Migrate Embeddings Without Drift
Plan an embedding-model migration with parallel indexing, evaluation, and cutover guardrails.
The migration risk New documents and old documents are embedded by different models but searched as one space. The result feels random because the comparison geometry is no longer stable. FMEA for migration Failure mode -> effect -> detection -> mitigation Name the migration failures before they reach users. Shortcut Start writing new vectors into the old field A migration that can be measured and reversed. A new embedding model is a new retrieval system until proven equivalent. 01 Separate space 02 Replay evals 03 Now you try Failure mode The new model has a different dimension and recommended metric.
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