Training course – Make – Automotive

Make for the Automotive Industry

Automation with Make (formerly Integromat) and AI modules: build scenarios, routers and AI steps while keeping data protection in check.

Duration
6 hours, one session
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 Make with the everyday processes of Automotive. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

Make, formerly known as Integromat, is a visual automation platform that lets you connect applications and automate recurring processes without writing code. In this compact course you will learn to build scenarios systematically, from triggers and modules through routers and filters to iterators, aggregators and data stores. You will understand how data flows through a scenario, how to reshape it with functions and how to keep an eye on operations consumption.

The second focus is AI. You connect language models through Make’s AI modules and provider integrations to classify text, extract information from emails and documents, draft replies or enrich content. You learn to catch errors with error handlers, test scenarios and document them clearly. Finally, you address data protection topics such as hosting region, data processing agreements and data minimisation, so that your automations can be run safely within your organisation.

The automotive industry is under immense pressure to change: electrification, software-defined vehicles, new competitors and demanding regulation are transforming manufacturers, suppliers and dealerships alike. Generative AI supports almost every stage of the value chain – from requirements management in engineering, through supplier communication and complaint handling in purchasing and quality, to sales and aftersales at the dealership. AI assistants help unlock specifications, standards and test reports, structure 8D reports or answer customer enquiries. AI agents connect data from different systems. What matters is protecting engineering know-how, meeting quality and safety standards and having clear approval processes.

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?

  • Engineering and requirements management staff
  • Purchasing and supplier management at OEMs and suppliers
  • Quality management and complaint handling
  • Sales, service and aftersales at dealerships
  • Production and logistics planning

Typical challenges we address

  • Extensive specifications, standards and requirement documents
  • Heavy documentation workload in quality management and complaints
  • Complex supply chains requiring constant coordination
  • Strict protection of engineering data and intellectual property

What you will be able to do

  • You can build Make scenarios independently using triggers, routers, filters and data transformations.
  • You can process lists and records with iterators, aggregators and data stores.
  • You can integrate AI modules for classification, extraction and text generation into your processes.
  • You can safeguard scenarios with error handlers, validation and human approval.
  • Analyse technical documents such as specifications and standards with AI in a structured way.
  • Accelerate quality, complaint and supplier processes with AI support.
  • Use AI while upholding confidentiality, quality standards and approval processes.

Course outline

Module 1 Fundamentals: scenarios, modules and data flow
  • Interface layout, scenario editor and execution history
  • Triggers, actions and searches: module types and their role in a scenario
  • Understanding bundles, mapping and data types and using them deliberately
  • Choosing between schedules, webhooks and instant triggers
Module 2 Logic: routers, filters, iterators and aggregators
  • Using routers and filters for branching and conditional flows
  • Splitting lists with iterators and combining them with aggregators
  • Applying text, date and maths functions to transform data
  • Using data stores and variables for interim values and duplicate checks
Module 3 AI building blocks in Make
  • Connecting language models via AI modules and provider integrations
  • Automating classification, structured data extraction and text generation
  • Building prompts from scenario variables and processing output as JSON
  • Combining AI agents in Make with tools and scenarios as actions
Module 4 Integrations, error handling and testing
  • Connecting common business applications and any API via the HTTP module
  • Applying error handlers such as Resume, Ignore, Break and Rollback
  • Validating AI output and routing unusable results to a person
  • Testing scenarios, optimising operations and documenting them for the team
Module 5 Data protection, governance and operations
  • Assessing hosting region, data processing agreements and data flows to AI providers
  • Applying data minimisation and pseudonymisation within scenarios
  • Managing connections, teams and permissions across the organisation
  • Defining approval steps, monitoring and ownership for live operation
Module 6 Practice lab: Automotive
  • Analysing specifications
  • Complaints and 8D reports
  • Supplier communication
  • Unlocking standards and processes
  • Sales and aftersales
  • Training and technical documentation
Module 7 Data protection, quality & transfer to daily work
  • Engineering data, design documents and customer specifications are subject to strict confidentiality agreements and industry information security requirements such as TISAX, and may only be processed in approved AI environments. Customer data at dealerships falls under the GDPR, and safety-relevant content always requires expert sign-off.
  • 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

Analysing specifications

AI extracts requirements from lengthy customer specifications, compares them with the supplier's technical response, flags contradictions and ambiguities and drafts clarification questions for customers or development partners.

Complaints and 8D reports

Complaint descriptions are structured, potential causes gathered using methods such as Ishikawa and 8D reports written in clear language – root cause analysis remains the expert team's job.

Supplier communication

Requests, formal notices, escalations and audit reports are written precisely and in several languages, supplier ratings are commented on and meeting preparation is produced. Agreements are recorded for follow-up.

Unlocking standards and processes

Internal process descriptions, work instructions and quality requirements are made searchable, so staff receive answers with a reference to the governing document. New staff find applicable rules much faster.

Sales and aftersales

At the dealership, AI drafts offers, vehicle descriptions, replies to customer enquiries and service reminders and helps service advisers explain repairs clearly. Customer requests are captured for follow-up in the CRM.

Training and technical documentation

Training materials for assembly, service or new vehicle technologies are created from technical documents, simplified for the audience and translated into other languages. Quiz questions per chapter are included.

Prerequisites

You should be comfortable with common office and cloud applications and have some experience with AI assistants. No programming skills are required. Professional experience at a vehicle manufacturer, supplier or dealership; no programming skills required.

Technical requirements

You will need a laptop with an up-to-date browser and a Make account; the free plan covers most exercises. API access for a language model is set up together during the course.

Data protection & compliance

Engineering data, design documents and customer specifications are subject to strict confidentiality agreements and industry information security requirements such as TISAX, and may only be processed in approved AI environments. Customer data at dealerships falls under the GDPR, and safety-relevant content always requires expert sign-off.

Dates & locations

For every location we suggest a date roughly four weeks ahead. Your preferred date is always possible.

  • Munich Wed, 16 December 2026 6 hrs Request
  • Salzburg Fri, 11 December 2026 6 hrs Request
  • Berlin Wed, 16 December 2026 6 hrs Request
  • Augsburg Thu, 10 December 2026 6 hrs Request
  • Hanover Wed, 16 December 2026 6 hrs Request
  • Bremen Tue, 15 December 2026 6 hrs Request
  • Stuttgart Tue, 15 December 2026 6 hrs Request
  • Kaiserslautern Wed, 16 December 2026 6 hrs Request
  • Online Tue, 15 December 2026 6 hrs Request

Frequently asked questions

Is Make the same as Integromat?

Yes. Integromat was renamed Make and substantially developed along the way. The core principle of visual scenarios made of connected modules remains, while a redesigned interface, many new integrations and AI building blocks have been added. If you used Integromat in the past, you will quickly feel at home and discover the new capabilities on the course.

How do I keep operation costs under control?

Every module that runs consumes operations or credits, and AI calls also use quota with the respective model provider. On the course you learn to design scenarios so that filters apply early, unnecessary runs are avoided and data is processed in batches. This keeps your automations economical and predictable as volumes grow.

Can Make be used in a GDPR-compliant way?

In principle yes, provided you set up the framework deliberately. This includes choosing the hosting region, signing a data processing agreement, reviewing connected AI services and applying data minimisation. On the course you work through these points with a checklist and learn to filter or pseudonymise sensitive data within scenarios.

Can specifications be uploaded to AI tools?

Only into environments approved by your information security team that meet your customers' requirements. Many OEMs regulate this contractually. The course shows how to work with approved enterprise solutions, clean documents beforehand and which content never belongs in external services.

Can AI carry out a root cause analysis?

AI helps gather potential causes systematically, structure methods such as 5 Whys or Ishikawa and write reports. The actual analysis with measurements, tests and process knowledge remains the expert team's task. AI speeds up the path there and improves documentation quality.

How much does “Make for the Automotive Industry” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 6 hours of live training with a trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. For every location we suggest a date roughly four weeks ahead. In the request form you can always describe your preferred date or period in free text – we check availability and get back to you 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 and Kaiserslautern. We can also run the course exclusively for your team.

Can the course be tailored to our team?

Yes. Tailor-made courses cost approx. €4,500 more, depending on the topic and by arrangement. We agree content, examples and exercises with you in advance.

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