> For the complete documentation index, see [llms.txt](https://docs.maiagent.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.maiagent.ai/tech/en/ai-agents/faq.md).

# FAQ Management

The FAQ feature processes information into an Excel file and places it in the knowledge base. It provides a convenient user interface for users to create FAQs online within the MaiAgent platform. Its fields include questions and answers, and MaiAgent includes built-in query optimization and enhancement. It can return the appropriate answer even when users phrase a question ambiguously or ask something related to the answer.

Example question:

```
What are MaiAgent's key features?
```

Example answer:

```
MaiAgent's key features include:

1. Rapid service launch: MaiAgent is the fastest development platform for launching generative AI assistant services.
2. Advanced technical architecture: It uses an advanced technical architecture and provides comprehensive functionality.
3. Security and reliability: Its technology has been validated by partners, is secure, and does not generate hallucinations.
4. Powerful RAG technology: It uses powerful RAG (Retrieval-Augmented Generation) technology recognized by the financial industry and public sector.
5. Diverse deployment options: It offers public cloud, private cloud, and on-premises deployment options, allowing you to select the appropriate deployment method based on different requirements and security considerations.
6. Extensive administrative features: These include rapidly creating AI assistants and managing knowledge bases.
7. Multiple application scenarios: It has been successfully applied in the financial industry, public sector, listed companies, healthcare companies, well-known brands, hotel chains, and many other fields.
8. Flexible language model selection: Depending on the deployment option, you can choose from various large language models, such as GPT-4, Claude, and Llama3.
9. High-quality responses: It provides the industry's highest level of response accuracy.
10. Information security protection: It offers robust information security protection and is particularly suitable for scenarios involving sensitive data or regulatory restrictions.
11. Modular design: It provides multiple modules and features, making it easy to implement AI in a variety of business scenarios.
12. Extensive implementation experience: It has more than 20 successful implementations and partnerships with more than 10 system integrators (SIs).

These features make MaiAgent a comprehensive and flexible AI assistant development platform that can meet the needs of a wide range of businesses and organizations.
```

***

Questions that can be answered:

* What are MaiAgent's key features?
* What are MaiAgent's strengths?
* What are MaiAgent's application scenarios?
* Which large language models can be used?
* Are there any financial industry case studies?
* Is an on-premises version available?


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.maiagent.ai/tech/en/ai-agents/faq.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.