Building AI workflows doesn’t have to be complicated. With ETLR, you can create powerful automation pipelines that integrate AI models, APIs, and data transformations—all using simple YAML configuration.
Why AI Workflows Matter
In today’s data-driven world, businesses need to process information quickly and intelligently. AI workflows enable you to:
- Automate repetitive tasks with intelligent decision-making
- Process data at scale without manual intervention
- Integrate multiple services seamlessly
- Reduce operational costs through automation
Your First ETLR Workflow
Let’s build a simple workflow that receives webhook data, processes it with AI, and sends a notification.
workflow:
name: ai-content-processor
description: "Process content with AI and send notifications"
input:
type: http_webhook
steps:
- type: openai_completion
api_key: ${env:OPENAI_API_KEY}
model: gpt-4
prompt: "Summarise this content: ${input.text}"
output_to: summary
- type: slack_webhook
webhook_url: ${env:SLACK_WEBHOOK}
text_template: "New summary: ${summary.content}"
This workflow:
- Receives data via HTTP webhook
- Processes it with GPT-4 to create a summary
- Sends the result to Slack
Key Features of ETLR
Simple YAML Configuration
No need to write complex code. Define your workflows in YAML and deploy them instantly.
Built-in Connectors
ETLR provides 24+ pre-built connectors for:
- AI models (OpenAI, Anthropic, Google Gemini)
- Communication tools (Slack, Discord, Teams, Email)
- CRMs (Salesforce, HubSpot)
- Storage (S3, databases)
State Management
Data flows seamlessly between steps. Each step can access and modify the workflow state:
steps:
- type: http_call
url: https://api.example.com/users
output_to: users
- type: for_each
input_from: users
var: user
steps:
- type: openai_completion
api_key: ${env:OPENAI_API_KEY}
model: gpt-4
prompt: "Generate a personalised message for ${user.name}"
output_to: message
- type: resend_email
api_key: ${env:RESEND_API_KEY}
from_email: [email protected]
to: ${user.email}
subject: "Welcome!"
html: ${message.content}
Environment Variables
Securely manage API keys and configuration:
steps:
- type: openai_completion
api_key: ${env:OPENAI_API_KEY} # Stored securely
model: gpt-4
Real-World Use Cases
1. Content Moderation
Automatically review user-generated content using AI before publishing.
2. Customer Support Automation
Route support tickets to the right team and generate AI-powered responses.
3. Data Enrichment
Enhance your CRM data with AI-generated insights and external API data.
4. Sentiment Analysis Pipeline
Process customer feedback at scale and identify trends automatically.
Getting Started
- Sign up at app.etlr.io
- Create your first workflow using our template library
- Deploy instantly and start processing data
Ready to build intelligent automation? Get started with ETLR today and join hundreds of teams automating their workflows with AI.
Next Steps
- Explore our documentation for detailed guides
- Browse available steps to see what you can build
- Join our Discord community to connect with other builders