Query claims in natural language with Amazon Bedrock Knowledge Bases

Query claims in natural language with Amazon Bedrock Knowledge Bases Query claims in natural language with Amazon Bedrock Knowledge Bases Claim answers are scattered across adjuster diary entries, repair estimates, police reports, payment ledgers, and scanned attachments rather than one searchable field. A policyholder might ask whether a claim was approved, while an adjuster might need every open auto claim over $10,000 from last month.

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• Query claims in natural language with Amazon Bedrock Knowledge Bases Claim answers are scattered across adjuster diary entries, repair estimates, police reports, payment ledgers, and scanned attachments rather than one searchable field.
• A policyholder might ask whether a claim was approved, while an adjuster might need every open auto claim over $10,000 from last month.
• Both tasks require finding and combining evidence quickly and accurately.
• Retrieval Augmented Generation (RAG) uses retrieved documents to ground model responses.
• Amazon Bedrock Knowledge Bases is the fully managed RAG capability for documents.
• Amazon Bedrock handles parsing, chunking, embeddings, and vector storage, so you can build a conversational interface that returns cited answers from claim files.