KOJIE Visual Agent Builder

Build powerful AI agents in minutes with drag-and-drop simplicity

Build Enterprise AI Workflows

Start with a template, or drag AI models from the sidebar to create custom workflows

Components
Drag & Drop
Agent Masterminds - Advanced Automation:
โ€ข Click categories below to expand Agent Masterminds
โ€ข Drag & drop Agent Masterminds to the canvas
โ€ข Connect Masterminds to create intelligent workflows
โ€ข Run automation with multi-AI orchestration
Agent Society Orchestration
Multi-agent coordination with persistent memory & task delegation
Memory: Active Agents: 3
Active Agent Society Last sync: 2 min ago
Research Agent
Writer Agent
Publisher Agent
Enterprise Integrations Marketplace
7,000+ business app connectors with real-time webhooks & OAuth 2.0
7,000+ Apps OAuth Ready
Popular Integrations 7,143 available
Google Workspace
Slack
Airtable
Salesforce
Meta Ads
Advanced Execution Engine
Sandboxed code execution, browser automation & real-time debugging
Sandboxed Auto-Scale
Execution Status CPU: 15% | Memory: 340MB
Python: Ready
JavaScript: Active
Browser: 3 instances
๐Ÿ“Š Data Sources
๐Ÿค– AI Processing
HTTP Tools
๐Ÿ“ Text Operations
๐Ÿ”€ Flow Control
Search Tools
๐Ÿ“‹ List Operations
๐Ÿ”Œ Integrations
๐Ÿ’ป Custom Code
๐ŸŒ Web Automation
Agents
Input/Output
Enterprise Business Logic
Security & Authentication
Social Media Publishing
Ready Never executed
Live Collaborators
YOU
1 active

๐ŸŽฏ MASTERMIND CANVAS ONLINE! ๐ŸŽฏ

โœจ NEURAL STAGE ACTIVATED! โœจ

NEURAL INTERFACE GUIDE
1 Access component categories on the left neural panel
2 DRAG & DROP AI modules into this neural matrix
3 Connect neural pathways between components
4 Configure each AI module's parameters
5 Execute your cyberpunk AI pipeline

Or choose one of these options to get started quickly:

Use Template

Start with a ready-made agent

Recommended
Drag & Drop

Drag components from the left panel

Typical workflow: Input โ†’ AI Model โ†’ Output
Properties

Select a node to view its properties

Step-by-Step Visual Agent Builder Guide

Master the neural workspace in 5 simple steps

01

Select Your AI Components

What to do: Browse the left component panel and find the AI agents you need.

What you'll see: Components organized by category (AI Agents, Data Tools, Logic, etc.)

Example Components:

  • ๐Ÿ“ GPT-5 Text Generator - For content creation
  • ๐Ÿง  Claude-4 Analyzer - For data analysis
  • ๐Ÿ’Ž Gemini Vision - For image processing
  • ๐Ÿ“Š Data Processor - For data transformation

Tip: Hover over components to see their description and capabilities

02

Drag Components to Canvas

What to do: Click and drag your chosen components into the neural workspace canvas.

What you'll see: A glowing drop zone with neural grid that pulses when you hover over it

Expected Experience:

  • โœจ Drag Start: Component glows and follows your cursor
  • ๐Ÿง  Hover Canvas: "NEURAL WORKSPACE" pulses with cyan/green effects
  • โšก Drop Success: Component appears with connection points and glow effects
  • ๐ŸŽฏ Grid Snap: Component automatically aligns to the neural grid

Tip: The canvas will show "Drop Zone" indicators and expand when you approach with a component

03

Connect Your Workflow

What to do: Click and drag from output points (right side) to input points (left side) of other components.

What you'll see: Connection points that glow and expand when you hover over them

Connection Process:

  • ๐Ÿ”ต Output Point: Blue circle on the right side of components
  • ๐ŸŸข Input Point: Green circle on the left side of components
  • โšก Connection Line: Animated curve that flows between connected points
  • ๐ŸŽจ Visual Feedback: Lines glow with neural energy when data flows through

Sample Workflow:

๐Ÿ“ Input Text โ†’ ๐Ÿง  GPT-5 Process โ†’ ๐Ÿ“Š Format Output โ†’ ๐Ÿ’พ Save Result

Real Workflow Output Example:

AI Workflow Demonstration

This is what your completed workflow looks like with real AI processing results

Tip: Invalid connections will show red warning indicators

04

Configure Component Properties

What to do: Click on any component to see its properties in the right panel.

What you'll see: A detailed properties panel with all configurable options

Typical Properties:

  • ๐Ÿ”ง Model Settings: Choose GPT-5, Claude-4, Gemini, etc.
  • โš™๏ธ Parameters: Temperature, max tokens, system prompts
  • ๐Ÿ“‹ Input/Output: Data format and validation rules
  • ๐ŸŽฏ Behavior: Retry logic, error handling, timeouts

GPT-5 Configuration Example:

โ€ข Model: gpt-5
โ€ข Temperature: 0.7 (creativity level)
โ€ข Max Tokens: 2000 (response length)
โ€ข System Prompt: "You are a helpful AI assistant..."

Tip: Properties automatically save as you type

05

Test & Deploy Your Agent

What to do: Use the toolbar buttons to test your workflow and deploy it.

What you'll see: Real-time execution with visual feedback and results

Available Actions:

  • โ–ถ๏ธ Run Flow: Execute your workflow with test data
  • ๐Ÿ’พ Save Flow: Store your workflow for later use
  • ๐Ÿš€ Deploy Agent: Make your agent live and accessible
  • ๐Ÿ“ Generate Code: Export as Python/JavaScript code

What Happens When You Run:

โœ… Validation: Checks all connections and settings
โšก Execution: Components light up as data flows through
๐Ÿ“Š Results: Output displayed in real-time
๐ŸŽฏ Success: Green checkmarks show successful completion

Tip: Watch components glow with neural energy as your agent processes data

Popular Workflow Examples

๐Ÿง  Content Generator

Input Topic โ†’ GPT-5 Generate โ†’ Format Output โ†’ Save Content

Content Creation Automated Writing

๐Ÿ“Š Data Analyzer

Upload Data โ†’ Claude-4 Analysis โ†’ Gemini Visualization โ†’ Export Report

Data Science Business Intelligence

๐ŸŽจ Creative Assistant

User Input โ†’ GPT-5 Ideas โ†’ DALL-E Images โ†’ Combine & Present

Creative Design Visual Content

๐Ÿ” Research Agent

Query โ†’ Perplexity Search โ†’ Summarize โ†’ Generate Insights

Research Information Gathering

Pro Tips for Success

๐ŸŽฏ

Plan Your Flow

Start with the end goal and work backwards to create efficient workflows

โšก

Test Early & Often

Use the Run Flow button frequently to catch issues before deployment

๐Ÿ”ง

Optimize Settings

Fine-tune model parameters for better performance and cost efficiency

๐Ÿ’ก

Use Error Handling

Add fallback nodes to handle failures gracefully in production