Why Your RAG Retrieves Wrong Documents—and How Reranking Fixes It

RAG systems often surface the wrong document even when the right answer exists in the database—a problem that better embeddings alone cannot solve. Reranking using cross-encoders evaluates candidates with full context and is the single highest-impact upgrade to any retrieval pipeline. For applications where accuracy is critical, this technique can mean the difference between a system users trust and one that loses credibility.