The hidden cost of changing embedding models in RAG systems

Production RAG systems can get stuck when a better embedding model appears, because switching may require every stored document to be processed again. For a large corpus, this can mean re-embedding and rebuilding the search index for millions of documents. Some teams may keep an older model simply because the migration is too costly or risky.

Possible approaches include re-embedding everything overnight, creating a separate shadow index and switching over later, or building a custom migration path. The real concern is whether the move causes downtime, high cost, or an operational incident, and whether existing tools or services can reduce the manual work.