The Real Finds Podcast, Episode 93: This MIT Startup Is Rewriting the Rules of Commercial Real Estate With Honghao Deng

A conversation between Gordon Lamphere, J.D. of Van Vlissingen and Co. and Honghao Deng, co-founder and CEO of Butler, a spatial intelligence platform spun out of MIT’s City Science group. Transcript edited for clarity.

Honghao Deng: People sometimes think the biggest energy consumption is industrial, like manufacturing, or transportation, but it’s actually buildings. Buildings are forty percent. So a small efficiency ends up becoming gigantic once you have that scalability.

Gordon Lamphere: I’m Gordon Lamphere, and welcome to the Real Finds Podcast, where we have real conversations with key entrepreneurs, activists, and researchers shaping the real estate industry and, as a result, our world. On today’s podcast we’ll be speaking with Honghao Deng, co-founder and CEO of Butler, a spatial intelligence platform spun out of MIT’s City Science group. Honghao brings a rare combination of architectural training and computer science to one of the most undervalued and under-leveraged problems in commercial real estate: the fact that buildings, the largest product on the planet and the single biggest energy consumer in human society, are almost entirely blind to the people inside them. We go deep on how occupancy sensing and spatial data are replacing badge swipes and gut instinct, and why energy waste in the office building world is far more fixable than most operators realize. We also take a dive into the concept of autonomous buildings, which could totally reshape the way we think about real estate as an asset class. If you own, manage, or invest in commercial real estate and you’ve ever wondered what your buildings would tell you if they could talk, today’s episode is well worth a listen. Honghao, thank you very much for hopping on today.

Honghao Deng: Thanks for inviting me, Gordon.

Gordon Lamphere: What got you into the world of work and how we use the physical workspace?

Honghao Deng: It’s a long story of how we started Butler, but I’ll try to be short about our founding story. As background, I’m an architect by training. I did my undergrad in architecture, but I did computer science for my master’s degree, so you can see why I do sensors in buildings. A lot of our founding team members have the same interest area. We all think the largest interface around us is not a screen we’re chatting through, but this interface, the built environment, which shockingly, or unsurprisingly, has a lot of daily active users. Workplace, office time, it’s a large portion of our daily life; we’re in this interface, our office environment. So we really want to create a great product and experience for people, seeing this as the most important interface people actively interact with. And if AI is going to have a body to interact with our daily life or our productivity, it will happen in this largest interface. So that’s a nerdy but granular reason why we’re doing this.

Gordon Lamphere: That’s all right. Many of our listeners are also workspace and real estate nerds. One of the biggest things we hear is that there’s a huge difference between what offices or workspaces are often described as and how they function through our perception as humans versus what’s actually occurring. Where are you seeing that gap between the human experience in the physical workspace and what the data tells you?

Honghao Deng: It starts from something about experience, better inclusivity, efficiency improvement, and all of a sudden it becomes mission-critical, honestly, to how an organization innovates. In the AI era, what are the unique parts of human intelligence that are different than AI? How do we have human creativity plus AI productivity? It’s gotten to that level now, and we feel very lucky to sit at that cross-junction. The old-school stuff you’re probably familiar with, workplace efficiency, workplace experience, things happening in physical space, comes from saving time, saving maintenance costs, all the way to saving energy based on utilization. The reason our founding team came from MIT’s City Science group is that all of us are at this cross-junction of buildings and technology. Buildings are the largest product on the planet.

I’ll let you guess: what’s the top energy consumption for all of human society’s activities? What’s the biggest?

Gordon Lamphere: I would have no idea.

Honghao Deng: People sometimes think it’s industrial, like manufacturing, or transportation, but it’s actually buildings. Buildings are forty percent. So a small efficiency ends up becoming gigantic once you have that scalability. On our platform, which we call a physical intelligence, spatial intelligence platform, some of the use cases are things like using activity to drive energy usage automation. For example, air conditioning: there’s no point cooling a space if nobody is using it, but that’s the norm. How many times do you see a huge floor with just somebody in the corner and the AC or heating is on? Or in the early morning the heating is up, it gets so warm, everyone goes out for lunch, and then suddenly cooling comes on. It’s unfortunate how analog building control systems are today. They’re not based on people’s needs. You see people bringing Dyson fans in winter for their own little microclimate. Butler came out of making the system have a basic understanding, which never even existed before, of whether people are using it and the environmental comfort, temperature, because we’re a thermal sensor, so we know exactly what’s happening in the microclimate and whether people are using it. This baseline input is missed in the largest product on the planet.

In the past two thousand years we’ve gone from riding horses, which you have to maneuver, very analog, to autonomous vehicles that take you wherever you want, responsive to your need. Buildings today, without further innovation, will stay as a few pillars and a slab, not responsive to your need. So on the baseline layer, knowing where people are and utilization to drive those automations and actuations is a must-have. The way we see it, what we provide is a sense of touch, a neuron in the space, versus privacy-intrusive cameras everywhere; nobody wants that future. You need eyes somewhere, but not everywhere, not in your bathroom, not in your private office. The baseline is efficiency, automation, having that sense of touch to achieve a muscle response, which is energy saving. If nobody is using the toilet, don’t send the cleaner and spend that money. We did a case study with one of the largest facility managers: it’s about fourteen hundred dollars per year you can improve in labor efficiency on a single bathroom by knowing when people use it, just by putting one of our sensors at the door. And then how does it scale? A top university campus with ten thousand students has more than five hundred bathrooms. You feel like fourteen hundred is small, but you apply it across a larger product and at scale it becomes very meaningful.

Gordon Lamphere: One of the biggest things we constantly hear from investors and occupiers is folks talking about information like badge-swipe data, which is close to analog. How does more advanced technology like dwell time or spatial use help over just badge-swipe data?

Honghao Deng: There are two layers. Badge data will get you into the zones but not into the important activities or detailed applications that matter to your daily work, like group meetings or talking to a different department. It doesn’t get to the granularity of a specific room; sometimes you just get to the floor. And you don’t have the dwell time, because we don’t badge out. So everyone came in, and on the building level you feel like the building is utilized and you should crank up the AC, but the fact might just be that there’s free food today, and people leave at two p.m. So you don’t have enough data to complete all the daily applications important for this space as a product. In any UI, the reason there’s a UX study is so you know where a user goes, where they touch, and whether they complete the important task, so you can provide automations. A lot of things you couldn’t do with just badge: you can’t use it to drive HVAC, because you don’t know when to turn it off; you couldn’t do the bathroom cleaning application, because very few people badge into a bathroom; and you couldn’t do room automations in a hotel.

A lot of what we described is the efficiency thing and the experience thing we’ve known for a decade. How does it get to the C-level? It runs up to the CFO now because of energy. Energy is very important for the organization, not just office but also data centers, mission-critical. And how does it get to the CEO’s attention? When you get to how teams collaborate in physical space, there’s a culture piece.

Gordon Lamphere: So how do teams collaborate differently in physical space versus what we often hear? One of the biggest things we hear is that conference rooms are always said to be used way more than they actually are. What are you seeing through your technology versus what people are claiming?

Honghao Deng: I can share a lot of anecdotes. We have customers in the AI world who, as you can imagine, run out of space, adding hundreds of people a month, and they have a cost-center problem: nobody gets into a meeting room because they’re all making phone calls at their desk, and there’s just not enough. When you go into the meeting room, collaboration is very different now. A lot of engineering work has become democratized, so it makes much more sense for organizations to have remote teams, and meetings got smaller, two or three people plus a lot of people remote. So large conference rooms a lot of the time are twenty, thirty percent occupied. We have a lot of industry data on that, and we’re starting to have an insight layer to help you benchmark, is that just me or is that the norm, and give you suggestions. A year ago, TV Tokyo did an interview on us, and we showed how we use AI to directly generate, based on our data, a rendered suggestion of layout. It turned a lot of open-air workplace into small huddle space and turned bigger medium rooms smaller, just from reading our data, and the funniest thing is the interior color also matched. This year we have about 1.5 billion frames of data every day, so we get more analytical, giving out a benchmark through our intelligence module.

Gordon Lamphere: We’ve seen such a rapid change in office usage that a lot of landlords are more afraid their office product might be underused in the future. I’ve worked with people looking at badge-swipe data and license plate readers to understand comings and goings and try to predict future rent rolls to make better economic decisions. Are you working with investors as well, to produce a future potential rent roll based on business traction?

Honghao Deng: The beauty of unique physical data plus the power of AI modeling is being able to predict the future for a physical space, beyond screen space. I’ll make a bold prediction: a lot of the areas where we have data are actually coming back. This layer of human interaction and collaboration is irreplaceable, and for more advanced, innovative organizations, the trend is clear that it’s getting more important to get people together. That’s why it gets to the CEO level, not just the CFO level. Going back to dollars saved and dollars earned on the owner side, the last thing people want is a sudden turn. It’s better for the sales cycle too; if it’s predictable on both turn rate, tenant retention, and net new customers, it’s a much more predictable business. Everyone wants the physical business to get closer to a SaaS business. We’re a great data set to help with that, because we all know for some tenants the utilization isn’t there. The owner can know way ahead. I’m providing more value by telling them, maybe you should think about downsizing these other suites, and we know there’s a lot more usage of the cafeteria or kitchen space, so get a stunning kitchen, less size, less rent. So you can plan ahead, know months in advance that this space will open up, and make your business more predictable.

That gap between how much office space owners think is being used and how much actually is sits at the heart of the demand-side story we unpacked in Five Generations, Five Submarkets: How to Pick Chicago Office Space in 2026.

Gordon Lamphere: One thing we’ve talked about a lot is the idea of trying to achieve return to office, much of it done through a two- or three-day return structure. Many of the strategies I’ve seen employed in the market, particularly from folks who aren’t our clients, have been underwhelming. Can you explain what you’re seeing with return-to-work data, particularly how it’s playing out in the two- and three-day hybrid structure?

Honghao Deng: I’ll give a nerdy analogy. It depends on what software you want to run on your organization. You have the hardware, which is the space and maybe the people, and the software, which is really your programming of how you collaborate, your policy, all those things. There are ways that are very visible, data-anchored days, come back three days a week; that’s one software you can run on your organization. There are also ways to be much more context-aware and self-evolving, a software supportive of your organization, understanding the areas that foster innovation and how different departments collaborate, and then supporting that and letting it happen. Today Butler doesn’t force people to come back, but we have very high occupancy at the office, because we know what kind of activity actually brings collaboration back. You can always say you have to be back three days a week, and that programming can ignite more physical collaboration, but the grand trend right now is inevitable: it’s coming back, because people realize the uniqueness of creativity coming from a group of people. It’s very old-school and enduring. There’s a saying in Silicon Valley that innovation comes from a coffee shop, people get together and a spark happens. You can’t recreate that randomness of ideas, and even mistakes people make and learning from them, and conveying ideas in physical space, all those nuances, completely in a screen space. Those things are the engines for creating new things for our society, and organizations will slowly find out those elements are irreplaceable. If you want to stay focused, lock yourself in a room and do things with AI, you can do that at home. So there’s creativity work that can’t be replaced by AI or productivity tools, and there will be a comeback of physical space collaboration. A lot of the office built before was about individual productivity work; that will change.

Honghao’s read on return-to-office as a comeback driven by collaboration, not mandates, lines up with the flight-to-quality and repositioning dynamics we tracked in our State of the Chicagoland Commercial Real Estate Market for Q2 2026.

Gordon Lamphere: When we’re talking about collaborating in physical space, data helps, but one of the big issues people talk about in the HR field is data’s great, but at what cost, and the big cost comes with the privacy line. How do you accomplish gathering all that data while protecting individuals’ privacy and not having a huge lawsuit on your hands because you put a bunch of cameras in the bathroom?

Honghao Deng: That’s the beauty of having folks with a background in the building space who cherish the quality of the product and understand the ideal experience for a human being. When we spun out of MIT, we were thinking that even someone at home in a bathroom should feel comfortable, not like their grandkids or somebody is surveilling them. We all want to live and work with dignity. So foundationally, on the physical level, our sensor does not have any footage at all. It’s just thermal blobs, humble temperature data. That kind of modality has existed in building systems for decades. The uniqueness of Butler’s technology is taking something very low-resolution, humble infrared temperature data, the kind of thing behind the motion sensor where you have to make a dance to turn the lights on, and putting our model on it to interpret location, number of people, usage, dwell time, posture, even fall prevention in healthcare or at home. On the physical level it’s privacy-friendly first. Second, that kind of IR data has existed for decades; it’s already in your bathroom, in the corner, that PIR motion sensor. We just abstract more out of very similar IR data by upgrading the sensitivity and spatial resolution, so people feel a lot more comfortable. And very soon, with our generation three, there’s nothing you could relate to privacy intrusion; the sensor can be covered with a white opaque cover, because we don’t see any visible light at all, we’re just sensing temperature.

Gordon Lamphere: One of the things we’ve gotten to in the office world is trying to be more intentional in predicting future trends, because they’re coming so fast we don’t have time to wait around and react. So let’s roll into the Final Four. Ten years from now, what do you think is going to change the most about commercial real estate and real estate in general?

Honghao Deng: On the broader real estate side, it’s this idea I keep pushing, which I’d call autonomous buildings. If you have that data layer, the data collection and self-evolving capability, just like organization software, five years ago you couldn’t have your Tesla take you from the parking lot all the way home, only pilot assist, reducing speed on the highway, keeping distance. Look where it is today; it’s become a norm. Similarly, buildings today, you need to make a dance to turn lights on, and there’s this fear-based control loop in a data center that’s just a minimum and maximum temperature. Those things will soon be a lot more responsive and adapt to individual needs, self-regulated, with better comfort, biophilia, efficiency, learning from the data, as long as there’s a scalable data layer, which is what Butler is creating. So the way I look at building as a product in the future is that it’s going to be more responsive, understanding users’ needs, and creating a better experience, similar to how we went from riding horses to autonomous vehicles.

Then, on sectors: office is about people together, ideas, inclusivity. It’s going to be a lot more about that instead of being like a machine. It’s the complete opposite of something extremely efficient like AI. So office will continue to evolve into matching what humans are more unique at than AI. On the real estate side, the fastest-growing verticals in commercial property are senior living and senior housing and data centers, and Butler has a lot of mission-critical use cases in both, matching what’s most important, understanding users’ needs. In data centers, the users are kind of the server racks; understand what’s needed, be responsive, and improve efficiency.

Gordon Lamphere: What is one topic the real estate industry should be talking more about?

Honghao Deng: We cannot always be thinking this is just a box. While we were working on a data center product for Butler, this repeated fear came up: a data center is an asset that depreciates so fast, because it’s just pillars and a roof, and inside there’s a bunch of GPUs depreciating. What’s the value of that, and how do we keep the value? That’s an extreme version, and it’s a good example to tell people we should think the other way: it shouldn’t be just a space or a roof to put important things under; it should be a product that evolves and provides value that fits the new reality. That means the space as a product should understand the best approach to optimize and be retrofitted into new uses. If it’s self-aware, understanding its thermal limits, it can tell you, if you do this layout, I can’t fit this many racks, but if you do the other layout based on my understanding of thermal performance, you can retrofit your rack, maybe not with H100s but a bunch of L40 GPUs, and now you create value. Your building itself is an advanced product. When I heard that data-center fear, I felt building as a product is not just a roof and a space.

That framing, buildings as depreciating boxes versus adaptable products, is exactly the valuation tension we worked through in Valuing Chicago Data Centers and Adjacent Properties.

Gordon Lamphere: If a building were just a roof and a space, our job in real estate would be a lot easier, but a lot of folks would need us a lot less. We have a lot of younger listeners, and one question they always love: what’s one thing, if you could travel back in time, you would tell your younger self?

Honghao Deng: Do what you love, trust your intuition, and don’t give up. Another thing is that you have to think about whether it’s not just for you, but the right thing for the world. Doing a startup is not easy, and every day I wake up thinking about every single sensor we put on the ceiling making the world a little bit better, saving energy for the planet and helping one elderly grandma or grandpa, or ourselves, be less likely to fall in a room and be safer. So work on something you love, knowing it’s for the world’s benefit.

Gordon Lamphere: One final thing: if somebody wants to get in touch with you or your company, what’s the best way?

Honghao Deng: Either through the online submission form, “talk to us,” right on the top right, or my email, deng at butlr.io. Butler is spelled B-U-T-L-R.

Gordon Lamphere: Thank you so much for hopping on today. We really enjoyed it, and we have to have you on in the future.

Honghao Deng: Yes, let’s build the future. Thank you, Gordon.

Gordon Lamphere: Thanks again to Honghao. We appreciate his insights. If you enjoyed the podcast, please give us a like, a five-star rating, and a review. Your comments, subscriptions, and interactions truly matter and help us continue to get quality guests. You can find us on YouTube, Spotify, or wherever you hear podcasts. I’m Gordon Lamphere, the Real Finds Podcast. Thank you for listening.

Van Vlissingen and Co. has been the Midwest’s oldest commercial real estate brokerage, development, and management firm since 1879, and today is independently ranked the #1 commercial real estate agency in Chicagoland, home to the #1 independently ranked agent, Gordon Lamphere, and the region’s #1 ranked commercial property management team. If you own, manage, or invest in office, data center, or senior housing property across Lake County, the North Shore, the Northwest and O’Hare corridors, DuPage and the I-88 corridor, Will County, or southern Wisconsin’s Pleasant Prairie, Kenosha, and Racine markets, contact Van Vlissingen and Co. at 📞 847-634-2300 or 🌐 vvco.com. For a market-wide view of where these dynamics sit today, see our State of the Chicagoland Commercial Real Estate Market for Q2 2026.