Training course · Make · Recruiting

Make for Recruiters

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 Recruiters” is designed for roles such as Recruiters and talent acquisition managers, Sourcers and HR generalists with recruiting responsibility and shows step by step how to use Make productively, safely and transparently in Recruiting – 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.

With talent shortages in many fields, recruiting has become a key business function: candidates must be found, convinced and guided quickly through the process. Generative AI supports recruiters at many points of the candidate journey. AI assistants write job ads that speak to the target group, build search strings for active sourcing, draft personal outreach messages, prepare structured interview guides and summarise interview notes. Automation handles scheduling, acknowledgements and status updates for applicants. At the same time, recruiting is a particularly sensitive area: selection decisions must be non-discriminatory and transparent, and AI systems used to screen candidates face strict requirements. Using AI for communication, structure and efficiency while keeping selection in human hands improves both candidate experience and time to hire.

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?

  • Recruiters and talent acquisition managers
  • Sourcers
  • HR generalists with recruiting responsibility
  • Employer branding leads
  • Recruitment consultants and staffing agencies

Typical challenges we address

  • Finding and approaching suitable candidates in tight labour markets
  • Writing job ads that genuinely reach the target group
  • Running fast application processes with a good candidate experience
  • Making fair, structured and legally sound selection decisions

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.
  • Create targeted job ads, sourcing strategies and outreach messages with AI.
  • Structure selection processes with AI-supported guides and improve the candidate experience.
  • Use AI in recruiting in line with anti-discrimination law, the GDPR and the EU AI Act.

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: Recruiting
  • Job ad optimisation
  • Active sourcing strategies
  • Personal outreach
  • Structured interview guides
  • Candidate communication
  • Recruiting metrics analysis
Module 7 Data protection, quality & transfer to daily work
  • Selection processes must comply with anti-discrimination law such as the German General Equal Treatment Act (AGG); AI must not disadvantage people based on age, gender or origin. Applicant data is protected by the GDPR, solely automated rejections are not permitted under Article 22 GDPR, and AI systems for screening and selecting candidates are high-risk under the EU AI 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

Job ad optimisation

An AI assistant turns the role profile and team information into an inclusive job ad tailored to the target group, checks it for gender-neutral language and unnecessary barriers and creates variants for different channels.

Active sourcing strategies

AI builds Boolean search strings, alternative job titles and relevant skills for professional networks and job boards and suggests target companies and communities for direct approach.

Personal outreach

Based on the public profile and the role, AI drafts individual contact messages and follow-ups that make the specific value of the position clear to the person.

Structured interview guides

AI creates competency-based interview questions, rating anchors and case exercises for a role, so that all candidates are assessed against the same criteria.

Candidate communication

Automations send acknowledgements, scheduling proposals and status updates, while AI drafts respectful rejections and offers that recruiters review before sending.

Recruiting metrics analysis

Applicant tracking system exports are analysed for time to hire, channel performance and drop-off rates, bottlenecks identified and improvements proposed.

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 recruiting or talent acquisition and know your organisation's hiring process.

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

Selection processes must comply with anti-discrimination law such as the German General Equal Treatment Act (AGG); AI must not disadvantage people based on age, gender or origin. Applicant data is protected by the GDPR, solely automated rejections are not permitted under Article 22 GDPR, and AI systems for screening and selecting candidates are high-risk under the EU AI Act.

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 Berlin Request
  • Tue, 15 December 2026 – Wed, 16 December 2026 Online Request
  • Tue, 12 January 2027 – Wed, 13 January 2027 Stuttgart Request
  • Thu, 28 January 2027 – Fri, 29 January 2027 Online Request
  • Mon, 8 February 2027 – Tue, 9 February 2027 Hanover 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.

May AI pre-screen applications?

Systems that filter or rank applications are classified as high-risk AI under the EU AI Act, with extensive obligations. The GDPR also prohibits solely automated rejections. The course therefore focuses on AI for communication, structure and preparation, while screening and decisions remain with people.

How do we avoid discrimination by AI?

Language models can reproduce biases from their training data, for example in job ad wording. Check outputs specifically for protected characteristics, use structured criteria and never enter sensitive data into AI tools. We practise concrete review questions that you can adopt in your process.

How much does “Make for Recruiters” 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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