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PODCAST OPENER
Welcome to the Inside Insight podcast presented by CR Solutions. At Consolidated Risk Solutions, we are taking our expert knowledge of the insurance world and using it to innovate the industry using technology, groundbreaking thinking and a personal touch. Join us as we talk to masterminds both inside and outside of CR Solutions about how the world of insurance is changing, and how we can be sure to grow along with it. If you have to manage insurance in your work, then you can benefit from the interviews, conversations and insights we’ll be exploring to elevate your business’s success.
INTRO (00:42 – 03:48)
Trevor Casey: Beau, we’re back again with another one.
Beau Lunceford: We are here and we’ve got some great conversation waiting to just enter into people’s ears.
Trevor Casey: Absolutely. So the episode that we have today is one that I feel like I easily could have gone down a rabbit hole with him and we’re going to have to have another second, third, fourth, whatever amount of episodes or I’m just gonna have to take him out for drinks and just go down the rabbit hole. But like the stuff that they’re doing without telling it who it is. Yeah, I know I’m getting into it, but the stuff that they’re doing at this new coming company that you’re about to speak about, it’s just so exciting and stuff that I really engage in. So the conversation was really fun with me, but while I continue to tease this mystery guest. Beau?
Beau Lunceford: Ladies and gentlemen, introducing Ryan Howsam with BLDX. Ryan is the founder and CEO of BLDX, an AI platform that identifies and monitors risk on construction projects and buildings to mitigate claims. Ryan was a principal with FMI Corp. The global leader in management consulting and investment banking services for the built environment, where he spent 10 years guiding contractors and industry players while leading FMI’s risk management practice. While at FMI, he took a keen interest in how the power of information could be leveraged to create a more sustainable future for the industry. Ryan is a certified Risk and Insurance Specialist, or Chris, and the lead accredited professional in building design and construction. With more than 20 years of experience within the built environment, Ryan holds both a Master’s of Science in Real Estate and Construction Management and an International Master’s of Business Administration in Corporate Finance from the Daniels College of Business at the University of Denver. He also earned a Bachelor of Arts in International Studies from Vanderbilt University in Nashville, Tennessee. This conversation, this guy, this company. Wow.
Trevor Casey: One of the things that I think’s funny about that intro is you cut out a part of the Alphabet soup that Ryan has after his name and I’m sure it’ll be in the show notes, but I just always refer to that as Alphabet soup because there’s so many letters. But it just shows Ryan has so many different certifications and degrees and education, and so the stuff that he is speaking to, he’s not just like some techie bro out there, buy my tech. Like, he’s really, really intelligent and thought through and thought provoking and just this conversation is exciting and I’m. And I’m really excited for everybody to listen to it. And if I could say excited one more time.
Beau Lunceford: I think you’re pretty excited about it.
Trevor Casey: Yeah, cut that part out.
Beau Lunceford: I’m leaving it. I mean, just the list of things that we’ve heard here. And as this conversation unfolds, people are going to, I hope, really understand that it’s not just the tech side of things that it really is. There’s a risk management element that he clearly has so much knowledge and experience in that really is what makes this company something special, which is why he’s here on the podcast today.
Trevor Casey: Absolutely. Well, without further ado, and you don’t have to listen to us blab anymore. Let’s get into it.
Interview (03:53 – 27:08)
Trevor Casey: All right. Welcome back to another episode of the Inside Insight podcast. We are joined today by Ryan Howsam, the founder and CEO of BLDX. How are you doing today, Ryan?
Ryan Howsam: I’m doing great. How are you doing, Trevor?
Trevor Casey: I can’t complain if I had any complaints. Most people don’t want to listen to them anyways. We really appreciate you joining us and bringing some of your insight to the podcast, so just get started, Ryan, tell us a little bit about you. What’s your background in and how did you get to BLDX?
Ryan Howsam: I spent about 25 years in the construction industry. Started by working my way through graduate school, getting a master’s of science in construction management and real estate, and working in the trades in the Rocky Mountains, doing some flat work, roofing, and tilt up. That led eventually to me saying, all right, I’m in the best shape of my life out here working in the trades, but I think I want to be working at a little bit of a different level within the construction, built environment. And so after wrapping up my master’s studying real estate internationally, Middle East, around the US, I landed at a company called FMI Corporation, and we were investment bankers and management consultants specifically for the construction industry and launched our risk management practice at that time. Solely focused on the underwriting and general contractor’s use of insurance in construction. And at that time, that’s where I really started to discover the enormous cost of these claims, really based on lack of information and insights on all the construction data that was produced on these projects. And so after being a partner at FMI for 10 years, right around COVID left to start BLDX to solve that problem and saying how can we create an AI enabled platform to eliminate claims on projects?
Beau Lunceford: And that’s such a huge thing that we’re seeing is that these companies have all of this data, they have all this information, but they’re not leveraging it either at all or they’re not doing it properly. So what is it that BLDX is coming in and doing and providing with taking this data? What’s given back?
Ryan Howsam: That’s a great question. You look at the level of investment in terms of SaaS solutions, technological solutions, innovative solutions within the built environment, and it really tracks to around 2018. And so there’s been a lot of great solutions, but for an industry that’s highly fragmented. So by the nature of construction projects and the specialists you need at every level throughout the early design, CD’s, SD’s through constructability, and then operating and maintaining these buildings that whole Debaum schedule, you have tons of different information that’s living in siloed locations all across the construction project. And to really try to centralize that one is tough. But when it is centralized, how do you actually make it intelligent? So BLDX looks at it in three ways. How can we make this data lifecycle history of a project, of the resulting building, more verifiable, accessible and intelligent? And so one is gathering that information. At the front end every project has to have insurance before that project can really kick off and move forward. And so when that information is created, conceptual budgets, who are the general contractors, some experience, materials used, or what does the surrounding exposures look like in the demolition, will explosive be used various things like that all get used for insurance submission, but that’s only about 1% of the information. And after that time, that insurance policy is bound, I call it bind and pray. All parties at that time say, the insurance policy is bound and it’s about 1% of the information. And I just hope that we don’t have any issues. And we know the average cost unfortunately of a construction dispute today is about $52.6 million. And we’re seeing really a huge upward trend, specifically in North America, reaching these higher values depending on project size and complexity. So where we enter in is gather that information. After that, insurance policy is bound eliminate the blind spots for the insurers, general contractors and the owners of these projects to provide continuous underwriting. What does that mean? To simply identify the risks preemptively that lead to claims. And instead of asking all the questions in a claim scenario years after the projects done, how do we have a system that asks those same questions every day in real time, 24/7 of all the documentation flowing through that project.
Beau Lunceford: And you mentioned that AI is playing a big role in what you guys are doing. So what exactly does that look like for the service that you’re offering?
Ryan Howsam: I think it’s really important. AI gets thrown around a lot. I don’t think you can open it in Adobe, a Microsoft Word, an Excel spreadsheet, go to a website. I’m waiting for my socks to be AI enabled in some way. Like I’ve got AI in my jackets. But in all seriousness, AI is here and it is playing an important part. The CEO of Google just recently mentioned pretty controversial statement that’s saying “AI is as important to mankind as fire”. Look, human survival based on fire and shelter pretty big, we could argue, is AI that important? Regardless, you got to sit up and take note. When the CEO of Google is saying that I would propose or believe AI is at least as important as the Gutenberg printing press. And the role it is playing even today in the next three years is the impacts are going to be immeasurable. That said, I think when AI came out kind of to the masses, 2022, ChatGPT coming into 2023, that’s really like the year of wonder for AI. Like, oh my gosh, here’s this large language model and I can converse with it. Unlike just a Google search, it can converse with me in a language and in this new way, searching through tons of information and then you follow up and you have what I call 2024, the year of generative AI. And that’s where now, I can create content and pitch decks and put together lecture notes. I can create images with logos and very content. So that kind of year of generative AI. And 2025 is really, but I think it should be called “The year of Agentic AI”. And that’s just a really fancy way of saying, we have AI agents that can autonomously perform tasks. So we’ve moved on from this conversational AI piece to one where it can take mass amounts of information and generate some content to where you have an AI agent, just like a construction company hires an APM or an underwriter at an insurance company hires somebody to go perform a task. And that person gets better at the task as they get used to the specific information. Where now we have these AI agents that can help perform the job to be done. Kind of in the words of Clayton Christensen with that famous format about what the job to be done is. So I say all that, that it’s important. AI has different elements of where it can perform in that realm. What we are doing is, yes, you can use chat functions and bots to what I say is find the needle in the haystack of these hundreds of thousands of pages of construction documentation, plans, loss control, audits, risk analysis reports, you name it, budgets. But where it really gets important is if you think about what is the job to be done for our customers, it’s not that we don’t know what these risks were that led to the claims. It just happens that we end up having to ask those questions later when the issue becomes known. If we had the time and the personnel to sit and read every single bit of documentation across these 50, 100 different subcontractors, inspectors, permits, outside vendors, loss control, bringing in data from the insurance carriers, the brokers, the owners, the municipalities, the environmental reports. All the stuff that makes up this life cycle, we would be able to preemptively say, “Oh, I’m spotting an issue.” And it happens all the time on every project but we miss a lot. And the complexity and the flow of this data comes so fast and furious that you have to have AI to be able to process this information.
Trevor Casey: One of the things you’d said, so AI as a whole really is incredibly interesting to me. And the AI being used as an agent, I think is becoming something that we’re seeing more and more. One of the things I’m curious about, so you said that at the beginning we collect maybe 1% of the information. And as we know as a project continues on, we’re getting new data every single day. So is this AI agent reaching out to, let’s say, a project manager and asking it for specific pieces of information every day, or is it just collecting that information, scanning it and sending it off to somebody? Or is it building a report and sharing that. And based off that report, a person is saying, X, Y, And Z is, is problematic or is the agent AI doing all of the above?
Ryan Howsam: Great question. So it’s really a combination of everything that you spoke to. So in terms of the system, we’re ingesting information and you can do this for a new build project and you can do it for an existing building as well, but you’re ingesting that information as that information flows from the beginning of the project. Generally around the general contractor, you can pull it from systems like Procore. Not everyone uses Procore. There’s multiple SaaS systems we’re agnostic to, whether it is a PDF documentation, an Excel spreadsheet plans, or if you’re pulling out native files, say of construction software P6 or Microsoft Project, for instance. As that data flows in, there’s an element of. Here’s the questions we always want to be asking of that data that’s really kind of that Q&A AI assistant. For instance, if we have an EIFS exception exterior interior finishing system, there’s an exception on that project. We could four years into a mega project, all of a sudden a subcontractor submit some documentation saying, “Hey, on this portion, we got a design change. We’re going to use EIFS.” Here on this element of it. So that’s just that question and answer. When you get to things like completed operations, these policies don’t end when the projects end. OCIPs, CCIPs, CGL policies, they go through stature, repose, sometimes 7, 8, 10 years post completion. And you think about the completed operations claims around the envelope, exterior work, the big one, water intrusion, structural issues, MEP systems, that’s where you start deploying an agent with the job to be done, who’s saying, “Hey, AI agent, I want you specifically to look around water intrusion? Like, what are those elements that we want to look at? What is the quality control during construction? When did some of the installation occur, how was that sequencing occurred? When did you go in and look at some of the shingling effect?” You have another AI agent that might be just looking at building envelope protection. So thinking about what were the layers of armor and how did each component overlap? And then leveraging other SaaS technologies like Halo, cameras, daily logs, really taking in that kind of virtually of a digital twin of this project from a risk view of trying to preemptively identify risks, monitor them and stop them before they ever become a dispute and claim.
Trevor Casey: So when it comes to the completed operations, for example, does the AI agent look at the building systems as a whole? So let’s say air filters need to be changed, a roof hatch may be open and water could get in. Does it link to those kind of systems where it could say, “Hey, building manager, roof hatches open, air filters haven’t been changed in three years?” I mean, that’s a dramatic example, but something where there’s more going on after completed or is it strictly turnkey completed operations done, it’s now offers there somewhere an owner could continue to use this system?
Ryan Howsam: If you think about the BLDX platform as continuous underwriting, it is through inception as early as possible throughout the life of the building and can continue on even after the project stops. So to your question, we pull in information from like Zen maintenance systems. Now, the caution there, your data and your risk insights are only as good as the data you collect. We all know that. What gets really good about AI though and what our system does today is where it starts to identify gaps of information. Being like, hey, as a building we should know X, Y, Z. Like, where is the maintenance schedules on the HVAC systems and filters change out. And that’s actually pretty easy to do because we’re just ingesting the O&M manual in which shows here’s all the systems in the building, here’s what’s under warranty, and then here’s the recommended maintenance schedules on this or during construction. Like a flooring issue. We got a flooring issue. What happened instantly, the AI and our agent go through and say up installation of that flooring needed to happen at a certain humidity and temperature. This is happening a lot with new materials. And if we look back on that date and pull in from the IoT sensors, up the temperature and humidity did not match what insulation needed there. So you can quickly say, hey sub, this is an issue. If you think about that flooring becoming an issue years later, $7 is wasted on every dollar paid out in claims. That doesn’t include the dispute. That’s just if it’s paid out in a claim. A lot of that is discovery costs. And so one really unique thing we do as this information flows in, we put that information on chain so you have a distributed ledger of what happened, when, by whom. And that gets into the verifiable part of what BLDX does. The accessible part is that we can get after it. The intelligent part is where you start to build up these machine learnings and models over time of ingesting this information, it gets very specific to those projects where now it is a predictive tool, not just a reporting tool.
Trevor Casey: It almost sounds like BLDX needs to split off and start a law firm also. So you can say our costs are cheaper and our claims are less. And then you put everybody in construction out of business.
Ryan Howsam: What we hope to do and I think what’s important with AI and the job to be done. Artificial intelligence, in my opinion, is very stupid without a human guiding it. And there really is no plug and play AI, so to speak. You can grab someone to be a conversational bot to place orders on a website for REI, but we’re talking about the unique complexities of these projects. Is the AI starts to perform these more mundane tasks like any human could eventually go through and be like, “Oh, we missed the water intrusion testing that that should have happened on this day.” But if you have 100 subs and a thousand activities happening that day and someone thinks it happened and it went on and the permit guy came out and he just signed off on it. And that water intrusion never test what happened, but we just thought it did, and years go by and all summon its own fault. AI does a great job of asking that questions. So then humans can start to think about the value engineering. How would I use a different material? Oh, the AI told me there’s eve, we got an exception. Let’s redesign it today, not install it and have a $10 million rework in a $50 million dispute claim. So there’s that element of what I think is important to think about AI. It won’t replace a job, but it will allow the people guiding it to do much better. And we have one of those aspects where we’re just putting into practice now where we have AI agent’s interview stakeholders on the project to pull that human intuition out. Like how do you think about claims? Or what are you worried about? Not just setting an algorithm saying, look for this permanent water intrusion, but where we use knowledge graphs that create these huge contextual windows that starts to think about the building envelope in a whole and thinks about what are these jobs and sequences and workflows. And that’s where the autonomous AI or Agentic AI starts tend to perform more of these mature tasks that only humans can do today. And then that’s where today it starts to raise flags or summaries and going this looks like a risk. This policy covers this or not. We know from past claims. Here’s all the major issues and completed ops. And these are what our AI agents are looking for each day and you can continue to inform them as the project goes on.
Trevor Casey: Man, this has been a very, very unique and cool podcast because it’s really bringing through the things that I nerd out over. One being insurance, but the second being just like AI and technology and how fast the industry is moving. And I think there is just so much use case for your product in the industry and it’s just so cool to see it really being played out and used and you being able to show how efficient and just better it is as a tool. I feel like there’s going to be a lot of questions on this episode, so we’d love to have you back in the future and just dive into it a little bit more. For sake of time, we’ll kind of leave it at that. But before we leave, we always like to ask everybody, or we’ve started to like to ask everybody, what’s their inside insight? So what is it that really drives you forward? What makes you wake up every single morning? Is it a poem, a song? The ability to say, I’m improving people’s lives with my technology? It doesn’t have to be work related, it can be personal. We’re just always interested into kind of what makes people tick.
Ryan Howsam: That’s a great question. What makes me tick is never accepting the status quo and always pushing the boundaries that you can out at sea. So I’m a sailor and I always like to think there are forces that are constantly around you that are raging. You are reacting to that environment, but you are always putting yourself in the best possible position to take advantage of where the wind is going to be, strategically where you can find yourself in the best position to succeed. So I just think of life as sailing a sailboat. You got to handle what comes at you in that very moment and address it intelligently. But always be thinking as many steps ahead of the potential weather, even though we may not know what’s around the corner.
Beau Lunceford: Oh, wow, that’s bet incredible. I think that also is reflected back exactly in what y’all are doing. Because we have talked to other people about AI. Like, it’s come up. Obviously it’s a hot topic. But the way that you guys are leveraging this and the way that you’re thinking that next step ahead of how it is that you can make this work for you in this new generation of AI really is just a cut above anything else that we’re talking about right now. This has just been so great. And like Trevor said, we’re going to have people who have questions about this. There’s going to be more that we have to get back together and talk about. So, Ryan, thank you so much for your time, for all of the information that you gave us, really getting into what BLDX is doing and how it is that you’re really just changing the game. So before we go, is there anything else that you want to make sure that our listeners know?
Ryan Howsam: Never accept that these risks are going to be hidden. There is a way to uncover them. And don’t be shy about dipping your toes into AI or other technologies. Our industry tends to kind of wait and see around some things. It’s a little bit slow adopters, which is just fine, late adopters. But now is not the time to pause. Now is the time where you really need to make sure your people are getting comfortable with AI, whether it’s just using ChatGPT trying to look at elements of their job that are mundane, that are time sucks, that you can actually save some time to get the best out of your people today. And in those folks who are using AI are going to be more valuable employees to those organizations than those that aren’t. And so I just think it’s important to things are moving fast. You don’t have to keep up and you don’t have to be on the bleeding edge, but you do need to be thinking proactively how as a firm, are we going to start using it? So then you’re prepared to take those next steps as it does tend to mature.
Trevor Casey: Awesome. Hop in the car or we’re leaving you behind.
Ryan Howsam: That’s great. Thank you so much Trevor and Beau. I really enjoyed the podcast.
Trevor Casey: Thank you so much, Ryan. We really appreciate it and thank you so much for your time.
OUTRO (27:12 – 29:53)
Trevor Casey: Do you have a pesky limb? A tree that needs cut? A little yard work that may need trim, trim, trimming. Monster Tree Service out of Athens, Georgia has brought to you this episode of the Inside Insight podcast with Ryan Howsam – BLDX.
Beau Lunceford: That’s a solid plug. That was really good.
Trevor Casey: Well, they did sponsor this episode.
Beau Lunceford: We’re excited to be partnering with a Georgia native company that is technically a franchise, but that they are located here in the Northish Middle-ish Georgia area, providing tree cutting services for all those around us.
Trevor Casey: Thank you, Monster Tree Service, for sponsoring this episode. Honestly, I just loved talking to Ryan.
Beau Lunceford: Oh yeah, it was really easy. Which is true of most of our guests, I would say. But I don’t know, just the way that he engages with the material and he shows off his expertise and gets into the nitty gritty of what BLDX is doing without going over our heads.
Trevor Casey: And that’s what’s so funny to me with what he’s doing in the AI space, is it is so easy to just hear, “Oh, AI”. Everybody just sticks an AI thing on. But what does that mean? So most people are just like, “Oh, it’s AI. It’s powered by AI.” Where Ryan actually takes the time and he breaks down what it is. What are the metrics we’re looking for, how are we using that? And you feel smarter walking away from the conversation versus like, “Oh, so AI’s doing it.” Great. What does that actually mean? You feel like, “Oh, wow, I know what this is doing. I have a say in it. The system does all this cool shit. The system does all of this cool stuff that I can implement into my systems and my software and my workspace and not feel overwhelmed, like you’re drinking out of a fire hose or just saying, oh, it’s AI.” I believe that’s it is what it is.
Beau Lunceford: And I hope that people got a good idea of what BLDX is doing and the way that they are getting ready to impact the space with this new technology, with this really specific kind of AI that they’re using. So if you have any questions about anything that you heard today, please let us know. Please reach out to Ryan. All of his information is going to be in the show notes. Ryan, thank you again for sitting down with us and for making the time, because you not only had the time to have the conversation, but we actually got to even have a little pre call before to dig in a little bit extra to the stuff that we were going to be talking about. So thank you so much and of course, thank you to all of our listeners. We hope that we will see you back again for our next episode. So until then, stay covered.
PODCAST CLOSER
Thanks for tuning in to Inside Insight presented by CR Solutions. If you like anything that you heard today, subscribe, follow and rate the show so that other industry pioneers like yourself can find it. Maybe even share it with someone you think might benefit from this episode. Do you have a question that you want answered or a concept that you need explain, you can email us at info@c-r-solutions.com with the subject line “Podcast Question”, and maybe your question, we’ll make it onto one of our episodes. You can also submit a question via our website at c-r-solutions.com/podcast. There are no dumb questions, only opportunities to learn something new. Now that’s a wrap on this episode. Join us next time on Inside Insight presented by CR Solutions. Stay covered.
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