n8n: Complete Definition and Guide

What is n8n?

n8n (pronounced 'n-eight-n', short for 'nodemation') is an open-source workflow automation platform that enables creating automated workflows between different applications, services, and APIs via a visual drag-and-drop interface. Created by Jan Oberhauser in 2019, n8n distinguishes itself from competitors like Zapier or Make through its open-source model, self-hosting capability, and technical flexibility that allows executing custom code directly within workflows.

n8n's interface presents workflows as graphs of nodes connected by links. Each node represents an action: fetching data from an API, transforming JSON, sending an email, querying a database, or calling an AI model. Trigger nodes launch the workflow in response to an event (webhook, cron, new message), and data flows from node to node, progressively transforming.

With the emergence of generative AI, n8n has become a preferred tool for AI workflow orchestration. Its native nodes for OpenAI, Anthropic, and other LLM providers, combined with vector store and document processing nodes, make it an ideal platform for building RAG pipelines, AI agents, and intelligent automations without writing thousands of lines of code.

Why n8n Matters

Process automation is a major competitive lever, and n8n offers a unique balance between accessibility and technical power.

• Open source and self-hosted: unlike Zapier and Make, n8n can be hosted on your own servers, ensuring your sensitive data never passes through third-party servers. This is a decisive criterion for companies subject to GDPR or compliance constraints.
• Technical flexibility: n8n allows executing JavaScript or Python code directly within workflows, offering a freedom that pure no-code platforms cannot match. When a connector doesn't exist, a developer can create it.
• Controlled costs: n8n's pricing model (based on workflows, not executions) is more predictable than Zapier's (based on tasks). Self-hosted, costs are limited to infrastructure.
• Native AI orchestration: built-in AI nodes enable constructing LLM pipelines, agents, and RAG workflows directly in the visual interface.
• Active community: over 400 native integrations, a template marketplace, and a community that actively contributes to the ecosystem.

How It Works

An n8n workflow consists of nodes connected in sequence or parallel. The flow begins with a trigger: a webhook (incoming HTTP request), a schedule (cron), an application event (new email, new Slack message), or a manual trigger. Each subsequent node receives data from the previous node, processes it, and passes it to the next.

Nodes fall into several categories. Application nodes connect third-party services (Gmail, Slack, Notion, Salesforce, PostgreSQL). Transformation nodes manipulate data (filters, loops, aggregations, JSON transformations). Code nodes execute JavaScript or Python for custom processing. And AI nodes interact with language models and vector stores.

For AI workflows, n8n provides specialised nodes: the 'AI Agent' node creates an agent capable of using tools, the 'AI Chain' node builds LLM processing chains, and vector store nodes (Pinecone, Qdrant, Supabase) manage embedding storage and search. A complete RAG pipeline can be built visually by connecting just a few nodes.

Concrete Example

KERN-IT uses n8n as an orchestration layer to automate business processes that integrate AI. A concrete example: for a client in the professional training sector, KERNLAB set up an n8n workflow that automates training request processing. When an email arrives with a request, n8n extracts the content via an AI node (Claude), queries the available training database via PostgreSQL, checks availability in the calendar via the Google Calendar API, and generates a personalised proposal automatically sent to the requester.

This workflow replaces a process that required a part-time employee. The advantage of n8n over 100% custom Python development: workflow visibility (each step is visible and editable in the interface), modification speed (adding a step takes minutes instead of hours of development), and simplified maintenance (no need for a senior developer to adjust the flow).

Implementation

1. Choose hosting mode: n8n Cloud to start quickly, or Docker self-hosted (docker run -d --name n8n -p 5678:5678 n8nio/n8n) for full data control.
2. Identify processes to automate: map repetitive tasks involving interactions between multiple systems (email, CRM, database, AI tools).
3. Build the first workflow: start with a simple workflow (webhook trigger + processing + action) to familiarise yourself with the interface and concepts.
4. Integrate AI: add AI nodes for steps requiring text understanding, classification, or generation. Configure LLM provider API keys.
5. Handle errors: configure error nodes for each workflow, set up failure notifications, and enable automatic retries.
6. Deploy to production: secure the n8n instance (HTTPS, authentication), configure workflow backups, and monitor executions.

Associated Technologies and Tools

• Alternatives: Zapier (most popular, SaaS only), Make/Integromat (visual, SaaS), Apache Airflow (data engineering oriented, more complex)
• Infrastructure: Docker for self-hosted deployment, PostgreSQL as workflow database, Redis for queues
• AI integrations: OpenAI, Anthropic Claude, Google Gemini, Hugging Face for LLM nodes; Pinecone, Qdrant, Supabase for vector stores
• Complementary development: Python/FastAPI for custom endpoints, LangChain for complex AI processing that exceeds n8n's visual capabilities
• Monitoring: n8n's native execution interface, notification webhooks, integration with external monitoring tools
• Security: environment variables for secrets, LDAP/SAML authentication in Enterprise version

Conclusion

n8n occupies a unique position in the automation ecosystem: accessible enough for non-technical profiles thanks to its visual interface, and powerful enough for developers thanks to its code nodes and AI integrations. For Belgian and European SMEs and mid-sized companies, n8n's self-hosted model meets GDPR requirements while offering flexibility that SaaS solutions cannot match. KERN-IT uses n8n as a key component of its intelligent automation offering, combining it with custom Python/Django development and LLM integrations via LangChain to create workflows that blend no-code speed with custom development power.