Crogl, a leader in cybersecurity risk management, announced that it has been granted U.S. Patent No. 12,277,177 B1, covering its breakthrough technology that enables its knowledge engine to analyze, traverse, and understand security-critical data from multiple sources without requiring normalization.

“In an era where threat actors are leveraging AI while security teams struggle with limited resources, our goal at Crogl is to empower these teams without adding more burden,” said Monzy Merza, co-founder and CEO of Crogl. “This patented innovation allows customers to use AI securely within their own environments—saving time, conserving effort, and eliminating lengthy onboarding cycles.”

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Filip Stojkovski, founder and lead researcher at SecOps Unpacked, shared his perspective on the industry challenge: “From a practitioner’s standpoint, analysts spend endless hours switching between tools just to answer simple questions. Either you’re waiting for data engineers to normalize everything—which rarely happens quickly—or you’re trying to teach analysts multiple query languages. What we need are systems that work with the data as it is, not as we want it to be.”

The High Cost of Data Normalization

Data normalization remains one of the most resource-intensive processes in cybersecurity operations, introducing significant risk and inefficiencies for organizations. Crogl outlines three major challenges associated with normalization:

  • Cost and Vendor Lock-In – Normalization demands expensive data cleaning and standardization processes, often requiring data consolidation into a single storage platform, which can result in long-term vendor dependency.
  • Complexity and Schema Dependence – Analysts must understand and remember how data has been standardized, a nearly impossible task given the hundreds of log formats and evolving enterprise environments.
  • Loss of Context – The process often eliminates vendor-specific fields and metadata, diminishing the quality of investigations and weakening detection capabilities.

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A Game-Changing Approach to Data Analysis

With this newly patented methodology integrated into its knowledge engine, Crogl can now seamlessly analyze and interact with customer data in place, without the need for data migration or normalization. This capability dramatically accelerates deployment timelines and boosts operational efficiency for security teams.

Organizations deploying Crogl’s technology can realize measurable value within hours or days—rather than weeks—allowing teams to focus on proactive defense rather than data preparation.

“Our approach transforms how organizations harness their existing data,” added Merza. “It’s not just about automation; it’s about enabling AI to work securely and efficiently alongside human expertise.”

By removing the dependency on normalization, Crogl is redefining how enterprises manage, investigate, and respond to cyber threats, setting a new standard for agility and intelligence in cybersecurity operations.

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