Why We Reimagined Continuous Controls Monitoring

Today, DataBee announced major advancements to our cyber risk management platform, including the next evolution of DataBee Continuous Controls Monitoring (CCM), new innovations in Frontier AI Defense, and expanded capabilities for User Access Review. Together, these solutions help organizations automate the manual work behind monitoring controls, assessing application exposures, and reviewing user access so security and IT teams can reduce risk faster with less effort.

While today's announcement spans our broader cyber risk management platform, it also introduces a fundamentally different approach to working with cybersecurity data, one designed to dramatically reduce the effort traditionally required to generate cyber risk insights. That innovation is central to the next evolution of DataBee Continuous Controls Monitoring (CCM). In this blog, I'd like to explore the challenge we set out to solve, why it has historically limited CCM programs, and how advances in artificial intelligence helped make a different approach possible.

For years, security teams have accepted a frustrating reality: before they can answer important cyber risk questions, they need to move, transform, normalize, enrich, and store enormous amounts of data.

Want to measure control effectiveness?

Build a data pipeline.

Want to understand whether controls are operating as intended?

Consolidate security, IT, business, and operational data.

Want trusted reporting for auditors, executives, regulators, and business stakeholders?

Prepare for exports, spreadsheets, manual reconciliation, and ongoing maintenance.

Somewhere along the way, we accepted the idea that cyber risk management would always require a large integration project before it could deliver answers.

At DataBee, we no longer believe that should be true.

Why Cybersecurity Is Different

For decades, organizations have largely relied on a single approach to cybersecurity analytics: collect the data, move it, normalize it, enrich it, and store it in a centralized location before meaningful analysis can begin.

That model emerged for a reason.

Unlike many business data sets, security data is highly fragmented. Every tool generates different formats, schemas, naming conventions, and levels of context. Some of that information is semi-structured or unstructured. Relationships between applications, assets, vulnerabilities, controls, identities, and ownership records often span dozens of disconnected systems.

Historically, that complexity made it extraordinarily difficult to analyze cybersecurity data across systems. As a result, organizations often had little choice but to move and normalize information before meaningful analysis could occur.

An alternative model has long existed. Known as federated analytics, it allows data to remain in its original systems and be analyzed where it resides. Federated analytics has been successfully applied in financial services, customer relationship management, and business intelligence because those environments typically rely on more structured and predictable data models. Customer records, transactions, product catalogs, and financial entries can be correlated across systems with relatively little interpretation.

Cybersecurity presents a fundamentally different challenge. The variability, volume, and complexity of security data make it difficult for traditional federated approaches to understand disparate schemas, correlate related information, and produce reliable results across systems. For many organizations, centralized data architectures became the only practical option.

Why AI Changes the Equation

If the first challenge was rethinking where cybersecurity analysis happens, the second was determining how to make a federated approach work in one of the most complex data environments in the enterprise.

At DataBee, we saw an opportunity to combine a federated approach to cybersecurity data with advances in generative AI.

Rather than requiring security data to conform to a predefined structure before analysis, AI can help interpret context, work across structured, semi-structured, and unstructured sources, and retrieve the information needed to answer specific questions.

That opened the door to a new approach: helping organizations generate trusted cyber risk insights without requiring massive data preparation efforts first.

Combining AI Innovation with Cybersecurity Data Science

Technology alone is not enough to solve this problem.

Understanding cybersecurity data requires deep knowledge of how security tools generate information, how assets and applications relate to one another, and how control measurements should be interpreted in the context of cyber risk.

Over the past several years, DataBee has built extensive expertise in cybersecurity data engineering, correlation, and analytics. Combined with a growing ecosystem of more than 340 integrations, that foundation enabled us to apply AI in a meaningful way.

The result is a new approach that enables organizations to connect to structured, semi-structured, and unstructured security data sources, calculate key measurements, and retrieve only the information needed to answer specific questions.

Instead of beginning with a data project, organizations can begin with the outcomes they want to achieve.

What This Means for Continuous Controls Monitoring

Continuous controls monitoring has always promised tremendous value.

Organizations want continuous answers to questions such as:

• Are our controls working?
• Where are the gaps?
• Are we compliant?
• What changed?
• What risks require attention right now?
• Where should I invest to get the most return in terms of reduced risk?

The challenge is that many CCM initiatives have traditionally required significant planning, integration, and data preparation before organizations can begin producing meaningful measurements. Teams often spend months building infrastructure before they can answer their first control question.

We believed there was a better way.

With the next evolution of DataBee CCM, we've shifted the focus from infrastructure to outcomes. Rather than beginning with a large implementation effort, organizations can start with the controls they want to measure, the frameworks they need to support, and the risk questions they want answered.

This approach enables cybersecurity and cyber GRC teams to create measurements faster, monitor the controls that matter most to their business, and generate explainable, data-backed results tied directly to operational data.

By connecting measurements to the data, assets, applications, users, owners, and business context behind each result, teams gain a clearer understanding of what is working, what is not, who is accountable, and what should happen next.

The result is a simpler path from periodic control validation to continuous assurance.

Ultimately, our goal is simple: help organizations turn control questions into actionable answers.

A Unified Approach to Cyber Risk Management

Although this blog focuses on the innovations behind DataBee CCM, it's important to view these advancements within the broader context of cyber risk management.

Organizations do not manage controls in isolation. Effective cyber risk management also requires understanding application exposures, prioritizing remediation, establishing ownership, and governing user access.

That is why DataBee continues to invest in Frontier AI Defense and User Access Review alongside CCM. Together, these solutions help organizations automate foundational cyber risk management workflows across control monitoring, exposure assessment, and access governance, creating a more comprehensive approach to reducing cyber risk.

Validation from the Market

We believe the industry is increasingly recognizing the need for a more scalable and operational approach to continuous controls monitoring.

Earlier this year, DataBee, a Comcast company, was included as a Sample Vendor in the Continuous Controls Monitoring category of the Gartner® Hype Cycle™ for Cyber-Risk Management, 2026¹. We believe it reflects growing interest in technologies that can help organizations move beyond periodic control assessments toward more continuous, data-backed approaches to cyber assurance.

The Bigger Opportunity

The goal is not better dashboards.

The goal is not collecting more data.

The goal is reducing risk.

To accomplish that, organizations need help automating the manual work behind cyber risk management, including monitoring controls, reviewing user access, assessing exposures, establishing ownership, and prioritizing remediation.

The future of cyber risk management isn't about generating more findings.

It's about helping organizations turn those findings into action.

We believe the next era of cybersecurity will be defined not by who collects the most security data, but by who can reduce risk the fastest.

That's the vision behind our latest innovations in Continuous Controls Monitoring, Frontier AI Defense, and User Access Review.

Try It for Yourself!

If you'd like to experience the next evolution of DataBee CCM firsthand, we're now accepting registrations for early access to our complimentary two-week trial program. We look forward to helping organizations explore a simpler path to continuous controls monitoring and experience the benefits of automated CCM for themselves.

¹ Gartner, Hype Cycle for Cyber-Risk Management, 2026, Deepti Gopal, Pedro Pablo Perea de Duenas, 27 April 2026.

Gartner does not endorse any company, vendor, product or service depicted in its publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner publications consist of the opinions of Gartner’s business and technology insights organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this publication, including any warranties of merchantability or fitness for a particular purpose.

We are recognized as Comcast Corporation (DataBee) in the report. Gartner and Hype Cycle are a trademark of Gartner, Inc., and/or its affiliates.