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

# Quickstart

> Get started with Radical Whale in under 10 minutes

## Welcome to Radical Whale!

This quickstart guide will help you set up your first workspace, import data, create an AI agent, and process your first dataset. Let's get started!

## Prerequisites

Before you begin, make sure you have:

* A Radical Whale account ([sign up here](https://radicalwhale.com/signup))
* A CSV file with data you'd like to process (optional - we'll provide sample data)
* An OpenAI API key (for AI agent functionality)

## Step 1: Create Your Workspace

After logging in, you'll be guided through workspace creation:

1. **Choose a Workspace Name**: Pick a descriptive name for your team's workspace
2. **Add Description**: Briefly describe what you'll use this workspace for
3. **Select Plan**: Choose the plan that fits your needs (you can start with the free tier)
4. **Invite Team Members**: Add your colleagues' email addresses (optional)

\[Screenshot Placeholder: Workspace creation flow]

<Tip>
  Workspaces are isolated environments where your team's data, agents, and tools
  are organized. Everything within a workspace is shared among team members
  based on their roles.
</Tip>

## Step 2: Set Up Your API Keys

Before creating agents, configure your API keys:

1. Navigate to **Variables** in the sidebar
2. Click **Create Variable**
3. Set up an OpenAI API key:
   * **Name**: `OPENAI_API_KEY`
   * **Key**: `OPENAI_API_KEY`
   * **Value**: Your OpenAI API key (starts with `sk-`)

<Warning>
  API keys are encrypted and stored securely. Only workspace members with
  appropriate permissions can access them.
</Warning>

## Step 3: Import Your First Dataset

Radical Whale works with structured data. Let's import a sample dataset:

1. Go to **Datasets** in the sidebar
2. Click **Import Dataset**
3. Choose **CSV Upload** and upload a file with customer data (name, email, company, status)
4. Click **Import**

The dataset appears in your list. Click it to view records in a spreadsheet-style table. Each record can be expanded for a detailed view.

<Info>
  Radical Whale supports CSV, Excel, and API imports. For details, see [Importing
  Data](/guides/datasets/importing-data).
</Info>

## Step 4: Configure Dataset Columns

After importing, you'll see your data organized into columns. Let's configure them for AI processing:

1. Click on a column header (e.g., "company\_name")
2. Click **Edit Column**
3. Configure the column:
   * **Data Type**: Choose the appropriate type (text, number, etc.)
   * **Instructions**: Tell the AI what to do with this column
   * **Agent Assignment**: We'll do this in the next step

\[Screenshot Placeholder: Column configuration modal]

## Step 4: Create Your First Agent

Agents are AI assistants that can read and write data in your datasets:

1. Click **Agents** in the sidebar
2. Click **Create Agent**
3. Configure your agent:
   * **Name**: "Customer Enrichment Agent"
   * **Model**: Select "GPT-4" (from OpenAI)
   * **Prompt**: "You enrich customer records by researching companies and adding insights"
4. Click **Create**

Your agent is ready to process data. Next, we'll connect it to your dataset.

<Tip>
  Agents can use models from OpenAI, Anthropic, and other providers. Configure
  them in [Configuring Models](/guides/agents/configuring-models).
</Tip>

## Step 5: Chat with Your Agent

Test your agent by starting a conversation:

1. Open your agent's page
2. Click the **Chat** tab
3. Ask: "What customers do we have in the dataset?"
4. The agent will use its tools to read your data and respond

The agent can answer questions, analyze patterns, and update records based on your instructions.

<Info>
  Agents remember conversation context and can perform multi-step tasks. See
  [Chatting with Agents](/guides/agents/chatting-with-agents).
</Info>

## Step 6: Assign Agent to Dataset Column

Connect your agent to a dataset column for automatic processing:

1. Go to your customer dataset
2. Click **Add Column**
3. Name it "Enrichment"
4. In the **Agent** dropdown, select your agent
5. Add instructions: "Research this company and provide industry insights"
6. Click **Save**

Now your agent can process records automatically.

## Step 7: Process Your Data

Run your agent on dataset records:

1. Select rows to process
2. Click **Process Selected**
3. Watch as the agent researches each company and adds insights to the Enrichment column

Processing happens in real-time with progress shown for each record.

<Info>
  You can process records manually, on a schedule, or via API. See [Working with
  Records](/guides/datasets/working-with-records).
</Info>

## Step 8: Review Results

After processing completes:

1. View enriched data in your dataset
2. Click any record to see the detailed view with all enrichment data
3. Export results as CSV if needed

The agent's outputs are stored in the Enrichment column for each processed record.

## Step 9: Create a Page

Document your work with Pages:

1. Click **Pages** in the sidebar
2. Click **Create Page**
3. Add a title: "Company Research Notes"
4. Choose an emoji icon (📊)
5. Write in the rich text editor

### Use AI Content Generation

Generate content with your agent:

1. Type `/ai` in the editor
2. Select your agent
3. Enter a prompt: "Summarize the company research findings"
4. Click **Generate**

The agent creates content using data from your workspace as context.

<Tip>
  Pages can be workspace-level documentation or attached to specific records.
  See [Creating Pages](/guides/pages/creating-pages).
</Tip>

## Next Steps

Congratulations! You've successfully:

* ✅ Created a workspace
* ✅ Set up API keys
* ✅ Imported a dataset
* ✅ Created an AI agent
* ✅ Processed data with AI
* ✅ Created a documentation page

### Explore More

<CardGroup cols={2}>
  <Card title="Core Concepts" icon="book" href="/concepts/workspaces">
    Understand workspaces, datasets, agents, tools, and pages
  </Card>

  <Card title="Managing Tools" icon="wrench" href="/guides/agents/managing-tools">
    Give agents access to web search, code execution, and MCP tools
  </Card>

  <Card title="AI Content Generation" icon="sparkles" href="/guides/pages/ai-content-generation">
    Generate documentation with AI using workspace context
  </Card>

  <Card title="Working with Records" icon="table" href="/guides/datasets/working-with-records">
    Filter, search, and manage dataset records effectively
  </Card>
</CardGroup>

### Need Help?

* **Documentation**: Explore our [user guides](/guides/workspaces/creating-workspaces)
* **Support**: Email us at [support@radicalwhale.com](mailto:support@radicalwhale.com)

***

Ready to build something amazing? Start creating in your workspace!

<CardGroup>
  <Card title="Advanced Agent Configuration" icon="brain" href="/guides/agents/configuring-models">
    Fine-tune your agents for specific tasks
  </Card>
</CardGroup>

## Need Help?

If you run into any issues:

* Check our [User Guides](/guides/workspaces/creating-workspaces) for detailed tutorials
* Review the [API Reference](/api-reference/introduction) for technical details
* Contact our [support team](mailto:support@radicalwhale.com) for assistance

Happy processing! 🐋