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RAG Architectures

Retrieval-augmented generation from ingestion through to the answer. The series treats chunking, embeddings, vector stores, reranking and evaluation as architecture questions, because they are what decides whether a knowledge base returns dependable answers or merely plausible ones.

9 articles

Baidu OCR in the stack: why classic text recognition stays alongside visual search

Baidu OCR in the stack: why classic text recognition stays alongside visual search OCR is not dead. PaddleOCR-VL delivers searchable text where visual search alone falls short. Tools •2 min 06/25/2026

F-RAG (RAG-Fusion): how it differs from plain RAG

F-RAG (RAG-Fusion): how it differs from plain RAG RAG-Fusion runs several query variants and fuses the results with reciprocal rank fusion. Better recall, some drift risk. Methodology •2 min 06/25/2026

Late interaction explained: why Qdrant and ColQwen build the better knowledge base

Late interaction explained: why Qdrant and ColQwen build the better knowledge base Late interaction compares every search term against every page excerpt. Qdrant stores that natively. Methodology •2 min 06/25/2026

The OCR-free document stack 2026: ColPali, ColQwen, ModernVBERT, and Qdrant

The OCR-free document stack 2026: ColPali, ColQwen, ModernVBERT, and Qdrant Visual retrieval models search the page as an image instead of via OCR. A sober overview. Methodology •3 min 06/25/2026

Query decomposition and the advanced-RAG toolkit: match the method to the failure

Query decomposition and the advanced-RAG toolkit: match the method to the failure Query decomposition, HyDE, RAG-Fusion, GraphRAG each fix one failure. The sophisticated 2026 RAG knows when to use none. Methodology •4 min 06/25/2026

The end of OCR? Visual document search and what it changes for the Mittelstand

The end of OCR? Visual document search and what it changes for the Mittelstand Visual retrieval models find tables and scans where OCR-based RAG fails. What that means in practice. AI •2 min 06/25/2026

Subquadratic LLMs: cheaper long context for on-prem RAG

Subquadratic LLMs: cheaper long context for on-prem RAG Subquadratic models lower the cost of long context. A real lever for on-prem RAG, but still young. Research •5 min 06/18/2026

What is RAG? Retrieval-augmented generation explained for the Mittelstand

What is RAG? Retrieval-augmented generation explained for the Mittelstand RAG couples a language model to your own documents, so answers stay verifiable and current. AI •4 min 06/16/2026

Retrieval-Augmented Generation, and why it underpins sovereign AI

Retrieval-Augmented Generation, and why it underpins sovereign AI RAG grounds a model's answers in retrieved sources, cutting hallucination and staleness. Why it underpins sovereign AI. AI •5 min 04/01/2024

Wayne Dyer

“If you change the way you look at things, the things you look at change.”