New York, United States, October 22nd, 2026, FinanceWire
Data security platforms help enterprises identify sensitive information and understand where it resides. Endpoint security tools, meanwhile, monitor activity on employee devices. As AI agents begin connecting these environments, organizations face the challenge of ensuring that data protection policies can be applied to the applications interacting with sensitive information.
Bloom Security and Cyera are addressing that challenge through an integration that connects Cyera’s data classification with Bloom’s endpoint AI visibility and runtime controls. The integration is designed to help security teams make access decisions based on data sensitivity and enforce those decisions while AI agents are running.
The Journey from Data Discovery to Enforcement
Identifying sensitive information is an important part of protecting it, but organizations also need to connect that knowledge to the systems accessing the data.
Cyera identifies sensitive datastores and classifies the information they contain. This includes data such as personally identifiable information, protected health information, payment card information, credentials, and business records. Its platform provides context about sensitivity levels, data types, record counts, and regulatory classifications.
Bloom Security approaches the problem from the endpoint. It monitors AI agents and tools running on employee devices, identifying what is installed, who is using it, where it connects, and whether its activity appears risky.
The integration brings the two perspectives together. Security teams can associate endpoint activity with the sensitivity of the data at the other end of a connection, providing a basis for more informed security decisions.
Why Context Changes Access Decisions
Not every AI connection presents the same level of risk. An application connecting to a datastore containing sensitive records raises different considerations from one accessing information with a lower sensitivity classification.
Bloom identifies the agent, tool, user, device, and connection target. Cyera supplies the corresponding data context. Together, the platforms allow security teams to prioritize activity according to the sensitivity of the information involved.
This combined view also helps teams understand data impact when investigating events. Rather than looking only at the application or the endpoint, they can consider the classification of the data associated with the activity.
That capability becomes increasingly relevant as employees use multiple AI agents, model context protocol (MCP) connections, and other tools that interact with enterprise datastores, databases, and software-as-a-service platforms.
Enforcing Policies While Agents Operate
The integration extends data classification into runtime enforcement at the endpoint.
Organizations can configure policies that block AI agents from accessing datastores classified as Sensitive and above. Bloom enforces those policies across endpoints as agents run, while security teams can block, pause, investigate, or remediate activity in real time.
This creates a direct link between data classification and endpoint controls. Security teams can use the sensitivity of information to inform restrictions on AI access, rather than treating data discovery as a separate process from the enforcement of security policies.
The companies say the approach enables organizations to stop risky AI activity before sensitive data leaves the business. Cyera customers can also gain real-time visibility into endpoint threats to their sensitive information.
Addressing the Expanding AI Software Ecosystem
The integration also reflects the changing nature of endpoint security. Employees may run numerous AI agents and tools on their devices, each potentially interacting with different enterprise systems.
Bloom’s platform is designed to manage the AI-native endpoint and its associated software ecosystem. Beyond monitoring AI activity, it provides capabilities for preventing risky installations, correcting misconfigurations, and enforcing context-aware runtime policies across endpoint fleets.
Cyera complements those controls with its focus on enterprise data. Its platform helps organizations control what data AI can reach and govern what happens next, protecting data at rest, in motion, and in use.
Together, the companies connect information about what is running on an endpoint with knowledge about the data those applications can reach.
Making Data Security Operational
“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 brings data intelligence closer to the point where AI activity takes place. By connecting Cyera’s classification capabilities with Bloom’s endpoint enforcement, the companies are giving security teams a way to turn data sensitivity into practical controls over AI access.
For organizations adopting AI agents, the result is a more direct relationship between identifying sensitive information, understanding which applications can reach it, and enforcing restrictions in real time.