As AI transitions from experimentation to production, securing sensitive data, proprietary models, prompts, and agentic workflows is critical. To build trusted AI systems that scale effectively, confidential computing has emerged as a fundamental pillar, ensuring that governance, control, and privacy remain intact.
The session will cover hardware-rooted trust, workload isolation, attestation, secure runtimes, and practical implementation patterns using NVIDIA reference architectures. Attendees will come away with a clear view of how to apply confidential AI in real-world deployments, including regulated workloads, secure multi-party collaboration, and production-ready agentic systems.
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