Course Objective & Scope
Using large language models (LLM) only through chat interfaces leaves most enterprise automation value on the table; real impact comes when models can query internal knowledge and trigger actions across business systems. n8n's built-in LangChain and AI Agent nodes enable multi-step AI orchestration directly on the workflow canvas.
Participants connect commercial and local models, build document ingestion and RAG pipelines with a vector store, manage session memory and equip agents with tool calling over CRMs, databases, APIs and sub-workflows.
Who Should Attend?
- Automation and software engineers embedding
LLM,RAGandagentcapabilities into workflows - Product and operations teams automating support triage, document extraction and smart routing
- Solution architects turning AI prototypes into integrated business workflows
- Prerequisite: basic n8n workflow skills and familiarity with REST APIs
Key Takeaways
- Configure OpenAI, Anthropic, Gemini and local Ollama models within n8n AI nodes
- Enforce deterministic schemas with
Structured Output Parserand Auto-fixing parsers - Build document
chunking, embedding andvector storeretrieval pipelines forRAG - Create tool-using
AI Agentworkflows with persistent conversationalmemory - Add
human-in-the-loopapproval gates, guardrails and token usage tracking
Curriculum
n8n AI Ecosystem and LLM Chains
- Basic LLM Chain, connecting OpenAI, Claude, Gemini and Ollama models
- Generating schema-validated JSON with
Structured Output Parser
Document Ingestion, Embeddings and RAG
- Loading PDFs, web pages and records with text splitters and embedding models
- Indexing and querying knowledge bases in Pinecone, Qdrant or pgvector
AI Agents, Memory and Tool Calling
- Agent architectures and managing buffer or database-backed chat
memory - Exposing APIs, SQL queries and custom sub-workflows as agent tools
Multimodal and Document Extraction Workflows
- Extracting structured data from images, audio transcripts, invoices and forms
- Automated ticket triage, summarization and smart routing pipelines
Human-in-the-Loop, Guardrails and Cost Control
- Approval gates using
Waitnodes with Slack, Teams or email actions - Mitigating prompt injection, masking PII, model fallbacks and token monitoring
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