Andrea Traversone, Managing Partner at the NATO Innovation Fund
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Scaling a deep tech startup from an IP or university spin-out to a global unicorn is a daunting journey. It requires navigating complex challenges, making bold strategic bets, and executing relentlessly on a groundbreaking vision. Founders must possess unwavering determination and the grit to make tough decisions in a fiercely competitive landscape.
That is why we are honored to present our second 2024 Masterclass episode with Andrea Traversone, Managing Partner at the NATO Innovation Fund (NIF). Andrea has been investing in deep tech companies for more than 25 years and shares a wealth of insights and practical tips in this conversation.
The NATO Innovation Fund is notable for being the world's first multi-sovereign venture capital fund, and it aims to invest in startups developing innovative technologies that address defence and security challenges. Under his leadership, the fund focuses on leveraging commercial innovation for critical defense applications and promoting the adoption of emerging and disruptive technologies across the Alliance.
EPISODE TRANSCRIPTION
Inès Makula (00:01:14) - Andrea, let's start by defining deep tech. Can you tell us what distinguishes a deep tech company from other tech ventures?
Andrea Traversone (00:01:58) - Deep tech usually means companies that are built on a scientific breakthrough that is often protected by IP and or knowhow, often a combination of both. This means that they are based on proprietary development of technology. That doesn't necessarily mean reuse of other technologies, but basically developing of their own proprietary stack.
Andrea Traversone (00:02:25) - So that is what deep tech usually mean.
Inès Makula (00:02:28) - And in your experience, what is the most fertile ground for deep tech ideas? Is it accurate to think that most deep tech startup companies start is like a PhD post-doc research thesis in academic settings? Or have you seen different ways for founders to basically build a deep tech company? Yes.
Andrea Traversone (00:02:46) - In fact, because of the definition of deep tech, inevitably I would say that the big majority of deep tech companies find their roots in some university or research lab. Often they include PhD work by done by some of the founders, but not necessarily all the time. But indeed they do find that we do find that most deep tech companies are usually born somewhere in their past, in a university lab, in a university or a research center, or sometimes a spin out of the research center of a large corporate.
Inès Makula (00:03:23) - Usually, you know, by the nature of being a deep tech startup, these startups require a lot of upfront capital to develop their technology. How would you say founders should approach the early fundraising process, and what are some of the funding options that they should consider.
Andrea Traversone (00:03:38) - In most deep tech? Probably even I would say in material or semiconductor. Actually, most of the capital is not needed. Very early on. The seed rounds, mostly in deep tech company, are there to attract the team and define the product. Then the significant amount of capital comes in the I would say the second phase, usually around the series A, series B, you're right, there is significantly more capital needed than in non deep tech company to basically productize the technology or scale it up to commercial level. That is where the capital is needed. Often. Then in the third phase, actually the capital needs are the same as non deep tech company. I would actually say that they're probably lower in deep tech at the commercialization and scale up phase, particularly if it's a well known business model that doesn't require building a plant or some specialty production processes. Because inevitably with deep tech company, you have a much more concentrated customer base, given that they're B2B and B2C. So the spend in marketing is a small fraction compared to SaaS or fintech or digital marketplaces companies.
Camilla Scassellati (00:04:44) - And talking about the early funding, which is where a lot of our listeners will be at in terms of phase a key part of, you know, raising money, but also showing that the product has some sort of is a valid product. Founders typically need to demonstrate traction. So just to show that there is demand for their product, start to get a sense for the product market fit. So how can deep tech founders do that if building their first prototype or product is very, very expensive and they need the capital to show the traction, but if they don't have traction, they can raise capital. I feel like especially for deep tech, the initial mode is really, really deep. So what have you seen founders do successfully in order to get out of that initial, you know, catch 22 moment when I.
Andrea Traversone (00:05:32) - Hear the word traction at the early. Stage, sow seed and pre-seed in deep tech company. I get really scared the reasons such a thing as traction in deep tech at that stage. And if the entrepreneurs on this call that are talking to VCs and they hear the word traction, I would say run a mile, you're talking to the wrong audience.
Andrea Traversone (00:05:50) - So the way you find traction, or actually the way that you find third party fundable milestone for your next round of funding is basically early stage across three vectors one building a great team. And the team here has to be a team that is relevant for the challenge, for the mission, for the focus of the company. There is no point hiring a data analyst in a hardware or semiconductor company. You want someone that has designed semiconductors, so finding relevant team members with the right expertise for the company strategy. That's point number one. And advisors of people who have done it before in that sector. Secondly, it's figuring out the IP strategy, the intellectual property strategy, whether this is patents or knowhow or what combination of both, and putting that in place. And third is product definition, understanding what is the product that the market wants in a very crystal way. If you hit those three milestones and the opportunity set is large enough so the service addressable market is large enough, then I am sure that any entrepreneur will be able to raise capital.
Andrea Traversone (00:06:54) - Now, defining service addressable market in deep tech is very difficult. What tends to happen is that people look at markets top down from the total addressable market, and then they make wild assumptions about adoption percentages and likelihood. And that is just not the way to do it. The way to do is to identify actually buyers or partners, figuring out how much they could buy of the product and then aggregate from the bottom up rather than making assumptions from the top down. And that is something that, again, should be done before raising the series A.
Camilla Scassellati (00:07:27) - For example, I recently read the story of Boom Aerospace. There are startups still because they haven't productized, but they're trying to build commercial supersonic flights. So the next Concorde but would fly, you know, commercially across the United States and many other destinations. And I read that their way of them of course, building your first supersonic commercial needs a lot of capital upfront, but the way they got around demonstrating traction of product market fit was to go out and collect letters of intent.
Camilla Scassellati (00:08:00) - So go to the various airline companies and say, if we do build this product and it costs us much, how many would you buy? And they were able to get, I think in the first round something like $500 million worth, letter of intent. And that was a good way to show that there was demand. So do you think having and they did all of this with an image like a really well done 3D image of what the plane would look like? And of course, being able to answer a lot of tough questions. What would you think of that story? Do you think that's a typical way that founders go around and show their ideas through a well done 3D model of a product? If it's hardware or some sort of prototype, if it's software that they can use for first conversations?
Andrea Traversone (00:08:43) - Absolutely. That's what I meant by product definition, having a crisp product definition. So to get this letter, they had to define the product clearly enough for those counterparty to write those letters and those references.
Andrea Traversone (00:08:53) - So in a way the letters are valuable up to a point. What is really valuable for an investor is the understanding that this team knows exactly what the product needs to look like to be adopted. So in a way, it's more the process rather than the outcome of the process, rather than the letter per se that is important for an investor.
Camilla Scassellati (00:09:18) - This masterclass was powered by BCG and Bits place. Unlocking the potential of those who advance the world is crucial for BCG, and this purpose has been leading the firm for over 60 years now. Over that time, BCG has supported companies and organisations in their process of growth and strategic transformation. BCG supports startups and scale ups with the same care to help them scale faster. If you're a founder and are interested in working with them, you can email m I l the seeds at bbc.com.
Inès Makula (00:09:49) - Bits place is a boutique financial consultancy specializing in the VC world. Since 2017, it has been supporting innovative startups and SMEs, offering entrepreneurs strategic consulting services, fundraising and facilitated finance to enhance and grow their business ideas.
Inès Makula (00:10:04) - Bits place position itself as a catalyst in the growing Italian VC ecosystem. If you're a founder or an investor interested in collaborating with them, you can reach them at info at bits. Place it all the details in the show notes.
Camilla Scassellati (00:10:21) - Just to talk about that this stage a little bit more. You said that product market fit is much harder to to achieve for a deep, or it takes a longer time to achieve for a deep tech company. How long does it typically take in your experience, and what are the key steps that deep tech startups should take to effectively commercial start to commercialize their research? And I guess at that point get product market fit. So yeah, and key steps just to break it down.
Andrea Traversone (00:10:53) - The problem with product market fit in deep tech is that fundamentally, the company is always is often 3 to 4 degrees away from the ultimate market. What do I mean by it. So think a semiconductor company. So a semiconductor company needs to have the product design into a subsystem provider. Think of Foxconn and the likes who do modules for phone makers.
Andrea Traversone (00:11:14) - Then they have the product to be designed into a phone or whatever piece of hardware that it needs to be designed in, and then this product needs to be launched, as you know well, a lot of consumer electronic products or even business to business products, they get all the way there, but then they don't get launched for whatever reasons. And then once they've launched, then you have to make an assumption about adoption. Okay. So as you can see, if you are a semiconductor company, you're actually four degrees away from the ultimate demand, which is an individual or an enterprise buying the device with the company's technology in it through three degrees of separation. How do you solve for that? That's where the quality of the team comes in. And having people on the team that understand this and the volatility around this and basically know who to talk into the organizations. So the type of question that a good product manager in a semiconductor company would ask, is this module going into an existing product as an upgrade to an existing customer, or is it a new product to a new customer immediately? The chances of the second one are increasingly lower than the first one, and then I would ask, okay, what is the launch ratio of those customers? In other words, you, module maker, have dealt with your customers.
Andrea Traversone (00:12:29) - How many of their products actually make it to market? So finding the right product manager to ask the right question along the value chain is fundamental on two things understanding product market fit, but even more importantly, understanding the time lag to product market fit, which has a direct correlation to funding needs and managing investor expectations about debt. Timing is fundamental.
Camilla Scassellati (00:12:54) - Appetite for risk is always, you know, part of the game when we talk about startups and venture capital. So whether it's deep tech or, you know, just a regular startup that comes into play. But as you were talking, it is very clear that in deep tech the risk is much higher. Both of the scientific breakthrough not playing out in the way that one expected. The hard the difficulty in getting to product market fit and finding the right customers and being able to scale. So it seems like the the road to success for a deep tech companies even more complicated as an investor. What level of appetite for risk do you have? How do you plan for.
Camilla Scassellati (00:13:34) - I guess I'm trying to ask the question like, how do you assess the risk that you have in front of you when and when a founder first comes to you? Would you what are you looking for?
Andrea Traversone (00:13:44) - So so there are two points to make regarding your question. One is a general, one is a specific one. The general one is that in reality there is no point talking about risk if we don't talk about reward as well. So in my firm and in my previous firm, we always ended up talking about risk adjusted returns. Yes, there is could be very high, but if the expected returns incredibly high, that risk is commensurate with the reward at the end of it. Just looking at risk per se and in isolation makes no sense. It's always important to look at risk and reward, i.e. upside. Then when it comes to assessing risk, which was your second question. So here there are 2 or 3 learnings. One to invest in deep tech you really have to have experience is not something that unfortunately one can be trained at or learn a university or an MBA or any other.
Andrea Traversone (00:14:35) - You just have to live through the experiences. It is very much like a craft. You have to see how these things happen. Make mistakes. They often say that to train a VC in deep tech takes 5 to $10 million. And that's absolutely right. It takes 5 to $10 million of mistakes to then make fewer and fewer mistakes. And the universe of making mistakes shrinks every time. So fundamentally, understanding of each subsector is important. Risk in a semiconductor company is totally different than risk telecom system company okay or in a material company. So having knowledge specific knowledge in each subsector is fundamental. And then. Finally, once you are into the sex subsector, you have to have yourself. You have to build these quadrants that I always talk about, which is known, unknown, knowable, unknowable. So when you're doing due diligence, what are the known knowable? What are the things you know, that you can find out in due diligence and assess the risk in that quadrant of the overall risk. So you should spend as little time as possible.
Andrea Traversone (00:15:45) - And then at the opposite hand, you have the unknown, unknowable. How big is the space that you cannot figure out where the risk is and you don't know it up to that one is a very difficult risk to assess, unless you've done many deals in that sector, and unless you have a very good network of experts in that sector. And if you do, you make that unknown, unknowable space shrink dramatically. And that's when you change the odds of the returns. And that's where you can take more risks, because you have an insight on de-risking the investment for the same return. And that's what good deep tech investors do. They shrink the unknown, unknowable space a priori before investing.
Inès Makula (00:16:26) - And you have 25 years of experience investing in this space. So you must have seen so much, so many different startups. and, you know, some successful ones and obviously the ones that didn't make it. What would you say are some of the most common pitfalls that founders should avoid when scaling their deep tech ideas from the lab to the market?
Andrea Traversone (00:16:46) - So one is believing that that hit product market fit when they are over reading the signals, when in reality it's not product market fit.
Andrea Traversone (00:16:56) - It looks like it, but it's not. It's a little bit self-fulfilling because an entrepreneur always wants to be able to tell themselves, I'm there. I've achieved product market fit, I can show it, but in reality you don't. I've seen many companies having good customer engagement, telling me we are there, we're going to ramp up revenue. We're doing a growth round only for the revenue actually to go down, not up, because that design never led to a product launch, for example, as I mentioned before. So really, really being disciplined and objective about product market fit is and to being conservative a priori before starting the journey with your investors about the time is going to take to get there. And if one is honest about that, they'll find out that it always takes longer, much, much longer. And I mean longer by a, you know, by 2 or 3, sometimes five years, which then puts the pressure on the other part of it, which is the reward. If I'm asking my investor to take this risk, that is more than they originally thought that they were taking, or they're originally thinking that they take, it has to be commensurate with a potential reward that is much higher.
Andrea Traversone (00:18:03) - So spending time figuring out what the scale of that market is and how competitive this technology is in that market. Opportunity is the only way for investors to accept the fact that the journey to get there is going to take longer, it's going to take more capital, it's going to be more dilution, but the return should be there because often what tends to happen is that it takes longer and the market is never as big as originally expected. And that's where there is disillusionment, burnout on the side of the entrepreneurs and investors that don't come back after having made 1 or 2 investments in deep tech, and then just moving to other sectors where the feedback loop is much faster and more evident. And that's where traction becomes important and relevant.
Inès Makula (00:18:48) - In your experience, should deep tech startups aim to first validate, you know, their, their, their technology, what they're building by starting with like a very narrow use case and then think of scaling? Or should they immediately aim to compete in a big market?
Andrea Traversone (00:19:05) - It really depends on a sector by sector basis.
Andrea Traversone (00:19:08) - I mean both strategies are good, but there are trade offs. It's often hard in deep tech to focus in a niche and then pivot to a bigger and bigger market and a bigger horizontal sector. So in certain areas, semiconductor being one is probably better to go for the first big market straightaway. Take the risk, the high risk and high reward. I've seen very few deep tech, deep technologies in general where you can de-risk the path to the upside by taking intermediate steps is just the issue with deep tech is that they are horizontal technologies, so they have to address large markets on day one. If they are niches, the capital needed to get to product market fit for a niche just doesn't work. I tend to be more of a fan, really looking at the big upside opportunity rather than going in a step by step way in terms of market addressing, market that are small and incrementally larger. Because also remember that once you crack the technology and you address that small market, your signal to the market is clear.
Andrea Traversone (00:20:17) - A competitor will look at that figure. Rather that technology can address a bigger market and jump into the market. So there is also the issue about competitive signaling that works against you in that strategy.
Camilla Scassellati (00:20:28) - I'm curious to hear what you think, but the reason to do a small niche rather than do small niche, but maybe there's a temptation to do if you're trying to get to to, to try the easiest version of the technology first. So try with the lowest cost, lowest effort version of the technology. That will help you to prove the I don't know. Let's say that you want to build specific parts for the aerospace industry. You want to start with the easiest part that you can build to prove your technology, and then more complex and more complex, and maybe put in robots in your manufacturing and make it, you know, always more complex, if that makes sense. Rather than start with the most complex, highest capital intensive idea and then and then directly prove that. So do you think one is better than the other? So going step by step, or starting with the big idea and just trying to raise more capital upfront to get there.
Andrea Traversone (00:21:25) - I understand. I mean, I'm leaving it with an investment we're making at the moment. Exactly. With the right team, with the right product strategy, it's always better to attract the capital to go for your second strategy, which is the full big opportunity, big market, you know, full of amortization. If you have access to the market, to the funding market to go step by step. I've seen it work, but by exception, and it is super hard, so fundamentally comes down to fund ability, i.e. the ability of the entrepreneurs to attract capital similar basis. So having this equal ability to raise capital, I would always go for the big reward opportunity. First, when.
Inès Makula (00:22:08) - We created the this invite for this masterclass, we gave all the listeners who have tuned in the option to also ask some more of their questions. So not only the ones that are coming through in the chat right now, but also previously. And there's there were we've selected a few ones that were very interesting. One of our listeners asked, I framed the problem and the potential solution, but it's now time to move further.
Inès Makula (00:22:32) - I would like to understand the next steps. How do I build deep tech in Italy? I don't know if you have a point of view regarding this.
Andrea Traversone (00:22:39) - To be honest with you, geography is not a limitation here. You can build a deep tech company wherever you are. It's easier in some markets, it's harder in other in terms of availability of capital. But you know, venture capital is very global. So there are multiple investors that can invest wherever the opportunity is. So if this entrepreneur has a clear problem set that he or she thinks has solved with the technology, focus on the three things I said before I lock in the intellectual property, make sure that you have a very strong, relevant team for that opportunity. Define the product very, very, very specifically. In other words, almost do a product spec. What would be what is today's products back and what is my product spec and if it is a new product still, what is the product spec. Because another failure mode is that deep tech companies, they often build the right product spec that doesn't fit with the fabric of the industry customer.
Andrea Traversone (00:23:39) - Just do not buy that product. They buy a bigger solution or that product is embedded in someone else's product. So figuring out the go to market and the integration path to adoption is equally important. And that drives also the business model of the company. Often what tends to happen is that deep tech companies, they go to market with a solution, meaning I know what the problem is. I have a customer, I'm going to build a customer, the solution, that product for that customer. And then as if by magic, I'm going to try and sell that to all many other customers. In reality, that doesn't work. I haven't even seen you work in software that becomes a solution business. A solution business is a perfectly viable business, but often it's not a venture bankable business because the gross margin, the cost of goods sold are too high because it's often a specific solution for a specific customer that doesn't migrate to other customers. So really understanding whether you are a solution business, the way that you're building it versus a product business is another fundamental failure of a deep tech company.
Inès Makula (00:24:41) - And something very important is obviously testing the technology that you're building before, you know, launching and before, you know, doing like basically the testing phase. How would you recommend to bring onboard future customers during that proof of concept or proof of technology phase while still testing the tech? Like, do you go to a very small company in your sector, like, do you have any best practices on how to navigate this phase of the startup?
Andrea Traversone (00:25:09) - The best way is to address to bring onboard a key counterparty in the best customers you can get. Who where in the customer? And have now left. And today we have LinkedIn. You can find any anybody from any company and attract them or contact them so that this is someone that maybe was at Google or Amazon and you had this key piece of technology you want to sell to those, and this person is now left there, maybe in a startup or in a consulting job or they've left. They are in an advisory level role. They understand the product definition, product market fit.
Andrea Traversone (00:25:44) - How do these customers buy and refine your offering with their input? And then go to those big company and say, hey, I think I have something that actually would be very interesting to you. And because you will basically speak in their language, having been trained by this other advisor, you will find that they they give you the time, they give you attention because they need to innovate themselves. So there is a need for this is just about how you approach them basically.
Inès Makula (00:26:14) - And another really interesting question that came up is the communication basic communicating your deep tech startup to investors. Obviously a lot of the investors are know a lot. And maybe there is investors who have PhDs and are very, you know, or very scientific, but, you know, it can be you can also have somebody who doesn't really know your sector. And it's it can be highly technical. Do you have any advice on how to communicate effectively like really difficult concepts?
Andrea Traversone (00:26:44) - What I would advise is to communicate to investors the same way you communicate to customers.
Andrea Traversone (00:26:50) - At the end of the day, investors, unless they are for some specific reason, real expert in that specific technology. And that would be more serendipitous moment. They often are learning themselves. And so the best way to talk to them is to talk to them as customers, because that they can do they will understand problem, they will understand product specification. They'll understand where the product sits in the stack of the customer, and they will think of themselves as customers. Does this make sense or not? So I would approach it that way.
Camilla Scassellati (00:27:21) - Before we open it up to more questions from the audience. We have a few that are coming through. We wanted to discuss your investment process just to better understand how you operate as an investor, but hopefully that will also give a shed some light onto how deep tech investors operate in general. And so what are the key factors that you look for in early stage deep tech startups before deciding to invest? I know we've talked about a lot already in this chart, but if you had to break it down, do you have like a list of five things that you're really looking for? For instance?
Andrea Traversone (00:27:56) - Once again, it's sector specific, so I will not put them in a priority.
Andrea Traversone (00:28:00) - But these three factors, they are the fundamental ones in each sector. So it is the size of the market opportunity, the strength of the team and the uniqueness of the technology. Those are the key three things that we focus on at the beginning. So what we call at the top of our funnel to figure out where to allocate time, team time to different opportunities. And this sort of selection is done individually by each team member as a group. So firstly it's done by myself, my colleagues who decide where to allocate their own personal time and then when it gets brought to the whole partnership is the whole partnership. Together they decide to prioritize on one opportunity or another, depending on independent who's bringing it again against these three criteria. So it's a two layer selection if you wish, in terms of where we allocate our time. And this is a process that, by the way, is absolutely the same pretty much for every VC firm. We're not any different here.
Camilla Scassellati (00:29:00) - Yeah. But it's important to note that when a founder meets with you or any investors, important to make sure that you're really defining those three things well, and especially on the addressable market or total market opportunity, that usually is easy enough to well, the calculation in theory is easy enough to make.
Camilla Scassellati (00:29:21) - But it's important that it's made in the right way and that it's justified in the right way when meeting with investors. Otherwise, you might immediately exclude some investors because you're not demonstrating a big enough opportunity. So it's an important calculation to make and maybe remake and change the idea if you're not satisfying the right market opportunity. Right. Because maybe you think you have a genius idea, but if it doesn't sell or it doesn't have a market that you can easily calculate, then that makes it harder for VC funds to be interested. Have you seen how do you want to see that calculation? Because I it's easy to find market research and say like the semiconductor market is a $50 billion. I'm making that up market. Right. But or do you look for someone who has actually calculated the market for their specific idea?
Andrea Traversone (00:30:09) - Much better. The second one, doing a due diligence call last night with a specialist, I loved it because he was able to tell me average order size per. Estimate average selling price per product to those customers.
Andrea Traversone (00:30:22) - Market share by customer. Market share by competitive supplier. If you can get to that level of granularity, I get confidence that you as an entrepreneur know the opportunity, set who your customer is and hopefully how they're going to behave so that you can really fine tune the product market fit and your product specifications. When I see slides that say, oh, the as you said, the semiconductor market or this material market is this big, doesn't do much for me in terms of.
Camilla Scassellati (00:30:51) - The need to innovation fund. We talked about how you are different in terms of who your LPs are and how you're set up, and your specific focus in terms of how you work with entrepreneurs. How is that different from any other VC fund that operates in the deep tech space?
Andrea Traversone (00:31:07) - So since I first spoke to Inez, we added one more investor in our fund, which is Sweden. So we now have 24 sovereign wealth fund. And the way we work with them and the way that differentiate the NATO Innovation Fund across multiple dimensions.
Andrea Traversone (00:31:23) - So besides the scale of the fund, we are also what in the industry is patient capital. So we are quite unique that we are a 15 year fund because deep tech takes more capital and takes more time or regionally. Those that design the funding sound of NATO a few years ago when it was originally developed, they did a lot of great product market fit work, so they went around multiple venture capitalists around the globe and basically asked them, what's wrong with the tool used to invest in deep tech? And the feedback was consistent size of the funds and duration of the funds. And so they designed the NATO they need innovation unit that design the fund, designed the fund in a way that fits the market need. So they designed something that had very good product market fit. And now we see it when we meet entrepreneurs that they say, wow, you know, this really makes sense because I need an investor that can be with me for more than three, five, seven years. So that's the first wave of differentiation.
Andrea Traversone (00:32:21) - So this is the first different interaction that we have with entrepreneurs. We have conversations that are significantly different because we have significant capital to back them. And more importantly, I would say over a much longer period of time. The second dimension is that all of our investors are also customers of our portfolio company. So we have an adoption team inside our fund whose only task is to support our portfolio company sells into our investors organizations. And these include anything from Ministry of Defense to Ministry of Economy and Information, in some cases sovereign wealth fund. But basically all the government organizations behind these representatives are all customers, and we have a direct and proprietary access to them. And we really leverage that to basically help our company not only find that product market fit, but refining it. And then really develop the famous traction word, which, you know, much later stage VCs like to see.
Camilla Scassellati (00:33:28) - And one of another audience question was, do you see any specific segments in robotics that you think could be particularly interesting in the next ten years for future deep tech investors? But I wanted to broaden that question, actually, and just ask you, is there any specific sector where you see opportunity for more disruption and that you think are particularly interesting for founders to explore in this period of time, in this moment of history, we.
Andrea Traversone (00:33:57) - Our current focus is in nine, what we call emerging disruptive technology areas, which are on our website. These range from quantum computing, new material, next generation communication, hypersonic, and many others that are let you check from our website. In terms of robotics, robotics, for us it's under 2 or 3 of these categories. Probably the predominant one is what we call autonomy. So basically, how can you create autonomy in robotics in any type of vehicles, both ground air and subsea? And how can you leverage that? And so that is a big area of strategic interest for us at the moment.
Camilla Scassellati (00:34:37) - So there's some great questions that have come through. so Luigi is asking a lot of hardware companies face the Valley of Death after series A when the science is proven. So post product prototype, but product market fit is not there as you haven't had commercialization yet. How do you advise founders navigating that critical phase?
Andrea Traversone (00:34:57) - This is exactly the phase I was telling you about, where actually you have the highest capital needs often, so this is where you actually need to spend time identifying the investor that has the most experience in your sector or even subsector.
Andrea Traversone (00:35:12) - Why? Because they will be able to assess the signals of product market fit before commercialization. If. You're a semiconductor investors and you're looking at revenues. You have missed the boat because by that time the company is going to ramp up dramatically and revenues are too much of a lagging indicator of product market fit. So you need to focus on designing. So find a semiconductor investors who understands how designing processes work, who can assess whether you really have a designing or not. And usually by the time you have a designing you have product market fit, assuming the product is launched. As I was saying before, but between product market fit and revenue, you probably have two years. So you need to meet an investor that will see the signal of a design in as significant as revenues. Talk to your networks. Talk to the deep tech networks that are available today, and identify the investors. That can be a little bit more discerning about product market fit, rather than just looking at a revenue or traction. That is really the only way that you're going to crack this one.
Inès Makula (00:36:17) - Another question came through from Federico when is it patent mandatory for a deep tech startup in Pre-seed? I personally think that will be too early.
Andrea Traversone (00:36:27) - That's not only I agree, but I would also challenge that a patent. A patent is never mandatory for a deep tech startup. We have backed. I have backed in many cases startups that didn't have a patent. Often a patent is detrimental to the to the company protecting their technology, particularly if it is a process. So I would make sure that when we talk about this, we talk about IP strategy, intellectual property strategy and intellectual property. Strategy ranges from patents to know how and often is actually a combination, a blend of part of both. That is the perfect intellectual property strategy for that company. It is never one or the other, or very rarely I should say. I totally agree that in Pre-seed it's too early, but I would also challenge that it should not be mandatory.
Inès Makula (00:37:15) - Then we have a question from Eduardo asking when a deep tech company goes into due diligence stage with a fund, what is your advice to founders at this stage? What are the biggest mistakes deep tech founders make?
Andrea Traversone (00:37:27) - This is very much firm and almost individual by individual.
Andrea Traversone (00:37:32) - So I would focus on building conviction. So figuring out whether the firm, the individual that is looking at the deal as built, the conviction on the thesis, the investment, the team, the product and whilst the build conviction be brutally open about the risk. You know, there is this very interesting and rude term in the VC industry, which is called the oh shit board meeting. So this is the first board meeting you go to after an investment and give it it. Now you're an investor. The entrepreneur is a freedom to basically share all the risks and all the mistakes that they've made. And they usually do it at the first board meeting. That's why it's called the oh shit board meeting, because you come back to your partner and you say, oh goodness, what have I done? More and more experienced entrepreneur, have this board meeting or this meeting with the new investors before the investment. And that builds so much credibility and so much strength of relationship between the investor and the entrepreneur. That really puts them both on the same side of the table.
Andrea Traversone (00:38:36) - So I would do that as an entrepreneur during the due diligence phase. Once I am confident that that investor, and more importantly, his or her partners have the conviction to make that investment. So what is the biggest mistake is when the VCs, they found these things without being told by the entrepreneurs in due diligence, and then the entrepreneur loses all credibility and you start to wonder what else is there, even if there is obviously nothing there. And you also start to wonder whether you can build open relationship based on trust with this entrepreneur. I've hardly ever seen a process recover after that, so I would on the side of openness, transparency even a little bit over conservatism. after I've reached the point where I'm confident that I've built a conviction.
Camilla Scassellati (00:39:26) - Yeah, I guess it's tough because one wants to, you know, sell the idea and make it as rosy as possible. But the truth is that once the investor gets into the company, then you have ten years of work to do together in front of you.
Camilla Scassellati (00:39:40) - So it's important that you set that relationship on the right foot and don't over optimize, like make everything better than it actually is, because then that that comes through really quickly once you start working together. That's I can see how that could happen because we are told to tell the story and fake it till you make it and sell it, but then it's important to do it in the right way and hit the right tone. When you're when you're going through that even pitching phase.
Andrea Traversone (00:40:06) - And that's and that's why I keep telling entrepreneurs, as you shouldn't feel like you're selling anything. You're not selling me anything. We are coming. We're coming together in a joint project. Most likely than not, I will. Probably need to sign another check down the line. So what actually you're selling me is a relationship. And how do I measure the quality of the relationship? Well, it's about openness, transparency and an attitude of working together. So that's actually what you're selling me. Not the technology, the product, the opportunity.
Andrea Traversone (00:40:34) - But you're actually selling me a relationship.
Speaker 4 (00:40:36) - I'll go to the next question. Guido Valter DiDonato.
Camilla Scassellati (00:40:41) - Is asking, when can a software startup be considered deep tech? So I guess another question on what does deep tech actually mean and what are you looking for? How you do differentiate the tool?
Andrea Traversone (00:40:52) - Well, in software it gets a little bit harder, but it's still applies if, if the software is built, a proprietary understanding of some technologies, maybe a proprietary process that has been digitized through software, proprietary models developed, hopefully built on unique or proprietary data, that is all deep tech. Cybersecurity is considered deep tech, and it's for 90% software. So it's much more about the innovation of the product and the barriers to replication. So think of deep tech more in software as barriers to replication. How quickly can this software be replicated? Well, if the software is built on a particular process that is unique to this team, in a sector that is very hard to understand, in a process that is very unknown to most operators, then it's deep tech because it's very hard to replicate.
Camilla Scassellati (00:41:50) - Another definition question from me are medtech medical devices and bio enhanced devices to treat? I conditioned suspect is his startup focus also in the focus of the fund? In the fund we mean the innovation fund.
Andrea Traversone (00:42:09) - bio enhancement is definitely a thesis of our fund. So we would need to figure out what is the condition and how relevant it is in our. But definitely bio enhancement is a big area for us. There is a new paper out by nature that I think was published a couple of weeks ago around biotech. And what are the key areas of interest? And and the ones that are mentioned in that paper are, biosecurity, bio manufacturing and bio enhancement, including human computer interfaces. So those are all areas that are of interest to us.
Inès Makula (00:42:45) - We have another questions from Jonas. Being NATO, an institutional stakeholder, do you actually put so much emphasis on market attractiveness? Don't you prioritize based on strategy, autonomy and key dual use tech areas e.g. space, nuclear, AI, bioengineering, despite market not being ready in some cases?
Andrea Traversone (00:43:04) - It's a good question with a somewhat complicated answer.
Andrea Traversone (00:43:08) - So for a dual use technology to be valuable either to the defense or security sector has to be optimized. Both on cost and survivability of supply. So basically, to have a single supplier or to have a single customer doesn't actually work for defense and security. why? Because you have one or a few suppliers. You are a you often have a solution business that cannot productize their technology in a way that lowers its cost and make it more addressable. So in a way, you really want the dual use case to be both commercial and defense, because it actually works for both. Yes, we do care about, proper dual use, about commercial portfolio companies. And we believe that that is being strategic because of the reason I said. So for us that it's an important point, for a technology to be successful with our investors, our customer has to be a technology that also has commercial application, because our defense security customer will benefit from the cost down of that technology that is being forced by the commercial market.
Andrea Traversone (00:44:20) - I think it works. It actually works both ways.
Camilla Scassellati (00:44:24) - Great. I think that concludes the questions that we got from the audience. If you have any last burning questions. Right. The min but we had one last question for you, Andrea. We always like to close out on advice. And last, you know, if you have any last wise thoughts that we should all bring home, is there one piece of advice that what is the one piece of advice that you would give deep tech founders and the founders that are on this call to.
Andrea Traversone (00:44:50) - Basically think about your proposition from the end point backwards to today. It's very normal and human to start doing this in an incremental fashion and basically not ignore, but to underestimate what's coming down the line. Think about what your company could be if fully successful. How big can it get? What would it look like? What product would they sell? What is the good to? Market and then work backwards from that and be rigorous in going through all the steps and figure out what needs to happen for those steps to be successful and go backwards.
Andrea Traversone (00:45:27) - So almost do a regression your future to today and then ask yourself, are the odds totally stacked against me? Or do I think I can get there with all the grit and doing the impossible that an entrepreneur needs to do? I think that the answer will still be yes, I will do it. I will start this business and I'll go for it, because that's where the passion for the product and the technology is. But at least it sort of aligns expectations with co-founders, investors, early team members, and it provides a very clear path in a clear a very clear Northstar where you want to take the company that often changes. That's absolutely fine, but having a clear picture on day one is really, really important.
Speaker 4 (00:46:14) - That's great. Thank you so.
Camilla Scassellati (00:46:15) - Much, Andrea. Thanks for everyone for participating and asking great questions, both in the lead up as we were preparing and now in the chat. if you have more questions, I see one more from Carlota Ferrari, for instance. She's asking about how the NATO Innovation Fund works, but we'll maybe I don't know if you want to quickly answer this one under the.
Camilla Scassellati (00:46:35) - Otherwise we'll we'll wrap it up.
Andrea Traversone (00:46:38) - we we work. We operate like, absolutely a normal venture capital fund with the only differences that I mentioned, that we have a longer period to invest in our companies. We have more capital to deploy in our company. And we have this internal team that helps our portfolio companies sell products and services to our investors. So from an operating model is the same, but we have these, different capabilities that are quite unique in the market in deep tech.
Camilla Scassellati (00:47:09) - Yeah. And in terms of mission, I think you've explained it. It's on the website too, if people want to find out more. but if you have more questions, don't hesitate to reach out to us or I, and we can make sure to write out your questions to Andrea as needed. So thanks again. it was a great chat, a complicated topic, but, really helpful to sort of break it down and try to understand all the phases that deep tech founders need to be thinking about, and especially how to approach fundraising when, you know, the timeline is so much more, diluted in terms of getting to product market fit.
Camilla Scassellati (00:47:46) - And yes, you want to move fast, but you can move a fast to some of the other startups. So really interesting chat and thank you. And I see a lot of things coming from the audience. So thanks a lot.
Speaker 4 (00:47:56) - Thank you. Thank you Andrea.