Hatcher+: Reinventing VC with AI and Blockchain
“We help early-stage emerging fund managers outperform the big guys.”
That’s the bold claim from John Sharp, Founding Partner at Hatcher+, a Singapore-based venture firm using AI to disrupt the traditional VC model.
As part of our latest Amrop Global Digital Practice report, we explored what it takes to lead successful AI integration from the top. We spoke with CEOs and GMs across private equity-backed, midsize, and family-owned companies to uncover practical insights into real-world AI leadership.
In Australia, our Amrop Partners sat down with John Sharp to learn how Hatcher+ transformed from a manual VC operation into an AI-powered platform. The result? A groundbreaking venture model built on blockchain and AI — FAST: Funds-As-A-Service Technology — that’s rewriting the rules of portfolio construction.
Takeaways
Amrop Australia: Can you say a few words about the evolution of Hatcher+?
John Sharp: Hatcher+ is a company that evolved out of a very manual VC operation. What we realized when we started to manage all these venture capital funds that there was a giant market potential for ways in which you could do the same things for the VC fund that people have been typically doing for public equities, real estate and so on for over the last 20 years. And, as we looked around the world, we realized there weren’t really any technologies available that can help you build a venture portfolio, do due diligence on deals, manage the back-end portfolio report to all the investors and so on. So, about six years ago we launched the company and today we have a fantastic library of AI and blockchain-based AI capabilities and various tools that we’ve licensed and that we work with to create this really powerful platform that we now call FAST – Funds As a Service Technology platform. We’re also a technology company – we still run several venture funds very profitably, but our emphasis today is on the technology that you can apply to creating and managing a venture fund.
Amrop Australia: Can you explain in more detail how the AI tools are used in your organization?
John Sharp: We started thinking about the use of AI in about 2017 when it was widely considered not to have any role in VC, and it was very hard for people to conceive how this could work. Now, seven years later, we’ve created capabilities that allow us, based on our Hatcher’s score, to predict with a high degree of certainty whether or not companies will get a follow-on funding round, that enable us to figure out fairly precisely what the company’s valuation should be based on its stage, its location and its sector, and to do a very fine dive down into what the company does, in the midst of say, 2900 other subcategories and figuring out what that valuation should be.
So, what AI can bring to the table now is valuation analytics, forward thinking and predictive capabilities based on whether or not this company’s going to get funding, and it, of course, can do a massively good job of handling all this information and making it digestible to shareholders and limited partners, and other people involved in these funds. But what it does spectacularly good, which no one expected, is that you can use it to construct venture portfolios. Previously we were all taking the view that venture portfolios were constructed incredibly organically – all of these portfolios were constructed by a guy telling a story who comes to another guy with capital to invest and then we invest and so on, and now we have 300 companies in our portfolio, and we’ve essentially created that portfolio organically. What AI allows us to do is to take a step back and ask: what kind of portfolio do we want to construct? Where do we want to invest - what sectors, what location, what stage? And then it does scenario planning, using really deep knowledge that we can obtain from, in our case, 560 000 companies. And now we can construct a portfolio based on science, which, by the way, is how all the other asset classes manage themselves. There are now scientific models available where you can actually construct the portfolio to have the outcome you want.
You have to have capital, you have to have lots of capability in terms of process automation and management, which we bring to the table. But it is possible to create these kinds of AI-led portfolios, where AI is used to construct and execute the portfolio strategy.
Amrop Australia: The sheer velocity of investment, and the number of startups that you can process must be incredible – it’s bound to disrupt the market, right?
John Sharp: It is, and that’s the future. As an example, we just finished investing in a series of about 10 climate tech companies. We went out to the market and said that we want to find the best climate tech startups from everywhere around the world, and we got 2370 applications through our system. That boiled down to eight or 10 investments, which is a really good selection ratio – you feel like you’re getting the real cream at that point. And you have a process to run it, because you don’t want to be reading 2370 business plans. Our AI does that for us, filters out all the figures, finds out who the best 5% are, who are the most consistently aligned with the strategy we’re looking to invest in.
I recently spoke to someone in VC and they asked me: why would we need your product? I told them: can you imagine getting 2000 business plans and having to go through all of them? I can tell you which 50 plans out of those 2000 you should really read so you can invest in 10 of them. And he said: yes, that’s pretty compelling. And that way they can have more quality time with the founders of the 10 companies, and that’s what we really want to be using AI for!
Amrop Australia: How about the use of AI in your own business? Are there any competencies and skills that you’re looking for in your employees or that you’ve had to develop internally in relation to AI?
John Sharp: We’ve developed the tools we offer to clients internally, and, of course, we also use tools like ChatGPT and so on, but we’re quite careful about the use of third-party tools because we don’t want private information to end up on the public internet. People use AI to try and solve some problems. For instance, popular areas are psychometric analysis, founder background analysis, portfolio analysis, trying to get timeframes down, and that’s where our technology really helps us achieve the tasks.
Amrop Australia: Who are the types of customers who are embracing AI and what are you saying to those who are, perhaps, struggling to do that?
John Sharp: In every new technology wave there are early adopters, there are those in the middle and then there are laggards. The way we see it, it’s the very large companies who will be the laggards in this case because they have massive numbers of human resources that they can throw things at. So, if you’re a very large valley-based VC with hundreds of employees, you can consume an unlimited number of business plans through humans. The problems is, there is no one informing the partners of any exciting deals that come through the door except those humans, so, if the humans determined that renting out your spare room to a visiting tourist is a really bad business idea, you wouldn’t be investing in Airbnb, the partners would never hear about it, it would get binned by a junior level person before it makes it to the top. Whereas in our system everything gets analyzed, and if something scores really well, they can send an email to the partner – nothing gets missed.
Amrop Australia: And who are those that are adopting the technology well?
John Sharp: The ones that we see rapidly adopting technology are those which want to become larger and competitive with the large existing VCs. They don’t have the human resources and the management fees yet, but they want to be able to consume deals and invest, they want to be able to manage things in a way that’s competitive and become even better than “the big guys”. Therefore, what we see as our main target are smaller, early-stage emerging fund managers, start-up funds, so to speak. There are hundreds of them emerging every year and they need the kinds of tools that we can give them to massively increase their capability, plug them into an amazing deal flow, give them reporting capabilities and everything they need to become a world-class VC fund. And we can do that literally within a day.
Amrop Australia: That’s amazing. It makes AI into the big leveler of the playing field.
John Sharp: Yes, and the interesting thing about VC is that everyone always enters a new business thinking that they’re the smartest guy on the block, but you realize soon that in the VC industry everyone’s pretty smart – there are no dummies in that business. And once you understand that VC is about probability, the question you should be asking is: how do I move the outcome from 50% to 51%?
There’s a lot of money involved so you make a lot just by moving the outcomes a little. So, we take a probability-based business and just add a little more science to it so we can move the outcomes more into the positive area and allow anyone to do this. So, the super-smart guys don’t have to go and do deals with 1000 technology companies – they can come to us, and we put all of that in place.
Amrop Australia: Looking at your own business, as opposed to the product you’re selling, which has AI at the core of it – what kinds of tools do you use internally?
John Sharp: There are a couple of things which I would define as founder-facing tools that we use. What we’ve discovered watching 10s of 1000s of deals come through our door is that founders, often highly intelligent, energetic and passionate people, are doing a pretty terrible job of telling their story, missing out on so many important components of it, like: who are you? Why do you have the right to do this? What’s your mission? What’s your passion behind this? What have you built? How much money do you want?... There’s all these important topics that, when you analyze the business plan, they are completely absent. So, there are tools we offer to founders – the executive summary analysis where they give us text and we give it a score. The description could, for example, score 15 out of 50, and it would obviously need to be improved, so we would give them 10 tips on how to improve their story. We’ll say it needs to be more passionate, more involved in how you explain your mission statement, connect with your impact on the environment and so on.
Also, simple factual things like where’s the ask, where’s the information about your team, where’s the information about the solution. Founders rarely get the story right the first time. And then we also do what’s called “The Hatch Score” where we look at an axis of eight items, mainly around fundraising – our prediction around whether they’re going to raise funding. There are questions like how impactful this is, has the CEO done it before, what’s the exit potential, is the return multiple? And we’re looking for a score above 700.
Amrop Australia: So, these tools enable the founders to improve their performance and chances dramatically, and then, through that process, you’re also populating the database, so that’s two sides of the marketplace, where you’re improving quality constantly.
John Sharp: AI is all about creating mathematical clouds out of something that isn’t a mathematical cloud. We never modify the business; all we’re saying is that relative to what you’re talking about here, you need to tell us more about your team, your product etc. What we’re expecting is a balanced, detailed and data-driven approach to telling the story, because it lowers our risk and increases our understanding.
Amrop Australia: So, this is your proprietary AI. You mentioned earlier that you’re doing a deal, a new investment, every one and a half days. What are you seeing in terms of the early-stage startups you’re investing in – how widespread is the AI theme?
John Sharp: We have this back-office technology that we’ve developed, and, among other things, it does analytics on a sector basis, so I can go in there and look at a pie chart. I checked yesterday and AI is the second top area that we’ve invested in after FinTech. This is one of our funds, but probably 9-10% of our investment dollars have gone into AI-based companies. We’re trying to invest in companies that have an ability to leverage their own proprietary tech.
Amrop Australia: And where is it being deployed in terms of domains and sectors? What examples are there?
John Sharp: Everywhere, but my favorite which I heard about recently is a farmer in Queensland, Australia, who had licensed some AI software and was using it in combination with video cameras to spot weeds on his crops, and then squirt pesticide just on the weeds so that the stuff that we eat doesn’t have any pesticide on it. When asked if this was to protect the food people eat, he said that he’s not protecting the food, he’s lowering his cost! This way he uses 99% less of his pesticide, and it’s amazing, he’s a farmer, he’s going the commercial route, but that’s what drives these innovations, right? Where I see AI operating is always somewhere really unusual which you wouldn’t have thought about before, and we’re not seeing so much in the area like robotics – that’s just the big-ticket stuff. But one thing is clear – the data centers that run this stuff are going to be immense. We’re entering a second area of AI where we’ll only be able to get so much efficiency, and those efficiency improvements will be dwarfed by the demands being placed on the core AI elements, and on the mechanisms themselves, which will just mean an expansion of data centers, but also people looking for efficiencies, looking for energy savings. There's going to be a huge emphasis, and a complete change of how these things get architected, and used and priced and delivered over the next few years - it's going to be an amazing space to watch.
Amrop Australia: What do you see as the necessary requirements and skills for a business leader in the AI field now and in the next couple of years?
John Sharp: I think people that really get AI tend to treat it more like water, while people that don’t really get it treat it more like religion. Someone treating it like water will be using it to optimize processes and help us out, will view it as a utility. They would just see it as the next iteration of a very powerful technology that will probably iterate itself to that level anyway. The most fascinating thing about this question of AI and leadership is actually – at what point does AI lead itself? Because we’re fast approaching the point where you can ask any AI, any question and they’ll have the answer that you want. So, at what point do you ask AI for the top strategy to take its own technology to market? It’s probably going to have a better answer than us within a couple of years.
Amrop Australia: The pace of it is mind-blowing.
John Sharp: The scary thing is when you start to combine these things. I recently spent a week at a defense technology seminar in Texas, which was quite enlightening. When we consider the potential of AI-driven near-field mind reading, such as how our AirPods and similar devices might interpret our thoughts to move a chess piece around the board, the implications are fascinating. Imagine a powerful AI with a tenfold increase in capabilities that can access your thoughts and understand your innermost feelings, even just differentiating between anger and happiness at the most basic level. These emerging technologies will have significant impacts across medical, consumer, and various other domains. The predictive capabilities of AI, based on data from everyday devices like glasses, earbuds, and headphones, will allow us to gain insights into our personalities and emotions in the coming years. This potential is undoubtedly powerful.
Amrop Australia: I would like to revisit your point, John, about the large companies that can afford not to think about AI solutions because of the vast number of employees they have. What do you envision as the potential solution for these companies in the context of this often-repeated notion that people will inevitably lose their jobs to AI?
John Sharp: There’s a lot of speculation surrounding AI right now, with discussions about both its potential benefits and risks. Some people view it as a threat that could lead to our demise, but I have a different perspective. I believe AI is an incredible technology with the potential to bring substantial positive change to the world. Just recently, I had lunch with someone, and we discussed AI's capacity to eventually facilitate a universal basic income for everyone. This could allow us to enjoy a more relaxed lifestyle, spending our days at home watching Netflix and simply unwinding—which honestly sounds like a pretty appealing way to live. As for the large companies, they’re going to go through a phase very much like what the big banks went through in the 90s. At the start of the 90s buying stock was a very manual, very individual and long process, but 10 years later 90% of time trading was happening algorithmically without anyone really knowing what was going on, except for the people who created these algorithms. Everything went from completely manual to completely automated – from three weeks to three milliseconds or less. I predict that the same will happen in venture – if we can move those decisions to a point where funding takes a day, the founders win and the funds win, and the bigger companies will have to move in that direction, or they will be out of business within 10 years… and it make not even take that long.
Download our full report: Digitization on Boards 7th Edition “The rise of the CAIO: How AI is reshaping leadership competencies”