'Deep Tech Startups Have Different Capital Needs'

Deep Tech funding in the first nine months of 2023 was down by 66 per cent as compared to the same period in 2022. Why is funding in Deep Tech so difficult?

The capital required for deep tech companies is different than that for ecommerce or SaaS. In the early stages, patient capital is needed to create a product, sometimes taking four to eight years. For drug discovery, it can take up to 15 years. Funding for deep tech has two aspects. Grant research funding is needed in the early stages and it comes from government or research agencies. There's a problem with the availability of grant money in India and the quantum required small. VC money comes into play once there's a product in the market. Deep tech requires a good amount of early money, which is not tied to outcomes initially. The Deep Tech Club, founded in 2017 by Nasscom, is building partnerships with VCs who understand the longer time frame required for returns.

In summary, funding for deep tech involves unique challenges and dialogues. Institutional investors may need to raise money from different types of LPs. Deep tech investors are more patient and less affected by short-term market trends.

Within Deep Tech, AI-led startups in BFSI and EnterpriseTech raised more than 60 per cent of the funding. This shows the importance of AI and its relevance in acquiring funding. Do you think that startups are adding “AI” to their company name to keep up with the times and not staying true to their mission?

Many of the companies we track have already integrated machine learning and AI as core components of their operations. Deep tech companies, in particular, are not merely chasing fleeting trends; they address substantial issues in specific sectors, such as healthcare, agriculture, and manufacturing. These firms were already harnessing machine learning and have now adopted AI to solve complex challenges. For instance, startups are using AI for tasks like cancer detection and microbial identification, though their focus extends beyond generative AI, which tends to be consumer-oriented. Instead, they are building their own models and leveraging data to achieve their goals. While there may be a current trend in incorporating AI into products, many deep tech companies view it as an additional tool rather than a fundamental shift in their focus.

How is the Indian Deep Tech ecosystem doing in 2023?

Indian deep tech is still in its early stages, reminiscent of the energy and excitement back in 2010-2011 in the startups space. Currently, there are around 3,000 to 3,500 deep tech startups characterised by research-driven, outcome-focused initiatives in various verticals. However, significant growth is anticipated, possibly tripling this number in the coming years due to increasing interest and collaboration between industry, academia and researchers. The momentum is building and the expansion is expected to continue. We are bullish about the prospects.

How is Nasscom helping Indian Deep tech?

We are working with the government and they are starting to think about supporting deep tech startups in three key areas. Firstly, securing funding is vital. Collaborating with the government to create substantial funding pools, akin to the proposed National Research Foundation, is underway to provide essential financial backing for these ventures. Secondly, evolving skill demands are a major concern. While traditional software skills remain important, expertise in fundamental sciences and cross-disciplinary engineering is increasingly critical. A thorough analysis of skill requirements is in progress, involving discussions with startups to understand their hiring needs better. The third focus area is market access. Many deep tech ventures require a physical presence and face regulatory complexities. Exploring fast-track processes for overseas regulators and assessing intricate supply chain demands for hardware and material science are essential to support these startups.

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