Documentation

Welcome to the ETLR documentation. Learn how to build and deploy AI workflows in minutes.

Getting Started

ETLR is a platform for building AI workflows as code. Define your workflows in YAML, deploy them instantly, and scale without managing infrastructure.

Workflows

Learn how workflows combine inputs and steps to create powerful automation pipelines.

CLI

Manage workflows from the command line with the ETLR CLI for local development and CI/CD.

Inputs

Configure HTTP webhooks, cron schedules, and other input sources for your automation.

Steps

Browse available workflow steps including connectors, transformations, and integrations.

State

Understand how state flows through your workflow pipeline and between steps.

Environment Variables

Securely manage configuration values, API keys, and secrets for your workflows.

Quick Example

Here's a simple workflow that processes webhooks with an AI model:

workflow.yaml

name: ai_workflow

input:
  - type: http_webhook

steps:
  - name: openai_completion
    model: gpt-5.2
    prompt: "Analyze this data: ${state.data}"
  
  - name: slack_webhook
    webhook_url: ${env.SLACK_WEBHOOK_URL}
    text_template: ${state.completion}

This workflow receives data via webhook, processes it with GPT-5.2, and sends the result to Slack. No infrastructure setup required – just deploy and run.

Deploy Your Workflow

Save the workflow as workflow.yaml and deploy it with the CLI:

# Install the CLI
pip install etlr

# Deploy your workflow
etlr deploy workflow.yaml

That's it! Your workflow is now running. Learn more about the ETLR CLI for local development and CI/CD integration.