What We Do

Foyer provides our Listing Optimization Engine and listing improvement recommendations using image recognition and deep learning.  Utilizing our proprietary AI, Foyer incorporates an analysis of every listing in the country and combines the results with listing text and property data to uncover useful guidance for understanding and improving listing effectiveness.

What you get:

  • Listing Optimization Engine Validation: Provides validation of your listing data and images to ensure your listing data has been distributed with the correct and relevant information.
  • Listing Optimization Engine Recommendations: Suggestions to improve individual images, gallery orientation, and property description to reach and activate potential buyers.
  • Marketability Score: See how competitive your listing is localized to the cluster of similar homes in the area.
  • Additional Agent Tools: Gain access to Foyer’s full suite of agent tools to know when your clients are shopping and find their interests.

What is the Foyer A.I.?

Foyer’s proprietary innovative technology does more than just read listing descriptions. Our A.I. is able to view images as a person can and understand the scene that is being presented in each picture. Using our vision, our A.I. can break down, classify, organize, and analyze over 100 unique image components in each real estate gallery image.

The first step in analyzing a listing involves breaking down each photo. Foyer’s A.I. classifies what kind of picture it is looking at, be it a kitchen, living room, exterior view, etc, and then applies image segmentation to precisely identify and outline each important image components. Each component is then matched and compared with similar components in millions of other images to provide accurate tagging and assessment.

Once Foyer’s A.I. has identified every component in the image, it will try to understand and map the scene. By cross referencing the sizes of other objects in the image, the actual sizes of image components such as refrigerators, tables, chairs, beds, windows, and even floor area and counter top size can be determined. This allows our A.I. to understand the field of view and relative depth, and create a map of the room and its features. Components found in other gallery images are also simultaneously analyzed to look for multiple views of the same room as well as for overall layout of interconnecting rooms.

Each image is then analyzed for objective characteristics such as framing, brightness, focus, color temperature, and resolution to ensure it meets a minimum standard and provide information for validation, recommendations, and improvements that our Listing Optimization Engine provides to our agents.