No pitch, no plan, no capital: Why deep tech fails to secure funding – and how we can change that
- Arise Innovations
- Mar 28
- 10 min read
The fog has cleared – at least linguistically. In the first part of this series, we showed why it matters whether you say high tech, deep tech, or tough tech – and how this vagueness determines which technologies are funded, scaled, or forgotten.
But now things are getting serious.
Because concepts are only the beginning. The real question is:
How do we finance technology that doesn't yet fit into PowerPoint – but could secure our future?
— eM.
In this article, we show why the current funding system for deep tech doesn't work, which misconceptions lead startups astray – and what a capital architecture based on scientific depth, not market cosmetics, could look like.
Welcome to part two: reality.
Funding without foundation – Why the system doesn’t understand deep tech
What happens when you confuse scientific readiness with SaaS logic
In theory, it all sounds quite logical. There's funding for the early stages, venture capital for scaling – and somewhere in between, a pitch deck that ties everything together. A seemingly well-thought-out system.
But in reality, this very system acts like an obstacle course for many deep or tough tech founders. Not because they don't master their technology, but because the system applies the rules of a completely different playing field.
Grants are too often misunderstood as a free cash cow – not as what they really could be: a strategic lever for validation.
Venture capital asks about KPIs such as traction, retention and scaling – and ignores the fact that in many cases the market has to come into being first through the underlying technology.
And the startups? They learn to adapt. They learn to make themselves "investable." And in doing so, they lose precisely what distinguishes them: depth, logic, scientific substance.
What remains is a pitch deck that fulfills expectations but doesn't reflect reality.
And if that isn't one of the greatest insults to science, what is?
— eM.
Grants: Not a cash gift, but strategic capital
Many research-oriented founders who come from academia, in particular, start with funding. And that's understandable – because they're often the only known funding path. The system knows them. They feel secure. They seem approachable.
But therein lies the danger.
Too often, grants are viewed as a means to an end – a subsidy to be "taken" when it's convenient. Or as a stopgap measure until "real" capital arrives. But they are much more...
Grants are not a gift of money. They are a strategic tool.
Used correctly, they can:
Securing technology paths
Making cooperation potential visible
prepare the capital architecture
Generate industry interest – long before a market exists
But what many overlook is that funding is almost always geared toward early-stage development. It doesn't finance scaling, go-to-market, or industrial integration.
And that is precisely why a dangerous gap arises at the end of many projects – between the final report and the actual connectivity.
What's often left is a good idea. A promising technology. And another great publication that never makes it to market.
Anyone who does not see funding as part of an overall strategy, but rather as a singular solution, will never get beyond the laboratory-scale prototype stage.
— eM.
VCs: Expectations meet reality distortion
For many startups, venture capital seems to be the next logical step – especially when funding has been exhausted.
But that's also a fallacy. Venture capital was built for a completely different playing field: software, platform models, products with a clear market, rapid scaling, and measurable user logic.
The associated metrics – CAC, LTV, ARR, TAM – work there. But in deep tech, they fail inevitably.
Because this isn't about app downloads or user loyalty. It's about:
physical scalability
regulatory penetration
industrial adaptation in complex systems
scientific validation over years
And yet you hear the same questions again and again:
“How big is your addressable market?” or
“How quickly can you scale to 10 million in revenue?”
It's like measuring a molecule with a tape measure. It's not only pointless – it's dangerous. Because it legitimizes wrong decisions.
Even more problematic is that grants and VC are often seen by the public as the only financing options.
Deep tech is still severely underrepresented in the startup scene – and the debate about financing is far too one-dimensional.
There are at least ten alternative sources of capital that would be significantly better suited to research-based technologies – more strategic, more patient, more effective.
— eM.
What's missing isn't capital. What's missing is an understanding of capital architecture—and a culture willing to think deeper rather than scale faster.
And what are the startups doing? They're playing along.
Many research-oriented founders do what the system demands of them: They translate their science into KPIs that investors want to hear – even though they know that these KPIs have no relevance to their reality.
They smooth out the narrative. They abstract the complexity. They fill in templates designed for platform startups – not for science-based technologies. And in doing so, something happens that is dangerous in the long run:
Technology is molded into shape before it is understood.
— eM.
The assessment is not based on technological potential – but on the ability to meet expectations that do not fit the nature of the technology.
Scale ≠ multiply
An example.
A startup is developing a novel nanomaterial for thermal management. Everything works in the lab – small, precise, and controlled. The effect is measurable. The results are promising.
The VC asks the classic question:
“Can this be produced in large quantities?”
The scientifically honest answer would be:
“Maybe – but then the material behavior changes.”
Because in materials development, "bigger" doesn't simply mean "more." It means different surface conditions, different interactions, different properties. And with different properties, the application context also shifts – sometimes so drastically that it becomes a completely different product!
But there's no room for such discussions in the classic pitch deck. Physics doesn't matter there. What matters is scalability. And the narrative.
Financing fails not because of the idea – but because of the system
The real problem isn't with the startups. It's with a system that claims to be technology-open, but in reality only favors technologies that can be easily mapped on Excel sheets and pitch decks.
The consequences are profound:
Capital is allocated incorrectly – where it is easily measurable, not where it is necessary
Projects are canceled because they do not meet the wrong KPIs
Research is made “marketable” too early – and loses its scientific substance
And many of the most promising ideas disappear again – not because they were bad, but because they did not fit the grid
What remains is an ecosystem that claims to promote innovation – but in reality systematically eliminates complexity.
If we want technology to reach where it is needed, we must stop funding it like software.
— eM.
We need a different understanding of financing:
technology-centric, multi-level, strategic.
In the next chapter, I'll show you how we at Arise Innovations do just that – with capital architectures, scientific readiness, and a deep understanding of the nature of technology and time.
The Arise Innovations approach – capital strategies from the depth of technology (reverse-engineered)
Why we don’t think about fundraising from a pitch perspective – but from a physical potential perspective
If you want to understand why so many technology-driven startups fail to secure funding, you have to ask yourself a simple question:
Where does the strategy begin?
For many, it starts with the market. The TAM. The use case. The pitch deck.
For us, it starts with technology.
— eM.
Because technology is not a means to an end. It is the origin. The beginning. The driving logic – not its appendage.
That's why at Arise Innovations, we don't develop capital strategies based on templates or benchmark data. Instead, we work backward: from physical potential to the appropriate structure. From the current state of research to the strategic path.
Reverse engineering – but in capital.
We don’t ask: “What does the market expect?”
But rather: “What does this technology need – in terms of time, finances, infrastructure – to become a reality?”
Capital architecture instead of funding round
The common model looks clear: Pre-Seed, Seed, Series A, Series B...
A path that you simply have to walk along – that’s the narrative.
But this narrative was not written for Deep Tech.
Because deep tech doesn't work linearly. There are detours. Loops.
Validation steps that arise not in decks, but in data. And that's precisely why we don't need phases – we need architecture.
Capital architecture means:
Funding not as a gap filler, but as a basic building block
Industry partnerships not as validation, but as proof of application
Venture capital not as an end in itself, but as an option at the right time
Debt instruments, IP monetization, corporate co-development – not as a plan B, but as an indispensable part of the landscape
Why all this? Because a linear financing logic doesn't fit non-linear technologies .
Technology-market fit instead of product-market fit
In the world of classic startups, product-market fit is considered the holy grail:
A product meets a specific need that already exists.
But what if the market doesn’t even exist yet?
What if technology comes first – and the need it solves only becomes visible through it?
Welcome to the world of deep tech.
A different principle is needed here: technology-market fit.
We don’t ask: “Who needs this today?”
But rather: “Which markets can develop from this technology – over time?”
This requires more than market research:
Time to allow validation and understanding
Analytical ability to correctly interpret signals
Industry knowledge to identify potential
System understanding to think of technology not in isolation but in an embedded way
Arise Innovations' three thinking tools
To make this approach tangible, we work with three strategic frameworks. They help us – and our clients – bring clarity to complexity:
1. Scientific Market Readiness
A framework that connects scientific maturity (e.g., TRL) with market potential. It builds the bridge between laboratory data and business model – and shows when a technology becomes viable and where .
2. Scalability Paradox
The widespread assumption: Scalability = good. But in deep tech, the opposite is often true: Scaling changes properties. And thus the business case.
A nanomaterial works in the microgram range – but what happens when you produce it in kilograms?
Physics changes reality. And we need capital strategies that understand this.
3. Innovation Asymmetry
Innovation costs and risks are systematically unequally distributed. Startups bear the burden – while industry and investors wait to catch up.
Our approach: rethinking risk sharing and capital allocation.
About consortia, funding logic, and co-investment structures. Not as an exception – but as a structural principle.
The difference in thinking
Investor readiness is often equated with: a compelling narrative, a clean deck, a roadmap for rapid growth.
For us, investor readiness means something different:
Technology expertise + capital architecture + market proximity
Not in the form of storytelling. But in the form of structure, depth, and an honest exploration of insecurities.
Because trust isn't built through perfect presentations. It's built through understanding: We know what this technology needs – and why.
How to do it better – A new way of thinking for Tough Tech & Deep Tech Funding
Funding must be based on physics – not PowerPoint
A pitch deck can do many things. It can tell a story. It can generate interest. It can attract investors.
But technology tells a different story.
And this story is rarely linear. It is fragmented. Experimental. It consists of iterations, hypotheses, setbacks, and breakthroughs. It doesn't require a smooth surface – it requires structural understanding.
But this is precisely where the problem begins: Funding often resembles a filter that filters out everything unclear. What's left is a narrative – but no strategy. A case – but no concept. A promise – but no plan.
If we really want to fund technology, we need to stop smoothing out its reality in pitch slides.
— eM.
Strategy instead of storytelling
Many deep-tech startups get what the system considers "help": pitch coaching. They learn how to approach investors, how to build the right slides, how to insert the perfect traction graphic.
But what they really need is something else:
Strategic navigation through uncertainty.
You don't need sales coaches. You need strategy architects.
People who:
be able to not only read scientific data but also classify it
Anticipate regulatory pitfalls before they become expensive
Orchestrate consortia – not just present
Build capital structures that do not exclude uncertainties, but rather support
and understand that timing in Deep Tech has a different dimension than in the software world
Deep tech doesn't need a stage. Deep tech needs structure. Protection. Planning. And partners who understand the system – not just the market.
— eM.
What needs to change
If we want deep and tough tech not only to exist but to have an impact, it is not enough to simply explain the rules of the game better.
We have to change the game.
This doesn't require a revolution. But it does require a new way of thinking:
Investors need more technology expertise. Not all of them – but some. Those who can build bridges. Those who understand that a TRL-6 isn't a bad KPI – but a milestone with substance.
Startups need guidance, not formatting. They need the freedom to be guided by physics – not by the pitch. And they need partners who see that as a strength, not a weakness.
Funding institutions must become bolder. It's not enough to push "high tech." We need programs that make in-depth research affordable – even if it's complex. Even if it takes time. Especially then.
🟣Substance instead of surface
This isn't about criticizing investors, nor is it about shifting responsibility.
It's about rethinking a system that has been based on false assumptions for too long.
A system that wanted to evaluate technologies before understanding them. A system that simplified complexity until it became harmless – and in the process lost its intrinsic value.
But good technology never begins with marketing. It begins with substance. With depth. With the willingness to endure the unknown – and still keep going.
— eM.
So perhaps the next big deep tech breakthrough won't be about who builds it, but rather how we finance it.
Takeaway message:
At best, an (ex-Big 4) MBA without a scientific degree is supposed to help with operational structuring of the numbers. But anyone who sees it as a solution for science-driven financing hasn't understood the playing field.
This – often unconsciously – devalues an entire scientific community that has researched for decades to even get to this point.
💡 Ready to stop pitching and start strategizing?
→ Click here to see our Deep Tech Funding Pipeline
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💜 Because Science doesn't follow Rigid Business Logic
eM. from Arise Innovations
— Your only partner for deep tech fundraising through reverse engineering
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