How to Evaluate Secure AI Infrastructure Providers: Enterprise RFP Guide

Evaluating secure AI infrastructure providers requires moving beyond marketing claims of enterprise compliance and rigorously verifying four technical pillars: hardware-level physical isolation, non-blocking private networking, sovereign cryptographic data custody, and legally binding compliance attestations. In high-stakes enterprise deployments, relying on generic cloud vendor questionnaires introduces catastrophic vulnerabilities, as standard multi-tenant virtualization models fail to provide true physical separation for proprietary model weights and sensitive client prompt data.

Most commercial GPU clouds operate under flexible shared-responsibility frameworks designed to limit provider liability. When selecting an AI infrastructure partner for mission-critical training or inference workloads, engineering leadership and Chief Information Security Officers (CISOs) must require verifiable technical evidence before committing capital to long-term compute agreements.

Beyond Marketing Claims: The Four Pillars of AI Infrastructure Security

1. Bare-Metal Physical Tenancy vs. Virtualized Slicing: True security begins at the silicon layer. Regulated AI workloads demand single-tenant, bare-metal server nodes where physical PCIe lanes, NVLink interconnects, and host memory are dedicated exclusively to your organization, completely eliminating hypervisor escape risks and noisy neighbor performance degradation.

2. Air-Gapped and Non-Routable Fabric Segmentation: High-bandwidth GPU clusters require specialized RDMA over Converged Ethernet (RoCE v2) networking. Verify that the provider provides private, non-routable Layer 2 network fabrics physically separated from public cloud management planes, preventing inter-tenant packet sniffing.

3. Uncompromised Cryptographic Key Custody: Infrastructure providers must support full Bring Your Own Key (BYOK) or customer-managed keys (CMK) backed by dedicated Hardware Security Modules (HSM). If the provider holds master decryption keys, your data remains vulnerable to administrative insider threats and extraterritorial legal discovery.

4. Verified Third-Party Compliance and BAA Eligibility: Demand current, unredacted SOC 2 Type II audit reports, ISO/IEC 27001 certifications, and formal Business Associate Agreement (BAA) execution capabilities for HIPAA-regulated healthcare and life sciences workloads.

Hyperscaler Shared Cloud vs. Dedicated Private AI Cloud: Provider Evaluation Matrix

Selecting an AI infrastructure partner requires evaluating architecture, security boundaries, and commercial terms. The decision matrix below details the core differences between traditional multi-tenant hyperscalers and dedicated private AI cloud providers:

A 5-Point Due Diligence Checklist for AI Infrastructure RFPs

1. Require Verified Hardware Sanitization SLAs: Mandate contractual commitments enforcing cryptographic disk wiping (NIST SP 800-88 compliance) and complete GPU memory zeroing immediately upon server deprovisioning, backed by verifiable audit certificates.

2. Verify Physical Facility Security Controls: Inspect data center specifications for Tier 3+ redundancy, biometric multi-factor physical access, 24/7 armed security, continuous CCTV monitoring with 90-day retention, and dual-independent power and cooling distribution paths.

3. Demand Explicit Zero-Egress Network Architecture: Require transparent network topology documentation confirming that internal GPU-to-GPU and GPU-to-storage traffic routes exclusively across private, non-routable fabrics with zero egress surcharges or public internet exposure.

4. Ensure Direct Engineering Support Escalation: Verify that support agreements provide direct, 24/7 access to dedicated infrastructure and network operations engineers (SREs), bypassing multi-tiered consumer helpdesk queues during critical operational incidents.

5. Establish Contractual Audit and Inspection Rights: Secure the contractual right to perform annual third-party penetration testing, physical facility audits, and compliance inspection verification without unreasonable access restrictions or excessive administrative fees.

Frequently Asked Questions

What is the single biggest security risk when evaluating public GPU cloud providers?

The single biggest security risk is multi-tenant hypervisor vulnerability and shared memory leakage. When multiple organizations run proprietary models and confidential prompt contexts on the same physical server, side-channel attacks and hypervisor exploits can potentially allow unauthorized actors to observe memory bus activity or extract sensitive artifacts. Demanding dedicated, single-tenant bare-metal infrastructure completely mitigates this vulnerability.

How does OneSource Cloud satisfy rigorous enterprise AI security evaluations?

OneSource Cloud delivers single-tenant, bare-metal GPU clusters hosted in hardened Tier 3+ sovereign facilities. By combining air-gapped RoCE v2 networking fabrics, customer-controlled encryption key custody, BAA-eligible HIPAA compliance, and transparent flat-rate pricing with zero data egress penalties, OneSource provides enterprise security teams with a verifiable, audit-proof infrastructure foundation.