Reranking Consultation — Choose the Right Reranker for RAG

I will assess your retrieval pipeline and deliver a written reranking consultation — covering whether adding a cross-encoder reranker would improve your retrieval quality, which reranking model is most appropriate for your content and query types, the latency and cost impact of reranking, and a recommended integration approach. Reranking adds latency and cost to retrieval pipelines in exchange for precision improvement — the right decision depends on your precision baseline (reranking delivers diminishing returns when bi-encoder retrieval is already highly precise), your latency budget (cross-encoder inference adds 50-200ms depending on the model and document length), and your cost tolerance.

The consultation covers your current retrieval precision assessment, reranking precision improvement estimate, latency impact analysis, cost analysis, model recommendation, and integration approach.