Training course · Make · Logistics & Supply Chain

Make for Logistics and Supply Chain Teams

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

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

“Make for Logistics and Supply Chain Teams” is designed for roles such as Supply chain managers and planners, Logistics and warehouse managers and Transport dispatchers and freight forwarders and shows step by step how to use Make productively, safely and transparently in Logistics & Supply Chain – from the fundamentals to advanced workflows.

Make, formerly known as Integromat, is a visual automation platform that lets you connect applications and automate recurring processes without writing code. Over two days 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.

Logistics and supply chain management are under constant pressure: volatile demand, disrupted supply chains, rising freight costs, staff shortages and growing demands for transparency and sustainability. Generative AI offers new tools for planning and communication. AI assistants analyse inventory and shipment data, explain forecast deviations, create work instructions for warehouse and shipping, answer customer status enquiries and help clarify customs and Incoterms questions. AI agents and automation process delivery notifications, freight documents and order confirmations, monitor delays and suggest actions. This frees up time for exception management and optimisation. The prerequisites are clean master data, access to ERP, WMS and TMS data and clear ownership of decisions.

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?

  • Supply chain managers and planners
  • Logistics and warehouse managers
  • Transport dispatchers and freight forwarders
  • Customs and foreign trade specialists
  • Demand and inventory planners

Typical challenges we address

  • Detecting and communicating delivery delays and disruptions early
  • Balancing inventory between service levels and working capital
  • Processing large volumes of freight documents and notifications manually
  • Onboarding new warehouse and dispatch staff quickly

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.
  • Use AI for inventory, forecast and disruption analysis in the supply chain.
  • Automate document processing and status communication with clear review steps.
  • Design AI-supported logistics processes that are secure, traceable and respect employee co-determination.

Course outline

Day 1

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

Day 2

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: Logistics & Supply Chain
  • Managing disruptions and delays
  • Freight document processing
  • Inventory and forecast analysis
  • Work instructions and training
  • Customs and trade questions
  • Shipment status enquiries
Module 7 Data protection, quality & transfer to daily work
  • Logistics data contains personal information, for example about drivers and recipients, which must be processed in line with the GDPR; AI-based analysis of employee performance or location requires works council involvement in Germany. Customs and export control decisions remain governed by applicable trade regulations, and AI output must be checked by experts.
  • 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

Managing disruptions and delays

Automations compare shipment status with planned dates; AI summarises critical delays, assesses affected orders and drafts customer notifications and options for action.

Freight document processing

AI reads delivery notes, consignment notes, packing lists and customs documents, checks them for completeness and consistency with the order and passes structured data to the ERP or WMS.

Inventory and forecast analysis

Exports from planning and ERP systems are analysed, slow movers and stock-out risks identified and forecast deviations explained clearly as input for S&OP meetings.

Work instructions and training

Process descriptions become clear, multilingual work instructions for goods receipt, picking and shipping, including checklists and quiz questions for onboarding.

Customs and trade questions

An AI assistant explains Incoterms, rules of origin or tariff classification as a starting point for research and prepares questions for customs experts, who verify results against official sources.

Shipment status enquiries

An assistant answers status enquiries based on tracking data, explains delays transparently and routes complaints with complete information to the responsible team.

Prerequisites

You should be comfortable with common office and cloud applications and have some experience with AI assistants. No programming skills are required. You work in logistics, supply chain management or dispatch and know the processes and systems in your area.

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

Logistics data contains personal information, for example about drivers and recipients, which must be processed in line with the GDPR; AI-based analysis of employee performance or location requires works council involvement in Germany. Customs and export control decisions remain governed by applicable trade regulations, and AI output must be checked by experts.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Tue, 24 November 2026 – Wed, 25 November 2026 Online Request
  • Thu, 3 December 2026 – Fri, 4 December 2026 Munich Request
  • Mon, 7 December 2026 – Tue, 8 December 2026 Online Request
  • Tue, 15 December 2026 – Wed, 16 December 2026 Stuttgart Request
  • Thu, 14 January 2027 – Fri, 15 January 2027 Online Request
  • Mon, 25 January 2027 – Tue, 26 January 2027 Berlin 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.

Will generative AI replace our planning software?

No. Specialised planning, warehouse management and transport systems remain the backbone. Generative AI complements them with analysis, explanation, communication and document processing. In the course we show how to analyse exports from these systems with AI and automate recurring workflows.

Is AI reliable for customs questions?

AI is a good starting point for research and structure, but it can be wrong about tariff codes, preference rules or sanctions lists. Binding decisions require official sources and expertise, such as binding tariff information. We practise checking AI output systematically against official sources.

How much does “Make for Logistics and Supply Chain 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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