Training course · Make · Real Estate

Make for Real Estate Professionals

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 Real Estate Professionals” is a hands-on course for roles such as Estate agents and sales teams, Residential and block property managers and Asset and property managers. Rather than learning Make in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from Real Estate.

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.

Much of the work in real estate revolves around documents: property listings, leases, service charge statements, minutes of owners' meetings, valuation reports and an endless stream of enquiries from prospects and tenants. Generative AI takes over the routine – drafting listings from key facts, summarising declarations of division and valuation reports, answering standard questions up front and structuring repair requests. AI agents connect the inbox, property database and scheduling into end-to-end workflows. For agents, property managers and asset managers this frees up time for viewings, negotiations and owner relations. What matters is handling tenant and owner data responsibly and having an expert check every legally relevant statement before it goes out.

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?

  • Estate agents and sales teams
  • Residential and block property managers
  • Asset and property managers
  • Developers and housebuilders
  • Staff at housing companies and cooperatives

Typical challenges we address

  • A high volume of recurring enquiries from prospects, tenants and owners
  • Time-consuming drafting of listings, letters and meeting minutes
  • Extensive lease and property documentation that must be grasped quickly
  • Data scattered across property management software, email and spreadsheets

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.
  • Produce listings, tenant letters and minutes with AI much faster and at consistent quality.
  • Analyse leases and property documents with AI in a structured way and review the results professionally.
  • Design simple automations for enquiries, repair requests and reporting across your portfolio.

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: Real Estate
  • Listings from key facts
  • Pre-qualifying enquiries
  • Minutes of owners' meetings
  • Summarising contract documents
  • Structuring repair requests
  • Market and owner reports
Module 7 Data protection, quality & transfer to daily work
  • Tenant, owner and prospect data falls under the GDPR, especially tenant self-disclosures and credit documents, and belongs only in approved AI environments. Legally relevant content such as contract clauses, mandatory listing details or resolution wording must be reviewed by a qualified person.
  • 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

Listings from key facts

Floor plans, location details and specification lists become compelling property descriptions in several tones and languages, which the team then reviews and completes with mandatory details such as energy performance data.

Pre-qualifying enquiries

An AI assistant triages incoming enquiries, answers standard questions about the property and documents, asks for missing details such as household size or financing status and proposes suitable viewing slots.

Minutes of owners' meetings

Notes or transcripts are turned into structured minutes with resolution wording, voting results and an action list, which the property manager checks before circulating and adding to the record of resolutions.

Summarising contract documents

Leases, declarations of division and valuation reports are condensed into key points such as terms, indexation clauses, exclusive use rights and maintenance obligations, speeding up due diligence and property handovers.

Structuring repair requests

Free-text tenant reports are classified by trade, urgency and property, enriched with follow-up questions and turned into draft work orders for contractors – including an acknowledgement to the tenant.

Market and owner reports

AI helps draft quarterly reports for owners and investors, summarising vacancies, letting activity and maintenance work from existing data and adding clear commentary on variances.

Prerequisites

You should be comfortable with common office and cloud applications and have some experience with AI assistants. No programming skills are required. Hands-on experience in property marketing, management or asset management; 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

Tenant, owner and prospect data falls under the GDPR, especially tenant self-disclosures and credit documents, and belongs only in approved AI environments. Legally relevant content such as contract clauses, mandatory listing details or resolution wording must be reviewed by a qualified person.

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
  • Mon, 14 December 2026 – Tue, 15 December 2026 Online Request
  • Mon, 11 January 2027 – Tue, 12 January 2027 Bremen Request
  • Thu, 21 January 2027 – Fri, 22 January 2027 Online Request
  • Wed, 3 February 2027 – Thu, 4 February 2027 Augsburg 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 enter tenant data into an AI assistant?

Only in an environment approved by your organisation, backed by a data processing agreement and clear rules. In the course we show how to pseudonymise data, which information never belongs in public tools and how to work with placeholders without losing the benefits of AI.

Will AI replace agents and property managers?

No. AI handles drafting, triage and summaries. Viewings, negotiations, owners' meetings and legal responsibility stay with you. The gain lies in time freed up for client conversations and in faster, more consistent day-to-day processes. Error rates in routine correspondence also tend to fall.

How much does “Make for Real Estate Professionals” 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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