#Information Retrieval
Hybrid Databases Were the Wrong Fix for Requirements RAG
A negative infrastructure result from a requirements RAG lab: Postgres, ParadeDB, and OpenSearch could host useful pieces, but none replaced the current retrieval stack without losing ranking quality or evidence bundles.
Read Post
I Flattened 13,244 Requirements Into Chunks. 97% Lost Their Meaning.
A practical retrieval study over structured automotive requirements: why flatten-and-chunk failed, where ordinary top-k search stopped being the right tool, and how query routing improved both quality and latency.
Read Post
I Tested a Simple RAG Idea: One Summary per Document. It Was Useful, But Not Enough.
A practical retrieval experiment: can an LLM-generated document summary replace chunk-level search? On a 5,000-document corpus, the answer was measurable — useful signal, clear ceiling, and a better baseline.
Read Post