Why the most important innovations are the hardest to fund
By: Olivia Arechiga, Co-Founder, Line Axia
AI Disclamer – As always, this blog was written by a human, me! ChatGPT helped me edit.
“DeepTech” has long been a favorite buzzword in venture capital circles, promising the next frontier of innovation, from quantum computing to advanced materials and synthetic biology.
Yet, when you talk to investors, many will tell you the same thing: they love the idea!… but it is too risky to invest.
@Tina and I saw this first hand during our time at the Sifted Summit in London this past October.
Fundamentally, DeepTech sits at a strange intersection.
It represents both bold and undeniably innovative visions for the future, and at the same time requires immense amounts of capital, over long periods of time. And often times, it ends up being not viable. It’s hugely risky, in other words.
Understanding, and bravely working within that quagmire, is a requisite if you want to build, invest in, or lead a DeepTech company that actually survives the gap between science and market.
First, Let’s Define DeepTech
I asked this question to a small group of EU DeepTech founders during a roundtable discussion at the London Sifted Summit: What is the actual definition of “DeepTech”? Is there one? Does it vary by industry or country?
No one had an answer. In fact, this question was met with concrete silence. No one had any definition of their own to provide. I jumped in and suggested it was something like – “You know it when you see it?”
Some may disagree, and no doubt this is a broad definition, but for the sake of brevity, we’ll define it as: technology rooted in scientific or engineering breakthroughs.
The Singapore Global Centre wrote a good definition: “
Deep tech refers to the cutting-edge and often disruptive technologies that are built on profound scientific discoveries, engineering innovations, or advancements in research areas that have the potential to radically transform industries, economies, and lives.”
Unlike SaaS or consumer tech, DeepTech companies aren’t selling an efficiency or an AI chat-bot; they’re really selling possibilities beyond our current reality.
Whether or not you can articulate this possibility with concrete requirements, steps, and most importantly, a timeline, will determine whether your DeepTech becomes a darling of daring investors, or if it dies in an under-funded lab.
Why Investors Want DeepTech:
- Massive Potential Upside
DeepTech companies are often trying to solve big problems, like climate change and healthcare, which means the upside is outsized. If it works, it can reshape entire sectors. It can literally, change the world. - Defensibility and IP
The moat is in the science. DeepTech ventures will build patent portfolios or proprietary engineering processes that are years ahead of actual replication or deployment. - Portfolio Differentiation
VC’s interested in this type of risk want their investment to be high impact and high return– which is typically what you get when you invest in DeepTech and it takes off. - Impact and Narrative
DeepTech is attractive when it’s an impact initiative – helping humanity and solving big problems makes a VC look good. Good headlines bring more opportunity for the VC.
Conversely…
Why Investors Don’t Want DeepTech:
- Technical Risk
The science can fail. And often does, sometimes spectacularly. (Think the Theranos story). - Time-to-Market
While a SaaS startup can iterate and pivot in months, DeepTech ventures can take 10+ years (or longer) to reach a minimum product or a marketable result. - Capital, Capital, & More Capital
Prototyping, manufacturing, data analysis, and creating regulatory pathways require incredible amounts of capital. The same components that make it defensible, also makes it incredibly expensive. - No Clear Exit Sign
Many DeepTech ventures have uncertain (or non-existent) IPO/capital return paths. The “exit math” doesn’t traditionally fit standard VC time or investment return horizons. - Operational Complexity
DeepTech teams need to align scientists, engineers, regulators, and business operators which demands an extremely high level of governance, expertise and oversight that most early-stage companies don’t need.
Here’s a quick real-world comparison of funding a non-DeepTech initiative by VC’s, compared to a DeepTech:
In June 2019, Commonwealth Fusion Systems (CFS) closed a $115M Series A to commercialize fusion energy. That number is already a tell: in DeepTech, “Series A” is often not “fuel to scale” (like it is in software, by comparison), it’s fuel to survive the middle: pilots, first-of-a-kind engineering, and a regulatory path that sometimes is being built at the same time.
CFS itself notes “ARC” (its first grid-scale fusion power plant) as arriving in the early 2030s. In other words, even after a nine-figure “A,” you’re still staring down a decade-plus gap between promise and market reality.
Now, put that next to a typical software timeline.
Notion was founded in 2013 and first released to the public in 2016 (roughly a three-year path to a shippable product). And when Notion raised $10M in 2019, it was widely described as an “angel round” i.e., capital coming in when the product already existed and the business case was legible.
This is absolutely not an apples to apples comparison, but that is the point.
In software, a “Series A” often comes after the market has already confirmed demand. In DeepTech, a “Series A” can show up when you’ve proven something in a lab, but the hardest part is still ahead: building the thing in the real world, under real constraints.
Even the “normal” baseline makes CFS stand out: PitchBook’s 1Q 2019 Venture Monitor put the median early-stage VC financing at $8.2M. CFS wasn’t just raising “more.” It was raising a different category of money for a different category of timeline; and then being judged by investors who are structurally optimized not to thrive through that ugly middle bit.
The paradox then, is pretty obvious.
The same traits that make DeepTech valuable, make it nearly uninvestable.
It’s desired because it’s visionary, defensible, and impactful.
It’s avoided because it’s slow, uncertain, and illiquid.
Many investors want to be associated with DeepTech, but not live through the difficult middle.
I’m sure we’ve all heard the (slightly inappropriate) analogy – “spare me the labor pains, just bring me the baby”.
Where DeepTech Investment Actually Breaks Down
The failure point is in translation – between the research and business. This was obvious in the convo at the Sifted Summit with DeepTech founders; my question should have been answerable, if only to be a plug for the founders own DeepTech projects.
A team can build groundbreaking, life-changing tech, but will fail to:
- Define measurable milestones (this is much harder than it sounds)
- How do you define milestones for something that doesn’t exist yet, and you don’t know if, when, or how it will exist?
- Build governance and timeline structures that can withstand funding cycles
- Again, building governance for something that has yet to be governed or regulated – where do you start?
- Translate scientific proof into commercial readiness
- How to make a technological advancement / scientific breakthrough, marketable? Results is the obvious answer, but what if results are decades away?
Conclusion
DeepTech is, across the board, worth investing in. The ambition though, requires a longer fuse. We’re talking about true world transformation in some cases – and the patience for this demands more bravery, grit, and discipline from founders and VC’s alike.
DeepTech founders however, need to learn to sell, plain and simple. Marketing without a market plan, without concrete metrics for investor return, pivot points, and governance parameters are all big red flags with VC’s. Most venture investors are optimized for software-style risk/reward: low capital requirements, fast iteration, and relatively short time-to-market.
DeepTech needs to do a better job at making risk more quantifiable, and make the technology more analogous commercially.
Firstly, if every R&D milestone is not directly tied to a business KPI (e.g. cost per unit, performance metric), you’re missing an opportunity as a DeepTech founder.
Secondly (and this one is not going to be very popular), but move away from the story-book “making a better world”. Don’t abandon it outright- but don’t rely on this narrative. Build investor decks that translate science into economics and strategic moat – not a story about saving the world.
As much as “saving the world” speaks to me personally, it’s not going to be the line that moves the investor from a maybe to a yes.
Keeping business mechanisms at the forefront of DeepTech may seem a bit icky, but it’s the only way DeepTech makes it out of the vision stage, and into the hands of those who really need it; which is all of us on this planet who need big breakthroughs in health, science, climate and energy, now more than ever.