Deep tech investment opportunity for a generalist VC platform
Why traditional VCs are doubling down on deep tech—and why it’s not about hype, but strategic opportunity.
“So you folks are now focusing more on deep tech, right?”
With dozens of Hello Tomorrow side events unfolding this week, it’s a question I’m hearing repeatedly.
Indeed, at Alven, we’re dedicating increasing time and attention to founders building in sectors like techbio, industrial automation, semiconductors, and new space. Far from chasing a fleeting trend, venturing deeper into these emerging frontiers aligns with:
(i) talent inflows, (ii) market opportunities, and (iii) our inherent curiosity and relevance.
Talent inflow: blurring the lines between researchers and entrepreneurs
Investment decisions at the early stage invariably hinge on the quality of founders and their ability to scale transformative projects. Today, deep tech sectors are seeing unprecedented talent migration:
Researchers turning entrepreneurs
Approximately 40% of deep tech founders now come from academic backgrounds, marking a clear shift from labs to entrepreneurship. The current elephant in the room here is obviously AI researchers launching a startup. Programs like DeepTech Founders and the EIT Deep Tech Talent Initiative, aiming to skill one million individuals in deep tech by 2025, exemplify this trend.
Experienced founders starting again in deep tech
Founders previously successful in digital and software sectors are shifting focus to deep tech, driven by impactful opportunities, curiosity about scientific topics and strong defensibility now that they have first experience in company building and first successes and scars.
Better matchmaking between scientific and business profiles
Increasing collaboration between business leaders and researchers has fueled more commercially viable ventures. Structures like EntrepreneurFirst have systematized this approach, but hopefully that is happening organically as well. The founding duet at Aqemia, an AI-driven drug discovery company, or the management setup at SeqOne, a next-gen sequencing data decision-making platform are perfect examples of combining business acumen with research excellence.
Market opportunity: investing in potential long-term differentiated monopolies
While traditional SaaS markets face saturation and diminishing returns, getting easier and easier to launch but harder and harder to scale — deep tech, being based on new scientific or engineering breakthroughs being brought to market for the first time, offers distinct advantages:
Solving the world’s most pressing issues
While software has been busy “eating the world”, it really has eaten the world of bits so far, enhancing productivity in a variety of sectors. The world of atoms has been less affected so far, while being lower in the Maslow pyramid of needs, in the form of access to healthcare, shelter (energy, climate), but also making science move forward. Working on this kind of hard problems is not only gratifying, but also helps attract talent, good intentions and attention around the project. How cool does “curing cancer with AI” sound?
Defensibility and strategic asset value
Deep tech ventures develop proprietary, complex technologies creating potentially significant competitive barriers. These offer a higher initial hurdle to product at all, and product-market fit second, but improved defensibility once they are launched, potentially resulting in the monopolistic positions Thiel’s fanboys and fangirls are dreaming about.
As Tom Perkins (yes, of Kleiner Perkins) said, “market risk is inversely proportional to technical risk, because if you solve a truly difficult technical problem, you will face minimal competition”.
Stable demand and reduced cyclicality
Deep tech sectors often align with long term megatrends which seem very much like the shape of things to come, creating and underpinning long term movement to smooth out the shorter term cycles:
living and aging healthily (from penicillin to techbio)
cleaner and more efficient energy (from coal to nuclear fusion)
more powerful computers (from Ada Lovelace to GB10s)
more productive industrial output (from steam machines to robotics)
pushing the boundaries of exploration of the universe (from Magellan to Falcon 9)
It’s hard to bet against these trends, which in turn fosters public support initiatives, with programs like the European Innovation Council (EIC) investing €10 billion from 2021-2027 specifically to back deep tech startups.
Attractive Exits and Investment Returns
Differentiated, potentially oligopolistic market positions drive superior valuation among buyers, especially as some behemoths (e.g. pharma companies) are de facto outsourcing their innovation roadmap to their M&A teams. As an example, over half of Roche’s R&D budget is through acquisitions.
Recent high-profile exits underline this trend—such as Darktrace’s $5.3 billion buyout by Thoma Bravo. According to Dealroom’s 2025 Deep Tech Report, deep tech-focused VC funds consistently outperform traditional tech funds, achieving net IRRs of around 16% compared to 10% in regular tech (not sure these IRR stats are a great news overall but you get the point).
Exit paths are also more predictable, deep tech companies don’t necessarily need to reach a massive business scale before attracting buyers, relying on strong team, IP and technological assets, as well as a potential shortcut to regulatory hurdles.
Capital Intensity: myth or reality?
Deep tech financing is often followed with deep pockets needed to fund long technological development cycles before revenue kicks in. However, the combination of (i) potential upfront payment from big, long-term contracts, (ii) grants and subsidy initiatives, and (iii) potential debt-based financing thanks to real-world assets being used as collateral help debunk this myth. When looking at the data from the European Deep Tech report, 3 main ideas emerge:
Purposeful capital allocation: While deep tech startups indeed require higher initial capital, most of this investment builds lasting value through infrastructure and intellectual property rather than transient expenses like marketing.
Comparable revenue milestones: Contrary to widespread assumptions, the timeline and capital required for deep tech startups to reach initial revenue milestones (e.g., $1 million in annual revenue) are similar to those of traditional tech startups. The divergence emerges primarily at mid-growth stages, where additional capital supports larger-scale infrastructure investments, subsequently accelerating long-term revenue growth.
Similar Exit Timelines: Deep tech startups achieve exits on timelines comparable to conventional tech ventures, with most exits occurring around 6-7 years post-founding. The misconception that deep tech inherently demands significantly longer periods to reach liquidity events is thus unfounded
In addition to investment opportunity considerations, we also think our generalist VC track-record and way of partnering with founders offers high leverage and is complementary to deep tech vertical approaches, which I’ll cover in the next post, before going down the rabbithole of techbio.
Enjoy the ride!