Deep Tech, Deeper Impact: Where Science and Investment Converge
How Science-Based Innovation Can Trigger Systemic Changes
Technology is often seen as a solution to the great challenges of our time. Yet while many digital innovations primarily offer efficiency improvements and comfort, they rarely have the potential to transform entire systems. Deep Tech is different.
Science-based technologies like synthetic biology, quantum computing, or advanced materials science do not just change individual processes — they attack the roots of our economy, industry, and society. They promise not merely incremental improvements, but fundamental upheavals: pulling CO₂ from the atmosphere, revolutionizing how energy is stored and transmitted, or healing diseases at the molecular level. However, precisely these groundbreaking innovations are capital- and time-intensive, subject to long development cycles, and require an entirely different ecosystem than classic tech startups.
The problem? Deep Tech alone is not enough. Technology only unfolds its true value when embedded in existing systems — and this is exactly where many science-based innovations fail. Without appropriate regulatory frameworks, market incentives, or scalable business models, even the most promising technologies often remain stuck in theory.
This article illuminates why Deep Tech startups, investors, and innovation programs must think differently if they want to enable genuine systemic change. For those who view Deep Tech only through the lens of classic venture capital models or short-term market expectations underestimate its actual potential. It’s not just about technological excellence — it’s about anchoring impact as an integral part of strategy.
Deep Tech Is Not a Sprint — But a Marathon
In a startup world characterized by quick exits and aggressive scaling, Deep Tech companies seem out of step with the times. While classic software startups can launch an MVP within a few months and generate initial revenues with minimal capital, science-based innovations often require years of research, prototype development, and regulatory testing before being market-ready.
Yet precisely here lies their decisive advantage. Deep Tech does not address short-term market trends, but fundamental problems — from decarbonization to cancer therapy. Those who develop such innovations create new markets instead of fighting for market share in existing ones. However, this process requires investors who focus not on quick profits, but on sustainable market leadership.
Why Patience Pays Off for Investors in the Long Term
The challenge: Traditional venture capital is optimized for rapid growth rates and short exit periods — a model that often collides with the realities of Deep Tech startups. While SaaS models can become profitable within a few years, innovations from materials research, robotics, or biotechnology may require a decade or longer to become commercially scalable.
Nevertheless, successful Deep Tech investors demonstrate that patience pays off. Breakthrough Energy Ventures, founded by Bill Gates, deliberately invests in groundbreaking climate technologies with a time horizon of 20 years — far beyond typical VC investment cycles. The strategy: Provide capital with foresight to guide innovations through the “valley of death” between research and market maturity.
For investors willing to think long-term, enormous opportunities emerge:
· Market Leaders Instead of Followers: Deep Tech companies that successfully scale often establish monopoly positions in new markets.
· Higher Entry Barriers: Complex development protects against quick copycats and ensures sustainable competitive advantages.
· Impact and Profitability United: Technologies with profound impact (e.g., CO₂ removal, new battery technologies) generate not just returns but are often political and societal priorities.
Investors and funding programs enabling Deep Tech do not bet on the next short-term hype — they are shaping the industries of the future. But capital alone is not enough: The interplay between science and business requires a new innovation ecosystem that rewards long-term thinking.
Great Ideas, Great Failure? Why Many Deep Tech Innovations Never Reach the Market
Long-term market opportunities and groundbreaking technologies — on paper, Deep Tech sounds like a safe bet. But reality looks different: A large portion of scientific innovations never make it beyond the laboratory phase. The reason? The notorious “Valley of Death” — the phase between basic research and market maturity, where many promising technologies fail due to lacking financing, market validation, or the right strategic orientation.
The “Valley of Death”: The Most Dangerous Hurdle for Science Startups
While classic startups can relatively quickly obtain product iterations and customer feedback, Deep Tech startups struggle with entirely different challenges:
· Long Development Times: New materials, energy innovations, or biotechnologies often require years of testing and approval procedures.
· Capital-Intensive Research: Without robust prototypes, many technologies are difficult for investors to grasp — and thus difficult to finance.
· Missing Market Pull: Scientists often develop groundbreaking technologies without checking whether the industry is actually prepared to adopt them.
But there are ways out of this dead end. Successful Deep Tech companies have understood how to bridge the gap between research and business.
Success Factors: How Deep Tech Startups Cross the Valley of Death
1. Think with Industry from the Start: Technologies developed in academic environments must be early aligned with economic realities. Successful startups work closely with potential industrial adopters to ensure their innovations actually have an addressable market.
2. Strategic Partnerships with Universities and Technology Transfer Centers: Many successful Deep Tech startups emerge through direct cooperation with universities and research institutions that provide not just intellectual property (IP), but also infrastructure and networks. Success models like the Fraunhofer model in Germany demonstrate how technology transfer can be efficiently organized.
3. Proof of Concept and Pilot Projects: Instead of focusing on a complete market entry, successful startups rely on scalable pilot programs with industrial partners to test and further develop their technology under real-world conditions.
4. Long-Term Capital Strategies: Many Deep Tech startups rely on a combination of public funding programs, patient capital, and corporate partnerships to survive the early development phase.
From Research to Scaling: The Next Big Step
The leap from scientific idea to market-ready product is enormous — but it’s only half the battle. Even when a technology is validated, the challenge of scaling remains. Deep Tech startups need completely different growth strategies compared to classic software companies. The next section illuminates what these look like and which scaling models work.
Impact Is Not an Add-on — But the Basis for Successful Deep Tech Companies
Deep Tech startups master enormous challenges to develop market-ready products from groundbreaking science. But even if they overcome the “Valley of Death”, a crucial question remains: What role does impact play in the business model?
Too many startups treat impact as a subsequent addition — a kind of bonus that might be considered sometime after product development and market launch. But that is precisely the mistake. Science-based innovations are often the only technologies that can solve systemic problems like climate change, resource scarcity, or health crises. If impact is not integrated into the business strategy from the beginning, many of these innovations remain economically and societally below their potential.
Thinking About Scaling AND Impact from the Start
Deep Tech startups must ask themselves early on:
· Is our technology merely more efficient, or does it enable genuine transformation?
· How scalable is the impact? Can our model trigger systemic change?
· Are there market mechanisms or regulations that favor impact-oriented business models?
Startups that define impact as a central value proposition benefit long-term — they attract not only far-sighted investors but also secure regulatory and societal advantages.
Climeworks: How Impact and Science Successfully Scale Together
An example of a Deep Tech startup that has integrated impact as a strategic core is Climeworks. The Swiss company develops Direct Air Capture technology for CO₂ removal — a solution that goes beyond classic emission avoidance and actively pulls carbon dioxide from the atmosphere.
What makes Climeworks successful:
1. Scientific Excellence Meets Market Viability: The technology is based on years of fundamental research but was scaled from the beginning with a clear business model.
2. Impact as a Driver for Financing: Investors like Breakthrough Energy Ventures and numerous climate funds have invested in Climeworks because the model is not just profitable but essential for the climate strategies of many companies.
3. Scalable Impact: Through long-term purchase agreements with companies like Microsoft and Shopify, Climeworks can offer CO₂ removal as a service — a model that is both economically and ecologically sensible.
Science as the Key to the Next Generation of Regenerative Business Models
The success of companies like Climeworks shows that science-based business models are not just economically viable but indispensable for systemic changes. However, to actually unfold this impact, they must overcome the next big hurdle: scaling. The next chapter will show why Deep Tech startups need different growth strategies than classic tech companies and how they achieve sustainable scaling.
Growth at Any Price? Why Classic Venture Capital Often Causes Deep Tech Startups to Fail
Deep Tech startups require years of research, extensive testing, and massive capital investments before they can enter the market. And precisely here lies the problem: The classic VC model is designed for quick exits and short-term returns — an approach that simply doesn’t work for most science-based innovations.
While software startups often generate initial revenues within a few months, Deep Tech ventures may require five to ten years before their technology becomes scalable and market-ready. This discrepancy leads to many Deep Tech startups either remaining undercapitalized or binding themselves to investors who lack the necessary patience.
Patient Capital: Why Groundbreaking Technologies Need Time
To finance groundbreaking technologies, an entirely different investment strategy is required — one that focuses not on quick exits, but on long-term transformation. Patient Capital, or long-term oriented capital, enables Deep Tech startups to continue developing their technology calmly, without having to make premature decisions under artificial market pressure.
Successful Examples of Patient Capital Investments:
· Breakthrough Energy Ventures (founded by Bill Gates) exclusively finances technologies that can achieve significant CO₂ reductions within 20 years.
· Evok Innovations, a Canadian Climate Tech fund, focuses on a 10 to 15-year perspective to successfully scale sustainable innovations in energy and industry.
However, long-term capital alone is not enough — smart financing structures are also needed to support startups in various development phases.
Blended Finance: When Private and Public Funds Collaborate
Blended Finance combines public and private funding sources to attract risk-averse investors for Deep Tech startups. This financing strategy is especially essential for startups with a strong impact focus.
How Does It Work?
· Public funds and grants (e.g., from the EU, state innovation agencies, or the World Bank) cover the risky early phases of technology development.
· Private investors enter later when the technology is validated and market potential is clear.
· Result: Startups receive capital without the pressure of quick exits, and investors can invest in secured, scalable business models.
An example is the European Innovation Council (EIC) Fund, which specifically finances Deep Tech startups and enables long-term scaling through a mix of public funding and private investments.
More Than Money — A Smart Capital Strategy Is Needed
Financing is one of the biggest bottlenecks for Deep Tech startups, but it’s not just about the amount of capital, but the right conditions. Sustainable innovations need investors who offer not just financial, but also strategic support — and who are willing to go the long road together.
But capital is only one side of the coin. The real challenge begins after financing: How do you build structures that make a Deep Tech startup efficiently scalable? That’s exactly what the next section is about.
Capital Alone Is Not Enough — Why Deep Tech Startups Need the Right Infrastructure
Even with Patient Capital or Blended Finance, Deep Tech startups face a crucial hurdle: They often lack the necessary infrastructure to bring their innovations efficiently to market maturity. Unlike the software industry, where new products can be created almost without physical infrastructure, science-based startups need high-tech laboratories, pilot plants, and specialized test environments.
This is where innovation clusters and specialized Deep Tech accelerators come into play. They offer not just financial support, but above all access to research infrastructures, regulatory expertise, and strategic partners from industry and science.
Deep Tech Doesn’t Grow in a Vacuum — Why Unconventional Hubs Shape the Future
The most successful Deep Tech ecosystems are no longer emerging only at well-known universities and research centers. Dynamic, often unexpected innovation hubs show that cluster formation can work beyond classic locations — when capital, talent, and political will come together strategically.
An example is the Armenian Deep Tech scene, which has developed into a growing center for AI, robotics, and quantum computing thanks to a strong global diaspora and strategic government initiatives. Programs like the Armenian National Science and Technology Fund or partnerships with international universities create an innovation-friendly environment that attracts talents from around the world.
Another role model is the Nordic Deep Tech landscape, where countries like Finland strategically use public-private partnerships to bring high technology to scale. The Nordic Deep Tech Business Summit brings together founders, investors, and scientific institutions, while programs like VTT LaunchPad in Finland connect research projects with industrial use cases. These models show that developing a strong Deep Tech scene depends not just on capital, but on targeted strategic networks and infrastructure.
Politics, Business, and Science — Radically New Cooperation Models Are Needed
Traditional innovation promotion mechanisms are often insufficient for Deep Tech startups. Regulations are not fast enough, classic funding models are too short-sighted, and industrial partnerships often emerge too late. However, some regions have shown that this problem can be solved with courageous, unconventional approaches.
An example is the Estonian E-Governance initiative, which provides startups with digital infrastructures to minimize regulatory hurdles. Here, the government acts not as a brake, but as an accelerator for innovative technologies — a model that enables Deep Tech startups to scale enormously quickly.
Singapore is also taking a radical approach, creating a platform with programs like SGInnovate that not only provides capital but specifically attracts international talents. Here, investors, regulators, and scientists work hand in hand to deliberately prepare Deep Tech startups in areas like biotechnology, quantum technology, and renewable energies for scaling.
These examples show: Successful Deep Tech ecosystems emerge where politics, science, and business not only coexist but actively work towards a common goal. However, even the best ecosystem is useless if leadership in Deep Tech startups does not grow along with it. That is precisely the next crucial point.
Why “Fail Fast” Is a Dead End for Deep Tech
While software startups can test initial market reactions with quick MVPs (Minimum Viable Products), this approach is often doomed to fail in the world of Deep Tech innovations. Development cycles are longer, regulatory requirements more complex, and many groundbreaking technologies have no immediate, mass-market application. Those who try to scale quantum computers or synthetic biology according to lean startup principles risk burning time and capital.
Instead, Deep Tech startups need a structured growth model oriented towards the phases of scientific and industrial development. From proof of concept through pilot projects to industrialization — each stage has its own challenges and requires specific financing and scaling strategies.
From Laboratory to Scaling: The Deep Tech Growth Path
A functional Deep Tech growth model typically passes through three central phases:
1. Proof of Concept (PoC): In this phase, the technological feasibility is demonstrated — often in university or institutional environments. Research funds, public grants, and specialized early-stage investors are crucial here.
2. Pilot Projects & First Commercial Applications: Companies test their technology in real-world environments — for example, through industrial partnerships or regulatory sandbox programs.
3. Industrialization & Scaling: The transition from a niche solution to a broad market requires substantial investments in production capacities, supply chains, and regulatory certifications.
Quantum Computing and Synthetic Biology: Why Long-Term Thinking Decides
Few areas demonstrate the necessity of long-term scaling strategies better than quantum computing. While classic software products can reach market maturity within months, quantum computers require decades of research, billions in infrastructure, and close collaborations between science, industry, and government. Companies like Rigetti Computing or IQM Quantum Computers therefore rely on a multi-stage scaling strategy that deliberately synchronizes research, hardware development, and industrial partnerships.
Synthetic biology looks similar. Startups like Ginkgo Bioworks have shown that the key to scaling is not in isolated product developments, but in creating standardized platforms that make innovation accessible to entire industries. This platform strategy enables efficiently scaling highly complex technologies with high investment needs, transforming not just individual products but entire market segments.
Scaling with System: Why the Right Partners Are Crucial
Deep Tech startups cannot afford to grow according to classic startup models. They need targeted partnerships with industry, science, and specialized investors to survive long development cycles and achieve market maturity.
The next chapter will explore exactly how these partnerships must be structured to not only bring Deep Tech innovations out of the laboratory but establish them as a transformative force in the economy.
Why Traditional KPIs Mislead Deep Tech Startups
The typical startup ecosystem often evaluates success through rapid growth metrics, user numbers, and short-term profitability. However, for Deep Tech startups whose innovation cycles often last ten years or longer, these traditional KPIs are not just inappropriate but potentially harmful.
A quantum computer will not be profitable after twelve months. A new biomaterial will not reach market maturity within a VC fund cycle. Evaluating Deep Tech startups by metrics developed for software startups either forces them into short-term thinking or causes potentially groundbreaking innovations to fail before they can unfold their impact.
Impact Must Be Thought Systemically — Not as an ESG Checkbox
Investors, accelerators, and strategic partners must develop new evaluation standards for Deep Tech startups. Instead of focusing on short-term revenue increases or user numbers, systemic impact should be at the center.
Possible New KPIs for Deep Tech:
· Scientific Validation & Technological Feasibility: Has the innovation been confirmed in independent tests?
· Systemic Scalability: Does the technology have the potential to transform an entire industry?
· Regulatory Feasibility: Is there a realistic roadmap for market approval and certification?
· Infrastructure Maturity: Are production, supply chains, and industrial partnerships present or plannable?
· Impact Multiplication: Will the technology lead to further innovations that can change markets long-term?
These questions help not only investors and accelerators make more substantive decisions — they also enable Deep Tech startups to align their development more strategically instead of being pressured by short-term financing cycles.
Deep Tech Needs Its Own Evaluation System — and a New Mindset
If the goal is truly groundbreaking innovation, the startup ecosystem must adapt. It is not enough to evaluate Deep Tech with classic startup metrics and then wonder about lacking scaling.
Instead, a framework is needed that considers the special dynamics of science-based innovations — and investors who understand that genuine transformation takes time.
The next section will explore exactly how investors and accelerators must adapt their strategies to not just finance Deep Tech startups, but to make them successful long-term.
Why Classical Due Diligence Fails Deep Tech
The traditional venture capital ecosystem often evaluates startups using a standardized set of criteria: Market size, traction, monetization potential, scalability. However, Deep Tech startups do not operate by the same rules as software or platform models. Those who measure them with classical VC due diligence approaches not only risk making incorrect decisions but also hinder groundbreaking innovations.
Deep Tech requires a different set of evaluation metrics — one that incorporates scientific and systemic factors. A company extracting CO₂ directly from the atmosphere or developing a new form of energy storage cannot be measured by whether it reaches an ARR (Annual Recurring Revenue) of 10 million dollars within 18 months. This is about long-term transformation — and this should be reflected in investment criteria.
New Investment Metrics for Long-Term Impact
Institutional investors, incubators, and accelerators seeking to specifically promote Deep Tech should adapt their evaluation criteria. Important questions that should complement classical due diligence:
· Technological Maturity: Is the scientific basis robust? Are there independent validations?
· Regulatory Environment: What hurdles exist for approval, certification, and scaling?
· Impact Multiplier: Does the innovation lead to systemic changes in markets or industries?
· Infrastructure Scalability: Are production capacities, supply chains, and industrial partnerships present or realistically buildable?
· Long-Term Capital Strategy: Is financing structured to support the long development cycles of Deep Tech?
An example of this is “Impact-Weighted Accounts”, a methodology developed at Harvard Business School. It goes beyond ESG ratings and quantifies a company’s real social and ecological impact in financial numbers. Approaches like these should be a fixed component of due diligence for Deep Tech impact startups.
From Short-Term ROI to Long-Term Impact — A Mindset Investors Must Change
Many institutional investors are already beginning to think beyond classical financial returns. However, Deep Tech investments require an even more consistent paradigm shift: away from short-term exit strategies towards sustainable capital that enables innovations transforming entire industries.
More funds are needed that focus on long-term impact instead of just the next “unicorn bet”. Models like Patient Capital, Blended Finance, or Public-Private Partnerships are crucial to not just finance Deep Tech startups but to accompany them to actual market maturity.
From Deep Tech to Deep Impact — Why Context is Crucial
When Deep Tech startups are to scale, it is not enough to only look at technological innovation. The greatest breakthroughs do not fail due to lacking research, but due to missing systemic change. This is exactly where COSMICGOLD comes in: Our venture studio approach combines science-based innovation with strategic scaling — and ensures that groundbreaking technologies do not remain stuck in the laboratory phase but create real market transformation.
Our Model: Impact Measurement as an Integral Part of Venture Building
We work with scientists, engineers, and developers to build not just new technologies, but truly regenerative business models. Our process begins not only with scaling, but already in the due diligence phase:
- Systemic Impact Instead of Isolated Technology We analyze early on whether an innovation can go beyond pure product solution and effect structural changes in markets or industries.
- Long-Term Scalability Technologies with impact potential require different growth strategies than classical SaaS models. We ensure that infrastructure for industrial scaling is co-conceived — from regulatory requirements to manufacturing processes.
- Measurable Impact Through Integrated Impact Methodology Instead of subsequent ESG optimization, we employ the Lean Impact Assessment Canvas and the Regenerative Business Model Canvas from the start to make impact measurable and controllable.
Deep Tech Startups Need an Ecosystem — We Build It
A scientifically excellent startup alone is not enough — it requires a strong network of investors, industrial partners, and political actors to enable true market transformation. COSMICGOLD acts not just as a company builder, but as a catalyst between Deep Tech and the structures necessary for systemic change.
This means: We do not focus on isolated success stories, but on strategic ecosystem development. Because only this way can Deep Tech unfold its full impact potential — and shape the markets of the future.
Technological excellence alone is not sufficient — only in combination with the right market strategies, financing models, and stakeholder networks is real impact created. The question is no longer whether Deep Tech startups can scale, but how we can specifically support them in doing so.
Deep Tech Needs Deep Commitment
Scientifically grounded innovations are the key to sustainable transformation — but their success depends on more than just technological progress. Deep Tech startups have the potential to change entire industries, but only if they are supported with long-term thinking, strategic scaling, and the right infrastructure.
Startups, investors, and funding programs are at a turning point. Those who continue to think in short-term cycles and measure Deep Tech startups against classical software metrics will not be able to exploit their potential. Scientifically founded innovations need time, capital, and robust partnerships to progress from research to industrial application. This requires new evaluation standards, adapted financing models, and an ecosystem that looks beyond quick exits.
Now is the moment for a rethink. The question is no longer whether we can develop groundbreaking technologies — but whether we as a startup ecosystem can create the structures that will elevate these technologies. Deep Tech can shape the future. But only if we approach it correctly.
