Deep tech startups are a subset of technology startups. Artificial intelligence (AI), life sciences, agriculture, aerospace, chemistry, industry, and clean energy are the primary areas in which deep tech startups are working. Deep technology rarely exists in isolation. Because it is a game-changer by definition, we may see aerospace technologies used to monitor crop conditions, or an AI advancement applied to the production of clean energy or patient monitoring.
Deep tech differs from shallow tech and other types of startups in several ways. Since technology underpins the entire business, deep tech startups typically have a board of advisors that includes CTOs, not just CEOs. They will frequently have patents or other intellectual property, and they will have spent years in a lab or other research testing before attempting to bring the technology to market.
Deep tech startups frequently require large long-term investments as well as extensive research. Commercial success may also take longer because we are discussing disruptive technologies that may take longer to achieve widespread market adoption. The good news is that when they do reach the market, competitors will find it difficult to replicate what they’ve done. They will almost certainly rewrite the rules, rendering other businesses obsolete.
Consider a fintech that uses blockchain to increase client security and enable them to bank from their phone on a global scale with low overheads. They have the potential to disrupt the old business model of uncompetitive local banks with cumbersome bureaucratic processes and high fees, which we are seeing more and more of today.
Where’s It Headed?
Deep tech fields such as AI, advanced materials, blockchain, biotechnology, robotics, drones, photonics, and quantum computing are moving from early research to market applications at an increasing rate. In some ways, it’s a new industrial revolution, with new platform technologies and infrastructures drastically altering how we live and work.
When you consider how much has changed since the last wave of new platform technologies such as the internet, mobile technologies, PCs, and silicon chips, you can see how far deep tech can advance broad industries and solve or mitigate global problems such as global warming, disease, feeding a growing global population, and dealing with ageing populations.
3D printing, DNA sequencing, and computer-aided design all contribute to the test and prototype stages being more accessible and faster than ever before. So, in some ways, the more these deep tech platforms advance, the broader their possibilities become, and the faster they’ll reach the market. Because of their complexity, scouting for deep tech startups requires a few extra considerations when compared to general startup scouting. Some examples are: Longer investment cycles
Deep tech startups take much longer to mature due to the significant technological advancements required. Creating and commercializing a product typically requires years of consistent investment. Deep tech startups can be an excellent catalyst for an organization’s long-term innovation goals. However, matching the time horizons can be difficult for companies that need to react quickly, and investing in other tech startups may be a safer bet.
Technical Risk Outweighs The Market Risk
Since there isn’t usually a market for competitors to be in, market risk is often minimal to none. Deep tech startups, on the other hand, pose a significant technical risk. If the novel technology fails to deliver on its promise, investments may be rendered ineffective. An unbiased tech evaluation is required for a corporate looking to collaborate with a deep tech startup. Investing in an independent audit of the technology can expose you to risks ranging from overinflated valuations to outright fraud.
Patents are critical for deep tech startups to protect their innovations. Before collaborating, a company must assess the potential of a startup’s intellectual property and determine the best way to incorporate it into or alongside internal projects.
Numerous Different Founder Demographics
The ease with which “shallow tech” startups can be built is a prominent feature, especially now that no-code tools are available. Two friends working out of their garage may create the next 10-minute grocery delivery app, but they are far less likely to create cultured meat that is the same price as animal meat. Deep tech startup founders, on the other hand, are frequently PhDs or have significant academic experience.
In BioTech and pharma, two industries where innovations are mostly deep tech, there are more founders with PhDs than without. Many of these businesses are spun out of academic or research institutions. Deep tech risks are frequently exacerbated by the founders’ lack of industry expertise.
Why Collaborate with Deep Tech Startups?
Most companies want a quick return on their investment. That is extremely unlikely to occur when investing in deep tech startups. So, why should you invest in deep tech when your competitors could make a quick buck? Here are three of them:
1. Create non-existent markets
Consider a biopharma company developing a novel drug or a MedTech company developing a surgical device to treat a previously incurable disease. Needless to say, if either of these startups succeeds, they will almost certainly be the first, and for a long time, the only, startups to serve this niche. Deep tech scouting provides unrivaled opportunities for the duration of the protection by creating a market where none previously existed.
2. Take a Technology-First Approach
Companies develop new technologies in one of two ways: marketing-first or technology-first. Companies in the first approach survey markets to understand customer needs before developing products to meet those needs. That works for most businesses most of the time, but the most significant innovations necessitate a technology-first approach.
A technology-first approach entails both greater risks and greater rewards. Working with deep-tech startups allows businesses to reduce the risk associated with this approach. Even so, most businesses will benefit from a healthy mix of market-first and technology-first innovation projects.
3. Discover New Business Opportunities
Deep tech startups are developing disruptive technologies that outperform the status quo. Furthermore, the majority of deep tech startups operate at the intersection of multiple such technologies. Working with such startups or scaleups allows companies to identify new use cases and opportunities for these technologies through open innovation. The deep tech ecosystem has the highest level of idea cross-fertilization of any startup activity. Using these concepts allows businesses to gain or maintain a competitive advantage.
Deep tech startups typically take longer to develop and require more capital in terms of the total investment for all of the reasons stated above. Most traditional venture capital funds are designed to work with technology startups and are frequently structured as a 10-year fund.
This timeline is insufficient for a science-based startup. As a result, it may be difficult for a science-based startup to raise funds from the same sources and on the same timeline as traditional tech startups. Angel, seed, A, B, and C round structures are rarely used.
So, what do the majority of people do? They frequently stay in the lab for longer periods of time in order to take advantage of research grant funding to harden and mature the scientific invention. Once the technology leaves the university, the startup team is frequently required to seek additional equity-free grant funding, either from the federal government (e.g., SBIR grants from the National Science Foundation) or from other grant funding sources, such as non-profits interested in advancing science in your field of interest.
Another distinction is a deep tech startup’s ability to use traditional iterative startup techniques to build their business. Before developing a solution, most tech startups should define the problem and understand the customer and end-user. The solution is discovered through iterative market experiments with end-users.
This is not the best path for a deep tech startup, because science is the foundation of the startup’s IP (intellectual property). So they must work backward to identify a problem worth solving and capable of being solved by the scientific invention, and then validate that the market is large enough. This is more difficult than starting with the problem – and it will take more time and resources
Deep tech advancements have the potential to change the world. Go for it if you have a significant scientific invention that you want to commercialize! Simply read everything you can about grant-based funding, talk to others who have done it before you, and expand your knowledge of how to proceed. Your path will differ from that of a tech startup (even in hard techs such as robotics or industrial automation), and that’s fine. All you need to do is be informed and plan for success.