Naive RAG hits 60% accuracy. These nine techniques — chunking strategy, re-ranking, hybrid search, metadata filtering — pushed our enterprise platform to 91%.
Baseline RAG and why it plateaus at 60%
Content for this section is coming soon. This article by Anna K. covers important aspects of baseline rag and why it plateaus at 60%.
Semantic chunking vs. fixed-size: real benchmarks
Content for this section is coming soon. This article by Anna K. covers important aspects of semantic chunking vs. fixed-size: real benchmarks.
Hybrid search with BM25 and dense embeddings
Content for this section is coming soon. This article by Anna K. covers important aspects of hybrid search with bm25 and dense embeddings.
Re-ranking with cross-encoders for precision
Content for this section is coming soon. This article by Anna K. covers important aspects of re-ranking with cross-encoders for precision.
Metadata filtering and permission-aware retrieval
Content for this section is coming soon. This article by Anna K. covers important aspects of metadata filtering and permission-aware retrieval.
Evaluation framework: measuring RAG accuracy at scale
Content for this section is coming soon. This article by Anna K. covers important aspects of evaluation framework: measuring rag accuracy at scale.