> ## Documentation Index
> Fetch the complete documentation index at: https://docs.featherhq.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Introduction

> Feather is an AI conversation platform for voice calls, SMS, email, web chat, routing, scheduling, and workflow automation.

Feather helps you build AI-driven customer conversations across voice and messaging channels from one platform. A single agent model powers live calls, SMS threads, email conversations, web chat, workflow-driven outreach, and handoffs between specialized agents.

## What You Can Build

<CardGroup cols={2}>
  <Card title="Voice Agents" icon="phone">
    Handle inbound calls, launch outbound calls, transfer conversations, and capture call outcomes.
  </Card>

  <Card title="Messaging Agents" icon="messages">
    Run SMS, email, and web chat conversations with the same prompt, tools, and variables model.
  </Card>

  <Card title="Automated Outreach" icon="timeline">
    Orchestrate multi-step call and text workflows with scheduling, throttling, and execution controls.
  </Card>

  <Card title="Booking and Routing" icon="calendar-range">
    Route calls through squads, connect calendars, and let agents schedule appointments in flow.
  </Card>
</CardGroup>

## Core Building Blocks

### Agents and Versions

An **agent** is the long-lived identity for a use case such as support, sales, intake, or reminders. An **agent version** is the deployable configuration for that agent: prompt, tools, model settings, voice, language, and channel behavior.

### Conversations

Feather supports four main conversation surfaces:

* Voice calls
* SMS threads
* Email threads
* Web chat threads

Each surface can use shared variables, metadata, tools, and knowledge sources.

### Workflows

Workflows let you automate outreach over time. A workflow defines the sequence. Each execution runs that sequence for one lead or contact.

### Tools and Knowledge

Tools let an agent read or write data in external systems. Knowledge base collections let an agent ground answers in your documents and internal content.

## Recommended Build Order

1. Create an agent for the job you want to automate.
2. Add tools, prompt variables, and optional knowledge base collections.
3. Configure phone numbers, email sending, chat domains, or calendars for the channel you need.
4. Deploy the agent version you want to expose to live traffic.
5. Test the behavior in Testing Lab before scaling through workflows or public entry points.

## Start Here

<CardGroup cols={2}>
  <Card title="Quickstart" icon="rocket" href="/documentation/getting-started/quickstart">
    Create, deploy, and dispatch your first agent.
  </Card>

  <Card title="Authentication" icon="key" href="/documentation/getting-started/authentication">
    Send authenticated API requests with `X-API-Key`.
  </Card>

  <Card title="Agents" icon="robot" href="/documentation/core-concepts/agents">
    Understand agent types, versions, prompts, and deployment.
  </Card>

  <Card title="Conversations" icon="headset" href="/documentation/core-concepts/calls">
    Learn how voice, SMS, email, and chat fit together.
  </Card>
</CardGroup>

## API Reference

When you are ready for endpoint-level detail, start with:

* [Agents API](/api-reference/agents/list-all-agents)
* [Workflows API](/api-reference/workflows/create-agent-workflow)
* [Phone Numbers API](/api-reference/phone-numbers/list-organization-phone-numbers)
* [Calendars API](/api-reference/calendars/create-a-calendar)