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Real Estate Pros · June 16, 2026 · 22 min listen

How AI Is Changing Real Estate Pricing, Comps, and Deal Analysis for Agents and Investors

Show summary

Steve Fishman, founder of Sigal Group Developments and creator of Apex Nexus and Deep Destroyer, discusses how AI is transforming real estate while emphasizing that human expertise remains essential. He explains that most AI tools provide generalized answers, whereas successful real estate analysis requires highly calibrated, asset-specific insights. Steve shares how his technology helps identify pricing errors, hidden risks, and investment opportunities while also discussing a new app designed to help homeowners evaluate equity-related decisions

Key takeaways

  • If a listing has no views or showings, the problem is almost always the price; compare your listing against the closest sold comps.
  • Don't price high hoping to adjust later. In a downward-trending market, every price cut chases the market further down, so price aggressively and honestly from the start.
  • Be straight with sellers about pricing even if it means turning down an overpriced listing; taking an overpriced listing and losing it to another agent at a lower price later damages credibility.
  • General AI tools like ChatGPT and Claude give roughly 70% accurate, generalized answers because they aren't calibrated to a specific asset or asset class; specialized tools are needed for precision.
  • Fishman's tools catch discrepancies general portals miss, such as a seller listing 4,000 square feet when county records show 3,000, due to an unrecorded finished basement with a gym, office, and media room.
  • Commercial real estate needs asset-class-specific analysis (e.g., retail plazas need proximity to an intersection or high school, offices have different criteria), and generalized AI isn't calibrated for these distinctions.
  • Treat AI-generated real estate or financial analysis as a starting point ('CliffNotes' version), then verify it with a qualified agent, broker, or financial advisor before making a decision.

In this episode

  1. 02:00Introducing Steve Fishman and his real estate tech platforms
  2. 02:31Why listings get mispriced despite abundant data and AI tools
  3. 03:07Why listings sit: it's almost always the price
  4. 03:49The problem with 'let's try a high price and reduce later'
  5. 04:47How his tools catch pricing errors Zillow and Redfin miss
  6. 06:22What makes a reliable comp, street by street and house by house
  7. 08:03Where AI is headed in real estate over the next couple years
  8. 11:04The AI 'echo chamber' problem and why his tools avoid it
  9. 14:21Risks of AI agents giving wrong answers and potential litigation
  10. 17:34Applying calibrated AI tools to commercial real estate deals
  11. 19:20New app for homeowners deciding what to do with home equity

About the guest

Steve Fishman is the founder of Sigal Group Developments and the creator of real estate technology platforms Apex Nexus and Deep Destroyer, built to help agents, investors, and brokers price listings and analyze deals more objectively. He says he has been in the real estate business a long time, has had both successes and failures, and is now building tools calibrated to specific asset classes to help people avoid the mistakes he made. He is also developing a new app to help homeowners, particularly older owners with significant equity, evaluate decisions like selling, renting, or taking a home equity loan.

Listen to the audio

“You need to price it aggressively from the beginning if you want these listings to move.”

Steve Fishman

“The AI doesn't have skin in the game. And that's a big difference. Because when you're making a mistake, you pay for it.”

Steve Fishman

“So like a Claude will give you seventy percent. That extra thirty is quite significant when you're dealing with... a ten million dollar deal, you know, I could save you a half-million dollars just because I saw a couple of landmines that Claude wasn't picking up.”

Steve Fishman
AI in real estatepricing strategycomps analysislisting agentscommercial real estatePropTechMLS data transparencyhome equity decisions

Questions answered in this episode

Why do real estate listings sit on the market without showings?

Steve Fishman says if a listing has no views or showings, it's almost always the price. He recommends pulling the closest comps, especially sold ones, and comparing your price against them to see if you're priced too high.

Should I list my home high and lower the price later if it doesn't sell?

No. Fishman says you only get one chance to make a first impression, and pricing too high means you end up chasing the market down, especially in a downward-trending market. He advises pricing aggressively and honestly from the start rather than planning for price reductions later.

How do Steve Fishman's AI tools differ from Zillow, Redfin, ChatGPT or Claude for real estate analysis?

He says general AI tools like Claude or ChatGPT give generalized, safeguarded, 'corporate' answers that are roughly 70% accurate, not precise or calibrated to a specific asset. His tools are calibrated per asset class and catch details sites like Zillow and Redfin miss, such as a listed 4,000 sq ft home where the county records show 3,000 sq ft because of a finished basement with a gym, office, and media room.

Will AI replace real estate agents and brokers?

Fishman doesn't think so. He argues AI has no 'skin in the game' and some models act like cheerleaders, telling you a deal is great when it isn't, unless specifically engineered to flag risks. He believes the human element and expert judgment remain necessary, especially for large transactions.

Is increased data transparency (MLS access, Zillow, Redfin) good for buyers and sellers?

Yes, Fishman says it's a good thing overall. He suggests buyers and sellers pull their own data as a 'CliffNotes' or 'SparkNotes' version, then take it to a qualified agent or broker to verify before making decisions, similar to using AI for financial advice but confirming with a professional like Fidelity or Charles Schwab.

How do AI tools apply differently to commercial real estate versus residential?

Fishman says every asset class needs specifically engineered tools since factors differ, for example a retail plaza needs proximity to an intersection or a high school, while an office building has different criteria. He says generalized AI models like Grok or Claude aren't calibrated for these specifics and only give about 70% of the needed answer, which can be costly on a large deal, like missing landmines on a $10 million commercial building that could save a half-million dollars.

Resources and links

Full transcript

Steve Fishman (00:00)

I think that’s a mistake. I think that you have one time to make a first impression. And when you get out there and you’re too high, you’re always chasing the market. And especially in a downward spiraling market or a downward trend market, you’re going to be pricing it at one point and then chasing the market down. Cause every time you lower the price, the market goes down on a downward spiral market. You need to price it aggressively from the beginning if you want these listings to move.

Dylan Silver (02:00)

Hey folks, welcome back to the show. Today we’re joined by Steve Fishman, owner of Sigal Group Developments and creator of Deep Destroyer, Apex Nexus, real estate technology platforms focused on helping agents, investors, and brokers make faster, more objective, data-driven decisions. His work centers on solving one of the industry’s most common problems—stuck listings caused by pricing disconnects and poor market analysis. Steve, thank you for joining us here today.

Steve Fishman (02:30)

Thank you so much for having me.

Dylan Silver (02:31)

Now, why are people still mispricing their listings when there’s so much data and also AI tools available to them?

Steve Fishman (02:40)

I think the biggest mistake agents make is letting the seller dictate the price. You have to stay in control and you have to be real with them, and then you’ll sell your properties.

Dylan Silver (02:50)

It’s oftentimes a price conflict, right? Because people are thinking about, well, what did homes sell for the last time that we were looking? And so there’s this element of coming to reality—what’s the current situation that people sometimes have a difficult time grasping?

Steve Fishman (03:07)

Well, I think listings usually sit because the price is too high. If you have no views or showings, it’s almost always the price. So I think the best thing to do is to get the best comps closest to you and if they haven’t sold—the ones that have sold—and look at your price compared to those. If your price is higher, it’s the price.

Dylan Silver (03:28)

Now, when people are having these conversations, oftentimes one of the tricky things that comes up is they still want to push back and say, “You know, I want to try to list at this higher price, and then we can, you know, pull it down later on or pull it back later on, drop the price, have some price reductions if it doesn’t sell at that price.” What’s your feedback on that?

Steve Fishman (03:49)

I think that’s a mistake. I think that you have one time to make a first impression. And when you get out there and you’re too high, you’re always chasing the market. And especially in a downward spiraling market or a downward trend market, you’re going to be pricing it at one point and then chasing the market down. Cause every time you lower the price, the market goes down on a downward spiral market. You need to price it aggressively from the beginning if you want these listings to move. And if you have a seller who says, “Oh, let’s just try it out,” well, you know, then you’re gonna be in the position where you say it’s not selling because I need to put in plants, or it’s not selling because you need to paint the kitchen, or it’s not selling because whatever it may be. I think that you need to be honest with the sellers and let them know that it needs to be priced right.

Dylan Silver (04:38)

Now, when we talk about the tools that you’re using to help folks, how on a granular level are you able to eliminate some of this pricing confusion?

Steve Fishman (04:47)

Well, my tools catch things that Zillow and Redfin miss. For example, you know, a seller lists a property at four thousand square feet and the county shows three thousand, but what it doesn’t show is it’s a finished basement with a gym, office, media room—and my tool picks that up. So you have better data and more precise data.

Dylan Silver (05:56)

Now, when we’re specifically looking at neighborhoods and even the difference between the same street but, you know, three blocks down, one of the things that is often tricky for folks is assuming that because they’re on the same street or because they’re in the same general area that that’s a reasonable comp—and that’s an often common mistake that we see being made. How do you approach, you know, what is a reliable comp?

Steve Fishman (06:22)

I think that a reliable comp is something that’s specifically adjacent to these properties. And you know, they might be both on a lake and you have to make adjustments for each thing like an appraiser would do. But you know, especially here—you’re in Texas and I’m in Florida—it can be street by street that they change rapidly, and house by house. You really have to dig down deep and see what the listing is saying to make sure that they’re compatible. And that’s why I was saying that my tool kind of does that, you know, to make sure that the listing—what they’re saying in the listing—and what you want to be congruent to what you’re saying in the listing and what it actually is, and compare those with those other comps that you’re pulling out.

Dylan Silver (07:06)

Now, for folks that are struggling with, you know, high days on market, this then becomes a bigger issue as days on market increase because there’s this element of, “Well, it’s been listed for so long. What’s wrong that I don’t know about this home? Where’s the distress?” What can folks do in that situation? Do they have to pull it off the market?

Steve Fishman (07:25)

I think that sometimes, well, what happens is—and unfortunately—is that you go in there and the seller says, “I want X amount of money,” and you know it’s overpriced and you know they were like, “Well, I just want to try it on the market.” The problem is that you’re out there for six months and then they pull the listing from you and they put it on with someone else at a lower price and they sell it, and you look like a jerk. That’s why I’m saying to you, be honest with your sellers. And sometimes I know it’s tough as a young agent to say, “I’m gonna turn down this listing,” but sometimes it’s better to turn down a listing than to overprice it because you lose some credibility when you do that.

Dylan Silver (08:03)

Pivoting here, Steve, where do you see AI’s role in real estate over the next couple of years? There’s a lot of talk in how this will interface with where agents are currently helping folks.

Steve Fishman (08:15)

I think that—so I’ve been calibrating my tools. I think the problem with AI right now is that it’s too general. And if you put in a property into Claude or you put it into ChatGPT, they’re gonna give you the safeguarded corporate answer of, “You know, this house…” and it’s not precise. It’s not calibrated, it’s not tight, micro-targeted. And I think that that’s where the industry’s gonna be going—to tools that do that. And they’ll never be able to do that.

Dylan Silver (08:47)

Now, one of the areas I would say of contention is you have some people who see, well, we have to fully embrace this and maybe even there’s gonna be a time in the future where an agent’s role is not necessary. But then you have folks that are saying, “Well, you’re always gonna wanna have someone involved because there’s so much paperwork and processes that you want to delegate that, especially if you’ve got a lot of things going on in your life outside of just buying or selling a home.” Where do you stand on that?

Steve Fishman (09:16)

I think that there’s certain tasks that AI is very good for, but there’s also tasks that you need a person there. So, you know, even the best tools are going to give you wrong answers. And there’s a human element of it—the AI doesn’t have skin in the game. And that’s a big difference. Because when you’re making a mistake, you pay for it. They don’t have any skin in the game and they’re just—a lot of times, and specifically there’s some that are better than others, some models that are better than others, but some of them are just cheerleaders and they’re saying, “This is great, this is great, this is great,” you know, and it’s not great. And they’re not, unless you’ve engineered it to tell you that it’s not great or to look at the different landmines and things like that, then it’s not great.

Dylan Silver (10:38)

Yeah, I mean you’re spot on. There there’s a lot of people that I know—I’m sure you know them as well—that have this echo chamber of AI where it’s confirming whatever it is that they went in, even if it was asked as a question, such as, “You know, what can I sell my home for?” But if you’ve been cueing it up with a bunch of responses that make it think that I want to hear a high value, then that is what it may present you with.

Steve Fishman (11:04)

Absolutely. And I think that that is, you know, that is the key thing of the tools that I’ve developed because I’ve gotten burned quite a bit. You know, I’ve been in the business for a long time. So I have my successes and I have my, you know, my failures. And the beautiful thing is that my failures are actually a strength at this point in my career because I’m building tools so that people don’t get burned—so that people are playing by a book, like they’re going to Vegas. You know, they get a hard fifteen and the dealer’s showing seven, they’re gonna hit ’cause that’s what I’m telling them to do, you know? And they have an advantage, you know, they’re not just playing out there in the wind.

Dylan Silver (11:39)

Absolutely. When we talk about the current status of data and access to information, folks have so many options right now and more so every day. Of course you’ve got, you know, Zillow, Redfin, you’ve got changes in the MLS in Texas. I’ve been told that they’re even potentially making the MLS available to unlicensed people, so if they want to have access to it. But even with all of this, there is a level of being able to sort through this data and make decisions based on that. Do you think that this increased transparency is ultimately a good thing for buyers and sellers?

Steve Fishman (12:22)

I do. I think I do—I think it’s very good. And I think that, you know, them pulling their own comps and looking—I look at it this way. You know, I think that they should be able to get an answer and then take it to a qualified agent or broker and say, “Hey, this is what I have.” You know, they need kind of a CliffNotes version or a SparkNotes version, as my kids would say. SparkNotes version of, you know, what is out there so that the buyers actually know. But they have a trusted—like you wouldn’t just go to AI and ask for financial advice. Maybe you would, but you really need to take that financial advice and go to, you know, a Fidelity or Charles Schwab and get someone who’s an expert in this stuff and say, “Hey, is this real? Is this really what I should be doing?” I feel it’s like the same way with the AI and the tools that are being developed to take it and look at it, and then take it to a qualified broker and say, “Hey, is this—is this really the price? Is this really what I should be doing? Should I be adding on a kitchen?” or whatever the case may be. You know, take it to a qualified agent or broker so they’re not going to be cut out. A lot of the grunt work will be cut out, but you don’t want to do that anyways.

Dylan Silver (13:37)

Yeah, I mean that’s spot on. When we talk about where this interface is best, it is in that decision fatigue, right? I don’t necessarily want to have to go through all of the arithmetic to get me to a point where I have some base foundation. But from there I’m gonna go get with the expert. I do wanna pivot here and talk about where agents and buyers and sellers as well as AI may be leading people astray right now. And one of the big things that I hear is, you know, people are delegating the communication to AI tools and that it’s getting maybe even more challenging to get a hold of a real person, so to speak. What’s your feedback on that?

Steve Fishman (14:21)

That is one of my pet peeves. I mean, it’s, you know, crazy when the AI agent comes on there. Some of the stuff that I’ve been looking at is actually breaking that. So like let’s say you buy a pair—you know, you have an AI agent and it’s a sales product. You have an AI agent and you ask them, “You know, I bought a pair of sneakers and it came in a box, the box was defective and I threw out the box, but I don’t want the shoes. And what do I do?” And the agent tells you, “You know, just return it.” But their website says you can’t return it, or website says you can return it. So there’s a—there’s a lot of stuff that they’re telling you because, like I said to you, they want to be agreeable. They want you to feel good. So I think there’s going to be some problems with the AI agents giving the wrong answers to compare, and then there’s going to be some litigation. There’s going to be some big litigation because people are relying on what the agent says and the website says something different.

Dylan Silver (15:57)

Yeah, and you know, we see this a lot with folks who are looking for speed to lead, right? They really want to get quick contact with their clients, or if it’s an investor—we talk with a lot of investors—quick contact with maybe a distressed seller. But this can lead people astray because they’re getting the wrong information or they’re being told something which is just not applicable to their situation.

Steve Fishman (16:19)

Absolutely. And I also think in terms of specifically AI agents—

Dylan Silver (16:24)

AI agents and then also this speed to lead scenario, which again there’s a place for it, but if you’re kicking the human can down the curb so far that people are not able to get in front of somebody, and you’re just relying on a speed to lead tool to answer a majority of like triage questions, then you may be missing out on that human touch of making someone feel valued, right?

Steve Fishman (16:51)

I agree with you a hundred percent. I mean, I think that the human, you know, the human element is huge. And that’s why, you know, some of the tools that I have, I’m actually involved in it. So I’m doing the eval on these real estate deals because like I said, you need a human element. And that’s where my expertise and my years of experience come in so that people know that they’re not just having, you know, going to AI asking. So like a Claude will give you seventy percent. That extra thirty is quite significant when you’re dealing with—you know, if you’re buying a commercial building and it’s a ten million dollar deal, you know, I could save you a half-million dollars just because I saw a couple of landmines that Claude wasn’t picking up or they said, “Yeah, don’t—don’t worry about that,” you know.

Dylan Silver (17:34)

Let’s dive in there. If we can get a little bit granular, talking about commercial, right? Of course, comps and the whole process is a little bit more drawn out, or a lot more drawn out, than it would be in the residential side. Are these tools maybe even more applicable than in these commercial scenarios where you’re having to diagnose and analyze maybe more complex data?

Steve Fishman (17:57)

I absolutely think so. I mean, that’s from my position—that every single asset class needs to have specific tools for those asset classes. So like if I look at a multifamily or I look at a retail, they’re different, they’re different. I mean, you can fork over what you’re looking over, but there’s certain stuff that you’re looking over. What I mean is if you go and you look at, I don’t know, an office building and then you look at a retail plaza, you know, you want that retail plaza to be located, you know, close to an intersection, or you want it close to a high school or close to wherever in proximity. Those types of things, like you know, if you’re looking—so these tools can be very good for looking. They can be very good for looking at your portfolio, seeing where you have leaks. So like you’re not only buying, but then you’re looking at it. So I think that that’s really where the value is—specifically engineered for the specific asset class. And I think that Grok can’t do that or Claude can’t do that because they’re not calibrated. So they’re giving you 70% of the answer. I don’t want to see, you know, when I’m buying a property, I want an A.

Dylan Silver (19:11)

That’s right, you know. We are coming up on time here, Steve. Any new projects that you’re working on? And then also anything you’d like to mention directly to our audience?

Steve Fishman (19:20)

I am working on a new project. I’m working on an app for older people—maybe, you know, someone who has some equity in their house and is trying to decide, you know, maybe they have a two point five percent interest rate and they’re saying, “You know, what do I do? I have all this equity in my house. Do I sell my house and take the equity out, you know, because I can protect five hundred thousand dollars because I’m married? Or do I, you know, rent it out? Or do I take a home equity loan? What do I do?” So this app takes you through that process of what you actually have, and it’s highly calibrated. So you just put in your address and a couple of other little things and it takes you all the way through. And it’s very powerful. And you know, it’ll be online probably in a few weeks, you know, in the App Store and in the Play Store.

Dylan Silver (20:12)

Steve, thank you so much for joining us today. Thanks for your time.

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