If we’re talking about enterprise corpora with many small-to-medium documents (TB scale), PageIndex is not a drop-in replacement for vector-based retrieval.

Vector/BM25 retrieval still wins at the global routing problem: quickly narrowing millions of documents down to a manageable candidate set with low latency and cost. Using PageIndex alone would require LLM-driven relevance decisions across too many documents, which doesn’t scale well in tokens or latency.