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Design AI guardrails for real-time avatars across identity, speech, RAG, model output, actions and handover with seven enforceable policy gates.
Prioritise AI patches across models, GPU runtimes, media and private infrastructure using risk-based lanes, end-to-end tests and rollback evidence.
Design AI network segmentation for private avatars with seven trust zones, default-deny flows, workload identity, WebRTC controls and 12 tests.
Detect and control AI configuration drift across prompts, models, voices, RAG, guardrails, GPUs and networks in private avatar deployments.
Secure real-time AI avatar sessions across authentication, reconnects, idle timeouts, delegated authority, memory cleanup and teardown tests.
Design AI rate limiting for real-time avatars with admission control, fair queues, tenant quotas, graceful degradation and overload tests.
