Ask most AI SOC vendors what their agent does, and you'll hear some version of "faster investigations, fewer alerts." Ask Monzy Merza, and he'll walk you through a blast radius map instead — because for Crogl's customers, the real problem was never speed alone. It was that patching a vulnerability and breaking production have historically been two different teams' problems, discovered too late and too far apart.
"Somebody says go patch SharePoint, and they say, well, in order to patch it, you're now changing it from TLS 1.2 to TLS 1.3. Well, that's going to break all your downstream applications," Merza said. "The patch is fixed, but the operations is dead."
Closing a three-day window that used to take weeks
Merza's customers, mostly in critical infrastructure and regulated industries, operate under a hard constraint: CISA's Known Exploited Vulnerabilities directive gives federal agencies and, by extension, the vendors and contractors that serve them, a three-day window to remediate certain vulnerabilities. Not three business days. Three days, period. Historically, meeting that meant a security team ran a scan, handed a list to IT, and hoped for the best. "The game has completely changed," Merza said.
Crogl's answer is what the company calls a blast radius assessment: when a CVE surfaces, the platform maps every affected application, identity, service account, and downstream dependency before anyone touches a patch. Instead of a security team throwing a vulnerability list over the fence, they hand over a prioritized, evidence-backed plan that shows exactly what breaks if a fix goes in, and what's actually at risk if it doesn't. "Now the security team is not just throwing something over the fence," Merza said. "They're giving very concrete, actionable information."
Reasoning models wander. That's why there's a deterministic layer underneath.
The architecture Merza describes is deliberately not just an LLM with tool access. Crogl combines three components: a reasoning layer built on large language models (the platform is model-agnostic), a deterministic symbolic layer and knowledge graph that maps a customer's entire data estate without requiring data normalization, and a governance harness that orchestrates the two and enforces consistency. "We all know models wander, the results wander, they're not always deterministic," Merza said. "So we need models' reasoning, but we combine it with a deterministic system."
That knowledge graph is also what lets Crogl skip a step most competing platforms require. Customers don't need to normalize or transform their data before the agent can use it, which Merza says removes a genuine deployment barrier for organizations running multiple SIEMs and data lakes.
Secure means sovereign, and sovereign was too big a word to use
Crogl isn't a SaaS product. It runs on-premises, in a customer's own cloud, or in air-gapped environments, by design. Merza said the company deliberately chose "secure" over "sovereign" in its own marketing because the latter invited too much interpretation. What it actually means: the LLM only sees what it strictly needs to see, and no customer data leaves their environment, not even to Crogl itself. "Our customers don't want any of their data to leak out to any third party, regardless if it's their security provider," Merza said. Because the product ships to run inside customer environments rather than living behind a hosted API, Merza said it has to clear every static and dynamic analysis scanner that exists. "We can't hide behind a SaaS test."
What "deploy in minutes" actually requires
Merza didn't hedge on this claim, largely because customers have already publicly tested it. Crogl ships as two binaries and a container; installation requires a Unix-like system and the ability to run Docker; nothing more elaborate is needed to get a first use case running. Merza pointed to unprompted LinkedIn posts from users who installed the platform and completed their first investigation in under ten minutes.
The report, not the action, is the default output
When an alert fires, Crogl classifies it, builds an investigation plan, and executes against every data source it's been given access to, documenting each step along the way. The output is a full report with a verdict: escalate or close, with the evidence attached so a security team can defend the decision to an auditor later. Crogl can take action directly, quarantining a file, pulling a malicious attachment, messaging a sandboxing system, but Merza was clear that most customers keep a human as the actual trigger, even when they trust the verdict completely. "There's nothing in the product fundamentally that limits action taking," he said. "It's just the mode of use."
That boundary is customer-configurable down to a granular level. A team might let Crogl work phishing and EDR alerts autonomously all day, while requiring a human to review anything touching a production system like SharePoint. Merza expects that boundary to loosen over time as trust builds, not because Crogl pushes for more autonomy, but because customers extend it themselves once a pattern of accurate, well-documented verdicts accumulates.
What developers need to understand before any of this works
For engineers whose systems generate the logs and alerts Crogl investigates, Merza's advice comes down to basics that are easy to skip. The agent needs real data to operate on. The security team needs a clear, internally agreed sense of what actually counts as a priority, or the agent's output won't be actionable no matter how sophisticated the investigation. And organizations need to get comfortable with a mindset shift: agents will make mistakes, the same way humans do, and the goal isn't perfection. "If you try to run an agent so tightened up that it will [never err], you're going to miss threats and you're going to miss breaches, because then you're back to a rules-driven world," Merza said.
What to be skeptical of
Asked what claim in the AI SOC space deserves the most scrutiny, Merza didn't point to a competitor's specific feature. He pointed to the framing itself. "The biggest one is that they can somehow replace the human, completely," he said. Agents can compress and accelerate much of a security analyst's workflow, but a human supervisor is still required, and any vendor pitching a policy-free, procedure-free autonomous SOC should raise a flag rather than confidence. "If there is no policy, there is no promise. You cannot hold that party responsible."
His closing advice for skeptical readers is characteristically blunt: ignore the pitch and try it yourself. Crogl is a free download, and Merza's pitch to developers and architects isn't a sales script, it's an invitation to bring a real use case and see what breaks.