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AWS 示範以 Amazon Bedrock Knowledge Bases 建立自然語言理賠問答助理
AWS 於 2026 年 9 月 30 日發布技術指南，示範如何建立可用自然語言回答問題並附上引用的對話式理賠助理。內容涵蓋從 Amazon S3 匯入理賠文件、使用 AgenticRetrieveStream API 查詢，以及多輪追問、metadata 篩選與情境 grounding 防護。
完整報導
AWS 於 2026 年 9 月 30 日發布技術指南「Query claims in natural language with Amazon Bedrock Knowledge Bases」，說明如何以 Amazon Bedrock Knowledge Bases 建立對話式理賠助理。指南示範助理如何回答自然語言問題並附上引用，讓回答能連回相關資料。
實作流程涵蓋從 Amazon S3 匯入理賠文件，並透過 AgenticRetrieveStream API 提出查詢。指南也包括多輪對話中的後續問題，展示使用者可在同一段互動中接續詢問。
在查詢控制方面，指南介紹 metadata 篩選與情境 grounding guardrails。這些步驟使範例不只涵蓋問答介面，也納入文件檢索條件與回答 grounding 的設定。前一天，AWS 也發布了以自然語言詢問影片內容的技術指南；該方案由 Strands Agents SDK 代理程式協調 Amazon Bedrock、Amazon Rekognition 與 Amazon Transcribe。兩篇指南處理的資料與架構不同，但都展示了 AWS 如何以對話式提問串接其 AI 服務。
為什麼值得注意
理賠文件問答的關鍵不只是能以自然語言提問，還包括答案附有引用、可設定 metadata 篩選，並處理多輪追問與 grounding。這份指南把這些實作環節放在同一個範例中，對評估如何將文件檢索納入對話式理賠工作流程具有直接參考價值。
來源證據
先看主要證據，再查看佐證來源與來源脈絡。
主要證據
1Query claims in natural language with Amazon Bedrock Knowledge Bases
Shreya Pawaskar
“This technical how-to builds a conversational claims assistant on Amazon Bedrock Knowledge Bases that answers natural-language questions with citations. It covers ingesting claim documents from Amazon S3, querying with the AgenticRetrieveStream API, multi-turn follow-ups, metadata filters, and contextual grounding guardrails.”
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