Our method involves using large amounts of data. In everyday terms, you may hear the words BIG DATA. This is where all the magic begins,  but it’s not as simple as it seems. Before we can even begin to push all the information we gather through our models, we need to first determine if a house is in fact a house and not a storage shed.

At Appraisal we understand the power of large scale datasets. We know that the quantity of data can literally affect the quality of the model. Therefore, AI models need large datasets to learn.

Our models include the following data:

ALL of U.S. home pricing 
data available

ALL of U.S. home pricing
data available

(including the 13 non-disclosure states)

Neighborhood 
information

Neighborhood
information

(crime, tax rates, schools, school rankings, hospitals, religious institutions, etc.)

Geo Spatial 
Data Sets

Geo Spatial
Data Sets

Social-economic 
data

Social-economic
data

(census)

Spatial data

Spatial data

(distance to the nearest: water body, highway, store, hospital, police department,firehouse, etc.)

FEMA

FEMA

(Flood Insurance Rate Map (FIRM) areas)

Building the Data Fabric requires us to establish uniformity across all the data at the right time and in the right way. We use a proprietary polygon engine in the standardization and unification of the data we collect to create data sets of unparalleled depth and coverage. The results are remarkable accuracy!