常見問題｜FAQ
此處，我們將會說明一些常見問題，讓您更快速了解 LumineOne AI。若您有其他疑問，也歡迎回饋給我們～
In this section, you will learn more about LumineOne AI by some frequently asked questions. If you have any other questions or feedbacks, please feel free to provide us~
一般 / General
為什麼企業需導入 LumineOne AI?/ Why LumineOne AI?
越來越多企業導入 AI 助理，不僅提升處理效率，也大幅解省人力工時。然而，AI 助理恐導致機密外洩，而自建 AI 成本極高，且結合知識庫的機器人門檻高追趕新模型導致維運吃力。
Lumine AI 提供四大優勢：1) 自帶 GCP 私有雲環境，保護機密不被 AI 獲取；2) 快速訓練企業知識庫，重複運用，免去繁瑣優化；3) 跨裝置多元互動整合；4) 易於使用的管理平台介面！
The increasing adoption of AI assistants by companies not only improves processing efficiency but also significantly reduces labor costs. However, AI assistants may lead to the leakage of confidential information, and building a custom AI is expensive. Additionally, integrating a knowledge base with robots has a high technical threshold, and keeping up with new models makes maintenance and operation challenging.
As a result, Lumine AI provides 4 advanatges: 1) Own GCP private cloud environment, which protects sensitve data from AI；2) Rapidly train the corporate knowledge base；3) Cross-device multi-channel interaction integration；4)User-friendly management platform interface！
Lumine AI 提供四大優勢：1) 自帶 GCP 私有雲環境，保護機密不被 AI 獲取；2) 快速訓練企業知識庫，重複運用，免去繁瑣優化；3) 跨裝置多元互動整合；4) 易於使用的管理平台介面！
The increasing adoption of AI assistants by companies not only improves processing efficiency but also significantly reduces labor costs. However, AI assistants may lead to the leakage of confidential information, and building a custom AI is expensive. Additionally, integrating a knowledge base with robots has a high technical threshold, and keeping up with new models makes maintenance and operation challenging.
As a result, Lumine AI provides 4 advanatges: 1) Own GCP private cloud environment, which protects sensitve data from AI；2) Rapidly train the corporate knowledge base；3) Cross-device multi-channel interaction integration；4)User-friendly management platform interface！
LumineOne AI 如何保護企業資料? / How can LumineOne AI protect enterprise's sensitive data?
我們使用RAG機制，保護企業知識與機密，將企業知識儲存於獨立資料庫，並作向量化處理後，再依提問的提示詞語意，產生整合後的提示詞與對應KM詢問生成式AI。
We use the RAG (Retrieval-Augmented Generation) mechanism to protect corporate knowledge and confidentiality. Corporate knowledge is stored in a separate database, vectorized, and then, based on the semantic meaning of the query prompt, integrated prompts are generated along with corresponding KM (Knowledge Management) queries for the generative AI.
We use the RAG (Retrieval-Augmented Generation) mechanism to protect corporate knowledge and confidentiality. Corporate knowledge is stored in a separate database, vectorized, and then, based on the semantic meaning of the query prompt, integrated prompts are generated along with corresponding KM (Knowledge Management) queries for the generative AI.
操作 / Operation
一般型與知識型機器人的差別?/ What's the difference between Common and Knowledge Bots?
一般型機器人常用於廣泛問答，不需要另外學習的資料庫，如翻譯機器人、聊天機器人。而知識型機器人則需有學習資料，以利產出正確回覆，如分機機器人、門市商品查詢機器人、法規機器人。
General Bots can generate responses without specific data, such as Translation Bot and Chat Bot. Knowledge Bot will response specific answers after learning data, such as Ext No Searching Bot, Store Product Searching Bot, and Regulations Searching Bot.
General Bots can generate responses without specific data, such as Translation Bot and Chat Bot. Knowledge Bot will response specific answers after learning data, such as Ext No Searching Bot, Store Product Searching Bot, and Regulations Searching Bot.
為什麼我設定完機器人，卻看不到該機器人?/ Why can't I see the Bot I just created?
請於「機器人管理」介面的「角色」頁籤，確認是否加入可使用該機器人的角色。
Please check in "KM" sheet of the "Bots" page to see if the corresponding roles are added.
Please check in "KM" sheet of the "Bots" page to see if the corresponding roles are added.
聯絡我們 / Contact Us
聯絡支援 / Contact Support
如有任何問題或需要技術支援，歡迎隨時與我們聯繫。
For questions or technical support, please contact us at:
📧 ec-aiportal@pic.net.tw