Confidential Metal: Run Secure AI Workloads on Secure Hardware

The Trust Problem: Policy isn't enough.

AI platforms running production workloads handle some of the most sensitive assets in the stack: proprietary model weights, customer data, and confidential inference context. For teams serving regulated industries - healthcare, finance, government - the security question isn't theoretical. It's the question that blocks every deal and stalls every audit.

The problem isn't that providers are negligent. Most run solid operational security programs. But operational security is policy-based, and policy can't be independently verified by the customer renting the hardware. Your compliance team asks a straightforward question: "Can you prove the infrastructure is secure?" And the honest answer, for most rented GPU environments, is no. You can review certifications. You can read attestation reports. But you can't cryptographically verify what's running on the machine before you send sensitive data to it.

That gap pushes teams toward expensive on-prem alternatives. Build your own cluster, hire your own staff, manage your own facility - all to answer a question that the hardware itself should be able to answer.

Introducing Confidential Metal

Confidential Metal replaces that gap with a Zero Trust framework. Instead of trusting provider security posture, you verify every layer of the stack cryptographically, at the silicon level, before your data touches the environment. Encryption and isolation at every layer gives AI Platform customers the security and privacy they need for the most sensitive workloads.

What that looks like in practice: your team deploys a cluster, runs remote attestation to confirm the hardware is genuine and the firmware is unmodified, and begins running workloads - all with full encryption active. TEE configuration that typically takes days of manual BIOS setup is handled automatically at deployment. With Hydra's Confidential Metal automations, AI Platforms can quickly deploy secure and confidential workloads to new AI servers. Your compliance team gets verifiable proof, not policy documents.

This opens markets that were previously off-limits for rented GPU infrastructure. Healthcare organizations running confidential patient data through AI models. Financial institutions processing proprietary trading signals. Government agencies with strict data sovereignty requirements. These teams can now use Hydra's bare metal GPU clusters with the technical controls that support HIPAA, SOC 2, and PCI-DSS audit requirements - without building and operating their own on-prem clusters.

Four Layers of Security

Confidential Metal implements four independent security layers, each enforced at the hardware level. No single point of compromise breaks the model.

Dedicated Bare Metal. Every server is single-tenant. No hypervisor, no shared host, no side-channel exposure from neighboring workloads. The machine is yours for the duration of the rental. This eliminates an entire class of attack vectors that exist in multi-tenant virtualized environments.

Agentless Deployment, Your Keys Only. Hydra provisions the server, hands you the keys, and steps away. There are no management agents running on your OS. No remote shells. No backdoors. Hydra support operates at the BMC/IPMI layer only - zero OS-level access, zero data access. That's an architectural decision to give AI Platforms increased privacy and security, not merely a contractual commitment.

Encryption at Rest. Full disk encryption is pre-configured at deployment. Model weights, training artifacts, and inference logs remain encrypted on storage at all times. Physical seizure of drives yields unreadable data.

Confidential Compute. Intel TDX and GPU-level confidential computing create hardware-enforced encrypted execution environments. Data stays encrypted in memory and during processing. Not even Hydra, the facility operator, or a compromised OS kernel can access what's inside the trust domain.

These four layers work independently. A breach in one doesn't compromise the others.

Remote Attestation ties it together. Before sending sensitive data, your team can cryptographically verify the execution environment is genuine and unmodified. Three independent roots of trust - Intel TDX, GPU-level confidential computing, and Canonical Ubuntu Confidential VM measured boot chain - give you verifiable proof that the hardware is real, firmware is intact, and confidential protections are active.

The Numbers

• Hydra is the first neocloud to offer bare metal TEE across all OEMs - Intel TDX and GPU-level confidential computing preconfigured on compatible servers from Dell, Lenovo, HPE, Supermicro, and Aivres
• Near-native bare metal performance - Full hardware-level encryption active - with only 4-8% overhead at steady-state inference, and no hypervisor performance tax
• Three-source remote attestation - Intel TDX, GPU-level confidential computing, and Canonical measured boot each provide independent verification. No single root of trust to compromise
• Automated BIOS configuration - TEE setup that takes days of manual configuration deploys in minutes. Your team focuses on workloads, not firmware settings
• Zero ongoing provider access - Support operates at BMC/IPMI only. No OS-level access, no data access, by design
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Hydra Confidential Metal vs. Alternatives

Get Started

Log into your Hydra control plane, deploy Confidential Metal compatible servers, and run attestation to verify security for your sensitive workloads. Hydra's team is available to support you and your compliance team to unlock your highest security workloads.

For more details - Download our Confidential Metal PDF