---
id: "en/ai-overview"
title: "Zhichao AI Overview"
language: "en"
description: "Completely introduces the positioning, modules, capability boundaries, permission control, training materials and applicable scenarios of Zhichao AI."
canonical_url: "https://www.babel.cc/public/babelwiki/en/ai-overview.html"
markdown_url: "https://www.babel.cc/public/babelwiki/ai/en/ai-overview.md"
alternates: {"en": "https://www.babel.cc/public/babelwiki/ai/en/ai-overview.md", "zh": "https://www.babel.cc/public/babelwiki/ai/zh/ai-overview.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."
---

# Zhichao AI Overview

Zhichao AI is a collection of AI capabilities built by BabelBird Enterprise Drive around enterprise documents, knowledge base, search, customer service and data analysis. It is not an isolated chat tool, but is combined with BabelBird's file storage, permission system, search engine, material library, project collaboration, online preview and private deployment capabilities to allow AI to work on the company's existing data.

![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.*

## Module Overview

| Module | Main capabilities | Typical scenarios |
| --- | --- | --- |
| [AI Search](https://www.babel.cc/public/babelwiki/en/ai-search.html) | Learn corporate documents, search and answer questions in natural language, support follow-up questions, source citations, multimodal retrieval and permission checks | Enterprise knowledge and policy queries, project document retrieval, technical Q&A |
| [AI Image Search](https://www.babel.cc/public/babelwiki/en/ai-image-search.html) | Search for images in the drive through text description or uploaded images. The search scope is filtered by permissions | Material library, brand assets, design gallery, image files |
| [Intelligent Data Assistant](https://www.babel.cc/public/babelwiki/en/ai-data-assistant.html) | Analyze Excel/table data, query, analyze, and generate charts across multiple Excel files, and support third-party URL data sources | Sales reports, project ledgers, supply chain data, and operational statistics |
| [Customized agent and knowledge base robot](https://www.babel.cc/public/babelwiki/en/ai-assistant-agent.html) | Customized persona, prompts, response logic, learning folders, industry templates, multi-Agent and website embedding | Enterprise knowledge base, online customer service, industry assistant, internal expert system |
| [Enterprise AI Assistant](https://www.babel.cc/public/babelwiki/en/ai-assistant.html) | Integrate most Zhichao applications in a conversational manner, answer corporate document knowledge points, and search drive files in multiple dimensions | Daily office assistant, file search, cross-data Q&A |
| [AI Customer Service](https://www.babel.cc/public/babelwiki/en/ai-customer-service.html) | Learn product descriptions, FAQs, customer service documents, and generate intelligent customer service that can provide external services | Official website customer service, product support, pre-sales Q&A, and after-sales knowledge base |
| [Standard Edition Modules](https://www.babel.cc/public/babelwiki/en/ai-standard-modules.html) | Entrance, usage and functional boundaries of 16 standard modules | Administrator selection, implementation scope confirmation, employee training |
| [BabelBird MCP](https://www.babel.cc/public/babelwiki/en/mcp-integration.html) | Securely expose files, search, vector knowledge, and image retrieval to external agents | Codex, WorkBuddy, OpenClaw, and enterprise AI integrations |
| [AI deployment and customization](https://www.babel.cc/public/babelwiki/en/ai-deployment-customization.html) | Private deployment, dedicated agents, industry applications and development of AI applications according to enterprise processes | Private cloud, dedicated model services, industry solutions |

## 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 |


## Core Competencies

- Enterprise-specific AI assistant and AI customer service, which can serve internal employees or external customers through embedded codes.
- AI search and dialogue-based compound query, users can inquire about information, find files, check policies, and find project information just like asking colleagues.
- AI automatic labeling and file classification is used to reduce the cost of manually organizing materials, information and archived documents.
- Customizable AI knowledge base and agents, you can specify learning folders, and you can also configure different assistants for different knowledge areas.
- AI image search, image similarity search, text-to-image search, OCR and multimodal understanding, used for pictures, materials and scans.
- AI document reading assistant, used to summarize single documents, extract key points, and answer document questions.
- Intelligent data assistant supporting Excel for multi-table cross-analysis, query and chart generation.
- [BabelBird MCP](https://www.babel.cc/public/babelwiki/en/mcp-integration.html) exposes files, search, knowledge, and image retrieval to third-party agents while preserving user permissions and folder scope.
- Support on-demand development and private deployment, adapting to industry knowledge, enterprise processes and deployment security requirements.

## Relationship with enterprise network disk

The value of Zhichao AI comes from the combination of "AI + enterprise file system". Traditional general-purpose chat tools usually don’t know where the company’s internal files are, who has permission to see them, which version is the latest, and which files belong to the same project; Zhichao AI can work around the files, projects, departments, material libraries and permission systems in BabelBird. For businesses, this means that AI doesn’t just answer general knowledge, but can provide help around the company’s own data and business context.

## Permission awareness

Internal AI search and Q&A follow BabelBird permissions and the factors below. A custom bot's external visibility is additionally defined by its knowledge scope and publication settings:

- The user's role within the enterprise, department, project, and folder.
- Access control, sharing permissions and validity period for a single file or folder.
- The learning scope specified by the administrator for the agent, knowledge base, or AI assistant.
- Enterprise external sharing, downloading, previewing, watermarking, confidentiality and auditing strategies.
- Configuration strategies for models, indexes, vector libraries and third-party APIs in private deployments.

## How files enter the AI knowledge base {#ai-library-scope}

With Zhichao AI enabled, uploaded BabelBird files that AI can read are automatically ingested and vectorized for AI assistance, AI search and image search. These services do not require each file to be manually assigned to a knowledge base. AI readability and parsing are distinct from storage or preview support.

For a custom knowledge-base bot, select a file scope in the BabelBird directory or upload new files. That selected scope is the bot's knowledge base. When publishing, choose the publication scope; people within it can view the agent, and anonymous access is supported. Knowledge scope determines the source material for answers, while publication scope determines who can view the agent. Configure both separately; see [creating a knowledge-base bot](https://www.babel.cc/public/babelwiki/en/ai-assistant-agent.html).

## Knowledge Bases and Models

Knowledge bases parse, index and retrieve readable documents. Uploading files does not inherently fine-tune a model. Agent configuration and specialized model training are different services. Verify sources because answers can contain omissions or errors.

## 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 care, law, 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)
- [FAQ: Deployment, AI and technical issues](https://www.babel.cc/public/babelwiki/en/faq-technical.html)
- Public introduction: <https://zhuanlan.zhihu.com/p/2052372550513072059>