Why XQ and Xage Are Better Together: Extending Zero Trust from Identity to Data and AI
As organizations modernize their IT and operational technology (OT) environments, Zero Trust has become the foundation for securing users, devices, applications, and infrastructure. Yet one critical question often remains unanswered:
What happens to the data—and the AI using it—after access is granted?
Traditional Zero Trust architectures excel at verifying identities and controlling access, but once an authorized user, device, or application gains access, sensitive information is often left unprotected. As organizations increasingly rely on AI to interrogate enterprise and operational data, securing the AI interaction itself has become just as important as securing the underlying systems.
Together, XQ and Xage deliver a comprehensive Zero Trust architecture that protects not only who can access systems, but also how data is secured and how AI can safely consume, reason over, and deliver insights from that data.
Two Different Layers of Zero Trust
Xage establishes trust across identities, devices, workloads, and communications. It continuously authenticates users and machines, enforces least-privilege access, and secures connectivity across enterprise IT, OT, IoT, and edge environments.
XQ extends Zero Trust to the data and AI layers. Rather than relying solely on network boundaries or application controls, XQ applies persistent encryption, granular policy enforcement, and AI-aware governance directly to files, records, databases, APIs, AI knowledge bases, and operational data. Even after access is granted, the data—and the AI interacting with it—remain protected by Zero Trust policies.
Together, the two platforms create a continuous chain of trust from identity to intelligence.
Securing Modern IT Environments
Enterprise data now resides across Microsoft 365, SharePoint, cloud storage, databases, SaaS platforms, APIs, and AI applications.
Xage ensures only trusted users, devices, and workloads can connect.
XQ ensures the data within those environments remains continuously protected through:
Persistent encryption
Record-level access control
Dynamic authorization policies
Data sovereignty enforcement
Comprehensive audit trails and chain of custody
Secure data sharing across organizational boundaries
This allows organizations to maintain control of sensitive information long after authentication has succeeded.
Bringing Zero Trust to OT and Industrial Operations
Industrial organizations are increasingly connecting operational technology to enterprise analytics and AI. This creates tremendous opportunities—but also new risks.
Xage establishes trusted identities for industrial assets, operators, gateways, and machine-to-machine communications.
XQ protects the operational data generated by these systems, including:
SCADA historian data
Sensor telemetry
Engineering documentation
Production recipes
Maintenance records
Digital twins
Operational reports
More importantly, XQ enables organizations to safely expose OT data to AI assistants and analytics platforms without relinquishing control over the information.
Operations teams can ask natural-language questions about production, maintenance, quality, or asset performance while XQ continuously governs which data the AI can access and what information it is permitted to return.
Securing AI from Prompt to Insight
AI is rapidly becoming the primary interface to enterprise and industrial data. The challenge is no longer simply protecting the underlying datasets—it is securing every interaction with the AI itself.
This is where XQ provides a unique layer of protection.
As users interrogate IT systems, OT environments, and enterprise knowledge through AI, XQ secures the complete lifecycle of every AI interaction.
XQ protects:
Enterprise knowledge bases
OT and IoT operational data
Retrieval-Augmented Generation (RAG) repositories
Vector databases
AI prompts
AI responses
Generated reports and insights
Every prompt can be evaluated against organizational policies before data is retrieved.
Every piece of retrieved data remains encrypted and policy controlled.
Every AI-generated insight can inherit the same data protection policies as its source information.
Sensitive information can be automatically redacted, filtered, or blocked before it reaches the user, helping prevent accidental disclosure of regulated, proprietary, or mission-sensitive information.
This enables organizations to implement true AI Data Loss Prevention (AI DLP), ensuring that AI becomes a trusted interface for enterprise knowledge rather than a new avenue for data leakage.
Delivering Trusted, Auditable AI
For regulated industries and government organizations, trust in AI requires more than accurate answers. It requires evidence.
XQ provides end-to-end governance for AI interactions by creating an auditable chain of custody that records:
Who submitted the prompt
Which identity and device were used
What data sources were accessed
Which policies were evaluated
What information was retrieved
How the AI generated its response
What information was ultimately delivered
Organizations gain complete visibility into the flow of information from prompt to response, simplifying compliance, supporting forensic investigations, and demonstrating responsible AI governance.
Whether users are querying financial records, healthcare information, engineering documentation, classified intelligence, or industrial telemetry, every AI interaction can be monitored, governed, and audited.
Enabling Secure Operations at the Tactical Edge
Defense organizations increasingly rely on AI to accelerate decision-making at the tactical edge, where bandwidth is limited and missions demand rapid, trusted insights.
Xage authenticates personnel, devices, and workloads operating in contested environments.
XQ ensures mission data remains encrypted while enabling secure AI interrogation of intelligence products, sensor feeds, and operational data.
Mission-specific policies govern what information AI can access, what responses can be generated, and how those insights are shared across coalition partners and command structures.
The result is trusted AI that can deliver actionable intelligence while preserving data sovereignty, operational security, and mission assurance.
Identity Trust Meets Data Trust Meets AI Trust
Zero Trust cannot stop at authentication.
Identity verification answers an important question:
Can this user, device, or workload connect?
Data-centric security answers the next question:
Can this specific data be accessed or shared?
AI governance answers the final question:
Can AI safely use this information to generate insights without exposing sensitive data?
Together, Xage and XQ provide a comprehensive Zero Trust architecture spanning:
Identity Trust
Device Trust
Workload Trust
Network Trust
Data Trust
AI Trust
This layered approach reduces the risk of insider threats, compromised credentials, ransomware, unauthorized AI disclosure, and data exfiltration while enabling organizations to confidently modernize IT, OT, cloud, edge, and AI initiatives.
The Future of Zero Trust Is Data-Centric AI
As organizations adopt generative AI across enterprise and operational environments, protecting infrastructure alone is no longer enough. Every AI prompt, every retrieved document, and every generated insight becomes part of the organization's security boundary.
By combining Xage's identity-centric Zero Trust architecture with XQ's data-centric AI security platform, organizations gain continuous protection from the user and device to the data and the intelligence created from it.
The result is a new model for Zero Trust—one where identities are verified, data remains protected wherever it travels, and AI delivers trusted, governed, and fully auditable insights without compromising security.
