> For the complete documentation index, see [llms.txt](https://raia2.gitbook.io/raia/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://raia2.gitbook.io/raia/dev-program/agents/building-apps-with-ai-agents.md).

# Building Apps with AI Agents

Here’s a **basic description** you can use in a Knowledge Base, onboarding doc, or sales collateral that outlines the **four primary deployment types for AI Agents in raia**:

***

## **Deployment Types of AI Agents in raia**

The **raia platform** supports multiple AI Agent deployment types depending on your business goal — whether you're answering questions, qualifying leads, automating actions, or handling conversations across multiple channels.

Here are the four main ways to deploy AI Agents:

***

### **1.** [**Conversational AI Agents**](#id-1.-conversational-ai-agents)

**Purpose:** General-purpose, multi-channel agents that respond to user questions via **Live Chat, SMS, Email, or Voice**. 

\
**Use Cases:** Assistants.

\
**Deployment:**

* Built in **Launch Pad**
* Trained on documents, Packs, or instructions
* Tested in **Copilot**

***

### **2.** [**Support AI Agents (Knowledge Base Driven)**](/raia/dev-program/agents/building-an-support-ai-agent.md)

**Purpose:** Internal or external-facing agents trained specifically on company documentation to answer policy, process, or technical questions.

\
**Use Cases:**

* Internal IT/support team help
* Employee self-service tools
* Customer-facing knowledge base automation

\
**Key Features:**

* Integrated with **raia Connect** for AI-ready document ingestion
* Deployed through **Copilot** (internal) or **Live Chat** (external)
* Supports scoring, escalation, and ticketing integrations

***

### **3.** [**Sales AI Agents (Conversion Driven)**](/raia/dev-program/agents/building-a-sales-ai-agent.md)

**Purpose:** Engage prospects, ask qualifying questions, provide product information, and escalate hot leads to human sales reps.

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**Use Cases:**

* SDR follow-up
* Website chat-to-lead conversion
* Lead re-engagement via SMS/email

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**Key Features:**

* Can run via **outbound campaigns** or **triggered from CRM**
* Uses **Scoring Skill** to assess lead quality
* Alerts reps via **Notification Skill**
* Logs conversations via **Webhook Skill**

***

### **4. Autonomous AI Agents (Workflow Embedded)**

**Purpose:** Agents embedded inside automated workflows to complete background tasks without human input.

\
**Use Cases:**

* Auto-tagging support conversations
* Summarizing and scoring chats
* Processing incoming form data
* Triggering downstream actions via webhooks

\
**Deployment:**

* Can be triggered via **functions**, **webhooks**, or internal **workflow orchestration**
* Often used for **backend automation**, not end-user interaction
* Supports **function chaining**, document processing, and API calls


---

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