatically remediate some of these nefarious actions that can happen in the enterprise. Thus, we block the attackers, no matter where they come from and what the vector of attack is.
Obviously, right now A.I. has a ton of buzz—it’s what everyone is talking about. But 10 years ago, how did you see a market fit for this technology that you were working on as an engineer?
Yes, many people didn’t completely understand what we were doing when we started. 10 years ago, the cybersecurity industry was just heavily leaning on the concept of signatures, which is if you see something is bad, you try and stop it. That was pretty much the state of the art. Our team and I came from an offensive cybersecurity background, so we knew how attackers are working and how they’re deceiving all of these defenses and we realized that if we can leverage the power of machine learning, it was and still is a very big market. From there we grew the platform to secure not only devices but also cloud workloads and users and identities and pretty much everything that touches your network.
VCs have mentioned to me before that for many cyber startups, the mark of success is to be acquired by a larger firm and that is an awesome end goal for a lot of companies. How did you decide to stay private and eventually IPO?
When I started a company, I didn’t have any outcome in mind. I was just focusing on building the most disruptive technology that we could, and we focused on that for the first couple of years. I think we got about close to 20 different M&A offers over the years, so we had the opportunity to go toward that coveted exit that you described. But we felt like there was so much we could do as a standalone company. There was so much momentum in the business and such great reception to what we do.
We were also building a special culture in the company and we realized that might be something that got lost if you got consumed by one of these global cybersecurity companies. When the opportunity to IPO presented itself, we were one of the fastest-growing companies on the public markets.
Do you think other cyber founders see your success, and the success of other startups like Wiz, for example, and will choose to stay private for longer and eventually IPO? Especially as M&A activity has declined in this market.
The biggest factor is the size of the market that you’re addressing and how robust your platform solution and vision is. Cybersecurity has a lot of “niche features” type of companies. You look at these companies that are doing something incredibly innovative, but something that’s very narrow. And you always wonder, how big of a company can that actually be? So some of these capabilities are just better suited as a part of a wider platform. I think if you truly have a line of sight to building a foundational platform for the enterprise, then that could be a multibillion-dollar standalone IPO. I think for many other use cases, it’s really hard to imagine how you get to a billion-dollar scaling revenue in a relatively short amount of time, with high growth and everything that comes with it.
Now you’re on the other side of those M&A offers and recently started a venture fund, S Ventures. How did you decide to go into venture?
When we started, the idea was always to grow through acquisition. This macroeconomic environment obviously doesn’t allow you to be as aggressive as you want to be. We started S Ventures pretty much as we went public, it was always part of that expansion philosophy where you realize that there are some companies you might not want to acquire, but they might develop interesting technology that you want to help propel and you want to help them scale. Further down the line, maybe we acquire some of these companies that we invest in during the early stages.
You mentioned that the market environment has been stopping you from pursuing acquisitions at the moment. When do you think you’ll start looking to acquire next and what other factors are you thinking about in this market?
For us, we still have about a billion plus dollars in our cash balances that we would love to put to work, but the market is incredibly challenging. I do hope that at some point, maybe toward the end of next year, you could do some more aspirational M&A.
The flip side of it is that you’re seeing just massive disruption with A.I. right now for every technology out there. In 12 months from today, I think you’re going to see a very different landscape. So I think it’s actually prudent to wait and see how the dust settles and then figure out your steps forward.
Do you think the pace of A.I. innovation is actually contributing to your company’s pause in M&A because you’re waiting to see how technology evolves and how things play out with some of these startups?
Part of it is wanting to see a little bit more structure and just see how things are going.
The other reason is that we’re realizing that we can do a whole lot more [in-house]. We have had machine learning and A.I. proficiency for the past 10 years. So it’s not a foreign concept for us. There were certain places where we thought we might want to acquire in the next couple of years. Now we’re looking back, and we’re saying, you know what, we actually do that.
See you tomorrow,
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