Our guest today is Laurie Menoud. Laurie is a Partner at At One Ventures, a VC that finds, funds, and grows deep-tech startups to catalyze a world where humanity is a net positive to nature. Laurie also joined the board of directors of several Startups, and is a multi board observer. Throughout her career Laurie was a Microbiologist, a Biochemist, and Biotechnologist. She was involved in the characterization of the giant virus, “Mimivirus,” at the French national laboratory, which shed new light on the origins of life and optimized new biological processes for wastewater treatment. All that, before she turned to VC, where she co-founded A DOZEN! deep-tech startups related to computer vision, Natural Language Processing, diagnostics and robotics during her time at SRI International and later as Co-lead of BASF’s North America Venture Capital efforts.

In this episode we talk about Deep Tech VC Investments. We learn how to invest in Biotech, robotics, AI, and much more. Laurie tells us how her background in research, biotech, biochemistry and biology has helped her be a better investor. We talk about investments in companies to lead humanity to a state where we are a net positive to nature. We learn about sourcing deep tech investments, doing due diligence, and helping net positive companies grow.

 

Links

https://www.atoneventures.com/team

Contact

If you want to get in touch: contact@thewallstreetlab.com

We look forward to your mail and will do our best to reply.

If you want to reach out to us personally, here are our LinkedIn profiles, please mention the podcast.

https://www.linkedin.com/in/andreasvonhirschhausen/

As always, please do not forget to take 17 seconds to leave us a review on Apple Podcasts or wherever you get your podcasts from.

Be well,

Andy

 

TRANSCRIPT

 

[INTRODUCTION]

 

[00:00:04] ANNOUNCER: Welcome to The Wall Street Lab podcast, where we interview top financial professionals and deconstruct their practices to give you an insider look into the world of finance.

Welcome to The Wall Street lab podcast, where we interview top financial professionals and deconstruct their practices to give you an insider look into the world of finance.

 

[00:00:24] AVH: Hello, and welcome to another episode of The Wall Street Lab podcast. Our guest today is Laurie Menoud. Laurie is a partner at At One Ventures, a VC fund that funds and grows deep tech startups to catalyze a world where humanity is a net positive to nature. Laurie also joined the board of directors of several startups and is multiport observer. Throughout her career, Laurie was a microbiologist, a biochemist, and biotechnologist. She was involved in the characterization of the giant virus, Mimivirus, at the French National Laboratory, which shed new light on the origins of life and optimize new biological processes for wastewater treatment. All that before she turned to VC, where she co-founded a dozen deep tech startups related to computer vision, natural language processing, diagnostics, and robotics during her time at SRI International. And then later, she co-lead BASF’s North America Venture Capital efforts.

 

[INTERVIEW]

 

[00:01:28] AVH: Laurie, welcome to the show.

 

[00:01:30] LM: Thank you so much for the invitation. I’m really excited to be here.

 

[00:01:33] AVH: That is such a deep, deep, deep tech by you. I hope I’ll be able to keep up and make the conversation interesting for the sake of our listeners. But why don’t we start with your mandate at At One Venture? It’s a quite unusual description for VC to fund startups with a net positive impact. All I mostly hear about is the race to zero.

 

[00:02:02] LM: Yes. So I guess it’s kind of very different mandate from our venture capital firm. So obviously firm is really on a mission to help humanity become a net positive to nature. And so concretely, for us, this means we find, we fund and we go early stage companies that are using deep technologies to upend the unit economics of the industries that are destroying our planet. And so it’s really about resetting the way we do things. We put your thing what we need, like food, or electricity while giving back to the planet, while we’re restoring and protecting the ecosystems that are beneficial for humanity to strive.

 

Just if you look at the carbon emissions since the industrial revolution, we hopefully emitted more than 2 trillion tons of carbon. But at the same time, nature has already absorbed 1.2 trillion of those tons. So there is really, I think, an opportunity to leverage nature’s ability to take care really the environmental challenges we are facing today. And really make sure that every year we are on this planet. Nature is healthier because we are here.

 

[00:03:20] AVH: And what kind of startups do you fund? What’s your deal focus in terms of size? Is it pre-seed C? And which kind of stages do you invest into?

 

[00:03:32] LM: Yeah. So we’ve, for this first fund, we’ve raised $150 million. And we invested so far in 21 companies. And we have nine more new deals to go with this first found. And so typically, we are looking at early stage deals. So typically seed Series A. We are open to invest in companies that are pre-revenue. And for us, we’ll invest anywhere between, I’d say, one to $3 million. For initial check size with the goal to 10% to 15% of the company. And in most of cases, we like to lead these. We like to take both seats to really be close to those companies, and we’ll help them to go.

 

[00:04:14] AVH: With your background in corporate venture capital, this seems like a clear value proposition. But could you, for example, give us an idea of what kind of startups or the kind of companies are you interested at?

 

[00:04:29] LM: Yeah, definitely. So related to our investment thesis, we have kind of three big topics. It’s really about the carbonization, carbon sequestration and reduction of chemical and plastic pollution. And for us, we ended up investing across sectors like agriculture and food, transportation, energy storate or energy production, manufacturing, or even stuff in the construction industry.

 

Just to give you an example. So we’ve made an investment in biotech related to alternative protein. Company called Finless Foods, which is using cellular biology to grow bluefin tuna cells directly in the lab. And so the idea here is to commercialize a cost competitive, healthier fish products that is going to go in the lab, really as a way to lower the pressure and the job fish species like bluefin tuna. So that’s an example in kind of biotech.

 

If I look, for example, in the chemical sector, we’ve made an investment in a company called Battery Resourcers, focused on lithium ion battery recycling and manufacturing. You’ve probably heard announcements from several automakers that are planning to be and to have fully electric models by 2030, 2035. So this is really putting some pressure on online metals. And we need to start thinking about recycling of those EV batteries. So this investment in battery resources is really to address this problem. So using a new chemical process, and are able to recycle over 99% of the materials in lithium ion batteries. So those are just a couple of examples.

 

But maybe I’ll finish with the last one. I’m really excited about this company. It’s more focused on robotics. It’s a company called AP Score. And it actually was our first investment in the construction industry. And this company is developing a fully robotic 3D printer, which is capable of printing entire buildings on sites, and are able to do it nine times faster than using traditional mercenary techniques that you see when people are building homes. And because of being very, very fast, they’re also able to be three acts cheaper. So really opening up the opportunity to build the half of the homes that are going to be released sturdy. And at the same time move towards [inaudible 00:07:03], which are materials that are 90% lower carbon footprint compared to traditional Portland cement.

 

[00:07:12] AVH: Wow! Okay. I get a sense of what this deep tech is about. So it’s all very, very technical. And the first thing you mentioned, I remember listening like one or two years ago to a podcast with Steve Jurvetson, about lab grown foods and lab grown meat. And I got really excited about the topic. So it’s really cool that we can speak about this today.

 

Now, I want to go back a couple of years. And you come from the technology of biotech sector yourself. Could you give us a bit more about your background? What did you do there and maybe then lead this into how it now helps you as an investor in deciding which deep tech companies are the real deal and which are just like fans and neon signs on the front that have nothing that’s just mentioned all the fancy words, but there’s nothing behind it?

 

[00:08:09] LM: Yeah. So I guess I have probably kind of a unique background as an investor. I’ll give you three examples from kind of my deep tech background and why it’s relevant for my calling in venture capital today. So my first carrier experience, and it’s a bit of a geeky experience. I used to work in fundamental research on environmental biology, because of the French National Lab, which is called CNFF. And I got involved in the characterization of the first giant virus ever discovered. This virus is called Mimivirus.

 

And it was just an amazing experience to me, because I mean, this virus at the end of the day shed new light on the origins of life. So kind of a big project. But you could ask myself, why is that relevant with the career in the seed? And I think that by working in lab in research, it’s really helped me comprehend how things work at the fundamental level.

 

And today, it’s something I use when I need to understand a new technology. When I need to understand the physics principle. So it really helped me understand and assess the technical feasibility of those new technologies and of those companies, and also to help the companies prioritize research and technical projects. So that’s one experience.

 

And then I also work in the chemical industry. So I spent a couple of years at survey in research and development strategy. Couple of years also at BASF in corporate venture capital. And both are chemical companies. BASF being world leading one. Really big one. Hopefully $60 billion in revenue over thousand, hundred thousand of employees. And whose experience have been exposed to operations at scale, to massive manufacturing line to complex internal organizations. And it’s something, again, I share today with the portfolio companies to help them understand complex value chains and also to navigate siloed organization and ultimately do better b2b sales.

 

And maybe less on the kind of tech experience. So I used to work for SRI International. For the people who don’t know the organization, it’s formerly the Stanford Research Institute. It was spun out in the 50s from the Stanford University to focus on governmental research. And most specifically, back then, on research for the Department of Defense. They’ve developed world-changing innovations. Like Internet was created there. They’ve created the computer mouse. First surgical robots. Also Siri, the virtual assistants on the iPhone that many people use also was developed at SRI. So lots of deep tech again. And there was part of the ventures group.

 

And so my role was to commercialize to new technologies. And I ended up building a dozen of companies based on deep technologies and based on those technologies developed for defense and military applications. And it’s really where I built my operational experience by working with very early stage companies. And by making mistakes, by seeing entrepreneurs making mistakes. It’s really helped me understand what makes a deep tech company successful. And the common mistakes is, for example, being too technology push. You have a technology that seems very performance, and it seems unique on the market, and you just build a company around it, but without necessarily thinking about what are the customer needs. Or thinking about are we going after a market that is large enough?

 

And sometimes, also, depending on the application, can be very difficult to apply the technology and to make it visible at scale. So through all of those experience, it’s really helped me learn about kind of assessing deep technologies and also helping companies with deep tech to scale to go.

 

[00:12:23] AVH: I think there’s a lot to unpack and to follow up on in regards of how this experience helped you to become a better VC. And the first thing that came to mind is do you also have a laboratory like approach to investing? So like a very well researched process? Or can you maybe elaborate on what the pros of investing? Does it have to do anything with the experience that you did have in the lab?

 

[00:12:49] LM: It does, yes. Because again, I mean, we do early stage investments. So most of the times the companies, it’s a few people. Maybe anywhere between 5 to 10 people. Maybe sometimes left. The company maybe has done one proof of concept in the lab. But sometimes the technology, the prototype is still at lab scale. So curious, as part of all of our due diligence process, we spend time with the team. We visit the lab. We really look at the experiments they doing at the prototypes. How it’s working. We look at the data from these technologies. And we also try to understand from kind of fundamental perspective how the technology works. What are, for example, the cost driver? When we’ll be thinking about scaling of this technology to really understand, “Okay, does that make sense from a technical perspective? Is it really feasible at scale?”

 

And then when you think about the economic viability of the company, are we going to have a product with disruptive unit economics? Are we going to be able to scale this technology while still be able to reduce the cost and have a product cost competitive on the market? And so for us, this technical evaluation is really a big part of our due diligence before we make the investments. And after we make the investment, we continue working with the company on the technical side. And we like to be really close to the technical development to make sure we are going the right direction.

 

[00:14:24] AVH: And you have a background in deep tech biotech and chemistry. But you also said that you often invest in the chemical sector, AI robotics and things like that. But what’s your approach to understand every technology you invest in, right? There has to be a method behind like learning to learn something. And even though you have a deep tech background, so many technologies are so different. So what’s your approach like really understanding those technologies before you invest?

 

[00:14:55] LM: Yes, it’s a lot about reading and researching about new technologies. It’s taking a big part of my time. So every day, I read about kind of what are new emerging technologies in a specific sector. I read a lot about news articles, and calls for proposals from government organizations, from NASA, from the DOD, from the DOE. Because lots of those new technologies are emerging from those programs also have subscriptions to scientific journals like nature. Just to be kind of aware of what’s going on and have this kind of high-level understanding of those new technologies. And really a fun part of the job. At the same time – So yeah, my background is kind of biotech chemistry. And also, I’ve worked on kind of robotics or AI topics. It’s not my kind of educational background. But I think what’s unique about At One is also the diversity of our team.

 

So my background, as I mentioned, really focused on biotech and chemistry. But my colleague, Tom, who is the founder of At One, spent his career in the tech industry. He was an executive at Yahoo and Microsoft, and actually one of the cofounder of Google X. So he work on machine learning issues on autonomous navigation and on those technologies where I’m a bit less familiar.

 

So I’d say, just between the two of us, we are able to cover a large set of technology. And then we really rely on our network. We have access to a bunch of people from a network with values, technical background. And so we really leverage this network when we are looking at technologies with less – Let’s say less expertise in.

 

[00:16:46] AVH: Okay. And you mentioned in the beginning that you actually have a lot of experience in operating scaling startups. And I imagined – But please correct me, that in the deep tech there is still – It’s a fairly risky field. I mean, early stage plus deep tech is there might be a lot of unknowns. You said it yourself. How can this technology scale? Will it be acceptable at the market? Will the market adopt it? Will it not? And if you look at the new startup that comes your way, as such an expert in operations, how do you try to balance looking at is the idea really good? Is the science really good? Versus are they actually on an operational level doing really well?

 

[00:17:36] LM: Yes. And I guess for us, we use two kind of main criteria to deal with kind of the ability of the company to scale at some point and to be good at operation. I think the first point is really the team. Especially when you invest in early stage, I mean, those companies don’t have revenue yet. No history of finance. So you invest a lot into kind of a technology and really with the hope that the company is going to scale and hit new targets.

 

And so for us, investing themes with strong domain expertise. And when I say domain expertise, really people who have been in the industry who understand what it takes to build those companies I think is extremely important. So it’s really about technical expertise, but also market and industry expertise. People who have done it in the past. So I think that’s one point.

 

And then it’s beyond investing in the tech. It’s investing in technologies with disruptive unit economics. Because, ultimately, if we want those companies to scale and to have strong operation, we need to end up with products that are going to be cost competitive on the markets. Because yeah, customers like, yeah, deep tech, it’s nice. Maybe the performances are better. But if the product is the next more expensive, I’m not going to adopt the solution. So we really focus on looking at the unit economics, even at that early stage. Really understanding, again, what’s the cost to cheer for this product? What is the kind of path to manufacturing? What is it going to take to manufacture this technology? Where do we source the feedstock of the different paths to make the product happen?

 

So it’s really something we do before investments at that early stage. Why is the company still in the lab? Because it’s going to give us clues whether the company is going to be able to scale on it. And again, assessing the team gives us clues on whether the company is going to be able to execute on the plan and be operational at scale.

 

[00:19:46] AVH: So in deep tech, there’s very few 25-year-old Stanford dropouts doing the startups. At least not the ones that you do. And how do you – I mean, I imagine it’s very difficult to – In this kind of deep tech robotics space, for example, just to take that as an example, or AI biotech, any of that, to imagine how a scaled company would look like and how their revenue and their costs look like, right? Because with so many things, you have – Just take the computer. Just imagine how then expensive to first computers were. How big they were? And now everybody has them. Do you kind of think of this in terms of, “Well, in 10 years, this might be super cheap technology. But just we have to fund the startup until there?” Or do you try to like, “Let’s look at a shorter time horizon.” Are you ready to scale in the near term?

 

[00:20:39] LM: Because of kind of mandates on helping humanity become a net positive to nature, of course, it’s going to take probably multiple generations. But at the same time, from an environmental perspective, we really need to act now. We don’t really have 20 years. So actually, we are looking at solutions that are going to scale and be commercializable in the short term, or at least in five years. And again, that’s why we look at the unit economics. And that’s why we spend so much time understanding how we are going to be able to manufacture those technologies. Because we don’t have time. We don’t have time from a mission perspective. And also because we are set up as a kind of standout venture capital firm.

 

So our plan, I mean, we have a 10 years lifetime for the fund. So we need to return the investment for LPs in 10 years maximum. So we are looking at companies that are going to be able to generate revenue in the short term.

 

And again, it’s all about unit economics, just I mentioned earlier. This company, lab grown meat sector. So again, trying to grow mix of fish directly in the lab. There are many companies that are doing that today. And there are also lots of challenges in terms of scale up. And people think from the unit economics perspective, it’s going to be very difficult in the future, because processes are very expensive. But actually is a company we picked – I mean, we net all of these companies focused on pork, on chicken, on fat, on beef. But we ended up investing in a company focused on seafood, and particularly bluefin tuna.

 

And the reason for that is that fish cells – And maybe I’m going to go too deep into the technology. But fish cells actually have a big advantage over mammalian cells in the sense that they are much more robust. You can basically culture choose two cells with a larger range of temperature, oxygen, pH, which makes it scale up much easier compared to mammalian cells. You also don’t need to make some genetic modification to grow them at scale. Again, very different to mammalian cells that require genetic modification for immortalization to be gold at scale. And so this advantage intrinsic to the fish cells actually makes the business much more attractive, because you end up with a scaleups that may happen much faster, and also with costs that are going to be relatively lower compared to mammalian cells.

 

And finally, this company is focused on bluefin tuna, which is a product on the market very expensive today. And so, again, the company is starting from the beginning with a strong unit economics advantage. And it’s again, something we really like. And so the goal is for the company to launch a first product probably in the next two years. So we are not talking about kind of a 10 years or 20 years timeframe here, but something that will be able to be commercialized in the short term. So I don’t know if I answered your questions, and maybe I went too deep into the technology. But that’s kind of the approach we are taking regarding get deep tech and time to commercialization.

 

[00:24:02] AVH: No. I love it, please keep taking us so deep into the rabbit hole. This is why we do 60 minutes episodes and not 20 minutes so we can actually have the time to talk about this. What’s just going on in my head was basically was it a part of your investment thesis that the people that did the startup actually understood, for example, that fish cells are much more robust, for example, compared to pork or chicken cells, right? Does that speak to the kind of expertise they have acquired over the years to know like, “Well, actually, we’re going to focus on what is like has this high impact or like has this high price in the normal market so we have a bit more error opportunities, right?” So even if the unit economics are a bit worse than they expected, as the price is so high anyway, they still end up turning a profit, right? This kind of thinking probably helped them to attract investors like you.

 

[00:25:01] LM: Yeah, exactly.

 

[00:25:02] AVH: How do you find those kinds of deals? So are there like industry showcases? Or do you go from university laboratory to university laboratory? How do you manage to find those very edgy startups that you then take on?

 

[00:25:19] LM: Yeah. So for us, I guess comes mostly from leveraging on network. And today, we are actually doing statistics on a deal flow. 60% comes from referral, and mostly fellows from other investors, research centers, and kind of incubators, accelerators that tell us about new companies that are applying. And I think it’s super important, because as a seed stage investor, having a high-quality sourcing is critical, because it’s very time-consuming activity. There are thousands of companies out there. Many of them are just starting. Sometimes it’s one person, two people. Lots of them just have concepts. They have not even done any proof of concept of the technology yet. So being able to get referred to those deals to have other people that we trust that are reaching out to us I think is a huge time saving, and will give us access to companies that will be otherwise very hard to source. Because again, when it’s maybe one or two people in the lab, it’s very hard to access these companies.

 

And maybe I can give you an example. I recently invested in a company focused on kind of improving the gene discovery process for agriculture as a way to develop more effectively new crops. And so I had been looking at the sector for probably four years taking to a bunch of research centers, to incubators, to really learn about what are the new technologies developed in that field.

 

And I finally ended up chatting with Duke University. And I met amazing two cofounders. One of them was still doing his postdoc at Duke University. And they were leveraging breakthrough interpretable machine learning technology from the Duke University Lab, and had started to apply the technology for the development of climate resilient cops. And more specifically, they were focused on called tolerant highs. Amazing technology. Amazing program.

 

Of course, back then was a bit too early stage for me. But by doing this kind of research, by talking to a bunch of research center, I really was able to identify this amazing team. And a couple of years after, they launched the company and started putting everything together. I ended up investing in the seed round, which was really, really exciting. So yeah, ultimately for resourcing comes from our network, network among research centers, and also among other investors and incubators.

 

[00:28:07] AVH: How do we then decide to which startups to go into this deep exploration with? Because especially from what the process you described so far sounds very arduous, very time consuming. And I mean, that they only have 24 hours. So how do you decide? And which startups to focus so much time on? Do you, at first, like in the first checklist, have a look at the technology on like the white paper basis and like this can’t make sense? Like this can’t be feasible? This must be nonsense. Or are you like, “Okay, that’s not deep tech enough. That’s not climate changing enough?” Or what are your decision criteria then to go and take a deep look into a startup?

 

[00:28:53] LM: Yeah. So again, yeah. So we have this kind of metrics with the kind of main criteria. And each time we meet a new company, we go back to this metrics and we try to understand, “Okay, is this actually checking all of the boxes? Or are we don’t define some yellow or red flag is rarely used. There is one white flag, which has decided to pass on to the team. But ultimately, in terms of criteria. So yeah, similar to some VCs, we have maybe some unique ones.

 

And I’d say first, it’s the team. Again, does the team has white kind of technical and market expertise? Will they be able to attract top talents? Do they have the grit to execute on the plan here? So team evaluation is kind of the first path. It’s something we do quite at the beginning during our first call. So that’s one. Then we look of course at the technology, like what we discussed earlier. Is this technology new? Is it differentiated enough? But it’s is it actually technically feasible in the short term? Will we be able to scale and manufacturers is technology in the next couple of years? So that’s kind of the second criteria.

 

Then we look at the markets. Really trying to understand, “Okay, are we really solving a big need here? Is this market worth billions of dollars? Is this market wroth maybe a couple of hundreds of millions of dollars?” Just as a quantitative matrix in our head, if a market is smaller than a billion dollar, typically, we won’t be investing in the company. And sometimes we do the calculations very quickly. We do bottom-up calculations. Okay, how many customers? If it’s, for example, b2b deal? How many customers? How many of those companies on the market? What is the maximum price we could sell the product? And we do a rough calculation to better understand the market size.

 

Then after the markets, it’s those two last criteria kind of unique to our ventures. For us, it’s really about the unit economics. Again, are we looking at a solution here that is going to be cheaper, or at least priced by the solutions that are out there? Because again, people, yeah, are interested to invest or to buy products that are better for the planet. But if it’s more expensive, people are not going to adopt them at scale. So you need to go to mixes is really critical for us.

 

And finally, it’s about solutions that are going to reset the way we do things and really help us produce what we need while giving back to the planet. So from an environmental perspective, we are not looking at solutions that are going to help the way we do things by 20 soluble sense. We are going to invest in solutions that are going to completely reset the way we do things. And I think the lab grown meat sector is a good example. Because it’s not about hedges things. Kind of carbon footprints of the animal farming industry by 10% or 20%. Actually, finding a new way to produce the food and the meats that we need with, drastically, I mean, different carbon profiles in the animal farming industry. So that’s kind of our main criteria. I mean, we develop this kind of recognition pattern after meeting hundreds or even thousands of companies now. And you know very quickly, after the first meeting, you know if the company is going to check the boxes on it.

 

[00:32:33] AVH: Interesting. You mentioned the carbon profile of a company. And I was wondering, how do you measure? How do you estimate its impact? Because you said you want to invest in companies have a net positive. So not a zero or even 10x improvement, but a net positive. How do you try to measure this kind of impact? Or what are your force behind this is actually a company that this kind of impact? Is this more of a gut feel? Or do you have a certain measurement that you take into account? Or do you take the prototype measure how much co2 this one used up versus fishing of tuna or something like that?

 

[00:33:19] LM: Yeah. So actually, many impacts VC firms that’s kind of the approach they’re taking where they kind of try to calculate the co2 footprint of a company. At the moment they invest in the company and then later on as the compatible. This is not the approach we are taking. Because again, the type of investments we do will typically are very disruptive to the way we do things today. Just to give you an example, and people often don’t know that, but the construction industry has actually a really large carbon footprint. Concrete is actually responsible for 8% of the carbon emission. So people have been investing in companies that are developing concrete with kind of a lower carbon footprint. For example, companies that are reducing the carbon footprint by 5%, by 10%, by 20%, and actually doing calculations on this new process.

 

The way we decided to look at the approach is actually to invest in something completely different. We didn’t end up investing in a company developing a new material with a better kind of carbon footprints. Instead, we decided to invest in a new way to build home. With this company I mentioned earlier, [inaudible 00:34:39] company, which is using 3D printers to build buildings and homes directly on sites. And because this company can be 10x faster than traditional mercenary techniques, and at least 3X cheaper, they just opened the opportunity to use ozone material and concrete that have been until now too expensive to be used probably. And so this company is able to use geopolymer. Geopolymer is if you don’t have kind of a 5% or 10% improvement over concrete. Their carbon profile is actually at least 90% lower or even kind of net carbon negative. Meaning that their process because you can use, for example, of waste from the steel industry, can be positive for the planet.

 

And so in that case, I mean, the calculation is pretty easy. We are looking at solutions that are going to have kind of a zero impact carbon are actually being positive for the planet. And again, it’s really about for us looking at the unit economics and looking at technologies that are going to be to completely reset the way we do things. So I didn’t share kind of specific calculation methods to kind of calculate the carbon impact. I think we are taking a completely different approach here.

 

[00:36:00] AVH: Yeah, I mean, this is what I tried to kind of get at what’s your kind of thinking? Maybe not what’s the formula, but what’s the thinking behind the approach you’re taking? And as such a deeply into technology involved VC as yourself, what are current trends that you’re having a look at? That you’re keeping an eye on? Maybe as the startup you mentioned before, from Duke University, it’s like it’s kind of two years too early. But I’m excited to see what’s coming out of this.

 

[00:36:31] LM: Yeah, yeah, yeah. So what are kind of the trends in the sustainable VC space? And I’d say, so there has been really an explosion of companies focused on climate tech since the pandemic. We’ve seen probably at least a 30% increase in deal flow in that sector. And there has been $30 billion poured into climate tech startups to Q3 of this year. We saw some sector, I mean, an increase of 50% of investments after 2020.

 

Basically, in the last 10 years, last two years, so in not even 10 years, just two years explosion of companies in the sector. And I think what’s really interesting before – I mean, so let me just take a step back. When you look at the kind of clean tech sector, even stores have been looking at it since the 2000s years. That’s what we call clean tech 1.0, which back then was mostly focused on the carbonization of energy and bio-based materials.

 

And so most people were thinking that by using renewable energy, and driving electric vehicles will be able to solve the problem. But I think that this thinking is changing right now. And this is leading to the emergence of companies in sectors that are really important. So in terms of trends, I think we see a bunch of companies that are emerging and really focused on decarbonization. And it’s not anymore just about decarbonizing the energy or the transportation sector, but it’s about decarbonizing industries that have been a bit put on the side until now, like agriculture and food. So we know that agriculture and food are generating roughly 25%, even 30% of the carbon emission if you look at the next 20 years. And in agriculture and food, we see emergence of a lot of companies around easy alternative protein sector. So lots of companies that are developing plant-based solutions, also lab coordinates. So definitely a trend there.

 

We, of course, still see companies that are focused on the electrification of the transportation industry. Companies also that are focused on reducing the impact of heating and cooling of buildings, which is also a big carbon emitter. And as I mentioned earlier, construction industry. So we also see now, and that’s kind of new, companies that are really addressing the construction industry and the impact of carbon quality to concrete production. But in addition to decarbonization, a new trend we are seeing is related to carbon sequestration. So it’s not anymore just about reducing kind of human activities and carbon emissions. It’s also about carbon sequestration, and making sure we leverage nature’s ability to tackle those environmental challenges. And so we are seeing companies that are focused on reforestation. That’s one of them. And you have companies that are using deep tech to target ecosystem restoration, which is really exciting. And also lots of companies that are kind of leveraging the current trend around carbon offsets and carbon credits. So that’s kind of the trend we are seeing. But what’s exciting is to see the number of new companies and entrepreneurs that are kind of fascinated about this field and launching companies not only focused on decarbonization, but also focused on carbon sequestration.

 

[00:40:10] AVH: Really interesting. I hope they all will succeed. And they really bring this – Especially with companies that do carbon sequestration, how can they make that commercially viable?

 

[00:40:23] LM: Yes, yeah. So yeah, carbon sequestration is an interesting space. And I guess in terms of business model, it’s still a bit blurry at the moment. But I think there are some interesting approaches here. So of course, the carbon market is developing, and you have some large companies at the moment. Like Microsoft is one of them that are paying for those carbon credits, actually pretty high price. But the question is, is that sustainable, and is that scalable?

 

But I think that, in the meantime, there are very interesting business models that can be developed still relative to ecosystem restorations with customers that are already paying today, I can just give you an example with the mining industry. So the mining industry today, and it’s actually from a global perspectives. They have self-regulation in place that make it mandatory for the mining industry to restore the ecosystem on all the nights.

 

And today, this industry spending millions of dollars to – Basically when a mine is at the end of life, just to understand the landscape. Understand the ocean. Understand what else is weeds in the space. And to really restore the ecosystem and to plant trees. One of our portfolio company is actually focused on this specific topic and using computer vision and drones to plant trees at a much lower cost than what is done today. They can actually plant 120 trees per minute. So the scale is just huge.

 

And so with this type of business model, and then you can have something that is really scalable, which has strong unit economics. And we discussed another theme today. And while still focusing on carbon sequestration, and while still focusing on topics like ecosystem restoration. So I think the kind of carbon market, it’s still a bit early to know exactly where it’s going to go into the future. But already today, we can find use cases where people are already paying for those type of activities. And we know it’s going to have a positive impact on nature and on the amount of caverns that is in the atmosphere.

 

[00:42:44] AVH: Super cool. I think I saw or heard about those tree planting drones. And I thought this is a really amazing idea.

 

[00:42:52] LM: And just to finish, because I think it’s really cool. I mean, when you just think about the scale. So I mentioned 120 trees per minute, they can do it at a 10th of the cost of planting trees today. But with just six drawer drones, you can plant 1 million trees in just one day. And just to give you a kind of a perspective on the scale, with 1 trillion trees planted, this presents a currend carbon that we have to the planet. So I think we really need those type off solutions. And again, it’s using deep tech, because they can dramatically scale activities such as kind of restoring forests or producing food more sustainably.

 

[00:43:36] AVH: Super interesting. Now for the last section, let’s switch gears a bit. And during this whole conversation, I don’t know if I was the only one wondering that or maybe some listeners were wondering that, too, especially maybe our younger ones, if they want to get involved in the VC space, maybe in general, and then our interest in this kind of deep tech VC space, do they all have to have funded a dozen startups and grown them? Do they all have to have worked on the exploration of viruses at the French National Laboratory? Or what other tips could you kind of give them on what they should focus on right now if they want to become VC in the deep tech space?

 

[00:44:23] LM: Yeah. And I think for me – And again, yes, so I’ve worked on a bunch of tech, but I definitely don’t have kind of the path that usually invest of tech to get into a VC firm. And to my career, I’ve had a lot of people telling me that I will never be able to get into VC because I had too much of a technical background, or I didn’t do the white school, or people telling me that it won’t happen. And so what I will say to kind of young people that are thinking about their career and where they want to go, there is always a path to the careers goals you have. And even if you’ve not taken and most of us have a need to get there. So just don’t listen to people that are telling us that you can do it. I think it’s important to stay determined to stay positive and motivated. And really use the current job you have all the cue education that you are doing to learn about the skills that will open doors for you.

 

I think that’s, yeah, working in the tech companies, of course, help when you make the tech investments. I think an understanding of technology helps. But I don’t think it’s kind of a deal breaker if you don’t have a technical background, definitely not. One of our colleagues at One Ventures, she comes from the finance industry. She used to work in private equity and actually spent close to 10 years in in Africa working on micro finance. So nothing related to the tech. But she’s someone really curious. She loves to learn new things. And I think because of that, she’s an amazing fit for the team.

 

So I’d say don’t overthink if you don’t have the exact kind of background that people ask you on paper. As long as you have this curiosity for new technologies, and that you have kind of started building kind of skills around entrepreneurship, and a bit of finance of course, you can reach firm like At One Ventures. There is no problem with that.

 

[00:46:33] AVH: Amazing. Then there might still be some hope for me. That’s very good to know. Laurie, thank you so much for spending this time leading me through the deep tech VC space and really helping me to at least scratch the surface of understanding of what is there to come in the future. And I’m a fan of Med Riley and his books about like being positive. And I would say, our conversation today really helped me to remain positive. To not only see the bad things to know that there’s a lot of very smart people investing and founding startups that will help us turn this boat around and make this planet really – And keep this amazing planet alive. So thank you for all the work you do. And if you want, you can have some last – I’ll leave the last word to you to address our audience with something that you want to get out there.

 

[00:47:42] LM: Okay. Sounds good. I guess I just want to kind of reiterate the origins of fighting climate change. And we said the way we do things. The IPCC from the UN, earlier December, they released a report and they declared a code red for humanity. And they really are just to keep warming below 1.5 degrees Celsius. But 1.5 degree Celsius is still a world of constant disaster. So I think we need to set our sights higher. Se need to act now. And we need to create planet positive industries really, again, producing what we need while giving back to the planet. And I think technology as a whole to play in it, with venture capital being a tool to achieve this goal.

 

Because again, technologies can dramatically scale activities like restoring forests or poising for more sustainably or making electric vehicles happen at scale. And technology can do it in a profitable way while maintaining a healthy economy. So I just encourage investors to look at the space and perhaps join forces with venture capital firms by becoming an LP or helping directly startup companies. And I’d also encourage young people and people that are thinking about becoming an entrepreneur that there is a lot we can do with technology and we need more people creating those amazing companies. So that’s it. That’s kind of my left world.

 

[00:49:22] AVH: Perfect. Perfectly fitting last words. Laurie, thank you so much for coming on the show. And I’m excited to hear more of your portfolio companies and how they tend to work.

 

[OUTRO]

 

[00:49:34] ANNOUNCER: Thank you for listening to the Wall Street Lab podcast. For the show notes and much more, visit us at www.thewallstreetlab.com to see what we’re up to before anyone else. Subscribe to our newsletter on our website and follow us on Facebook and Twitter.

 

Disclaimer: Information contained in this podcast constitutes the opinions of individuals and should not be treated as investment, tax, financial or legal advice. We take no responsibility for the accuracy of any statements made in this podcast. This podcast is for informational and educational purposes only and it does not contain an offer to sell or buy any sort of financial products and should not be treated as advertisement for such. Any copying, distribution or reproduction of this podcast without the prior permission of the creators of the podcast is strictly prohibited.

 

[END]

Published On: January 6th, 2022 /

This podcast is supported by

Fintalent.io is a professional community for M&A and Private Equity professionals. Connect with peers, and work on exciting deals together.

Browse by Category