# AI Assistant Features

## Purpose and Applications of AI Assistants

AI assistants can be widely applied across diverse industries and use cases, helping enterprises automate repetitive tasks and enhance operational efficiency, allowing teams to focus on high-value work and core competency development.

Below are common examples of AI assistant applications in enterprise workflows:

<figure><img src="https://1360999650-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F6v6TNkkOQVfRYfcNirHL%2Fuploads%2Fgit-blob-bf43aacb68fe112214ee71f970e0a230ef416879%2F%E6%88%AA%E5%9C%96%202025-04-22%20%E4%B8%8B%E5%8D%882.46.51.png?alt=media" alt=""><figcaption></figcaption></figure>

AI assistants can be applied across various industries, leveraging intelligent automation and real-time interaction advantages to help enterprises optimize processes, improve service quality, and enhance user experience. The following table lists common AI assistant application scenarios across different industries for reference.

<table><thead><tr><th width="214.15234375">Industry</th><th>Application Scenarios</th></tr></thead><tbody><tr><td>E-commerce &#x26; Retail</td><td>Intelligent customer service, shopping recommendations, return processing</td></tr><tr><td>Finance &#x26; Insurance</td><td>Policy consultation, financial recommendations, risk Q&#x26;A</td></tr><tr><td>Education</td><td>Course assistance, learning diagnostics, language practice</td></tr><tr><td>Healthcare</td><td>Health consultation, appointment scheduling, patient education support</td></tr><tr><td>Government</td><td>Public service inquiries, policy Q&#x26;A, public feedback</td></tr><tr><td>Manufacturing</td><td>Internal knowledge management, maintenance operation guidance</td></tr><tr><td>Travel &#x26; Tourism</td><td>Itinerary recommendations, tour guidance, real-time Q&#x26;A support</td></tr></tbody></table>

## Four Stages of MaiAgent AI Assistant Setup

The setup process for MaiAgent AI assistants can be divided into four major stages. Below is a brief explanation of the objectives and functions of each stage. Complete operational procedures will be introduced in detail in the following chapters.

### 1. Create a New AI Assistant

Customize AI assistants according to your needs by selecting appropriate language models, configuring RAG (Retrieval-Augmented Generation) sources, and defining the AI assistant's role and task positioning to create intelligent assistants that fit enterprise scenarios.

### 2. Provide Reference Materials for AI Assistant

Establish a comprehensive knowledge foundation for the AI assistant by setting up knowledge bases, creating FAQ sections, or importing web crawler data sources to further enhance the accuracy and practicality of responses.

### 3. Launch the AI Assistant

Decide whether to make the AI assistant publicly available or limit it to internal use only. If choosing public availability, it can be integrated through company website embedding, LINE, Messenger, or other channels, flexibly integrating into existing platforms.

### 4. Track AI Assistant Performance

Utilize all conversations, response quality, webhooks, and usage analytics features to track performance, serving as a basis for continuous optimization and experience enhancement of the AI assistant.

<figure><img src="https://1360999650-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F6v6TNkkOQVfRYfcNirHL%2Fuploads%2Fgit-blob-5e6ae460314a77370950d546955125250dc63452%2Fimage%20(2)%20(1)%20(1)%20(1).png?alt=media" alt=""><figcaption></figcaption></figure>

Before starting to create an AI assistant, consider reading a few helpful articles!

{% hint style="info" %}
🗣️[How to Choose an LLM Large Language Model?](https://docs.maiagent.ai/tech/quickstart/llm)
{% endhint %}

{% hint style="info" %}
🔎[What is RAG (Retrieval-Augmented Generation)?](https://docs.maiagent.ai/tech/quickstart/rag)
{% endhint %}

{% hint style="info" %}
👨‍👩‍👧‍👦[What are System Prompts?](https://docs.maiagent.ai/tech/ai-agents/system-prompt)
{% endhint %}


---

# Agent Instructions: 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:

```
GET https://docs.maiagent.ai/maiagent-user-guide/maiagent-user-guide-en/build/explain.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
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.