Create a Workflow
Learn how to create automated workflows using Noema AI's drag-and-drop workflow builder.
Overview
Workflows in Noema AI allow you to automate complex business processes by connecting multiple steps, data sources, and AI capabilities in a visual, easy-to-use interface.
Prerequisites
- Active Noema AI account
- Understanding of your automation requirements
- Relevant data sources configured (if needed)
Steps to Create a Workflow
1. Navigate to Workflows
Go to the Workflows section from the main navigation menu.
2. Create New Workflow
Click the "Create New Workflow" button to open the workflow builder.
3. Name Your Workflow
Provide a descriptive name and optional description:
- Name: E.g., "CV Formatting Pipeline"
- Description: Brief explanation of the workflow's purpose
4. Design Your Workflow
Use the drag-and-drop interface to build your workflow:
Add Trigger
- Choose how the workflow starts (manual, scheduled, event-based)
- Configure trigger settings
Add Steps
Drag components from the palette:
- Data Input: Upload files, API calls, database queries
- Processing: AI analysis, data transformation, validation
- AI Actions: Use assistants, run models, extract information
- Output: Save results, send notifications, update databases
Connect Components
- Draw connections between steps to define the flow
- Configure conditions for branching logic
- Set up error handling
5. Configure Each Step
Click on each component to configure:
- Input parameters
- Processing options
- Output format
- Error handling
6. Test Your Workflow
Before deploying:
- Click "Test Run"
- Provide sample data
- Review results
- Debug any issues
7. Save and Deploy
Once tested:
- Click "Save" to store the workflow
- Click "Deploy" to make it active
- Set up monitoring and alerts
Example: Simple CV Processing Workflow
1. Trigger: File Upload (PDF/Word)
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2. Extract Text: AI Document Parser
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3. Structure Data: Extract name, contact, experience, skills
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4. Format: Apply standard template
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5. Output: Save formatted CV to database
Best Practices
- Start simple and add complexity gradually
- Test with real data samples
- Add error handling for robust automation
- Document your workflow logic
- Use clear naming conventions for steps