Training course · Make · Accounting

Make for Accounting 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

This course connects Make with the everyday processes of Accounting. 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. 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.

Accounting is shaped by recurring processes, high document volumes and strict requirements for proper bookkeeping. Generative AI and automation provide real relief: AI assistants extract data from supplier invoices, suggest account assignments, explain transactions under local GAAP or IFRS and draft queries to suppliers or internal departments. AI agents support account reconciliations, the month-end close and the preparation of documents for external auditors and tax advisers. Responsibility for correct postings stays with people, but routine work shrinks, leaving time for exceptions, process improvement and analysis. The prerequisites are clear review steps, documented procedures and tools that respect requirements for traceability and immutability, such as the German GoBD principles.

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?

  • General ledger and accounts payable accountants
  • Accounts receivable specialists
  • Financial accountants preparing statements
  • Heads of accounting
  • Shared service centre staff

Typical challenges we address

  • Processing high volumes of documents in many formats on time
  • Resolving reconciliations and open items during the month-end close
  • Accounting correctly for complex transactions under GAAP, IFRS and VAT rules
  • Providing complete, traceable records for audits and tax inspections

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 document processing, account assignment suggestions and reconciliations with clear review steps.
  • Use AI assistants to clarify GAAP, IFRS and VAT questions and verify the answers professionally.
  • Design AI-supported processes that meet bookkeeping compliance requirements and are fully documented.

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: Accounting
  • Invoice data extraction
  • Account assignment and guidance
  • Reconciliation support
  • Dunning and supplier communication
  • Close checklists and procedures
  • Audit request preparation
Module 7 Data protection, quality & transfer to daily work
  • AI-supported accounting processes must meet bookkeeping requirements such as the German GoBD, in particular traceability, immutability and up-to-date procedural documentation. Invoices and bank data contain personal data, so processing them in AI tools requires a GDPR-compliant data processing agreement.
  • 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

Invoice data extraction

AI reads incoming invoices in PDF or e-invoicing formats, checks mandatory VAT details, suggests supplier, GL account and cost centre and flags incomplete or unusual documents for review.

Account assignment and guidance

An AI assistant explains transactions such as prepayments, provisions or capitalisation of assets, proposes possible journal entries and points to the relevant rules, which you then verify professionally.

Reconciliation support

Automations compare bank transactions with receivables and payables, match payments to open items and produce a list of unexplained differences with suggested explanations for the month-end close.

Dunning and supplier communication

AI drafts polite, factual payment reminders, queries about missing purchase order numbers or credit note requests and adapts tone and language for domestic and international customers and suppliers.

Close checklists and procedures

From existing notes, AI creates structured closing checklists, work instructions and sections of the procedural documentation required for compliant bookkeeping, which the team reviews and maintains.

Audit request preparation

When auditors or tax inspectors send requests, AI helps structure the questions, map the evidence required and draft clear explanations of postings, estimates and judgements.

Prerequisites

You should be comfortable with common office and cloud applications and have some experience with AI assistants. No programming skills are required. You have a basic knowledge of financial accounting and work regularly with an ERP or accounting system.

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

AI-supported accounting processes must meet bookkeeping requirements such as the German GoBD, in particular traceability, immutability and up-to-date procedural documentation. Invoices and bank data contain personal data, so processing them in AI tools requires a GDPR-compliant data processing agreement.

Suggested dates

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

  • Wed, 25 November 2026 – Thu, 26 November 2026 Online Request
  • Tue, 8 December 2026 – Wed, 9 December 2026 Salzburg Request
  • Thu, 17 December 2026 – Fri, 18 December 2026 Online Request
  • Thu, 21 January 2027 – Fri, 22 January 2027 Online Request
  • Tue, 26 January 2027 – Wed, 27 January 2027 Augsburg Request
  • Wed, 3 February 2027 – Thu, 4 February 2027 Online 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.

Are AI-supported postings compliant?

AI provides suggestions, but postings are made in your compliant accounting system after review by staff. What matters are documented review steps, logging and updated procedural documentation. In the course we work out how to embed AI steps cleanly in your process and make them transparent to auditors.

How well does AI handle invoices with different layouts?

Modern models usually process varied layouts and structured e-invoices reliably, but they make mistakes with blurred scans or unusual formats. Plausibility checks such as total reconciliation, VAT rate validation and supplier master data matching are therefore essential. We show how to build these controls into your workflow.

How much does “Make for Accounting 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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