How Microclimate Modelling Helps Cities Adapt to Climate Change

ALI: Another thing, you know that I see that this trend is changing and you know it's a good sign. For example I can say in some projects, for example in uh, Middle east, in Saudi Arabia or in Singapore that they have very hot climate now I see that for every single project they have to do microclimate simulation. And uh, like the cities they are asking for it and this is a very good sign. SHORMILA: Foreign. You're listening to Navigating Major Programs, home to the conversations elevating the infrastructure industry. I'm Shormila Chatterjee. RICCARDO: I'm Riccardo Cosentino. Evgenia: And I'm Evgenia Jilina. And together we press the industry's experts about the complexities of program management, emerging digital trends and the critical leadership skills required to approach this multi billion dollar project. RICCARDO: Let's see where the conversation takes us. Evgenia: Hello everybody and welcome to another episode of Navigating Major Programs. I'm joined here today by Riccardo. Hi Riccardo, how are you? RICCARDO: Hi, I'm great Evgenia, how are you? Evgenia: I'm doing great. We have an exciting conversation ahead of us. Our guest for uh today is Ali Katal Welcome Ali. ALI: Thank you Evgenia. Happy to be here. Evgenia: It's very, very nice to have you here. I'm looking forward to this conversation. We usually like to put our guests on the spot and do a self introduction. So why don't you tell us uh, a little bit about who you are and what you do and I'll let you introduce yourself. ALI: So I'm Ali Katal I'm a building and microclimate engineer and uh, I studied my PhD at Ah, Concordia University in Montreal. Uh So during my PhD study I worked on extreme heat in Canadian cities and uh, I developed some tools to model uh, Heatwave, uh and uh, fix this problem, find solutions for Heatwave. And after that uh, I started my own startup. So now I'm the co founder and CEO of Planet Greenleafs. We are a Canadian startup. We developed City Digital Twin which is a tool for uh, microclimate simulation. Basically heat, wind, shade, energy. So basically we are providing this tool to cities, planners, designers to uh, integrate microclimate analysis into their design process and find solutions to make spaces, streets more comfortable for people. Evgenia: Sounds very technically savvy and interesting and we'll definitely dive into that. But I'm more curious about the transition from being an engineer to studying and getting a PhD and then becoming a startup. Tell us more about that. ALI: Yeah, of course. Uh, actually it was a long journey and it was a good experience for me because uh, as I said my background was engineering and mainly mechanical and aerospace engineering. But when I immigrated to Canada and I started my Ph.D. actually it was around 2018 that we had a heatwave summer heat wave in Montreal and uh, 66 people died because of that. And uh, so this event entirely changed the direction of my study. So I decided to use my programming knowledge, uh, to develop a tool that uh, first researchers and the later cities and uh, urban planners and basically all the decision makers can use it to integrate uh, microclimate climate analysis into their design process. So to make sure that cities that they are designing are more comfortable and safe for people. Because cities are designed for people so it should be safe. And um, yeah. So uh, during this PhD study I worked on many projects and I modeled heatwave in many Canadian cities. And uh, after I graduated I noticed that there is this gap that for example this tool that I developed was used uh, by researchers, by universities, but uh, not by decision makers. So that's because uh, it was the idea that I worked with my colleague and co founder Mohammad. So we decided to develop this web based platform to make it accessible for all cities, for urban planners, for uh, engineers, uh, anyone who is a decision maker or can change the decisions, make a better design process, something like that. Um, so that was the main reason that I started to become an entrepreneur and I start my own startup. Evgenia: Fascinating. You saw a gap and you decided to fill the gap uh not just with research but with the tangible outcome by the sounds of it. Maybe walk us through kind of that transition from developing research, connecting it to the problem by the sounds of it, what you're trying to do. Again you saw the research, research backed up certain ideas and the problems. But now you're trying to connect it to a product. We work with ah, infrastructure, major projects. We talk a lot about the end goal in mind and kind of the operation side of it, how the actual tool or project gets implemented and used. I think we're talking about similar things here. Walk us through that transition. Kind of developing the product versus having the research to identify the problem. ALI: Yeah, actually this transition from academia to uh, uh entrepreneurship was a long journey and it very challenging at the beginning especially. It's still, you know, challenging but uh, yeah because you know as a researcher I was always uh, thinking about uh, scientific things and publishing uh, journal papers and uh, just you know, working you know with other universities. So I was explaining everything scientifically and uh, technically. So uh, when I started you know my own startup I joined uh, this accelerator program that they were helping us uh, to go through this transition. And uh, we had a judge, uh, actually different coaches, and we were uh, pitching in front of them. So whenever I was pitching at the beginning, they told me that, uh, okay, whatever you're talking about, I don't understand. So you are just using some technical words and uh, I don't know what they mean. So imagine I'm an investor and you are pitching to raise the money. So I should easily understand without any technical knowledge. So even at the beginning, uh, for the first, uh, period, I failed the program. So then I had to rejoin and go through it again. So these were all the problems. And then after that, uh, we started working, uh, on discovering the market. So I had this tool and first I had some imagination that, okay, so if I go talk to a city and say I have this microclimate, uh, simulation tool, and they immediately say, oh, okay, so this is very interesting, I will use it, give it to me. Uh, but you know, whenever I reached out to them, I said, okay, I have this tool. They said, yeah, it's interesting, but at this stage, you know, we don't need, you know, such a tool. It's not our problem. We don't have budget. So then, you know, I gradually tried, you know, to discover the market and uh, to find a niche market, you know, for our uh, product. And it was the interesting part. When I talked to for example private, um, planning firms, I noticed that, okay, so this tool is more useful for them, uh, not for cities at this stage because cities are not ready for it. So uh, that was because when I talked to them, then I started finding the problem. What's their real problem? So for example, I noticed that they say if they want to do the microclimate simulation, like wind comfort, thermal comfort, shade, heat, all of them together, uh, current tools cannot provide one single tool, cannot provide all of them together. Uh, they have to use separate tools. And sometimes it takes a long time. For example, uh, for one scenario study, they have to wait a few weeks or months to get the results. And most of the time it has to be done by another specialist or a consultant, uh, something like that. But they like to have their own tool so they can easily, without any technical knowledge, do the simulation. So for example, they have iterative design process so they wanted to just quickly get that and be cheaper. So because of all of that, I got clear idea about what they need and I started refining the model and developing this web based platform that can provide exactly what they need in the market. RICCARDO: So Ali, we're not investors, uh, I'm a geek, so let's geek out. Tell us first about the type of modelings that you do. And don't skimp on the technical terms and don't skimp on the technical details. And then tell us about the sort of the uh, engine that you use for the web application, if you don't mind. ALI: Yeah, of course I would be happy. I'm always happy to share more technical information because when I, you know, talk about that, you know, then I will be more excited and I can talk more. So uh, yeah, about you know, the engine. So basically uh, when we are talking about microclimate modeling and especially thermal comfort, so it's important to consider all the important uh, parameters, uh, into the simulation. So it starts uh, for example with uh, when we have this urban area, we need to model exterior shading. That for example, we call it short wave radiation, long wave radiation. So it's like a radiant heat between different surfaces. So for example, if you have a building, if you have a tree, if you have a road, all of them, they are exchanging this uh, radiant temperature between each other. So all these things are very complicated, but we need to consider them when we want to model microclimate accurately. Basically this model that we developed at the first step, we use um, uh, the technique that we call it ray tracing. We send rays in the entire domain. So we calculate the shading, lightweight, radiation, everything. And then we calculate surface temperature, humidity, moisture for all the surfaces, all the objects inside this area that we are modeling, for example for building, tree, grass, road, ground, everything. After that we have this uh, microcalena solver which we call it computational fluid dynamic. So it calculates the 3D airflow, temperature, humidity, everything. And with the previous steps that we calculated shading, surface temperature, we use it as input data to this microclimate solver and then it calculates the uh, uh 3D, uh, airflow temperature. And at the end we put all of them together to calculate a final index that we call it utci, which is universal Thermal climate index. So this index shows the heat stress on the pedestrian body. So for example if you are a person standing outdoor in the street, uh, so it shows how much uh, what's the real temperature that you feel is different from the temperature that we see, uh, in our uh, weather app, for example. So usually this UTCI is much higher. So uh, yeah. So basically this is what we calculate at the end. And then when we are talking about optimizing the design, uh, to basically uh, make the space more comfortable, we need to find a Solution to reduce this UTCI temperature, UTCI value. Uh also this model, the technology is based on a GPU solver that we have developed. And about the web based platform that you asked, uh, the backend is on uh, Amazon AWS server. We use their uh, GPU servers to run the model. So basically if you are an urban planner, you want to do the microclimate simulation. So you just go to the web app, you define your project, upload your uh3D model, everything and then uh, everything else will be down on the AWS GPU servers and you can only get the results, the visualization, the graphics to see how your uh, design looks like for climate modeling. RICCARDO: Cool. You mentioned you do heat. Obviously this is for heat. Are you also doing smoke modeling and smoke and other fluids circulation? ALI: Yeah, yeah, exactly. So um, we started with heat. Uh so basically it was airflow and uh, the wind, heat, temperature. But then uh, we noticed that when we are talking about extreme weather events and uh, about vulnerability and risk. So uh, for example flood and uh, smoke and uh, pollutants are also important. So uh, these are the next modules, the next features that we added to the model so we can provide all the uh, climate issues RICCARDO: and this um, M measuring. Sorry, what was the index? ALI: UTCI RICCARDO: UTCI Is that statutory? Is it part of the planning process that you have to do that modeling and demonstrate as part of your planning application? So is that like a planning requirement that developers have to put forward? ALI: Yeah, that's a very good question and uh, about that actually it wasn't like a requirement uh, from cities, uh and actually it's not yet you know, uh, it's not required you know by many cities, uh, uh, still. But for example city of Toronto, uh, they adopted their uh, thermal comfort guideline in 2025 and I'm very happy that uh, I can say Toronto uh, was the first city which did that. Uh now they are in this guideline, they are specifically asking for this UTCI analysis to be done uh, during the pre design process. And it's like four season study uh because in Toronto we have a very cold winter, we have a very uh, hot summer. So we have to make sure that uh, the space stays comfortable during both winter and summer. And because of that ah, thermal comfort guideline. Now for some specific projects planners, they have to follow this guideline and calculate UTCI and make sure everything is good. Also in some other countries like for example in Singapore and recently in Saudi Arabia they also started asking for this. But yeah, Toronto you know, was the first one. RICCARDO: No, I Was asking because I actually just making the connection maybe for some of the listeners or major program and what you do and you know my experience, you know I never being a designer but I know that when, when we had to um, bid or design and build large LRT systems, I think one of the requirements from our clients was to do a uh, micro climate analysis on every single station and understand the microclimate. So it is, you know, it's not just for cities but like transit. I uh, know transit clients make that as a requirement of the design development process. And I think the word, the reason I was asking for smoke is because also from a safety standpoint you, you need to, you need to model especially if it's an underground, an underground system, you need to model, you need to do a uh, CFD model for what happens if there's a fire in the tunnel? What happens if there's a fire in the station? How does that affect the neighborhood? All of those things are required and requested as part of a large transit project. And I'm sure it's the same for airports and any major infrastructure. Is that your experience? ALI: Yeah, exactly. And uh, this is very important because previously like uh, for projects maybe they were only asking for indoor environment, uh, simulation and analysis. Like you know, as you said, for example if there is a fire, they wanted to see, you know, uh, how smoke, you know, is the smoke dispersion is happening, you know, inside you know, the building. But they were not looking you know at outdoor environment. Uh so it was usually the projects you know that I faced, you know it was focused on only indoor or outdoor. But recently I noticed that now for the projects they are asking for this kind of CFD analysis like uh, for example thermal comfort analysis and other things for both indoor and outdoor environment. Uh, for example in a project in Singapore they had some uh, like uh, air conditioning and you know, some other uh, equipments you know that they wanted to test. So it was for like you know, shopping center, center. But they wanted to see if the indoor space stays comfortable and also the outdoor space at the same time. Uh, so these ah are the kind of projects that we are seeing more frequently. Just maybe from last year. And uh, another interesting project was for example for a data center because now all the countries they are designing new data centers and uh, these data centers because they, for the cooling they generate uh, a very hot exhaust air which going to the outdoor air and then because of the wind uh it will impact the local microclimate condition. So when they are designing uh, like a data Center. So they want to first make sure this cooling system works well, the data center condition is good. And also they want to make sure it doesn't impact the local microclimate significantly. So people, it doesn't feel too hot. Uh, this is something that in some projects that we need, we noticed that these data centers made the local, uh, neighborhood during the summer to be up to 2 degrees Celsius higher just because of that data center. So that's because. Yeah, exactly. So now indoor and outdoor, they have to be modeled together. Evgenia: What would you say stakeholders typically misunderstand about environmental and climate performance or measurements? And I specifically kind of refer to. Because you're dealing with planners, you're dealing with cities, obviously technology providers. What do you find? Kind of. Have you seen any trends or patterns in terms of common misunderstandings when it comes to measuring, uh, the impact or um. Index. ALI: Yeah, yeah, exactly. So actually, um, the most important problem for us, uh, was to explain to them the difference between air temperature and this UTCI Because for example, when they want to plant a tree, they think that, okay, so if I plant this tree, then under this tree the air temperature will be like 2, 3 degrees Celsius cooler. And uh, this is not really what's happening because, uh, the cooling impact from the tree is, for example from the shade, it blocks the sun. And that shade is exactly, uh, impacting the UTCI that we are calculating. So air temperature is the same, maybe just 1 degree Celsius cooler. Uh, and this is like, uh, many studies, uh, have been done on this topic that trees just 1 or 2 degrees Celsius, the air temperature will be cooler. But for UTCI, then it's gonna be like maybe 5 or even 10 degrees Celsius lower. And this is the uh, exact impact by trees and other things. So we need to explain to them that all these concepts, everything, so they can better, so they shouldn't expect that air temperature is impacted a lot. And another thing is, for example, if you replace a uh, uh, dark pavement with a cool roof. Ah, sorry, cool pavement. Then the surface temperature will be like maybe 15 degrees Celsius lower. But it's a surface temperature, it's not air. It's not something that people feel. And uh, this is like a big misunderstanding. And uh, it's interesting that for example, this uh, summer in Los Angeles, so they spend a lot of money, they uh, uh, actually converted uh, this dark pavement to cool pavement in some neighborhoods. And then, uh, some researchers, they went and they did some measurement and they noticed that now for people it's even 4 degrees Celsius hotter because this uh, cool, uh, pavement, uh, it reflects the sunlight and then it's absorbed by people's bodies. So now it's not even, it's even worse. So all these things need to be explained clearly. And when I talk to stakeholders, they have no idea about that. Evgenia: So is this, what you're describing is essentially, if we were to simplify it, what you're describing is that your customer, your owner or infrastructure owner, landowner, does not fully comprehend or understand, um, first of all what they're trying to measure the impact and the solution. So they end up getting the wrong technology or the wrong quote unquote solution. And then it just kind of doesn't, doesn't make an improvement. So is this a design problem or is this a policy governance problem? Uh, like if we were. I'm trying to compartmentalize uh, the issue that you're naming and I'm kind of struggling to understand like where are we coming short in identifying where do we come in to fix it? Because you've got technology to fix it, but I feel like it's a bigger supply chain or chain reaction rather. ALI: Yeah, exactly. So actually it's uh, all of them that you mentioned. So the first problem uh, is that there is no policy. So for example, this uh, thermal comfort guideline by City of Toronto, now it's forcing uh, some, uh, for some projects to consider UTCI and thermal comfort into the project. And then uh, so this urban planning firm which is working on that project, so they have to come to us and say, okay, uh, I have no idea about this and help me to do this analysis to understand and make a better decision and prepare a better design to make sure this place is comfortable. Yeah. So the first problem uh, is cities, they have to make policies to force them. And the next problem is that. Yes. Ah, so I was studying and I was working on this topic for like uh, 10 years. So you know, I don't expect like the urban planners, architects, you know, to have like any idea about, you know, this UTCI So then yes, we have to explain to them so they can better understand that, uh, how different uh, solutions, different technologies, different design decisions can impact that. And actually uh, it also depends on the site, on the location on the city. And it's not like for example, one solution can work for everywhere. So for example, we say in some countries that they are very hot, arid climate, so they use like a water spray, water misting to cool down. Because yes, it's good because you know, it's A dry hot climate and it can work. But for example here in Toronto during the summer it's humid if you use water aspiration, you know, water misting. So then it doesn't work and it's going to make it even worse because humidity is important factor in this UTCI that we are talking about. So yeah, so these are all the things that they need to better understand. Evgenia: That's why in Vancouver we have cooling stations and there are spray fountains for people. To your point of different climates learn something new. Very interesting. Yeah, so it's, it uh, sounds like it's a combination of both lack of policy, kind of governance and then I guess simply not understanding the microclimate and how that impacts infrastructure. And then obviously that links up to not having any sort of specifications. Is that the direction that uh, maybe you're recommending or you're seeing that we need to have certain frameworks and in place that we start requiring these measurements to be taken into considerations? ALI: Yeah, actually this is the correct uh, direction that it has to go. So as I said, I hope that more cities, uh, they do this kind of studies and adapt uh, thermal comfort guideline and other guidelines. If they prepare that then they force these designers and planners, you know, to consider them and uh, then uh, some kind of, I don't know, guideline or something like that to fight uh, against you know, this heat wave. And for Riyaz, there is a project called Cooling Riyaz, you know they are investing lots of money on that. So yeah, I see this is the correct direction and you know everyone is moving into that direction. But I hope that it becomes faster. RICCARDO: Let me take you back to your product. Obviously cfd, Computational Fluid Dynamics. Nothing new, you know, that uh, been doing that for a long time. How is your product different than any other cfd, um, modeling tools? ALI: Very good point, very good question. So uh, when we are talking about cfd, there are different uh, types of CFD schemes or numerical methods that are used. So uh, for example there are some tools like we uh, call them Fluent, like Ansys Fluent or uh, like open foam. So they were designed for like specific uh, projects or some other applications like for aerodynamic for example, uh, for cars, you know, something like that. Uh, but they were never designed to work for microclimate modeling for large urban areas. And that's because uh, they are very time consuming and sometimes it's impossible to do the modeling with them. So what we did, uh, we used a different uh, numerical scheme that uh, if I want to use the exact terms in conventional CFD models, they use Eulerian approach and now we are using a different approach which is called semi Lagrangian. So this approach makes the CFD simulation more stable numerically and also much faster. And uh, we also uh, use the GPU technique. So basically we run the model on gpu. For example, when we compare with other old uh, conventional CFD models, they only run on CPU. So GPU is like you know, 100 times faster for example. And now that we use AWS GPU servers, for example, the new generation G7 generation, you know, that we are using, you know the GPU memory is great, you know, it's the best one you know, that I ever saw. So for example I was modeling the entire GTA with 150 km square and it was like one uh, billion grid cells, you know that I was doing the modeling. So previously I couldn't even think about it. Then you know, using this G7 generation I was able to model the heat wave during the July in just few hours. So it was something that I could never imagine previously. RICCARDO: Very interesting. Um, I'm trying to figure out if I want to go even deeper with the geeking. Okay, let's go there. Okay, so what kind of, what programming language do you use for your application? ALI: So the main programming language is C, but uh, we use JavaScript for the web app that we have developed and also Python for some other like post processing scripts that we use. So these are the main ones. And uh, also I can say just recently we started developing our AI model because we didn't want to go into that direction because uh, this physics based model, the physics is very important. That's because we invested lots of money and time to make sure this model is fast and accurate. Uh, but what we want to do is to make it like a hybrid physics and AI model. So basically AI will help this physics based model to be faster so maybe become like a real time. But we don't want to use only AI because pure AI will compromise the accuracy. So these are the kind of things that you are doing. RICCARDO: Okay, uh, I don't like the word AI. Can you be more specific when you say AI? What do you mean? ALI: Yeah, so you know uh, for AI and csd, so usually you know what we do, we develop machine learning, uh, methods, uh, that uh, we run many uh, cases and we generate lots of output data from the physics based model. Then we train this AI model machine learning based on this uh, output from the physics based and then we use it to do the prediction. So this Is uh, like a surrogate models that uh, many other companies they are using, using even some big companies. I don't want to bring names here because I will be in trouble. So what they did, their AI model is only trained based on some specific cases and they uh, generalize it for all other cities, regions that the model is not trained for and it provides some nice visual uh, results that for example, if even me, even me with this, you know like a 10 years experience, when I look at it first I think, okay, so this is correct, but when I zoom in I see that no, this model is not accurate. So yeah, when I'm talking about AI, I don't want you not to do that. So I want to still keep the physics and you know, make it faster. RICCARDO: So which algorithms are you using for the machine learning? If you can say, if you can say, if you. Evgenia: That might be the secret sauce. RICCARDO: Yeah, yeah, sorry, I just realized I was always asking that, Evgenia: taking notes and he's going to go off and rebuild. RICCARDO: No, no. Okay, never mind, never mind. Evgenia: Kidding. RICCARDO: So maybe, maybe just because the reason I said I don't like the word AI because I mean now everything, uh, nowadays everything is AI but like you know, you use large language models. That's not the AI that you're using. You're using the uh, you know, the old school machine learning models, uh, probably neural nets. You're doing, you're building some neural nets and, and do the machine learning through that. ALI: Yeah, yeah, exactly. So I can't uh, mention uh, the exact name as you said, but uh, RICCARDO: yeah, you're not using uh, chatgpt, uh, in your. ALI: Oh no, no, no, no, not at all. Yeah, actually so this is the second part that uh, just to make it more user friendly. So we want to develop our AI agent. So whenever you go to the platform, you want to create a new project, ask AI. I want do that for me. Something like that. But uh, no, the uh, simulation is like as you said, so neural network. RICCARDO: Okay, I told you we were going to geek out. Evgenia: I'm going to bring us back to me trying to compartmentalize things as I'm still catching up. If we were to uh, kind of categorize what you're describing, would you put it under the category of climate resilience, Cities planning and development or technology? ALI: Actually I like to say climate adaptation, but yeah, it will go under, you know, the uh, like uh, urban development. Not climate resilience. Exactly. But yes, some more. Evgenia: Okay, so not, not resilience there, but it impacts resilience. Wouldn't it be? Wouldn't be. ALI: Yeah, uh, exactly. So this, this is, you know, what I'm discovering. So as another like a market or opportunity or usage, you know, of this tool. Because when they are talking about uh, climate resiliency, they usually don't use very high resolution microclimate data. So I was speaking with uh, this uh, resilience officers in cities or even in big planning firms. So when I was talking to them, they said, uh, they only get the weather data, for example from some weather station, from airport or some uh, course resolution that we call it meso scale weather models, that it's enough for them. They don't want to go to the street level. But for insurance companies, uh, I see that probably in the future they will come to us and say, okay, I need this. Because now they want to see at each street when there is a, uh, heavy rainfall, the flood problem, everything. They need a uh, street level, not a meso scale. Evgenia: So this prompts me to ask an uh, interesting question. I was thinking in terms of procurement, and then you said something earlier that stuck with me. Cities, quote, unquote, cities are not ready for it. Who are you designing this product for? Who is your kind of best ideal client? ALI: Yeah, the best ideal clients right now are like urban planning firms, uh, that they work on, like uh, big, uh, urban planning, urban designing projects, master plan projects or landscape design projects, something like that. Uh, so for example, uh, let's assume there is a project to design like a big park in a city. And uh, this uh, landscape design company or urban planning company is working on that. So they have to do the microclimate simulation and then they have to find the best, uh, the design solution for planting trees, how many trees, uh, the fraction uh, of, of tilly canopy or something like that. So usually, you know, for these type of projects they come to us and they ask us to do the microclimate simulation for them or use our platform to do it. Evgenia: Would you prefer if cities came to you directly kind of for that service? ALI: Yeah, yeah, I tried very hard. You know, you can't imagine. You know, I tried very hard. Uh, for example, I went into the LinkedIn and I searched city, uh, planner, city of Toronto. And you know, I connected with all of. I can say I met with more, maybe more than 50 city planners, urban planners from city of Toronto. I said, okay, I have this tool. I have done the microclimate simulation, everything for City of Toronto. This is where I'm living. So do you need that? You have the thermal comfort guideline. You Know, I can do this even as free for you, like as a pilot, you know, something like that. But they said okay, yeah, I know another one, another city planner, you know, I can talk to them about that and something like that. Then I switched to smaller cities, for example Kingston, city of London in Ontario. And then you know, I went to them and they said, oh yeah, this is very interesting thing and you know, we want to work on it but we have to go through different channels and you know, go to, I don't know, some kind of uh, group meetings. And then you know, we get approval, we don't have budget. And uh, you know, whenever I talk to them at the end, you know, it comes to the budget and they say we don't have budget. We are very interested but maybe in the future. RICCARDO: Mhm. Evgenia: I mean Riccardo and I are just keeping our mouths shut because we probably have very strong questions and feelings about it. Um, why is it like that? Why is it like that in our industry when it comes to innovation? This, you know, I've said this before, this typical answer, you know, we've always done it this way and we've never done it this way. And it's kind of a paralysis. How do we unlock this, this kind of, you know, new technology implementation? RICCARDO: Let me be the advocate. Since there is no, no city planner on this, on this podcast. Let me, let me, let me give what I think is their perspective. I mean look at the end of the day city, you know, cities higher. Like a city doesn't do a, ah, master planning. The city, you know, the days where Citi had massive planning office where they would do all this in house are gone. So nowadays cities rely on supply chain to do this work, right? So they don't need this tool because they're always going to hire a firm to do this work for them. And the reason a city would do that is because again, I mean you could build a department in house and then, so then you could sell the tool to the department in house. But if that department is now procuring the service, then they don't need the tool. And I think it makes sense that way because I think 40 years ago they probably would have had that department in house. But everything is being outsourced, everybody is being privatized and, and so the uh, you need to sell to the service provider. The service provider is the one that needs the tool. Um, I mean obviously the planner are interested but the reason they say oh let's, you know, we don't have budget is because the budget that have is being allocated to the project and then that budget will be spent with consultants. Sorry. And I took a long detour because what I also wanted to say is like you need for insurance liability purposes, you know, the master plan need to be done by a professional firm. And you know, as we know we like to have the biggest brand signing the certificate that this was done according to certain standards. And so even though the tool in itself is super helpful, but if you don't actually have a large engineering firm standing behind the output of that and provided the liability cover that a large engineering firm can provide, then it becomes difficult to use that tool because firm is a legal and liability issue. To be honest, I don't know if that's your, your sense too. Ali. ALI: Yeah, exactly. So you know, what you mentioned is uh, one side, you know, of this, uh, I can't say problem. Yeah, but exactly, you know, what's happening in cities. And uh, so you know, this thermal comfort guideline for city of Toronto is a very good example. So when they wanted to work on it, so they hired uh, two large urban planning firms. Uh, so they uh, worked on this uh, thermal comfort guideline and they prepared that for city of Toronto. So here, uh, the problem was that one of those uh, uh, urban planning firms that uh, it was working on this guideline so they used uh, uh, some kind of open source tool that was not that efficient. And when I was talking to people, you know, who were involved, you know, in that process, they said to do this uh, microclimate, uh, simulation for one small area in downtown Toronto. It took like one month, two months, you know, to get the simulation results. And uh, I can say, you know, if they were using you know, our tool, you know, it could be done in one day, you know, not one month. So now the thing is, so when I go to cities, I don't expect them, you know, to start using my tool. So I just say okay, look at City of Toronto, if you also adopt uh, this uh, thermal comfort guideline, prepare it, you know, for your own city, then you force uh, these uh, planners, designers, architects to consider microclimate analysis, thermal comfort and climate, you know, into their design process. So yeah, this is, you know, what RICCARDO: I expect from the smart, this is Evgenia: more about this early stage, you know, who directs and who establishes those guidelines and maybe certain policies around so that then the companies doing the design can use the product and service. RICCARDO: Yeah, you're stimulating the demand from the top. Right. And so they gonna then um, force the index down to the, to the planner and Then you're going to be to, able to then sell your product. Makes perfect sense. How long did you take it to figure that, that approach out? How many, how many mistakes did you, how many bad turns did you take to figure that out? ALI: I can say, uh, two or three years. RICCARDO: I like the honesty. I like the honesty. ALI: A very good example for that is, you know, what happened this summer in India. So in India, you know, it's, you know, we cannot imagine it. You know, like the temperature goes like, you know, even around 50 degrees Celsius. So ah, I can't even imagine that temperature. So uh, we have a partner in India and they said, uh, microclimate simulation is not required by cities. But this summer, the heat wave, everything was worse. And they actually uh, said this uh, extreme heat is a national disaster. So when they said that, now it's like a game changing. You know, it's a different game, it's a different thing. And now, you know, cities, everyone, you know, they have to consider, you know, microclimate, thermal comfort, heat wave, everything, you know, into their design process. So cities, you know, will think about it and then, you know, they will force, uh, these uh, urban planning companies, everyone you know, is involved, you know, to consider that. And now, you know, this partner, you know, he said that is the best time for us, you know, to go to the Indian market. RICCARDO: So cool. Evgenia: Fascinating. RICCARDO: So before we press record, you were telling us about your fundraising journey, but can you maybe tell us where you're coming from and where you're heading with your fundraising? What stage of the startup process are you at? ALI: Yeah, yeah, absolutely. So when I started uh, PGL uh, with my uh, colleague Mohammed, uh, so we joined, uh, because I studied my PhD at Concordia University and they started a program called V1 Studio, which is a scientific venture program. And uh, so they hired graduated PhD students at postdoc and uh, they supported financially, uh, as like an investor. So to do this transition from academia to entrepreneurship. So for example for me and my colleague Mohammed, that we had this micro climate simulation model. They helped us to understand the market, do the market discovery, market validation and then develop our MVP and uh, going to the market. So it was a combination of uh, this V1 studio program with another program called District 3 in Montreal. So both of them, it was like two years that, you know, they taught us everything, you know, from 0 to 100%, you know, to learn everything from, uh, about entrepreneurship. RICCARDO: Yeah. ALI: And so it was, you know, like earlier stage, you know, fundraising, you know, that we did. Um, so it was like you know, kind of we call it safe, uh, agreement that uh, in future if we go to another round of fundraising so they will get some equity from the company. Uh, and now that for example in the last two years uh we have started getting some clients in different countries, different cities and we made some revenue but uh, still we have some cash flow problems. So we started to go to the next stage of fundraising for parisit funding and uh, for that we are working with uh, some advisors to hopefully raise more funding, we can uh, expand our company because we want to develop some new features, new things. AI model. Because with AI everything is changing so we want to uh, stay updated and uh. Yeah, so basically that's uh, everything about fundraising. RICCARDO: You have some revenues already, right? So it shouldn't be too difficult to do a pre seed round. ALI: Yeah I can say because uh, it was good uh, so far. But uh, we had some challenges. For example we were in a uh, program for actually called Nvidia Inception program and uh, AWS Activate program. So they provided us with some uh, credits, free credits that everything we were doing on AWS was supported by them. And unfortunately our credit is going to be finished soon. So the cost of AWS is uh, very much. And uh, now that we are getting more clients, more users because of the huge amount of data that we are saving on an AWS server and these GPU servers that we are running, we uh, are spending maybe four thousand, five thousand dollar per month, you know, for aws, uh, uh, servers. So yeah, because of that, you know we need to raise some funds. Uh, unless you know, it can't, we can't continue like that. Evgenia: That's the part most people don't realize is that the costs now associated with data storage and technology like the plumbing infrastructure behind supporting these big models and projects is the cost is very significant. ALI: Yeah, yeah, exactly. Evgenia: Just also curious, there's obviously a lot of accelerator programs for startups. What was your experience like with those? You're a first time entrepreneur by the sounds of it. Like this is your first venture. Was that beneficial? Was it helpful? I think you mentioned um, a startup accelerator you might have uh, used, right? ALI: Yeah, yeah, exactly. You know my uh, experience, you know, was great. Uh, I can say so because I had no idea about starting a startup, about entrepreneurship and uh, they taught me everything from beginning. We had uh, different uh, advisors, coaches and they helped us step by step to build a company. And I can say uh, if uh, anyone is a first time entrepreneur, they have to go to one accelerator program and uh, learn everything, uh, Fundamentally from beginning, um, but if we go to a later stage, uh, I don't think accelerator programs, uh, are good anymore because now, uh, for example, I feel, um, actually after District 3 program, I joined another program. It was good, but we were being distracted by them. So they asked us to do something that I didn't think is good for our company at this stage. So for example, when the product is launched, we have the mvp. We have to focus more on finding clients, outreach and sales and marketing. But they asked us to work on other things. So, yeah, it depends at each stage we are going to accelerators. Evgenia: Interesting. Has, um, becoming a founder changed your views on research and how research gets implemented? ALI: Yes, actually it changed uh, my understanding about that. Uh, but basically, for example, right now we are working with uh, many universities, many researchers. And because this tool that we have developed, we have an academic version that we license it to universities and they use it. So whenever I talk to them, I talk about my experience, uh, when I was a researcher and now as entrepreneur and uh, you know, they ask about it and when I talk about it, I see that, you know, they are excited and somehow, you know, their approach or, you know, the way, you know, that they looking at their research changes and you know, they want to their research be more practical, be more useful for real problems. Because previously some of the research work that we did, uh, you know, we just published some papers and that's it. Then you know, people, uh, researchers, you know, they were, worked for like companies on different things and you know, they didn't continue, you know, what they did during their research. So yeah, I think, you know, this is, you know, based on my experience, Evgenia: You now have the cold hard truth of how to raise money for a startup and running a startup, it's uh, I'm sure it's quite, quite different from the research phase and uh, developing the idea. RICCARDO: Well, Ali, I think we're at time. I think it was a fascinating conversation. Uh, thank you for indulging my geekiness and I'm sure Evgenia enjoyed it for a completely different series. Evgenia: Sure did. I always start to connect the dots, make things relevant in my head. This is great. RICCARDO: But yeah, no, thank you very much and I'll be following your progress and uh, I hope you succeed. Hope you go well with your fundraising. ALI: Yeah, thank you very much. Uh, it was great, uh, speaking with you. Thank you. RICCARDO: Okay, till next time. Evgenia: Awesome. Thanks for coming on. ALI: Thank you. RICCARDO: That's it for this episode of Navigating Major Programs. If you enjoyed the conversation, please follow the show and consider leaving a review to continue elevating the conversation. Join us on navigating major program program's LinkedIn page. I'm Riccardo Cosentino alongside Shomila Chatterjee and Evgenia Jilina. Thank you for listening.