Fresh off an $18 million funding round, the Israeli-based startup discusses further refining the precision of its predictions for property values over time
Skyline AI, an Israeli real estate tech startup using artificial intelligence to predict property values, has been moving fast over the last few months. One year after its launch and four months after raising $3 million in seed funding, the company closed off an early-stage $18 million founding round led by Sequoia Capital and TLV Partners with participation from JLL Spark, a division of JLL.
Skyline AI co-founders Guy Zipori, Or Hiltch, Iri Amirav and Amir Leitersdorf have been firm believers in artificial intelligence (AI)’s power to revolutionize many of today’s most common real estate transactions. Their platform, which mines data from over 130 different records and uses AI and machine learning technology to evaluate different situations in the real estate market, and make predictions about how the value of different properties will change in time.
In the industry, the uses for AI are still fairly novel.. We spoke two of Skyline AI’s co-founders, Hiltch and Zipori, about how they see real estate professionals using the technology as part of their jobs in the decades to come.
Do you think the range of your investors shows that there is an increasing interest in real estate technology across the industry?
Zipori: When we started with the seed funding from Sequoia, one of the challenges we thought we would have was getting real estate people to join us on this journey.
We wanted to convince them that AI and big data can really transform the real estate industry as we know it today. We were surprised by how fast they understood the impact that this kind of technology could have on this industry. Most live in big cities and are big real estate players.
What are some ways the real estate industry could benefit from AI specifically and automation more broadly?
Hiltch: We see what we do as being less about automation and more about precision. While there’s no doubt that there are local experts who know their market inside and out, the amount of data that the human brain can process is no match for AI just because humans have a limited point of view.
This is why humans actually can’t predict how an asset will perform with high levels of certainty while AI can. Humans are not able to receive information from hundreds of different data sources going back decades like AI can.
Our point of view is very limited which is why we believe we can reach much more accurate results [with AI]. For us, the use of AI is not about automating stuff and replacing people. It’s about augmenting and providing the environment to be able to underwrite a lot more quickly and a lot more precisely.
What is in store for Skyline AI?
Zipori: Sofirst of all, the funding will go toward increasing the team — both the real estate and the engineering team and the data science team in Tel Aviv, as well as the sales team in the US. We opened the US office in September. We’re bringing in real estate people and sales people.
In real estate and in engineering, we plan to acquire much more data. Some of the data that we’re using is public but some is data that we pay for. We have a lot of data that will come in and will improve our predictions and our ability to analyze real estate opportunities.
Hiltch: And also, we signed with the multi-family asset class but now, after the funding, we will try to expand to other asset classes as well. For example, industrial and retail and so on.
Will Skyline AI’s artificial intelligence product also expand?
Zipori: Yeah. Basically, we have a lot of projects that are going to be progressing. With the new funding, we can step it up a notch and make AI models around predicting things like learning who the asset is going to be marketed to ideally before the owner realizes that they’re going to sell.
We have a lot of plans for AI being used to make predictions, so being able to detect anomalies in the market automatically. We also have quite a few projects based around estimating value automatically, so not just estimating how much the land is going to be worth but also learning how to optimize the property for sale later.
How do you see AI being used in real estate in the future?
Hiltch: Ultimately, data is going to be more available. This will allow AI access into providing better insights. Today, there are also still a few places where a human insight is irreplaceable — for example, when you step into a property and find that it doesn’t smell good or something like that.
We expect that, in the future, a lot of these things are going to be available through AI as well. We also expect to see AI reaching other industries, such as construction, engineering and that type of thing.
Real estate saw an explosion of new technologies over the last two years. Why do you think this industry could really benefit from incorporating technologies such as AI?
Zipori: I think that, in the last few years, we saw some areas of real estate enjoy major success experimenting with new technologies. We think that real estate investors and players are starting to understand the value that real estate technology can bring to the table and just how much of a difference it can make in real estate.
I think this is one of the reasons we are starting to see more money flowing into real estate technology in general. In the last 10 years, the main thing that you needed to do to get yield from real estate was to buy real estate.
Now, most real estate investors will say that the next ten years are going to be different. In this specific industry, you need to have a competitive advantage. Real estate technology offers just such an advantage.