By Vibhore Sharma
It’s always winter for Deep Tech startups and founders. I would go as far as to call Deep Tech founders Eskimos living in the Tundra! Did you know the Eskimos call themselves “Inuit”, which means “the people”? In the span of a few months, the color of startup news has changed from flashy neon stories of high valuations to muted gray talks about mark-downs. Spirited conversations on growth have given way to somber questioning of runway and profitability. The total funding in the Indian start-up landscape fell by 40% to $6.8 billion during Q2 CY22, as per PwC.
It’s a tough time to raise money for startups everywhere but it’s just another day for Deep Tech startups. This is because they are not convincing VCs about the growth, users and multiples but about the mere possibility of their idea coming of age!
There are three challenges (apart from several others) that a Deep Tech startup needs to address to raise capital, which is not remarkably different from the non-Deep Tech paradigm.
There needs to be a stronger narrative of the problem that the startup/idea is solving – this is of great importance and relevance, not just for the VC audience but for the team as well since understanding this better will enable them to power the DBTL (Design-Build-Test Learn) engine that will lend a lot of structure and velocity to move in the desired trajectory. Not just that, this narrative has to flow from Science to application on a time scale and delve into current solutions, markets, ecosystems, regulations and policies, etc. – all the other factors that could help give a context to the direction and timing of the idea and move the conversation from possibility to outcomes, scale, revenue and even profitability. For the VCs, this story could help qualify the tech and market risk better at the early (design) stage itself and not take just a leap of faith for a far-out possibility as a binary call.
Second, since most Deep Tech companies are born in universities/research labs – there is an incredible amount of dependence on grants and rightly so, to transmogrify research into an application/solution which was not possible until now. By the time some of these companies start looking for institutional investors, there’s a large portion of equity taken away by the university, angels, accelerators, corporates and so on.
The startup founders must forge a pathway early in the DBTL cycle and meet VCs with the least possible dilution of the cap table. This would not only increase the possibility of VCs coming in early with a better understanding of tech/product/timing risk but also feed the startups with early feedback that would enable them to answer real-world queries and question their assumptions.
Lastly, Deep Tech founders should have a clear yet simple explanation of their technology (or science) and ownership of the IP (Intellectual Property) for it. It’s a hard one since the tech is what makes the company possible and not the other way round thus divulging or explaining more risks IP exposure. On the other hand, in the absence of technical due diligence, for most VCs, it becomes a difficult decision whether to invest or not.
In recent times, the vaccine for Covid19, the desperate need to address global warming and the rise of some outstanding work being done in Bio-tech, Space-tech, Electric mobility and infrastructure, etc. have helped recognise the potential of DeepTech to solve problems of great magnitude and that too at an unprecedented pace has led to governments, corporates
and VC firms focus on investing in Deep Tech. The time has never been better.
(The author is partner at Capital 2B. Views expressed are personal)