AI that meets the bar your DPO actually signs off on.
We build AI systems engineered for GDPR compliance from the first design review, data residency, consent flows, right to erasure, DPIAs, and audit trails. Production AI that legal and security clear without rework.
Compliance baked in,
not bolted on.
GDPR isn't a feature you add at the end. We design the system around lawful basis, data minimization, and erasability from day one, so the audit doesn't surface surprises.
EU/UK Data Residency
Inference, training, and storage pinned to your jurisdiction, with documented data flows for the DPO.
Consent & Lawful Basis
Granular consent management, with model behavior gated on consent state, no consent, no inference on that data.
Right to Erasure
Subject access, rectification, and deletion paths that propagate through training data, embeddings, and caches.
DPIA Ready Documentation
Architecture diagrams, data flow maps, and risk assessments delivered alongside the working system.
PII Redaction & Encryption
PII detection at ingestion, encryption at rest and in transit, and minimization of personal data in prompts and logs.
Auditable Inference Trail
Every model decision logged with input, version, output, and lawful basis, queryable and exportable for regulators.
Six situations where the DPO is in the room from day one.
Companies do not come to this page for AI. They come because legal said no, an auditor asked a question nobody could answer, or a deadline moved from abstract to dated. Here is what each situation turns into.
AI Products Serving EU Customer Data
The core case: your SaaS, portal, or AI agent touches the personal data of EU or UK residents, which puts every prompt, embedding, and log line inside GDPR's scope. We architect the whole inference path for lawful basis, minimization, and erasability from the first design review, so the feature ships once, with the DPO's signature, instead of twice, with a remediation budget.
High Risk Systems Under Annex III
If your AI touches hiring, credit, education, essential services, or biometrics, the EU AI Act classifies it high risk, with conformity assessment, technical documentation, logging, and human oversight obligations attached, and fines up to €15 million or 3 percent of global turnover behind them. We build Annex III systems with those obligations engineered in, and for organizations still mapping what they own against the risk tiers, our regulatory AI consulting practice runs the classification exercise first.
When the Data Cannot Leave the Country
Some clients face rules stricter than residency clauses: government contracts, health data, or internal policy that says the model comes to the data, never the reverse. For those cases the compliant architecture is on premise and sovereign AI, self hosted models inside your perimeter, and this practice designs the compliance layer that runs on top of it.
The Shadow AI Cleanup
Somewhere in your company right now, an employee is pasting customer data into a personal ChatGPT account, with no DPA, no lawful basis, and no record it happened. Blocking the tools without an alternative just drives it underground. We deploy the governed alternative, a compliant internal AI gateway with logging, PII redaction, and policy enforcement, so employees keep the productivity and the company gets its data flows back on the map.
Making an Existing AI System Compliant
The rescue engagement: the AI feature already shipped, and now legal, a customer's procurement team, or a regulator letter is asking questions the architecture cannot answer. We retrofit consent gating, erasure propagation through training data and embeddings, audit logging, and residency controls, and we are honest that this costs more than building it right would have, which is an argument for the next system, not a reason to leave this one exposed.
EdTech and Systems Touching Minors
Education platforms sit in a double bind: education is an Annex III high risk category under the AI Act, and children's data carries heightened GDPR protections on top. Consent flows involving guardians, age appropriate design, and strict minimization are not optional extras here. Our EdTech AI practice builds learning platforms inside that double frame from the start.
Your GDPR Program Is a Head Start, Not a Rerun.
The good news buried in the AI Act: organizations with mature GDPR programs already own most of the machinery, records of processing, impact assessment workflows, vendor management, breach response. The genuine gaps are AI specific: logging granularity, bias assessment documentation, and human oversight workflows. We map your existing controls to the new obligations and build only the delta, which is routinely half the project some advisors would sell you.
One System, Two Regulators, Stacked Fines.
An AI system processing personal data answers to both frameworks at once: data protection authorities keep full GDPR jurisdiction while market surveillance authorities enforce the AI Act, and the fines stack. A single badly governed hiring model can draw penalties under both. This is why we refuse to treat privacy and AI compliance as separate workstreams, one architecture has to satisfy both, by design.
From DPIA to deployed system.
Compliance work runs in parallel with engineering, not as a gate at the end. The DPO sits in the kickoff, not the launch review.
Joint Compliance Review
Engineering, your DPO, and (often) outside counsel jointly review the proposed architecture and identify risks early.
Privacy by Design Build
Data minimization, consent gating, and erasure pipelines built into the system, not retrofitted later.
DPIA & Documentation
Full DPIA package, data flow diagrams, and operational runbooks, handed over before go live.
Production & Audit
Deployment with monitoring on consent state, data residency, and erasure SLAs, ready for any regulator inquiry.
The deadline, the fines, and the classification trap, as of right now.
AI compliance in 2026 is a moving target with a fixed penalty schedule. Here are the answers buyers need this quarter, dated honestly, because in this vertical stale advice is worse than none.
Almost certainly yes, if your AI touches EU users at all. Like GDPR, the AI Act is extraterritorial: you are in scope if you sell to EU customers, place an AI system on the EU market, or if your AI's outputs are used by people in the EU, regardless of where your company or servers sit. A US or Asian company running algorithmic credit scoring for European applicants is fully covered. The honest test is not "where are we", it is "where are the people our AI affects", and for most companies with any EU revenue the answer settles the question.
Plan for a 20 to 40 percent premium on the build when compliance is engineered in from day one, covering the consent gating, erasure pipelines, logging, and documentation the regulations demand. Ongoing compliance for a high risk system runs roughly €30,000 to €50,000 a year in industry benchmarks, with conformity assessments at €5,000 to €50,000 per system where required. The number that matters more: retrofitting compliance onto a shipped system reliably costs a multiple of building it in, because erasure through embeddings and audit trails through history are architectural, not additive. The premium is real, and it is the cheap option.
Three tiers of AI Act fines, up to €35 million or 7 percent of global turnover for prohibited practices, €15 million or 3 percent for high risk violations, the tier most companies face, and the ceilings exceed GDPR's. Where personal data is involved, GDPR fines stack on top under a separate authority. Beyond money: regulators can order systems withdrawn from the market, mandate retraining, and list non compliant systems in a public register, and early enforcement will be complaint driven, a rejected candidate or a denied loan applicant is all it takes to open a file. GDPR enforcement started slow and passed €4 billion in cumulative fines; the AI Act inherits that machinery already warmed up.
It is the classification that decides most of your obligations, and studies suggest around 40 percent of enterprise AI systems currently sit unclassified or misclassified. Using a foundation model through its API generally makes you a deployer, with lighter duties. Substantially modifying one, extensive fine tuning included, can reclassify you as a provider, inheriting the full technical documentation, conformity assessment, and post market monitoring stack. Teams discover this after the fine tuning project, which is the expensive order. We run the classification before any build decision, because the answer changes both the architecture and the budget.
As of this writing, both, and that is precisely the trap. A provisional political agreement from May 2026, the Digital Omnibus, would defer Annex III high risk obligations to December 2027, but it has not been enacted, which leaves August 2, 2026 as the legally operative enforcement date. Pausing your compliance program on a provisional agreement is a bet with full penalty exposure on the downside and nothing on the upside, because the work transfers intact if the deadline moves: early compliance is not wasted compliance. Our advice, and the advice of most counsel we work alongside: build to August 2, and treat any extension as breathing room you did not need.
First, accept the finding before the audit forces it: surveys consistently show most employees use AI at work, approved or not, and every unapproved paste of customer data into a consumer tool is processing without lawful basis. The fix has two halves that only work together. Block the ungoverned channels at the network layer, and simultaneously give people a governed alternative, an internal AI gateway with logging, redaction, and a real DPA behind it, that is genuinely as useful as the tool you took away. Companies that only block get shadow AI with better hiding. Companies that only offer get partial adoption. We deploy both halves as one project, usually in weeks.
Bring your AI system inventory to the call, or bring the uncomfortable fact that you do not have one. Either way, the classification exercise is where every compliant architecture starts, and it is the part we will do with you before any contract.
Questions about
GDPR Compliant AI
Yes, with the right contractual setup (DPA, SCCs), regional endpoints, and data minimization in the prompt path. We design the integration layer that makes their APIs usable under your DPO's terms.
EU or UK by default, AWS Frankfurt/Ireland, Azure West Europe, GCP europe west, or your private cloud. For on prem, see our data sovereignty offering.
Subject access is a query against the audit log. Erasure cascades through prompts, embeddings, retrieval indices, and any cached state, with a documented SLA for completion.
We design with risk classification in mind from day one. Where your use case falls into a high risk category, we deliver the technical documentation, conformity assessment support, and post market monitoring infrastructure required.
Yes, every engagement ships a DPIA ready package: data flow diagrams, risk assessment, mitigations, and residual risk register. Your DPO finalizes; we provide the technical scaffolding.
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Book a free discovery call. Bring your DPO if you want, we'll walk through the compliance architecture together.
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