Your AI Project Failed DPIA Review.
Now What?
Most AI projects in regulated enterprises stall at the same point: the Data Protection Impact Assessment. The DPO has questions. Legal has concerns. Nobody knows how to design AI infrastructure that satisfies GDPR without crippling the use case. We do.
GDPR Wasn't Designed for AI. Your Infrastructure Must Bridge the Gap.
GDPR was written in 2016, before enterprise AI deployment was mainstream. The principles are clear — lawfulness, purpose limitation, data minimisation, accuracy, storage limitation, integrity, accountability — but applying them to AI systems requires infrastructure-level solutions, not just policy documents.
Data Residency
Challenge: AI training and inference may process data across regions
Solution: EU-only compute zones, region-locked inference endpoints, encrypted data pipelines with EU-held keys
Transparency & Explainability
Challenge: GDPR Article 22 gives individuals rights regarding automated decisions
Solution: Explainability layers, decision audit trails, human-in-the-loop workflows for high-impact decisions
Right to Erasure
Challenge: Deleting someone's data from a trained model is technically complex
Solution: Architecture that separates PII from model training, machine unlearning capabilities, data lineage tracking
Purpose Limitation
Challenge: Data collected for one purpose may not be usable for AI training
Solution: Consent management integration, purpose-tagged data pipelines, automated compliance checking before training
Data Protection Impact Assessment
Challenge: DPIAs for AI systems are complex and often block deployment
Solution: DPIA templates for common AI patterns, pre-assessed architecture blueprints, DPO-friendly documentation
Third-Party Processing
Challenge: External AI APIs mean personal data leaves your control
Solution: Self-hosted inference options, data processing agreements, on-premise and private cloud deployment patterns
GDPR-Compliant AI Architecture
We design AI infrastructure with GDPR compliance built into the architecture — not bolted on after deployment.
Data Layer
- EU-resident data stores
- Encryption at rest (AES-256, EU-held keys)
- Purpose-tagged data catalog
- Automated PII detection and classification
- Data lineage from source to model
- Retention policies enforced automatically
Processing Layer
- EU-only compute zones
- Kubernetes with namespace isolation
- Model training on anonymised/pseudonymised data
- Inference endpoints with request logging
- Guardrails for PII in model outputs
- Consent verification at inference time
Governance Layer
- DPIA workflow automation
- Data subject request handling (access, erasure, portability)
- Audit trails for all data processing
- DPO dashboard with compliance metrics
- Automated Article 30 records of processing
- Incident detection and 72-hour notification workflow
Built for Organisations That Can't Afford to Get GDPR Wrong
Financial Services
Healthcare
Public Sector
Enterprise SaaS
Frequently Asked Questions
Can we use US-based cloud providers for GDPR-compliant AI?
Yes, with appropriate safeguards. EU-only regions, Standard Contractual Clauses, and supplementary technical measures (encryption with EU-held keys) are typically required. We help you design the architecture that satisfies your DPA and legal team.
How do we handle right-to-erasure for AI training data?
This is one of the hardest GDPR challenges for AI. Options include machine unlearning, retraining without the subject's data, or architectural choices that separate PII from model training. We design the approach that fits your use case and risk tolerance.
Do we need a DPIA for every AI system?
Not necessarily. DPIAs are required when processing is 'likely to result in a high risk to the rights and freedoms of natural persons.' Most AI systems processing personal data will trigger this threshold. We help you assess which systems need DPIAs and conduct them.
What about the EU AI Act intersection with GDPR?
The EU AI Act and GDPR have overlapping but distinct requirements. High-risk AI systems under the AI Act must also comply with GDPR when processing personal data. We design infrastructure that satisfies both simultaneously.
GDPR Compliance Shouldn't Kill Your AI Strategy
Book a free consultation. We'll review your AI use case, identify the GDPR challenges specific to your situation, and show you how compliant infrastructure design solves them.
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