Data from Thousands of Tests: How Simpson Strong-Tie Is Building an AI Moat

0:00We have a pillar which is AI for customer growth. And we focus under this pillar on embedding this Simpson domain know-how into our solutions, into our software.

0:11Peter High: Welcome to Tech Innovation. I'm Peter High, president of Metastrategy. My guest today is Udit Mehta. Udit is the chief technology officer of Simpson Strongtie, a leader in engineered structural connectors, building products and software solutions that help people design and build safer, stronger structures. Its parent company, Simpson Manufacturing, generated nearly$2.4 billion in revenue in 2025. Udeet leads global technology strategy and operations, spanning enterprise modernization and customer-facing software solutions. He's helped guide the company's evolution into a technology-first building solutions provider, combining engineering expertise with data, software, and AI.

0:52Peter High: Prior to joining Simpson Strong Tie in 2024, Udeet held technology and digital leadership roles at Carrier and Siemens. In this conversation, we'll discuss how Udeet balances internal transformation with digital business growth, how technology can help builders address labor shortages and reduce waste, and how he sees AI and new construction methods shaping the future of home building. Udeet, welcome to Tech Innovation. It's great to speak with you today. Peter, thank you for having me. Always a pleasure to talk to you. And now for a word from our partner, Blitzy. Want to shift software five times faster?

1:24Peter High: Meet Blitzy, the autonomous software development platform built for enterprise-scale initiatives. Your code base has outgrown any one team. Tens of millions of lines, decades of technical debt, more than any other AI tool can hold in its context window. Blitzy starts by understanding. Thousands of specialized agents map your architecture, dependencies, and business logic across every language into a knowledge graph. That graph also services hidden CVEs and zero days before an alert ever reaches your desk. Then you describe what you need in plain English and approve the agent action plan Blitzy builds.

1:59Peter High: Grounded in the knowledge graph, Blitzy executes entire engineering epics over weeks of continuous compute, and every line is tested end-to-end before it reaches your team. Modernize legacy systems, close critical vulnerabilities, ship new features five times faster. Learn more at blitzy.com slash technovation. That's B-L-I-T-Z-Y dot com slash technovation. And now on to the interview. Yeah, I feel the same way. I'm so grateful you would take this time with me, Adit. Let's begin with your business, Simpson Strong Tie. I mentioned a little bit about it, and I would imagine there are some people who are listening to this or watching this who may be less familiar with it.

2:38Peter High: So fill in some of the details as to the business you're in. In the simplest form, if you want to know Simpson Strong Tie, our products make the connection possible between any steel, wood, and a concrete structure at the core of it. people who are in construction generally know us for our connector products that hold the structures together and residential commercial but our business actually Peter is is much broader than that we bring in engineered products we have software portfolios equipment expert services to solve all types of structural challenges across the residential domain and the construction setting the commercial construction setting and behind these products is a deep deep research of 70 plus years of product build, innovation, rigorous testing, and of course, the white glove support that we provide to our customers.

3:28And our role particularly is very interesting in this construction industry that, you know, sometimes it's kind of known as a laggard, but really has an opportunity now with all things AI, that we participate across the value chain of construction. So we've got material hardware, we play in the software space, we've got exclusive services, and then we offer deliver our equipment to our customers as well. And many cases, our software is kind of the ERP. Think of it as the ERP because it spans in design and estimating, material planning, material procurement, and production management. And another key highlight, I would say, of Simpson Strongtie, which is very near and dear to my heart, even where I am coming from, is the core values of our company.

4:13And we have some amazing people working at this company whose passion, ingenuity, and the commitment have enabled us to be the most trusted construction solutions provider for jobs worldwide.

4:27Peter High: Fascinating. Thank you so much for sharing more details as to the diverse business that you're a part of. Describe your role as the Chief Technology Officer. What's within your purview? My purview spans across both technology that runs Simpson Strongtie as a company, so all things enterprise technology. Call it ID, if you will, but we call it enterprise digital technology and digital solutions that help our customers run their businesses. And what connects these responsibilities truly is the opportunity to combine our engineering domain expertise to our hardware products, our services, all kind of underpinned with that software thread to elevate the value even higher for our customers.

5:11On the enterprise side, my team focuses on advancing the foundations of technology to support our global workforce, our operations, and that includes everything from infrastructure, security, enterprise applications, and very recently now all things enterprise data and AI federation across the company. And the objective here is to stay current, operate efficiently, serve the customers, keep augmenting where capabilities are needed for the future. On the customer side, the team builds and delivers digital solutions that support construction professionals as well as our customers across a variety of workflows on construction value chain.

5:49And as I said before, from designing a structure to estimating the bomb of the structure, selecting materials for that structure, production management of the different components of the structure, and finally installation, among many others. And here our objective really, Peter, is to translate this deep industry experience that we have, the knowledge that we have into AI-enabled software that's easy to use, that's value-add, that's embedded into our customers' workflow day to day. So at the end of the day, ultimately, you know, I feel responsible for connecting technology investment to the business value outcome, as well as a customer value and outcome and making those choices of what do we build?

6:32What do we modernize? What do we source? What do we integrate? Is most of my brain space.

6:38Peter High: Yeah, very interesting. And as you, thinking about the, I mean, what a broad set of responsibilities you have, as you described the customer-facing aspects to the work that you do, talk a bit about the customer touch points that you and your team have. How many of them are, you know, like direct touch points to customers, working with other members of your team who have those direct touch points in order to ensure that you're designing the right solutions for the needs they're articulating? Yeah, our feedback loops are pretty strong. So what we do is, you know, we take our hardware products, we go, we have distribution channels that support them.

7:13We also have software capabilities that work with our customers directly. So every time builders who are, you know, having lots and they're trying to option manage the lot, they would use our software. We would also provide estimating capabilities to different lumberyards, to component manufacturers. But then component manufacturers would even help be helped by our software to actually produce the components that are going on the job site. So across a variety of domain, the teams kind of interact with the customers. We also have a commerce channel. So for many of our customers who are very familiar with our products, or even if they want to search and order, they have a capability of a direct front door to Simpson so that they can place our orders and we make them available.

7:56We give them availability information, but then also the supply chain information of when they're going to get it. The name of the game is very high turnarounds, high level of service, and making sure that they are getting the parts when they need at the job site in a very confident and quality manner.

8:13Peter High: And you joined the company about two years ago. And I know that in the early stages of your time with the company, Udit, you really focused on a modernization campaign. And I'd love to have you reflect on some of the form that took. What did you prioritize as some of the most important changes to implement early on? That's a great question. When I joined the company, the first question that was coming up was what capabilities would Simpson need to serve the customers better? And what are the key opportunities that we have for our next stage of growth? And if you look at Simpson, we have been in business for 70 years.

8:50In fact, this year we are celebrating our 70th anniversary of our foundation. and we have been listed for more than 30 years as well. So as we look at the next growth story, it's all about digital solutions. It's all about technologies that can help make homes and structures safer and stronger. So very early on from my site visits and my interviews, it was pretty clear that the company has a tremendous amount of strength in structural engineering, a vast portfolio of products, very deep customer relationships and a very high service standard. So my opportunity was to kind of build on top of those strengths and to make our expertise even more accessible to our new customers, to our existing customers, as well as to give our teams that sort of stronger foundation for the future.

9:38So the first step was strengthening that foundation. And that meant infrastructure modernization, advancing our cloud native capabilities and footprint, introducing responsible AI to all the knowledge workers. And our teams have done a fantastic job. We have more than 1 ,000, 1 ,200 plus employees and workforce today that are familiar with AI, that are using AI and maintaining a very resilient cyber posture. So these investments sometimes are less visible to the customers directly, but they really underpin reliable operations and our ability to introduce these capabilities. Second step was really connecting that modernization that I talked about to practical customer needs and business applications.

10:24And the clear test of that was, what's the problem that we are addressing from a customer perspective? What's the pain that we are alleviating? And then how do we assess that that particular solution is, in fact, useful? And in construction, if you are familiar with the territory here, the technical feasibility alone is not just enough. Any solution has to embed into the workflow to make economic sense for the industry. Given this industry, you know, sometimes feels it's kind of stuck with the walkie-dalkie age, but, you know, this is the opportunity we have with AI. So we build very strong feedback loops.

11:02We prioritize customer co-creations where possible. We have fast pivots as we look at the horizon. And finally, you know, I think organizational capability to sustain change. Technology, as we all know, moves very fast. Sometimes I feel faster than the rate of the planet, movement of the planet. But, you know, pure technology investments only take us so much so far. So developing our workforce and encouraging the learning, making a high performing team. These are all capabilities that are more ongoing rather than like one time campaign. So that's another area that I stress quite a bit.

11:43Peter High: in a recent conversation you and i had indeed i was fascinated to hear about some of the challenges that home builders face from pressures around labor availability material cost affordability more generally speaking and i'd love to have you talk a bit about how those challenges shape your technology priorities um to talk a bit about that if you would yeah i mean it's true that i mean very true that affordability or labor shortage or material cost volatility from a tariff perspective. I mean, all these are factors that are affecting the sort of larger housing market. And I truly feel, I mean, there's no one person or one company that can go solve for all these factors.

12:22Instead, what we can do, particularly as technologists, is to focus on the data flows, the decision flows, the workflows that can influence the cost of the home and the speed at which a home is built. And for us, it's always a safer and a stronger home. So if I translate this back to me, it affects me in two very distinct ways. One is making it easier to access and interact with Simpson's core expertise, which is structural engineering, which is our product design, which is our product application. How do I take that and embed that into digital solutions supported by our technical teams who do specialized training for our customers on product selection, on procurement, on costs, on installation.

13:10And I must say, I mean, AI is playing a very important role here because it's starting to support our engineering judgment and not bypassing that judgment. So we internally have developed capabilities that would assist our technical support team, engineering teams, troubleshoot for some of the most complex connections and efficiently using their judgment, finally combine our proprietary data and domain knowledge to deliver value to the customer. And the second I would say is improving this handshake between intelligence and the actual workflow in the field. So rather than optimizing every task of construction independently, what we are focused on is enabling choices that would influence the end-to-end workflow.

13:58So think of designing a home, doing a material takeoff for it, manufacturing for those materials, procurement of those materials, and finally installation of those materials. So our digital solutions give us very practical ways in which we could solve for those unique customer challenges across whether it's pre-construction, construction, post-construction phases. So those are two kind of unique ways of how it all comes back to technology.

14:26Peter High: Yeah, fascinating. And it strikes me also, you work with home builders of various sizes. And part of what you're describing, I imagine, is a universal set of needs and perspectives across large ones and small ones alike. But I wonder, what are the nuances? Surely there are some between some of the largest builders that you serve and smaller ones that you also serve. I'd be interested in your perspectives there as well. Yeah, I mean, the opportunity, the way I look at it, the opportunity of working with a broad range of home builders is to really understand where construction process can be further optimized and where are problems worth solving for.

15:03I don't treat any company size as a substitute for understanding that pain or for understanding the value proposition. Our core company value, number one, is relentless customer focus. So for us, it's especially important with the builder in the field that we listen, we partner, we deliver, and we serve. And doing all those things repeatedly helps us learn about the decisions that they are trying to make. Where do the information gaps exist? What's making a task difficult? What's making it expensive? What's making it dependent? And there are particular builder preferences as well, as you kind of talk about production builders that are large scale and smaller builders who are building fewer homes.

15:48I would say deliberately, I try to spend a lot of my time connecting and learning from my counterparts in the customer's organization just to understand, like give me a perspective on the challenges they are facing from a back-end perspective of building and a front-end perspective of how they are meeting with the customer and serving. So our product roadmaps have worked time now over the last two and a half years. built a very strong discipline in connecting this insight into a career problem statement and a practical solution that gives us evidence in the field. So we treat every release as a delivery milestone.

16:26Testing whether it makes the customers work easier. Does it make it efficient? Does it make it intuitive? Is there value attached to it? And, you know, you would see very recently we launched at the BCMC conference. We showcased our integrated cloud native portfolio of component manufacturing software and differentiated services that go with it. This is a major milestone, not only for us as a company, but also for the entire residential construction industry. So, you know, my goal is to is to make sure that our customers experience that Simpson understands. We pay very close attention to how they build and that our software comes with the same amount of expertise, service and commitment that they have enjoyed from all of our physical products so far.

17:15Peter High: Fascinating. I also find fascinating that you're building a software business alongside the physical products business as well, Udit. And I wonder, as that evolves, as the company's mix continues to evolve, what have you found needs changing in terms of your talent mix or your digital product management approach or the commercial model more generally speaking? What insights come to mind? Let me first address the commercial and the kind of software business. So we all understand that a software business or any, let's say, AI-led business is only going to succeed and it requires sort of recurring customer value to be created all the time.

17:53So we at Simpson are very uniquely positioned for delivering this value. And I'll tell you why. Because we have an unmatched product portfolio of hardware. We have a suite of software that spans across the value chain. Our services are white glove and we work with our customers both upstream and downstream all the way from their education, engineering certifications, as well as on the field and helping them install. We provide the equipment and all of this is underpinned by our trust, our global footprint and our very high service level. So as Simpson, we can offer value at multiple levels and in multiple combinations, depending on where our customer is in their journey, what their priorities are, their ambitions and their constraints.

18:42A new pure play software entrant in this market doesn't have all the possible value combinations to match such a proposition. I would say, I mean, they could have capabilities, but it makes us very unique given how we are spread. But on the talent part, I mean, in today's day and age, particularly where everything is driven by AI, product management and software engineering in itself are not that sufficient. I mean, what matters is to bring our domain know-how, our structural engineering know-how, our proprietary data. And I'll tell you, I mean, we conduct thousands and thousands of tests on every single product every year.

19:23And we have data from all of it to know how these products perform in real life, our relationships and our service. So when we combine that with digital product management and digital product delivery, those capabilities is really in that combination is what creates that value. We can influence change to the industry. We can drive adoption. And that's eventually where we extend ourselves beyond our traditional footprint and traditional business model.

19:55Peter High: Fascinating. It's interesting to hear across the evolution of your couple of years now in role, the setting of a better foundation upon which to build. And now parlaying and taking advantage of some of the different areas you can, in fact, go as a result of that great foundation. And it strikes me that artificial intelligence is among those areas that as a result of the work done to get better data hygiene and governance and so on, now an ability to take advantage of that in some great ways. I'd love to have you talk again about some of the foundation laid from an AI perspective, from a security and governance and accountability perspective, some of the things that you did in order to ensure that you had the right practices in place in order to better take advantage of artificial intelligence.

20:39Yeah, I mean, as we were evolving the capabilities of AI, we wanted to make sure that, you know, AI does not change our obligation to earn customer trust. I mean, it changes what we must actually uphold for that trust. So my approach has been to connect and interweave cybersecurity, data governance, accountability to the specific AI decisions that, you know, it is supporting across the workflows. So we run all of our decisions through a dedicated governing body, which is comprised of cross-functional leaders. Security focuses on all things AI with access, with real-time monitoring, audits. They oversee governance controls, permissions, policy enforcements.

21:29The data team, on the other hand, really addresses the fit for purpose. And it oversees things beyond just availability of data. They make sure that the data lineage independencies are clear. It is coming in fresh. It's protected and it's purpose fit for the particular purpose. So what we do is we have data products that we have created within the organization. So we have an orchestration layer that feeds in the data from all our applications. We normalize it because we do have both structured and unstructured. We purpose fit them into data products, which is then consumed by both humans as well as agents for the unique value delivery that it has.

22:14And finally, I would say accountability. I mean, in this world of AI, accountability should remain with us, should remain with us humans. So in every step, every enabled workflow that a business owner designs for, he or she is accountable for the intended outcome. So my technical team supports it and we help execute it within the operational boundaries. But there is a business owner that is accountable for the intended outcome. So it's this constant trade-off of making experimentation easy, secure, scaled, without making this consequential deployment very casual or seen casual is something that is a leadership challenge and always kind of makes us better.

23:03Peter High: Makes sense. Talk a bit about where you're deriving the most value from artificial intelligence today. Now that you have this, again, great foundation laid, what are you building upon it that has you most excited? We have kind of created an approach where our AI strategy is threefold and it's equally weighted. It works in parallel. So it's not sequential or, you know, doesn't kind of overpower the other. But the first pillar is all things AI for productivity, which focuses on individual and team productivity. And the approach here is to empower the people. We provide AI education to uplift folks and make sure that they are fully enabled to derive value.

23:46We give them the tooling. As I talked about, we have approved data products that increase their throughput. And it kind of helps them reimagine sort of their next workflow. Our enterprise data and AI has a governed orchestration layer that provides the team access to a variety of models. So they don't have to go outside the organization to procure models. They can build capabilities and agents for themselves within the org and their teams to safely scale their use cases with speed. The second bucket is AI for enterprise value, we call it. And this bucket focuses on cross-functional use cases that are prioritized by this governing body.

24:29And they only do it if there is a very clear ROI that is impacting the P &L and impacting in a very time-bound sort of fashion. So these are generally complex use cases with multiple data sources. Many times these data sources have to be normalized. They have a variety of integrations. Sometimes external data is also used. They have sophisticated data engineering and AI engineering into it in case we are combining vision models with LLMs. and very strict sort of adoption metrics. So this is the bucket where we really zoom in to make sure that the ROI is realized. And once we do this, we expect that these process re-imagination exercises that we undertake are going to scale further into other departments as well.

25:17So we've seen operations, we've even seen HR, we've seen legal. We are one currently working with our sales teams. So many, many use cases that are coming up that are adding value to the P &L. And then finally, we have a pillar, which is AI for customer growth. And we focus under this pillar on embedding this Simpson domain know-how into our solutions, into our software. And the idea here, Peter, is to provision our capabilities as close as we can to the point of consumption by our customer. So whenever they are ready to estimate a particular lot or a particular option within a lot that we are having the latest and the greatest know-how available to them for the right estimation and for the right product selection.

26:07So, you know, our platform team internally has done an amazing job building an AI harness across product management, software dev, quality testing, security controls. And the handshake is such that it even helps teams exchange thoughts, capabilities across releases. So it's making us so much more efficient. And my conviction, honestly, is that AI will continue to extend our customer offerings as Simpson. It's going to enhance our service model in the future. And then it'll create this next layer of our business mode. And that's how I see AI kind of developing both within the company and in the sector.

26:53Peter High: Fascinating. And thank you so much for sharing a bit more about the way in which you think about the threefold strategy. And I can certainly understand the AI for productivity and the AI for enterprise value in many ways, educating the third strategy, AI for customer growth, focus these internally, build expertise, comfort. Again, we talked earlier about the governance and security and all the necessary ingredients for this, getting then to the point of being able to develop things that push out to the customers and impact their outcomes as well. Am I right that there's a logic to the order itself in terms of how the value is attributed and how one builds upon the one prior?

27:30Absolutely. Absolutely. The capabilities that we have internally really look at the enterprise modernization, really look at how we can be more efficient. And in the same way, when we combine that with our domain know-how and our data, our product data, our test data, our enterprise data, we can now start creating another layer of value for our customers who are already very familiar and very used to the quality and high level of service that they get on our hardware. So that makes it very easy to talk to our customers and tell them where we can enhance their growth as well.

28:07Peter High: Phenomenal. Before I let you go, Udita, I'd love to understand anything you recently read or listened to that you'd recommend to others during this time. It's always, I think, interesting to understand the intellectual diet of different executives. I'd love to have you share a bit about yours if you would. Well, Peter, I have to start with Technovation itself. And I'm not saying this as a polite guest flattery, but I mean, genuinely occupies a regular spot in my rotation. As you know, from my previous days at Carrier and the drives between Orlando and Palm Beach, there was not a week I would miss an episode.

28:39Peter High: So thank you for doing what you're doing and sharing all the insights with us. Outside of it, I also like listening to the podcast called This Week in Machine Learning and AI by Sam Charrington. for a company like Simpson Strong Tie, where safety, precision, trust are paramount, staying grounded in the mechanics of how models actually perform in production is very essential. So that podcast kind of goes beyond generic headlines and into real world applications. So I like that. On the other spectrum of it, I do like watching the lively banter of the All In podcast with very unfiltered debates about macroeconomics and technology shaping future, capital allocation, regulatory shifts.

29:24The challenge for us and for a CTO today is really synthesizing these various inputs, keeping the technical radar tuned to the frontier and maintaining that pulse on both macro and micro while learning from other executives and leaders like yourself and others in the industry. So that's what I would recommend to folks.

29:47Peter High: Phenomenal. Thank you for your kind words, Udit. I'm delighted that now you're part of that growing content that your peers might take advantage of as well. And speaking of which, I'm grateful for our time today. Thank you so much for sharing more about a very consequential two years in role. And I can only imagine with the progress already made, the foundation laid, some of the value already derived, the next two years will be even more meaningful. But thank you so much, Udit, for taking time with me today. Thank you, Peter, for having me. Pleasure talking to you and I look forward to many more.