Enterprises are rapidly moving AI into production, but a critical risk remains: protecting AI models and sensitive data during inference. Traditional security protects data at rest and in transit, but not in use, where models and data are most exposed. This creates a real risk of model theft, data leakage, and compliance failures.
Fortanix Confidential AI closes this gap by securing both AI model IP and sensitive data during execution using hardware-based Confidential Computing. With encrypted CPU and GPU enclaves and cryptographic attestation, workloads run in trusted environments, protected even from privileged access.
What You’ll Learn
- Why inference is the highest-risk stage in AI
- How model weights and sensitive data are exposed in memory
- How Confidential Computing protects AI in use
- How to securely deploy third-party or proprietary models
- Architecture for trusted, scalable confidential inference
Unlock Trusted AI at Scale by learning how to run AI workloads with verifiable trust, security, and compliance without compromise.
