Specialised chips and GPUs are key to process huge amounts of data and carry out complex computing involved in AI workloads. While India has a lot of catching up to do here, it is a highly capital-intensive area, limiting the scope for startups that are instead focusing on the application side of how AI tools interact with users.
Abhishek Prasad, managing director of Cornerstone Ventures, said GPU is the hardest layer in the AI ecosystem to crack. “It’s also a tough one for startups to be able to make a dent simply given the capital requirements,” he said. “The market leader (almost unchallenged) is Nvidia, and it’s near impossible to challenge them in this space.”
It is a different story in the application space.
“The application layer dominates the AI landscape in India, as it also plays to the historically natural strength of our ecosystem,” said Prashanth Prakash, founding partner of Accel India.
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“The lack of established domestic hardware ecosystems and high capital intensity of chip manufacturing make it less appealing for VCs compared to other layers of the AI stack. Indian startups are more aligned with software development and IT services,” added Brijesh Damodaran, cofounder and partner at Auxano Capital. “Indian startups often provide services that enable the adoption of AI for global markets,” he said.
ETtechInfrastructure & tooling
Infrastructure and tooling comprise technologies, platforms and tools involved in developing and deploying AI models and scaling them up, an area that Anandan says is seeing a lot of activity.
However, according to Prakash, there have only been a handful of globally competitive infrastructure and tooling layer startups from India, “even from the pre-AI era”.
These areas (newer types of AI chips, data centre infrastructure, tools and software) need very specialised and experienced talent, hence the number of such companies will not be very large, said Arjun Rao, general partner at Speciale Invest which is making investments in this space.
A company that is involved in the segment is fabless semiconductor startup Morphing Machines, developing runtime reconfigurable dataflow processors that deliver high performance and power efficiency at a low cost. It has raised $2.76 million in its seed round led by Speciale Invest.
Despite the application-centric focus, several players are recognising the importance of infrastructure and tooling. “We at Speciale are strongly focused on the infrastructure and tooling layer in GenAI, mainly due to the technology differentiation and talent advantages there,” Rao said.
Speciale’s portfolio includes companies like Protecto AI focused on secure and trustworthy AI and Tursio that transforms enterprise databases into generative AI machines.
“We see infrastructure and tooling companies as the picks and shovels to provide the underlying foundation to build robust applications,” said Poorvi Vijay, vice president of Elevation Capital.
But broadly, Rao said, VCs are investing heavily in the application layer, given the breadth of opportunities in horizontal (which are designed for a wide range of uses across fields) and vertical (developed for specific industries and purposes) applications.
ETtechChallenges and opportunities
Development of AI chips in India faces significant hurdles. “It’s not an easy game, requiring significant capital and, most importantly, close collaboration with pioneering system customers who will use these chips,” explained Somshubhro Choudhury, cofounder and partner at Bharat Innovation Fund. “Beyond designing the chip, it’s also important to create an ecosystem of software infrastructure on top for easy adoption of the chips in electronic and data centres.”
These challenges also present unique opportunities.
“We’re seeing the most vibrant startup activity in India at the infrastructure tooling and application layers,” said Sharvi Dubey of the investment research team at Good Capital. “However, it’s important to understand this isn’t a limitation but rather a reflection of India’s unique market opportunities.”
Dubey believes that Indian companies can gain a competitive edge by focusing on solving India-specific challenges through AI-powered applications.
While the development of AI chips may still be at a nascent stage, the future of AI in India appears bright, with a strong emphasis on application development and a growing focus on critical infrastructure and tooling.
As the industry continues to evolve, it is crucial for Indian players to navigate the challenges and capitalise on the unique opportunities. By fostering a strong ecosystem of innovation and collaboration, India can emerge as a global leader in the AI revolution, experts say.
