Introduction
Deep tech means high innovation technology, an innovation/discovery in science and technology, and advancement in engineering. Shallow tech is the opposite of that.
Artificial intelligence. Blockchain. Quantum computing. Virtual reality. Augmented reality. These are examples of deep tech and the startups that leverage these to solve problems are referred to as deep tech startups. These are those startups using these technologies to further enlarge their uses and discovery reach and whose business models are based on these emerging technologies.
Then we have the shallow tech startups who are not bad in themselves but simply digitalize solutions for instance a bookstore now using eBooks or a system using a fintech app instead of accepting cash. It is simply a better way of doing a thing and doesn’t revolve around new, innovative, disruptive technology.
It is important to note that these shallow tech startups that simply digitise solutions are very important to creating a digital economy in Africa, moving from paper-based systems to digital/online platforms, allowing people to connect digitally and ultimately uplifting society. Nevertheless, the disruption in sectors across the world would need the innovative power of deep tech.
The world of deep tech startups
As per the data sourced from Venture Capital Journal, funding allocated to deep tech startups witnessed a remarkable quadrupling, rising from $15 billion in 2016 to a substantial $60 billion in 2020. Presently, the cumulative valuations of these startups globally stand at an impressive $468 billion.
They attract a heavy amount of funding because they solve complex problems and innovate across industries. Deep tech startups solve problems that span across various sectors at the same time.
As articulated by Patricia Pastor, the CEO of GoHub, these entities possess an exponential innovative value, as they demonstrate an exceptional ability to address profoundly intricate problems effectively. You would imagine that an AI startup working on ways to simulate scenarios and generate manoeuvre plans for operators so they can avoid space collisions would not need anything below a ten million dollar funding; or a startup like Babara IOT, a deep tech startup using edge computing to enable the use of real-time data from sensors based on multiple devices in a facility or infrastructure. It served one of its clients Acciona, to deploy Artificial Intelligence models at the Edge, and predict chemical levels in the water supply and purification plant, based on real-time variables in a cyber-secure manner.
Even though they might have attracted huge amounts of funding, those funding came from very few investors. Investors typically invest in information technology compared to deep technology. This is because deep tech startups are riskier, have a higher chance of failing and tend to require a lot of time for their process to start to make sense. It is generally tasking and takes part of regular science experiments. It is also longer to reach the exit.
Unlike other startups really focused on what the market holds, what the customers say and whether it will sell or not, deep tech startups are focused on if it will work and how uncomplicated it must be when it is brought to market. It is difficult to push the world of physics, matter, time and space to create a machine, product or/and startup out of this to solve a problem for the industry. It is less concerned with the customer needs because it is needed and many times already in demand. By virtue of their existence, they already solve problems.
For instance, look at the field of medicine, the challenges in the way healthcare is managed already exist. Deep tech is required to disrupt the industry and cause great development in the sector. The startups that will be doing the change in this sector will require deep tech in AI, Machine learning and even Robotics.
It is also commonly known that deep-tech startups face very little competition. It is quite unexpected that someone else will go through the pain and hurdles to copy a deep scientific innovation. The little competition it faces is not a challenge but an indicator of how time-consuming building in this space is and the level of specialisation required. This means startups in this space would have employed deep specialists at every point of creation. Qualifying the risks associated with cutting-edge technologies becomes notably less precise, necessitating access to preeminent specialists well-versed in the respective fields.
The world of deep tech is also characterised by patents. Usually, a single startup would combine at least two technologies (e.g., AI & synthetic biology) which results in owning a few intellectual properties at once. In fact, investors prefer not to invest unless there is a robust IP strategy on ground, usually because it takes years before many deep tech startups are profitable and their IP would be the only valuable asset for some time.
Why Deep Tech?
The world’s problems cannot be solved with digitalization alone or with startups focused on obvious challenges in food, shelter and energy. The deeper problems of these very basic human needs will require science and technology. Many problems in Africa are truly technical and require technical expertise most of which cannot only be determined by the “customers” but also an understanding that technical knowledge brings and the demands per time of humanity as a whole.
For instance, let’s look at the venture called Predictive Insights which amalgamates the power of machine intelligence with profound economic and behavioural insights. This unique synergy empowers restaurants and retailers alike to anticipate demand, enhancing the accuracy of revenue forecasts up to 18 months in advance. It also fosters a reduction in costs and the environmental footprint by mitigating wastage.
We also see a startup like Puraffinity which is currently engaged in the advancement of adsorbent materials specifically designed for filtering PFAS, colloquially referred to as “forever chemicals” from water sources.
Then there is Fineheart which has successfully pioneered the development of an innovative permanent pump. This pump can be implanted through a minimally invasive surgical procedure and is uniquely powered through wireless charging technology.
What about the technology behind air protein? A startup making meat, which looks, tastes and cooks like meat but does not come from animals but rather from air created to reduce greenhouse emissions and fight climate change.
Lisa Dyson says that the food industry today produces more greenhouse gases than the entire transportation sector. What’s going to happen when we have 10 billion people on the planet? She asks.
Deep tech startups solve deep problems with deep technology that requires deep technical expertise/speciality in various sectors across the world.
Deep tech startups push technology barriers and are usually products of extensive work in research and development. In Europe, they have close ties with leading universities like Cambridge, MIT.
University students around Africa pass through three, four, five and more years engaging in research. Many are not even aware that they research all year long. Deep tech startups should be encouraged to give life to this theoretical-based knowledge and birth the future in solutions in Africa. It not only produces the solution we speak of but makes the university a finding place, a school of learning and practical, an area to experiment. The Professors, Doctors, and Lecturers in these universities with their strength in those technical fields automatically serve as advisors.
Conclusion
Although the world of deep tech sounds exciting, it is not as glamorous as it looks. Startups in this field must work. This means that it does require a lot of funding, time and patience to create and failure is dreadful. As described above, it is obvious that 80% of deep-tech startups require a physical product. Unlike SaaS technologies that can go to market even without being perfect, a deep tech startup will be crushed the moment it enters the market when it is imperfect. Unlike software technology products, revenue cannot be made unless it has gone to market and is accepted by the specific market it is made for.
Research and development should be encouraged as it is the mother of deep tech startups, but more importantly, investors must take up the responsibility of being financiers of innovation not just investors for the sake of it.
Nubia Capital is passionate about Impact Investing.
Nubia Capital is heavily involved in pouring our investments to improve the continent of Africa. Investing in African tech startups presents a unique opportunity to generate substantial social impact while fostering innovation and economic growth across the continent. By supporting these ventures, Nubia Capital addresses critical societal challenges, empowers local communities, and creates a lasting positive change.
Social Impact Focus Areas
Education: Investing in EdTech startups to revolutionise learning, improve accessibility, and empower students worldwide.
Healthcare: Backing HealthTech companies that develop innovative solutions to enhance healthcare delivery, patient outcomes, and accessibility.
Financial Inclusion: Partnering with FinTech startups to promote financial access and inclusion for underserved communities.
What are you building in these areas?
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