VoltageGPU vs OneTrust

GDPR Article 32 requires the data controller and processor to implement "appropriate technical and organisational measures to ensure a level of security appropriate to the risk." That sentence has carried the weight of European data protection for eight years, and for most of that time the practical reading was lopsided: the organisational half — written policies, signed DPIAs, RoPA inventories, vendor questionnaires, training logs — was something a platform like OneTrust could put on rails, while the technical half — the part that says the operator must not be able to read the data — was answered with adjectives like "encryption at rest" and "encryption in transit" and a contractual promise about access controls.

The gap was always known. Data at rest is encrypted on the disk, data in transit is encrypted on the wire, but during processing the data lives in plaintext in the workload memory of whatever machine is doing the work, and the cloud operator running that machine has technical access to it. The Article 32 technical measures clause was a contractual aspiration, not a cryptographic statement. Auditors knew it, CISOs knew it, and the response was to layer more organisational measures on top: more questionnaires, more DPIAs, more vendor reviews, more reports. OneTrust's entire product surface is the industrialisation of that response.

Intel TDX changes the answer on the technical side. The CPU encrypts the VM's memory with an AES-256 key the operator never holds; NVIDIA Protected PCIe encrypts the bus traffic between CPU and GPU so model weights and prompt tensors never cross the wire in the clear; an Intel DCAP attestation quote signs the configuration with an Intel-root certificate that any verifier can re-check offline. That quote is legal evidence in a way that a paragraph in a DPA is not — it is a fresh cryptographic statement, produced by the silicon, that says exactly which code is running and that the workload memory is sealed against the operator. For Article 32 the practical consequence is that the technical measures half is no longer a contractual aspiration; it becomes a mathematical property the controller can verify and hand to a regulator on request.

OneTrust still owns the organisational half on its own terms — and that work is necessary; nothing in this page argues otherwise. The thesis of the comparison is simpler: when the technical measures clause needs to mean something stronger than "we wrote it in the policy," the answer is not another policy module. The answer is the silicon underneath, and the agent that runs on top of it.

OneTrust launched its AI Governance module in 2024, and on a surface read the name implies that it governs the AI itself. Read more carefully and the module is a metadata layer: an inventory of the AI systems the organisation is using, a risk-tier classifier that maps each system to an EU AI Act category, a model-card review workflow, and an audit-trail layer for which humans approved which model for which use case. That work is valuable and the AI Governance category needed it. It is, however, structurally distinct from governing where the AI compute physically runs.

The AI features that live inside OneTrust's own products — the assistants that help draft a privacy notice, the summarisers that condense vendor questionnaires, the classifiers that triage DPIAs — call the OpenAI API and the Azure OpenAI service under the hood. That is the same architectural decision dozens of US enterprise SaaS vendors made in 2023–2024, and it is the rational decision when the value of the product is the workflow on top of the model and not the model itself. The consequence for buyers is that the prompts those features process — which by definition include the names, scopes, and risk classifications of the customer's AI inventory and DPIA contents — are sent to a US-hosted closed-weight model running on Azure infrastructure with no Intel TDX, no GPU TEE, and no hardware attestation. The AI governance tool is itself US-hosted AI without confidential-compute properties.

For a European data controller whose Article 32 posture needs to extend to "the tools we use to manage Article 32 compliance," this matters. The metadata about where your AI runs is itself AI-processed metadata, and where that processing happens is governed by the same Article 28 / Article 32 logic as the rest of the AI estate. VoltageGPU's Compliance Officer agent answers that question in a different way: the agent runs on Qwen3-32B-TEE or Qwen3-235B-TEE inside an Intel TDX guest on European hardware under a French operator, attestation quote per session, AES-encrypted memory, AES-encrypted PCIe. It does not replace the workflow features of OneTrust's AI Governance module — it replaces the part where the AI processing leaves European confidential infrastructure to get the work done.

The honest list of OneTrust wins is long, and any comparison that downplays it is not credible. OneTrust's regulatory content library is the deepest in the market: every privacy law in every jurisdiction tracked, regulatory updates pushed as content rather than as an afterthought, controls mapped to dozens of frameworks (ISO 27001, NIST 800-53, SOC 2, HIPAA, PCI DSS, EU AI Act, NIS2) so that the work of building the controls catalogue does not start from a blank page. Audit-committee acceptance is the second structural win — when an internal audit committee asks "is the vendor known to the auditor," OneTrust is a name that does not require justification. Workflow depth is the third: the DPIA module, the consent-management platform, the third-party risk inventory, the vendor-questionnaire engine are mature products with years of customer feedback baked in, and replacing any one of them is a project, not a swap.

The OneTrust losses are equally specific. Entry pricing of roughly $10K per year, with $15K–$25K of implementation services on top, locks out anyone below mid-market — a regional law firm, a clinic group, a fintech pre-Series-B, a regional accounting practice. The six-month implementation cycle locks out anyone whose timeline is "we need this for the audit next quarter." The architecture locks out anyone whose Article 32 reading requires the technical measures to be hardware-enforced rather than documented — and that reading is becoming more common as CNIL guidance, EU AI Act high-risk classification under Article 9 and Article 15, and emerging case law all push toward verifiable cryptographic evidence over contractual claim.

VoltageGPU is built for that second set. The Compliance Officer agent ships at $349/mo on the Starter plan with three seats included and a two-minute setup time, the Professional plan at $1,199/mo adds the full eight-agent vertical lineup (Compliance, Contract Review, Due Diligence, Legal Research, Financial Compliance, FP&A, Operations, Cybersecurity) on Qwen3-235B-TEE with a 256K context window, and the Enterprise plan at $3,499/mo opens dedicated TDX nodes and per-audit attestation. The architecture answer to Article 32 technical measures is built in — the workload runs inside Intel TDX, the attestation quote is exposed as a first-class endpoint, and the operator is VOLTAGE EI in France under European jurisdiction. We do not replace OneTrust's privacy-management workflow. We replace the part where the AI work itself has to happen on infrastructure the auditor can verify cryptographically — and we do it at a price that fits the buyers OneTrust's sales motion cannot reach.