Editorial desk
RAGStackGuide Editorial
The editorial desk that publishes RAGStackGuide. It is a byline for the site's editorial process, not a person, and this page carries no author biography because there is no individual author to describe.
How this desk works
- Articles are researched from primary sources: vendor and project documentation, published standards and specifications, release notes, advisories, and measurements published by the people who took them.
- Drafts are produced with AI assistance and then edited against those same sources before publication.
- Nothing published here claims hands-on lab testing, benchmarking, or first-hand measurement. Where a figure comes from a datasheet or someone else's test, the article names the source.
- Corrections go to [email protected] and are made on the affected page. Funding is set out on the disclosure page.
Posts (4)
- vector-databases
Qdrant vs Milvus vs Pinecone: Vector DB Comparison
How Qdrant, Milvus and Pinecone differ on deployment, index types, quantisation, filtering and hybrid search, and which one fits which kind of RAG workload.
- pipeline-design
RAG Pipeline Architecture: Components and Build Order
The seven components of a RAG pipeline, what each one decides, and the order to build them in so retrieval quality is measurable before you tune anything.
- troubleshooting
RAG Retrieval Debugging: Why Results Come Back Wrong
A stage-by-stage checklist for RAG retrieval failures: isolate the fault to extraction, chunking, embedding, filtering or ranking before changing anything.
- retrieval-quality
RAG Chunking Strategy: Picking Chunk Size and Overlap
A practical guide to RAG chunking: working chunk sizes, how much overlap to use, structure-aware splitting, and the metadata that decides retrieval quality.