Lineation.ai secures autonomous AI agents at runtime

Lineation.ai has officially launched its publicly available agentic security platform, designed to bridge the gap between generative AI application security and real-time runtime protection. The solution introduces a zero trust unified control plane paired with a lightweight endpoint daemon, enabling organizations to secure autonomous AI agents directly at the point of execution.

As enterprises increasingly deploy autonomous AI agents that access sensitive data, interface with APIs, and execute complex workflows, traditional static security perimeters and standard LLM gateways prove ineffective. Lineation.ai addresses this gap by assigning a Zero Trust Non-Human Identity (NHI) to every agent and integrating an LLM/MCP Gateway. This architecture prevents critical threats such as goal hijacking, memory poisoning, and tool misuse before an agent can act on malicious instructions.

The platform enforces continuous policy-as-code evaluation and generates an immutable, forensic Reasoning Audit Trail. This allows security teams to query and replay an AI’s internal reasoning process, providing regulators with a verifiable record of agent behavior.

“Legacy networks and traditional LLM gateways were never designed for software that reasons, accesses databases via MCP, and executes operations autonomously,” said Cameron Manavian, CEO of Lineation.ai. “With Lineation, we introduce a Zero Trust control plane that empowers enterprise CISOs to define rigid operational guardrails once and enforce them everywhere an agent resides.”

Key features of the platform include real-time runtime monitoring, granular access controls based on non-human identities, and full auditability of agent decision-making. The solution is tailored for enterprise environments where AI agents must operate securely across distributed systems, databases, and third-party services without compromising data integrity or compliance.