SentinelOne, which develops AI-powered software for cybersecurity, launched its IPO today. There was certainly substantial demand from investors. The initial price range was $26-to-$29 but this was lifted to $31-to-$32. The offering was then priced at $35 and the amount raised came to about $1.2 billion. Tiger Global, Insight Venture Partners, Third Point Ventures, and Sequoia Capital also participated in a $50 million concurrent private placement for the stock.
The CEO and cofounder of SentinelOne is Tomer Weingarten. Before launching the company in 2013, he had helped to create several other tech startups. His background was mostly in analytics.
He would team up with Almog Cohen, who was a security expert at Check Point Software Technologies. Cohen and Weingarten were actually childhood friends and went to the same college.
As for SentinelOne, the vision was to build a next-generation cybersecurity platform that leveraged AI. But interestingly enough, the timing was too early. “In the first few years, it was an absolute battle to get the trust of customers,” said Weingarten.
Yet things started to change as the cybersecurity threats became more frequent and dangerous. The reality was that traditional systems—such as those based on human-powered signatures–were failing even more. It was “akin to bringing a knife to a gunfight,” according to the SentinelOne S-1 filing.
While building the AI system, Weingarten learned some important lessons. First of all, success would not involve building better algorithms. The reason? They tend to be similar, standardized and open source.
Next, success with AI would not be about having huge amounts of data either. The focus instead should be on having the right data that produces signals that can be modelled. “We look at it as a contextual narrative, such as like telling a story,” said Weingarten. “We even received a patent on this approach.”
Building the platform has required using the latest in data systems to process petabytes of data in real-time. Every second counts when it comes to fending off cyberattacks. “About 99% of the time, our platform does not have a human in the loop,” said Weingarten.
The SentinelOne system is flexible as well. For example, it can be deployed on environments like Windows, macOS, Linux, and Kubernetes.
The Growth Engine
Consider that none of the company’s customers were impacted by the SolarWinds Sunburst cyberattack. This was definitely a major validation of the AI approach.
And yes, the growth has been standout for SentinelOne. During the latest quarter, revenues soared by 108% to $37.4 million. There are currently more than 4,700 customers and a majority of them are large enterprises.
Some of the other metrics include:
- The dollar-based gross retention rate: 97%.
- The dollar-based net retention rate: 124%.
- Annual recurring revenue: $164 million.
- Customer satisfaction: 97%.
Note that the SMB (small-and-medium size business) category has shown even more growth. A key has been the leveraging of MSPs (Managed Service Providers).
The IPO
This was the first public offering for Weingarten. “It was a lot of hard work,” he said. “But we thought that an IPO was critical. I think it is about becoming a more mature company.”
Being public also helps with the trust of customers. After all, there are stringent disclosure and audit requirements. In fact, some larger enterprise companies will not even purchase cybersecurity software from private companies.
Now it’s true that SentinelOne faces intense competition. Just some of the key rivals include CrowdStrike and Palo Alto Networks.
Yet the market is massive. Based on the analysis from IDC, the spending is expected to reach $40.2 billion by 2024, which represents a compound annual growth rate of nearly 12%.
Tom (@ttaulli) is an advisor/board member to startups and the author of Artificial Intelligence Basics: A Non-Technical Introduction, The Robotic Process Automation Handbook: A Guide to Implementing RPA Systems and Implementing AI Systems: Transform Your Business in 6 Steps. He also has developed various online courses, such as for the COBOL and Python programming languages.
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