Confidential AI - 2026 Pricing, Features, Reviews & Alternatives

Confidential AI runs AI workloads inside trusted execution environments (TEEs) backed by Intel TDX, AMD SEV-SNP, and similar hardware attestation technologies, ensuring that prompts, model weights, and inference outputs remain encrypted and inaccessible even to infrastructure operators. The platform targets enterprises in regulated industries, including finance, healthcare, and legal services, where data sovereignty and auditability are non-negotiable requirements. Deployment is cloud-based, with support for private cloud and on-premises configurations depending on organizational policy.

Confidential AI provides cryptographic attestation reports that allow organizations to verify the integrity of the execution environment before submitting sensitive data. The platform integrates with existing MLOps pipelines and supports major model formats, reducing friction for teams already operating AI infrastructure. Access controls, audit logging, and policy enforcement are configurable at the workload level, giving security and compliance teams granular visibility into how AI resources are consumed across the organization.

By isolating AI computation within hardware-enforced boundaries, Confidential AI addresses a critical gap in enterprise AI adoption: the inability to run proprietary or regulated data through third-party AI systems without exposure risk. The result is an architecture that allows organizations to leverage large-scale AI capabilities without compromising on confidentiality, compliance, or control.