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Knowledge Base

Definition

A knowledge base is an organized collection of information, typically help articles, FAQs, guides, and documentation, that enables customers to find answers independently. In modern support, knowledge bases also serve as the training data for AI chatbots.

How it works

A knowledge base serves two purposes in 2026:

  1. Self-service: Customers browse and search articles to find answers without contacting support. A well-organized KB with good search answers many questions before they become tickets.
  1. AI training data: The knowledge base content powers RAG-based AI chatbots. Articles are processed, chunked, and embedded so the AI can search and reference them when answering questions. Better KB content directly results in better AI answers.

Knowledge base software typically includes a content editor, category organization, search, custom domains, and analytics on article performance.

Why it matters

A knowledge base is the foundation of scalable customer support. It reduces ticket volume through self-service, trains AI chatbots to answer accurately, and provides a single source of truth for your support team. Without a knowledge base, AI chatbots have nothing to retrieve from, and customers have no self-service option.

How Chatsy uses it

Chatsy includes a full knowledge base CMS with articles, categories, custom domains, and rich text editing. Knowledge base content is automatically processed and indexed for AI retrieval. When you update an article, the AI immediately reflects the change, no manual re-training needed.

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What else should I know about Knowledge Base?

Start with 20-30 articles covering the most common support questions for immediate impact

Key takeaways

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Add your help content, ask the questions on this page, and check every answer before you publish.

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Example scenarios

  1. 01

    Public help center for SaaS product

    A SaaS company publishes 150 help articles organized by category (Getting Started, Billing, Integrations). Customers search and browse articles directly, deflecting 25% of potential tickets. The same content powers their AI chatbot for an additional 50% deflection.

  2. 02

    Internal IT knowledge base

    An IT department maintains a private knowledge base covering VPN setup, software installation, and security policies. New employees use the AI chatbot to get instant answers to onboarding questions, reducing IT ticket volume by 40%.

  3. 03

    Product documentation as AI training data

    A hardware company uploads its 200-page product manual as knowledge base articles. The AI chatbot can now answer specific technical questions like "what is the maximum operating temperature for Model X?", pulling the exact spec from the manual.

Key takeaways

  • A knowledge base serves dual purposes: customer self-service and AI chatbot training data
  • Start with 20-30 articles covering the most common support questions for immediate impact
  • Well-structured, focused articles produce better AI retrieval results than long, dense documents
  • Knowledge base content should be updated regularly, outdated articles produce outdated AI answers
  • Modern platforms automatically re-index content for AI retrieval when articles are updated

Frequently asked questions

Start with 20-30 articles covering your most common support questions. Even a small KB can answer a meaningful share of repeat questions and improve AI chatbot accuracy. Quality matters more than quantity.

Public for customer-facing support (help center). Private for internal documentation (IT helpdesk, employee handbook). Chatsy supports both, public KB with optional custom domain, and workspace-level access for internal content.

Write short, focused articles (300-800 words) covering one topic each. Use clear headings, bullet points, and direct language. Avoid jargon and walls of text. Structure articles as questions and answers when possible, this format maps naturally to how customers ask questions.

Most platforms support importing from various sources. Chatsy allows importing content from URLs, files, and documents. You can also use the API to programmatically sync content from external documentation systems like Confluence or Notion.

Related terms

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Further reading

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