Blog Post

How Swiss Organisations Are Implementing Secure Sovereign RAG Architectures on Exoscale SKS

October 12, 2023
June 3, 2026
8 min read
10
min read
Data visualization and AI network

Retrieval-Augmented Generation (RAG) has become essential for making large language models useful in enterprise environments. However, most public RAG solutions send sensitive company data to foreign cloud providers — creating serious risks around data privacy, regulatory compliance, and intellectual property protection. Swiss organisations are now building secure sovereign RAG architectures entirely on Exoscale SKS that combine the power of modern AI with complete data control, full EU AI Act compliance, and Swiss-grade security.

Before implementing Singularity IO's agentic platform, underwriting teams spent up to 40% of their time manually extracting data from PDFs, emails, and legacy systems. This not only slowed down the quotation process but also introduced the risk of human error in critical risk assessment models.

Key Takeaways
  • Full data residency — no sensitive documents ever leave Switzerland
  • High-performance vector search and retrieval on GPU-accelerated Exoscale SKS
  • Built-in EU AI Act compliance with transparency and auditability
  • Sovereign RAG delivers better accuracy and security than public alternatives
  • Organisations maintain complete ownership and governance of their knowledge base

The Risks of Public RAG Solutions

While public RAG services offer convenience, they require uploading proprietary documents, policies, and client data to foreign infrastructure. This creates unacceptable risks for Swiss companies under the EU AI Act, DSG/nFADP, and industry-specific regulations.

The Sovereign RAG Architecture on Exoscale SKS

Leading Swiss organisations are implementing a secure, high-performance RAG stack that runs entirely within dedicated tenants on Exoscale SKS. This architecture combines:

Private document ingestion and vectorisation pipelines
GPU-accelerated vector databases (such as Qdrant)
LangChain/LlamaIndex orchestration with full LangSmith observability
Isolated namespaces with strict access controls and encryption

All components stay under full Swiss control with zero data transfer to third countries.

How the Secure Sovereign RAG System Works

The architecture follows a clean, auditable pipeline:

Secure Ingestion Layer – documents are chunked, embedded, and stored privately
Hybrid Retrieval Agent – combines vector similarity search with metadata filtering
Generation & Citation Agent – produces accurate answers with direct source citations
Governance & Compliance Layer – enforces access policies, audit logging, and EU AI Act requirements

The entire system is monitored and governed through a central sovereign platform.

Proven Benefits for Swiss Organisations

Early adopters report:

• Significantly higher answer accuracy and trustworthiness
• Elimination of data leakage and compliance risks
• Faster knowledge access for employees and AI agents
• Full auditability for regulatory reviews
• Strong foundation for building compliant agentic AI applications

Why Sovereignty Is the Only Responsible Choice for RAG

In an era of strict data protection laws and increasing cyber threats, Swiss organisations cannot afford to entrust critical knowledge assets to foreign providers. Sovereign RAG on Exoscale SKS delivers both powerful AI capabilities and the peace of mind that comes with true data sovereignty.

Implementation Stack

LangGraphLlama 3 (Self-Hosted)ExoscalePostgreSQLn8n

Ready to implement a secure sovereign RAG architecture for your organisation?

Book a free 30-minute strategy call with one of our AI experts.

Ready to implement a secure sovereign RAG architecture for your organisation?

Book a free 30-minute strategy call with one of our AI experts.

Book 30-Minute Strategy Call

Measurable Impact

How Singularity's sovereign agentic workflows transformed operations and delivered concrete ROI for this implementation.

85%
3.2x
$1.5M
99.9%
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