Corvex Among the First Companies to Achieve Verified Production Deployment of Confidential Computing for AI on NVIDIA HGX™ B200 Systems

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• In production AI, security is only trustworthy if it can be independently verified. Confidential computing makes trust at runtime measurable, using hardware-enforced isolation and cryptographic attestation across CPUs, GPUs, and interconnects, so customers can prove that sensitive models and data are protected while in use.

  80% confidence

• The deployment establishes confidential computing as an operational, production-ready infrastructure primitive for AI workloads on the NVIDIA HGX B200 system

  80% confidence

• As AI systems move from experimentation to mission-critical production infrastructure, customers increasingly require runtime assurances for workloads where sensitive data and models must be decrypted in memory to execute

  80% confidence

• Remote attestation is foundational for highly regulated industries and protecting valuable IP in AI workloads like model weights, enabling continuous compliance, defensible auditability, and deployment models where trust must be proven rather than assumed

  80% confidence

• With the NVIDIA HGX B200 system, verification comes with near-native performance, removing the historical trade-off between security and speed

  80% confidence

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