Introduction

I have the pleasure of hosting this panel tonight. I'm going to get everyone to introduce themselves in just a moment.

Purpose of the Panel

The aim of the game is to give you an insight into the different components within investment in AI from the legal and different investment classes as well.

Meet the Panelists

Introduce yourself, panel, starting at the end. Hi, everyone. My name is Alex. My background is private equity.

I worked 12 years in three funds, started in Vienna, then moved to France, then moved to London. 45 deals in total, 3.5 billion in value.

Then I bootstrapped my company that provided smart city, smart parking solutions, reached 15 million ARR, sold it in 2018, and invested everything in my fund, Bigging Capital. We've got 62 million under management, a team of four, invest in B2B software companies, deep tech software companies, got some focus on AI as well, ticket size from few hundred thousands up to five million per deal, invest globally.

Hi everyone, sorry to keep you from pizza. My name is Maria Zherebtsova. I'm an investment director in Raw Ventures. We are a small, essentially family office company investing in seed and pre-seed companies.

We say we like tech, we like tech, but we are a bit of a mixed bag, so we look at a lot of different projects. My background is in finance, I was always on business development and sales side, and then I transitioned into the world of startups and then venture capital.

I'm on a panel for once. So I'm Josh, but you know about me. I am an engineer by background. I started a few companies before. Last company I started was a company called Super Awesome before MindStone, which became the biggest kids technology company in the world before being acquired by Epic Games.

But for this panel, I'm also an investor, and so I invested in about 50-ish startups, mostly London-based, a few US, and I get a lot of exposure to startups right now with eight meetups every month, and trying to figure out what works and what doesn't, so hopefully I can add some value to people who actually know how to invest.

And then a brief 30 seconds about me. So my name's Jamie. I'm a partner at Oryk. You've already heard about us tonight. Before I fell into the murky world of law, I actually was writing code and doing silly things with software. I then realized I wasn't cool enough, so I became a lawyer. On the side, I'm also an LP in certain funds, and I make some angel investments also. So I think that covers most of the hats in one game.

The AI Investment Landscape

I do have notes, so forgive me if I look down every once in a while, but we've got some great questions for this panel. I guess, first things first, I first cut my teeth on AI deals probably about 15 years ago. The landscape changes and now it's back again today.

Key Trends and Strategies

Maybe Alex, do you want to kick us off by saying what you're seeing as some kind of key trends within the AI investment landscape at the moment? or maybe if you've changed your investment strategy to cater for AI over the last?

I would probably tell you about two things. 1Before this event, I've surveyed my portfolio companies, whether they use AI or plan to use it in a short-term period. Right now, almost 60% of 30 companies are actively using AI or have short-term plans to implement it in its product. And a year ago, it was just 20%.

like, to be completely honest, if they asked my advice, like, a year ago, should we, like, focus on, like, building AI and go to our products, I would say, stop this bullshit, like, focus on your current go-to-market and so on. And what we probably call AI is other people call it, like, applications, so don't do it. But what we see on the market right now is that already, like, in our portfolios there are, like, several, like, Series B, Series C companies. And when they start new rounds of fundraising, everybody from the, like, Tehran funds, from United States, other funds are asking about AI. What do you have... Do you plan to implement AI in the short term? Show us AI. What do you have there? So it's, like, definitely hot. And probably, like, my number one trend right now is...

For me, compute is a new oil, so everything related to compute, databases, infrastructure layers, is like amazing. We invest in much earlier stage companies, but I would say that I think we see that AI in itself cannot be a driver unless you're going very deep tech. But in pretty much every single company that we see, if they are not thinking how AI can optimize either their operations or in terms of including as a feature and thinking about it as a very clear feature roadmap, then there's definitely something wrong with the strategy of the company, I would say.

So on my side, I would say maybe somewhat controversial. I'm actually very pro-GBT rapper, or at least how people talk about that. I think there's an enormous amount of value to be unlocked by using the technology, basically... riding the wave of all these big models that are unlocking new potential use cases and building the best possible user experience on top of those. And I don't think they're getting the user experience and the solving a problem bit, I think at this particular point in time, are not getting enough credit for the companies that are getting built in some cases. It's not a technological moat, but it is definitely still, you can still build a product moat in my opinion. Awesome.

Comparative Landscapes: US vs UK

Yeah, I guess we hadn't caught up recently, but Raf and I have just spent the last couple of weeks in the States, and it's really quite interesting in terms of comparing current landscapes here versus the other side of the pond. The level of excitement that we saw for some of the companies there precede in the US is a totally different concept to the UK, a lot larger. Okay, so we've touched on the investment landscape.

The Role of Angel Investors

I'm very conscious that you all represent slightly different investment models from the P, VC, and then the angel network. Josh, I'm gonna make you work. But angels in particular play a crucial role in, you know, the early stage rounds. Is there anything particular from your kind of stage of financing, if that is a phrase that works, that kind of really makes you pick AI over non-AI companies?

Or what do you think makes an AI company stand out at the moment for you? Well, there's one part where we're the dumb capital here. I'm not a professional capital allocator, so that's where it starts, is exited founders trying to help other founders go and build stuff. Because you really believe, and I somehow, I am so optimistic because I'm a founder ultimately, and so I want to believe that everything will work. which makes me not as good of a professional investor. 1But I do think there's a really good role for angels for exactly that reason, which is having that first person that actually believes you might be onto something, especially as an exited founder, kind of having built something before, that might give someone the confidence at that point, like, okay, shit, actually, maybe we can really do this. Like, if... If I'm not the only one in my head that thinks that this can work, somebody else is willing to believe in it. I think that can spark something which helps people go on to the next stage. So I think that's the number one thing.

And then the second thing is just opening up networks. Making sure you have a little, you can make that raising of a first pre-seed round easier by making the connections for someone who's never been there before. Perfect.

Competition in VC Deal Flow

Maria, how about you? I'm imagining a large number of VCs at the moment are staying there in the AI space. Are you seeing any competition there in terms of your deal flow or do you have free access? Well, I have to start by saying that we're not typically a typical VC fund. So we are closer to a family office with a very clear mandate to invest into early stage tech companies. So in that respect, that actually gives us a lot of flexibility in terms of what we can look at for how long we could look at. and potentially not get sometimes maybe pushed or rushed into decisions just based on sort of peer pressure.

But I just wanted to follow on the point that Josh said that there is so much value in terms of having those networks and having those introductions from kind of warm introductions from founders themselves, from angels who invest in other companies. And we certainly see in our deal flow that we probably would look closer at deals that have been recommended to us by founders who we have invested in the past or people they bring over. I think that there's definitely a network effect. It's a very important strategy to keep developing that network.

Private Equity Perspectives

Alex, looping you in here, PE typically has a longer growth journey perhaps. I'm very conscious that with your approach to investing, it's got to be on scalability, long-term growth. What are the key metrics that you're looking for in your investments? I believe there are two types of investments that we are currently looking at. The first one are, let's say, front-end text solutions, which is probably like a red ocean already. It's a very competitive... So if you're looking at a startup in this niche, actually not the technical skills we believe are the most important, but our execution skills. It is like almost a B2C game, even if it is a B2B solution, how fast you are going to the market, what is the key value. The second part is backend solutions like compute and databases and so on. And here is the tech defensibility, the unique value proposition of the product is the most important things. So for the second one, very, very technical teams, unique product, unique go-to-market strategy, and so on. Perfect.

Investment Experiences and Challenges

Hopefully a safe space, obviously, within these four walls. I think the best thing about a panel is sharing some experiences, good and bad, about some of the investments or decisions that you might have made. Anyone open to the panel on this one, be grateful to hear of any successful investments that you've made, what made them successful, or any kind of challenging decisions that you've had recently on opportunities.

Maybe I'll start. It's an example actually of the value of, so we have a company and they are actually a sort of deep tech company that has engineered a full digital human from a cellular level up. and what we found is that we invested heavily in this company and they were doing great and they were essentially showing us that they had all those contracts and go to market and everything was great but for some reason we felt stickiness and then it turned out that essentially the technology that they built was amazing but they did not find a way to productize it into an actual product and that's why they ended up being almost like a bespoke development company just trying to pitch different things to different people.

So that meant quite a painful decision which at the same point culminated in a decision to kind of continue funding the company, there's a decision to bring in a new CEO, and also to fundamentally rethink the strategy. And the idea there, which I think was hopefully a success story, is that we were able not to go into an antagonizing relationship, but to go into a very highly collaborative relationship pulling our resources, the resources of the team, to get into one room and essentially to deconstruct the product back to MVP. And we see a fundamental shift in results coming in from that.

The kind of the moral from that and again, we don't know if it's going to be a success. We're seeing early signs of success and it's great. But the moral there is to find partners and collaborators in your early investors because the pivots are going to come and you will have to make them very, very fast.

I remember pretty vividly about a year and two months ago or so. I'm a very hands-off investor. I'm running Mindstone, so I can't really do stuff. But from time to time, when I see something interesting, I ping it across the founders.

And we had this discussion at some point where one of the companies I invested in was basically doing chart analysis. So you have an interesting... chart that comes up in a report. You can automatically figure out what that is. We all have these PDFs of market analysis and wouldn't it be great if you can automatically extract all the data that comes out of it? And you started to have the first steps of these models being able to, starting to be able to do analysis of what an image was. And I was like, This is maybe problematic because you're now going to have to deal with Google and Microsoft and OpenAI and, and, and, who are all going to try and do this. It's like, yes, but we're specialised. It's like, yes. Yes, but image analysis is a thing that everyone is working on, and so this might just be the thing everyone does. And over the last year, the image analysis on the generic models we can use today is crazy good. If you give it a good graph, it's within a 2% to 3% error ratio being able to know exactly what the data is that goes into the graph, which is crazy. So that's the one thing for me. And this comes back to the wrapper bit. I actually prefer being in startups that are clear about, hey, our value is not that we have a specialized model. Because if you think you have a specialized model, you have the risk of getting squashed by a big model that ends up just flowing into your space. But it's the thing that you build on top that then becomes the differentiator.

I was going to say, the other way around, there's a company that I've been supporting from the start, which is a company called Humanity. I think maybe a few people in the room here know Humanity pretty well. And Mike, one of the cofounders, two days ago, he actually wrote a very interesting article about, he was calling it the large biological model. And he was talking about, okay, with all these changes that we're seeing, all these evolutions that we've gone through from a large language model perspective, are there more learnings that we can take from the unlocks and the capabilities of large language models that we might be able to replicate in other spaces? And so their entire business is about the increase of human lifespan, and so can you take biomarkers, can you actually hook into biomarking data and start to build a model that takes the learnings from what large language models have done and then basically be able to predict the increase of lifespan in a way that we've never been able to do. And I thought that was really, really interesting as well. And I wonder if there are more applications taking the learnings of what we have from LLMs but applying them in slightly different contexts and that might be another differentiator as well.

Wonderful. Alex? In terms of our portfolio, I currently have some controversial feelings because some of our preceding seed companies were extremely lucky to raise huge rounds of investments. And on one hand, it makes us on paper top 1% performing funds based on net asset value. But on the other side, like Those companies, they're like really pre-seed or seed companies, and now they're raising at, we just recently closed the deal, 30 million round, 200 million valuation, with a startup that has like 200,000 pounds in revenue per year. So in this case, sometimes it's like a huge mistake to raise way more money than you currently need. because this can also ruin the company. And it's good news that they're raising so easy on these tough markets, but I'm pretty concerned and I believe we need to spend way more time with the portfolio companies because we need to be sure those high valuations, they also bring high expectations. Awesome. OK. I'm conscious we're getting very close to pizza time.

Predictions and Final Thoughts

So one more mini plug and then question, and then I'm going to throw it to the floor. The mini plug is we at Oryk produce an annual report called DealFlow, which shows all of the kind of aggregated deal terms across the venture market. It also predicts what's going to happen within venture.

It's free. You can find it.

Future of AI Investment

Quick fire question to the panel. If you were to predict one key change or outcome within the AI investment space in the next 12 months, what would it be? Don't all at once.

Okay. Well, to be honest, it's already happening, but maybe not in deep tech, but consolidation. I mean, you've seen a lot of companies popping up and now it's the time for consolidation, for maturity. So we're already seeing that.

Nice. One prediction. AI-generated song or music will be in billboards to 100 by the end of the year. Very cool.

Who knows that it already isn't? So, what was it, in a gold rush, back the ones that are selling shovels, and so everyone is talking about AI, very few are talking about how everyone is gonna be using AI, and so helping, figuring out how the entire world is gonna have to use all of this technology, I think is going to be one of, is right now one of the more under-explored categories, which I think has a lot more leeway. Awesome.

Audience Q&A

Two questions from the floor, and then pizza time. Thanks, Jamie. Thanks, guys.

Do you think that the traditional sweet spot for VC is getting squeezed out insofar as the big foundation model companies need so much money, they can only get it from Microsoft, and the wrappers potentially are never going to be billion-dollar companies, although they might be really nice bootstrap businesses? Very good question. I suppose that's why you see companies going early and early and really kind of rolling up their sleeves and working with the companies to try to achieve that. So I think you're right, the model is slightly changing and it's all about building the network and really kind of also getting stuck in and understanding what particular niche you want to occupy. I think it's about gathering knowledge.

Very interesting question. I literally had this discussion earlier today with my co-founders actually about exactly this. It's like, well, if you're looking at additional capital, where do you go? And because you have increased productivity across the team, you have fewer requirements for capital to go farther.

Part of it might be like the outcomes, but actually I would say the bigger thing is that if you don't need a lot of capital, then the returns for VCs quickly kind of put you out of the category of what they look at. And so we were suddenly, I mean, and I've only done venture-backed stuff before, but suddenly we're looking at, oh, maybe venture is not the we want to go and build a $100 billion company, but even in that type of environment, venture might still not be, we don't look like something that venture would normally be looking for. And so it becomes a really interesting question at the moment.

Right, one more. It's going to be for Alex, so make it a good one. He's excited for it. Oh, and we've got one here.

Here we go. Thank you. My question's basically U.S. versus Europe. So with the recent legislation that was just passed on all of the AI stuff in general, it's definitely becoming a question that we've internally thought about of why stay in Europe. Seems like, you know,

Sam Altman was opened with welcome arms into Europe because he was calling for regulation, I believe for regulatory capture. And then also the really large rounds you can raise in the US. So I guess the question is, why raise Europe?

Why stay Europe and not go to the US? I fully agree with you. US seems to be like a way better market. And even if you think about VC, being a VC in London,

We really feel that just going to work every day is already a competitive advantage. And regarding the regulations, European Union will definitely get another 200 commissions to make more and more sophisticated legislations and it would be a tough environment. But still, there is some money. If you can raise in U.S., raise in U.S.

and be there. I will just add a small note that it really depends on the company as well. If the fundamentals of the company and the go-to-market kind of allow to show U.S. revenue, then yes, it would be easier to raise in the U.S.

But usually, a lot of the VCs will say, okay, we'll prove your traction here and then we'll look at you. So... Yeah, I mean, there's nothing controversial against that. I think it's very clear that if you can, if you have US revenue, there's more capital there.

I would put one bit for the UK specifically, not continental Europe, but for the UK, I think there is an easier access to talent. You have less competition right now for talent that would allow you to scale the business. So it depends on where your scaling limiting factor is. If the scaling limiting factor is there is not enough capital,

Yes, you can get that much easier in the US. But if your scaling factor right now is that you can't find the talent fast enough, then I would say the answer is more nuanced at the moment because it might actually make it harder in the US than in the UK at the moment. Minor addition for me is, again, maybe pro-UK for some of the early stage folks is obviously we have a huge thing called SEIS and EIS, which is like an amazing way for really early stage companies to get access to angel capital very quickly and easily, which obviously doesn't really translate across to the States.

Okay, big round of applause for a fantastic panel.