PRODUCTION SCENARIO
A manufacturer is loading 1,200 PDF maintenance manuals into an Amazon Bedrock knowledge base. During ingestion, the job splits each manual into pieces before it creates embeddings.
What is the purpose of the chunking step in this pipeline?
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Answer: To split documents into manageable pieces that are embedded and indexed
During ingestion, Amazon Bedrock splits content into manageable chunks, converts each chunk 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 a specific relevant passage instead of an entire manual.