The following interview is a conversation we had with Matei Stratan, CEO of Ogre, on our podcast Category Visionaries. You can view the full episode here: $2 Million Raised to Build the Future of Energy Management

Matei Stratan
Hi, Brett. Thanks a lot for having me. 

Brett
Yeah, no problem. So before begin talking about what you’re building, can you start with a quick summary of who you are and a bit more about your background? 

Matei Stratan
Okay. So I’m Matte, studied business and finance in university, and about 2006, I started my career as a consultant. I was very active in projects which were both strategic and technical. So I was doing things like financial schemes for the EBRD or the World Bank or developing more technical projects like digitalization projects for utility companies. Before Ogre, I was very involved in the utilities field, and at group level, we had built, let’s say, two, balancing responsible parties with about 600 clients. So I got a first insight into basically how to build the analytics solutions and how important they are. So this is a very high level intro, very cool. 

Brett
And two questions we like to ask just to better understand what makes you tick as a Founder. Is there a CEO that you’re studying right now, and if so, who is it and why are you studying them? 

Matei Stratan
I can’t say that I’m studying a CEO right now. I have studied in the past. I guess Steve Jobs would have to be my first pick, and has always been because of his great ability to mix creativity with the business and product development. In my opinion, I think he’s really the person that has built some, if not the best products around. 

Brett
As a longtime iPhone user, I have to agree, they do build the best products. 

Matei Stratan
Yes. 

Brett
And what about books? Is there a specific book that’s had the greatest impact on you as a Founder? 

Matei Stratan
I think in general, very inspired by numerous articles or books, to be honest. But I think something which always pops to mind, because I did get this question quite recently would be The Man Who Solved the Market, probably by Gregory Zuckerman. It’s a book about Jim Simmons, basically, and it describes a story of how technologies that we use today in Ogre, such as AI, machine learning, basically how they were invented. And it’s just the story of some of the greatest technology builders of all time. Nice. 

Brett
I’ll have to check that out. I haven’t read that one. 

Matei Stratan
It’s a very nice book and let’s. 

Brett
Switch gears here and talk about Ogre, AI and what you guys are building there. So could you walk us through the origin story and then give us the high level pitch that you’re making to customers to get them to buy the product? 

Matei Stratan
Okay, firstly, the origin of the story comes from the fact that we had, let’s say, first hand insight into how important forecasting is. As I mentioned earlier, in your first question, I was working in a group of companies where we had two balancing responsible parties with about 680 clients. And we saw how, let’s say, bad forecasts or average quality forecasts affect the losses of these companies. So we got to understand how important they are. Moreover, as I was implementing other solutions as a consultant or writing digital strategies, I already got insight into what will happen to the field, how utilities will digitalize over time. So I think this was the actual story behind the origin of Ogre. I also had the chance to meet very proficient people in terms of AI and machine learning. My two partners, Mihai and Paul, they’re very proficient. And this Mihai is a professor at Oxford. 

Matei Stratan
Paul was also, let’s say, a quantum hedge fund, so they have a very big understanding of the topics. So we kind of connected all the information from my background from the energy field and their background, and we tried to push some of the best solutions around. This is what we’re building. 

Brett
And who are the ideal target customers that you’re after? 

Matei Stratan
In a nutshell, I would say we are targeting all types of operators from the energy field along the whole value chain. Whether you’re talking about generation supply or distribution or transmission system operators. We basically target the whole value chain from small producers to very large scale, let’s say, DSOs and TSOs. So we have products for all these, let’s say, operators. And we’re planning to build very advanced energy management systems that can even do, let’s say, grid level management. 

Brett
And when you’re having these conversations with them, what are some of their hesitations or concerns that prevent them from buying a solution like yours? 

Matei Stratan
Mostly, there is a lot of, let’s say, problems with the data quality. And depending on the region where you’re trying to sell the product, these problems may better or worse. But in general, they do know that they have problems with the data because it’s a highly regulated business. Sometimes even the legislation in certain areas doesn’t help the way that they store their data, the way that they manage, let’s say, the historical data, especially that you use to do forecasting, for example. So I think most of the problems are related to data quality, but also obviously to trials which have been done in the past, for example, and have failed. So it’s hard to sometimes come back from failed projects to go and sell your product to companies which have had failed attempts in the past. 

Brett
That makes a lot of sense. And in terms of geography, where are you focused? Is it on Romania, is it on Europe as a whole? Or where are you focusing your efforts? 

Matei Stratan
We’re focusing on Europe for now because we had a lot of opportunities, even locally. So we didn’t really get a chance to scale very much outside of our region, let’s say, because we had a lot of projects to implement and very complex projects for big DSOs with big challenges. So we wanted to have all this applied knowledge before we scale outside of our region. In a nutshell, I think we have enough opportunities here and we had enough opportunities not to be able to worry about scaling for the time being. 

Brett
Got it? That makes a lot of sense. And what’s the competitive landscape look like? Are you seeing other companies raise funds to try to solve this problem? And then what do the legacy solutions look like? 

Matei Stratan
I think the legacy solutions and the competition usually has very isolated, let’s say, forecasting solutions. For example, like the generation forecast solution is aimed just for the producers. The demand forecast is usually aimed just for suppliers or DSOs. What happens is they have very isolated solutions which ultimately are not integrated. And we believe that through integration of the data, for integration of the operators, we can bring ultimate efficiency to grids, both financially and operationally. So I think if we have to look towards the future and we are trying to be part of it in a very serious way, we are trying to integrate and to not only have, let’s say, the best forecasting individual style of solutions, but also to be able to integrate and to develop the real, first real grid level AI, which has the capability to orchestrate the whole grid, to tell you when to store, to tell you when to take energy, to transport it, where to take it and how to do demand response, how to do storage, when to tell people to inject energy into their cars and to charge them. 

Matei Stratan
Because this will become a huge problem over time as more and more electric cars are being bought by the population. So these problems, as time goes by, will only get more complicated. I think the renewables adoption, as we try to go to a carbon free economy will also have a huge impact on the reliability of energy supply and so forth. So I think a real energy management system that has a full 360 degree view of the grid and all the problems, all the potential hazards, is essential if you look towards a smart future, towards a sustainable future. 

Brett
Nice. That makes a lot of sense. And are there any numbers that you can share in terms of adoption and growth? 

Matei Stratan
In terms of adoption and growth, I can tell you that we’re currently forecasting about 90% of the demand in our local region, in our local country. And we are about to start in the countries nearby to also do a very big portion of the energy demand. So I think the main focus, at least for us has been on the demand and even the technical losses forecast, which is basically forecasting how much energy will be lost as grid operators provide the service. So this was, let’s say, the main things that we found we could sell faster because they are highly needed by the big operators. We have focused less on selling, let’s say, the solutions for example, for generation because we wanted to also improve our solutions in the meantime with the money raised for funding. So today we are pretty confident that our solutions are really ahead of the. 

Brett
Curve and as you move through country by country, do the laws and regulations vary that much? And do you have to redo the playbook every time or is it a repeatable playbook that you can use throughout each country as you go? 

Matei Stratan
I think it’s repeatable. Our business is very scalable. Of course the local regulations are different but the principles stay the same so because we have built a very scalable system, it’s very easy for us to, let’s say, to go from one region to the other. The legislations are obviously different and the incentives are different so they may have, for example, in a region you may have an incentive to reduce non technical losses which are basically energy steps, for example. So you may be incentivized to purchase such solutions. In other regions, like the United States you may be incentivized to reduce demand so you may want to get a better solution to do demand forecast in order to better evaluate and plan. So it really depends but there is always a need for such solutions and especially now as most of these companies are getting digitalized everybody has smart meters or soon will. 

Matei Stratan
This will be even of more importance as time goes by and as I’m. 

Brett
Sure you’ve experienced, bringing an innovative product to market isn’t easy. What’s been the single greatest challenge you faced and how did you overcome that challenge? 

Matei Stratan
Well, Brett, to be honest, the hardest challenge was actually to implement projects to further develop our systems and to do the recruitment at the same time. This was the biggest challenge because building the artificial intelligence requires a lot of talented individuals, they are always hard to find on the employment market. So I think this balance between implementations and research and development this was the biggest challenge how we managed to pull it off? I think it was because we had a very strong base of people to start off with very proficient which were able to fulfill certain gaps at certain points. So I think we’re on a very good track, to say the least. 

Brett
And what excites you most about the work you get to do every day? 

Matei Stratan
The most exciting thing is actually the bright minds with whom I’m spending my time on a day to day basis. I’m very proud of the team that we’ve built, and the efforts are really looking very promising. As I said, I think the second most important thing that I can think of is that we’re working on something which really can have a positive impact on both the business world and the environmental and social aspects. So I think this is also very important to us, and we know that by reducing the forecasting errors of every operator, we can actually reduce the environmental damage and we can quantify all this even in CO2 numbers and decarbonization and so forth. So we’re trying to basically provide really real benefits to both the business world society. So we’re very excited to have built this great team that can also have a very important goal. 

Brett
And if we zoom out, what’s the five year vision look like for the. 

Matei Stratan
Company, my five year or our five year vision of the company, I would say is we want to have the first real grid AI implemented. And we really want to show and have a proof of concept that this concept is really the way forward, because we believe. We really believe. And we have done. Our calculation is that we can really speed up the energy transition. We can really reduce this time by even up to 10% if you would have such a system put in place that can really manage and give business intelligence and operate the whole grid on behalf of all operators. So I think we want to build this for the company and obviously for the future. So my five year vision would be to have a product which can actually orchestrate everything, even the cars, to tell people when to charge their cars, to do demand response, to do all the things necessary in order to reduce all the inefficiencies and everything which is being lost today, which is significant. 

Matei Stratan
Really significant. 

Brett
Nice. I love that. And that’s certainly exciting. Unfortunately, that’s all we’re going to have time to cover for today before we wrap. If people want to follow along with your journey, where’s the best place for them to go? 

Matei Stratan
Think on our website, on LinkedIn, I think would be ideal. Awesome. 

Brett
Well, thanks so much for your time and thanks for sharing your story and really love what you’re building here, so let’s definitely keep in touch. 

Matei Stratan
Thanks so much for your time and thanks for the opportunity to discuss. 

Brett
Yeah, take care. Bye.