GDPR-Compliant Cloud Services for AI Development
Build and deploy AI systems without compromising data privacy. We provide cloud infrastructure with built-in GDPR compliance: data residency controls, pseudonymization at scale, and audit-ready logging. Examples: federated learning pipelines with EU-only data storage, automated DSAR (Data Subject Access Request) handling, and model training with differential privacy guarantees.
See the Architecture DetailsGDPR-Compliant Cloud Infrastructure: Data Localization and Safeguards
EU-Based Data Processing Only
Our cloud infrastructure enforces strict data localization for European clients. All processing occurs in EU-based data centers, eliminating cross-border transfer risks under Article 44 and ensuring compliance with Article 46 safeguards.
- No data leaves the EU—period.
- Self-hosted AI frameworks (Ollama, vLLM) keep control in your hands.
- Open-weight models (Llama, Mistral) allow customization without compliance trade-offs.
No Third-Party Data Sharing
Your AI systems operate within your compliance boundaries. We don’t share data with external vendors, and our German-Filipino engineering teams design pipelines with GDPR-aligned handling from the start.
- Full data sovereignty—no vendor lock-in.
- Production-ready deployments with clear cost and performance metrics.
Self-Hosted AI Frameworks: Full Control Without Vendor Lock-In
Deploy Ollama, vLLM, and TGI on Your Terms
Run open-weight models (Llama, Mistral, Qwen) in your own environment. No proprietary APIs, no hidden telemetry. Inference pipelines are fully customizable—adjust batching, quantization, and GPU allocation without compromising GDPR compliance or latency.
- Zero third-party data sharing—your models and prompts stay within your compliance boundaries.
- German-Filipino engineering teams optimize pipelines for cost, performance, and data sovereignty.
- Production-ready deployments with measurable metrics: throughput, token/s, and per-request cost.
Open-Weight Models: Full Customization Without Compliance Trade-Offs
GDPR-Aligned Data Handling by Design
Our cloud infrastructure enforces data localization for EU clients—all processing occurs in EU-based centers. Open-weight models like Llama, Mistral, and Qwen run in your environment, ensuring no third-party data exposure.
- No vendor lock-in: Self-host with Ollama, vLLM, or TGI.
- Fine-tune or deploy out-of-the-box—your choice.
- German-Filipino teams optimize pipelines for scalability and GDPR compliance.
Production-Ready Deployments
Clear metrics on cost, performance, and data sovereignty. No hidden telemetry, no proprietary restrictions—just full control over your AI systems.
GDPR-First AI Pipelines: Engineered for Compliance and Scale
German-Filipino Teams Build Auditable AI Systems
Our engineering teams design AI pipelines with GDPR compliance as the foundation—not an add-on. Every data flow is documented, access is logged, and compliance checks are automated. No manual audits, no surprises.
- Data localization enforced for EU clients (processing in EU-based centers).
- Self-hosted frameworks (Ollama, vLLM, TGI) eliminate vendor lock-in.
- Open-weight models (Llama, Mistral, Qwen) with full customization control.
Compliance-First AI Infrastructure: Full Control Over Data Governance
No Third-Party Data Sharing, Ever
Your AI systems run within your compliance boundaries. We provide the infrastructure—you retain full control over data governance. No unexpected subprocessors, no hidden data flows.
- Self-hosted frameworks (Ollama, vLLM, TGI) eliminate vendor lock-in.
- Open-weight models (Llama, Mistral, Qwen) allow customization without compliance trade-offs.
- Production-ready deployments with clear cost, performance, and sovereignty metrics.
Production-Ready AI Deployments: Cost, Performance, and Sovereignty Metrics
Predictable Pricing per Inference
No hidden fees—just transparent, usage-based pricing. Pay only for what you consume, with granular cost breakdowns per model and endpoint. Example: A Llama 3 70B deployment costs $0.002 per 1K tokens, scaled linearly with throughput.
- No egress fees
- Volume discounts for committed workloads
- Real-time cost dashboards
Latency and Throughput Benchmarks
Performance is measurable. A vLLM-optimized Mistral 7B deployment averages 50ms p99 latency at 100 req/s on A100 GPUs. Throughput scales linearly—double the nodes, double the output. Benchmarks are workload-specific, not marketing fluff.
- Pre-deployment load testing
- SLOs tied to your workload
- Autoscaling based on queue depth
Data Sovereignty Guarantees
Full audit trails and regional residency enforcement. Your data stays in your chosen region (e.g., Frankfurt for EU clients), with immutable logs for every inference. GDPR compliance isn’t optional—it’s baked into the deployment pipeline.
- No cross-border data transfers
- Customer-managed encryption keys
- Automated compliance reporting
Core Infrastructure Services for AI Workloads
Dedicated GPU Clusters
Provision isolated NVIDIA A100/H100 clusters with direct attach NVMe storage. Configure bare-metal or virtualized nodes via Terraform. Includes GPU health monitoring and automatic failover for long-running training jobs.
Zero-Trust Network Segmentation
Micro-segment training and inference workloads with Calico policies. Each AI pipeline operates in its own Kubernetes namespace with strict network ACLs. Example: LLMs in one segment, vector DBs in another—no lateral movement possible.
Low-Latency Inference Endpoints
Deploy vLLM with automatic tensor parallelism scaling. Endpoints support gRPC/HTTP2 with <50ms p99 latency for 13B parameter models. Includes built-in request batching and KV cache optimization.
Observability Stack for AI
Pre-configured Prometheus + Grafana dashboards tracking GPU utilization, token throughput, and model latency percentiles. Alerts trigger on anomaly detection (e.g., sudden latency spikes or memory leaks).
Illustrate the step-by-step workflow for deploying a GDPR-compliant AI system.
Model Fine-Tuning with Privacy Guards
• Fine-tuning pipelines enforce differential privacy to prevent data leakage. • Training data is tokenized and encrypted at rest, with access logs audited daily.
Inference Rate Limiting & Cost Controls
• Per-user rate limits prevent abuse and unexpected billing spikes. • Real-time dashboards show token usage and projected costs before execution.
Automated Compliance Reporting
• Pre-configured reports map AI operations to GDPR Articles 15-22. • Audit trails include model versioning, data provenance, and access timestamps.
Zero-Trust Deployment Architecture
• Microsegmentation isolates AI workloads from other cloud services. • Short-lived credentials and mutual TLS enforce strict service-to-service auth.
Deploy GDPR-Compliant AI Today
Ready to build AI systems with GDPR compliance baked in? Our engineering team can walk you through the technical details—from data localization to auditable pipelines. Contact us for a deep dive.