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Season 5 - Episode 2

Chaitanya NK

Track 3D CEO Chaitanya NK on AI Construction Monitoring and Scaling a Construction Tech Company

How reality capture plus AI turns job-site progress into actionable data—without slowing down the field.

Chaitanya NK explains how Track 3D uses reality capture and AI to automate construction monitoring—showing what’s installed, what’s missing, and what’s off-spec without manual reporting. Henry and NK unpack the founder journey behind the product, the shift from founder-led sales to scaling go-to-market, and why adoption on the job site is the real test.

Chaitanya NK on Henry Harrison Podcast

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About This Episode

Construction projects routinely slip on schedule and budget, often because field data is collected manually and arrives late, incomplete, or inconsistent. In this episode, Chaitanya NK—Co-Founder and CEO of Track 3D—breaks down how his team is using reality intelligence (site capture + AI) to give project teams real-time visibility into progress and deviations.

Track 3D enables a superintendent or project engineer to walk a site with a camera (or use drones and robotics) while the system reconstructs the space in 3D, maps imagery to the floor plan, and automatically quantifies what’s been installed. The platform can flag issues early—like an HVAC duct installed in the wrong location or sprinkler heads missed before ceilings are closed—helping teams reduce rework and manage risk proactively.

NK shares how his background across 3D vision, AI, robotics, and digital twins led to Track 3D, and why this company is the first time he and his co-founders raised venture funding. With more than 400 job sites live—from airports and data centers to hospitals and single-family homes—the company is scaling go-to-market in the U.S. after raising a total of roughly $14.3M.

The conversation also highlights a key founder lesson: adoption is won in the field. If the tool isn’t simple and immediately useful, it won’t scale—no matter how strong the top-down mandate is.

Key Insights

  • Manual job-site reporting creates delayed, inconsistent data—AI can turn reality into usable metrics.

  • Early detection of deviations (wrong placement, missing installs) is where rework savings compound.

  • Reality capture plus AI can quantify progress and map it to floor plans without manual input.

  • Field-first design matters: if crews don’t feel immediate value, adoption stalls.

  • “Zero learning curve” is a competitive advantage in construction tech.

  • Founder-led sales works early, but scaling requires dedicated go-to-market teams.

  • Hardware improvements (cameras, drones, robotics) amplify what AI can deliver.

  • Conferences and job-site visits still matter because trust and workflow fit are proven in person.

Episode Transcript

Transcript Disclaimer: This transcript has been edited for clarity and readability. Filler words and minor repetitions were removed, and formatting was adjusted to improve flow. The substance and intent of the conversation remain unchanged. Henry Harrison: It’s going to be a terrific episode of the Henry Harrison Podcast—Entrepreneurs, Business, and Finance. We’re fortunate to have NK, Co-Founder and CEO of Track 3D. He’s founded multiple companies over the years and has been building Track 3D for almost four years. Hello, NK. Chaitanya NK: Hey, Henry. Thanks for having me. I’m excited for this conversation. Henry Harrison: Let’s start with what Track 3D does. I’ve got a background in construction—I ran a custom homebuilding company for 10 years. I know the chaos and the constant need for control, data, and good management. What are you doing to improve that? Chaitanya NK: You’ll understand the context well. Most construction projects go over budget, over schedule—often both. Track 3D helps keep projects on track by automating construction monitoring. You can capture the site with a moving camera—using a robot, a drone, or someone walking with a camera. Our AI automatically tells you how much work has been done, what has been done, when it happened, and whether it matches specifications—without manual input. You can walk around with a phone, even on a single-family home, and the system identifies what’s installed. That gives teams proactive visibility so they can mitigate risk and keep the project on track. Henry Harrison: You didn’t just wake up and build this. You’re a software engineer, and you’ve started multiple companies. Track 3D has raised significant capital—about $10 million in a seed round—and you’ve been investing heavily in the technology. Chaitanya NK: It’s been a long journey. We’re three co-founders. Two of us have been on this path for more than 15 years, and all three of us have worked together for eight years. We’ve been friends since high school. I started my first company in 2007 after a corporate internship confirmed I wasn’t meant for that world. I’ve always enjoyed building new, impactful things and working on cutting-edge technology. Early on, I worked with 3D vision, AI, robotics, and IoT. I’ve also always believed that pictures are powerful—but turning pictures into 3D is even more valuable. Over the years, we worked across medical, home automation, industrial automation, furniture, augmented reality, and smart cities. In our last startup, we built digital replicas of entire cities using drones and robots. That led us into construction because cities do a lot of construction. We helped administrators track job sites and realized construction is a massive global problem that technology can solve. That’s why we started Track 3D four years ago: apply our expertise to a trillion-dollar industry where job-site data is still collected manually. Manual data is often inconsistent, incomplete, inaccurate, or inaccessible. Stakeholders don’t get the right data at the right time. This is also the first time we raised venture funding. We wanted the right partners and the resources to create impact at scale. We’ve raised about $14.3 million total, and we announced our Series A about a month ago. Henry Harrison: Where are you right now? Are you in market? Do you have clients? Chaitanya NK: Yes. The first year and a half was co-development and learning customer requirements. We’ve been commercially available for the last two years and are working with some of the largest construction companies in the U.S. We’re on more than 400 job sites right now—airports, data centers, hospitals, wastewater treatment plants, retail units, and even single-family homes. The technology is scalable. Henry Harrison: What was the purpose of the funding? Technology investment, people, growth capital? Chaitanya NK: The Series A is primarily to scale go-to-market. Early on, it was mostly founder-led sales supported by my co-founders and the team. We didn’t have a strong U.S. presence from a sales and marketing standpoint. Now we’re investing heavily in sales, marketing, and go-to-market because every job site globally is our target market. We want Track 3D to be accessible everywhere. Henry Harrison: Give me a real story. A problem you solved where it was a clear win. Chaitanya NK: There are many. One example is a major airport project in California. Our platform is field-first. It’s built for field teams while also giving the office visibility. In one case, an HVAC duct was placed in the wrong location. Our AI detected it and showed it on the floor plan. Catching it early made rework drastically cheaper. Another example is sprinklers. Sprinkler heads needed to be installed before closing the ceiling panels. A subcontractor said they were 100% complete and asked for payment. The superintendent checked Track 3D and saw they were at 98%. The system identified four missed sprinkler heads and showed exactly where they were on the floor plan. On a large airport floor, finding four missed sprinkler heads after the ceiling is closed can be extremely costly. With Track 3D, they could verify instantly. Henry Harrison: How does it know? Is it mainly through cameras? Chaitanya NK: Yes. The most common method is walking the site with a 360 camera or even a phone. Our AI reconstructs the space in 3D, detects installed objects, and quantifies what’s there—counts, areas, heights, and more. Henry Harrison: I can relate. In residential, you can walk a few homes and take notes. On a large commercial site, you can’t realistically walk everything and remember it all. Chaitanya NK: Exactly. Think of construction like building a Lego set. You may love building, but nobody loves documenting every step. If a camera is observing the build and AI records what changed and what’s installed, documentation becomes automatic. Physical assets are some of the largest capital investments people make, but the documentation is often ordinary and inaccurate. We want the reality of the site to become the system of record. We call it reality intelligence: reality capture plus AI. That’s how we understand the physical space, track changes, and generate actionable insights without manual reporting. Henry Harrison: Adoption is always the concern with new software. How hard is it to implement? Chaitanya NK: Construction is called a tech-laggard industry, but I think the real issue is that technology hasn’t been simple enough for the field. Our design principles are zero learning curve and fitting into daily workflows. Onboarding can be just minutes. You give us drawings and you can start. We’re not perfect yet, but we’re seeing strong adoption because it’s practical and field-first. Our goal is that customers can pick it up and use it without us walking them through it. Henry Harrison: I saw a chat function on your site. Are you using AI for support and usability? Chaitanya NK: Yes. We have an AI agent that lets field teams ask questions naturally. A superintendent doesn’t even need to log into the system. They can message a bot and ask, “How much drywall was done in the last three weeks?” and the system responds with square footage and location. That’s part of our goal: make information accessible with no learning curve. Henry Harrison: Does adoption happen bottom-up or top-down? Chaitanya NK: Both. Leadership may drive adoption, but the real test is the field. If the tool doesn’t save time and reduce friction, it won’t scale. Our measure of success is that field teams become dependent on it. If you take it away, they should feel like they can’t do their job the same way. Henry Harrison: You’re now in the Bay Area. Are you finding that ecosystem helpful? Chaitanya NK: Yes. I moved from Dallas a couple of months ago. The Bay Area ecosystem—founders, investors, mentors, and talent—is valuable, especially as an AI-first company. Dallas is strategic and we’re still active there, but Silicon Valley remains one of the best AI ecosystems in the world. Henry Harrison: What’s your marketing and sales strategy now? Chaitanya NK: We still believe strongly in in-person engagement. We’ve been coming off back-to-back conferences. Face-to-face conversations cut through the noise better than email alone. We do digital outreach too, but meeting users in person matters. We also spend a lot of time on job sites. That’s where the best learnings and the best conversations happen. Henry Harrison: Anything you want to say to wrap up? Chaitanya NK: Thanks, Henry. We’re excited about becoming the operating system for every job site globally, regardless of size. We believe the impact can be massive, and we’re excited to build the team and partnerships to get there. Henry Harrison: It’s a pleasure to have you on the show. I wish you the best, and let’s stay in touch. Chaitanya NK: Absolutely. Thank you for your time.

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