An Internal-Documents Q&A Bot Wired into Chat
What this scenario solves
Staff cannot find policy and process documents, so they keep asking colleagues the same questions dozens of times.
Tool stack
Not the only solution, but a stack we have verified end to end. Each tool links to its full review, including who it is not for.
What you end up with
Q&A directly inside your chat app, answers citing document and paragraph, with unmatched questions tracked to close documentation gaps.
Full steps
- 01環境準備
- 02安裝 MemoryHub
- 03MCP 四平台配置
- 04Dashboard 使用指南
- 05自動啟動配置
- 06性能優化建議
- 07卸載
Articles carrying the full content
- MemoryHub Practical Installation and Complete Usage Guide: From Zero to Four Platform Automatic Memory Capture
A step by step guide to installing MemoryHub v2.0: from Docker environment preparation, one click pip installation, four platform MCP configuration, Dashboard usage tips, to the complete process of daily maintenance and troubleshooting.
2026-05-2120 minRead - Build Your First AI Workflow Without Writing Code
You can build a usable AI application with your own hands even if you cannot write code. Using a customer-support knowledge-base Q&A as the scenario and no-code platforms like Dify, Coze, and n8n, this article walks you through six steps — prepare the data, build the knowledge base, set the prompt, test, launch, monitor — each concrete enough to follow, without depending on interface details that go stale.
2026-09-3012 minRead - Three Levels of AI: Chat, Collaboration, and Agent
They are all called AI, yet their capabilities and cost structures differ enormously. This article breaks the tools on the market into three levels — chat, collaboration, and agent — and gives you a decision table to first clarify which level a need belongs to, then talk tool selection and budget, so you avoid spending money on the wrong tool.
2026-09-308 minRead - A Framework for Choosing AI Tools: Five Questions That Eliminate 90% of Options
Facing a dizzying list of AI tools, trialing them one by one is the most expensive way to choose. This article gives you five screening questions — data sensitivity, error tolerance, integration needs, usage scale, and cost of failure — each mapped to which category of tool to pick, and ends with a decision-flow table that walks you through the whole judgment.
2026-09-3010 minRead - Enterprise Data Security Basics: What Data Should Never Be Fed to AI
Employees pasting customer personal data into free AI tools is one of the most common and hardest-to-prevent data leakage paths in enterprises. This article provides a four-tier data classification standard, a 'never upload' red-line checklist, a comparison of enterprise vs. consumer terms, local deployment options, and a question list for IT and legal teams.
2026-09-308 minRead
Adjacent scenarios
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Level: Intermediate · Tracks: Business Track · Last verified: 2026-09-29