Security at the system boundary.
Enterprise security depends on knowing what a system can access, what it can change, and how those actions can be checked.
We examine security where AI applications meet enterprise data, cloud infrastructure, and operational authority.
Explore SecurityIdentity and access
Follow analysis of service identities, agent permissions, authentication, and the controls needed when software acts across multiple systems.
Retrieval and enterprise data
Understand how data permissions, source selection, and context handling affect an AI application's exposure. Examine where information can cross an unintended boundary.
Cloud and infrastructure risk
Explore configuration choices, third-party dependencies, isolation, and the operational work of reducing exposure across an environment.
Detection and response
Look at the evidence teams need to investigate a problem, limit its effects, and restore service with confidence.
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What makes AI security different?
AI introduces additional questions about model behavior, retrieved content, and delegated actions. Those questions sit alongside established responsibilities for identity, data protection, application security, and infrastructure.
Does an architecture guide replace a security assessment?
No. A guide can help define questions and controls. A deployment needs assessment against its own data, permissions, threats, and operating environment.