Raven Runtime AI Agents is a runtime security platform that provides visibility and control over AI agents operating inside production applications. The platform addresses three core problems: - AI agents blend into normal application behavior using legitimate libraries, frameworks, and APIs, making them indistinguishable from normal traffic to traditional security tools - Shadow AI agents created by developers or vendors without centralized security approval bypass IAM reviews, policy enforcement, and audit trails - External controls such as network controls, API gateways, and IAM policies lack visibility into in-process agent decisions Core capabilities: - Runtime AI Agent Discovery: Automatically discovers AI agents running in production, including embedded agents, framework-based agents, and tool-driven workflows, without requiring registration, tagging, or manual inventory - Real Behavior Monitoring: Monitors what agents actually do at runtime, including what data they access, which APIs and tools they invoke, and which code paths they execute - Policy-Based Runtime Control: Allows security teams to define permitted agent actions and can alert on or block unsafe actions in real time before data leaks or misuse occurs - Developer Attribution and Accountability: Traces every agent action back to the owning service, deployment, code change, and author The platform operates inside the application runtime rather than at the model or request layer, distinguishing it from AI guardrails or prompt monitoring tools. It does not require code changes, agent instrumentation, language-specific SDKs, or prompt modification. It uses passive runtime instrumentation designed for production environments with low performance overhead. Supported languages include Java, Node.js, Python, Go, and others in polyglot environments.