Commercializing Deep technology: Challenges in Indian Deep Tech Ecosystem

While the term "Deep-tech start-up" lacks a universally accepted definition, its meaning is generally understood. Starting in the STEM labs of universities and other research institutions, Deep-tech startups tackle intractable problems and issues. Companies that develop, implement, or make use of cutting-edge technology in their offerings are classified as "Deep-tech startups" by the National Association of Software and Services Companies (NASSCOM). These fledgling businesses focus on developing cutting-edge technologies like AI/ML, IoT, Blockchain, Big Data, AR/VR, Robotics, and more.

Deep technologies, which have been spawned by the ongoing tech revolution, will be at the core of the next wave of information disruption. It’s also the next big thing that both corporations and venture investors desire, but Deep tech startups and the ecosystem have their own unique set of challenges in India.

First, their development period is longer than that of average startups. Revenue generation for the latter could occur in as little as one to three years, while it could take Deep tech start-ups as long as five to eight.

Second, developing and validating a science-based innovation requires more resources, specialized talent, and expert knowledge in multiple domains.

Third, the failure risk of a deep-tech startup is typically higher than that of other types of startups at each and every stage. It's because it takes time for a startup to reverse-engineer a problem that would be worth solving with its technology. The next step is to confirm that there is a significant and appropriate need in the market for the innovation.

As a fourth point, India has a number of VC firms, though they tend to focus on "lower risk" sectors. Start-ups that take advantage of India's rising consumer economy are of particular interest.

Fifth, India's academic researchers aren't as empowered and resourceful as their global peers in translating their discoveries into commercially viable deep-tech businesses. Their lack of progress can be attributed to two factors: (a) their lack of expertise to turn their innovations into businesses and (b) their lack of the necessary psychological make-up (the entrepreneur's mindset). There is a lack of understanding among policymakers and university administrators about the importance of developing capacity in the areas of entrepreneurship and research commercialization.

Let’s understand a few points in detail to understand the challenges in the commercialization of Deep tech products or services.

 Skill

It has been observed that most Deep Tech start-ups are founded by technical founders, such as researchers, scientists, and engineers. Many of them lacked proper business and management education. In order to ensure the continued success of their businesses, technical founders need to develop their knowledge of business management. In addition to strong leadership, Deep Tech start-ups require a talent pool with extensive experience in the aforementioned technology domains. However, it's not enough to simply be an expert in the relevant scientific and technological aspects. Awareness about the steps that are needed to translate scientific discovery to commercial products or services is critical.

High levels of technical proficiency in any area of Deep Tech are required of all employees, but especially those in the middle and lower echelons. However, it's crucial that workers be reminded of the importance of quality and flexibility. The failure of many universities to regularly update their curricula to reflect changes in the industry and student needs is a major flaw in higher education. If India has to emerge as a strong country for Deep Tech, then the curriculum has to be cutting edge. When it comes to information technology, India stands head and shoulders above the rest of the world. Creating new programmes in fields that are adjacent to IT, like artificial intelligence, cybersecurity, blockchain, cloud computing, and so on, would allow us to better capitalise on our strengths.

 Funding

The available financial options lack depth and flexibility. Deep tech poses a higher credit risk, as its assets are intangible (e.g., patented/not patented intellectual property) and difficult to value (especially pre-revenue). Additionally, many Deep tech innovations are not taken seriously by investors due to their lack of knowledge about their technical and economic viability.

Due to its relative youth, the Deep tech industry is still not well understood. In the business world, the full extent of its potential influence is not fully appreciated. Consequently, companies leveraging Deep tech in their products may find it more difficult to raise capital compared to their widely popular counterparts engaged in B2C e-commerce, aggregator, or app-based business models.

According to Venture Intelligence, in 2021, Indian Deep tech VC investment was over $1.4 billion, representing an increase of about 24 percent from 2020 and 180 percent from 2019. While India's industry grew rapidly in 2021, Deep tech investments accounted for only 4.5 percent of total investments (Venture Intelligence), indicating that more work is needed to foster the development of technologies that combine scientific discovery and engineering innovation.

Grants, patient capital, blended finance, targeted project finance, government support, and mainstream capital are all part of the continuum of capital that must be established through early risk and growth to pave the way to scale. The government can reduce the risk of venture capital investments through sweat equity and funding, especially in areas where rules have been relaxed, like drones, space, geospatial technology, and data access.

 Infrastructure

 India lacks the resources or infrastructure to reliably test products or iterate on solutions. We require a reliable system by which govt agencies and well-established businesses can contribute their knowledge of engineering and mass production to the development of a new product and act as beta users. Instances of Deep tech startups that have not sustained their compute requirements because of the lack of a supporting infrastructure is common in the ecosystem. Existing incubators are better suited for tech mentoring and business mentoring, and they lack a high-end computing infrastructure, making it difficult for startups in the deep learning domain to find support when trying to train their ML algorithms, develop proofs of concept, etc. As such, it would be very useful.

 Timeline

Deep Tech harnesses a scientific discovery or breakthrough and it rebuilds everything from scratch. For Deep Tech startups, seeking product-market-fit is not about A/B testing features and phases. The key is to test the technology in realistic settings over and over again. The science and technology fields and patents that could propel this transformation must also be navigated. This is why Deep Tech projects tend to take longer to bear fruit. Depending on the innovation, it can take months or decades before the technology is ready to be commercialised.

Deep Tech faces problems because the process of putting new technologies on the market is complicated. These problems can be put into five broad categories:

R & D

Phase I/Testing

Deployment

Diffusion

Mature in terms of the marketplace

 Market Access

 India is currently not a good fit for advanced technological enterprise solutions due to its small size. Small and medium-sized businesses in India are reluctant to invest in software, and when assessing the value of adopting new technologies, they often fail to take the total cost of ownership into account. However, we anticipate that these difficulties will soon become opportunities for startups in the Deep tech ecosystem, as the increased emphasis on automation and digitization acts as a tailwind for economic recovery.

While the Indian Deep tech market is not large enough on its own to justify billion-dollar valuations, neither are the markets for IT services or software as a service. Yet, companies in the IT and SaaS space have found much larger markets for their offerings: the North American and European markets. So, why can't Deep tech do the same? Putting in place some sort of governing structure is the short answer here. Deep tech is a heavily regulated industry, as it absolutely should be!

One cannot decide to suddenly begin selling in the International Market. It takes years (from inception) to prepare and get clearance from the relevant authorities.

 Conclusion

Deep tech certainly has challenges, but as we are moving forward, all the stakeholders in the Deep tech ecosystem are consistently improving and seeing an upwards trajectory. The year 2022 started on an optimistic note as VC firms are willing to invest in the Deep tech niche and innovations. The response rate is relatively high, and the business background also involves many variants, such as pharma, automotive, retail, etc. Indian investors have been holding the ground for deep science solutions. SanchiConnect is among those platforms that are assisting Deep Tech startups, enterprises, entrepreneurs, investors, and more, and helping them connect with each other to build a network for the ultimate growth of all of the Deep tech enthusiasts. Our objective is to assist in scaling up a business involved in scientific innovations. Backed by some of the most popular VCs and angel investors, Sanchi Connect stands as a trustworthy platform in support of Deep tech startups, SMEs, entrepreneurs, and others to help them grow both in strength and revenue.