What proprty.ai does
proprty.ai is a Danish software company that develops domain-specific artificial intelligence for long-term maintenance planning and prioritisation in property portfolios.
The company was founded in 2022 and is headquartered in Copenhagen, Denmark. The primary market is Denmark, with expansion into other European markets. proprty.ai received the Danish Basic Data Prize in 2025.
The problem we address
Property owners and operators must make long-term maintenance and investment decisions under tight constraints.
Budgets are fixed. Regulatory and documentation requirements are increasing. Sustainability targets must be met. At the same time, building components age over decades, and decisions made today affect cost, risk, and emissions far into the future.
The challenge is not identifying isolated risks in individual buildings. The challenge is deciding what to do first, what can be postponed, and how maintenance and investment decisions interact across an entire portfolio over time.
Traditional condition assessments, spreadsheets, and generic analytics tools do not support this type of portfolio-level decision-making.
Our approach to artificial intelligence
proprty.ai uses domain-specific machine learning models combined with explicit domain logic.
The system is designed to solve sequential decision problems under real-world constraints. It is not designed to generate generic text-based answers or stand-alone predictions.
Large language models are used for interface-level tasks such as explanation and navigation. Core maintenance planning, prioritisation, and optimisation are not delegated to general-purpose AI models.
This approach supports transparency, auditability, and governance requirements in regulated European markets.
What our software does
proprty.ai translates building data into prioritised and auditable maintenance and investment plans.
The platform combines structured public building data, such as building registers and energy labels, with owner-specific operational and maintenance data. These data sources are processed using domain-specific models for building components, degradation, and remaining lifetime.
Based on this, the system produces scenario-based maintenance plans that account for budget limits, regulatory requirements, and long-term portfolio trade-offs.
The output is not a single prediction or risk score. It is a prioritised set of feasible actions over time.
What we are not
proprty.ai is not a generic AI assistant or chatbot.
It is not a dashboard-only analytics tool, a stand-alone prediction engine, or a consulting service.
The platform is built as an operational decision-support system that integrates into existing maintenance, budgeting, and documentation processes.
Who the platform is built for
The platform is used by organisations responsible for large and complex property portfolios, including municipalities, public-sector property owners, social housing organisations, institutional and private property investors, and professional property administrators.
The system is designed for European markets with strong regulatory, documentation, and sustainability requirements.
Data, governance, and transparency
proprty.ai is built for environments where decisions must be explainable and defensible.
Models are trained and applied using structured data sources and documented assumptions. Outputs are designed to support internal decision-making, political and organisational processes, and external reporting requirements.
Professional judgment remains central. The system supports decision-making by providing a consistent and transparent basis for prioritisation.