Running LLM inference on US-controlled cloud GPU infrastructure exposes regulated organisations to CLOUD Act and FISA 702 risks. This guide covers on-premises GPU options, model sizing, inference frameworks, and compliance obligations under...
Training AI models on personal data triggers strict GDPR obligations. This article maps the lawful basis requirements, EDPB guidance, DPA enforcement signals and the technical measures that create a demonstrably compliant posture.
Agentic AI systems that act autonomously introduce exfiltration and jurisdictional risks that conventional LLM inference does not. This guide covers containment, AI Act obligations and audit-ready governance for sovereign on-premises deployments.
European open-weight models from EuroHPC and AI Factories offer a jurisdictionally clean alternative to US API services. This guide covers compliance, hardware baselines and supply-chain integrity for regulated sectors.
Fine-tuned model weights and proprietary training datasets represent irreplaceable competitive and legal assets. This article explains how to secure them on sovereign on-premises infrastructure against exfiltration, insider threats, and compliance failure.
The EU AI Act classifies many public-sector and regulated-sector AI systems as high-risk. This guide explains what that means for sovereign, on-premises deployments and how compliance can be made audit-ready.
Public AI services expose sensitive queries to foreign jurisdiction and training pipelines. This guide explains how regulated organisations deploy Mistral and Llama 3 on private infrastructure with full data sovereignty.
