From RAG to Production: Lessons Learned at Scale
Chunking Strategy Matters More Than Model Choice
The single highest-leverage decision in a RAG pipeline is how you chunk your source documents. Overlapping semantic chunks with metadata preservation consistently outperform fixed-size token windows, especially on heterogeneous corpora.
Hybrid Retrieval Beats Pure Vector Search
Combining BM25 keyword search with dense vector retrieval and a cross-encoder reranker produces significantly better recall than any single retrieval method. We see ten to twenty percent improvements in answer accuracy with this hybrid approach across every deployment.
Monitoring Retrieval Quality
In production, retrieval quality drifts as source documents are updated. We run automated evaluation suites nightly that compare retrieval results against curated test sets and alert when recall drops below acceptable thresholds.
ActiveMotion Team
AI Research
The ActiveMotion engineering and research team
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