Pattern Based
Agent
Explore 8 multi-agent orchestration patterns. From simple two-agent conversations to complex hierarchical workflows with LLM-driven routing and delegation.
Orchestration Patterns
Choose a pattern to see how agents collaborate
Two-Agent Chat
Direct messaging between two agents
Auto Pattern
LLM-driven speaker selection
Round Robin
Fixed cycle debate pattern
LLM Condition
Natural language routing rules
Context Condition
Variable-based routing
Sequential Chat
Pipeline processing
Nested Chat
Hierarchical delegation
CaptainAgent
Workflow designer agent
Key Features
Built for developers and AI researchers
8 Orchestration Patterns
From simple two-agent chats to complex hierarchical delegation with nested workflows.
LLM-Based Routing
Natural language conditions let the LLM decide routing based on query intent and context.
Visual Flow Builder
Interactive visualization of agent interactions, handoffs, and conversation flows.
Real-time Streaming
Watch agents collaborate in real-time with AG-UI protocol over SSE.
Pattern Templates
Pre-built templates for common use cases: support, content creation, analysis.
Debugging Tools
Step-through execution, routing decisions, and agent state inspection.
How It Works
Declarative multi-agent orchestration
1Define Agents
Create specialized agents with system messages and capabilities:
- Each agent has a role, description, and system message
- Agents can have tools, skills, and custom behaviors
- LLM configuration controls model, temperature, etc.
2Configure Routing
Set up handoff conditions for intelligent routing:
- LLM Condition: Natural language routing rules
- Context Condition: Variable-based routing
- Pattern-based: Auto, Round Robin, Sequential
3Run & Observe
Execute workflows and monitor agent interactions:
- Real-time streaming via AG-UI protocol
- Visual routing decisions and handoffs
- Step-through debugging and inspection
Use Cases
Real-world applications of multi-agent patterns
Customer Support Routing
Triage agent routes billing, technical, and general inquiries to appropriate specialists based on query content.
Content Creation Pipeline
Researcher gathers information, Writer drafts content, Editor refines, Publisher formats for distribution.
Design Review
Designer presents, Critic challenges assumptions, Synthesizer improves — iterating until consensus.
Research Report
Lead researcher delegates to sub-team for deep-dive analysis, then synthesizes findings into final report.
Dynamic Workflow Creation
Describe a complex task and CaptainAgent designs the optimal multi-agent workflow automatically.
Brainstorming Session
Multiple experts collaborate with LLM-driven facilitation to explore ideas and reach conclusions.
Try the Interactive Demo
Experience all 8 orchestration patterns in action. See how agents collaborate, route, and delegate tasks.
Specialist firm focused on agent orchestration, scalable backend systems and fintech infrastructure.
Dubai, United Arab Emirates
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