Vi har analyseret Forsvarsministeriets bygningsportefølje med proprty.ai’s specialiserede AI-model – udviklet specifikt til at vurdere bygningers tilstand og planlægge vedligehold.
I forbindelse med udviklingen af den nye version af vores model til at forudsige bygningsdeles vedligeholdelsesomkostninger blev der lavet en masse behandling af nuværende data samt indhentning af data fra nye og kendte kilder. Det arbejde har vi nu udnyttet til også at udvikle en ny version af vores model til at forudsige bygningsdeles tilstand og resterende levetid.
Efter nogle måneders arbejde med at behandle allerede eksisterende data og indhente mere data fra kendte og nye kilder, har vi nu sat anden version af vores model...
Det er fristende at bruge Google Maps og Street View, til automatisk at tilstandsvurdere udvendige bygningsdele, ved hjælp af multimodale sprogmodeller. Men på...
PropTech Danmark er netop udkommet med deres seneste nye PropTech Rapport, og det er dælme interessant læsning! Rapporten er baseret på undersøgelser i samarbejde...
Så er MIPIM fandme i gang!
MIPIM er noget, vi har sammen – alle os i ejendomsbranchen. Efter check-in i lufthavnen er vi der. Tilstede. Nærværende. Klar til at...
Rebecca Siebenschuh is a student at HWZ University of Applied Sciences in Business Administration Zurich, where she’s pursuing a CAS in Smart Real Estate AI, Data, and Values. We had the pleasure of meeting Rebecca during her study visit to Copenhagen, where she was working on her final thesis. During her visit, Rebecca took a deep dive into the Swiss real estate market and focused on how AI-driven solutions, like those offered by proprty.ai, can help tackle some of the biggest challenges in the industry. As part of her thesis, Rebecca aimed to understand how the Swiss real estate sector could benefit from smarter, more efficient processes, especially given the growing pressure around sustainability and the need to digitize outdated practices. It’s been exciting to see how Rebecca’s research highlights the potential of AI to reshape the market, and we’re thrilled that our platform could play a role in her findings.
Switzerland’s real estate market is massive, with 3 million buildings and a value of CHF 3.1 trillion. However, despite its size and potential, the industry faces major hurdles. Outdated processes, fragmented data, and unpredictable maintenance costs are slowing progress. On top of that, there’s increasing pressure to meet sustainability goals, adding another layer of complexity. These challenges drive up costs, delay decision-making, and lead to inefficiencies—issues that AI is perfectly equipped to tackle.
Rebecca’s research dives into how AI-powered platforms like proprty.ai can solve these problems. Instead of relying on outdated methods, AI can help centralize data, predict when maintenance will be needed, and automate workflows. This means property managers won’t need to waste time sorting through spreadsheets and old systems. With AI, they’ll have real-time insights at their fingertips, allowing them to make quicker and better decisions.
AI also helps with sustainability efforts. By simplifying ESG reporting (which focuses on environmental, social, and governance factors), AI can make it easier for real estate companies to meet their sustainability targets, ensuring that their buildings stay compliant with the latest regulations.
To successfully introduce AI into Swiss real estate, Rebecca outlines a step-by-step strategy:
1. Form strong partnerships with key players to build credibility and integrate with the existing ecosystem.
2. Launch pilot projects with major industry stakeholders to test AI-driven insights and demonstrate real-world impact.
3. Scale up and localize by adapting to Swiss regulations, expanding multilingual support, and refining the platform based on user feedback.
Her thesis suggests that by following this approach, proprty.ai can drive real change in Swiss real estate and position itself as a leader in the industry’s digital transformation.
After reading Rebecca’s research, we’re more convinced than ever that AI is the key to modernizing the Swiss real estate market. The challenges she highlighted—scattered data, unpredictable maintenance costs, and the pressure to meet sustainability goals—are real pain points that proprty.ai is uniquely positioned to solve
We see Rebecca’s work as more than just a thesis—it’s a clear roadmap for how we can successfully enter the Swiss market. Her suggestions around building strong partnerships, piloting with industry giants, and localizing our platform are all steps we’re excited to take. This research has not only mapped out the potential of AI in Switzerland but also provided a strategic framework for our next moves.
By following these insights, we believe proprty.ai can make a lasting impact on Swiss real estate, helping property managers stay ahead of the curve in an industry ripe for digital transformation. We’re excited to turn these observations into action and can’t wait to see where this journey takes us!
Hos proprty.ai arbejder vi hele tiden på at gøre vedligeholdsplaner mere brugbare, effektive og...
Du har fået tilstandsvurderet dine ejendomme af eksterne specialister og modtaget tilstandsrapporter. Dette er et vigtigt skridt mod at forstå bygningernes stand, planlægge fremtidige cashflow-behov og optimere afkast eller budgetter. Men hvad nu? Mange oplever, at tilstandsrapporter er fyldt med kvalitative vurderinger og generelle anbefalinger, som kan være svære at omsætte til konkrete handlinger. Hvordan sikrer du, at denne information bliver brugbar til at træffe databaserede beslutninger og handle effektivt?
En af de største udfordringer ved tilstandsrapporter er, at de ofte indeholder lange, teksttunge beskrivelser og subjektive vurderinger. Ejendomsadministratorer og beslutningstagere kan derfor have svært ved at overskue og kvantificere opgaverne på en måde, der gør prioritering og budgettering lettere.
Tilstandsrapporter indeholder typisk detaljerede beskrivelser af bygningens opbygning, materialer og tilstand, ofte ledsaget af billededokumentation. Men for at omsætte disse rapporter til konkrete handlingspunkter kræves der omfattende efterbehandling. Tiltagene skal desuden integreres i et FM-system, så opgaverne kan videreføres til de rette aktører. Denne proces er ofte tids- og ressourcekrævende og mangler en direkte kobling til praksis.
Derudover er det svært at generalisere tilstanden og de økonomiske udgifter på tværs af ejendomsporteføljen, da tilstandsrapporterne ikke er databaserede, og vurderingskriterierne varierer fra rapport til rapport.
For at gøre tilstandsvurderingerne mere operationelle bør der stilles krav om en mere struktureret tilgang, hvor kvalitative vurderinger omdannes til kvantificerbare data. Her er nogle vigtige principper:
Ved at fokusere på kvantificerbare data og digitale løsninger kan du gøre dine tilstandsvurderinger langt mere operationelle – og dermed træffe de rette beslutninger hurtigere.