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AnswerDesk AI Product Knowledge

Inspect the original source, the normalized retrieval document, and the chunks stored for vector search.

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Normalized Markdown

The AI model only restructures content for retrieval. It must not add or remove facts; LangChain chunks this version.

Used For Vector Search

AnswerDesk AI Product Knowledge

AnswerDesk AI is a deployable AI customer support system for one client at a time. It is not positioned as a multi-tenant SaaS demo.

Core Capabilities

  1. Website chat widget
  2. Telegram Bot
  3. REST API
  4. Fixed FAQ answers
  5. RAG knowledge retrieval
  6. AI playbooks
  7. Human handoff
  8. Inbox review
  9. Action traces
  10. Reports
  11. Deployable support workflows

Knowledge Base

Stores factual materials such as product docs, SOPs, PDFs, policies, and FAQs.

AI Playbooks

Define how the AI should handle cases, what it must not promise, and when to hand off to a human.

Hybrid RAG

Combines vector retrieval, keyword retrieval, and reciprocal-rank fusion so answers can match both semantic questions and exact terms such as SKUs, policy names, order words, or product names.

Human Handoff

Can be triggered by:

  1. Exact keywords
  2. Semantic classification
  3. Low confidence
  4. Sensitive issues
  5. Missing knowledge
  6. Customer request

When configured, handoff can emit a webhook event to the client's system.

Language Support

The system supports English and Chinese data isolation. Admin language controls which knowledge, FAQ, playbooks, conversations, and reports are shown and used.

Model Layer

The model layer is replaceable. The current deployment can use a chosen AI model behind the same product architecture.

Original Content

The source material uploaded or pasted into the system. Keep it read-only for factual review.

# AnswerDesk AI Product Knowledge
AnswerDesk AI is a deployable AI customer support system for one client at a time. It is not positioned as a multi-tenant SaaS demo.
Core capabilities: website chat widget, Telegram Bot, REST API, fixed FAQ answers, RAG knowledge retrieval, AI playbooks, human handoff, inbox review, action traces, reports, and deployable support workflows.
The knowledge base stores factual materials such as product docs, SOPs, PDFs, policies, and FAQs. AI Playbooks define how the AI should handle cases, what it must not promise, and when to hand off to a human.
Hybrid RAG combines vector retrieval, keyword retrieval, and reciprocal-rank fusion so answers can match both semantic questions and exact terms such as SKUs, policy names, order words, or product names.
Human handoff can be triggered by exact keywords, semantic classification, low confidence, sensitive issues, missing knowledge, or customer request. When configured, handoff can emit a webhook event to the client's system.
The system supports English and Chinese data isolation. Admin language controls which knowledge, FAQ, playbooks, conversations, and reports are shown and used.
The model layer is replaceable. The current deployment can use a chosen AI model behind the same product architecture.