Full Retrieval Reranking System — Multi-Stage Precision Pipeline

I will build a complete multi-stage retrieval and reranking system — covering first-stage hybrid retrieval for recall, a cross-encoder reranking stage for precision, an optional LLM reranking stage for complex queries, result caching, and a monitoring system tracking precision and latency at each pipeline stage. Multi-stage retrieval pipelines produce the highest-quality retrieval by applying the right tool at each stage — first-stage retrieval optimises for recall (finding all potentially relevant documents), cross-encoder reranking optimises for precision (correctly ordering the relevant documents), and optional LLM reranking handles complex queries where cross-encoder understanding is insufficient.

The system covers first-stage hybrid retrieval, cross-encoder reranking, adaptive LLM reranking for complex queries, result caching, stage-level monitoring with precision and latency tracking, and end-to-end quality evaluation.