AWS has published a case study on building a secure multi-tenant LLM analytics agent with row-level security. The architecture is designed to let different users query data while preserving tenant boundaries.
That problem is central for enterprise AI analytics. Natural-language interfaces are useful only if they respect the same permissions and data controls as the underlying systems.
The post shows how AI agents are being adapted to existing security models rather than replacing them, which is essential for regulated or multi-customer environments.