For much of the last decade, venture capital was dominated by software. The reasons were understandable. Software businesses could scale rapidly, required relatively little capital, and often reached enormous markets without building factories, supply chains, or other physical infrastructure. Investors became accustomed to companies that could move from concept to meaningful revenue in a relatively short period of time.
Deep tech followed a different path. Companies developing advanced manufacturing technologies, robotics, new materials, biotechnology, energy systems, aerospace, and industrial platforms typically faced longer development cycles, greater technical risk, and higher capital requirements. Building products that interact with the physical world has always been more difficult than deploying software.
For years, many investors viewed these sectors as harder to finance and slower to scale. While exceptional companies continued to emerge, deep technology occupied a relatively small share of the venture ecosystem, particularly as capital flowed toward software and internet businesses.
That perception is beginning to change. Over the past several years, a convergence of economic, technological, and geopolitical forces has renewed interest in deep tech. Artificial intelligence is accelerating research and engineering. Governments are investing in domestic manufacturing and energy security. Supply chain disruptions have exposed vulnerabilities that many businesses once overlooked, while advances in computing, automation, and scientific tools are making it easier to commercialize technologies that previously required far more time and capital.
The result is that deep tech is no longer viewed as a niche category within venture capital. Increasingly, it is being recognized as an important driver of economic growth, industrial competitiveness, and long-term resilience.
Innovation is Moving Beyond Software
Much of today’s technology conversation revolves around artificial intelligence, and for good reason. AI is already transforming how businesses analyze data, automate routine work, and build software. Yet some of its greatest impact may come from helping improve the physical systems that underpin the global economy.
Artificial intelligence is becoming a powerful tool for engineers, scientists, manufacturers, and researchers. It can accelerate product design, optimize manufacturing processes, improve logistics, enhance robotics, and speed scientific discovery. In many of these cases, however, software is only part of the story.
A more capable robot still depends on sophisticated hardware. New battery technologies still require manufacturing capacity. Medical breakthroughs still rely on laboratories, production facilities, regulatory approval, and distribution networks. Intelligence may increasingly come from software, but real-world impact often depends on the ability to build, manufacture, and deploy physical products at scale.
That shift is broadening the way investors think about innovation. Rather than separating software from hardware, many are beginning to view them as complementary. The most valuable companies of the next decade may not simply build better software, they may combine advances in artificial intelligence with engineering, manufacturing, biology, materials science, and industrial systems to solve problems that software alone cannot.
This shift is already becoming visible across multiple industries. Companies developing reusable launch systems, autonomous defense technologies, advanced manufacturing platforms, new battery chemistries, and breakthrough biotechnologies are combining sophisticated software with equally sophisticated physical engineering. Artificial intelligence may help design better products and accelerate research, but long-term value is ultimately created by successfully manufacturing, scaling, and deploying those technologies in the real world. Increasingly, competitive advantage comes from integrating software and hardware rather than choosing between them.
Those businesses also tend to develop different competitive dynamics than traditional software companies. Scaling a new manufacturing platform, commercializing a breakthrough material, or bringing an advanced medical technology to market often requires years of technical development, regulatory work, and operational execution. Those challenges can slow growth, but they also create barriers to entry that are difficult for competitors to replicate.
Artificial intelligence may strengthen those advantages even further. Better modeling tools, simulation software, automation, and data analysis are helping companies design products faster, run experiments more efficiently, and improve complex engineering decisions. Technologies that once seemed too capital intensive or technically difficult to commercialize may now reach the market much sooner than previous generations of founders could have imagined.
The result is a broader innovation landscape than many investors expected. AI will remain a powerful driver of value creation, but some of its largest economic impacts may come through companies using intelligence to improve how energy is produced, goods are manufactured, medicines are developed, and infrastructure is built.
Why Deep Tech Is Becoming More Important
Several long-term trends are reinforcing this shift. The pandemic reminded businesses and governments alike that physical infrastructure still matters. Supply chain disruptions exposed vulnerabilities that had accumulated over decades, while rising geopolitical competition highlighted the strategic importance of semiconductors, advanced manufacturing, critical minerals, and energy systems. Around the world, governments have responded with policies designed to strengthen domestic industrial capacity and reduce dependence on fragile global supply chains.
At the same time, the tools available to entrepreneurs have improved dramatically. Cloud computing, advanced simulation software, artificial intelligence, automation, and increasingly sophisticated laboratory equipment have lowered the barriers to scientific research and product development. Small teams can now pursue technologies that would have required far greater resources only a decade ago.
The commercialization ecosystem has also matured. Universities, research institutions, specialized accelerators, and experienced investors have built stronger pathways for moving scientific discoveries out of the laboratory and into venture-backed companies. Commercialization remains difficult, but founders have more support than ever before.
Many of these companies are pursuing problems with enormous economic significance. Whether the challenge is producing cleaner energy, improving industrial productivity, developing new materials, advancing biotechnology, or modernizing manufacturing, the markets are often measured in trillions of dollars rather than billions.
None of this eliminates the risks. Deep technology remains difficult. Development timelines are longer, technical uncertainty is real, and capital requirements often exceed those of software startups.
At the same time, solving difficult engineering and scientific problems can produce businesses with durable competitive advantages. Companies that successfully commercialize breakthrough technologies often become deeply embedded within the industries they serve, creating value that extends well beyond a single product or application.
For investors, that creates a different risk-reward profile than traditional software investing. The journey may take longer, but the potential impact can be significantly broader, with technologies capable of reshaping entire industries rather than simply improving existing workflows.
The Role of Specialized Investors
One of the defining characteristics of deep technology is that it often requires a different approach to investing than traditional software. Evaluating an enterprise software company typically centers on product-market fit, customer acquisition, and recurring revenue. Evaluating a company developing a new battery chemistry, robotics platform, advanced manufacturing process, or medical technology often requires a much deeper understanding of science, engineering, regulatory pathways, and commercialization.
That is one reason specialized investors have become increasingly important to the ecosystem. Many deep tech founders need more than capital. They benefit from access to prototyping facilities, manufacturing expertise, supply chain relationships, experienced technical mentors, and operational guidance that can help bridge the gap between scientific innovation and commercial success. Building a physical product often involves solving dozens of engineering and manufacturing challenges long before meaningful revenue begins to appear.
Organizations such as SOSV illustrate the value of this approach. Founded by Sean O’Sullivan and led by Managing Partner Stephen McCann, SOSV has become one of the world’s most active early-stage venture firms, investing in thousands of startups across deep technology, climate, health, and biotechnology. One of its best-known programs is HAX, an accelerator focused on hard tech and advanced manufacturing that helps founders move from prototype to production. Through HAX, companies receive far more than funding. They gain access to engineering expertise, prototyping facilities, manufacturing support, supply chain relationships, and experienced mentors who help bridge the gap between scientific innovation and commercial success.
Beyond accelerators, a growing group of specialized venture firms has also emerged to support founders tackling complex engineering and scientific challenges. Many focus on sectors such as climate technology, advanced manufacturing, industrial software, robotics, biotechnology, and resilient infrastructure. Rather than applying a one-size-fits-all venture model, these investors often bring deep domain expertise, technical networks, and long-term perspectives that better align with the realities of commercializing breakthrough technologies.
As deep technology continues to attract investor attention, these specialized ecosystems are likely to become even more important. Capital will always matter, but in many cases the expertise, networks, and operational experience surrounding a company may prove just as valuable as the investment itself.
Part 2 looks at why manufacturing matters again, how deep technology fits into a broader venture portfolio, and why software and physical innovation are becoming increasingly interconnected.
By Jarett Emert
