Identify Water Leaks
To evaluate how well AI can classify cases as water leak–related, creating a new datapoint that can be used in maintenance planning and analysis.
Tid | 3 nov 2025 – 1 feb 2026 |
|---|---|
Plats | Digitally |
This AI project is co-funded by the EU – via the European Regional Development Fund (ERDF) and the Just Transition Fund.
What we want to solve
By analyzing the text in case descriptions, we want to automatically classify whether a case is related to a water leak or not.
This creates a binary datapoint for every case:
Water leak: Yes / No
This datapoint can then be used in dashboards, analyses, and maintenance planning to identify where and how often water leaks occur in the property portfolio.
Example case description:
”Water has started to run down into the hallway from the ceiling. We suspect that a pipe in the wall has burst.”
Generated datapoint:
Water leak: Yes
What value does it create?
With better insights into water leaks, property management can make more accurate decisions regarding planned maintenance, especially for piping, waterproofing, or plumbing systems.
Example:
”We were able to prioritize the right buildings in this year’s maintenance budget, since we identified a pattern of water leaks in certain properties.”
What happens if we don’t do this?
Risk of incorrect priorities in maintenance budgets.
Higher costs due to emergency repairs.
A worse living environment for tenants.
For whom?
This test is aimed at those who:
Are responsible for maintenance planning or technical property management.
Make decisions about investments in plumbing systems, waterproofing, or piping.
Work with analysis and follow-up of property operations and costs.
The test group’s mission
The beta program runs for about 12 weeks and is carried out together with a small group of selected real estate companies. The goal is to understand how the categorization works in practice and what value it can create in decision-making.
Registration, Form, and Selection (Weeks 42–44)
Fill in your name and email address above, and we’ll contact you with a short form to understand why this information matters to you. During this period, you’ll also manually classify 100 of your own cases. These will later be used to compare with the automated classification in Homepal.
Meeting 1: Precision and Classification (Weeks 45–46)
In the first meeting, we focus on how accurately the AI classifies your cases. Together we review the results and discuss:
Do the classifications match reality?
Is anything important missing, or does something feel unnecessary?
What kinds of decisions or insights could this help you make in everyday work?
We compare the automated classification with your manual assessments and talk about what works well and what might need adjustment. You’ll also see how Homepal categorizes your cases — and have the chance to influence how this should look going forward.
Further Development Based on Feedback (Weeks 47–48)
Homepal improves the classification based on what we learned in the first meeting. If needed, we’ll add new categories, remove unnecessary ones, or fine-tune the logic to make the results even more relevant.
Meeting 2: Using the Classification (Weeks 49–50)
Now we shift focus from testing to real use.
You’ll gain access to a dashboard showing your classified cases, where you can start analyzing:
Which types of cases dominate.
Where issues occur most frequently.
How the insights can support prioritization and planning of actions.
We also collect feedback — does this help you make faster and better decisions? After the meeting, we’ll make small adjustments to ensure everything works smoothly.
Beta in Use (Weeks 51–4)
During this period, you’ll use the dashboards and analyses in your daily work. Homepal follows up together with you, collects feedback, and makes small improvements along the way.
Evaluation and Closing (Week 5)
We end with a joint session focused on the most important question — what real value the AI classification has created in practice. The goal is to understand how Homepal’s solution needs to evolve to deliver even greater impact in real-world use, and to identify whether there are areas where the current setup doesn’t yet provide sufficient value.
Why participate?
As a participant in the test group you will:
Have a unique opportunity to influence the continued development of the solution.
Gain early insights into where water leaks occur and how often.
Take part in discussions about how data can be turned into decisions that reduce costs and improve the tenant experience.
Directly impact which features and priorities are developed next.
Participation requirements
The test group has a limited number of places. To participate, you need to:
Submit your role and a short motivation explaining why this information is important to you.
Describe which decision(s) you hope to make based on the material.
Commit to attending all three sessions and set aside time between meetings to review the sample cases.

