The security perimeter around enterprise data is becoming more complicated as employees use AI agents that connect to corporate systems from their laptops. These tools can interact with cloud datastores, databases, and software-as-a-service platforms, raising questions about which agents should be permitted to reach sensitive information and how organizations can enforce those decisions. Bloom Security and Cyera are bringing endpoint monitoring and data classification together to address this challenge.
The integration combines Bloom’s visibility into AI activity on endpoints with Cyera’s understanding of enterprise data sensitivity. It is designed to help security teams identify AI access to sensitive information, prioritize activity, and enforce restrictions in real time.
The Endpoint as an AI Control Point
AI security increasingly requires organizations to understand what happens on employee devices. Workers may install AI tools, run agents, and establish connections to systems that hold important enterprise information.
Bloom Security monitors this activity by identifying which AI tools and agents are installed, who is using them, what they connect to, and whether their activity appears risky.
The platform is purpose-built for the AI-native endpoint, where traditional application and device controls must account for a growing ecosystem of AI software. Bloom also supports preventing risky installations, correcting misconfigurations, and enforcing context-aware runtime policies across endpoint fleets.
However, knowing which agent is running and where it connects does not necessarily reveal the sensitivity of the information involved. That requires an understanding of the data itself.
Adding the Data Perspective
Cyera provides that complementary view by identifying sensitive datastores and classifying their contents. The platform accounts for information such as personally identifiable information, protected health information, payment card information, credentials, and business records.
Through the integration, Cyera’s data context can be considered alongside the endpoint details supplied by Bloom. Those details include the agent or tool involved, the user, the device, and the connection target. Cyera adds sensitivity levels, data types, record counts, and regulatory classifications.
This combination allows security teams to understand AI activity in relation to the information that may be affected. It also helps them prioritize activity based on data sensitivity and assess potential data impact during investigations.
The result is a more contextual view of AI access, connecting the activity occurring on employee endpoints with the sensitivity of the information available through enterprise systems.
Moving Beyond Alerts
Monitoring AI activity can help security teams identify potentially risky behavior, but the Bloom-Cyera integration also focuses on enforcing decisions.
Organizations can establish policies that block AI agents from accessing datastores classified as Sensitive and above. Bloom enforces those policies across endpoints while agents run.
Security teams can also block, pause, investigate, or remediate AI activity in real time. The companies say this helps organizations stop risky activity before sensitive data leaves the organization and provides Cyera customers with real-time visibility into endpoint threats involving sensitive information.
This connects data classification with operational controls. Instead of using information about data sensitivity only to understand the environment, security teams can apply that information when deciding whether an AI agent should be permitted to access a particular datastore.
One Integration, Two Security Perspectives
Bloom and Cyera approach the problem from different directions. Bloom focuses on the endpoint and the software running on it, while Cyera focuses on the data that organizations need to protect.
Bloom provides control over AI activity and its associated software ecosystem. Cyera helps enterprises control what data AI can access and govern what happens next, addressing information at rest, in motion, and in use.
By connecting these capabilities, the integration gives security teams a way to combine endpoint visibility with data classification and runtime enforcement. The objective is to make policies more responsive to the sensitivity of the information involved and to help teams understand which AI activities pose the greatest potential concern.
Securing AI Access at the Point of Activity
“Data security has always been close to my heart, having spent a large part of my career building in this space,” said Itay Keren, CEO and co-founder of Bloom Security. “The challenge now is that AI agents are running on endpoints with direct access to sensitive data, and traditional endpoint security simply can’t see which agents are touching which data. Bloom monitors endpoint AI activity. Cyera knows what data is sensitive. Together, we’ve brought together endpoint visibility with data context: real-time enforcement grounded in data sensitivity.”
The integration reflects an approach to enterprise AI security that connects the endpoint with the data it can reach. As organizations introduce more agents and AI tools into their workflows, the ability to understand both sides of that relationship becomes increasingly important.
By linking data sensitivity to real-time endpoint controls, Bloom Security and Cyera aim to help enterprises apply data protection policies directly to AI activity, giving security teams greater visibility into potential exposure and a way to restrict risky access before sensitive information leaves the organization.
