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Plain-language explainers and buyer's guides on retrieval-augmented generation in Switzerland — what a Swiss RAG platform is, how GraphRAG and agentic retrieval work, and what Swiss data protection and financial regulation expect from an AI deployment.

RAG fundamentals

What is GraphRAG?

GraphRAG combines retrieval-augmented generation with a knowledge graph of entities and relations, so an AI can answer multi-hop questions that span m

What is agentic RAG?

Agentic RAG replaces single-pass retrieval with an autonomous plan-act-reflect loop: the AI decomposes a question into sub-queries, retrieves in paral

RAG vs. fine-tuning

Retrieval-augmented generation queries your documents at answer time; fine-tuning bakes knowledge into model weights. Costs, freshness, citations, dat

Multilingual RAG for Swiss documents

Swiss corpora are German, French, Italian and English at once. Why translate-then-search fails, how cross-lingual retrieval works, and what breaks on

Sovereignty & compliance

Sovereign AI in Switzerland

Sovereign AI means AI whose entire data path — inference, storage, backups — stays under one jurisdiction. Why Swiss organisations demand it, what the

Swiss RAG vs. US cloud RAG

A Swiss RAG platform and a US cloud RAG stack look identical on a feature slide. They differ in legal control, where embeddings and logs live, and who

RAG under the Swiss nFADP (nDSG)

How to run retrieval-augmented generation in compliance with the Swiss Federal Act on Data Protection (nFADP/nDSG): legal basis, cross-border transfer

RAG under FINMA outsourcing rules

Deploying retrieval-augmented generation in a Swiss bank or insurer is an outsourcing decision. Materiality, the sub-outsourcing chain, banking secrec

Buyer's guides

How to evaluate a Swiss RAG platform

Twelve questions that separate a genuinely sovereign Swiss RAG platform from cloud RAG with a Swiss flag — covering inference location, embeddings, en

Enterprise RAG in Switzerland

Build or buy, which deployment model, what it really costs, how long it takes and where projects fail. A practical guide to deploying enterprise retri

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