AI agents are moving beyond conversation. They are no longer limited to answering questions. They can call tools, access systems, read files, operate data, and complete business workflows across applications. This shift also explains why the discussion around “AI agent entry points” and “security infrastructure” is becoming more important. A recent 36Kr article about “Lobster Box” highlighted the growing need for end-cloud security infrastructure in the AI agent era, especially as agents increasingly rely on local scheduling, plugin-based execution, and data movement between devices and cloud environments. For enterprises, this issue is even more critical. Individual users may worry about privacy leakage. Enterprises face a broader set of risks: Can an agent access data it should not access? Can it respect different permission boundaries across departments, roles, and systems? Is the query generated by the agent aligned with the correct business definition? Is the data source trustworthy?…