Why Construction Leaders Are Turning to Reality Intelligence

[00:00:00] - [Speaker 0]
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[00:01:47] - [Speaker 0]
And while most people still picture construction as maybe slow moving and low tech, My guest has a very different view. He will argue that the sector has been ready for innovation for years and that the real barrier has always been that technology was too slow, too fragmented, or too difficult to use. But today, I wanna learn about how technology is changing all that by bringing together reality capture, AI, robotics, and computer vision so that every stakeholder on a building site can finally see what's happening, when it happened, and whether it meets the correct specification. He's also gonna bring it all to life with some practical stories about how to detect mistakes before they turn into costly work, spotting deviation spotting deviations the moment they occur, and giving teams the clarity they need to reduce to reduce risk and deliver with confidence. So if you work in the construction industry, operations, digital transformation, or indeed any environment where progress and accuracy matter, and I would argue that that is every industry.

[00:02:56] - [Speaker 0]
I hope that this episode will offer you a fresh lens on what AI can do right now. So a massive warm welcome to the show. Can you tell everyone listening a little about who you are and what you do?

[00:03:10] - [Speaker 1]
Absolutely. Thanks for having me first evening. It was great to have a conversation with you. By way of my introduction, I go by NK. Much easier that way.

[00:03:20] - [Speaker 1]
And I'm the CEO and cofounder of our company, Prak three d. We started Track three d about four years ago. And what Track three d does is it automates construction monitoring. So everything that happens on a job site, you can record it with any camera, drone, three sixty camera, mobile phone. And Track three can automatically with its AI first platform, it will automatically quantify and qualify progress for you.

[00:03:46] - [Speaker 1]
That is how much of work is done, when it is done, where it is done, and also is it done to the right specifications or not. So that's what track three d does.

[00:03:57] - [Speaker 0]
And one of the things that I love doing on this podcast, business technology perspectives, is getting people thinking differently about the way that technology is impacting any industry and industries that you don't automatically associate with technology. And when you think of construction sites, I think a lot of people will not think about AI. I think that's safe to say. So when you think about the state of construction and construction technology today, what kind of problems feel most urgent to solve for you? And and why has reality intelligence become such a significant part of that conversation?

[00:04:36] - [Speaker 1]
No. Great question, Neil. In fact, let me start by giving you a bit of perspective. We are three cofounders, and none of us actually come from the industry. We have been doing startups for quite some time.

[00:04:47] - [Speaker 1]
I personally have been working on the technology domain and startups over the last twenty years now. And technologies such as three d vision, AI, robotics, especially the convergence of these technologies is what's been something I've been extremely passionate about. Now when we entered construction industry, right, to your question, we initially thought that is a that is a impression everyone has. Construction doesn't have a good reputation. They consider to be digital laggards, right, in a way.

[00:05:18] - [Speaker 1]
But when I entered in that, I that was not the case. I was very pleasantly surprised. These guys are not technology laggards. In fact, they're ready to adopt technology provided it helps them simplify their lives,

[00:05:33] - [Speaker 0]
you

[00:05:33] - [Speaker 1]
know, take away all the menial tasks that they're doing right now. And anything that helps them to increase their productivity, they're ready to take. In fact, some of the largest construction companies we have been working with, they have a portfolio of 300 apps. I have not seen that even in some other industry. The 300 enterprise apps, think about it.

[00:05:53] - [Speaker 1]
Right? And everything is siloed. Everything is disconnected. And the problem is not of construction being a digital laggard. The problem is the technology is not being good enough until now.

[00:06:07] - [Speaker 1]
Right? So they were not simple enough. They were not fast enough. They were not accurate enough. They were not cost effective enough to see mass scale adoption.

[00:06:18] - [Speaker 1]
So that was the genesis of PractiD in that sense. So we started PractiD about four years ago just with that vision that, you know, why can't we create a technology which is extremely simple and super valuable to the field so that, you know, irrespective of its shape, size, or geography, you can apply these technologies and people can take benefit. And that is what reality intelligence is all about. So reality intelligence is nothing but reality capture plus artificial intelligence. So it's like the physical AI.

[00:06:52] - [Speaker 1]
We understanding our physical spaces in three d measuring that and giving deep actionable insights on them. That is what we position reality intelligence as a New York Track three d pioneers reality intelligence. So no matter which reality capture source you use, it could be a drone, it could be three sixty camera, mobile phone, laser scanners, or even terrestrial robots. The idea is how do we can take this data, convert it into actionable and measurable insights, and present it in the simplest accessible way possible for the job site.

[00:07:28] - [Speaker 0]
And a question I've got to ask, because you said earlier in your answer that that none of you are from a construction background. So what was it that that first attracted you to that industry and and solving problems? I feel there's gonna be a story there too. Right?

[00:07:43] - [Speaker 1]
Absolutely. In fact, the last startup that all the three of us were together at, in fact, three of us have been working together for quite some time. We are friends since high school and know each other for more than twenty years now. So we go a long, long way back. And all the three of us were working on previous startup, which was in the smart cities domain.

[00:08:02] - [Speaker 1]
Uh-huh. We were creating digital replicas of entire cities. And that's where we got introduced into the world of construction. Because cities do a lot of construction, they wanted that operational visibility over what is happening. Right?

[00:08:16] - [Speaker 1]
So every job site until then also, right, when we got started, even today for that matter, data from the ground is predominantly being recorded manually. And manually captured data is either incomplete, inconsistent, inaccurate, or inaccessible. So the right decision makers of the project or the stakeholders of the project, both on field and back in the office, never have the right data or insights at the right time to take the right decisions. And most projects go over budget, over schedule as you rightly know. Right?

[00:08:49] - [Speaker 1]
Yeah. Yeah. So we thought we can solve that problem by smartly applying these technologies and making people more efficient. Now now people don't do this because they have any malicious intent. No.

[00:09:03] - [Speaker 1]
In fact, these are the best people I have ever come across in my life. Right? The people working on a construction site. But it's impossible to go on a field and measure thousand rod drops on a ceiling, on a 70 foot ceiling. It's just not practically possible for humans to do it.

[00:09:20] - [Speaker 1]
To measure everything that's installed, take take a tape measure and do it. No. In fact, these are tasks that we are not supposed to be doing in the first place. The actual physical work, the coordination, that is what actually derives the value. So that became the genesis of TAC three d.

[00:09:38] - [Speaker 1]
Right? So these were insights we could uncover. And I guess what helped us was being industry outsiders because we were a curious bunch of people. We knew nothing about construction. But our learning came by visiting job site to job site.

[00:09:53] - [Speaker 1]
Just being on the ground and being genuinely curious. We were not even trying to sell anything. We were like, you know, please make me understand what are you doing currently. How can we help you? That created a kind of rapport that actually unlocked so many use cases for us.

[00:10:11] - [Speaker 1]
So many stories got built because of that. So many relationships got built just by that curiosity. And I think that was something that has worked tremendously in our favor. Just being curious, just being, you know, on the ground, and talking to the folks that we are building a product for.

[00:10:30] - [Speaker 0]
I absolutely love that side of your story there. The power of curiosity, asking questions, wanting to help. These things are as important as the technology, if not more so. And I think many industries have talked about digital transformation, and yet construction does have that reputation for slow adoption. But as you've said, they are far from digital laggards in quite quite the opposite.

[00:10:54] - [Speaker 0]
So from your perspective, what what happened that shifted and created the conditions for platforms like through, Track three d to to gain traction? Tell me more about that because it feels like it's a perfect moment for you, but but what changed?

[00:11:09] - [Speaker 1]
And, great, there are variety of factors that came into play, actually. Because I've been working in this technologies for more than twenty years now, and, like, we are right now at that golden moment for AI where, you know, technology has become accessible and powerful enough to actually create great value. And when I say technology, right, it's it's multiple technologies that have come together to make it the perfect timing. Firstly, you know, AI. Right?

[00:11:36] - [Speaker 1]
What is possible today with AI was not even possible, like, even three years ago, nearly twenty years back. So last year to this year itself, the rate of progression of AI has been tremendous. Now you don't need to train models manually. You can create very accurate models, very accurate AI models in a very, very cost effective manner. So, you know, both the speed and accuracy and the scalability of it, all the three factors get massively adopted because you have AI now.

[00:12:11] - [Speaker 1]
It's not people doing all the manual work. That is number one.

[00:12:15] - [Speaker 0]
Yeah.

[00:12:16] - [Speaker 1]
Then number two is, you know, the improvement in the camera technology itself. Think about drones with cameras or, you know, robots or even three sixty degree cameras. The kind of resolution improvements that they have gone through has been tremendous again. So what the camera can see now has tremendously improved from even one year back, actually. Last year, you look at the camera technology available to today.

[00:12:43] - [Speaker 1]
It's massive difference, and that is again one massive factor. Number three is robotics, and this is again something we are excited about as well. With the lack of people that the construction industry usually suffers with. Right? Now you have robotics, which are again becoming accessible, and technology is actually building at such a rapid place that, you know, I foresee every job site to have its robot of its own, irrespective of its shape and size.

[00:13:15] - [Speaker 1]
So it could be a 10,000 square foot retail to a 1,000,000 square feet of a stadium or a data center. I see every job site in the future or the near future would have a robot. And, again, that is one more unlock to why technology has become so accessible. So, again, all the factors that I initially talked about, that the speed, accuracy, simplicity, and cost effectiveness. Every of these factors have exponentially changed.

[00:13:48] - [Speaker 1]
Now you don't need for for example, with track three d. Right? You can set up a project in fifteen minutes. You don't need months of setup time. A fifteen minute setup, you can get started.

[00:13:59] - [Speaker 1]
You can start capturing and start tracking things immediately. No. Take the BIM model, take the schedule, do huge implementation. All of that is already gone. And people start seeing value instantaneously.

[00:14:13] - [Speaker 1]
And because it is automated, the cost benefit gets passed on to the customer. There's no or very little human in the loop possible. So all this was not even possible even one year back, let alone three, four years back. So I think that is a huge unlock, and that is what we are very, very excited about for this industry. Right?

[00:14:35] - [Speaker 1]
One last thing, I know I'm giving a very long winded answer, but one last thing I wanted to also mention is with AI, integrations now become very, very easy. You had all the silo. I talked about 200, 300 applications that people use. Right? It could be a financial system.

[00:14:53] - [Speaker 1]
It could be a project management system. It could be a ERP. All of these different systems. Irrespective of how closed world they are, today, AI makes it possible to talk to all this unstructured data and extract meaningful insights. So, again, that is an unlock.

[00:15:12] - [Speaker 1]
Right? You don't have to learn a new tool. Your all the existing data can be leveraged, and you can be created such good value that never existed before.

[00:15:24] - [Speaker 0]
And I think something else that every business is experiencing right now in every industry, and that is every tech project is under close scrutiny for ROI, the the kind of measurable impact that it it can have on a business. And as someone who's at the intersection of AI, reality capture, and progress tracking and site operations, How do you explain that real business impact to stakeholders who measure success through things like risk reduction, cost control, timeline certainty, and so many other different metrics? How do you get that ROI over to them?

[00:16:00] - [Speaker 1]
Great question, and let me answer this by giving you a practical example. Yeah. Right? So today, on the job side, if you would go and ask what's the progress to three different stakeholders, you'll get three different answers, actually. Mhmm.

[00:16:15] - [Speaker 1]
Because it's very subjective. People are eyeballing the measurements. And so if your data itself is not right, how can you improve that? That is the number one part of track three d. Right?

[00:16:27] - [Speaker 1]
We say you can't improve something you can't measure. Mhmm. And we make the measurement totally possible. Now when we say 50% of a ductwork is done in track three d, we say it's not 50% on a hypothetical basis or very subjective basis. We actually tell it's 1,950 linear feet of ductwork out of 3,900 feet done.

[00:16:52] - [Speaker 1]
And we show it to you exactly where it is as well. So this becomes very objective single source of truth for the project. That itself makes your decision making, your planning, your coordination much better. That is part one. Part two is, you know, now that you know how things are actually moving, you can coordinate much better between the different disciplines.

[00:17:16] - [Speaker 1]
Construction is like in a way controlled chaos. Right? You have multiple stakeholders, multiple trades working together, and it's about how do you plan and coordinate between all these activities in the best way possible. Now with this good objective data, you can plan things better between all the trades, all the activities that are happening, and be proactive about it rather than reactive. Because, you know, this is like practically becomes a smoke alarm rather than a firefighter that, you know, the fire is there and you are actually fighting it.

[00:17:53] - [Speaker 1]
You're catching deviations early on, deviations with respect to schedule, also deviations with respect to design, which are one of the leading cost of project overruns and cost overruns in construction industry. Those are reworks. By catching mistakes early much before they are much costlier, you can you can directly have an impact on your bottom line. Now on your question of ROI. Right?

[00:18:21] - [Speaker 1]
Construction industry, some of the builders over here make billions of dollars of business annually, But the profit margins are actually in the single digit. And just imagine, right, if we impact the project by even 5%, so that is the rework cost typically attributed to project itself is 10%. If you're able to save 5% of that, it it makes it 50% more profitable. Mhmm. So that is a kind of ROI that is technically possible with tools like Track three d.

[00:18:56] - [Speaker 1]
And that is why it becomes a no brainer for our customers. Right? So when we explain them, hey. You're getting all these tangible benefits plus the nontangible benefits. You don't have enough people.

[00:19:07] - [Speaker 1]
You can do more with less number of people. You can manage your sites better. You can have better operational visibility across your entire portfolio, and your profitability. The bottom line is directly impacted. That that makes it a very com compelling offering.

[00:19:24] - [Speaker 0]
Wow. Some big figures there. And, of course, one of the challenges I would imagine is that reality data can be incredibly fragmented, especially when we're looking at drones, scanners, cameras, and field reports. So what have you learned about unifying a day the data in a way that feels usable, repeatable, and valuable across entire project life cycles? Because although we're talking about the construction industry, data fragmentation, and data silos is something very real for every business owner, isn't it?

[00:19:58] - [Speaker 1]
100%, Neil. And, you know, I can't stress on this enough, but when we got started, there were so many point solutions. Everyone were talking about a drone solution, a three sixty camera solution, a mobile solution. Like, what we when we came in, right, what our learning point was, what are these things doing actually? All these tools are essentially monitoring your job site, and it makes the most logical sense for all these things to work together.

[00:20:28] - [Speaker 1]
Now initially, it was a technical challenge. Right? You have different pipelines to processes of this data. Then how do we get integrated it? It was not a very trivial engineering problem to solve.

[00:20:39] - [Speaker 1]
But that became our design principle to start with as well. We said we are solving we are automating construction monitoring. So that means that, you know, any data source that can technically plug in to monitor should be part of PRAC three d by default. So it could be drones. It could be three sixty cameras, laser scanners, mobile phones, robots, doesn't matter.

[00:21:01] - [Speaker 1]
As long as, you know, it's giving you a visual representation of the site, we should be able to integrate it and comprehensively track it across the life cycle as you had mentioned, Neil. Because, you know, originally, when we started, we were called construct l. But the name change to track three d was on that side because, you know, we wanted to be a asset life cycle management solution. Right from design to construction to operations and maintenance to even demolition before you again start the cycle again. We believe this reality intelligence to be the central framework that ties the entire asset life cycle management together.

[00:21:43] - [Speaker 1]
And so it has to be that way. As per us, right, you cannot have siloed solutions or siloed tools for monitoring it. It has to be one unified solution. And that hypothesis got validated very badly early on because one of our earliest customers were using only 10 different reality capture solutions. Just imagine that.

[00:22:05] - [Speaker 1]
10 different reality capture solutions, and these were only data. So that that was what prompted us to start Track three d in the first place Because they're capturing all this data, and they're storing it. No one ever looked at it ever. So this was primarily done as an insurance policy. Something goes bad, we can go back and look at it.

[00:22:27] - [Speaker 1]
We at least have the visual proof of when something went bad. And we felt there's such a huge data leverage gap between the amount of data captured and the amount of data leverage that we can we can do a very good job of bridging this gap with our expertise and technology and create this value to our to our partners and customers. So I think reality intelligence basis came from that.

[00:22:53] - [Speaker 0]
And before you join me on the podcast today, I was doing a little research on you, and I was reading that Track three d to can Track three d detects deviations and delays, and it also changes how decisions are made on-site. So how do you see that reshaping roles, accountability, and collaboration across everyone from contractors, engineers, and and project owners? It feels like some big changes here.

[00:23:20] - [Speaker 1]
Absolutely. Now I'll give you again a practical example of this so that it becomes easy to visualize. Right? So one of the projects that you're doing is a large airport project. And the superintendent over there was managing at one phase the sprinkler heads.

[00:23:36] - [Speaker 1]
But the trade partner who was doing the sprinkler heads comes and tells, hey. All the sprinkler heads are installed. Please release my payment. He immediately goes into track three d and says that, you know, hey. Something is a mess.

[00:23:49] - [Speaker 1]
Track three is showing it's 98% complete, and it's showing one ninety six out of 200 are complete. That means four Sprinklr heads are missing. Now he quickly opens the platform, and he can practically see where those four are missing as well, But the system exactly shows it showed what is installed, what is not installed. Now imagine without practically what had to be done was someone had to walk the job site just spotting each of those sprinkler heads. So 200 of them across the entire structure.

[00:24:21] - [Speaker 1]
Now if you're taking 10 levels of the airport, you're talking about 2,000 sprinkler heads. How manually intrusive intrusive it is and how impractical it is for people to go and say. And imagine that, you know, they had closed the ceiling. It would have been even more difficult to track that. Then they would have to remove the ceiling panels and then look at it.

[00:24:43] - [Speaker 1]
So I think that became instant practical value. The other thing on deviations that you talked about, I'll give you one more example. The same project, there was a duct installed, and the system was showing a location where a duct is installed. But as per the design, the duct was not supposed to be over there. So there was an error in installation.

[00:25:06] - [Speaker 1]
So you could detect it much early on and rectify it much early. That means the cost associated with the rework drastically reduces. So say you had done the ductwork and then you had done the insulation, then the connections, and then realize, oh, no. This was not even supposed to be here. The cost of rectifying it becomes much larger.

[00:25:26] - [Speaker 1]
So this early detection and proactive management of the job site almost in a near real time basis is something extremely, extremely valuable, and you cannot stall this problem by having more people. Like, you may have five people on job site just to manage this, but it's for people because, you know, we are not efficient in measuring, tracking everything, whereas AI is, like, super efficient in actually managing this. So that was a huge unlock for us. These use cases, these stories that we see keep hearing, right, I believe are extremely, extremely valuable.

[00:26:06] - [Speaker 0]
Yeah. I completely agree with you. And one of the things that I love about listening to you today is you're providing very practical examples, relatable examples that people can just visualize even though this is an audio podcast. And if I was to ask you to look ahead, are there any other future scenarios that might excite you, whether it's self correcting schedules, predictive risk models, digital twins adapt in real time? What what excites you?

[00:26:32] - [Speaker 0]
This there seems to be so much scope and so much opportunity here, but I'm curious what excites you.

[00:26:39] - [Speaker 1]
Absolutely, Neil. And I can go on hours on this, but let me keep it concise. So the number one thing is what is possible with AI. Right? So today, we are doing production tracking and deviation tracking.

[00:26:53] - [Speaker 1]
These are the first starting points. But say production combined with your manpower data can unlock productivity rates, which can again be such deep insights because you can now start planning your activities much better. You can do what are scenarios. Like, you know, today, track three d is already doing this. It's telling you that, you know, this was a planned.

[00:27:18] - [Speaker 1]
This was the actual. But if you go at this rate, you're likely to be five days behind schedule. And probably you should add 10 more people or add this machinery on-site so that you can cover it and, you know, make it five days earlier. But AI agents unlock this value by connecting it to different data systems. Can connect to your inventory management system.

[00:27:41] - [Speaker 1]
It can connect to your manpower system, your project management system, and the value that it's unlocking already is, like, tremendous. This is what we are truly excited about, and 2026 will be about making these more and more integrated product, more automating more of these workflows, and all through agentic workflows. So there'll be AI agents almost for every role. QAQC, there'll be an AI agent. Scheduler, there'll be an AI agent.

[00:28:12] - [Speaker 1]
Cost estimation, there'll be an AI agent. So we'll unlock more and more agents who can be partners to our customers and partners, basically, who are working on-site and take away all the tedious manual work that they generally don't enjoy doing and make them super efficient, making them focus on what they really love. So exciting future ahead. 2026 road map is especially with AI agents and what it can unlock. We are we are so passionately excited about that.

[00:28:47] - [Speaker 0]
Exciting times ahead indeed. And a question I've gotta ask, especially for the IT people listening and, people concerned with protecting information, etcetera. As AI inevitably becomes a bigger part of construction workflows, how do you think about trust, governance, and balance between automated insights and human judgment, especially when projects involve millions or, in some cases, even billions of dollars in investments? How do you see this?

[00:29:17] - [Speaker 1]
No. And when we got started, right, we started working with the largest construction companies in The US. And, obviously, the security and governance requirements were really, really high. But first things first, need to have all the security policies in place. For us, that included SOC two, type two, ISO, GDPR as well.

[00:29:41] - [Speaker 1]
Yeah. We said, you know, at the minimum level, we should have all the certificates because we are dealing with enterprise projects, and these projects actually run into billions. Number two, what was important was generate the trust around AI. And what we are using AI for? How are we using AI?

[00:29:59] - [Speaker 1]
How are we building our AI? And what policies do we use? Especially, like, training of data becomes very, very important. We tell our partners and customers that, you know, we do not use your schedules, your design, your models for actually training our AI. AI has already auto evolved to certain level that, you know, we don't need to use this data unless we have your explicit permission to do so.

[00:30:24] - [Speaker 1]
That again creates trust. I think the main thing about trust is, you know, being open and telling exactly how are you actually working. So what we did initially also was, you know, not only show the product, but we showed the background of what happens as well. How our AI engine is actually working, How it is getting trained? How it is actually able to predict?

[00:30:46] - [Speaker 1]
And to your second part of your question, Gagnil, we believe that AI will always be an assistant. It will do majority of your job, but the human in the loop is what actually drives those decisions. So AI may give you an insight that, you know, you are running behind on schedule on this thing, and it might give you prescriptive suggestions that, you know, doing this based on my thing, I believe will actually create value. But then we leave it to the human judgment to act upon those insights so that, you know, because of their experience, their know how, they are the best placed in coordinating, communicating, and actually driving those results. The way we look at AI is, you know, a very simple example will be Iron Man and Jarvis.

[00:31:38] - [Speaker 0]
Yeah. So

[00:31:38] - [Speaker 1]
Iron Man is a superhero. The construction folks are the superheroes, actually. This is what makes them more efficient. So we we just plan to be that. Right?

[00:31:49] - [Speaker 1]
The Jarvis to a superintendent or the Jarvis to a project manager, Jarvis to a field engineer.

[00:31:56] - [Speaker 0]
You had me at Jarvis. Incredibly cool what you're doing here. And we've only scratched the surface of some of the incredible, incredibly cool tech that you're working with here. So for people listening that maybe wanna dig a little bit deeper, find out more information about anything we talked about, and also keep up to speed with the latest developments and things you're gonna be working on in 2026 and that road map that you mentioned. Where would you like to point everyone listening?

[00:32:22] - [Speaker 1]
Linden would be a great page to come in. Linden@track3d,track3d. And you can always mail me. I always am still super curious, eager to learn, eager to have conversations, and you can mail me at nk@track3d.ai. So happy to connect, and thank you so much, Neil, for having me.

[00:32:45] - [Speaker 0]
No. Thank you. I'll be adding links to the web page as well and your LinkedIn page to make it easy for people just to send you a quick message. And I just love learning more about what you're doing here, how you've became this leader in reality intelligence, and in doing so, revolutionizing construction monitoring with cutting edge AI driven technology. But I think more than anything, what really brought it to life was the practical examples that you delivered there.

[00:33:13] - [Speaker 0]
And for people listening that the beginning of an AI journey or thinking about how technology impacts their business, to hear these practical examples, I'm sure, set off so many different light bulb moments around the world. But just thank you for taking the time to sit down with me and share that with me. Thank you.

[00:33:29] - [Speaker 1]
Thank you so much, Neil. It was really fun having this conversation with you.

[00:33:33] - [Speaker 0]
So I hope you found this conversation as eye opening as I did today. And I think my guest's way of explaining construction challenges that made them universally relatable, And the examples he shared show how much value can be unlocked when data becomes clear, connected, and usable. And Track three d, they it is proving that reality capture and AI, they're not just abstract ideas. They are tools that can reshape coordination, timelines, risk, and accountability, and do it in a way that teams can just feel the benefits of from day one. And I think it's also a reminder that innovation often comes from stepping into space with curiosity rather than long held assumptions.

[00:34:18] - [Speaker 0]
And I think the story behind this company where they they too were outsiders and and brought a fresh perspective to the industry that helped them spot gaps and also building trust on job sites and creating solutions that genuinely serve the people that are doing the work. But over to you, what aspects of the story resonated with you today? Where do you see reality intelligence reshaping your own projects or workflows? Love to hear your thoughts. Tech blog writer outlook.com.

[00:34:49] - [Speaker 0]
Techtalksnetwork.com. You'll find thousands of interviews just like this one. And don't forget, you can also follow me on LinkedIn, x, Instagram, just at Neil C Hughes. But that's it for today. So thank you as always, and I'll be back again real soon with another guest.

[00:35:06] - [Speaker 0]
Bye for now.