Workflow Automation

Build powerful AI pipelines with a visual editor. No coding required -- just drag, connect, and run.

How It Works

1

Design Your Flow

Drag nodes onto the canvas and connect them to define your workflow logic.

2

Configure Nodes

Set up LLM prompts, conditions, HTTP endpoints, code scripts, and variables.

3

Test & Debug

Run your workflow and inspect each node's input/output in real-time.

4

Deploy & Schedule

Run manually or set up scheduled triggers. Publish to the marketplace.

15+ Node Types

Everything you need to build complex AI automation pipelines.

LLM Call

Send prompts to AI models

Condition

If/else branching logic

HTTP Request

Call external APIs

Code Execute

Run Python/JS scripts

Variable

Set and transform data

Loop

Iterate over collections

Merge

Combine parallel outputs

Delay

Wait before continuing

Human Review

Approval checkpoints

Text Template

Generate formatted text

JSON Parse

Extract structured data

Filter

Filter data by rules

Aggregate

Collect and summarize

Switch

Multi-way branching

Output

Return final results

Key Capabilities

Visual DAG Editor

Drag-and-drop interface with real-time validation. The DAG engine ensures no circular dependencies.

Scheduled Triggers

Run workflows on a schedule with cron expressions, or trigger manually.

Variable Templating

Use {{variable.path}} syntax to pass data between nodes dynamically.

Marketplace

Share your workflows publicly or clone workflows created by others.

Who It's For

Automation Engineers

Build complex data pipelines that combine AI processing with API calls and business logic.

Content Teams

Automate content generation, translation, review, and publishing workflows.

Data Analysts

Create repeatable data processing workflows with AI-powered analysis steps.

Build Your First Workflow

Start with a template or build from scratch. No coding required.

Get Started