The investor realizes that the data is inconsistent and goes back to previous steps to obtain new listings and verify the data.
The investor conducts research and compiles all data in an Excel spreadsheet.
The investor goes to online classifieds to double-check the information and goes to developers' websites to verify the data.
An agent contacts the investor by phone and sends them property listings.
An investor visits a real estate agency website and submits a request.
The investor finds a property and attempts to make a reservation, but it has already been sold.
The investor searches for a new property, sends money, fills out a booking form, and goes to a SPA.
After some time, the investor wants to sell the property but does not know its current value or when to sell.
As a result, the investor may end up with the property, sell it at a significant discount, or sell it successfully.
Investor makes an online reservation
Investor browses through best offers Investor sees all information about developers and competitors in one
Investor visits Realiste Platform
Investor sells the real estate.
Investor receives SPA
The investor reads news and studies the real estate market to determine when it is best to sell the property.
The investor contacts the agent and discusses the sales conditions.
The agent does not want to sell the property, and the investor tries to contact other agents to sell it.
#1 AI Broker for real estate investments
2 000 000+
We analyze 2 000 000+ real estate properties daily for accurate data analysis and market trend forecasting, improving price information and development prospects.
We are increasing our business efficiency by reducing the use of manual labor and speeding up the decision-making process by two times. This is achieved through real-time data analysis.
We improve customer service with personalized offers and precise analytics, resulting in higher satisfaction and accurate evaluations.
Technology for buying and selling
AI improves the real estate market by helping investors, agents, and developers make faster decisions and improve forecasting accuracy. The result is an improved service for clients doubling returns and reducing risk by up to 99%.
AI Realiste is a self-learning algorithm whose task is to evaluate any apartment in the world, taking into account local preferences (simulating the decision-making process of a buyer in a specific location) in order to determine the investment attractiveness of real estate.
What data we use
The algorithm uses a large amount of input data from dozens of sources, in some cities in the world it uses more than 200 parameters (sources and parameters will be listed below and their weight in the algorithm structure).
VERY HIGH impact
CRM systems of Developers
Building location ( Latitude/Longitude )
Parameters of the apartment 20-27 criteria (area, floor, repair, the presence of a balcony, terrace, etc.)
Top 3 real estate websites in the city
Public data ( deals )
Year of construction /reconstruction
Points of attraction
Transport accessibility in minute
Infrastructure data (Google map)
Infrastructure data from Wikimapia
Infrastructure data from OpenStreetMap
Nasdaq index Data
Traffic attraction points
Sites of construction and repair companies
Data on the cost of materials and work
Utilities Condition of houses
Reviews on review sites ( about the building )
Semi-automatic map marking Districts, special zones
Databases of taxes
Cadastral number of the sold apartment Cadastral number of the apartment for sale
VERY HIGH impact
Exposure time current
Sold price of apartments
The exposition period of the sold apartment
Count of sold apartments
Liquidity of the apartment
Transport accessibility in minutes by car
Transport accessibility in minutes total
House reputation patent for house rating algorithm
Reputation of the district
Apartment rating among competitors
Falling prices / growth / stagnation
Listing price changes
Correlation of changes in price and volume of supply
Correlation of supply volume and dynamics of demand
Factual data from users
Feedback from users
The power of demand
Marketplace sites Data on the cost of materials and work for repairment
Points of attraction
Number of floors
Liquidity of the area
Presentation of material (positive/negative) in mass media
Recognition of the recontact level on a 10-point scale from photographs
Archived data for listings on websites
Who help us succeed
More than 30 top officials in MENA support Realiste and provide market's insights from EMAAR, Ministry of Economy UAE, Nakheel, Al Jaber Group & etc.
The future of the real estate investments starts here!