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Build an AI model licensing rights matrix for on-premise avatars across deployment, copying, optimisation, derived artefacts, support and exit.
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.
