Like any other industry, real state and construction are facing a challenging transformation. After some years of crisis, the sector is flourishing again and is ready to adopt new technologies. AI in the real estate and construction industries has the ability to reduce operational costs, improve customer service and improve efficiency.
Next, we list our solutions for Real Estate and Construction enterprises.
Real estate agents and property investors can be intelligently advised when a property meets
their investment or deal criteria, and at the same time, it can reduce
wasting time by automatically discarding the options that do not interest the customer.
Machine learning algorithms can personalize every customer interaction and
automatically tailor the message and imagery to increase the likelihood of selling a property.
Artificial intelligence can be used in property management to monitor and predict when critical maintenance systems are ready for replacement. The technology is also useful in keeping tabs on rental trends in specific geographical areas and raise tenant rents automatically when leases expire. Other property management details such as building automation and expansion analysis can be performed by property management companies to determine potential returns based on critical inputs that impact rents, expenses, and profits in rental housing.
In the real estate and construction industries, it is essential to
correctly maintain the properties and machinery.
Predictive maintenance uses machine learning and real-time data gathered from equipment to
notify the company's personnel when something is starting
to go wrong. That way the machinery can be fixed before there is a catastrophe. This method
goes beyond standard maintenance, using the actual condition of
an equipment to determine when repairs should be performed.
AI algorithms can be used to understand the current real estate market and make intelligent predictions on future market trends. Machine learning systems can analyze massive amount of data taking into account historical prices, locations, property details, demographic information, and economic trends to accurately predict the future price of a property.