As enterprises accelerate AI adoption, they face a critical challenge: their most valuable proprietary data remains largely inaccessible to AI due to privacy, security, and compliance concerns. Traditional security measures encrypt data at rest and in transit, but leave data exposed while in use—creating risk, compliance friction, and a major barrier to operationalizing AI at scale.

This joint white paper explores how OPAQUE and AMD address this challenge with hardware‑backed Confidential AI and verifiable runtime governance, enabling enterprises to safely unlock their most sensitive data for AI workloads. It explains how AMD Secure Encrypted Virtualization (SEV), combined with the OPAQUE Confidential AI Platform and illustrated through a real‑world deployment at a leading U.S. credit management company, enables organizations to securely process sensitive data while maintaining end-to-end encryption—including in use—enforcing runtime policies with cryptographic proof, and delivering comprehensive auditability through tamper-proof logs. 

The result is a new foundation for enterprise AI—one that turns sensitive data from a privacy liability into a durable competitive advantage by making trust verifiable.