919.504.9898 info@reso.org  

 

With Ashish Antal, Engineering Director of MLSListings

 

 

Ashish Antal, Director of Architecture at MLSListings and co-chair of the RESO Distributed Ledger Workgroup, is a leader in MLS innovations.

In this video interview, Antal talked about how MLSListings is leveraging machine learning by Intel combined with RESO standards to transform search and improve client experiences.

“One of the goals for [Intel] is to get some adoption, so from the MLSListings side, we wanted to provide the next search – we wanted to make it easy for consumers to find homes that they like,” said Antal.

According to Antal, MLSListings machine-learning efforts resulted in the ability to automatically find similarities between images of homes. “We want to recommend other homes which are similar to the house that they are interested in and provide them as a possible alternative to the property that they are looking for,” said Antal.

By connecting Intel with MLSListings APIs, they have created the ability to provide consumers with closer search matches. During the proof of concept, Antal noted, “We were surprised to see how close it could match the images that looked similar to what the user was looking at, so we integrated it, and it’s working better than we expected.”

The next step, said Antal, is to use the power of machine learning to identify home features within the image to auto-populate those features for the agent. In essence, the images could be used to automatically create content for the listing.

The ultimate goal of MLSListings, Antal explained, is to give consumers greater ability to find the right house by using images to find and match those features, even if the information is not featured in listing data.

Because MLSListings uses RESO standards, it made data pulls easier for Intel. In fact, it’s the same API that clients of MLSListings use and the same data being used by their own product.

Antal encourages all MLS technology firms to take advantage of RESO standards. “It shaves a lot of development time off, because you don’t have to worry about that data access anymore, because the API has already done that work for us,” he said.

“The end goal should be adoption,” said Antal. “Once you know that you have built a technology that you can integrate with an MLS with the least friction, which means more standards, then it will most likely get more adoption.”

 

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DLU October 25th, 2019