How to Identify Tomorrow's Billion Dollar Startups Today
DDVC #62: Where venture capital and data intersect. Every week.
👋 Hi, I’m Andre and welcome to my weekly newsletter, Data-driven VC. Every Thursday I cover hands-on insights into data-driven innovation in venture capital and connect the dots between the latest research, reviews of novel tools and datasets, deep dives into various VC tech stacks, interviews with experts, and the implications for all stakeholders. Follow along to understand how data-driven approaches change the game, why it matters, and what it means for you.
Current subscribers: 15,430, +300 since last week
Brought to you by Harmonic - The Sourcing Tool for Data-driven VCs
Harmonic is the startup discovery tool trusted by VCs and sales teams in search of breakout companies. Accel, YC, Brex, and hundreds more use Harmonic to:
Discover new startups in any sector, geography, or stage including stealth
Track companies’ performance with insights on fundraising, hiring, web traffic, and more
Monitor their networks for the next generation of founders
This post was written by my partner Hendrik Brandis and me, and was recently published via Tech.EU here. We explore how Earlybird, as an established venture capital firm with more than 26 years of history shifted towards an Augmented VC approach, and how leveraging data & AI allowed us to identify Aleph Alpha, among other promising startups. Following the positive feedback on the original post, I am reposting it here for the Data-driven VC community. Looking forward to hearing your thoughts!
Innovation champions of the future create jobs, prevent the emigration of skilled workers, and thus ensure prosperity. To be able to identify and promote champion companies early on, artificial intelligence and data-driven approaches have become indispensable — but the difference is still made by humans.
When we first became aware of Aleph Alpha at the beginning of 2021, their description in the commercial register did not yet read like that of a future AI champion. The vision for technology sovereignty was recognisable and great, but at the time, the approach and structure of the startup still resembled more of an academic chair for artificial intelligence than a commercially oriented company. Certainly highly exciting, but still a long way from concrete applications.
In the absence of a meaningful company website, we would probably never have discovered Aleph Alpha so early if the commercial register entry had not been enriched with further data and appeared on the result list of our proprietary AI-powered platform, "EagleEye".
To better understand the idea behind Aleph Alpha, we therefore contacted Jonas Andrulis, co-founder and CEO of the startup. The serial entrepreneur and former AI manager at Apple had a convincing answer to every one of our questions and strong hypotheses about AI as a future platform technology.
The rest is quickly told: In July 2021, Earlybird led Aleph Alpha's Series A financing round, followed by groundbreaking research successes around trustworthy and explainable AI applications as well as strategic partnerships with industry giants such as SAP, Bosch, Hewlett-Packard Enterprises (HPE), BCG, and many more.
In addition to these operational partnerships and customer relationships, some of the named companies also participated in the $500 million financing round led by Innovation Park AI (Ipai), Robert Bosch Venture Capital (RBVC), and the Schwarz Group. Aleph Alpha has long been considered one of the biggest tech hopes of recent years and the European answer to ChatGPT developer OpenAI from the USA.
Join 15,400+ thought leaders from VCs like a16z, Accel, Index, Sequoia, and more.
The example shows that without AI, we might not have found the next AI champion that early. That was three years ago. At that time, EagleEye was still in its infancy, and the software has become much more powerful since then. So much more powerful, that we dare to predict: Without AI support, venture capitalists and investors with bigger size funds will no longer be competitive in the medium term — especially those of us who seek to invest in startups at the early stages. This is because startups — unlike companies on the stock exchange — do not have to comply with disclosure obligations.
Information about the startups is difficult to access, incomplete, and partly contradictory. Whoever can shorten the tedious path of data acquisition, cleaning, and subsequent AI screening gains time and has an information advantage. It becomes possible to proactively address startup entrepreneurs. This increases the chances of promoting the development of the coming innovation champions.
The current champions still come from the time before AI support in seeking them. So the effects of this tectonic change in the venture industry are not yet visible. In the coming years, however, it will certainly become clear who has secured AI support in time to optimise their investment processes.
AI-based investment solutions
Earlybird is, of course, not the only nor first company from the investor cosmos to have recognised the possibilities of AI and acted accordingly. GV, Google's venture capital arm, was one of the first investors to deal with the topic in 2015. This was obvious, as Google already had highly relevant data on young companies.
Shortly thereafter, other companies such as the Swedish investor EQT, or the US investor Signalfire joined in. We at Earlybird also started this journey in 2017. According to the "Data-driven VC Landscape 2023," there are now around 150 venture capital firms worldwide that are working on AI-based investment solutions with internal developer teams. That's only about 1 percent of the world's venture investors, but the trend is strongly upward. On the other hand, that also means: 99 percent of technology investors are starting with a significant delay and have to catch up first.
AI helps — but alone, it does not secure optimal investment access. The chances of landing a hit in the search for the upcoming startup stars can be increased by further measures. The AI tools are, however, the basic requirement for this: they identify relevant tech startups in the first step through information they collect from the depths of the internet.
A simplified example: If a person is looking for co-founders in a forum, changes their status to founder on LinkedIn, or registers a GmbH (limited liability company in the DACH region) with the commercial register, the entrepreneur with all available online information about the new startup appears on our platform.
While our platform contains a variety of data on more than four million companies and ten million people, around 50,000 new tech startups and concepts are added annually — which EagleEye filters in a second step. The AI searches for patterns in the data of the 50,000 startups that have led to particularly large corporate successes in the past.
The most promising startup lands in first place on the results list. This puts all the startups in order. We then look at this selection with our investment team and decide manually who we actually contact. This does not necessarily always have to be the top placements. In other words, humans have the final say in this "augmented VC" approach.
The example of Aleph Alpha shows the difference this makes. The AI startup was high up on the list at that time, but not at the top due to the thin data. However, in a personal conversation with the founder, it quickly became clear to us that we were dealing with a possible next tech champion. We were able to foresee this at that time because we bring another prerequisite that is equally crucial in assessing innovations: top-trained employees with great expertise and a deep understanding of industries.
In addition to the fact that we have real chances with EagleEye to contact founders before most traditional capital providers — which impresses them, creates trust, and increases the probability of a deal — we also provide early contact points through other initiatives.
Together with partnerships at Handelsblatt Media Group, the consulting firm Bain & Company, and leadership and advisory firm Egon Zehnder, for example, we support business ideas from entrepreneurs from migration backgrounds with funding of 25,000 euros as part of Earlybird’s "Vision Lab" initiative.
As a result, around 500 potential companies per year get to know us from the beginning. If these startups take off, they approach us first. In our view, the combination of such organisational initiatives, a powerful AI-powered platform, and employee expertise leads the way toward a successful future of startup financing.
Only if we as an industry recognise, promote, and thus bring to full bloom the innovation champions of tomorrow early on, Europe's economy — and therefore all of us — will benefit.
Thank you for reading. If you liked it, share it with your friends, colleagues, and everyone interested in data-driven innovation. Subscribe below and follow me on LinkedIn or Twitter to never miss data-driven VC updates again.
If you have any suggestions, want me to feature an article, research, your tech stack or list a job, hit me up! I would love to include it in my next edition😎