Workflows
Build complex AI pipelines using a visual drag-and-drop interface. Chain together data sources, transformations, AI models, and actions to automate processes with full distributed tracing and execution monitoring.
What are Workflows?
Workflows allow you to create sophisticated automation pipelines by visually connecting different components. Each workflow consists of:
- Trigger: The event that initiates the workflow (webhook, schedule, API, or form)
- Processing Nodes: Components that transform, analyze, or route data
- Destinations: Where the processed data is sent
Key Features
Visual Builder
- Drag-and-drop interface for building workflows
- Real-time execution visualization
- Node connections show data flow
- Canvas organization and grouping
Distributed Tracing
- Track execution across all nodes
- Waterfall charts for performance analysis
- Node-level input/output inspection
- Detailed error tracking and logging
Scalability
- Automatic parallelization where possible
- Resource optimization
- Handle high-volume executions
- Performance metrics and monitoring
Version Control
- Each deployment creates a versioned snapshot
- View version history and diffs
- Rollback to previous versions instantly
- Tag versions for organization
Workflow Components
Triggers
Start workflows from various sources:
- Webhook: HTTP requests with HMAC signature verification
- Schedule: Time-based execution (intervals, daily, cron)
- REST API: Authenticated API endpoints
- Form: Form submissions with CAPTCHA
Node Categories
| Category | Purpose |
|---|---|
| Sources | Read data from APIs, databases, email, cloud storage |
| Transform | Parse documents (Excel, PDF, Word, Email) |
| AI | Connect to AI models via AI Gateway |
| Memory | Conversation history, context buffers, knowledge bases |
| Agents | Entity extraction, document classification |
| Control Flow | Merge, conditional, loop, map, router, switch, filter |
| Destinations | Send to webhooks, databases, email, storage |
| MCP Tools | 112+ pre-integrated external services |
Monitoring & Observability
Every workflow execution provides:
- Real-time status updates
- Execution timeline with node durations
- Input/output data for each node
- Console logs and error messages
- Performance metrics (success rate, duration, throughput)
Getting Started
Ready to create your first workflow? Check out these guides:
- Creating Workflows - Step-by-step guide to building workflows
- Workflow Nodes - Available node types and their uses
- Workflow Triggers - How to start your workflows
- Testing Workflows - Test and debug your workflows
- Deploying Workflows - Deploy to production
Use Cases
Workflows are ideal for:
- Data Processing Pipelines: Extract, transform, and load data from multiple sources
- AI-Powered Automation: Chain AI models for complex analysis
- Event-Driven Integrations: React to webhooks and trigger actions
- Scheduled Tasks: Run recurring jobs and data synchronization
- Form Processing: Handle submissions with validation and AI processing
- Document Analysis: Parse and extract information from documents
- Multi-System Integration: Connect databases, APIs, and cloud services
Best Practice
Start with simple workflows and gradually add complexity. Test thoroughly in Development environment before promoting to Production.