ABOUT
Industry:
Defense Technology
CUSTOMER OVERVIEW
A leading AI-driven defense technology company set out to modernize its data and AI security posture as it scaled operations tied to a major government program. With sensitive engineering data, mission-critical systems, and AI-enabled workflows rapidly expanding across cloud platforms, the organization faced a familiar but urgent challenge.
How do you maintain strict control over sensitive data while continuing to innovate at speed?
To address this, the company deployed Symmetry Systems DataGuard, establishing full visibility into its data environment and laying the groundwork for secure AI adoption with AIGuard.
The Challenge
Innovation Outpacing Data Control
Like many defense organizations operating at the forefront of AI and advanced systems, the company’s environment had evolved quickly.
Large volumes of sensitive data were distributed across SharePoint and OneDrive. Engineering, operations, and leadership teams needed broad access to collaborate effectively. At the same time, AI tools were beginning to integrate into workflows, increasing both productivity and risk.
This created several underlying challenges:
- Sensitive data was widely distributed with inconsistent visibility
- Access permissions had grown complex and difficult to audit
- Data classification was incomplete, limiting enforcement of policy
- AI systems were beginning to interact with sensitive data without clear guardrails
- Compliance requirements such as CMMC required tighter control and auditability
The organization needed a way to understand its data environment holistically and take action quickly.
The Goal
From Data Risk to Mission Readiness
By deploying Symmetry DataGuard, the organization achieved:
- Rapid reduction in data exposure risk
- A clear and scalable path to compliance
- Improved control over identity and access
- A secure foundation for AI adoption
With AIGuard on the roadmap, it is now positioned to extend that control into the next generation of AI systems.
The Approach: Deploying Symmetry DataGuard
The company deployed Symmetry DataGuard across its Office 365 environment to establish a unified view of data, identity, and access. Within a short period, DataGuard provided a comprehensive map of:
Where sensitive data resides
Who can access it, directly and indirectly
How that data is being shared and used
This visibility allowed the organization to move from assumptions to evidence-based decision making.
Why Symmetry
What made Symmetry the Right Choice?
The success of this deployment highlights a fundamental difference in approach. Most security tools focus on infrastructure or activity. Symmetry focuses on data. By building a complete picture of data, identity, and access, Symmetry enables organizations to:
- Understand risk in precise, actionable terms
- Prioritize remediation based on real impact
- Secure AI systems by securing the data they rely on
For defense organizations, this level of clarity is essential.
The Outcomes: From Invisible Risk to Actionable Insight and Enforcement
The initial deployment surfaced several critical patterns that are common in high-growth defense environments.
Sensitive data was more broadly accessible than expected, often shared across large internal groups or external collaborators. Most data lacked proper classification, making it difficult to enforce controls or demonstrate compliance. A significant portion of data had not been accessed in months but remained available to hundreds of users. In parallel, identity-related risks became clear, including users with access beyond what their roles required.
At a high level, the findings revealed:
Widespread exposure risk, driven by overly broad sharing configurations
A major classification gap, limiting the effectiveness of security and compliance controls
Access sprawl, where permissions had expanded beyond least privilege principles
These insights provided a clear starting point for remediation.
Reducing Exposure and Regaining Control
One of the most significant outcomes of the deployment was the speed at which the organization was able to act.
With DataGuard, security teams could clearly see how sensitive data was being exposed and who had access to it. This enabled targeted remediation across the highest-risk areas.
Key actions included:
- Reducing overly broad sharing permissions
- Restricting access to sensitive data based on role and need
- Prioritizing remediation based on data sensitivity
Within weeks, the organization dramatically reduced unnecessary exposure and brought its data environment under control.
This shift from reactive investigation to proactive control was a turning point.
Enabling Compliance: A Scalable Path to CMMC Readiness
Compliance was a central driver for the deployment. The organization needed to ensure it could identify, classify, and control access to sensitive data in alignment with CMMC requirements, which are common in defense sector.
Before Symmetry, this process was largely manual and difficult to scale.
DataGuard introduced a more effective model by:
- Automatically identifying sensitive data across multiple categories
- Mapping data to compliance requirements
- Integrating with Microsoft Purview to apply and enforce sensitivity labels
This allowed the organization to move toward a state where compliance is:
- Continuously enforced rather than periodically assessed
- Directly tied to actual data and access patterns
- Measurable and auditable
Securing AI Workflows: Establishing Guardrails with DataGuard
As AI adoption increased, the organization recognized a critical dependency.
AI systems can only be as secure as the data they can access.
Without proper controls, AI tools can surface or expose sensitive information based on user permissions. In a defense environment, this risk is amplified.
Using DataGuard, the organization was able to:
- Identify which data could be accessed by AI-enabled users
- Ensure that only properly classified and controlled data was available
- Reduce the likelihood of sensitive data being surfaced unintentionally
This created a set of guardrails that allowed AI tools to be deployed with confidence.
Operational Benefits: Reducing Cost While Improving Security
Beyond security and compliance, the deployment also revealed opportunities to improve operational efficiency.
The organization identified a large volume of dormant and redundant data that contributed to both cost and risk. With DataGuard, it was able to take a structured approach to data minimization.
This included:
- Identifying unused data based on activity patterns
- Detecting duplicate or redundant files
- Prioritizing cleanup based on sensitivity and business value
This approach reduced storage overhead while also shrinking the organization’s attack surface.
Looking Ahead: Securing AI Agents with AIGuard
As the organization continues to expand its AI capabilities, it is preparing for a shift toward more autonomous, agent-based systems.
These systems introduce new risks because they operate across workflows, interact with multiple data sources, and make decisions using sensitive inputs.
To address this, the organization plans to deploy Symmetry AIGuard.
AIGuard extends Symmetry’s data-first security model into the AI layer and will enable:
- Fine-grained control over what data AI agents can access
- Enforcement of least privilege at the AI level
- Continuous monitoring of agent behavior
- Prevention of unintended data exposure
Together, DataGuard and AIGuard form a unified approach to securing both data and the AI systems that depend on it.
In modern defense environments, the challenge is no longer just protecting infrastructure. It is about controlling data and ensuring that AI systems operate within secure boundaries. This case study demonstrates that with the right visibility and control, organizations can reduce risk, enable compliance, and continue to innovate at speed.
That is the role Symmetry Systems plays.