Training course · n8n · Customer Service
n8n for Customer Service Teams
Workflow automation with n8n and AI: master nodes, the AI Agent node, integrations and GDPR-friendly self-hosting in practice.
- Duration
- 2 days (14 hrs)
- Format
- Online or on-site
- Language
- German or English
- Participants
- open dates or exclusive for your team
- Certificate
- Certificate of attendance
Overview
This course connects n8n with the everyday processes of Customer Service. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.
n8n is a flexible workflow automation platform that combines visual flows with language models and hundreds of integrations. Unlike many cloud services, n8n can also be self-hosted, so your data can stay in your own data centre or with a European hosting provider. Over two days you will learn how triggers, nodes and data flows fit together, how to transform data between applications and how to automate recurring tasks from your day-to-day work reliably.
The core of the course is the combination of automation and AI. Using the AI Agent node, chat models, memory and tools, you build workflows that classify emails, summarise documents, enrich records or answer enquiries. You learn to catch errors, test workflows and document them properly. Finally, you look at hosting options, credential management and data protection, so that your automations run stably, securely and in line with GDPR once they go into everyday operation.
Customer service teams are the voice of the company: they answer questions, solve problems and have a major influence on customer satisfaction. Generative AI is changing service in many ways. AI assistants suggest replies to tickets and emails, summarise long conversation histories, translate enquiries and search knowledge bases in seconds. AI agents and chatbots answer routine requests around the clock and hand complex cases over to agents with full context. Automation classifies requests, sets priorities and detects sentiment. This gives service staff more time for demanding cases and empathetic conversations. The prerequisites are a well-maintained knowledge base, clear escalation rules, transparency towards customers and careful handling of the personal data in every ticket.
The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.
Who is this course for?
- First and second-level service agents
- Team leads and service managers
- Knowledge managers and service trainers
- Customer success managers
- Contact centre and service process owners
Typical challenges we address
- Handling high ticket volumes while maintaining response quality
- Keeping knowledge up to date and quickly accessible for everyone
- Onboarding new staff quickly
- Handling customer requests consistently across languages and channels
What you will be able to do
- You can build n8n workflows independently using triggers, logic nodes and data transformations.
- You can connect n8n to the applications you use every day and fall back on the HTTP Request node where needed.
- You can use the AI Agent node and other AI building blocks for classification, extraction and summarisation.
- You can safeguard workflows with error handling, validation and human approval steps.
- Use AI for reply suggestions, summaries and ticket routing in your service process.
- Build an AI-ready knowledge base and define clear escalation rules for chatbots.
- Deploy AI in customer service transparently and in compliance with data protection rules.
Course outline
Day 1
Module 1 Fundamentals: workflows, triggers and nodes
- Getting to know the n8n interface, canvas and execution view
- Trigger types: schedules, webhooks, incoming email and app events
- Understanding items and JSON data and working with expressions
- Using core nodes such as Edit Fields, IF, Switch, Merge and Loop Over Items
Module 2 Integrations and data processing
- Connecting common applications: email, spreadsheets, CRM, collaboration and cloud storage
- Using the HTTP Request node for APIs without a ready-made integration
- Creating, managing and sharing credentials securely within the team
- Filtering, merging and reshaping data and writing it to target systems
Module 3 AI in n8n: the AI Agent node and LLM building blocks
- Connecting chat models from different providers as well as locally hosted models
- Configuring the AI Agent node with a system prompt, memory and tools
- Automating classification, structured data extraction and summarisation
- Using your own documents via vector stores for retrieval-augmented generation
Module 4 Error handling, testing and maintainability
- Setting up error workflows, retries and failure notifications
- Validating AI output and defining fallbacks for unusable responses
- Working with pinned test data and tracing past executions
- Modularising, naming and documenting workflows for colleagues
Day 2
Module 5 Self-hosting, data protection and operations
- Cloud versus self-hosted: effort, control and licensing model compared
- Assessing data flows to AI providers against GDPR requirements
- Managing access rights, logging and retention of execution data
- Adding human-in-the-loop approval steps to automated processes
Module 6 Practice lab: Customer Service
- Reply suggestions
- Ticket classification and routing
- Case summaries
- Knowledge base building
- Self-service assistant
- Quality analysis and coaching
Module 7 Data protection, quality & transfer to daily work
- Tickets contain personal data, so processing them in AI tools requires a GDPR-compliant data processing agreement; under the EU AI Act chatbots must be clearly identifiable as AI. If conversations are recorded or agent performance data analysed, works councils must be involved, for example under the German Works Constitution Act.
- Ground rules for safe AI use in your team
- Checking results: facts, sources, tests and the four-eyes principle
- Personal action plan for the next 30 days
- Open questions, outlook and resources for further learning
Practical scenarios from your field
Reply suggestions
An AI assistant analyses the request, searches knowledge articles and past resolutions and suggests a reply in the company's tone of voice, which agents adapt and send.
Ticket classification and routing
Incoming requests are automatically categorised by topic, product, urgency and sentiment and routed to the right team, with critical cases prioritised.
Case summaries
Long email threads, chat logs or call notes are condensed into a short summary of the problem, steps taken and open issue, ideal for handovers and escalations.
Knowledge base building
From resolved tickets and expert knowledge, AI drafts knowledge articles and FAQs, spots documentation gaps and keeps existing articles up to date with suggested changes.
Self-service assistant
An AI-powered chat answers frequent questions based on approved content, collects structured information for complex cases and hands them over to agents with context.
Quality analysis and coaching
AI reviews ticket samples against defined quality criteria, identifies recurring customer issues and gives team leads pointers for coaching and process improvement.
Prerequisites
You should be confident with common office applications and have basic experience with AI assistants. No programming is required, although a basic grasp of structured data is helpful. You work in customer service or customer success and know the ticketing or CRM systems your team uses.
Technical requirements
You will need a laptop with an up-to-date browser. We provide an n8n environment for the exercises, or you can use your own instance; API keys for a language model are set up together during the course.
Data protection & compliance
Tickets contain personal data, so processing them in AI tools requires a GDPR-compliant data processing agreement; under the EU AI Act chatbots must be clearly identifiable as AI. If conversations are recorded or agent performance data analysed, works councils must be involved, for example under the German Works Constitution Act.
Suggested dates
All dates are suggestions – your preferred date is always possible.
- Wed, 25 November 2026 – Thu, 26 November 2026 Online Request
- Thu, 10 December 2026 – Fri, 11 December 2026 Salzburg Request
- Mon, 14 December 2026 – Tue, 15 December 2026 Online Request
- Tue, 19 January 2027 – Wed, 20 January 2027 Bremen Request
- Mon, 25 January 2027 – Tue, 26 January 2027 Online Request
- Tue, 9 February 2027 – Wed, 10 February 2027 Augsburg Request
Frequently asked questions
Do I need to code to work with n8n?
No. Most workflows are built visually by connecting nodes. During the course you also learn simple expressions to reference and reshape data precisely. A Code node is available for special cases but is not essential. A logical understanding of processes and data fields is entirely sufficient to get started.
Why is n8n attractive from a European data protection perspective?
n8n can be self-hosted, for instance on your own servers or with a European hosting provider. This keeps you in control of where workflow and execution data is stored. What still matters is which data you send to external AI services. On the course you learn to assess these data flows and, where appropriate, connect locally hosted models.
How does n8n differ from Make or Power Automate?
All three automate processes across applications. n8n stands out for its self-hosting option, its fair-code licensing and particularly flexible AI building blocks such as the AI Agent node. Make offers a very approachable cloud interface, while Power Automate excels at deep Microsoft integration. The course puts these differences into context for typical scenarios.
Will an AI chatbot replace our service team?
No. Good chatbots take care of routine questions, but complex, emotional or unusual requests need people. What matters is a smooth handover with full context. In the course we show how to define which requests are automated and when a human takes over.
How do we prevent chatbots from giving wrong answers?
Restrict the chatbot to verified knowledge content, show sources and define topics that are always handed to agents, such as legal questions or cancellations. Regular reviews and tests with real requests keep quality high over time. Clear feedback loops from agents help close knowledge gaps quickly.
How much does “n8n for Customer Service Teams” cost?
The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 2 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.
Can I suggest my own date?
Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm within one working day.
Is the course online or on-site?
Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart or Kaiserslautern. We can also run the course exclusively for your team.
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