The Hidden Challenges of Scaling a Deeptech Startup

The Illusion of Scaling in Startups

In the world of startups, we often hear stories of rapid growth—companies going from idea to product-market fit in a matter of months, securing millions in funding, and scaling at an astonishing pace. The dominant narrative, particularly in venture-backed businesses, is simple:

1. Build an MVP.
2. Test with early adopters.
3. Iterate, raise capital, scale exponentially.

For deeptech startups, this playbook simply does not work.

Deeptech, by its nature, is fundamentally different from traditional software or consumer startups. It requires significant scientific breakthroughs, extensive R&D, complex hardware integration, and deep ecosystem dependencies. The result? A much longer and riskier path to commercialization.

This reality creates three major challenges that make deeptech one of the hardest sectors to scale:

• Funding is harder to secure because investors hesitate when they don’t see an immediate revenue path.
• Sales cycles take years, not months, because enterprise adoption is slow, often requiring regulatory approval and multiple decision-makers.
• No company succeeds alone—deeptech thrives in ecosystems, not in isolation.

Through my experience in deeptech strategy and commercialization, I’ve seen these challenges firsthand. Let’s break down what makes scaling deeptech uniquely difficult—and how founders can navigate these barriers.

Deeptech Funding: Why Are Investors Hesitant?

For most deeptech startups, securing funding isn’t just about demonstrating traction—it’s about educating investors on a completely different risk-reward model. Unlike SaaS or consumer tech, where investors look for rapid adoption and predictable revenue growth, deeptech follows a longer, less linear trajectory.

A typical VC fund operates on a 5-7 year exit timeline. Investors expect to see clear evidence of traction within the first 2-3 years after investment. This works well for software startups that can quickly launch an MVP, iterate based on user feedback, and scale at low cost. But deeptech, by contrast, may need 5-10 years of R&D before a product is even market-ready.

Many investors struggle to evaluate deeptech because:

• They are used to software metrics (ARR, CAC, LTV), which don’t apply to capital-intensive, hardware-driven innovation.
• They find it difficult to assess scientific risk. Unlike software, where execution is the main risk, deeptech innovations often face technological and commercialization risks.
• They hesitate due to high capital requirements. Deeptech often needs early-stage funding for R&D before reaching a commercially viable state, making it riskier from a VC perspective.

This creates a funding gap—traditional VCs are reluctant to invest, while corporate and government funding often moves too slowly for early-stage startups.

How Can Deeptech Startups Overcome the Funding Barrier?

Rather than relying solely on VCs, deeptech startups must diversify their capital sources and rethink how they frame their value proposition.

1?? Shift the investor narrative. Instead of focusing on short-term traction, position deeptech as a long-term, defensible market creation opportunity. Highlight the unique advantages of deeptech, such as high IP protection, industry-wide impact, and long-term competitive moats.

2?? Show traction beyond revenue. While revenue is the primary indicator of traction in traditional startups, deeptech founders must highlight other proof points that de-risk investment, such as:

• Partnerships with industry leaders
• Research validation and successful pilot projects
• Interest from large enterprises, even if deals are not yet finalized
• Government or non-dilutive grants

3?? Target alternative capital sources. Given the hesitancy of traditional VCs, deeptech startups should consider:

• Corporate venture arms of large enterprises that see strategic value in the technology.
• Government funding and non-dilutive grants for research-heavy innovations.
• Deeptech-specialized investment firms that understand the risk-reward dynamics of the space.

Deeptech isn’t just about funding rounds and investor pitches—it’s about aligning with the right capital providers who understand the ecosystem.

The Sales Cycle Dilemma: Why Deeptech Adoption is So Slow

Even after securing funding, deeptech startups face a major commercialization challenge: enterprises don’t adopt disruptive technology overnight!

Unlike SaaS, where businesses can implement a new tool in a few weeks, deeptech often requires industry-wide change, regulatory compliance, and large-scale integration. This results in multi-year sales cycles, making revenue growth a slow process.

From experience, I’ve seen that deeptech sales cycles are prolonged due to:

• Multiple decision-makers involved. Unlike consumer products, where a single buyer makes a purchase, enterprise deeptech deals involve R&D teams, procurement, compliance, finance, and C-level executives.
• High switching costs. Businesses are reluctant to replace existing systems unless the new technology offers a massive, undeniable improvement. In other words, unless your solution offers the industry a STEP CHANGE in performance, cost and/or efficiency, it is NOT enough to be better than what works today in the industry.
• Regulatory approvals. Many deeptech solutions in healthcare, materials, or energy require certifications and government approvals before commercialization.

For a deeptech founder, this reality can be frustrating—especially when investors expect fast traction despite the nature of enterprise sales.

How Can Deeptech Startups Shorten the Sales Cycle?

1?? Start building industry relationships early. Enterprise customers are not impulsive buyers. Engaging them years before commercialization allows time to align interests, refine use cases, and integrate feedback.

2?? Use partnerships to accelerate adoption. Rather than selling directly, deeptech startups should embed themselves into existing ecosystems. Partnering with established industry players can help bypass lengthy adoption barriers.

3?? De-risk enterprise adoption. Instead of pushing for large contracts immediately, consider:

• Pilot projects that allow customers to test the technology before full adoption.
• Joint research collaborations to establish credibility.
• Co-funding models where customers share the investment risk.

Sales cycles in deeptech may be long, but proactive market engagement and de-risking adoption can help move things forward faster.

Scaling Deeptech: It’s an Ecosystem Game

One of the biggest lessons I’ve learned is that deeptech doesn’t scale in isolation. Unlike consumer tech, which can often rely on network effects and viral growth, deeptech relies on industry adoption, R&D alignment, and supply chain partnerships.

Success in deeptech comes from building an ecosystem—engaging with customers, suppliers, investors, and research institutions to align interests and de-risk commercialization.

Final Thoughts

Deeptech startups face funding challenges, long sales cycles, and complex adoption barriers. But those who position themselves correctly, engage early, and leverage ecosystem partnerships will be the ones to succeed.

?? For those in deeptech:

• What’s been your biggest challenge in scaling?
• How have you approached funding and enterprise adoption?