AI agents are marching around the world, with a startup called Crogl making their debut in their contributions to the field on Thursday. An autonomous assistant that helps cybersecurity researchers analyze daily network alerts to find and correct security incidents.
The assistant, described by Crogl CEO and co-founder Monzy Merza as the researcher’s “Iron Man Suit,” is already deployed in many large corporations and organizations. In addition to launching products from today’s private beta, the startup also said it has raised $30 million in funding.
The funding comes in two tranches: a $25 million Series A led by Menlo Ventures and a $5 million seed led by Tola Capital. Based in Albuquerque, New Mexico, Krog will continue to build its products and customer base using its capital.
Today’s enterprises have access to hundreds of security tools, including security tools that help you analyze and fix alerts from security software. Sometimes it feels like there are as many tools as security alerts. But Krogl is a little different, in part, but in part, who created the idea in the first place.
Melza has a long and interesting background in the security industry. After college, he worked in security at the US government’s Sandia Atomic Research Lab, and later joined Splunk, where he built and led the security research business. He then moved to Databricks to do the same.
When Merza began thinking about doing his thing after Databricks, he didn’t immediately launch a startup.
Instead, he chose to go back to the industry. He worked at HSBC and worked among end users and understood the issues from their perspective. Putting all of that under his belt, he tapped former Sprank colleague David Dorsey (now Crogle’s CTO) and they got to work.
That was two years ago. Last year was spent building a customer base via private beta.
As Melza explained to me, “Crogle” is a Porte Mantoo of three words and ideas. “G” comes from Gnosis. This means knowledge and consciousness. And the final “L” stands for logic. In a way, the name encapsulates what a startup is trying to do.
As Melza sees, the heart of the problem is that security analysts in the operations team can usually resolve approximately two dozen security alerts a day. But they may see up to 4,500 people in that same period.
So far, market tools believe that alerts and human cans cannot be evaluated.
He and Dorsey observed that when the team sees many alerts, security leaders usually prefer it. The principles of reinforcement learning mean that they experience each alert of triage, experience and understand more.
Of course, that is not acceptable. The crunch has driven many security products up until now. “The security industry has been telling people to reduce the number of alerts,” Melza said. “So what happens if you can create this scenario where all your alerts are actually multipliers and your security team is “anti-collapsing” with the ability to analyze what you actually need? ”
That’s effectively what Krogl is trying to do. Relying on the idea of big data and the oversized parameters that drive large language models, startups have built what Melza describes as the “knowledge engine” for running the platform (think of it as a “large security model” here).
The platform not only flags suspicious activity, but also learns in detail what signals constitute suspicious activity. Critically, researchers can also use natural language when necessary to elicit and understand all alerts.
Over time, it is possible that the clogs will take on more than just an alert. Repair is one of the obvious areas that it can tackle, says Tim Tully, Menlo’s partner who led the investment.
He is well versed in the founding team of Talley’s Crogl, including the founding of Brad Lovering, who was Splunk’s chief architect.
“I knew what they could make. I know they know the space well. The hook in the mouth is the only team in itself. I think it’s pretty rare on the venture side that you have that kind of experience,” Tully said.
He added that he missed the opportunity to invest in the company during the seed stage, and then continued to listen to the product and think, “All is enough.” He flew to Albuquerque and saw his own demonstration, which sealed the deal.
“I felt this product was like a mapping of Monzy’s security brain in terms of how the problem was resolved.”