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

# Overview

> Build your first GenAI workflow - a customer care automation system

This quickstart shows the Launchpad in action through a customer care example. You follow the steps end‑to‑end without writing new code, and you see how the same steps map to your own client workflows.

## General Development Flow

<Steps>
  <Step title="Define an event schema">
    Create a Pydantic model that defines the structure of your incoming data
  </Step>

  <Step title="Implement the endpoint">
    Build a FastAPI endpoint that receives events and triggers workflow processing
  </Step>

  <Step title="Build the workflow">
    Design and implement the workflow logic using various node types
  </Step>
</Steps>

## What We're Building

In this quickstart, we'll explore a customer care automation system that:

<Steps>
  <Step title="Analyzes Tickets">
    Processes incoming support tickets through intelligent analysis
  </Step>

  <Step title="Filters Spam">
    Detects and filters out spam messages automatically
  </Step>

  <Step title="Routes Intelligently">
    Makes smart routing decisions based on ticket content
  </Step>

  <Step title="Generates Responses">
    Creates appropriate AI-powered responses to customer queries
  </Step>
</Steps>

## Getting Started

The fully implemented quickstart workflow ships on `main` under `app/launchpad/workflows/examples/quickstart/`. After installation, run it directly from the playground:

```bash theme={null}
uv run playground/quickstart.py
```

## What You'll Learn

By the end, you understand how to structure event schemas, create API endpoints that trigger workflows, build multi‑node pipelines, integrate AI models for processing, test locally and end‑to‑end, and monitor results in the database or optional Supabase Studio.