Paromik Chakraborty speaks with Somshubhro (Som) Pal Choudhury, partner, Bharat Innovation Fund (BIF)—a US$ 100 million early-stage venture fund for deep-tech IP-led startups in India—to understand how the fund plans to handhold the Indian startup ecosystem in its progress.
Q. How does the Indian startup ecosystem look today?
A. It has evolved with global and local venture capitalists, angel/seed funding, 200-plus accelerators/incubators along with 1000-plus MNCs that have made India their R&D hub. Majority of startup founders are experienced, are well-travelled, have worked globally and are, hence, more focused on creating globally-competent products and platforms.
Many challenges still remain. Businesses continue to be lukewarm in adopting new technologies. Cheap labour in comparison to other developed regions is delaying automation ROI. There is a lack of confidence in home-grown startups and a pervasive mindset of squeezing the best possible price out from them.
Q. Which application verticals provide the best business opportunities for electronics and tech startups?
A. For startups, a purely hardware play might prove difficult in a competitive landscape. But a hardware-software combination—which builds on the software strength of India—that captures the physical world data and then uses artificial intelligence (AI) and machine learning (ML) to build an analytics solution is where the opportunity lies.
While there are opportunities to innovate in the electronics sector alone, with sensors, bio-printing, AI/ML hardware accelerators and so on, the pool of such innovative startups from India is relatively small, and they need to compete on these fundamental technologies globally.
Q. What are the biggest challenges product-based technology startups face today?
A. Lack of prototyping, design for manufacturability and dearth of an overall electronics manufacturing ecosystem! Iterations take time and access to quality vendors in India is still a challenge.
Government initiatives, although improving, still have a long way to go. Many startups have ventured out to China, but relatively smaller quantities and lack of physical presence have hindered their efforts.
Then there is lack of funding in subsequent rounds and access to early home-grown customers who are willing to adopt.
Q. How can this be resolved?
A. Indian Electronics and Semiconductor Association (IESA) and IoTForum—an IoT ecosystem building thinktank—are focused on potential resolutions to such challenges. For example, IESA has started an initiative with Karnataka government for incubating fab-less semiconductor startups by giving them access to EDA tools and funding test chips.
There are also hardware-only incubators/accelerators like Forge, Nasscom IoT and Revvx that are focused on bridging this gap. Large MNCs including Intel and Airbus have their own incubators to help startups.
Entrepreneurship is tough. I tell entrepreneurs, “Conduct better market research and competitive landscape analysis, and look for opportunities to partner rather than build the entire solution on your own.”
Q. What is the main motive of BIF?
A. BIF’s mission is to invest in deep-tech startups in India beyond the current wave of consumer-focused e-commerce, hyper-delivery and marketplace models. Roots and affiliations of BIF go back to Center of Innovation Incubation and Entrepreneurship (CIIE), IIM Ahmedabad.
BIF supports deep-tech innovations in various industrial segments including healthcare, agriculture, energy, fintech, digital and other emerging sectors, at pre-Series-A and Series-A stages.
We bring together global networks, distribution channels, research infrastructures, strategic insights, customer and partner connects, and deep sectoral understanding of our investors and team.
Q. How can startups get selected for BIF funding?
A. We look for all the usual criteria that make a startup successful—emerging markets, founding team, innovative solution, traction in market and globally competitive idea. We also try to understand what to expect in the next few years, drawing analogies and comparisons on similar models and ecosystems.