Molten Ventures Plc (GROW) Earnings Call Transcript & Summary

Thank you, Shannon, and I'd like to add my welcome to everybody to our Investor Day for 2024. This is such an important day for us, and I hope it's both an important day and also a valuable day for you as well. It's interesting talking to a few people outside, getting a sense for how much people value getting an insight into our world. And I think that it is something that's particularly relevant now when you look at all the conversations we've had around at various stages of the cycles, what's been happening in the public arena, whether it's macroeconomics, geopolitical issues, interest rates, et cetera, et cetera. There's so much going on in the public arena. Our job today is to give you a glimpse into the private markets. And I said in the past, some of you may recall, I think this is my fifth one. I've done a number of you who have been here before, that in the land of the blind, obviously, the one I -- man is king. And we don't profess to know everything about the private markets and about how private markets operate and venture. But we do know, and we've got a great deal of experience over many years of how these markets and how these companies develop. And so our job today is really to share that with you. Give you a glimpse for our world and how our world operates. And we hope that, that will enable you to form a better view as to some of our portfolio -- exciting portfolio companies we have today, the model that we think is the best model to generate value out of private markets and also how private markets operate. And so that's the purpose. I think right now, when you consider where we are, as I said, a number of you would have been at these for a few years. And as we've seen the cycle start to move through, there's been an awful lot of talk about cycles over the last couple of years. And the one we're in right now is no different. The last 4 years has been an incredible Topsy-Turvy, up and down period, and particularly in this stage of the cycle. And in 2021, we went into COVID, the world went into free fall. Bounced back very quickly, not everybody was expecting that, but I think a number of people were expecting that it was going to be some time before the cost of COVID was fully paid back. But I'm not sure many could see or could look forward and say, 4 years down the line, we would be economically where we are today. And we're very much starting to pay the price for the COVID-lockdowns and what's happened subsequently. So by 2021, even a year after lockdown, everybody was trying to understand what this meant for everybody in all of these cash piles that household cash piles, we're beginning to spend people coming back to the world. And of course, this drove a huge amount of excitement around tech. And also around tech's role in the post-COVID new world order. But the post-COVID economic environment was starting to bite and household stockpiles were starting to dwindle quite quickly, but this only after there had been a drive on inflation. But also we started to see some really significant geopolitical shocks, starting potentially with the change of leadership in The White House in the U.S. But by 2022, the warning signs were definitely there. Compounded by Russia's invasion of Ukraine, February seems to be one of those months where a lot of this stuff happens. You may recall over the last 2 to 3 years, it's generally a lot of enthusiasm seems to be and excitement coming into the new year. But in February 2022, Russian's invasion of Ukraine sparking and energy crisis worries about EU's stability, inflation taking off. And inevitably, the Central Bank's response with the largest hike in interest rates in history, which changed the entire landscape for investors. But moving into 2023, we had something different. The launch of the ChatGPT propelled opportunities and risks associated with generative AI to the forefront of the public debate. And as Micky will explain later on, this isn't necessarily something new and it's certainly not something new to Molten, but it is something that we need to deal with as everybody gets very excited about these boom and busts with these -- with technology. But without a doubt, in 2023, the constant question was, when will inflation peak? Will it be a hard or soft landing? And I think there was a general view that things couldn't possibly get worse. And then they did. Certainly for our sector, Silicon Valley Bank's rapid collapse sent real shock waves across the VC community. And anyone who was unclear about the impact of rising rates on the VC space in private markets, right, it became very crystal clear now. On top of that, we had geopolitics in the Middle East, U.S.-China relations are compounding what was already a pretty grim year. So that brings us all to where we are now in 2024. Another year in the cycle. I think many think that this is a stage now where we're getting to the end of the cycle. But it definitely does continue to pose the same old questions, around geopolitics driven by, to some extent by the conflict in Russia, China-Taiwan relationship, obviously, Israel, but also election fever. So a huge amount of uncertainty are going around. And certainly, still the big question about rates -- will it be lower and deeper? Will it be lower but later? Which may mean higher and longer. These debates will continue to rage on. But what we can do, all we can do in the light of these macro challenges is to continue to do what we do best and that is to invest in next -- tomorrow's tech winners across Europe. And so with that in mind, that's what we'll be covering today, and that's how we have constructed the agenda. Now we've put the agenda together to give you really a highlight of our priorities for 2024. We have, as a business, we've navigated through cycles, and it's very important to understand that. We do understand how these cycles move. We reacted very quickly 2 years ago when it was clear that we were in the current cycle to help our portfolio companies to manage their own businesses. So today, what we're going to do is to give you a flavor of some of those exciting portfolio companies, how they're managing in the current environment, but also critically how they are planning and able to innovate while also preserving their own capital. We're also going to have a few internal sessions where we share some of what we're doing, which has been a slight change from the past. And so we'll have Jonathan who's going to talk about our fund to funds program and particularly why this is so important in helping us to build the pipeline of the most exciting companies. Ben is then going to -- before lunch, talk about our valuation methodology. Again, I think in the high rate environment, this is something that's so critical and very important for people to understand. So we think it's important for us to give you a view about how we view valuations. And then as I mentioned earlier on, Nicki from our investment team, after lunch, will give you an insight into how we see generative AI and how from a -- we're very much investment -- with thesis led investment and how that is impacted by changing technologies and in this instance, generative AI. But also, I'm very aware that as your businesses and our businesses, we all understand that this is very -- it's all about people. People ultimately generate value. And so what today is also about is to make sure that you get an opportunity to interact with us, interact with each other and have the opportunity to get under the skin of some of the presentations and how our business operates. We've got pretty much all of our team here, certainly all of our investment team and I'd really welcome them. They're very keen to meet you and tell you what they do and they -- and please use the breaks. We've got a decent break in the morning, we've got a good lunch, time for lunch and one in the afternoon. And please use that time to talk to our people and to each other to get an understanding of how our business operates and how our market operates. But I'd like to start by giving you a glimpse into -- some insight into our market and what we're seeing in the environment that we're operating on. And look, we cannot talk about our environment, we've already been talking about it already without talking about the macro factors that have had a much bigger impact on us over the last 3 to 5 years than probably they ever had. So just as I've said earlier on, rates are stabilizing. We do believe that it's -- all the forecasting is that rates are stabilizing and what that greater viability to the cost of capital 12 to 24 months down the line, that's led to a really strong recovery in the equity markets to -- in the U.S., certainly to all-time high -- all-time highs. But this market strength is also driving up expenditure by enterprises, and that's very encouraging for our portfolio companies. Companies looking -- enterprise is looking to deliver solutions for the cyber, for operational efficiencies, the supply chain innovation, and in turn, we are seeing some encouraging signs of strategic M&A. It's still early but we are seeing more and more signs of strategic M&A from corporates looking to get hold of the best and most critical technologies. And remember, 70% of our exits as a business traditionally have come from strategic M&A. So we do have IPOs, but that isn't the principal route to exit for our portfolio companies. But as the cost of capital is becoming clearer, we're seeing an early shift towards fresh capital raising. Generally, GPs are raising slightly less, and it's taking them slightly longer to close funds, which is very sensible when you consider the shortage of liquidity over the last few years. But as we're seeing this, we're also seeing investment clearly slow write-down. What's interesting when you look at the impact that higher rates are having on fundraising is when -- and the impact on deployment. If you look at since second half of 2015, fundraising has raised fairly consistently at around 1.8x per year. Now clearly, that dropped off quite significantly with the higher rates and it's dropped off quite significantly, but at a much lower -- slower rate than the rate of growth of rate of interest rates. But it's also been driven by a rapid drop in deployment. And the rapid drop in deployment really kicked off much earlier as early as Q3 in 2021. And what that's meant is that it's left lots of dry powder, capital commitments made but not deployed. And this virtual circle that we operate within the public markets where you commit funds, you deploy capital, you return capital, and you recommit funds, that works very well until it doesn't. And when you get a blockage, the blockage at the moment is in returning funds and realizations. When you get that blockage, then the whole machine slows down. And so this is creating a real problem for this virtual circle of continual funding for private assets. But it's also important for us, we can't control the macro factors. We have more control over some of the micro factors. So I think it's also important for us to focus on some of those things that are closer to within our control. So within the portfolio, we've seen a consistent reduction in expenses as measures were taken 18 months ago and into last year has resulted in extended cash runway, which has been very, very important in an environment when there is -- we're short of liquidity. But we've also been very careful to make sure that these expense reductions are not at the expense of growth or margin. So holding margin and holding the growth as much as possible has been something that we've been helping portfolio companies been doing. So we've been working with our founders, many of whom not worked and not managed businesses through a down cycle to focus what's important to be disciplined around cash management and having a clear picture around how they move their business to a cash-positive position. But also what's really important for them, what the company needs to look like, what the fundamentals need to look like, in order for them to be able to raise new capital, ideally flat, but obviously, ideally at an up grant, but a minimum of flat. So we've been helping portfolio companies to understand what they need to look like in order to be able to raise that capital if that's what they need to do. But critically, we also have to encourage them to continue to innovate. And I think that's really, really important because all of our companies are disrupting and innovating and they have to continue to do that to be able to continue to create value. And you're going to hear from a number of those today about exactly how they're managing that very fine balance. But it's also important for us to understand what we have to do within Molten as a plc and for our investors. And we've been very consistent in that we believe that it's possible to manage NAV growth of 20% per year through the cycle. When you look at the last 8 years since IPO, we've actually been able to deliver 30% and also generate cash returns and generate cash returns is also critically important for investors. And again, we set a target of 10% per year of the opening our portfolio. And as of September last year, we were delivering 16% per year since our IPO in 2016. And I think it's very important for us to remain clear that NAV growth and that cash generation are really important elements for our investors, and it's something that we focus on a lot. Now I'm very clear also when we talk to investors, we talk about this on a rolling 3- to 5-year period because, of course, exits NAV growth doesn't happen on a neat calendar year. But through the cycle on a year-on-year basis, our delivery of NAV and our delivery of cash has been above where we would expect -- where we are targeting. But you may ask how do we believe we can continue that in these very difficult economic times. And we believe that we can continue to deliver that for a number of reasons. One is that tech continues to innovate, disrupt and deliver real value across the whole value chain supply chain the way we live, the way we work, the way we operate our lives. And so we're very confident. And you'll hear today about why we're confident that tech can still deliver a significant value. And as markets have shown over the last they've shown public markets showing really a year of game now, very much driven by tech in the U.S., obviously by the Magnificent 7 doing a lot of that growth with their very strong results last week. But in private markets, particularly venture, they tend to lag public markets. And so once we see the shift in the macro environment, we will catch up with that lag. So we do think that there will be -- that public market, there will be some pull-through into private valuations. We're already starting to see some softening of valuations over the last 6 to 12 months. And we also believe that we'll see a greater pickup in M&A activity as this public markets lag starts to come through. But over the first -- the past 3 downturns, the greatest value has always been generated and creative during the crisis period. So we also have confidence that VC as an asset class can continue to outperform other asset classes over time. Now on this chart, we've taken an average of IRR performance over -- for 10 years' worth of fund vintages with each a private market and VC is a clear outperformer. Now being at the higher end of the risk spectrum, we understand now that we have to deliver real alpha to outperform fixed income. But even against private markets, VC performs better than PE, better than private debt, and better than real estate over time. But in order for us to be able to capture this value and to deliver that value, we have to consistently devolve and evolve our model over time. And over the past 12 months we've made some real progress in that area. We are very close to the completion of the Forward Partners acquisition. We have some of the Forward Partners team here with us today. I'm sure they'd be very happy to share their views on the market we do as well. But this is really important for us because it fills a gap in our own model. Not only does -- do they have a very interesting set of portfolio companies at a slightly earlier stage, which gives us some interesting follow-on opportunities. But also what it brings to us is that investing capability in that earlier stage investing. And I'll talk a little bit about why that's important later, but this provides us investment capability, provides a nice gap -- a nice bridge between our fund of funds, which is predominantly seed, and our traditional investing, which is traditionally more in the venture growth space. But we're also live to the opportunity to being able to participate in really interesting pricing deals at the moment. I mean clearly, the secondary market is with reduced liquidity, price is depressed. And as I said before, because of that lag that liquidity is not going to change anytime soon, and that presents us with some really, really good opportunities to pick up good assets at very good prices. And we will continue to do that. We have one running at the moment that we're nearly close to closing. And obviously, we'll give you more details of that as it happens. But we also to grow -- continue to grow our third-party assets. We launched and funded our Irish fund over the last 12 months. We've grown our EIS and our VCT businesses, and we've completed our first syndication deal for our Fund of Funds program. So building third-party assets is something that's important to us as well. And in that vein, we continue to work on our Eastern European fund. And Bakhrom is here today. He'd be very happy to talk to you about our plans for our recent European fund, but also our climate funds, and we're looking to launch a secondary fund. So a specific fund that will take advantage of those secondary opportunities that we think, particularly for the next 12 to 18 months, there is going to be huge opportunity across the VC market across Europe. Elsewhere, we're continuing to work with government bodies as the market continues to develop, like the British -- the BVCA, the British Private Equity and Venture Capital Association, to facilitate improved access to venture capital. So we're one of the 20 signatories of the Venture Capital Compact that was signed at Mansion House with the Chancellor to try to generate the ability to deploy defined contribution, pension fund, money into venture, which we've opened in the long term, we're very positive about. But as we start to look ahead to the next year and we look to an environment where rates look like -- certainly, the forecast are that rates will stabilize and maybe drop. We think it's very clear to say that we don't think that we've got to the bottom yet. We think that there may -- there is still some pain to come, but we're very close to it. And we do believe that when we look back in a number of years, we'll say that this period, whether it was last quarter, this quarter or next quarter, was the time that the market really turned. And so therefore, we have to prepare ourselves for the recovery and to make sure that we're in the best possible position to grow when that recovery really starts to come through. And that's why we continue to invest in companies, exciting companies such as IMU Biosciences, which we're going to hear about later on, but also in Morressier, and 2 companies we've announced in the last month that we've made 2 investments, very typically different investments, very different investments, we're very diversed by portfolio. One is a Berlin-based Series B and other is U.K. spin out from a U.K. university in a Series A. So we will continue to invest in tomorrow's winners, and that's very important for us as we go into the next stage of recovery. So as we start to build the platform across different stages, the risks and our focus does change because it changes across stages. And we're very aware that in tough times you should focus on what you're good at. I mean you -- what I tried to show here is a chart that shows the different levels of risk that you see when you get across -- can you just go back to the next slide -- previous slide, sorry -- you get the various levels of risks that you get at the various stages. So the start-up journey through its development pre-revenue into then post revenue, which is shown on the red line, and it scales through revenue acceleration, the business grows and the risks start to change. Now I've not put, people tend to talk about Series A, B, C, et cetera, and values. The reality is that, that's all been a bit skewed over the last few years. We've seen -- traditionally a Series A would have been maybe GBP 5 million to GBP 7 million. We saw early bid, one of early birds companies [ Alfalfa ] did a Series A EUR 500 million earlier on this year -- at the end of last year. So the round sizes can be -- the round letters can be somewhat misleading. But the early-stage businesses do have different characteristics, and they do have different elements of risk. And so as you see at the early stage, it's about -- it's much more about proving the concept and building flexibility. Then it goes through into the growth stage, which is much more about execution and scaling and then it goes into the more mature stage where again, there's another set of risks. And for us, it's very important for us to be able to manage those different risks and different skill sets. And so that's why one of the reasons why the Forward Partners deal makes sense for us because managing those slightly earlier risks for those early-stage investment sits quite nicely with our overall platform. When you look at the middle line there, you can see our Fund of Funds where we invested at generally the seed level, plc through the middle, and then our follow-on opportunities, that's broadly how we invest. But from a capability perspective, where ours is traditionally in the middle, the early-stage investment, but also the third-party capital that we can attract is something that's very important for us. What we're trying to do is to build a model that enables us to be able to invest across the stages because in the new world that we're in now, businesses are moving through the stages at a different pace. And whereas maybe 2 or 3 years ago, they have gone through seed, through an A to a B, C, D very, very quickly. We believe in the new world, that's going to take more time and therefore more support from us. And so building that capability and be able to invest across the various stages is something that we think is very important for our model and we continue to build out the model. So finally, I mentioned earlier that a lot of this is about people. And sometimes when we talk about markets and we talk about models, and particularly we talk about numbers, people, it's very easy to forget that ultimately, this is about people, it's about decision-making, it's about how people make decisions. It's about stability, it's about professionalism, it's about commitment of the best people. And we -- at Molten, actually have a very clear purpose. We've got good alignment across the team and we've got very good diversity of thought within the business. And we think that that's something that enables us to make consistently good decisions and to execute well over time. Many of us are here today -- as I said earlier on, many of the team are here today, and I think it would be really good for you to meet them in and to get a sense for what makes us tick. But I think the other thing that's really important is that we believe that our founders, and ultimately the founders and the management teams we invest in are where the ultimate value is created, of course. We think it's really important for us to do what we can to help them come together a number of them here today. Again, I would ask you to take the opportunity to speak to them. We had -- managed -- we did run our second founders Summit in last September, some of it being appropriate works. It was in the Alps. And we've built the founders -- gave an opportunity the founders to meet and to be able to share ideas and to help each other manage through a very difficult time in the cycle. And I think that's something that we also think is very, very important. So not just our people, but the people we invest in is something that we focus on very much. So that comes to the meat of what we are here today. I really appreciate your time today. I know everybody is busy, the markets -- everything that's going on is a very busy time of year, but we really, really do appreciate you taking the time to come and hear from us and from our founders. We've got a really exciting group of companies. Some you will have heard before, some that you won't. But I think it's a really good mix. And as I said earlier on, we'll mix it up a few with some of our own presentations.

So we've seen a real breadth of our companies this morning, all exciting and driving innovation. But as much as how do we evaluate these businesses, particularly when you've got a range of these companies. The process is very important because it reflects on our public market share price. Clearly, we're trading at the moment with a discount to that price. So it's even more relevant in some respects. And the fact that we're daily traded is distinct in that respect to other venture funds. We do follow similar guidelines to our funds. I would say that we're following the accounting principles on the right side here, the IFRS and we're regulated, so we have the principles coming from the regulator under AIFMD. But the commonality of all of the valuation guidelines comes on the International Private Equity Venture Capital Guidelines. And what we put in the colored boxes here is just an overlay of what they are. And they're not all entirely relevant to our portfolio because we have private companies and private companies don't trade every day. So there's different aspects of the analysis you need to look at. So at the very top of this here, actually, Jonathan touched on some of this earlier, with the net asset value of underlying funds. This is funds that we've invested in. So if you consider the fund-to-fund program where we've invested in almost 80 funds, they will report to us on a quarterly basis. We'll look through those numbers to look at the underlying approaches of those companies, those managers as well. And then that gets brought into the value of our portfolio. Quoted market price is not relevant to us right now because we don't have any of our companies listed. We were invested in trust pilot that went to listing, as an example. We then held that for a period of time in the public markets. And that's very easy because you've got a daily traded price to look at. So it just mark it to the price at the balance sheet date. And then we get into the techniques that are more reflective of what we have in our portfolio. So if we look at calibrated part of recent investment, this is what everybody used to know as last round price, but it's calibrated price of recent investment and the distinction being you have to reflect through changes since around that occurred in either the market or so the company's performance relative to its projections at the time. And this is a change in IPEV guidelines from a couple of years ago, and that's a crucial part of why we're able to reflect changes in public markets into our valuations very quickly because we don't just leave those companies on the last round price. We have to move them relative to those two aspects. The other most important part of what we do is similar in some respects because you are looking across the public market comps. This is the earnings or revenue multiple. In our companies, the majority of them will be driving revenue and revenue growth that won't necessarily be profitable, and the majority of those won't be profitable. So the multiples that we will look to will be enterprise values against revenue multiples. And that's by -- for each individual portfolio company from we have to go through every single company in our portfolio, which before we complete the forward transaction will be about 80 companies. We have to look across to a peer group of public market companies that are relevant to them in terms of their sector, relevant in terms of their profile of their financials as well. So their gross margins, for example, we'll have to look across and create a comparable set. So these rules around how we approach the valuations. Future market transactions, we don't tend to focus on, that's looking at obviously where a company is in an M&A process. But that isn't something that we tend to focus on. We focus more on the fundamentals of where the commercial traction is in the business out of the balance sheet date. So that's all well and good, but we have to have some governance around those processes. Valuation is clearly the biggest risk to our business. We don't want to get that wrong. We want to ensure that our investors are understanding our approaches that they're understanding the value that we ascribe to the companies. And why we're ascribing those values. And in our reporting, we try to make sure that there's enough information there to get that across. But clearly it's not a straightforward process where you can just take a screen price and validate what we're doing. So we have to have a lot of governance around the structures that we have in place. We process our valuations internally. We keep that separate from the investment team because that's what the regulations and the guidelines push us to do, but also keep the level of pragmatism in terms of how we look at and review these companies. We get a lot of information coming through from the investors that sit on the board, but the actual process of delivering the valuation is done through the finance team. Alongside that, we have every 6 months when we put out an updated valuation, we have an audit from PwC. And so that's 1 level of external checking that goes on within our process. Alongside that, from the Board level, we have an independent board, and we have nonexecutives on the Audit Risk Valuation Committee that go through each of those situations at the valuation as well. So for every 6-month period, we have both the audit committee and our auditors reviewing what we do. And then in the third box, the third row that we're looking at here, we have corporate events that drive another layer of checks so we have a debt facility in place, which the lending banks, both JPMorgan and HSBC, have the right to have an external validatory check on valuations as well. And that's happened a few times through the process of having this facility in place. And then the most recent check that we've had related to the acquisition of Forward Partners. Part of the regulations around that require us to -- through Rule 29 of the Takeover Code requires to have another external check on our valuations, and that was therefore, a firm independent of PwC, who are our auditors, and therefore, not considered independent. And so we had a process with Deloitte that ran through November and December last year, and then led to a 2-page opinion from them, supporting the numbers that we've been publishing that went into the scheme document. And so these are all important areas of validation, external validations of what we do, but I'll go through some of how that translates into the numbers that we've been publishing in the market. There's 2 sides of this chart. On the left-hand side, this is how we've applied those techniques. I went through on the first slide. The light blue, we can see about 38% of how we valued the portfolio. That's on earnings and revenue multiples. So as I say, principally the revenue multiples, looking at the comparable basket. So it's again reflecting public market movements into the portfolio of companies. The green-shaded area is the Fund of Funds, about GBP 130 million roughly, slightly more of that is what Jonathan was presenting earlier, the Fund of Funds program, and the remainder is in funds like Earlybird where we're in now being underlying funds. And again, we're looking through the underlying funds looking at their processes, looking at the companies where those companies are significant to us, we will value them ourselves. So we make sure we've got clarity around those aspects of the process. And then the -- I guess, salmon pink shaded area, we have 45% of the company's valued on this calibrated price of recent investment. And just to give you a sense of those, the next pie chart is showing you how many of those have been calibrated and therefore moved away from their last round price. And how many have been held at the price of recent investment. And it's just 1/4 of those. And those will be the transactions that have occurred pretty much broadly speaking, over the last 12 months and therefore, in a relevant market environment. And as we've seen, on the very right-hand side, our valuations have grown over time as we've invested in new capital, the NAV has grown and NAV per share. And then as we've had a falloff in the market, we've quickly reflected through the changes in public markets into our underlying assets. There's a few structural parts to how we invest that I'll go through in a moment, but you can broadly see from the period FY '21 moving into FY '22 as the market dropped, we moved our enterprise values of our companies, on average around 40%. That doesn't translate into a 40% reduction in our valuations, our fair value of how we hold the company. So I'll come on to why that is in a moment. But it is a significant movement that occurred effectively in the public markets and therefore moved through to our valuation process. This slide gives a lot of detail on here. I'm not [ expecting them to be ] able to read it, obviously, but this is 1 of the tables that gets reflected into our reports every 6 months in the financial review section. And this has all of our core companies, which is 17, and they represent around 65% of the value of the portfolio. And then it has 1 line for our remaining, which we call the emerging portfolio. And again, we're blending different maturities of company. And what we're showing our public market investors is the ones that are most relevant to them. These are the ones that are currently driving the value and have the most materiality. And this process, I should say, is the same for the PLC as it is for the EIS and the VCT assets. So the same valuation approach and the same underlying valuation of those companies where each of those pools of the capital we invested across. But the important aspect of this chart here is to show you the cost of invested capital. And the reason we think that's important is because our track record of delivery ahead of that cost is around a 2x mark over time. And where you can see the portfolio is valued at the moment is at a 1.6x in aggregate. So GBP 824 million invested against GBP 1.3 billion of portfolio value. And if you then bifurcate between the core, which is where we have uplift in the value of the portfolio and also looking secondly at the emerging portfolio, you can see that this GBP 500 million of invested costs in that emerging bucket that's held at 1x cost. So I think that's an important consideration, 1 relative to our current market cap, but 2, looking at venture performance. And the third part of why that's important, I'll come on to in terms of the structure of those investments. Quite rightly, someone when I was talking to them about this on one of our investor roadshow said, when did you invest that capital? Because clearly, if you invested it all in the peak market, then that's a different equation. And so the chart on the right-hand side is showing that consistency of investments over the last 7 years. In that peak period, I think on that chart, it's showing us '22. A lot of that capital we invested went into our existing portfolio. So that's also been important for understanding that those are the companies we understand best. Those are the companies where we see the upside potential in that journey, and then we can put more capital to work. So being able to double down in our winners is an important part of the evergreen balance sheet model. Coming on to structure of investments. When we deploy capital, we'll invest in a preference share. And this -- the preference share structure is very common in private markets, particularly in venture capital. They're probably less common in public markets, and therefore they take a bit of explaining. And what we've done here is to demonstrate a scenario on this chart on the left-hand side, that's a company that's raising GBP 50 million of capital at a GBP 200 million pre-money value. So the post-money value will be GBP 250 million. And what we've shown on the left-hand side of the axis is the multiple of returns. So at the 1x return, you can see that from GBP 50 million all the way up to GBP 250 million, that's your 1x return. And the important part of looking at that analysis is to see that we have downside protection in those values. So when I talked about flexing the headline enterprise value of those companies, 40%, actually, our underlying fair value only moves around 16% because of this downside protection. We can move the value of the company from GBP 250 million and let's say the market moves 50% down, we can get down to GBP 125 million, but our cost of investment is still protected. So that's very important when you think about GBP 800 million plus of invested cost downside protected. And I think that's a very stark a way of understanding the venture capital model. It is a portfolio approach to investment. It is a model where the returns are skewed to the winners. But because of the fact that there are risk aspects to this, then you protect yourself for mitigating factors. One of those mitigating factors is the structure of preference share investing. One of those mitigating factors will be sitting on the boards of the companies having the governance being close to them and being able to affect their journey. On the upside, importantly, you share the returns. So the preference shares effectively fall away and your upside is treated like ordinary shares. And that's quite crucial to understand that you're not capping that upside. The right-hand chart that I've shown here is what we have in our investor presentation, which is showing you how many companies in our portfolio have this structural protection, and it's 97% of those companies. So again, looking back to that GBP 800 million of invested cost with downside protection, that's an important feature of the model. This is another chart that we show as we present to investors. And this is demonstrating the over GBP 520 million realizations of capital that we've had in the last 7 years since we've been public. So the governance around your valuations, the processes you do, all of the -- the analysis that demonstrates your valuations relative to the market, all well and good, but it's a "show me the money" scenario. Everyone wants to understand when you realize companies, how much capital you bring back and how does that look relative to where you're holding them previously. These returns, we put them into 4 brackets. The first is less at 0x, so we get 0x, less than 1x. So those 2 brackets together, if you look at the percentage of invested capital, 36% of our invested capital is getting is less than 1x our money back. But you can see these are very traditional venture returns and that they're very much skewed to the winners. So on the right-hand side, more than 3x coming back, that's GBP 380 million of the value that we've generated. So the ability to run your winners to stay in those companies to double down on them as they scale and progress is very important. And what you'll find with us, Molten as a firm, we spend a lot of time in those middle 2 cohorts because that's where we can feel that we can affect outcomes, and that's where we feel we can drive value. And that as a fund is very important when you look at the fund returns, the amount of capital you can get back from those middle companies. And as you've seen today, all the companies are exciting. They're all driving innovation with underlying technology. So they're valuable to somebody. It just might not be growing and scaling at the speed that we need them to do. This is a very [indiscernible]. But it's important is because this is where we've held the valuations of each of those exit companies before we exited. So you can see over time they'll move up with rounds of financing that they have or changes to the market, but it's showing the commercial traction over time. The important thing is when we exit them, we're selling them above where we've been holding them in the books. And we don't get it perfectly right all the time. You can see on the very high green line there that was a listed stock. So by then, it's listed, and we're not in control of any of those pricing points, we're not valuing them ourselves. As you can see, in the majority of cases, we've got a good track record of holding these companies such that when there's good news coming, we're behind the good news. And then when there's bad news coming, we're going to be ahead of that to start taking them down early. And hopefully that can give all of our investors across all of the capital platforms confidence in our approach, but also in the NAV that we put out every balance sheet there. And so I'm going to just finish on the last slide, I'm conscious I'm in between everybody's lunch with a case study of how that works in practice. On the left-hand side, we have the valuations of our company over time. The last round price is the blue bar, and then the multi-enterprise value is the pink bar. The line in the yellow is our fair value. So that's where we've held it as a value to us over time. And then the green line is the comps multiple. So where we've applied comps multiples with how that's moved and come down over time. And you can see the story of this investment is that we held it at the last round price validated by the market with third-party capital coming into the company. And then as they've raised a subsequent round at a much higher valuation in the period of 2021, where the multiples that were being applied were much higher. We've decided that we'll actually wait a bit longer for that commercial tractions to come through. So we'll see the revenue proof points coming through in the business. And so we've held it at a discount to the value for last round. And you can see our fair value has gone up, but we're holding below where that was. Moving forward, the market is actually reduced in that period of time in terms of the comps and the multiples. And so we've then brought that valuation down in line with the market. So the last round price of the middle of '21, that's going to be -- is no longer relevant to us. We're just looking at the market and looking at the delivery of those types of businesses in the market. That business has continued to deliver. So it's continued to grow and it continues to grow its revenues. And you see as we get our enterprise values flat on the green line, the implied comp for multiple that we're applying is reduced because the revenue of that company has continued to grow. And I think if you see on the right-hand side how the market has moved when using here the Goldman Sachs's non-profitable tech index as a proxy. You can see that those movements in valuations and us being able to track that market has been an important part of making sure that our valuations for the underlying business are prudent, and we're making sure that they're within a range that is anchored on the realities of the day. So I'm sure with that, as always, we'll have questions, but I don't want to stand in the way of everyone's lunch. Are we moving straight to lunch? [Break]

I've been given the unenviable task trying to distill and probably dramatically oversimplify the very deep work that's going on across the team in AI. But what we wanted to do, I mean no question, there's been a huge amount activity. So I might say, hype cycle since we all last met this time last year. So what we wanted to do is try and put a little bit of context around that from a macro perspective and to kind of tell you a little bit about how that informs our approach to investment. Disclaimers. So what is AI? Shannon to just keep an eye on my notes there. Thanks, Shannon. Look, you've heard this Martin's referenced it a number of times. And most people in the room will well know this AI is not a new technology. How we define? It's the science of making machines perform human level tasks. And really, these are algorithms that have underpinned much of what we know of the software industry. For the last 10 years, we all interact with and engage with AI on a daily basis, whether it's face ID on our own phones, personalization of our social media feeds or the ads that we see, even the banking transactions that we go through and the fraud detection engines that underpin those. So it's not new. So why are we all talking about it today? I mean you've heard directly from some of the CEOs who will give you a lot more of the color on the real-world examples, and it's brilliant to be following Armando, who can actually bring a lot of this to life. We have seen a huge way of interesting capital flows. So what's changed? In 2017, Google published a paper on Transformer Architecture, right, which was a new approach to neural networks that dramatically improved language understanding. That has inspired this sort of wave of R&D into LLMs that we've seen over the last few years, which has really been the basis of generative AI or Gen AI. This is we look at generative AI as a sort of subset of the wider AI market, but what it really means is that these are models that can create new data. Data is based on the patterns that have been learned from the data used to train those models. This research combined with massive changes and acceleration in compute power and infrastructure, explosion in data and access to data over the last 10 years and ever increasing complexity and capability of algorithms has kind of created this sort of perfect storm. But while much of this has been happening over the last 6 to 7 years, I mean, that's the true reality of generative AI. 2022, we did see a step change, and that was when OpenAI released ChatGPT, and this was really, for the first time, a front-end put on AI technology. It was the first time that this -- the power of this technology could really be seen and could be touched, it could be accessed, and could be visible and could be played with by anyone in this room. I didn't ask ChatGPT to write my notes for this speech, but I kind of probably should've seen where they got me. But what ChatGPT did was sort of put access to this technology into people's hands. So I want to talk through the details of this slide, but suffice to say, this is a technology that has been evolving for 70-odd years. And there's been continuous breakthroughs in AI over that journey. And that's what it is. It is a journey of AI getting closer and closer to human capability. And that really gets crystallized in our minds. These developers that are working with this technology every day. But in our minds, that gets crystallized in these real-world moments. The first of which was back in 1997 when IBM's Deep Blue Supercomputer beat Kasparov, the World Chess Champion. I mean that got people talking about AI really for the first time. And it was kind of widely considered one of the first indications that AI was kind of catching up with human capability, human intelligence. And what we're seeing with this kind of latest iteration of AI, in particular, with generative AI is while AI has been evolving with human intelligence, it's now starting to match human creativity. And I think it's this combination of sort of intelligence and creativity that's driving a lot of the excitements that we're sort of seeing in this space. And I won't talk an awful lot of this, but a lot of the developments we've seen have come from the fact that many have taken an open-source approach. And what that has meant is that this technology has been able to sort of taken out of the lab, the research papers and actually put into the hands of global communities of developers. And allowed global communities of innovators and developers to play with this technology to work with it to figure out how to use it within their own businesses to build new businesses. So AI has been made more accessible in the last few years or the last couple of years and made way more cost effective to access. And that in itself has driven this sort of acceleration and pace in model development. Now a lot of that development has been around foundational models. Armando touched a little bit on this. These are the LLMs or, in some cases, text to image models. And these are the models that are trained on very, very wide, broad spectrum generalized data sets, maybe the 10% that Armando sort of referenced, but generalized data sets. They're highly compute-intensive and highly capital-intensive but really sort of form the base layer of what we're sort of now seeing as being the value chain of AI where opportunity is going to come. And the question what we're starting to increasingly see is more specialized and vertical focused LLM and foundational models. So 2022 brought AI more mainstream. And this was kind of combined with a couple of reasons. The technology was got into people hands, as we said, and of course, people are going to do what they do and use it and test it and play with it and figure out how to use it. Combined with capability, this top line here is images from mid journey. This is a 15-month progression of image quality for mid journey. With the image on the far left, being mid journey was creating in Feb '22 for 15 months later, the same front developing that level of image quality. So the combination of that capability and the accessibility has really put it in front of people, my personal favorite, was what became known as Balenciaga Pope. And this was the pope seen snapped in the Vatican wearing a Balenciaga Puffer Jacket. So many of you may have seen it. This went viral in early 2023 -- is actually what we consider to be one of the first, it may be whimsical example, but 1 of the early sort of examples of disinformation. And it genuinely had a lot of people kid of fooled that the pope without/with his Balenciaga jacket. But I think the point is that when images like that go viral, people start to see, people start to understand, it brings AI from the realm of developer and engineer community and sort of deep tech companies into the hands of consumers or frankly on to the front pages of mainstream media. This economists cover from June 2022, which actually was the first AI-generated machine -- AI-generated front cover by the economist, and that was published at 5 months before ChatGPT came out. So it's accessibility, it's visibility. So what does this mean for our portfolio? We've been investing in AI and around AI technologies for 10 years. You've heard from many of the entrepreneurs and I'm not here to tell their stories because you're going to get a much better picture and a much greater understanding of what they're doing for speaking to them directly. But I think what this indicates and what we try to do here is that this is a selective and something not exhaustive list of companies that sort of are operating in and around the space. But it sort of gives a picture of sort of how we break it down in the portfolio. So the color coding here references the difference between what we call AI first companies. These are businesses that are directly producing or developing AI tools or infrastructure to AI-powered companies, those that have AI as a key component in their products, like you heard from Armando or AI powered, which is -- or AI enhanced, I should say, which is products that sort of leverage AI to enhance what they're doing to drive better efficiency or to drive sort of new product innovation. And as you would expect, I mean, the founders that we back are naturally inclined to embrace new technology and to test, and they will always look for ways to innovate. Again, really convenient to be following Armando who's really -- who's launching now a new product off the back of what generative AI is enabling. So I think we're seeing some really interesting examples, not just sort of the wider AI applications but specifically generative AI within our portfolio. Other examples what [indiscernible] are doing and taking the kind of one-to-one clinician to patient healthcare model in therapy and scaling that using AI as a sort of a copilot and the scaling engine or a material exchange, another business who have developed Frank, who has introduced to us at a Board meeting, and Frank is a Digital Sales agent built on ChatGPT, trained on their own CRM and e-mail and all that unstructured sales data that they have in their own business and they're sitting along the sales agents automating an off a lot of the presales and sales tasks. So even within the portfolio, we're starting to see some really exciting examples. So what does this mean for the investment opportunity? It goes without saying it's a key theme across the entire investment team. And our expectation is that AI will be the dominant technology that sort of underpins the software industry sort of over the next sort of decade. But like anything with a platform shift, what we've seen thus far is that it's been -- it's a horizontal technology. And a lot of the focus has been on sort of the enabling infrastructure that ultimately will power the real-world use cases. And so what we're focused on is now as we move from that sort of horizontal approach and that infrastructure approach to AI, what does that mean for vertical applications and industry adoption of this technology. And this is where we start to sort of build our investment thesis. So whenever we start with an industry or with looking at a new area, the first important call for us is sort of mapping the value chain and understanding sort of the tech stack of what we're looking at, really with a view to deciding where do we think value will accrue. What do we think the underlying dynamics are going to be, where do we think investment will flow and where do we think there's going to be opportunity? And it goes without saying that generative AI tech stack largely maps the software tech stack with the addition of the sort of foundational models and the intelligence layer, which we, sort of as I said, we consider almost like the sort of hardware infrastructure or the enabling infrastructure. But this middleware and application layer historically where we've focused a lot of our software investing is where we see a lot of the most interesting opportunity, right? How will these models be assessed? How will they be accessed? How will they be fine-tuned? How will they be orchestrated and ultimately how they will be built on and embedded into products that will be sold and focused on sort of key industry applications to solve very large real-world problems. And that's kind of where each of the investment teams are sort of spending -- spending their time. But despite the high cycle and the headlines of really large brands and -- of which there have been many over the last year, we're still really early in seeing the application of this technology. The green bar here is sort of the wider AI ML market. And what you see there will be -- we'll capture a lot of what we do today, a lot of algorithm-based sort of software investments or some of the infrastructure that we've seen. But we definitely saw a big uplift in generative AI investment activity starting in 2021 and really peaking in sort of 2023. So it's become a significant theme. And what we expect over time, these lines will just blur, right? It will not be sort of the historic AI industry and sort of the gen AI, this really will -- it's kind of an evolution of where we see the software industry. I think the thing that's really notable in this space is how much of a role that sort of incumbents and big tech have played in establishing the infrastructure perhaps it kind of comes as sort of no surprise. But our view is very much that the AI model market and infrastructure market will mature into sort of an oligopoly market, much like we've seen in sort of the cloud space where value will kind of accrue to a sort of smaller number of kind of high value players with the exception of a few new entrants in the space. But this is an example of some of the investments in Open AI and Microsoft case and acquisition, but some of the investments that have been made by big tech. And so we have seen a little bit of an arms race. And it makes sense. This is a -- this infrastructure market is hugely capital intensive. And so these players can bring massive access to compute power, not just compute power, but distribution via their own platforms. And it's really been where we've seen a lot of the activity sort of concentrated. But where we want to sort of spend our time is the kind of understanding the development and the commercialization of this technology and the applications that are going to make a really meaningful difference. With in early gen AI, what we've sort of seen is the early use cases around kind of consumer-facing tasks. We've seen automated code generation, copywriting, video editing, movie scripts being written by ChatGPT. So really significant developments, but sort of arguably sort of lower states. We made -- we were having a conversation in the office sort of last week when one of the guys made the observation around where we are in comparison to the smartphone wave, which is after the first iPhone was released, the earliest application that everybody here was playing with where simple, highly functional clock applications, alarm applications, calendar applications. But very quickly, when you put the power of that technology into people's hands, we started to see really much more complex apps end to end, but this is where big, big businesses have been built. And I think we see this as being kind of where we are in this generative AI way. We've seen some really interesting and fun use cases, but actually increasing activity in sort of vertical AI where we think big businesses can and will be built to solving very real world problems. And I think -- that's an important point to note. I mean we -- as we stand up here, we don't talk about it, and it would be wrong with me to talk about AI thesis. We don't -- our job is not to build a thesis around the technology. I mean our industry is littered with people who make the right bets on technology, but their own bets about how that technology is going to be adopted and the scale and the size and the speed of real-world problems that it will solve. So that's a theme that's across the investment team. So whether that's Inge looking at the HealthTech space and how this technology will be used in HealthTech or how it gets applied to the clean tech industry or in to Fintech, I think that's where individual thesis are built on industries rather than sort of a broad horizontal view on AI. And I don't think we could talk about AI without talking about the AI debate. This is obviously a really deep topic and something that we could probably spend a day on or longer if you're the U.K. government. But really this refers to -- this isn't going away, and we are constantly going to see and have discussions around AI and its ethical use being kind of one of the -- sort of the key topics, and that means that are their biases and built-in algorithms. Biases built into the sort of base data on which these algorithms are trained. How do you see it? How do you understand it and how do you manage for that? No question -- the misuse of AI is an incredibly powerful technology. And whether it's Balenciaga Pope or whether it's actually some more sort of nefarious -- more nefarious things that we're going to start seeing emerging, perhaps particularly in the U.S. election year, it will be a challenge, the proliferation of sort of very real world but disinformation, misinformation inventory. And I think the theme around how everybody and how we all educate ourselves to understand that and to assess how to kind of filter through real information and disinformation is going to be a core and a key topic. Then regulation is sort of part of that. We've seen global governments got to race to govern responsible AI, responsible use of AI. And I think our view is regulation absolutely has a role to play in maintaining a necessarily very high bar for accuracy and equity of models. And I think regulation absolutely will have a role to play. In the same way that regulation has a role to play to maintain the high bar in the HealthTech industry to maintain the high bar in sort of the financial services space, ultimately for sort of consumer and societal protection. So the guardrails that are going to be put in around AI, how it is developed, how it is used is going to be a really important theme. It's a really interesting thing for us as we look at some of that opportunity. But I think it's something that we will all want to understand and really, really closely -- and closely use. And tied up in the regulation team is sort of issues of data privacy, data ownership. Data privacy, all of our data is the data that's being used to feed these models. These models are earning on the data that we have put out there, our transactions, our engagement with technology. And now the low form part of the regulatory framework. Data ownership, some of the clearest examples around data ownership is just some of the debate we've seen around the use of coffee right imagery that has been fed into these models. These models have been trained on. This is sort of a very obvious, but very simple example of a copyrighted image from National Geographic on the top, that's probably pretty recognizable to most people, but just a general prompt into mid-journey, of showing me an image of a Afghan girl produces these images on the bottom. So again, it's going to be a continuing theme, and I think how that data gets used and how the economic models evolve to ensure that copyright owners and data owners are incentivized for what they're contributing in. I think, again, is going to be a very open theme. And jobs replacement, sort of the other leg of the AI debate. I mean, look, with the capabilities, the sheer automation capabilities that AI, there's no best in the job, so we automate it and this is sort of no different to the technological progress and ways that we see sort of decades and even centuries gone by. A recent Goldman Sachs report estimated 300 million jobs, full time equivalent jobs would be replaced by AI. But that same report also have to start that 60% of the jobs that we're in today didn't exist in the 1940s. So we can see and we can talk through where do we think jobs will go, but will be replaced. There's no question this going to be a shift. It's going to take time, and it's going to take a lot of time. And -- but broadly we're sort of optimistic like anything we see in technological progress, I think GDP growth, productivity and the impact that this will have, while it needs to be done in a responsible way, will be very much a net positive. So sort of what's an AI future? I was kind of trying to summarize how we sort of think of it. And brave is the person who would stand up here and sort of confidently predict sort of what we're going to be seeing. But what's really clear and the direction of travel is really clear is that it will underpin and it will change how we either as consumers or as businesses engage with technology or engage with applications. And on the consumer side, we're already seeing an evolution of hardware devices that are being built to either replace or sit alongside our smartphones, whether that's Apple's Vision Pro or the [indiscernible] glasses or even new companies developing new form factors like AI pins that allow us to sort of engage with AI in a different way. I mean, fundamentally, it's going to change a lot of how we engage with this technology. But what's even more exciting to us is sort of some of the B2B opportunities we're seeing. And like I said, as we build our thesis, we sort of -- we tend to do so in sort of different verticals because for us, it's about not understanding whether we want to back an AI company. It's really understanding how is the technology being used to solve a very big problem in an industry in a unique and defensible way. And I think what that means is domain expertise and understanding how to sell and how to apply these. And so some of the things that we're seeing, I thought I'd sort of highlight some of the themes and again, speak to all of the team here because everybody has various touch points on this, whether it's robotics that is transforming, warehousing and logistics. We're seeing AI-driven diagnostics and drug discovery in sort of the healthcare space, fully automated software coding. Copilots, you think about all of the enterprise software applications that we all engage with on a day-to-day basis, they will all eventually have sort of AI kind of copilots. And it's these themes and these opportunities that we will sort of continue to monitor. But I think the overarching theme in our sense is that 2024 will see sort of AI moving from sort of -- or this generative AI from a period of excitement to a period of actual sort of deployment into real-world applications. And I will leave you with this, which is [indiscernible] impression of what Molten's Investor Day will look like in a couple of years. I actually have to say we have to prompt it a couple of times because it's depressing to say when we first added the prompt, there wasn't a woman in the audience. And everyone on the stage was a robot, and I didn't think that was the right message to send. So after multiple -- after multiple prompts, this is where we landed and we hope the robots are just here to serve coffee. Thank you.

Thank you for being here. I would like to talk about 2 things today. One is the state of our Fund of Funds after 6 years of operation. And number two, it's how we leverage the data that we have in this program, which is now strong of 2,200 companies. But before I do that, I'd like to talk about the market environment for RGPs and for our ecosystem. Martin talked about doom and gloom this morning for 2023. I remember last year I was here sitting in front of you. And the theme of the presentation was navigating through choppy waters or thriving through chaos. And it's fair to say that 2023 has its fair share of challenges for our GPs and for the early stage ecosystem. Some of RGPs actually, one of the most experienced RGP that we have in the program even went on to say that this was one of the most powerful, sorry, one of the most painful time that he had in his living carrier in venture. What we've seen in the last 6, 7, 10, 12 months was quite brutal actually. If you're looking at the numbers in terms of volume, in terms of valuation, and as you would expect, 2023 was not exactly marked by up rounds, but more down rounds. We've seen in our broader ecosystem, not necessarily the Fund of Funds, but we've seen or we've heard a story of portfolio wipeouts and down right, left and right. And this was also the golden age of convertible and bridges. Companies trying to push the time they're going to market. And tougher fundraising also mean that the bar for good enough has increased substantially and that was really reflected in the numbers. Deal cadence has gone down for the last few quarters. And clearly, for GPs, also for the entrepreneurs, this was really a time for tough conversations with the time for recalibration, it was a time for protecting cash and a time to be very disciplined for our GPs with portfolio management. Now encouragingly, what we have observed is that this hasn't impacted individual companies morale as much as we would have expected. And I think you're hearing that on stage from our entrepreneurs. Founders at early stage moved to survival mode. And startup survive as long as they focus on the product they serve and keep the customers happy. I mean it might sound trivial, but that's the nature of the game. Resilience is the name of the game. And what we've observed again across the portfolio is that successful founders at early stage, we're the one that we're able to quickly to adjust to ensure default alive. Teams were more focused, more productive around went on from becoming a nonevent to a morale booster for most of these companies. And it was also about being ruthless about what matters and what creates ROI. And I think scarcity breeds intolerance for nonsense. And that was really the time to do more with less really. And you know what, a lot of the companies managed to do this. The other thing is that the crisis has accelerated automation, cost reduction, building a more healthy ecosystem. The other name of the game is focus and discipline. And with solid business fundamentals and more runway, I think cautious optimism still prevails in our program and the portfolio companies. Another piece of good news. The future is coming awfully fast at us, and it's not going away. And we've heard that again this morning, but any crisis really is the good time to create a market leader. Technology is often the answer. And we've got very good depth in this portfolio. We'll talk about a few other companies. But we have a number of companies that are performing well. So anyway, with that in mind, where are we in the program after 6 years. Just quickly to remind you what the objectives were for the Fund of Funds, it was really about creating -- really about creating an ecosystem of the best European seed funds, almost an index. And it was about covering the market map more -- both from a geographical standpoint, and also from a CCs driven perspective, we'll talk about that. And of course, getting access to [ curated deflow ] and signaling the important deals that the PLC team and the investment team can do and that the Fund of Funds has done. So where are we today? After 6 years, 63 Fund Managers, 79 funds all together, which means that Molten is the largest private European program for early-stage leases. And you can see here our coverage of the market map. And the thesis is twofold. One is local capital. We think at early stage, nothing beats having fit on the ground, speaking the language, being part of the local ecosystem. And the other angle that we have is CCs driven. So we are trying to identify the best Fund Managers in very particular clusters of innovation or sectors, and that goes from impact to hardware to quantum computing consumer, software, foodtech. And on stage today, for instance, you have 4 companies that are coming from the Fund of Funds program. Another piece of good news is that I think we still get to see most of the deal flow at GP stage, early stage. So there are a few players out there. But Molten really is a go-to player when it comes to raising capital for an early stage fund manager. And the reason is very simple. We speak the same language. We are, this is investors first and foremost. And that chart shows over time how many funds we've seen, so more than 450 by the end of Q3 last year, and we've invested in roughly 20% of them. So we are in the business of saying no inventory, 99.9% of the time. We are saying, yes, more often for the Fund of Funds. It's quite reassuring. And in terms of numbers, so GBP 152 million of total LP commitments for the last 6 years into 79 funds. Those funds have invested in over 2,000 companies, 2,150 to be precise. Unique assets, 200 companies are basically cross-holding between several funds, which I also think is interesting, and this is something that we're trying to encourage. And we have an average 0.3% of indirect economic exposure to those assets. In terms of pound value, it's almost identical to investing GBP 40,000 into 2,200 companies. The program is at 1.4x TVPI and 17% net IRR, so that's net of fees and carried. But I think the most important stat because again, why we're doing this? We doing this to build an ecosystem, to make sure that the grassroots of early-stage investing are properly served, but we're also making this program to identify the interesting deals and, this is an interesting data point for every pound that we've committed to early stage fund managers, we've been able to deploy GBP 1 in the companies that came directly from this program. So that is the flywheel that I'm talking about. Data. I heard this the other day, "In God we trust, everyone else bring data." So those words were pronounced by William Edwards Deming, in 1986, American economist. And I think it's very interesting because it couldn't be more true today. So with my team and David is here, he's in the room, so feel free to ask him any questions. He's our data guy. We were wondering how can we create a data set that we can use for ourselves and share back with the ecosystem? And this is coming from that pool of 2,200 companies where we're tracking data on them. We've got obviously investment metrics, cost, NAV, equity stake. We've got data on their financials. We've got data on their cash burn. We know when they're going to run out of cash. And we also have data from the portfolio managers. So we've combined all of that. And it's quite interesting because picture book indicates that since 2018, about 14,000 companies have rated the [indiscernible] round and through our program, we had exposure to 2,200. So about 50% of the market. So we thought why don't we run some data on this knowing that this data is coming from the best European seed fund managers. And so that is spearheading those efforts. And data, again, for two things: one, to find the top performing companies that Molten can get into. And #2, to share the data back to our GPs because this is proprietary data. It will help them with our benchmark and further enhancing our position as a value-add LPs. So there are 3 takeaways that I would like to talk about today when it comes to the data. Number one, valuations are definitely recalibrating. Number two, large rounds are happening again in the portfolio. And #3, deal cadence has picked up. So this is a slide that is basically showing the valuation. So in green, you have the overall median valuation of our Fund of Funds companies. So you can see that within 5 years we went from GBP 4 million to over GBP 16 million, that is pretty obvious. Our companies are growing, so it's our valuation on average. But the pink line is actually quite interesting. It shows the medium entry valuation. So here we're not talking about average valuation about -- across the portfolio. We're talking about entry valuation. You can see like, clearly a spike in -- really Q4 2022, which basically was largely due to Series A investors coming to seed, clearly a trend that we've seen last year. But the median valuation basically was up until Q4 2022 went down and now it's coming gradually back up. But I think the next slide is even more interesting. This is something that is very proprietary. So what Dave and I are doing every quarter is we're looking at the 60 companies in the program, again, out of 2,200 that have a book value of $300 million plus. We're looking at that book value and we are comparing it with the last round valuation, and we're tracking that delta quarter-over-quarter. What it says is pretty interesting. So on the left, you have the few -- well, a sample of the sample, the most valuable companies of the program. And on the right, you can see that the discount that we've seen on those largest companies is gradually slowing down and growing back into the last round valuation. This is not because companies that just value more because they are growing and solving big problems. And we're starting to see that across the portfolio. We have the Q4 numbers in about a few weeks now. So I would be very pleased to see what it shows. But that is definitely a trend. The other thing that I would like to mention is last round -- sorry, large rounds are happening again. So in 2023, we've seen about 714 companies raising money or doing around in the portfolio. But we've also seen a few exit, which I think is very refreshing. Augmenta was sold to CNH for GBP 92 million, and Caption Care to GE for GBP 122 million. But you can also see here some very interesting round. Well [indiscernible] we're exposed to that companies through 2 funds, raised $500 million at $2 billion pre-money, so quite refreshing to see those large round happening again. Pascal, which is a quantum computing company, raised an GBP 85 million Series B. Synthesia part of [indiscernible], GBP 71 million about 6 months ago. So definitely interesting to see that things are picking up again also from the dealer size perspective. And I'm running out of time. So the last thing I would like to talk about is deal cadence. So the message here is that we're going back to prepandemic level. 2021 was out of the ordinary in terms of deal. We're living in a world where capital was very cheap and entrepreneurs time quite expensive. But if you look at the numbers, we are slowly but surely going back to the 2.5 average number. The deal per fund on quarter, which is a par with what we saw during the pandemic. And to finish, I'd like to talk about performance. So obviously, our performance, which has spiked to 2x TVPI in Q4 2021, has decreased, reflecting the new reality of the world, companies being valued at 30% on average discount to last round. But we're seeing that coming back gradually and stabilizing for the last few quarters. So that's it for me. The last thing I would like to tell you is that as we are producing this data information and sharing back to our GPs, we are gearing up now to do the same thing with our Fund of Funds LPs. So Dave is producing some very interesting quarterly updates, but also deep dive into strategies, which is what we want to elaborate further with our LPs. So for any question, please talk to me or Dave or [ everyone ] who is in the room, and we'll be very happy to answer your questions. Thank you for listening.