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Qlik 分享 Qlik Answers 的企業 AI 架構與客戶成效：以 Amazon Bedrock 串接多種資料來源
AWS 的案例報導指出，Qlik Answers 已於 2026 年 2 月正式推出，建立在 Amazon Bedrock 上，並從知識庫、分析應用、詞彙表與文件提供回答。報導也列出 Bystronic、Lintech International 與 TouchPoint Support Services 的使用案例。
完整報導
AWS 於 10 月 7 日刊出 Qlik 的案例報導，說明 Qlik Answers 如何以 Amazon Bedrock 為基礎，為 Qlik 超過 40,000 名客戶提供涵蓋結構化與非結構化企業資料的回答。Qlik Answers 已於 2026 年 2 月正式推出；AWS 也指出，開啟 agentic tools 的 Qlik Cloud 帳戶中，多數帳戶會積極使用這些工具。
Qlik Answers 可將問題導向知識庫、即時分析應用、詞彙表定義或文件。非結構化文件的索引與檢索由 Amazon OpenSearch Service 處理；Qlik 則透過其 LLM gateway 連接 Amazon Bedrock。Qlik 也對每一筆請求與回應套用 Amazon Bedrock Guardrails，包括內容過濾與 grounding 驗證。
AWS 報導列出數個客戶案例：Bystronic 在 15 分鐘內部署 AI 聊天機器人，讓員工查詢即時營運資料並取得附來源的回答。Lintech International 索引超過 17,000 份技術文件，表示回應時間加快 75%，並稱每週最多為業務主管省回七小時。TouchPoint Support Services 則在 650 個醫療服務據點，使用 Qlik Answers 為 15,000 名員工提供符合規範的指引。
Qlik 表示正評估在特定工作負載採用 Amazon Bedrock AgentCore，以降低營運負擔。這與 AWS 先前介紹的 HEMA 案例有所不同：該案例描述 HEMA 已以 AgentCore 和 MCP 建置內部助理 HAL。兩個案例呈現的是不同企業採用 AWS 代理工具的進程；Qlik 的報導重點仍是 Qlik Answers 的資料路由、安全控制與客戶使用結果。
為什麼值得注意
這篇案例提供了比單純產品功能描述更具體的企業部署參考：資料如何進入回答、文件檢索由何種服務支援，以及安全防護如何套用至請求與回應。客戶案例中的部署時間、文件數量與回應成效，也讓讀者能辨識 Qlik 所報告的實際使用範圍；這些數字仍屬案例中的客戶回報。
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
1How Qlik built grounded, enterprise-scale AI with Amazon Bedrock
Sunil Yerkola
“Qlik built Qlik Answers on Amazon Bedrock to give its 40,000+ customers grounded, sourced answers across structured and unstructured enterprise data. Learn how a layered, multi-agent architecture with cross-Region inference and Amazon Bedrock Guardrails delivers trusted AI at global scale.”
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