Built for regulators, not just for demos
Most AI security approaches protect the infrastructure around the data. We protect the data itself, using reversible pseudonymisation under your control, aligned with GDPR and recent case law, without pretending that personal data becomes anonymous when it leaves your systems.
Why pseudonimisation and not anonymisation
Most AI data protection strategies fall into one of two traps. They either block AI tools entirely, killing productivity, or they claim data is "anonymised" when it leaves the organisation. The problem is that true anonymisation, under GDPR Article 26 and the Court of Justice (CJEU) Breyer ruling, requires that no party can reasonably re-identify the individual. That is an extremely high bar, and most solutions that claim to meet it do not.
AliasPath™ takes a different approach. We pseudonymise data at your verification boundary before it reaches any AI model, processor, or third-party tool. The pseudonymised records remain personal data under GDPR because you, as controller, retain the ability to re-identify. This is deliberate. It keeps your legal obligations intact, preserves your control over the data lifecycle, and ensures that processors and AI providers only ever see records they cannot independently tie back to real individuals.
GDPR alignment and controller accountability
Under GDPR Articles 4(5) and 25, pseudonymisation is recognised as a technical measure that supports data protection by design and by default. AliasPath™ implements this at the infrastructure level rather than relying on policy documents or user behaviour.
When your organisation sends aliased data to a GenAI tool, a cloud processor, or an agentic AI workflow, the receiving party sees coherent, structured records - names, addresses, account references - but none of them map to real individuals without the key you hold. This means your Data Protection Impact Assessments (DPIAs) can demonstrate a concrete technical safeguard, not just a written policy. It also means that in the event of a breach at the processor level, the exposed data is non-attributable without your cryptographic authority.
AliasPath™ keeps the controller in control. You decide when and whether real identities are restored, under what policy conditions, and for which downstream actions. Re-identification happens server-side, just-in-time, and only when a real-world action legally requires it.
CJEU case law and the Breyer test
The CJEU's ruling in Breyer v Germany established that data is personal if the controller has legal means to obtain additional information that would allow re-identification. This matters because it means pseudonymised data sent to a processor who lacks the re-identification key has a materially different risk profile than data sent in the clear.
AliasPath™ is designed around this distinction. When aliased data reaches a non-EU hyperscale AI provider or a third-party model, that provider cannot independently re-identify the individuals. The alias mappings and cryptographic keys never leave your environment. A model compromise, a subpoena to the processor, or an infrastructure breach at the AI provider yields structured but non-attributable data.
This does not eliminate your transfer obligations. Cross-border data flows still require assessment under Chapter V of the GDPR. But the risk profile is materially reduced, and your Transfer Impact Assessments (TIAs) can reference a concrete technical measure rather than relying solely on contractual safeguards.
What regulators expect to see
Data protection authorities across Europe are increasing scrutiny of AI deployments. The ICO, CNIL, and Irish DPC have all issued guidance requiring organisations to demonstrate how they protect personal data when using AI tools. Common expectations include evidence of a DPIA, a lawful basis for processing, and technical measures to minimise data exposure.
AliasPath™ gives you a clear answer to the question regulators are asking: "What technical controls do you have in place to prevent personal data from being exposed to AI systems?" Rather than pointing to a policy document or an employee training programme, you can demonstrate an infrastructure-level control that pseudonymises data before it leaves your trust boundary, maintains cryptographic separation between identity and utility, and provides audit logs of every data flow.
Processors see utility. Only you see identity
When you send aliased data to non-EU or hyperscale AI providers, the model can still operate on coherent records, household structures, policy references, transaction chains, without access to the underlying individuals. The AI produces useful output. Your data stays protected. And when a real-world action requires the actual identity (sending a letter, filing a regulatory return, updating a CRM record), re-identification happens server-side, under policy, with a full audit trail.
Cross-border transfers and Schrems II
Since the Schrems II ruling invalidated the EU-US Privacy Shield, organisations have relied heavily on Standard Contractual Clauses (SCCs) supplemented by technical measures for international data transfers. The EDPB's recommendations explicitly cite pseudonymisation as a supplementary technical measure that can support transfers where the recipient cannot re-identify individuals.
AliasPath™ provides exactly this. When aliased data is processed by an AI provider in a jurisdiction without an adequacy decision, the provider receives utility-preserving but non-identifiable records. Your SCCs are backed by a demonstrable technical safeguard, not just a contractual promise. This strengthens your position in regulatory audits and reduces the residual risk that the EDPB requires you to assess.
Review your AI controls with our team.