PandaWiki

PandaWiki

PandaWiki is a knowledge base construction system launched by Changting Baizhiyun. With the help of large models, it provides AI creation, AI question answering and AI search. It can quickly build product documents, FAQs and blogs, and supports open source and multi-model access.

AI Note Taker#Knowledge Base#AI Q&A#Open Source

Updated: 2026-10-26

What is PandaWiki?

PandaWiki is a knowledge base construction system launched by Changelong Baizhiyun. Officially, it is described as "leveraging the power of large models to provide capabilities such as AI creation, AI question answering, and AI search, enabling you to quickly possess intelligent product documentation, FAQ, and blog systems". Unlike personal notes, it is more of a "website-building" knowledge base: it can serve as an internal enterprise wiki, and also be used externally for product documentation and customer service Q&A. According to its official website, it is compatible with Markdown and HTML, can be made into web page widgets or chatbots for DingTalk, Lark, and WeChat Work, and also offers a large number of practical cases.

Who is it for?

  • Technical teams that need to quickly build external product documentation, FAQs and blogs.
  • Enterprises that want to internalize their internal knowledge into a searchable wiki.
  • Organizations that want to use chatbots for customer service Q&A and integrate with DingTalk/Lark.
  • Knowledge base managers who want open-source controllability and self-deployment.

Key features

6
1

AI-driven intelligence

Provides AI-powered intelligent Q&A, AI intelligent search and AI-assisted creation, reducing the cost of content maintenance.

2

Rich Text Editing

Compatible with Markdown and HTML, supports export to various formats such as Word, PDF, and Markdown, facilitating migration.

3

Third-Party Integration

Can be made into a web widget to be embedded on other websites, or into chatbots for DingTalk, Lark, WeChat Work, etc.

4

Multi-source Import

Supports importing content through web page URLs, website Sitemaps, RSS subscriptions and offline files, and old materials can also be reused.

5

Open Source & Multi-Model Support

The official states that it is an open-source project available for free use, and it supports integration with official BaiZhiYuan models, local models, and third-party large models such as OpenAI and DeepSeek.

6

Appearance Customization

Offers rich appearance customization options such as layout, colors, fonts, and positions to align with your brand.

How to use PandaWiki

  • Try the open-source version first: The official states that it is free to use as an open-source project, and deploying it on a local or self-owned environment is the most secure option with full data control.
  • Use import instead of manual entry: Batch import existing documents via URLs, Sitemaps or RSS, which is much faster than writing from scratch.
  • Integrate large models with compliance in mind: If integrating third-party or local models, confirm their data flow and authorization.
  • the official question-answering capability is subject to the actually deployed model, and the rules may be adjusted.
  • Recheck before going online.
  • Organize the structure before import: Use Sitemap or category-based import first to avoid the knowledge base being cluttered from the start.
  • Chatbots should be launched on a small scale first: Test DingTalk/Lark bots internally before opening them up to users.

Traffic & popularity

Data month Sep 2026

PandaWiki receives about 24.0K visits per month and ranks #1,335,234 worldwide.

Monthly visits
24.0K
▼ 20.6% vs last month
▼ 1.3% vs 3 mo. ago
Global rank
#1,335,234
of all websites
Bounce rate
32.9%
leave after one page
Avg. duration
1:09
per visit
Pages / visit
3.09
per visit
Country rank
#65,010
in its top market

Monthly visits

12 months
40.0K30.0K20.0K10.0K0
Oct 2025Apr 2026Sep 2026

Traffic sources

  • Referrals55.5%
  • Direct34.6%
  • Search8.1%
  • Social1.6%
  • AI assistants0.1%

Top countries

  • China76.6%
  • India3.2%
  • Taiwan, China2.9%
  • Hong Kong, China2.1%
  • Brazil1.7%

Estimated from third-party traffic data.

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PandaWiki
24.0K · #1,335,234
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