proprty.ai
proprty.ai is a Danish platform that applies domain-specific AI to building maintenance. It scores condition, forecasts remaining service life and turns public registers and FM data into prioritised, budgeted maintenance plans for large property portfolios.
What is proprty.ai?
proprty.ai is a Danish software platform that applies domain-specific artificial intelligence to long-term maintenance planning across large property portfolios. It is built for organisations that must decide what to repair first, what can wait, and how those choices interact across hundreds of buildings over many years: municipalities, public property owners, social housing organisations, institutional and private investors, and professional administrators.
The platform works in three movements. It first consolidates data, pulling automatically from Danish public registers — BBR for buildings and dwellings, OIS for valuations and ownership, DAR for addresses, the land registry, the owner register EJF, energy labels from the Danish Energy Agency, aerial imagery and Google Maps — and combining them with records from FM systems and the customer's own operational data. It then scores condition and calculates the remaining service life of individual building components, work the vendor says takes seconds and reaches 85% accuracy, validated on more than 4,000 buildings. Finally it produces prioritised maintenance plans that carry budgets, update themselves as data changes, and can be compared as scenarios against cost, risk and regulation.
A sustainability module tracks energy consumption, calculates the portfolio's CO₂ footprint and ranks the improvements that cut emissions most cheaply. It currently works only in Denmark, and only for buildings that already hold an energy label; a grant-funded rebuild aims to base it on measured consumption and extend it across Europe.
What sets the product apart is how narrowly it defines its own AI. Analysis runs on machine-learning models specific to the building domain, combined with explicit domain logic. Large language models are used only for interface tasks such as explanation, navigation and user support, and never for analysis, planning or optimisation. The vendor describes the system as decision support rather than a decision-maker: recommendations trace back to the data and assumptions behind them, and final responsibility stays with the organisation. Customers reportedly manage over 40 million m² across Denmark, Norway, Switzerland and Germany. A Standard API ships with the base package, while Dalux integration and Power BI reporting are sold as options.
What it does
- Assess a building's condition automatically from data, in seconds
- Forecast the remaining service life of individual building components
- Generate and continuously update prioritised maintenance plans that carry budgets
- Consolidate public registers, FM systems and in-house records into a single view
- Calculate portfolio CO₂ and energy use, then rank the most cost-effective improvements
- Quantify the maintenance backlog and compare scenarios across the whole portfolio
- Produce traceable reports for management, elected officials and compliance
When to use proprty.ai / When not to
A quick filter to help you decide if proprty.ai is the right fit.
When to use proprty.ai
- Municipalities and public property owners responsible for large building stocks
- Social housing organisations planning maintenance and rent levels years ahead
- Operations managers who run day-to-day upkeep across many buildings
- Asset and fund managers overseeing institutional real-estate portfolios
- ESG and sustainability officers reporting on CO₂ and energy performance
When not to use proprty.ai
- Homeowners and small landlords with a single property: the platform is sized for large portfolios
- Estate agents and property marketers, since the vendor states it is not a listings or advertising platform
- Investors hunting for a deal-sourcing, pricing or valuation tool
- Anyone looking for a general-purpose AI assistant or chatbot
- Teams that want instant self-service sign-up, as entry runs through a scoped, quoted proof of concept
How to use proprty.ai
A typical end-to-end flow, from setup to results.
- Contact the team through the website form, or book a demonstration
- Request a proof of concept, the vendor's standard entry route, and receive a tailored quote
- Check the terms: the PoC carries no binding period and ends on one month's notice
- Have your organisation's profile set up during vendor-led onboarding
- Create user accounts, which the vendor does not cap in number
- Add your properties to the system
- Connect the data sources: public registers, FM systems and your own operational records
- Have your super-users trained so they can support the wider organisation
- Review the generated condition assessments and remaining service-life forecasts
- Work from the maintenance plans, comparing budget scenarios and tracking CO₂ over time
Pros & Cons
Pros
- Domain-specific machine learning rather than a repackaged chatbot, with the vendor stating plainly that large language models touch only the interface
- Recommendations trace back to source data, assumptions and scenarios, so decisions can be explained and audited
- Native links to Danish public registers mean a portfolio can be assessed from public data alone, without building a dataset first
- Claimed 85% accuracy validated across more than 4,000 buildings
- Fast to start: typically running within a day, with no cap on the number of users
- Volume-tiered rates are published openly, and the proof of concept carries no lock-in
- Named, checkable public-sector references including KAB, By & Havn, Københavns Ejendomme and Rudersdal Kommune
Cons
- No terms and conditions are published at all, leaving data ownership, service levels and liability undocumented
- Customer data is used to improve the models, and no opt-out is documented anywhere on the site
- No hosting country, no named subprocessors, no data processing agreement and no security certification
- No firm price without a quote, since the entry route is a scoped proof of concept
- Data depth is heavily Danish, and the CO₂ module works only in Denmark and only where an energy label already exists
- An API is sold as a standard feature, yet no public documentation for it exists
- The legal notice still shows an address the Danish business register superseded in May 2026
Pricing & Plans
There is no free plan and no free trial. Pricing is quoted per square metre of portfolio per year and falls as total area grows: the English pricing page opens at €0.27 per m² per year, with published tiers of €0.27, €0.15, €0.12 and €0.04, while the Danish page states the same rates as 2.00, 1.15, 0.90 and 0.30 kroner. Because the charge is levied per square metre rather than per user or per month, the entry ticket depends entirely on portfolio size and cannot honestly be reduced to a single figure. The standard commercial route is a proof of concept priced by tailored quote, with no binding period and one month's notice.
- the standard entry route
- priced by tailored quote
- no binding period
- one month's notice
- condition assessment
- prioritised maintenance plan with budget
- and Standard API
- optional Dalux integration
- Power BI reports in beta
- and the Sustainability module
- Across all packages
- rates start at €0.27 (2.00 kroner) per m² per year and fall as portfolio area grows
Data, GDPR & hosting
A consolidated view of how proprty.ai handles your data.
GDPR overview
Implementation is documented and specific, though it lives entirely in the privacy policy dated 10 September 2024. proprty.ai ApS is named as data controller and cites its legal bases article by article: Article 6(1)(b) for contract, 6(1)(c) for legal obligation, 6(1)(a) for consent and 6(1)(f) for legitimate interests, with a documented balancing test. Data categories, recipients and all data-subject rights are enumerated, portability and withdrawal of consent included. Personal data is not transferred outside the EU or EEA unless Chapter V of the GDPR is satisfied. Non-essential cookies require consent, and on the platform itself cookies are limited to technical authentication. Datatilsynet is named as supervisory authority. No data protection officer is designated, and no Article 27 representative applies since the company is established in Denmark.
Who owns the data?
proprty.ai publishes no terms and conditions, so no contractual clause states who owns the building and operational data a customer brings to the platform. The only legal document is the privacy policy, which covers personal data alone. It names proprty.ai ApS, CVR 43641298, as data controller and says external processors handle data on the vendor's instructions, under confidentiality, for technical operation, newsletters and customer feedback; none is named. Personal data may be passed to third parties acting as independent controllers to establish or defend legal claims, protect safety, investigate fraud or answer public authorities, and may transfer to any entity that buys or merges with the business. The pricing FAQ adds that customer data feeds model improvement.
Reuse rights
With no terms of use published, nothing defines what a customer may do with platform outputs without asking permission. Under the privacy policy individuals hold the standard GDPR rights, including portability of the personal data they themselves supplied, alongside access, rectification, erasure, restriction, objection and withdrawal of consent. In practice the vendor presents its outputs — condition assessments, prioritised maintenance plans, scenarios and reports — as material customers put to work in their own processes, including political decision-making, and states that every recommendation can be traced back to the underlying data and assumptions so it can be explained, reviewed and documented externally. Power BI reporting is offered as a paid option, still in beta.
Data retention & training
Hosting summary
proprty.ai publishes no hosting jurisdiction. Neither the privacy policy nor any other page names a country, a region, a cloud provider or a data centre for the platform. The one adjacent statement is a transfer clause: personal data is not transferred to recipients outside the EU or EEA unless compliance with Chapter V of the GDPR has been secured. That governs transfers, not where the platform runs, and should not be read as a hosting declaration. The company is established in Denmark, is subject to the GDPR and names Datatilsynet as its supervisory authority, which places the controller inside the EU even though the processing location is undisclosed. External data processors are acknowledged for technical operation, newsletter distribution and customer feedback, but none is named or located. On the platform itself, cookies are limited to technical authentication. The public website is built with Webflow and served through Cloudflare, which says nothing about where the application and its customer data actually reside. Buyers with hosting requirements will have to ask.
Things to keep in mind
Risks and trade-offs to weigh before adopting proprty.ai.
- No terms and conditions are published, so ownership of the building data you upload, service levels, liability and exit terms are documented nowhere
- The vendor states customer data is used to build better models, and no opt-out is offered or even declared unavailable
- No hosting jurisdiction, no named subprocessors, no data processing agreement and no security certification, which is a real gap for public buyers
- Over-reliance is a genuine risk: the vendor itself insists the tool supports decisions rather than making them, and does not replace condition surveys or professional judgement
- Performance figures such as 85% accuracy, 20% lower costs and 90% of forecasts used directly in budgets are vendor or customer claims, none independently audited
- Coverage is Denmark-centric: outside Denmark the data foundation is thinner, and the CO₂ module still needs an existing Danish energy label
- Identity confusion is real and the vendor addresses it directly — proprty.ai is not PropertyAI, Properti.ai or Prop-AI — and its legal notice still shows an address the Danish register replaced in May 2026
Setup & Integrations
Technical difficulty
Low for the customer. Onboarding is vendor-led: the team sets up the organisation profile, creates users, loads the properties and trains super-users, with the platform typically running within a day and no limit on user numbers. Public registers connect automatically, so a portfolio can be assessed without assembling a dataset first. Dalux is offered as a standard integration and a Standard API is included for existing systems, though no public documentation exists for it. The real effort is organisational rather than technical: gathering and cleaning whatever operational and maintenance data the customer already holds.
Deployment
Integrations
Supported languages
Behind proprty.ai
Fundraising
Social
Resources
All the official URLs gathered for verification and reference.
Frequently asked questions
What does proprty.ai actually do?
What kind of AI does it use?
Does it make decisions on my behalf?
What does it cost?
How do I get started, and how long does it take?
Which data sources does it draw on?
Is my data used to train the models?
Is there a mobile app or an API?
Should you pick proprty.ai?
proprty.ai is a narrow, serious tool rather than a general AI product, and it benefits from that focus. The vendor is unusually candid about where its intelligence sits: machine-learning models trained on the building domain do the analysis, while large language models are confined to explaining and navigating. Recommendations trace back to the data and assumptions behind them, which matters a great deal for public buyers who must defend a maintenance budget to auditors or elected officials. The native hook into Danish public registers is the other real strength, because it lets an organisation get value from data it already has rather than commissioning a survey first. Named references such as KAB, By & Havn and Københavns Ejendomme are checkable, and the company reports profitability and more than €1 million in ARR within two years of launch.
The reservations are contractual rather than technical. No terms and conditions are published at all, so nothing on the site defines who owns the operational data you upload, what service levels apply, or how you would leave. The pricing FAQ states that customer data is used to build better models, and no opt-out is offered or even declared unavailable. There is no stated hosting jurisdiction, no named subprocessor, no data processing agreement and no security certification — a combination that will stall most public procurement reviews. Pricing is transparent in its rates but unknowable in its total until a portfolio is measured, and coverage remains Denmark-centric, with the CO₂ module still requiring an existing Danish energy label.
For a large European property owner, proprty.ai is worth a proof of concept. Go into it with a list of contractual questions the website does not answer.
- Choosing a selection results in a full page refresh.
- Opens in a new window.