Training course · Make · Consulting

Make for Consultants

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 Consultants” is designed for roles such as Management and strategy consultants, IT and process consultants and In-house consulting teams and shows step by step how to use Make productively, safely and transparently in Consulting – 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.

Consulting thrives on rapid onboarding, structured analysis and persuasive communication – exactly where generative AI makes a difference. Consultants use AI assistants to get up to speed on new industries, synthesise interview notes, build hypothesis trees, analyse client data and develop storylines for steering committees. AI agents support desk research, document comparison and first slide drafts. At the same time, AI is reshaping the business model: clients expect faster results and ask what value consultants add beyond what they could generate with AI themselves. Consultants who use AI confidently shift their time from grunt work towards judgement, implementation support and relationship building.

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?

  • Management and strategy consultants
  • IT and process consultants
  • In-house consulting teams
  • Independent consultants
  • Analysts and junior consultants

Typical challenges we address

  • Short ramp-up time for new clients, industries and topics
  • Large volumes of interviews, documents and data under time pressure
  • Heavy effort for slides, reports and proposals
  • Confidentiality of client information when using AI

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.
  • Accelerate onboarding, research and synthesis in consulting projects with AI.
  • Develop structured storylines, slides and proposals with AI support.
  • Use AI in client work in line with confidentiality obligations and communicate its use transparently.

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: Consulting
  • Rapid onboarding
  • Synthesising interviews
  • Hypotheses and issue trees
  • Storylines and slides
  • Proposals and bids
  • Faster data analysis
Module 7 Data protection, quality & transfer to daily work
  • Client information is usually covered by confidentiality agreements and may only be processed in AI environments cleared contractually and under data protection law. AI use should be agreed with the client, and personal interview data must be handled in line with the GDPR.
  • 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

Rapid onboarding

AI produces industry overviews, explains terminology, value chains and typical KPIs and drafts key questions for the kick-off – as a starting point to be verified with reliable sources.

Synthesising interviews

Notes from stakeholder interviews are organised by theme, pain point and quote, patterns and contradictions are drawn out and the results prepared as a basis for hypotheses.

Hypotheses and issue trees

Problems are broken down with AI into mutually exclusive, collectively exhaustive sub-questions, hypotheses are formulated and the required analyses and data sources derived. This quickly yields a robust workplan for the team.

Storylines and slides

Analysis results become pyramid-structured storylines, action titles and slide drafts, which the team then sharpens and builds out in the house style. The core message stays at the centre of every slide.

Proposals and bids

Tender documents are analysed, requirements turned into checklists and proposal sections on approach, work packages and team profile written with a clear focus. The client's evaluation criteria are addressed directly.

Faster data analysis

Client data is cleaned, analysed and visualised with AI support, for example for benchmarks, cost analyses or process KPIs, with documented calculation steps. Sanity checks safeguard quality before client presentations.

Prerequisites

You should be comfortable with common office and cloud applications and have some experience with AI assistants. No programming skills are required. Experience in consulting projects or analytical project roles; 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

Client information is usually covered by confidentiality agreements and may only be processed in AI environments cleared contractually and under data protection law. AI use should be agreed with the client, and personal interview data must be handled in line with the GDPR.

Suggested dates

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

  • Thu, 26 November 2026 – Fri, 27 November 2026 Online Request
  • Thu, 10 December 2026 – Fri, 11 December 2026 Stuttgart Request
  • Wed, 13 January 2027 – Thu, 14 January 2027 Online Request
  • Mon, 25 January 2027 – Tue, 26 January 2027 Berlin Request
  • Thu, 11 February 2027 – Fri, 12 February 2027 Online Request
  • Wed, 24 February 2027 – Thu, 25 February 2027 Munich 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 I use client data in AI tools?

Only if the contract, NDA and your firm's policies permit it and the tool is covered contractually. It is often sensible to agree AI use with the client. The course shows how to work with anonymised data and set clear rules for project teams.

Will AI make consultants redundant?

Grunt work such as desk research or first slide drafts becomes cheaper. Judgement, industry experience, facilitation and implementation support remain in demand. Firms that use AI well deliver faster and can invest more time in real impact for clients. Value shifts towards advice quality and outcomes.

How much does “Make for Consultants” 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.

More courses for Consultants

More Make courses

All 45 Make courses

Make · MunichMake · SalzburgMake · BerlinMake · AugsburgMake · HanoverMake · BremenMake · StuttgartMake · KaiserslauternMake · Online