PRODUCTION SCENARIO
A manufacturer is loading 1,200 PDF maintenance manuals into an Amazon Bedrock knowledge base. A technician who asks about one procedure should get that procedure back, not the whole manual.
What does the chunking step during ingestion accomplish?
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Answer: It splits documents into pieces that are embedded and indexed
During ingestion Amazon Bedrock splits content into manageable chunks, converts each into an embedding and writes it to the vector index while keeping a mapping back to the original document. That is what lets retrieval return one procedure instead of a whole manual. Removing sensitive information is a separate redaction step; chunking makes no judgement about content. Ranking passages happens at query time, after retrieval. Chunking compresses nothing, and the index grows with the chunk count.