LLM Confidential Inference in Production: GPU Remote Attestation, Key Release on Proof, and Evidence Chain for Sensitive Data
This article provides a production architecture deep dive into how LLM confidential inference uses CPU/GPU Trusted Execution Environments, remote attestation, key release on proof, and evidence retention to protect sensitive prompts, model weights, and intermediate inference states. It also covers compatibility boundaries and pre-deployment checklists.