--- id: "en/ai-standard-modules" title: "Standard version module" language: "en" description: "The standard version module summarizes 16 modules, their entry points and usage scenarios of Zhichao AI." canonical_url: "https://www.babel.cc/public/babelwiki/en/ai-standard-modules.html" markdown_url: "https://www.babel.cc/public/babelwiki/ai/en/ai-standard-modules.md" alternates: {"en": "https://www.babel.cc/public/babelwiki/ai/en/ai-standard-modules.md", "zh": "https://www.babel.cc/public/babelwiki/ai/zh/ai-standard-modules.md"} reading_note: "文档记录不等于当前部署能力；以实际版本、授权模块与配置为准。保留原文的可选、限制及待确认说明，勿补猜接口。 / Documentation is not a guarantee for every deployment. Preserve optional-module requirements, limitations and unresolved API contracts." --- # Standard version module The standard version module summarizes 16 modules, their entry points and usage scenarios of Zhichao AI. ![AI tools and agents](https://www.babel.cc/public/babelwiki/assets/images/ai-agent.webp) *AI tools and agent entry points, not the detailed interface of each module.* ## Standard version module list The following modules constitute the main functional scope of Zhichao AI Standard Edition. Actual entry and availability may be affected by version, entitlement, and deployment configuration. | Number | Module | Entry | Function | | --- | --- | --- | --- | | 1 | Zhichao AI Assistant | AI assistant entry at the top right | Conduct AI conversations based on the enterprise knowledge base, and answer questions in combination with online searches | | 2 | AI search | Search bar | The search results include AI search content and use natural language to find corporate information | | 3 | Zhisou | Zhichao AI section | Provides question answering, in-depth research and article writing capabilities | | 4 | Text-to-image search | Zhichao AI section | Search for pictures in the drive through text description | | 5 | Image-to-image search | Zhichao AI section, image thumbnail entry | Match similar images in the drive by uploading or selecting images | | 6 | Image OCR | Search, Zhichao AI section | Recognize the text in the image and let the image content participate in the search | | 7 | Document Assistant | File Preview Interface | Summary, Q&A and reading assistance based on the current document | | 8 | AI automatic tagging | File list | Match the closest tag in the tag library for the selected document | | 9 | Table Q&A | Excel file preview interface, Zhichao AI section | Q&A, table generation and function operations based on Excel | | 10 | Deep thinking | AI assistant, spreadsheet Q&A, document assistant | Switch to a deeper reasoning mode for complex problems | | 11 | Internet search | AI assistant | Search Internet content and answer with external knowledge | | 12 | In-depth research | Intelligent search in the Zhichao AI section | Research-based answers are formed through multiple rounds of search and comprehensive sorting | | 13 | Enterprise knowledge base | Backend server | Enterprise documents are automatically stored in the database to form a searchable knowledge base for question answering | | 14 | Knowledge base robot | Zhichao AI section "Create an agent" | Create a customizable agent or knowledge base robot | | 15 | PDF image search | Search bar | Search image content in PDF documents with images | | 16 | [MCP interface](https://www.babel.cc/public/babelwiki/en/mcp-integration.html) | Settings > API Keys; create a key, then copy API Key or the AI connection prompt | Provide permission-aware knowledge query, search, and file operations to Codex, WorkBuddy, OpenClaw, and other agents | ## Module relationship These 16 modules can be divided into four groups: the first group is conversation, search, document reading and spreadsheet Q&A for employees; the second group is multimodal retrieval for images, PDF images and OCR; the third group is enterprise knowledge base, knowledge base robots and agent configuration for administrators and implementation teams; the fourth group is MCP interfaces, third-party data sources and on-demand development capabilities for development and integration. ## Implementation suggestions - First, identify the organization’s main task: "finding files", "reading documents", "supporting customers", "analyzing spreadsheets" or "providing an external knowledge base". - Prioritize AI assistants, AI search, document assistants and spreadsheet Q&A for internal employees. - Prioritize text-to-image search, image similarity search, image OCR and PDF image search for material or brand teams. - Focus on configuring knowledge base robots and custom agents for customer service, pre-sales, training and policy Q&A scenarios. - For external agents that need knowledge or file operations, use the [BabelBird MCP quick start](https://www.babel.cc/public/babelwiki/en/mcp-integration.html) to plan credential scopes, folder access, and audit policy. ## Permissions and usage boundaries - Internal AI assistance, search and file references follow BabelBird permissions. Custom knowledge-base bots also have a knowledge scope and publication scope; anonymous publication should use knowledge suitable for that audience. - Uploaded BabelBird files that AI can read are automatically ingested and vectorized for AI assistance, AI search and image search. Ingestion does not make files public. A custom knowledge-base bot uses the file scope selected or uploaded for it. - External customer service, website embedding, third-party data sources, privately deployed models and GPU computing power are optional deployment or customization capabilities and should be subject to actual authorization, implementation plan and enterprise configuration. - When AI answers involve high-risk content such as contracts, finance, medical, legal, and engineering safety, the AI ​​output should be used as auxiliary information and reviewed by professionals. ## Related information - [Permission system](https://www.babel.cc/public/babelwiki/en/permissions.html) - [Security and Audit](https://www.babel.cc/public/babelwiki/en/security.html) - [BabelBird MCP](https://www.babel.cc/public/babelwiki/en/mcp-integration.html) - [FAQ: Deployment, AI and technical issues](https://www.babel.cc/public/babelwiki/en/faq-technical.html) - Public introduction: