Enterprise security teams are gaining more visibility into how employees use AI, but visibility alone does not necessarily prevent sensitive information from being exposed. As AI agents connect to databases, cloud services, and other enterprise systems, organizations need ways to turn their data protection requirements into enforceable controls. Bloom Security and Cyera are addressing that need through an integration connecting endpoint AI monitoring with data sensitivity classification.
Why Monitoring AI Activity Is Only the First Step
AI tools can operate across an employee’s endpoint and the enterprise systems it connects to. Knowing which applications are installed, who is using them, and where they connect provides an important starting point for security teams. However, those details do not fully explain the potential consequences of a connection.
The destination may contain personally identifiable information, protected health information, payment card information, credentials, or business records. The sensitivity and volume of that information can influence how an organization should respond to an AI tool attempting to access it.
Bloom Security monitors AI agents and tools running on endpoints, identifying users, devices, connection targets, and potentially risky activity. Cyera identifies sensitive datastores and provides information about how their contents are classified.
Their integration connects these two perspectives, allowing security teams to evaluate AI activity with greater awareness of the data involved.
Turning Data Sensitivity Into an Enforcement Rule
The integration allows organizations to use Cyera’s data classification as a basis for endpoint-level AI access policies.
For example, security teams can establish a rule that blocks AI agents from accessing datastores classified as Sensitive and above. Bloom enforces that policy across endpoints as the agents run.
This links a data protection requirement to an operational security control. Instead of simply identifying sensitive information or recording an AI application’s activity, organizations can apply restrictions based on the sensitivity of the data an agent is attempting to reach.
The integration also supports real-time responses that include blocking, pausing, investigating, or remediating AI activity. According to the companies, the objective is to stop risky activity before sensitive data leaves the organization.
Bringing Data Context Into Endpoint Decisions
Bloom and Cyera contribute different information to the enforcement process.
Bloom identifies the agent or tool, the user, the device, and the connection target. Cyera supplies context about the data, including sensitivity level, data type, record count, and regulatory classification.
Together, those details help security teams prioritize activity based on data sensitivity, enforce policies consistently, and investigate incidents with a clearer understanding of the potential data impact.
This is particularly relevant as employees use dozens of AI agents, MCPs, and other tools on their laptops. Those tools can connect to multiple enterprise services, creating a need to assess activity in relation to the information available through those connections.
The integration is designed to make data classification more actionable by connecting it to the endpoints where AI activity occurs.
A Different Role for Endpoint Security
Bloom Security describes its product as endpoint security purpose-built for the AI-native endpoint. Its platform gives security teams control over AI tools and the software ecosystems associated with them, considering who is using an application, what else is running, and what data it can reach.
Its capabilities include preventing risky installations, fixing misconfigurations, and enforcing context-aware runtime policies across endpoint fleets.
Cyera focuses on securing enterprise data in an environment increasingly shaped by AI agents. Its platform helps organizations control what data AI can reach and govern what happens next, protecting data at rest, in motion, and in use.
The integration brings these capabilities together so data sensitivity can inform endpoint enforcement. It gives security teams a way to connect information about enterprise data with controls over AI activity on employee devices.
“Data security has always been close to my heart, having spent a large part of my career building in this space. 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,” said Itay Keren, CEO and co-founder of Bloom Security.
Making AI Policies Operational
For enterprises, AI security involves more than knowing which tools employees use. Organizations also need to understand what those tools can access and establish controls that reflect the sensitivity of the information involved.
Bloom Security and Cyera are connecting those requirements through an integration that combines endpoint AI visibility, data classification, and runtime enforcement. The approach gives security teams a mechanism to turn data sensitivity into practical restrictions on AI access, helping them manage exposure as AI agents interact with enterprise systems.
