AI & Knowledge
Build intelligent conversational agents with LLM integration, tool connectivity, and RAG-powered knowledge retrieval.
The AI & Knowledge ecosystem provides a complete solution for building intelligent conversational workflows. Combine AI Agents, Sub-Agents, and Knowledge Bases to create sophisticated systems that reason, delegate, and retrieve information autonomously.
Available Nodes
AI Agent
Core LLM-powered conversational agent with tool integration and agentic reasoning capabilities
AI Sub-Agent
Nested agent for delegation, specialization, and hierarchical multi-agent architectures
Knowledge Base
RAG-enabled document retrieval with vector embeddings and semantic search
AI Ecosystem Architecture
The AI & Knowledge ecosystem consists of three complementary node types that work together to create intelligent workflows:
Workflow Composition Patterns
Build sophisticated AI systems by combining nodes in different architectural patterns.
Progressive Complexity
Getting Started
Quick Start Guide
Choose your complexity level and build from there:
π’ Simple Agent - Single AI Agent with basic capabilities
- Start with one AI Agent
- Connect essential tools for your use case
- Perfect for focused, domain-specific tasks
π‘ Enhanced Agent - Agent with knowledge and tools
- Add a Knowledge Base for context
- Connect multiple tools from different categories
- Ideal for comprehensive single-agent solutions
π΄ Multi-Agent System - Orchestrated agent workflows
- Use AI Sub-Agents for specialization
- Distribute knowledge bases and tools across agents
- Best for complex, multi-domain applications
Common Use Cases
Transform these business scenarios using the AI & Knowledge ecosystem:
Customer Support Hub
Architecture: Main Agent + Support Sub-Agents + Knowledge Bases
- Route queries to specialized support agents (billing, technical, general)
- Each agent has domain-specific knowledge bases and tools
- Seamless handoffs between agents for complex issues
Content Creation Pipeline
Architecture: Sequential Sub-Agents + Shared Knowledge + File Tools
- Research Agent gathers information using knowledge bases and APIs
- Writing Agent creates content with brand guidelines and templates
- Review Agent validates and refines using quality tools
Data Analysis Workflow
Architecture: Orchestrator + Specialist Agents + Database Tools
- Triage Agent routes requests to appropriate analysis specialists
- Each specialist has domain knowledge and analytical tools
- Results aggregated and presented by orchestrator
Node Selection Guide
| Scenario | AI Agent | AI Sub-Agent | Knowledge Base | Key Benefits |
|---|---|---|---|---|
| Simple chatbot | β Primary | β | Optional | Quick deployment, focused functionality |
| Domain expert | β Primary | β | β Required | Rich context, specialized knowledge |
| Multi-department | β Orchestrator | β Required | β Per domain | Scalable, specialized, maintainable |
| Complex workflows | β Coordinator | β Required | β Distributed | Maximum flexibility and capability |
Learn More
Dive deeper into specific areas of the AI & Knowledge ecosystem:
Core Concepts
- AI Agent - Master the agentic loop, tool selection strategies, and autonomous reasoning
- AI Sub-Agent - Learn multi-agent orchestration patterns and delegation strategies
- Knowledge Base - Implement advanced RAG patterns and semantic search optimization
Related Node Categories
- Data & Storage Nodes - Tools for file operations, databases, and data management
- Code Execution Nodes - JavaScript, Python, and custom logic execution tools
- Integration Nodes - HTTP, webhooks, and third-party service connectivity
Quick Start: Begin with AI Agent for single-agent workflows, then explore AI Sub-Agent for multi-agent orchestration.