While 90% of enterprises are experimenting with AI, highly regulated industries are hitting a wall. They cannot deploy at scale because they cannot risk sensitive data leaving their jurisdiction or entering opaque 'black box' managed services. Forward-thinking organizations are now building AI capabilities they fully own and control—on European soil, with European values.
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We are seeing a move away from convenience (managed public cloud) toward control (sovereign, portable AI). The market demands the ability to 'build once, run anywhere'—whether on-premise or in an EU-native cloud. Reliance on US-based managed services creates risks that threaten business continuity, cost control, and regulatory compliance.
US-based providers are subject to US laws (e.g., Cloud Act), conflicting with EU privacy requirements. Changes in surveillance laws, tariffs, or sanctions could disrupt services overnight.
Critical data and analytics landscapes increasingly depend on a single US vendor—leading to loss of commercial leverage and forced alignment to vendor roadmaps.
Managed AI services lack transparency around data handling, model weights, and data flows—creating unquantifiable security risk and inability to guarantee compliance.
Unmanageable compliance liabilities that threaten your license to operate and your ability to audit effectively.
High-performance NVIDIA GPU clusters hosted in European data centers. Your data stays where it belongs—under your control, within your jurisdiction.
Build on leading open-source models like Llama and Mistral. No API dependencies, no usage restrictions, no surprises. The model is yours.
Train models on your proprietary data to create AI that understands your domain, your terminology, and your customers—better than any generic model ever could.
A robust framework to deploy, manage, and scale multiple models. Built-in load balancing, monitoring, and cost optimization—so you can focus on value, not infrastructure.
Pre-built templates and proven patterns to fast-track your most valuable use cases. Don't start from zero—start from experience.
A leading European bank faced mounting pressure to process loan applications faster while maintaining strict regulatory compliance. Manual review of credit documents—income statements, tax returns, bank statements—was slow, error-prone, and created bottlenecks that frustrated both customers and underwriters.
Using sovereign AI infrastructure, we deployed an intelligent document processing system that automatically extracts, classifies, and validates data from loan applications. The solution uses fine-tuned models trained on the bank's specific document types and regulatory requirements—all running on European infrastructure with no data leaving the jurisdiction.
65% reduction in document processing time. Faster loan approvals with improved accuracy. Full audit trail for regulatory compliance. Complete data sovereignty maintained throughout the process.
A leading Dutch insurance company struggled to manage complex accident claims while adhering to strict regulatory standards. Employees were overwhelmed by the intricate information landscape, relying on manual processes that resulted in delays, high operational costs, and extensive training requirements for new staff.
We developed an AI Chat Assistant that allows employees to quickly find relevant information from the internal knowledge base. The assistant uses Retrieval Augmented Generation (RAG) to provide clear, concise, and human-readable responses. We also built a tool that helps employees determine claim payouts more accurately—all running on sovereign infrastructure.
Faster claims processing with instant access to information. Significant cost reductions through streamlined processes. New employees onboard faster with AI-assisted guidance. One claims handler noted: 'It's like having a knowledgeable colleague available at all times.'
A global bank serving 60 million customers across 100 countries received 85,000 customer inquiries per week. Despite an existing chatbot handling 40-45% of queries, 16,500 still required live agent support. The chatbot relied on predefined intents and couldn't access the bank's evolving knowledge base, leading to incomplete responses and frustrated customers.
We built a next-generation AI chatbot that pulls real-time information from the bank's website, FAQs, and unstructured documents to create a unified knowledge base. AI-driven validation mechanisms ensure every response is accurate and risk-mitigated, with source references for transparency and trust.
20% more queries resolved in real-time without live agent support. Reduced operational overhead and maintenance costs. Seamless, instant support across global markets. Higher customer satisfaction and retention.
AVROTROS, a Dutch public broadcaster, wanted to understand viewing behavior at a deeper level—segmenting audience data by topics covered and people featured. But TV is fast-changing; topics aren't known beforehand and can only be extracted after broadcasting. Manual timestamping was time-consuming and only performed on selected episodes.
We implemented an automated labeling solution that identifies and timestamps topics and guest speakers in video content. The extracted labels are stored in a vector database for fast search, with an intuitive web app for editors to inspect and correct labels when needed.
90% accuracy in identifying topics and individuals. Direct correlation between viewer numbers and content topics. Data-driven decisions for future programming. Dramatically reduced manual labeling effort.
A European business bank specializing in large-scale project financing faced a significant bottleneck in their credit underwriting process. Teams of domain experts had to manually review hundreds of pages of diverse documents—applicant details, project specs, market analyses, and financial statements—for every loan application. This manual extraction consumed around 25% of the roughly 10-day timeline needed to draft transaction proposals, diverting expert attention from higher-value analysis and risk assessment work.
We co-developed an AI-powered document extraction hub built on the Xtractor platform. Working closely with underwriting experts, we captured their knowledge in prompt-based questionnaires that guide precise, structured information extraction. The system automatically pulls key details from large, varied document sets and returns answers with direct citations to source documents for easy verification and full traceability. The platform runs securely on Azure within the bank's private network, with robust authentication and scalable containerized deployment.
Reduced manual effort required to prepare underwriting proposals. Experts spend less time sifting through documents and more time on meaningful analysis. Shortened overall approval timeline. Built-in transparency through document citations ensures high accuracy and trust in AI-generated insights. Standardized extraction workflows with reusable questionnaires deliver a more agile and reliable credit underwriting process.
Sovereign AI isn't just about compliance—it's about competitive advantage. Eliminate geopolitical risk, vendor lock-in, and black-box security concerns. Let's discuss how to build AI capabilities that are truly yours.
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