docs(ai): clarify analysis and privacy benefits

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@@ -10,19 +10,22 @@ ChatLab 先把聊天记录整理成结构化数据,提问时只取出真正相
## 为什么不直接把聊天文件发给 AI?
导出文件不是为 AI 准备的,整份上传常常会遇到三个问题:
把整份文件直接丢给 AI 分析,通常会遇到三个问题:
- **太大读不完**:几万条消息超出模型一次能处理的长度,被截断后容易漏掉关键内容。
- **夹带无关内容**:你只想问一件小事,却把大量无关的聊天也一并发了出去。
- **隐私没法把关**:聊天里可能混着密码、银行卡号、身份证、住址等敏感信息,整份上传前很难逐条检查。
- **隐私没法把关**:聊天里可能混着密码、银行卡号、身份证、住址等敏感信息,整份上传可能会把这些内容一并**暴露给外部 AI 服务商**。
想知道“我和小红最近在聊什么”,其实用不着每次都上传全部记录。
总而言之,把整份聊天记录直接交给 AI,**Token 花得更多,结果未必更准,隐私风险却更高**。
多数问题真正需要的,只是其中一小部分记录。
## ChatLab 怎么解决
- **先整理,再分析**:把不同平台的聊天记录统一成会话、成员、消息,结构清晰、可检索。
- **按需取数**:按时间、成员、关键词或统计条件,只取当前问题需要的那部分。
- **本地优先**:数据存在你自己的电脑上,交给 AI 前会先脱敏、按黑名单过滤。
- **专用工具**:提供搜索、上下文、统计分析、成员画像、图表绘制、RAG 检索等能力,AI 会根据问题按需调用,只取当前分析需要的数据。
- **隐私防护**:手机号、身份证号、银行卡号、邮箱、API Key 等敏感信息,会移除并替换成占位符,再交给 AI。
- **本地优先**:聊天数据库保存在你自己的电脑上,只有当前问题需要的少量结果,才会经过处理后交给 AI。
## 如何使用ChatLab提供的AI能力?
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## Why not send the file directly to an AI?
Chat exports aren't built for AI, and uploading the whole file usually runs into three problems:
Dropping the entire file into an AI for analysis usually creates three problems:
- **Too large to read:** tens of thousands of messages exceed what a model can take in at once, and truncation drops important context.
- **Carries unrelated content:** you only want to ask about one thing, but a heap of unrelated conversations goes along with it.
- **No way to vet privacy:** chat records may contain passwords, bank card numbers, ID numbers, or addresses, and it's hard to check every message before uploading the whole file.
- **No way to vet privacy:** chat records may contain passwords, bank card numbers, ID numbers, or addresses, and uploading the whole file may **expose that sensitive information to an external AI provider**.
To find out "what have Alice and I discussed recently?", you don't need to upload your entire history every time.
In short, handing an AI your entire chat history means **spending more tokens, getting results that may not be any better, and taking on more privacy risk**.
Most questions only require a small, relevant slice of the record.
## How ChatLab solves it
- **Organize, then analyze:** normalizes records from different platforms into sessions, members, and messages — structured and searchable.
- **Fetch on demand:** retrieves only the part your current question needs, by time, member, keyword, or statistical condition.
- **Local first:** your data stays on your own computer, and can be desensitized and blacklist-filtered before it reaches an AI.
- **Purpose-built tools:** provides search, context, statistical analysis, member profiling, chart generation, and RAG retrieval. The AI calls them as needed and retrieves only the data required for the analysis.
- **Privacy protection:** sensitive details such as phone numbers, ID numbers, bank card numbers, email addresses, and API keys are removed and replaced with placeholders before being sent to an AI.
- **Local first:** your chat database stays on your own computer. Only the small amount of information needed for the current question is processed and sent to an AI.
## How to use ChatLab's AI features
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@@ -10,19 +10,22 @@ ChatLab 會先把聊天記錄整理成結構化資料,提問時只取出真正
## 為什麼不直接把聊天檔案傳給 AI?
匯出檔案不是為 AI 準備的,整份上傳常常會遇到三個問題:
把整份檔案直接丟給 AI 分析,通常會遇到三個問題:
- **太大讀不完**:幾萬則訊息超出模型一次能處理的長度,被截斷後容易遺漏重要內容。
- **夾帶無關內容**:你只想問一件小事,卻把大量無關的聊天也一併傳了出去。
- **隱私沒法把關**:聊天裡可能混著密碼、銀行卡號、身分證、住址等敏感資訊,整份上傳前很難逐則檢查。
- **隱私沒法把關**:聊天裡可能混著密碼、銀行卡號、身分證、住址等敏感資訊,整份上傳可能會把這些內容一併**暴露給外部 AI 服務商**。
想知道「我和小紅最近在聊什麼」,其實用不著每次都上傳全部記錄。
總而言之,把整份聊天記錄直接交給 AI,**Token 花得更多,結果未必更準,隱私風險卻更高**。
多數問題真正需要的,只是其中一小部分記錄。
## ChatLab 怎麼解決
- **先整理,再分析**:把不同平台的聊天記錄統一成工作階段、成員、訊息,結構清晰、可檢索。
- **按需取資料**:依時間、成員、關鍵字或統計條件,只取目前問題需要的那部分。
- **本機優先**:資料存在你自己的電腦上,交給 AI 前會先脫敏、依黑名單過濾。
- **專用工具**:提供搜尋、上下文、統計分析、成員畫像、圖表繪製、RAG 檢索等能力,AI 會依問題按需調用,只取目前分析需要的資料。
- **隱私防護**:電話號碼、身分證號、銀行卡號、電子郵件、API Key 等敏感資訊,會移除並替換成佔位符,再交給 AI。
- **本機優先**:聊天資料庫保存在你自己的電腦上,只有目前問題需要的少量結果,才會經過處理後交給 AI。
## 如何使用 ChatLab 提供的 AI 能力?