Burlington-based Edgewise, which automates security systems for companies, just raised $11 million to close out its Series A funding.
The round was led by .406 Ventures and Accomplice, and it brings the startup's total funding to $18 million after a seed round two years ago.
The company is placing all its bets on its machine learning software, which automates a security system called "microsegmentation." Essentially, Edgewise creates a zero-trust environment in which all communications are treated as hostile until they are authenticated. To achieve zero trust, security teams have to microsegment their networks—thus reducing access points—and create policies for each application, host and other digital assets.
Microsegmentation, says CEO Peter Smith, is more secure than traditional security systems.
"You've got a bunch of systems that are in a big open network, which is what is typical in corporate America today, and when the attacker gets in, they jump between boxes by using these unnecessary access points to compromise vulnerable systems," Smith said. "You've got to shrink those networks. The attackers are just walking through as if you have no protections."
Microsegmentation has soared in popularity in the cybersecurity community in recent years. Alan Cohen, chief commercial officer at California-based cloud computing security company Illumio, wrote in a March report that it was "fast becoming a foundational layer of the security architecture for today’s data center and cloud computing environments." Last year, global research and advisory firm Gartner listed microsegmentation in its top 10 security projects for chief information security officers.
But microsegmentation can be complicated to set up, Smith notes, requiring months or years of intensive overhead. The startup's automation shaves that off.
"It gets machine learning recommendations based on the analysis we've performed and automatically builds the segments," Smith said. "It builds the policies to allow access between them. Then, once it's done, it shows us the results of the process. It can be as quick as 10 seconds. It can be as long as around a minute and a half."
Edgewise has spent about three years building its machine learning technology. It has had three patents approved, with eight more pending. Since its seed funding round in 2017, the startup has built out its management team, continued development on its enterprise software, and won over key clients, including cloud communications provider Vonage and law firm Goulston & Storrs.
The company is currently hiring for a senior/principal software engineer and a business development representative.
For Smith, the goal is to make cybersecurity simple and accessible—and prevent future attacks like 2017's Equifax data breach and the Quest Diagnostics breach that was revealed just last week.
"We can literally land a rocket on a floating barge in the middle of the Pacific Ocean," Smith said. "We can we can drive door to door without touching a steering wheel, and we can search, on Google, 30 trillion pages instantly. It is baffling to me how cyber security can be as complicated as it is today when we have the technology to make it simple."
