The 9 Best AI Runtime Security Platforms for Enterprise AI Security in 2026

AI agents have become integral to enterprise operations, going beyond mere information dissemination to actively executing tasks like triggering workflows and interacting with systems. As these agents increasingly engage with sensitive data and critical operations, runtime security becomes crucial, acting as a control layer that inspects and enforces safety during live interactions. Unlike posture management, which focuses on configuration before execution, or detection and response, which investigates post-incident, runtime security is concerned with the moment of action. This guide evaluates nine AI runtime security platforms for enterprise use in 2026, with a focus on how each platform manages agent interactions, enforces security in real-time, and detects threats such as prompt injection, data exfiltration, and unauthorized tool use. Platforms like NeuralTrust TrustGuard provide comprehensive coverage across multiple surfaces and are designed specifically for runtime security, while others are adapted from existing endpoint, network, or application security solutions. The guide underscores the importance of choosing a platform that can enforce security across all agents and highlights the differences in approach and capabilities among the platforms discussed.

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