S3E37 – Sam Ramadori – Scaling a B2B SaaS (AI + Energy)

Key Timecodes

• (00:46) – Show intro and background history
• (01:53) – Deeper into his background history and philosophy
• (05:03) – Understanding his business model and AI technology
• (10:05) – How his AI technology can help clients to save energy
• (14:34) – How his technology can integrate with other systems
• (16:50) – What kind of average energy savings his product can bring to clients
• (20:49) – Deeper into his business model
• (23:46) – How about his company size
• (25:18) – What are his sales process and strategies
• (27:58) – How the company raise capital
• (30:19) – May the company go public soon?
• (33:21) – What is the worst advice he ever received
• (33:55) – What is the best advice he ever received
• (36:10) – Guest contacts

Transcription

[00:00:04.500] – Intro

Hey, this is Sean Tepper, the host of Pay Back Time, an approachable and transparent podcast on financial independence. I’d like to bring on guests to hear authentic stories while giving you actionable takeaways you can use today. Let’s go. My next guest is an attorney who worked in management consulting as well as private equity. He eventually stumbled upon a unique opportunity in the energy industry. He joined a startup that helps companies save as much as 25 % per month on energy costs. In this episode, we talk about how energy is saved, how they sell B2B, and how we help grow this company from 15 employees to over 150 employees in four years. Please welcome Sam Ramadori.

[00:00:47.710] – Sean

Sam, welcome to the show.

[00:00:49.170] – Sam

Thank you. Thank you, Sean, for having me.

[00:00:51.120] – Sean

Good to have you here. So why don’t you kick us off and tell us about your background?

[00:00:55.290] – Sam

Sure. Sean, I started off… I like to say I made the mistake of starting off as a lawyer many moons ago, but only lasted a few years in that profession. Then decided I very much wanted to be on the business side of things, went back to university, did a business degree and off to the races into the business world. After that, I t was mostly did some management consulting, but most of my career has been in private equity investing. So investing in small midsize businesses and helping them to grow. Somewhere four years ago, I met the team that started Brain Box AI and did not expect to make a career change late stage in my career. But I found what they were doing so compelling. And it sounded like it was exciting from a combining both solving a big world problem and an exciting business growth opportunity. And so I jumped into the venture startup world and joined the team to grow Brain Box AI to where it is today and beyond.

[00:01:53.290] – Sean

Awesome. And thank you for that background. We’re going to dive into the business, what it does, how does it help customers here in a moment. But I love stories like this where you have investors from either you’re from private equity but there’s also venture capitalists that jump across the line and say, Hey, I don’t want to invest not only in the business, I want to actually help run it. And that you know you find a really fun, very intriguing model when a situation like that happens. So this company really motivated you to say, Hey, I know not only want to invest some time and money, maybe into this, let’s dive into the business here and help build it.

[00:02:29.650] – Sam

Yeah. I know it. I guess it came at a moment of time where it built up a significant amount of experience and know the challenges project or startup was going to face because I’d been on the other end of this equation and it really came at a moment in time. This is four years ago. The climate is front and center and only becoming more and more front center. And at a certain point in your life, you’re just like, okay, I could keep doing what I’m doing or I can do what I love and at the same time really make an impact. How often does that really come up? Usually, you separate those two lives. You have your philanthropic contribute to society life, and then you have your passion work, passion life. Well, I think I’m very lucky that I was able to combine those when I made the call to make the jump.

[00:03:15.730] – Sean

Sure. I like hearing stories from people who come from management consulting as well as venture capital and private equity. Can you share with us what management consulting firms did you work with?

[00:03:27.380] – Sam

So the experience there was with Bain & Company at the time. I would say most of the years was really in private equity. That was the bulk of my career. Started off with a large firm, Brookfield Asset Management, and then moved on to some family office platforms and then made the jump to this venture.

[00:03:46.610] – Sean

Awesome. Really nice background. All right, let’s dive in a brain box. What does it do?

[00:03:51.460] – Sam

I try to make it clear because when we start talking about the actual subject matter, it doesn’t make you the most popular person at the bar. So e have an autonomous AI that plugs into the heating and cooling systems of buildings. And hence why you’re generally not the most exciting person at the bar. But when you step back and you look at it, you talk about this global challenge we have. There’s very large categories and you clearly want to hit the big ones as fast as you can. Some of them are very obvious to everyone, the cars we drive, how we produce our energy. But at the end of the day, buildings is a huge contributor to emissions globally. Usually they cite the STAT 38 % of global emissions are coming out of buildings, either building them or running them every day. We’re on the side of the running them every day. And when you look at a building’s energy consumption, half of it typically is heating and cooling. So on a global basis, it’s an enormous category. The energy consumed by heating and cooling buildings is 30 % of all the energy we use in the world.

[00:04:53.300] – Sam

So you got to do something there. So as unexciting as it may seem, from a climate perspective, it’s a big, hairy, audacious goal to go tackle that and make a difference.

[00:05:04.300] – Sean

Got it. So I assume the AI helps companies or businesses, essentially they’re saving money. Is that right?

[00:05:09.430] – Sam

That’s right. And it’s been very interesting to watch over the last years that we’ve been growing brain box, it’s almost like four or five years ago, you were presenting this technology and you were really presenting the fact that you could save money and energy consumption. That discussion in just four years of really flip itself on the head. And today it is a lot of folks focus around, okay, what emissions can I reduce out of my operations? How hard is it going to be? How fast could they be? How can I track them? That’s also a real important one because measuring emissions is not something that we’ve been used to doing, and yet here we are. That whole discussion has really changed over the last years. It’s exciting to see. When you’re in a climate space, you get worried over time, unfortunately, things seem to be getting worse and worse, and you look for rays of hope. And in there we see the fact that emissions is now getting right up there in terms of priorities for companies and individuals.

[00:06:06.550] – Sean

Let’s dive in a little further to really… I really like to dive in deep, understand how the business works. So is this some software or hardware component? What is the model here?

[00:06:18.620] – Sam

So this is a cloud delivered, I want to use the word service, but service doesn’t do it justice because it is autonomous AI optimization or control. And I often allude to the self driving car market or segment because it’s the most intuitive one. So autonomous AI is a very new technology. It’s not widely applied. We see how much time and money that sector of all the companies pursuing the autonomous vehicle are putting into it. It is difficult. So it is taking that technology. So this capability of this… And again, I don’t like to use the word software. This AI model or infrastructure that’s able to learn its environment using the data it’s suggesting in real time, and then being able to make decisions autonomously and implementing those decisions in real life. So the self driving car is, it turns the corner, it doesn’t know what’s going to be there. Well, within milliseconds, it turns the corner and knows parked cars, kid on a bike, soccer ball, and stop sign at the end, within milliseconds. And then it starts saying, go to the stop sign and stop, or kid is crossing the street, stop p now.

[00:07:30.630] – Sam

So that capability, it’s exciting. It’s really exciting. And for the car, it’s obvious. For the buildings, it takes a bit of a fast explanation here. I’m not going to take too long. But the problem with buildings right now, the room you’re in, the room I’m in, things are turning on and off to heat or cool it. And the only thing that it’s using to make that decision really is the thermostat on your wall. It does not know I’m sitting here in my office, there’s sun coming through the window. Obviously, right now, this room is heating up a lot more than it was this morning when there was no sun. The HVAC system, the heating and cooling system, let’s use the term HVAC, doesn’t know any of that. It doesn’t know how much my energy costs. It doesn’t know if my electricity I’m using right now is green or more fossil fuel generated. It doesn’t know how many people are in the room. It just knows that basic information, the thermostat, the humidity sensor, etc. What we want to do is take the building’s data, we move it to the cloud, and then we enrich it with all this external information that I just referred to, and then have the AI learn that building.

[00:08:31.320] – Sam

And why that matters is because each building is different and each building has many, many different rooms. They’re in different locations, they react differently. Some of them get the sun, some of them don’t as the most basic example. And so the AI is able to take this data and learn that building on its own. And then what it’s really exciting, there’s a few things AI does really well. One is predictive capability. So when it’s done learning a building, it’s able to predict what’s going to happen on the next call. It’s six hours hours in each with 99 % accuracy. So now you’ve taken a building like the way I described at the beginning that just knows what the thermostat is saying to, hey, I know what’s going to happen in each of the rooms in my building over the next six hours with 99 % accuracy. How much smarter do you think im going to be making decisions? Then one last one and I’ll stop the explanation there. The self driving car means you want to take the driver out of the equation and let the car go. In a building, that’s autonomous control. That’s what that gives you.

[00:09:29.110] – Sam

In a building, what it really gives you is the fact that buildings are made up of hundreds of pieces of equipment in the HVAC system. Pumps, motors, valves, dampers, a big boiler in the basement. We would not be able economically, you’d need like 20, 50 engineers in a building living there 24 hours a day to try and go tweak those systems every five minutes based on what’s happening outside and people moving, etc. Well, that’s what AI gives us here is the ability to make all these autonomous decisions on its own and go make these changes in these hundreds or thousands of individual pieces of equipment in real time.

[00:10:05.080] – Sean

Thank you for the description there because before the podcast, you said it is a little harder to explain, but this in simple terms, this totally makes sense. And comparing it to the autonomous vehicle makes a lot more sense. So just to go a little further there, it sounds like it will know, let’s say people are coming in at 8 AM, it’s going to start to heat up maybe a little more if it’s in the colder months of the year. And then it knows if people are leaving at, let’s say, 5 PM, it’s going to maybe back down a little bit just to automatically save energy.

[00:10:35.720] – Sam

Exactly. It’s probably the quickest or easiest example that will be clear to people listening here that are not HVAC experts. Most of us are. You could imagine your office open to up at 7 30 in the morning. So at 7 30 in the morning, that office needs to be warm or cool enough for you to work comfortably. So somewhere in that system is a schedule that says in the summer, start up at 6 30. So every day, 6 30 equipment turns on, away it goes. But it’s going to start 6 30 in the morning, whether it is 105 degrees outside, humid or 71 degrees in raining. And you’re going to quickly say to yourself, why is that thing air conditioning like crazy on the day where it’s 71 and raining outside? It doesn’t have to. It doesn’t have to start at 6 30. It could maybe start at 715. But the way things are programmed today, they are. They’re just programmed on averages. And someone said, 630, I’ll cover most days and we’re good. But there’s wasted energy in there. There’s a lot of wasted energy in there. But if you had that brain that says, Hey, today it’s hot, let’s start at 6 30.

[00:11:33.610] – Sam

Tomorrow morning, if this thing wakes up, it does the math, it’s pretty cool. It doesn’t have to start at 6 30. It could start at 7 12. Let’s start at 7 12. I know it sounds like small stuff, 42 minutes. That’s a lot of energy. You multiply it by many, many thousands of buildings, huge amount of energy.

[00:11:48.730] – Sean

Yeah, exactly. I’m thinking about in my home, which was built in ’99 and had the basic, I think it was like a honey well system, and it’s 2200 square foot home. And it’s like, having the base system it came with is nice. And I installed the Google Nest, which is great because you can control everything by your phone. But it’s not AI. It doesn’t like, hey, we’ve got now 10 people coming over and now the temperature of the room is heating up. It doesn’t need to be running that hard. And that’s not a big… For a home, that’s fine. But then you go to an office complex which is 100 times larger. That’s where the real dollars.

[00:12:27.020] – Sam

Start adding up. Exactly. And it’s like things change. Even though it’s a building and a building feels like it doesn’t change because it sits there every day. But things around it, I mean, right now, literally, I said before, the sun is literally shining through my window. In 15 minutes, the clouds could be rolling in and the thermal behavior of the room changes so dramatically, but no, the systems don’t know that and they can’t benefit from it, can’t fight it, etc. And then this gets into a whole new level. But if you sit back and you think about, in essence, what that building now is. Before, it’s this closed system that’s just turning fans up and down because of a sensor saying inside that room is too hot. By the time we’re done, this is like an unawakened building. It’s now sitting there going, I know the temperature that coming. I know that the energy I use in the morning is greener than in the afternoon because the wind stops blowing or the sun goes down. I know that the electricity being generated to get a super carbon intense. It’s like this awakened, much more intelligent asset that’s able to make much smarter decisions.

[00:13:33.620] – Sam

And one building cool, but when you have 500 buildings behaving that way, you can really support the movement we have to make now, which is going towards renewable energy. There’s that whole world coming at us right now. Renewable energy is coming more and more. Problem with renewable energy, it’s not like a coal plant. You turn on a coal plant, it’ll run forever. Well, sorry, exaggerated. It’ll always run. It’ll always be there. You put on renewable energy and in not a moment’s notice, but in an afternoon, it could just stop. Clouds roll in, wind stops, bang. Well, that new world we face requires us to be much more flexible than we ever were in the past. You and I went home, turn on the switch, full expectation that the light will go on. Never had a moment’s thought that I’m using energy right now and it’s not a good time. That future is not our future anymore. It is now we are getting renewable energy. It’s what we want. But it means as users, we have to be far more flexible. So when we have this AI capability running hundreds of buildings in a city, the support we can give to that energy transition is tremendous.

[00:14:33.220] – Sam

Sure.

[00:14:33.710] – Sean

Right on. I want to get into cost savings here in a moment, but first off, I’m curious about the tech. This cloud AI, can you integrate with most HVAC systems?

[00:14:45.660] – Sam

That’s a really good question. And it is an absolute reality of what we face day in and day out. Our work on autonomous AI is hard. It took a lot of investment, a lot of years. As challenging as that is finding ways to plug into more and more HVAC systems over time and doing it scalably. So we started off with a one edge device approach that connects to the existing system in the building and connects to the cloud. Over time, we’ve developed software drivers. We’ve integrated to other people’s cloud platforms that already have connections to thousands of buildings. But over time, we just keep working on more and more ways to plug into buildings. And it’s important because, Sean, the one thing when we talk about buildings, and you’re seeing behind the view, downtown Montreal, we always think about the big, tall, shiny towers. But the reality is the vast majority of buildings will make up the most footprint are those medium sized buildings, smaller buildings, and we got to find a way to get to them, connect to them and make them more efficient. And so you just got to keep pushing and finding new ways to connect.

[00:15:49.300] – Sam

So that’s a big area of focus for us.

[00:15:51.770] – Sean

Sounds like your engineering team is very focused. It’s probably a lot of questions that come through the door. Okay, new prospect or new customer has this HVAC system. Do we already have this connection? If no, then it’s like an, oh shoot moment. We got to create a new driver or connection.

[00:16:05.910] – Sam

Exactly. And you’re making calls, right? You want impact. We have these the term I bring to some of the words we use, scale and impact. And we’ve purposefully really pushed, deployed in buildings a bit around the world. We could have just stayed North American, but we really believe in scale and impact, and we got to find ways to make it scalable. Ai gives you a fantastic opportunity to do that. Cloud infrastructure today is almost in every country. It’s an exciting time to be doing this. And it now works 10 years ago without the cloud as present as it was now, I’m not sure we could do what we do. But now is an exciting moment in time and we can have a real global reach. We plug into buildings on the other side of the planet and we never send anybody to them. That’s how you scale.

[00:16:49.490] – Sean

All right. Energy savings. What average energy savings are we talking about here?

[00:16:55.020] – Sam

So we’re typically reaching or usually hitting between, let’s call it high teens and typically up to 25 % energy savings of the energy consumed by the heating and cooling systems.

[00:17:07.750] – Sean

That’s.

[00:17:08.800] – Sam

Huge. Wow. It’s huge in the fact that we’ve, in essence, removed the CapEx. If you’re going to try to chase that out otherwise, maybe you’re going to replace a big piece of equipment. Maybe we’re going to put in new windows that are more thermally friendly. It’s huge because it comes with very little investment up front.

[00:17:24.580] – Sean

And you could probably dive into numbers a little better than myself, but I remember talking to, let’s say, small midsize businesses. They could have a company of, let’s say, 25 employees. They got some office space, maybe some warehouse space. And I remember CEO telling me once, he’s like, we’re paying like, get this, like $3,000 a month in energy costs. Well, you take 25 % against that, it’s like, hey, that’s.

[00:17:47.220] – Sam

Huge savings. It’s meaningful. And today it’s interesting. I mentioned it before. People talk in tons of emitted carbon now, just as much as they talk about the dollars like you just did. It’s fascinating to watch. It’s something we never did even five years ago. Now all of a sudden people know how many tons they’re emitting. That’s cool. Yeah, it’s cool. And then they also know, I don’t know, imagine you run a company with a fleet of trucks, the cost of replacing those trucks to get electric vehicles and then make sure you have all the charging stations in place and that they can do what they do with charging stations access out in the road. It’s so intense. What’s exciting is that we can show up and give you a more very low cost, fast deployment, no major equipment, et cetera, option to get those emissions down quickly. Then unfortunately, you have to keep doing the rest, but this could be a really fast initial step.

[00:18:38.390] – Sean

I didn’t think of that because you’re tapping into the EVs and I’m hearing more and more, let’s say it’s a group of electricians at a small business, they could have like 10 trucks and they want to move at some point from gas to electric. Well, where are those vans or trucks being charged?

[00:18:56.270] – Sam

This is also something that we’re going to be interacting with, integrating with. Let’s take electricianshop 10 people. They probably have a building that’s, I don’t know, 15,000 square feet. It has an electricity pipe going into it, like normally it does. And you add 10 vans charging at the same time, there’s no way that building is going to be able to handle it. No way. And so you have to get into systems, either batteries or different ways to charge or charging on timers combined with us managing the other big load, which is the heating and cooling. Maybe we could do trade offs. We can use energy at a moment in time and then deliberate it for the chargers. That world is coming like a mile a minute right now.

[00:19:38.560] – Sean

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[00:20:42.190] – Sean

Com. That’s TYKR. Com. Again, Tykr. Com. All right, back to the show. Well, let’s dive into that. Let’s dive into your business a little further. This is a good transition point. So is your model classified as a B2B SaaS?

[00:20:57.230] – Sam

Yeah. So it’s a recurring monthly fee structure. And each project is a bit different. So we structure it slightly differently if there’s an upfront cost or if there isn’t and whatnot. But at the core of it, it’s a monthly B2B recurring revenue.

[00:21:11.900] – Sean

Can you share with us from low end to high end what you usually charge customers per month?

[00:21:16.890] – Sam

It really goes by building size. We’re often tying it to square feet. So it really varies. I mean, we could have an annual recurring revenue contract of over $100,000, and we want to have one that’s $5,000 or $1,000, depending on how small the building is. That’s the other exciting part about AI. I alluded to it before. Our building size is very tremendously. We got the ginormous one that’s a million square feet, and then we got your local store that is, I don’t know, 5,000 square feet, slightly bigger than a big home. And it’s because of that autonomous AI that you can be doing that. Because the problem with that small building, it uses, relatively speaking, such a low amount of energy. And as soon as we have to send person to it, bang, the economics no longer makes sense. As autonomous AI gives you that reach right down to even more modest or smaller buildings.

[00:22:08.970] – Sean

I do this from time to time with the podcast. I’ll talk to the audience. So the listeners here, this is a great model to look for with public companies. Think of like, we like really boring businesses because Warren Buffett likes boring businesses. But it’s going back to the gold rush of the 1850s. The people that made money weren’t the ones mining gold. It was the people creating the shovels and making the jeans, the boring products that support the needs that are going on. So you’re essentially, as you said in the beginning, relatively boring, but this is a solid in demand business. So public companies look for this. And then if you’re starting a new business, this is good to think about as well. Not saying they should be a direct competitor to you, but think about energy and AI and how two worlds meet.

[00:22:58.180] – Sam

Yeah. I mean, we’re entering an era. So, Sean, I don’t know what the last… You’ve been doing podcast for a while. We’ve gone through… I’m old enough to remember the dot com era. And then we went through a few. What’s interesting about the era we’re in now is that it’s the tech touching the physical. It’s no longer even just the mobile phone in your hand or the smartwatch on your wrist. I mean, the technology of the future that we need to get to, it’s not just making it more convenient. We have to decarbonize major industries. The major industries means you’re touching usually a power plant, a steel plant, transmission system, the guts of our economy that we never talked about if you’re a technology company. Well, the brave new world is when those two worlds collide, basically.

[00:23:44.980] – Sean

Yeah, good call. Now, you joined when there was just a handful of employees. How many employees were there when.

[00:23:51.910] – Sam

You joined? We were about 15, and 15 of all mechanical engineers, coders, AI specialists. We had hadn’t yet started touching the commercial side at that point.

[00:24:04.040] – Sean

Okay. So are you a mix of… You said commercial, so you do residential?

[00:24:10.360] – Sam

Sorry, when I say we hadn’t touched the commercial function of the company, basically. There was no salespeople. Well, we did have one marketing person, but nothing else. No finance team, no HR team. It was just pure tech team doing its thing. And then I joined and then started growing the business more broadly with the team.

[00:24:28.790] – Sean

Got you. Okay, we’ll get into that in a second here. So how many employees today?

[00:24:33.060] – Sam

Today, we are just about to close our first acquisition. So I would have answered 150, but it’s going to be 170 about shortly. Okay.

[00:24:41.170] – Sean

And you coming in to run as CEO. See, I like, again, going back to your experience with Bain, management consulting and private equity. There’s the type of entrepreneurs or business leaders that are good at creating a tech company, putting the foundation in place, building the tech and whatnot. And then you get to a certain revenue. They’re not always the best fit for really scaling to a whole another level. To go from like five employees to 50 is hard. Going from 50 to 150 is completely different animal. In this case, you’re really, this is impressive, go from 15 to over 150 employees. And how many years is that?

[00:25:16.970] – Sam

It would have been just under four years.

[00:25:19.080] – Sean

That’s impressive. Okay, what’s your sales.

[00:25:22.140] – Sam

Process look like? It really does vary. Back to the big building, small building comment, you end up dealing with very large real estate firms or very large retailers with chains that have thousands of stores down to maybe a school system, school board that manage 10 different schools or just a handful of stores, a small retailer. So it really does vary tremendously and the process varies tremendously as well. But that’s our challenge. We want to have an impact on many buildings and we’re dealing with very different customer groups week in and week out.

[00:25:55.840] – Sean

So it sounds like your strategy is connect with a property management owner that has multiple properties because it’s like if you get in the door of one decision maker, you get introduced to a whole bunch of different projects.

[00:26:09.430] – Sam

Exactly. If I run a chain of 1,000 stores, it’s great that I try Brain Box AI on 10 of them, but it’s not going to solve my problem. So they pilot, they want to test this new technology, they want to do it. But then automatically it becomes a discussion of a much larger rollout because they have a board to report to says, by the way, show me your sustainability initiatives, year in and year out. So that’s our real approach to get the scale.

[00:26:34.030] – Sean

Brilliant. So for the audience here, there’s two different sales strategies you could deploy, and I’ll talk through them, and then you can make your comments here. So strategy one would be the one to one to one ratios, which pick a new business which has a new owner or new team and go and sell them and then move on to the next. That takes a very long time to scale. Option two is like, what you’re doing is going to the head, the top of the food chain that has a lot of properties or maybe an association or maybe a network that has all these buildings. They run a pilot, they try before bias, or making a big commitment for the long term, that’s a much better way to… That’s how you come from the space, but that’s how big businesses scale is you go for those big home runs, you want to find that main contact that has a connection to 20 properties or 100.

[00:27:22.760] – Sam

Properties or whatever. Yeah. And we double down on that because it’s also like we’ve set up distribution arrangements with large OEM, Original Equipment Manufacturers. In our industry, they’re truly large. These are businesses that are 10 billion to 50 billion in revenue type businesses. And they have platforms and they’re connected to thousands of buildings already. They have large commercial teams, so you can really expand, but it takes a lot of work. If you’re going to go down that route, you have to be prepared to invest time and development hours. But we do it because it’s what will drive scalability for sure.

[00:27:58.270] – Sean

Yeah. Going back to your comments earlier scale and impact. Now you are venture.

[00:28:05.980] – Sam

Backed, is that correct? Yeah. So we have venture backing. I would say our investor group is a different mix than traditional VC backing. So we do have, for instance, our lead investor in the last two rounds was ABB, which is a Swiss based global engineering firm that has a lot of footprint in the electricity system, smart buildings, et cetera. So in there, too, is a collaboration investment, but also working through their distribution channels and potentially developing ways to connect our products together better. The Government of Quebec, which is our province here in Canada, invested in our last round as well. Huge motivation around building efficiency, carbon reduction, energy transition. So a lot of collaboration there. We have earlier investors which are more traditional VCs as well. But we really appreciate that mix. We are looking to get support beyond the capital. And climate technology is really, I believe, need that mixed support.

[00:29:08.300] – Sean

Yeah, that’s a good lesson learned here is there’s people starting businesses or growing businesses raising capital. And you got to, as we phrase it, we look for smart money. We haven’t raised, we haven’t really need to. But smart money being not just money, but they have connections to your customers can make an impact. So you, same situation, you’re looking for the money aspect, but you’re also looking for those associations, those people out there that already have connections where they really need help the most.

[00:29:36.080] – Sam

Yeah, absolutely. And again, if they have platforms that we can integrate into, it takes real investment on both sides to make this work. So that alignment really helps.

[00:29:46.100] – Sean

Can you share with us how much have you raised to date?

[00:29:49.010] – Sam

To date, we just announced around about seven or eight weeks ago, and we’re working on a follow on round as well. So the numbers keep moving. But it’s a little over $70 million dollars raised to date. Probably, hopefully in a couple of weeks, will be over $80 million raised. And it’s that mix of investors that we just spoke about. And it’s a great geographic. Our problem is global. We love the fact that we have North American investors, but also European investors as well, and hopefully in the future, even abroad.

[00:30:20.010] – Sean

I could see your company in the next few years. Are you guys having the conversations of potentially taking this company public?

[00:30:27.270] – Sam

It’s not an easy decision by far. So climate technology companies always face the challenge of scale. You know the B2C world a million times better than I do. But you think it can go rapidly when people start downloading your app in a way you go. Climate technologies are almost always plugging into something physical and make it happen owned by a large companies, etc. So that scalability challenge is always something to think about when you think about going public where the market likes predictability, stable growth. But yeah, we’re obviously looking for the best possible outcome in terms of supporting growth and getting us out into the market. But you got to be mindful when you’re talking about going public.

[00:31:11.140] – Sean

Yes. All right, well, let’s transition to the rapid fire round. This is the part of the episode where we get to find out who Sam really is. Oh, no. I know. Pressure’s on. If you can try to answer each question in about 15 seconds or less. You ready? Yeah. Okay. First question, what is your favorite podcast?

[00:31:31.240] – Sam

I’m going to answer. I got two of them. I can’t pick a one. But given that we’re a climate technology company, spent a lot of time listening to climate podcast. Couple of them to highlight, Just Have a Think is a great one. And My Climate Journey as well. What’s important with climate technology companies is they got to present in a way that the public can understand. And they both do a great job at that.

[00:31:52.160] – Sean

That’s awesome. All right, next question here. What is the recent book you read and would recommend?

[00:31:57.340] – Sam

I think it’s Timely, the entire Homo sapiens, Homo Deo series of books by Mr. R arry is a good one to read, especially now that we’re getting into generative AI and we’re having to ask ourselves questions about what does this lead to and how do we make sure we take the right path there because there could be wrong paths. That series of books, I think, is a good context for that discussion.

[00:32:21.170] – Sean

Nice. Movie question. What is your favorite movie?

[00:32:24.800] – Sam

This one’s pure entertainment. Man on Fire, Denzel L oshie. And great actor, one, two. Good shoot them up movie every so often. Great. But it was done so well. Such a different style, both from the way the cinematography was done, the music, it was intense. I thought it was a great put together movie.

[00:32:45.400] – Sean

I would agree with you. I think that’s a Tony Scott film, going back to the early 2000s. I’m a total movie nerd, so I’m going back. But yeah, that is solid. You can’t go wrong with Denzel. I mean, I love the equalizer movies as well. Going back to training day.

[00:33:00.780] – Sam

But even the soundtrack to Man on Fire, you could listen to that without the movie on the side all day long. So it was great.

[00:33:07.040] – Sean

True. Nice call. That’s a first on this podcast.

[00:33:10.380] – Sam

And by the way, thank you, Sean, for reaching back and making the link because I even forget how long ago that movie came out. I thought 10 years ago, but now it’s probably more than 10.

[00:33:20.990] – Sean

All right, few business questions here. What is the worst advice you ever received?

[00:33:26.940] – Sam

It’s the one that’s basically translated it into stick to your swim lane. And look, I don’t want some people to get just incredibly good at what they do and experts in their field and so on and so forth. I’m just personally jazzed by learning something new. Private equity now this venture, I don’t think I’ve worked in the same industry twice in my life. You’re learning all the time. That’s the downside. You’re having to come up speed really quickly, but it makes life really exciting.

[00:33:53.080] – Sean

Yeah, I would agree. All right, and next question here. You’re going to flip that equation. So what is the best advice you ever received?

[00:33:59.530] – Sam

The model there would be just go for it. This point in my life where I joined Brain Box AI, I was doing private equity before, had been doing it for 15 years. It’s a sector you can get well compensated on. It’s exciting as well. So on and so on and so forth. To take that career and then jump to a startup of 15 people using AI, which, frankly, I did not know much about other than what I read in the news, that was a big jump. And colleague along the way and not someone 20 years older than me, someone in my career level that is like, If you’re talking to me about it, why are you even debating it? If you’re excited by it and you truly believe in it, just do it. Go for it.

[00:34:40.670] – Sean

Right. Love it. Last question here is the time machine question. If you could go back in time to give your younger self advice, what age would you visit and what would you say?

[00:34:51.170] – Sam

I’d probably go for the… And this could vary for different people, but something like between the 28 and 32. Because I guess many people talk about probably going back to adulthood or something like the moment you became 20, 18, 19, 20. I’d go back to that age because I find before you’re on a career path of some kind. You’re studying for what you’re passionate about or getting into your work life. I find that age, you’re just soaking it all in and running. But somewhere in that late 20s and early 30s, you start making decisions that really set your path for a while. I’m super excited by what I’m doing today. Frankly, I wish I’d have started this earlier. So if I could go back, I worked for a very large law firm, large consulting firm, large investment firm. Great career, fantastic. And it one led to the other. But to say hey, if you’re passionate about that, break away, go do it earlier. Maybe someone who’s 50 will say that to themselves now. And maybe that’s right or wrong thing, but that’s probably what I would have caught back, said to myself.

[00:35:56.390] – Sean

You’re never too old. And we always hear those stories of people who are in their 50s and 60s, they’re like, Well, I’m way too old to start a tech startup or join one. It’s like, No, there have been people who’ve been there and done that. So good advice. Thank you. All right. Where can the audience reach you?

[00:36:13.450] – Sam

Brain Box AI is website, brainboxai. Com. I’m on LinkedIn as well, fairly present and reach out to the company, go to our website, reach out to the company as well. We’re here to save the planet. That’s our big motivator and so always willing to speak to people that are on that same journey.

[00:36:31.200] – Sean

Awesome. Well, thank you for your hard work and keep up the good work on saving the planet. I love learning more about how we can use technology to improve the environment and make a positive impact. So, yeah, again, keep.

[00:36:44.570] – Sam

Up the good work. Thank you very much, Sean. Thank you for having me on. All right, we’ll see you. See you.

[00:36:50.300] – Sean

Hey, I’d like to say thank you for checking out this podcast. I know there’s a lot of other podcasts you could be listening to, so thanks for spending some time with me. Also, if you have a moment, could you please head over to Apple podcast and leave a review? The more reviews we get, the more Apple will share this podcast with the world. So thanks for doing that. And last thing, if you do hear any stocks mentioned on this podcast, please keep in mind this podcast is for entertainment purposes only. Please do not make a buy or sell decision based solely on what you hear. All right, thanks for your time. Talk to you later. See you. You.