In the construction sector, as I said, a project manager comes and solves the problem, finishes the project, and then he is happy because he finished the project and then he starts another project. He just carries his experience; he doesn’t carry any database with him, generally. So this is a very important, big problem of the sector. We are not long-term oriented; we are solely short-term. Welcome to the Bricks and Bytes podcast. I’m Owen Drury, and together with my co-host, Martin P. Karch, we will be interviewing the people involved with transforming the construction and property industries through the latest and most innovative technologies. In today’s show, we have Aydin Ostsekic, who is the CEO of Botmore. Botmore offers AI-driven solutions within the construction industry to increase productivity and smart decision-making processes. Please join us for this exciting conversation with Aydin. Welcome to the Bricks and Bikes podcast, where we take you on a journey in construction, technology, and business. All right, let’s get this episode started.
Erynn, you mentioned that you were a civil engineer by background. And before that, or even after that, you had some interesting things happen, right? And I think this is coming out of the discussion. Sorry, before you answer that, I just wanted to tell you that it’s the third civil/structural engineer that we are talking to. Yeah. That means that these are smart people. Me, I am a civil engineer, and I like the construction sector and civil engineering. Then I made a master’s in construction management in Turkey, then I made an MBA. The more I tried to learn, the more I wanted to understand the business side of the work. This is my general education, but mainly I started in a construction company. For six years in my early career, I worked in a big international construction company in Turkey. Generally, we were working in Qatar, Libya, Saudi Arabia, and Turkey, and we were developing large infrastructure and building projects. So when I was there, I was always a curious engineer, trying to solve problems, especially during the tender preparation stage and, more importantly, maybe the planning stage.
Mainly, we couldn’t collect data from anywhere, and we tried to make assumptions using the experienced people’s ideas. Okay, they said that they know everything. They do know a lot of things, I know, but it’s a bit ridiculous because we have a big company, a billion-dollar company at that, but we are just making some tender preparation activities. We couldn’t collect the offers from our supply chain effectively, and all offers were so complicated, and we just made assumptions, assumptions, and it seemed silly.
At that point, I focused on the data, and I always tried to classify the data and create a database for the company. It was my ambition. So, in my master’s thesis, I worked on it a bit, and I tried to create a model that combines cost data and the duration of projects, attempting to make automatic risk analysis using statistical methods. It was a bit interesting because I did this as experienced people made some assumptions using their experience, but they could only see about 100 projects in their whole life. They were making assumptions that a project is very risky because it is in Libya, and so on. I tried to create a model that could define it, and if you put in some inputs, it could directly measure the risk of
Then I entered the BIM world, the building information model world, and I consulted different companies, especially in Turkey and the Middle East, about how they can use BIM in a more data-oriented way. Again, I focused on data, and I said that, of course, BIM is important, but you can put different data on this model, and you can use it all in the building life cycle and up to operation. We worked with some big airport projects, trying to carry this data in the construction phase to the operation side, which is very important and very challenging. It seems easy, but transferring is not an easy process generally. People create data in some silos, but they don’t use it effectively. So I worked on it for four years in different airports, big airports, and we solved different problems there.
And then I came to a point where we had to do more things. My wife is a computer engineer, and she’s already working in the AI side in the financial sector, doing fantastic work. When I saw her work, I realized that we needed those kinds of things in the construction sector as there were a lot of problems. So I started to focus there. Then I started my startup with more technology-minded people in Turkey, and later I moved it to the UK. Generally, I think we are focusing on the digitalization of the construction sector and the transformation of data processes.
Before Botmore came along, between the phase of you working internationally and creating Botmore, where did you decide that data AI was the area that you loved and wanted
All of the problems are mainly related to data because if we don’t talk about data, we just argue about something, but we couldn’t solve the problem. So, I always try to make solutions using data. It’s simple; when I talk about it, it can be Excel. I try to show people that data is so important and try to summarize and classify them. Step by step, I need to use more advanced technologies, first Excel, then different tools, and at some point, these are intelligent tools. I need more advanced tools and AI starting at that point. AI is just a tool. People are a bit confused about it. AI is not a result; it’s a tool. You can’t buy AI; you can use it. You can use it in your projects to make them better. It’s like Excel; Excel is a tool. People can use it differently. You can use it at different advanced levels. Others can use it as a table. But in the end, Excel provides many opportunities for you. Your aim is not to use Excel; your aim is to make your process better using Excel. It’s the same for AI. So I don’t want to oversimplify it, but it is not rocket science. Now, especially now, it’s more reachable and easier to use for many people.
You said that you noticed your wife working in finance was using much more digitized techniques for dealing with problems, and you didn’t see it in construction while you were working there. So why do you think it was that, and it is still that other industries
You have to put key performance indicators for the long term for your company. But in the construction sector, as I said, a project manager comes and solves the problem, finishes the project, and then he is happy because he finished the project, and then he starts another project. He just carries his experience, not a database with him, generally. So this is a significant problem in the sector. We are not long-term oriented; we are short, so short-term.
Another thing, maybe the most important thing, is the culture. Why is culture important? Because we are not a new sector. We are a stable sector, with a long history, and we know different techniques for how we will do our job. It comes from history, and we have a lot of experience there. Because of that, we are not open to new innovations, new techniques, because generally, we know the working solutions, and they are working. We know that. Why are we looking for better ones? Yes, we can look, but they say, “I did it. I know because it is working.” And this, of course, seems like a shortcut if you are not looking long term. When we combine them, it’s a big problem for the sector.
It’s also difficult to make a product in construction because every building is different, and you can’t just copy and paste on site. It’s not a product; every product is different if it’s a product. You are right about it because geography is changing. I think that, and maybe you can make the same project, try to do
Not that I don’t sell just one product and solve all the problems of the people. I try to disrupt the sector. It’s a big, big promise, I know that. But startups are like that; for example, Google, maybe now it is a business because it has a product and is trying to sell a product. But at the beginning, it disrupted an industry, the search industry, and it’s very important. It disrupted the data collection industry. So it’s the same for us. Now, many construction startups try to disrupt the sector in different ways. Some may be unsuccessful. We know that because startups are generally not successful. But we will try to disrupt the sector. I think this is important because we can say we are a startup at the moment.
What I like about you, Elin, is that you have a lot of experience in, let’s say, traditional construction, also international construction, which is interesting. Then you’ve gone into a technological venture, should I say. And that brings me to the next question, which is: So, like a typical business construction owner that has a traditional small, medium-sized business. Why should they be focusing on AI and data?
I think there’s a big opportunity for them. Why? Because now this technology is reachable for everybody. And it is very democratized. For example, 10 years ago, it was not possible to make some machine learning algorithm to run on a computer, but now it is so easy with the cloud. So, if you have some problems, you can solve these problems in different ways using these technologies. What does this mean? You can create a differentiation in the sector; you can create a competitive advantage for yourself. We know profit margins are not so high in the construction sector at the moment; there’s high pressure from competition. If you want to differentiate yourself, I think it is the time to make something, and AI is one of them. You can spend a bit of time and a bit of your money, not too much now, and create different advantages for your company, showing them to your customers to make a differentiation. And it will be different from them. Now everybody is preparing and offering a small business, small company thing, and giving the same kind of offers to their customers. You can add new features there. You can add new values there.
For example, you can add new values about the sustainability of this building and you can support it with the data from your company, and you can show the new solution for them, how you can make it. So, I think this is so simple: data manipulation and understanding your data can make a difference for your company.
And afterwards, you can use this data in different ways, in AI, in machine learning, or different analyzers. But I think it’s a good place to make an investment for a company because other things you can make, like differentiation, equipment investment, or big human resource investments, are not so sustainable for a company, especially with these profit margins. Okay, Aiden, can you tell us how you used machine learning or AI in your business? And then can you also tell what Botmore Technologies does? Like, to someone who completely has no idea about construction, if you can put it in a very, very simple way.
Basically, Botmore Technologies has two targets. One, we try to make your data more accessible. What I mean is, you are collecting data. Every company has data somewhere, whatever you have. We try to make it accessible for everyone because if you can access this data, you can make comments, and you can use it, and your productivity will increase. The second thing, we try to make data collection easier using different machine learning and AI technologies. One of the main usages of machine learning is to understand people’s language. So when you are speaking, when you are writing, you are creating some documents, you are creating a knowledge base. We try to summarize it, take it, label it, using AI and machine learning.
What I mean, for example, you are using messaging tools like WhatsApp, and you are sending messages to each other. We try to use a chatbot, like an assistant, which asks questions to you, takes answers from you, and then it collects this data and labels it, identifying which message is related to which questions or subjects, and it makes automatic analysis of questions and these messages. And it’s very important for us to understand this, then we can make good forecasts and estimations about the problems and the solutions.
Another thing is documents. We are creating a lot of documents, long documents for specifications, that kind of things. We can summarize it automatically using AI. And it is very, very good for us because you can find a related part of the document easily and in a summarized way. And this is very important. It saves a lot of time for the people’s lives. I think it’s very important, very valuable.
Okay, so the communication channel is interesting to me. So you say that if there is a team, a group of people who is working together on some projects and exchanging information through WhatsApp, for example, then you can implement your AI tool to help this communication to make it more effective between them. Yes, basically, it’s that. The main thing is the coordination.
People spend a lot of time on coordination because there are a lot of problems that involve people calling each other, sending messages, and trying to solve problems. In all these coordination tasks, there are a lot of errors, which is normal because we are human. Our AI-powered digital assistant solves this problem by automating coordination and providing feedback about progress, identifying critical points and bottlenecks in these workflows for you. I think the main series of our solution is that.
Aside from the use of a chatbot to collect data and help coordinate construction processes, in terms of AI and machine learning as a subject throughout the whole industry, there are other uses that could be helpful to small and mid-sized businesses. For example, visual recognition is now available. What I mean is that you can take photos or videos of your site and automatically have systems label this data. For example, they can check if workers are using helmets, identify safety problems on the site, or automatically check quality aspects like how many drills are there, how many formworks are being used at the site, and other similar numbers using AI-powered image recognition. I think this is very powerful and a very accessible technology. There are a lot of startups doing that. It works like a plugin; you add it to your video stream, set different rules, and the system automatically checks these rules in real time.
If you have a video, for example, I think this is an interesting topic and it’s very usable for small and medium-sized companies. Any others? Yes, of course, you can use AI and machine learning to automatically enrich data if you have it in various formats, like Excel or different silos, such as cost data. This is very useful because even though you already have this data, you might not be able to analyze it effectively due to errors or mistakes. AI can help you create a better database, and you can make more effective analyses on it. This kind of table optimization or using machine learning on your tables and databases can optimize them and make them more useful for your operations.
Regarding companies that still use paper and handwritten notes for site records, OCR (Optical Character Recognition) technology can help enhance their operations. OCR technology has been used for a long time and works very well. It can convert handwritten text into digital text, allowing for easier organization, analysis, and storage of data from handwritten notes.
It’s an advanced algorithm already working. So you can just use different suppliers of this technology, and you can easily convert your paper documents to digital formats. I guess what I’m trying to say or get to is that even if you have an old-school business and you’re worried that you can’t jump on this technological revolution, the fact is that some of the oldest businesses all the way to the newest can benefit from improving their data strategy.
As for how the industry changes, it’s possible that we’ll see 15, 20 or more software products in construction that incorporate AI tools to assist professionals like structural engineers in their day-to-day activities. AI is interesting in that it initially may not contribute as much as expected, but as it learns patterns and usage, it becomes more useful.
For example, if you’re a designer using a tool like AutoCAD and you have an AI tool working in the background, it tries to learn how you design using AutoCAD and observes your moves. It can collect data from different people and start to make suggestions. We already see this with word processing software making automatic suggestions about word usage. It could be the same for design, where AI can make suggestions to help improve your work.
And then you like it because it makes suggestions, and some of them work, some of them don’t, but you can select them. When you approve some suggestions and reject others, you teach the system what is better and what is not. Over time, it will automatically make suggestions about your design, similar to how PowerPoint makes design suggestions when you add pictures. As you use specific objects or items, it will make assumptions or suggestions for you. This will continue to improve, and while it won’t take your job, your job will change.
As for training AI to run a business, it’s only a matter of time. If AI can design things and there are rules for running a business, it could potentially stay on top of various tasks. However, it may not achieve this in every situation. If you’ve played SimCity, you know that there are rules, and AI can solve SimCity or play chess very well. But in the real world, human relations are not always logical. We sometimes make unwise decisions or act foolishly, and AI can’t predict these unpredictable actions from humans or any entity.
So when the AI algorithm encounters unexpected or illogical human behavior, it struggles to determine if something is right or wrong. You may have heard about the Twitter chatbot that was designed to learn from people and answer their questions. However, the chatbot eventually started to adopt extremist beliefs because people taught it both good and bad things. In that case, it became less logical and more of a negative influence.
This highlights the fact that AI cannot fully replicate human behavior, and creativity remains crucial. It’s essential for humans to have their unique place in the world because we can handle unexpected situations and adapt to a variety of conditions.
Yes, currently we have many apps that we use in our daily lives, such as paying for parking or managing other tasks. These technologies help to streamline our lives, but they cannot replace the full range of human capabilities and creativity.
And I find it so many times frustrating that there is a set of basic rules that the company providing the service follows. Sometimes, when you want some variation, it’s not possible to achieve that. This is annoying because you end up with a product or service that’s not exactly what you wanted. And there’s nothing else on the market, or you can’t buy what you want because that’s what is easy for the providers to offer. Yes, these are the hyperparameters for their data collection and product strategy.
Aiden, what’s your opinion? I read a few books on AI. A good book is by someone called Moqadar, a book called “Scary Smart.” Have you heard of it? Yeah, it’s very worthwhile reading, but I almost get the impression that I’m not sure if this is the message he wants to come across in the book, but AI is fully capable of replacing humanity at some point in the future. What’s your opinion? Mainly, as far as I can see from a more practical perspective, because I’m generally implementing solutions.
Now, at the moment, as far as I see, it doesn’t happen because AI is mainly using data to make predictions, and this is not everything for human beings or a match for human behavior. It’s very different. Yes, AI has some different features like NLP, which is about language, vision, which is about sight, and voice detection. They are taking different functions of humans and copying them. And there are some cognitive aspects to it. But with this technology progress, we couldn’t exceed human capabilities.
There are different works, research, and development going on, more in neuroscience. This is a totally different area, and I’m not an expert in it. But this research tries to copy human brain functioning using different technologies. AI is totally different from that research and development. And it can go there. But now, using the technologies we have at the moment, we are not going there. AI is just trying to copy some features of humans and just copy. So it can’t exceed our capabilities. It couldn’t understand different nuances.
So, because of that, I believe that with this technology progress, it seems possible, but of course, different technology can come and do that. I guess the good news for the people listening to this is that it’s unlikely that they will experience AI robots completely overtaking their jobs, taking their businesses, and leaving them homeless on the streets.
I would love to give mine to someone, to some bot. That would be nice. What is the most exciting AI thing that you’ve seen in the construction sector or you see coming into the construction sector? Robot technologies are something people are working on a lot. If we are talking about the future, robots and robotic arms, basically supported by AI, are learning the processes generally about construction. So they will optimize construction processes. And it seems interesting because they will do a lot of jobs. They will do quality checks. They will do, for example, different construction tasks, like painting and various other works. It’s interesting, and it’s coming in the future.
And for someone, if someone’s looking to implement an AI strategy in their business, specifically in construction, as this is the topic we’re on, what would you recommend their first steps are? First, digitalization is critical. Everybody should complete the digitalization stage. We’re talking about paper.
If you are still using paper or have your data in different silos, first create a central database for your company and digitize everything. This is very important. At this point, you can create a strategy for how you will manage this data. Personally, I don’t recommend going directly to AI. First, collect data and understand your data. To understand your data, you need to use it, for example, in dashboards. Dashboards are important for different professionals like civil engineers, project managers, etc., since different data is important to them. You can create your dashboards using business intelligence tools like Tableau or Microsoft tools. When you look at these dashboards, you understand the importance of data as it relates to your daily business, and this is crucial.
In other words, you can consume AI products more effectively and more understandably when you have a good grasp of your data. If you just take an AI tool and try to use it without understanding the importance of the data, you might say, “Oh, this is not working.” But it’s not working because you don’t need it yet, or your maturity level isn’t there. You need to understand the importance of data and how you will consume it. Then you can start asking questions about your data.
You will ask questions relevant to your role in the company. If you are a designer, you will ask about design. If you are a project manager, you will ask about project management. Then you try to find the answers to these questions. There are many tools to solve problems related to data, but marketing tactics often encourage people to buy AI-powered solutions as a miracle fix. However, this is not possible; AI doesn’t solve all problems instantly.
First, you should understand and create your AI strategy. By “AI strategy,” I mean working with technical people from the IT side. These professionals are widely available. You don’t have to hire them full-time initially; you can find freelancers. But first, create a good data pipeline for your company. This is very valuable and not too expensive. You will see that this data is useful because when you start to look at your dashboards and tables, you’ll understand the importance of the data. You might realize you always look at the same thing and wonder if it can be optimized. This question will change everything and take you to another stage. It could be rule-based, or it could be AI, but it will make a difference for your company.
Otherwise, you just spend money on AI without making a long-term strategic difference. So, the first step is to take baby steps, and that’s important.
It’s essential to recognize that just having all your projects in digital form doesn’t necessarily mean you have useful data. The first question is about organizing and classifying the data so it can be utilized effectively. At this stage, it often comes down to hiring someone to help you understand what data you should be collecting and how to make it useful.
It seems likely that many construction companies will need to hire data analysts to digest and make their data work for them. A lot of problems in the construction industry result from a lack of useful data or people not using the data in the way it should be used because it’s scattered or disorganized. This often leads to valuable information being stored in a project database that doesn’t make sense to anyone and eventually gets left on a computer, unused.
So, the key is to understand how to collect, organize, and utilize your data effectively, which may require the assistance of data analysts or experts who can help you optimize your data strategy.
Ogun emphasizes the importance of understanding the definition of useful data. Many people collect data and store it on their hard drives, thinking they have data. The main question is whether they use this data for their daily business. Often, the answer is no, because they don’t know how to use it effectively.
To address this, focus on key performance indicators (KPIs), which help determine the types of data that can change your daily business. You know your daily business and challenges, so when you look honestly at your problems, you can identify the data needed to address them.
Business analysts can help, but they are not magicians. They won’t know everything about the construction sector or your specific business. To get the most out of their expertise, you need to guide them, explaining the data and information you need. This is not just a technical issue; it’s a matter of understanding your business and its requirements.
In the case of Qantas Reveying, data is collected through previous projects they work on. When they send out to get prices for projects, the data comes back in messy formats but with rich information. Part of the work they’ve been doing with Aiden is getting that data into a usable format that can be applied across multiple projects. Standardizing the data is indeed one of the key steps in the data science process.
Eventually, the end goal with that data would be to predict or produce pricing models for future construction projects before tender prices come in or before they put cost plans together. While this may not be revolutionary, it aligns with Aiden’s suggestion to take baby steps. They try a pilot project first, see how it works in the real world, and then look at advancing the technology further.
Aiden and Owen have recently applied for a grant to explore how the data could be used to enhance the adoption of sustainable technologies in construction projects. While the outcome is uncertain, trying new approaches and experimenting with the data is essential for progress. Collecting and standardizing data is a crucial step in the process.
On the technical side, cleaning the data, enriching it, and combining it to create a single source of truth is critical. In the construction industry, it’s essential to create a common data environment because data sharing often involves non-standard formats like Excel documents. By standardizing data collection and creating a common data environment, it becomes easier to manage building data throughout the building lifecycle.
The main goal and future of the construction sector involve understanding the impact of design on various aspects such as carbon footprint and operational costs. By collecting data and using algorithms, it’s possible to better manage the building lifecycle, which is crucial for sustainability and cost management. Construction is just a small portion of the overall process, and there’s a long lifecycle to consider.
Of course, there’s a bigger picture that may involve government and other factors. However, for a small company, it’s essential to start somewhere and solve problems internally. By creating value for customers and offering unique solutions, companies can differentiate themselves and make a difference in the industry.
For example, this guy is saying that he will prepare a service for you that works for the entire building lifecycle, which is important for building owners because they will experience the entire building lifecycle. I think it’s very important and valuable.
Aiden, this is going to be a difficult question, but if there was one piece of advice or something that could really help people listening to this who are interested in artificial intelligence, maybe you’ve already covered it, I don’t know, but this could just be a summary of what we’ve discussed. How would you describe that?
All construction sector professionals know that the industry is good at planning. Our sector generally excels at creating project plans and understanding strategy. Use this strength for the AI side or the data side. Make a plan for your company, whether small or large, to solve problems, make a difference in the sector, and provide value to customers. You know your customers better than anyone, so you can cater to their needs by automating some aspects with data, which will make a difference and be valuable.
If you’re a small business owner and want to start at some point, try to use this strength. Leverage the data you already have to win more projects and profit. This is possible if you spend a bit more time, use your planning skills, and reach out to experts in the area. There are many people you can connect with, so it’s achievable.
I was
Maybe it’s not such a special question after all, but it’s a good one nevertheless. So, mine, go ahead. The question from CREtech taken from our podcast is, if someone gave you an unlimited budget to invest in any emerging business technology, but not AI, what would that be and why? It’s a tough question, but I believe that modular construction is very important. Maybe it’s the future of construction, along with 3D printers for the construction sector. I’m talking about the big 3D printers because I have a lot of money. They are making good concrete works, and there are some 3D printers for steel as well. These technologies are changing the construction sector, increasing productivity, and decreasing construction durations. It’s essential for housing increases, for example, in the UK, where people can complete construction projects faster using these technologies.
On that point as well, I’m glad you mentioned that because we had Henry and Terana from a company called Hyperion Robotics on before you, Aiden, whose company predominantly focuses on 3D printing concrete. So, check out that episode.
Oh yeah, good. I created continuity in New York. Yeah, thank you for that. And just before we sign off then, Aiden, where can people find out more about you and Botmore?
Maybe it’s not such a special question after all, but it’s a good one nevertheless. So, mine, go ahead. The question from CREtech taken from our podcast is, if someone gave you an unlimited budget to invest in any emerging business technology, but not AI, what would that be and why? It’s a tough question, but I believe that modular construction is very important. Maybe it’s the future of construction, along with 3D printers for the construction sector. I’m talking about the big 3D printers because I have a lot of money. They are making good concrete works, and there are some 3D printers for steel as well. These technologies are changing the construction sector, increasing productivity, and decreasing construction durations. It’s essential for housing increases, for example, in the UK, where people can complete construction projects faster using these technologies.
On that point as well, I’m glad you mentioned that because we had Henry and Terana from a company called Hyperion Robotics on before you, Aiden, whose company predominantly focuses on 3D printing concrete. So, check out that episode.
Oh yeah, good. I created continuity in New York. Yeah, thank you for that.
And just before we sign off then, Aiden, where can people find out more about you and Botmore? And I must say you’re very active on LinkedIn. You do some live streams on YouTube, which are full of great stuff. I think LinkedIn is a good start because I am there and Botmore Technology’s website and LinkedIn page are okay. You can reach out through my personal LinkedIn page or our website, botmore.co.uk, to see our services and products. But if you just want to talk to me, I mean, I like to talk to people. I say it, I like networking, so we can talk if you reach me through these channels. And of course, we have a YouTube channel too, where we create some informative videos. That’s all.
Great. Yeah, okay. Perfect. All right, Aiden, we appreciate your time. Thank you very much for coming on. Thanks so much, Aiden.
Thanks so much for tuning in to this episode of the Bricks and Bites podcast. If you are enjoying the show, please feel free to rate, subscribe, and leave a review wherever you listen to your podcasts. We really appreciate it, and we’ll catch you in the next episode.
