The Road to Optimization

Podcast Transcript 

Sarah McGuire: 

Hello, concrete revolutionaries, and welcome to the first official episode of Building Better with AI. I’m Sarah McGuire, a VP of Business Development here at Giatec. And for the next eight episodes, I will be diving deep into various topics related to the transformative power of artificial intelligence and how this is impacting concrete and optimization today. Today, I’m joined by Dr. Aali Alizadeh, the Co-founder and CTO of Giatec. He has his Ph.D. in Concrete Nanotechnology from the University of Ottawa, and he is a 40 under 40 recipient. I have had the privilege of learning from him for nearly a decade, and I’m thrilled to be here with him. Today, we’re going to be getting into problems that are in our industry that are worth solving with AI and what we foresee to be the biggest challenges on the road ahead. Aali, welcome to the first episode of Building Better with AI. 

Aali Alizadeh: 

Thank you, Sarah, for having me. It’s a pleasure to be on this limited series with a focus on the concrete production and concrete producers. 

Sarah McGuire: 

Yes, I am very excited about this, and I’m not going to call you Dr. Alizadeh for the rest of the podcast because I know you too well, and that would be very weird. But we have podcast episodes from the past that discuss the story of Giatec, so I’m not going to go too into that today. But I do want to run through a quick summary and just find out from you if I’ve summarized as well. So you and our CEO, Dr. Pouria Ghods, both completed your Ph.D.s here in Canada in concrete matter, and you wanted to stay in Canada instead of going back to your home country. And instead of going into research or academia like most people would do, you two decided I’m going to start a company because you saw that what you could actually solve in the industry would be really amazing, but you wanted to make sure that it left the world of research and academia. But that company started 13 years ago, and I’m really interested to hear about what you thought the company was going to be back then because today we have nearly 150 employees. We’re working in over 85 countries. We’ve been one of Canada’s fastest-growing companies for five years in a row, we were the first in the entire world to deploy AI in the concrete industry. We’ve run numerous Best of Ottawa Business Awards, Employer Excellence Awards, Best Canadian Business Awards, and the list goes on. How does it feel to hear all of that out loud? 

Aali Alizadeh: 

Yeah, in hindsight, to know, we would’ve not expected or imagined to be here one day, and we just had one big vision, and that was revolutionizing the concrete industry, the two of us out of school. We had job offers in academia, but we couldn’t just settle because the gap was so big between what we were doing at the academic level and the industry challenges. And at that time, bridge collapses were at the top of the news, and we couldn’t just sit and see that. And so we thought, okay, we have to do something about this and bridge the gap by bringing our knowledge to the industry, but we would’ve not imagined that we will one day be able to cover everything throughout the lifecycle of concrete, from concrete production to delivery and concrete placement. And even after that, while the concrete is in service with our technologies, we just had one simple idea on how to prevent these structures from collapsing and detecting those damages early on. 

And we developed a few products to look at the concrete quality and concrete inspection, and that was the early days at Giatec. And working out of a couple of cubicles here in Ottawa, it was a very fun time. And if I actually go back to the original business plans that we had, the dream was to get to 3 million in revenue, and that was it. And now in hindsight, that was too small to be able to revolutionize the concrete industry; you have to think big. And along the way, we learned this through the development of various types of products that are addressing bigger pains every step of the way. We learned that there’s a bigger pain, and to be able to change the industry, we have to address that. And it wasn’t until seven or eight years ago when we developed SmartRock, our flagship product, that we hit on a big pain point in the construction industry, and then the rest is history. And we can get into that too. 

Sarah McGuire: 

And when I first joined Giatec, the SmartRock wasn’t even here yet, and the first iteration of SmartRock actually wasn’t even cloud-based. It was just a simple sensor. 

Aali Alizadeh: 

It was mobile-based. 

Sarah McGuire: 

It was mobile-based; there was no cloud technology. We weren’t thinking big data, nothing. That wasn’t at all what was happening there. But within a couple of years, obviously, newer iterations came out. And I just remember in 2017, about two years after the product launched, I kind of remember just a spike in a quick uptick in adoption, but I don’t really recall why. I guess maybe I was too in the weeds. I was so customer-facing. Do you recall a moment in time after the sensors were launched where you realized Giatec is actually becoming this global company that people are watching and we’re onto something big, and it’s about to take off? Do you have that memory? You start from a startup where, for those that don’t know, I mean, I joined very, very early on, and I remember just sharing a cubicle with three people at one point because we were growing quickly. But do you remember a time when you realized, wow, Giatec is getting recognition? 

Aali Alizadeh: 

No, it wasn’t until just a few years ago when we were able to see that customers or even prospects online are debating and discussing Giatec products. When you see that, then you realize you’ve made a big impact. I think I remember there was a post that someone asked, “Have you seen these sensors?” And then other people responding to it without Giatec being involved. And when you see that debate, it shows that you are now relevant to the industry. 

Sarah McGuire: 

I agree. I have a couple of memories that stick out to me. We’ve seen, you know, that when people are having conflict with you or all of a sudden there’s a small controversy about what you’re doing, you’re obviously doing something right. And we’ve had quite a lot of people that will be left unnamed kind of coming onto our LinkedIn and trolling us a little bit. And you’re wondering why, what is possibly, why are you doing this on a Saturday? Go enjoy your time with your family, but it’s because we were disrupting something. So I want to talk a bit about your transition to AI because I remember when we were sitting around a boardroom in 2018 talking about needing to hire data scientists for AI, and we were kind of starting to have those conversations. Then we launched Roxi, our first official AI, in 2019, but before that, obviously, work had to be put into actually creating this algorithm and creating who she is today. Do you recall a moment where you went, we’re going to now focus on AI? 

Aali Alizadeh: 

This is when we started deploying smart sensors in a wide range of projects and collecting hundreds of thousands of data points from these sensors. We realized that we are onto something big here. This is data coming from projects in different geographical regions, different mix designs, different ambient conditions, and things like that. And we knew that with big data coming in, you can train an AI algorithm. This is basically an essential component of developing any algorithm; you need to have big data. So we engaged one of the top institutions in the world, Mila – Montreal Institute of Learning Algorithms, and worked with them on the first generation of Roxi, which was simply trained to look at the concrete temperature and detect the pouring time. Pouring time is an important parameter in calculating the strengths of concrete based on the maturity concept. And we didn’t want people to make human error by selecting the wrong time, or sometimes they go back and select the time later, but we wanted to see if we could train that algorithm. 

And it was successful. It’s a very successful, simple problem to solve, but it was actually a very interesting and fascinating algorithm to be developed for Roxi to within seconds take the pouring time for you as a user. And that was exciting enough for us to say, now we need to develop in-house capability. We started hiring AI researchers and worked on the next generations of Roxi to detect anomalies and mix behavior and so on and so forth to add to the capability of this algorithm so that users always have this powerful suggestive algorithm that is giving them alerts and indications of something might be wrong and bring them peace of mind, and we can discuss that. But that’s been the approach for us on the AI side. 

Sarah McGuire: 

And so, when you first brought AI into the industry, it was really to create more validity behind the technology that we already had. It was to make our users feel that they could trust the results coming back to them because we were also taking that extra step of removing any human error that could happen. 

Aali Alizadeh: 

Exactly. 

Sarah McGuire: 

But then you guys invested deeper, and we have always been a company that has looked at a problem and figured out how we can solve that problem before creating a solution. So at first, Roxi was there to solve a small problem within a bigger product that we had, but then Roxi grew to be solving really, really big challenges in the industry. Tell me about that shift when you went from doing things in the backend to saying, “Wow, we’re going to solve a real problem here.” And yeah, just talk me through that. 

Aali Alizadeh: 

Yeah, so the second, I think that as soon as we started Roxi with the pouring time detection, we thought, “Okay, can we train Roxi on detecting mix performance?” And from the surface, it looks like a simple problem. If you have tons of mix designs with tons of data related to the performance of those mix designs, you would think that I can train an algorithm to predict the performance of a mix design. And at the time when we were developing these sensors, we thought about can we use that kind of approach to validate the maturity calibration? Because for maturity calibration, you develop a mix, you break cylinders, and then it’s an equation that you basically put these results in it and you get the parameters that are used in the maturity equation. But like any other equation, garbage in, garbage out. So we wanted to add a double safety level here by collecting a mix design from the user and predicting what the strength’s going to be and compare that against the calculation coming from the maturity concept. 

And that went really well. Actually, that was very successful. We had thousands of mix designs collected from our concrete producer partners who were reselling our sensors. So they shared their data with us, and we used that data to train Roxi with this new capability. And during that process, we learned about a bigger pain compared to what we have been already solving. And these producers, as we were collecting the data and the discussions with them, realized that they are overdesigning their mixes by a significant margin, some of them up to 30% overdesigned. This was an odd challenge for us. And why would you overdesign your mixes? And with so much data and capabilities that are available these days with sensors and AI, we thought we want to change this big problem. And this is not only financially a big challenge for concrete producers, but environmentally adding to major contributions to the CO2 emissions that our industry has. 

Sarah McGuire: 

So there you have a huge problem, way bigger than probably what we were solving before with just sensors. Now coming into a bigger part of the equation, overdesign is a huge issue, and we can talk through why that’s actually happening in the industry. There’s a variety of reasons, but the concept of optimization then comes into play. And optimization is not a new concept. Companies have been optimizing their mixes for decades, but they’re just doing it in a very different way than what newer age technology is now allowing, very similar to sensors. Before the first project to ever be built with maturity sensors was the CN Tower in 1976, it completed with three-day stripping times in the seventies, which is wild. But at that point, it made sense to hire five to 10 people to just run around and collect all that data, whether it was hardwired or not, because they had the time. It’s a mega project. So optimization is something that is happening to a certain degree as well, but the ability for it to happen on a wider scale wasn’t there before. 

Aali Alizadeh: 

And concrete producers have tried optimization. You talk to them, and they say, “I tried to optimize my mixes because that’s adding a lot of pressure on their bottom line.” And they’re highly motivated to do that. And every time they do an optimization, they’ve told from their experience that something goes wrong again. And they have to do overdesign because their load breaks on the job site and their weather changes, and they cannot predict it. And because of that, they’re naturally forced to add more cement than needed to their mixes. 

Sarah McGuire: 

You can only optimize as much as your testing is going to allow. And of course, Giatec, we’re trying to solve a part of that problem with sensors, but we know we don’t have our sensors on every single project in the entire world. Today, testing was a big, big aspect of why this problem was worth solving. But let’s talk through some of the other ones. So I want to run through some of the numbers on profits that have just kind of come out of some of the research that we’ve done in the last few months, or based on the last NRMCA report in the last 12 months, the selling price of concrete has risen by almost 30%. We know that we’re in a crazy time of inflation in the US and Canada, both are experiencing that, but we’re not experiencing 30% inflation across the board, although sometimes it feels that way when I’m buying my groceries. 

But aside from that, you then also have profit margins are decreasing by a whole percentile, which in this industry when you’re averaging about five to 6%, an entire percentile is a lot. So profits is something that we really need to spend extra time on, especially as we’re going into 2024, 2025, there’s talks of recession. We’ve been talking about it for a year now. Of course, it’s never going to happen the same way that the 2008 crisis did, but we’re set for one, and people are going to be spending more time on their bottom line. So let’s talk about how optimization, why should optimization be something they prioritize? Now 

Aali Alizadeh: 

You actually touched on a very important point. The material cost is going up significantly, and I think over the past five years, the material cost has gone up by 25%, and that’s driving most of the increase in the cost of concrete. Material is adding up to about 60% of the cost of concrete, and almost half of it is coming from the cement cost. And the overdesign of concrete is mainly driven by adding more cement. So you can imagine that slight change in the amount of cement can significantly add to the cost of materials. Hence, to maintain your margin, you have to bring the cost of concrete up. And for an average producer in general, the profitability or profit margin is about three to 5%. And on $140 per cubic yard of concrete, this is not much. And if you look at the cost of cement, the overdesign translates to about $10 per cubic meter or cubic yard of concrete. 

And that’s almost equal to the profit margin that these producers have. So in a way, they are halving their margin or profit margin by overdesigning the mixes, or if you look at it the other way, if they optimize their mixes, they’re going to double their profitability. So with the cost of material going up, the skilled labor, that is going to become less and less in our industry, the optimization through AI, AI-based approaches, and sensor-based approaches is going to become even more important. And next year, I think with the recession coming up, I think this is going to put a lot of pressure on the producers to bring their costs down or bring their prices down. So to maintain their margins, they have to find solutions on optimizing their mixes, which is going to be a big challenge. 

Sarah McGuire: 

Now, as we said, optimization, it’s not new; companies have been doing this for decades, some very successfully. Some have very strict goals that they follow, but also these are larger companies. They have more resources, they have more people, they have more skilled labor that most people are struggling to find. We’ve talked about. So why do we think that AI now is going to make a big change in this? Because of course, bad testing, we can’t snap our fingers tomorrow and fix that. We know that tests don’t always go the way that they should. Even when sensors are used, sometimes those things, they are the way they are. But AI is now coming into the space and making it more accessible. Why is now the time for people to focus on this? What can AI do that we just simply can’t do on our own? 

Aali Alizadeh: 

With tons of data coming in from your batching system, dispatch system, your QC software, your material suppliers from cement and aggregate suppliers, it’s almost impossible for a human to be able to analyze all of that data in real time and to make decisions that are relevant to the day of operation. And instead of waiting for getting all the results back and analyzing the data later to do optimization, you need to do real-time changes. And if you base your data or your decision based on the data that is collected over the past months and you make a decision based on that, your cement might have changed by then. Your aggregate source may have changed by then, and so it’s too late. And if you do optimization for that, you may actually go wrong on the performance. So it’s very important to analyze data in real time as they come in. 

And the regular softwares are not capable of doing that. You need to have AI capability. And the AI algorithms have advanced so much in the past few years, and you see actually ChatGPT emerging because the algorithms are more sophisticated and things that have not been possible in the past are now possible to drive conclusions. The anomalies, to detect changes in the way that you can pinpoint exactly what is the source of optimization or overdesign that you need to optimize, rather how can you improve consistency? This is another challenge, and it’s not necessarily overdesigning mixes. There’s a lot of inconsistency in the results coming back because of batch changes or yield issues or things like that that can be easily captured by AI algorithms and correct that so that you decrease your variability and increase the mix consistency. And that at the end of the day can help you optimize even more. So these are challenges that with the sophisticated AI algorithms that we have these days can be easily addressed. And on top of that, the data that is collected from all of these data sources, whether it’s batching, dispatch, QC, can be through cloud solutions collected in one place. In the past, we had a lot of on-prem solutions; access to data on, say, your test results were on a piece of paper, so things were not centralized, and data wasn’t as easily accessible. So that’s another change that I think is going to help the AI-based driven optimization. 

Sarah McGuire: 

Right. And we are now in a time where, had we tried to tackle this issue five, even three years ago, I think that’s something that even the pandemic may have spearheaded a little bit, was the importance of having things on the cloud so that people could operate their plants from home. We saw more and more of that, and although they were trying to solve a different issue at the time, they’ve now opened themselves up to a lot of opportunity because with everything sitting in these places, we can actually access it and use it to be more impactful. Although we’re not here to talk commercially about our products and what we’re doing, that is what SmartMix is. It’s an AI-powered platform that is bridging that gap and bringing all the performance data that you need across your concrete operations to actually make economical decisions quickly. 

And the reason why AI is so important in that is because it’s just super speed processing. It would be physically impossible for humans to actually process that in that same time period. It’s not replacing the departments that are there, but it’s bringing together things that we may not have seen before. For me, that has been something that’s been very interesting is this industry has a huge pool of labor that just has that gut feel because they know if you’ve been working in this industry for 20 years and you’re seeing concrete poured, you can tell the difference between a three and a five-inch slump pretty regularly just by looking at it. But the reality is that the newer generation coming in, it’s going to be harder and harder to find and train those people. And the demands of the industry are also demanding something so much bigger. They’re not demanding the one or two people that can come on a job site and fix your problem today just because they have the experience, they need 10 of those. And we can be using AI to kind of bridge that gap, not necessarily dumbing down the workforce, but super speeding the processing power to get the workforce into a more impactful place. 

Aali Alizadeh: 

And free up their time so that they can spend more of their time on more important stuff. Exactly. And this is empowerment and enablement, and I think we’re at the right time. Maybe 10 years ago, if you had said that to a concrete producer that AI is going to be able to do this for you, they would’ve not believed it. But today, I think they see that movement across all industries, and concrete and construction is no exception. 

Sarah McGuire: 

And I think there’s this concept too of, oh, we’ve seen this a lot in the news with OpenAI for example. There’s a lot of companies, OpenAI or ChatGPT, however you want to call it. There’s been a lot of discussion about who’s going to win AI, but that’s not really, in my opinion, the right way to look at it because that’s completely unrealistic. Somebody’s not going to go and start a company tomorrow and be like, “I’m going to win AI in every sphere that exists.” There are going to be companies across the entire world that are going to leverage AI to become the winner in their industry or the winner in the problem that they’re trying to solve. So when we’re talking about who’s going to win AI in concrete, well, there’s probably 10 other places that this can be applied really successfully. It’s not just the concept of managing our mixes and optimization. There might be something we can do with the labor pool and upskilling them. There might be something we’re using, I don’t know, our trucks more efficiently. We’re not even going into that telematics program. Procore is doing a lot of that on the construction project management.  

Aali Alizadeh: 

Exactly. Cement producers can use that to optimize the production of cement. So there’s a lot of areas, and that’s actually a very interesting point because I think construction has the largest amount of data. Billions and billions of data points are produced every day in all these job sites and all these projects across the world. So to be able to analyze that in real-time using AI is going to be a big transformation in our industry. 

Sarah McGuire: 

I’m glad you mentioned Procore, and I’m glad you mentioned all of these billions of data points. That brings us to a very interesting topic I want to ask you about. And it’s this issue of interoperability or the lack of integratable technology that we have right now. I think we were very privileged when we first came into this industry with our solution because we worked with a partner that had already been cloud-based, and all of their customers were cloud-based. And then we start going into the bigger industry, and we realize this is a step that a lot of people are working on taking to get their operations into the cloud, but that’s going to take a long time. We have a lot of companies that have it on their forefront, but to just go ahead and rip out your dispatch tomorrow for a prem to a cloud solution, that’s not an easy feat. 

We would never ask somebody to just rip it out and do that. So there’s a whole elevation that is happening in the industry. And Procore is an interesting example because when they had maybe 15 years of operation, I don’t want to quote this verbatim, I don’t know exactly, but their CEO has talked a lot about how the first decade plus was very difficult because they were trying to build a system that was going to operate on job sites using Wi-Fi and internet, but these job sites in 2001 didn’t have Wi-Fi. They had to build the starting blocks so that they could just put their own solution there. And I feel like we’ve been going through a bit of this, I don’t want to say pain, but it’s definitely been a learning lesson for us on where the industry is. And I feel like there’s this big rise to come up into the cloud, but it’s still not there. What do you think, where do you see this issue of interoperability going in the next three to five years? And do you foresee this to be one of our bigger challenges? 

Aali Alizadeh: 

Spot on. I think this is the biggest challenge in our industry. A wide range of systems have been developed over the past decades, and they are integrated into the daily operation of our user base, concrete producers namely. And to change that is not going to be easy. And that’s why our vision is revolutionizing the concrete industry. Part of that is to transform the way that things have been done. And because these are mostly on-prem solutions and they have been developed by companies that had in the past no connection to each other, even the data models are done in a way that they’re not able to be mapped easily. The way that concrete mix design was captured on a QC software was different from a dispatch or batching system. And even as simple as that, to be able to connect these together, even if you had tomorrow, all of these capabilities on the cloud, on these systems, they’re not going to be mapped easily because the way that aggregate is captured or cemented, aggregate captured in QC is completely different from that on the batching system. So we need to have an alliance in the industry players to come together and say what the industry would look like in 10 years, 20, and to start building blocks of it together so that in the future when all of us are in the cloud, we can connect and talk together easily. I think the main challenge in the interoperability of our industry. 

Sarah McGuire: 

So you think that interoperability is the main challenge because, and I want to repeat that back. I think that’s very interesting as a company like us that we came into this sphere in the last half decade and really started to build our technology. So we had the privilege of starting on cloud because going on-prem would not have made sense for us. So there is credit to be given to the companies that have been operating for 40, 50, 60 years, and they built solutions that were really amazing back then. But now, people are having bigger demands. And like you just said, this is not just a simple task of upgrading everything to the cloud; it’s completely different code. How are we going to talk to each other now? They have to rethink how they’re doing everything. And that’s not easy, especially in an industry where if you rip out software for even a day, we experience huge, huge impacts with that. So I think that’s important because sometimes as companies like ours that come out and we’re pushing change and we’re driving people to adopt new technology, there’s this misconception that we don’t have appreciation for where people are. And that’s why we’re having this discussion so that people are challenging each other and getting their step by step and making sure that we’re bridging that gap, but it is going to be a slower burn and we have to be okay with that. 

Aali Alizadeh: 

And we’re pushing the boundaries as a technology-based innovative company; that’s our mandate. Otherwise, we are not going to be able to create a bigger impact. And I think the fact that we’re not from this industry ourselves is enabling us to reimagine things in the way that they are easier to operate or more efficient. And that’s what we did actually with the SmartRock. We got into the construction industry without having any background in the actual job sites, and we just looked at the pain that they have and reimagine how the solution can be developed for that pain. And early adopters are going to pick up the technology no matter what, but over time, you’ll be proven as a technology company if you are visionary enough to look at what the industry will look like in five to ten years from now. And we did the same thing with the mobile app development for SmartRock. 

And I remember this actually. People were saying, “Oh, the smartphone, they fall and break on the job sites. You have to develop your rugged data collector for these sensors.” And I said, technology is becoming cheaper and cheaper. Even if your smartphone breaks, you’ll buy another one for a couple hundred dollars. I mean, just to collect data at that point in Android points were relatively cheap, and we were proven. And instead of developing our own rugged system that every time if something happens, we have to send the firmware updates or ship them another device delays, all the frustration would add up. And the same thing on the concrete producer side. If we are bold enough to reimagine the way that things need to be done, I think all of us, all of the technology players that we have in our industry, can change the concrete production I’m hoping in the next five to ten years. 

Sarah McGuire: 

Yeah, I think that’s a great point. And now you’ve mentioned, now that we’re talking on this concept of change, there’s a lot of fear in the industry, and I would say the whole world honestly right now. I mean, OpenAI ChatGPT was one of the most talked-about things this year. Sam Altman was the CEO is the CEO again, 

Aali Alizadeh: 

Yeah, 

Sarah McGuire: 

Very confusing month that happened there. For anyone that wants to learn about that, Google Sam Altman and hear about that whole controversy, but he was one of the most talked-about people in the world this past year. He was in the running for Time Person of the Year as well. What I find interesting is that there’s a lot of talk about AI this and AI that, but AI is only as powerful as what you have it programmed into. And as a company, we need to actually be thinking a little bit more about cybersecurity and kind of the regulation that we’re pushing forward and the walls that we’re putting up, making sure that our employees are well-trained on phishing scams, all these sorts of things. And we’re going to have an episode that dives really deep into this later because there’s a big belief that yes, AI needs to be regulated, but we’re already seeing crazy hacking schemes happen just with human power. 

So let alone what will happen when AI really starts to make a dent in that. And for every technology that’s developed for good, you always have it developed for bad as well. So that’s going to be a very interesting discussion. But then it kind of comes back to the fear of AI and there’s one of, oh, it’s going to take over everything including my job. And I think that’s a big thing that people have been the most concerned about, and studies have shown that AI is going to replace quite a lot of it is going to replace certain jobs, but it’s probably going to replace the jobs that if we were able to reallocate those resources elsewhere, we’d be able to make a bigger impact. Somebody at NCA’s convention, I don’t want to name him without asking permission to first, but he made an incredible point that people were very concerned about, are we worried that AI is going to dumb down our industry because it’s going to do all of these things for us and then we’re not going to have any view or control over it. 

But he made a very good point that, well, do you think that Excel using Microsoft Excel dumbed you down? No. It took when’s the last time I had to actually do a logarithm on paper? It’s been ages. It’s probably calculus when I was in high school, but that didn’t dumb me down because I don’t really care about how to get there. I have a calculator in my pocket now. Now I’m actually able to do something impactful with that result. But that also, that takes time, that takes change management and guiding people through what they’re now seeing in front of them. For us, one of the most interesting but also kind of rewarding experiences has been plugging people’s data in and now suddenly they’re seeing all of their data in one place and they’re seeing things that they didn’t expect to see, but they’re also seeing information that it’s a bit overwhelming because to suddenly go from having everything, all this data living in different pockets and now seeing it all together and actually processed to a certain degree with our own algorithms that we’ve put in with, here’s a way that you can save $2 a cubic yard today. 

That is really exciting, but kind of overwhelming because it’s such a leapfrog. But that’s been one of the things that has been most interesting. 

Aali Alizadeh: 

No, I’m not going to lie. I think it is inevitable for the job market to dynamically change with the introduction of technology. We’ve seen this through the centuries with the introduction of different technologies. Some industries are going to evolve into a new shape and form, and that means that the jobs are going to be defined in a new way. This is going to happen in every industry, and if you’re not on board, you’re going to be left behind. This is the truth about every technological revolution that we’ve gone through in human history. But the way I look at it is that the forward-thinking users are going to look at this as an opportunity on how to become more efficient, where I can become more profitable, how can I allocate my resources on things that are bringing me the highest return? And this is what I think our industry should look at as opposed to resisting the change. 

I don’t want them to open their eye in five years or 10 years from now and see that every producer is going to use AI and sensors and concrete that is fully automated in the production and they’re left behind. I think concrete production is going to be democratized in that sense. In the past, historically, these big producers had lots of know-how and smart and experienced QC managers. And with the technology advancements, I think this is going to be easily accessible to a wide range of producers. So competition dynamic is going to change over the next decade, I believe. And with the same way that I look at the sensors that are used in job sites and even a smaller construction companies are becoming more profitable because they’re moving so fast with using these sensors and getting data in real-time and not being relying on lab results that are delayed. 

Concrete production is no exception. The new generation of workforce I think are going to be okay with that. They have seen how AI is changing the way that things are done. For example, in their car or in their software application they’re using and their smartphone, the Alexa or Siri, how is it helping them to become more productive? They’re going to demand the same level of assistance in every place they go to work. So this is just one thing that is inevitable. And you made an example about a calculator and then people using Excel. I mean, you can go back and people were using an abacus and then a calculator. So did they become more dumb? No. People became more efficient and they used their brain power in something that was more impactful, 

Sarah McGuire: 

Furthering our industry and furthering our projects and our efficiency. 

Aali Alizadeh: 

But I can bet that at that time, there was the same debate. 

Sarah McGuire: 

Absolutely. 

Aali Alizadeh: 

I’m not going to use a calculator; that’s going to make me more dumb. 

Sarah McGuire: 

I remember being in elementary school and high school and having your teachers go, “What, do you think you’re going to carry a calculator around in your pocket for the rest of your life?” And that sounds hilarious now because I’m not even that old for that to have been that long ago. But the fact that it was, “Yeah, you’re not just going to be able to search up the answer every time you need it.” Actually, we can now. And it’s interesting to see the way that the education system has actually changed as well to being a lot more critical thinking and problem-solving as opposed to just teaching kids what they can just search up in the future. It’s very interesting how that is adopted, and I think a lot of industries have too. And like you’ve said, it perfectly, our industry, it’s going to happen. 

It’s probably not going to happen as fast as other industries. That’s a reality. We are building structures that if something goes wrong, lives are at stake and that can’t be taken lightly. But at the same time, it’s going to happen eventually. And this is the point of having this podcast is let’s start that conversation now. Let’s discuss. Let’s have that dialogue so that we can make sure that when you are ready, you’re aware of what’s happening and you don’t just blink one day and everything’s changed around you. Because that is the fear of not bringing people along on this changing journey with us of just forcing them to change. And if they don’t, we move on. Giatec has always been a company that we really focus on education. We’re very involved in the associations. We want to make sure that we’re keeping the education going so that when people are ready to adopt, it’s there and it’s simple for them. 

So that’s a very interesting point. Well, we’re going to wrap up soon here. As we wrap up, I would love to hear some of the most exciting moments that you’ve had thus far in bringing SmartMix, our AI-powered mix management system, to the industry. But of course, it’s still early days and not just even with our adoption but also with where it’s evolving to. So the successes that we’re having today are definitely not going to be that of two years, three years, or even 10 years from now because it is going to evolve. But I’m curious to hear if you have one or two stories that really stand out of, wow, this is when we had some exciting feedback. 

Aali Alizadeh: 

Sure. Yeah. So we’re still at early days of getting SmartMix to concrete producers. There are a few producers who are using our system as we speak. And it was interesting, actually, when I look at what we had in mind and when we were developing SmartMix, which is basically relying on existing data from these concrete producers, we’re connecting to their batching system, dispatch system, their QC system to collect that data and analyze it in real-time using our powerful Roxi algorithm to give them suggestions on mix adjustments and mix optimizations. And one of the things, actually, the reactions I saw from one of the QC managers, even getting all of that data in one place, she said, “I’m going to cry.” And literally, she said, “I’m going to cry.” And she explained then that in the past, I had to export data from my QC software, export data from the dispatch, and then put those together in one Excel sheet and analyze that data so that I can draw a conclusion about the performance of a particular mix on a job site for a particular customer. And that’s now possible in one dashboard, in one simple view, and this was actually, we never thought that this is a value proposition that customers care about, but having all of this data simply in one place and to be able to connect them together to make immediate decisions and conclusions was a big, big win. 

But this came with SmartMix without even us thinking about the value position of that. But on the mix optimization, the early adopters that we worked with, this is a producer that I’m not going to name, but they, as soon as they plugged in SmartMix to their systems, we were giving them suggestions on over designs that were as high as 30%. Wow. And so we said, “Okay, these are suggestions. You can take it or leave it.” And they were looking at it and one day they came back to us and said, “We’re pouring the new concrete mix design. No. Well, we were not expecting that. Wait, did they trial that first? No. Oh, dear. Okay.” So they took it at face value and they actually went, and luckily nothing happened. The concrete mixed really well. They achieved the slump and the strengths that they initially designed that mix for, with reducing the amount of cement by 30%. So these are really powerful early experiences that we’re getting, and there are thousands of producers in the world that are not going to be any different. So we believe that over the next few years, we’re going to work very closely with these customers to learn about their pain points and evolve SmartMix to a new category of software for them that you have your batching and dispatch, and then you have SmartMix, which is mix management and mix optimization. 

Sarah McGuire: 

Well, Aali, thank you so much for joining. For those that want to reach out to Giatec and learn more about SmartMix, normally this is where I would ask you, please give us your contact information. But in fact, that would be my contact information. So if people are interested in learning about SmartMix and learning a little bit more about how that can apply to you, even if you’re not set up in a way that you could plug it in today, that is okay. We have a lot of companies that we’re working with that don’t work on systems that are integrating in with SmartMix yet, but having those conversations now, discussing what they would be looking for, discussing where their current data is today, these are all really important steps. As we said, for some companies, it’s going to take a month. For some companies, it’s going to take a couple of years, and Giatec is willing to be a part of whatever journey you choose. Aali, thank you so much for joining. The next episode is going to be out in two weeks from today. Don’t forget to subscribe and share with all of your friends that are also concrete revolutionaries, and we will see you in a couple of weeks. Thank you, Aali. 

Aali Alizadeh: 

Thank you, Sarah for having me.