Discover how NVIDIA is catalyzing deeptech innovation in India, overcoming challenges and accelerating AI startup growth through its Inception program.
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Introduction: The Growing Importance of Deeptech in India
As India continues to grow its startup ecosystem and proves itself as a leader in IT services, deeptech startups are facing significant hurdles to keep pace with global counterparts. Currently, there are more than 5,800 deeptech companies in India, according to Traxcn data. However, these startups are plagued by challenges such as a lack of robust R&D culture, long gestation periods, regulatory hurdles, and a heavy reliance on imported components. Despite these issues, NVIDIA is stepping up to empower deeptech innovation, offering solutions that propel these startups from concept to scale.
During a recent event, Unnikrishnan A R, Head Developer Relations for South Asia at NVIDIA, emphasized that “acceleration is not just a buzzword; it’s the core of what we enable.” His keynote at the NVIDIA Inception program showcased how this tech giant supports startups in achieving unprecedented speed and efficiency.
NVIDIA’s Three Pillars of Deeptech Innovation
At the heart of NVIDIA’s strategy for fostering deeptech innovation are three foundational pillars:
1. Graphics
High-fidelity rendering allows startups to simulate the physical world accurately. This means rendering realistic visuals, critical for industries ranging from gaming to healthcare simulations.
2. Physics Simulation
This involves modeling real-world behaviors in virtual environments, enabling startups to run simulations that closely mirror reality. Such capabilities are particularly useful in sectors like engineering and product development.
3. Intelligence Simulation
Integrating AI into digital agents that can perceive, reason, and act autonomously is a game-changer. According to Unnikrishnan, transitioning from traditional APIs to autonomous agents empowers startups to create solutions that can operate workflows and execute tasks end-to-end.
“Founders must design not just for function, but for autonomy and scale,” he notes, signaling a significant cultural shift in how products should be engineered.
The Deeptech Stack: Behind the Scenes
Bharath Gidwani, Senior AI Data Scientist and Solutions Architect at NVIDIA, provided insights into the powerful infrastructure that drives deeptech innovation. He highlighted the critical role of GPUs and optimized libraries such as TensorRT, CUDA, and NeMo. These tools are essential for scaling AI development effectively.
“An agent doesn’t just respond; it decomposes the prompt, reasons, calls tools, accesses memory, and acts,” Gidwani explained. To bring these capabilities to scale, startups require robust orchestration, long-context models, and a solid computational backbone.
Innovative tools like the NeMo Curator help startups focus on data curation and synthetic data generation. As inference costs rise—sometimes requiring 100 times more computing power than training—it has become essential for startups to ensure their models are both efficient and highly accurate.
India’s Window of Opportunity in Deeptech
The panel discussion titled “Accelerating India’s journey to becoming a global AI powerhouse and net producer of AI” brought together investors and founders to discuss the unique opportunities India presents.
Pearl Agarwal, Founder and Managing Partner at Eximius Ventures, noted that India possesses a unique digital infrastructure involving Aadhaar, UPI, and the Ayushman Bharat Digital Mission. “We have the data and developer talent,” she said. “What India needs is public-private collaboration to turn this into deep tech leadership.”
Kriti Gupta, Vice President at Peak XV, mentioned the rise of small team AI builders, marking a “builder explosion.” The accessibility of tools has enabled startups to rethink traditional workflows, particularly in industries like manufacturing, healthcare, and BFSI.
Arjun Attam, Co-founder and CTO of Empirical.run, emphasized the need for educational institutions and businesses to invest in soft skills like communication and structured thinking, which are essential for engineering that drives collaboration and problem-solving.
Divya Manohar, Co-founder and CEO of DevAssure, shared practical insights from her experience building a deeptech product in India. “Data is your moat,” she stressed. “It’s not just about collecting it; you have to structure, label, and train on it in a way that’s defensible and specific.”
Charting India’s Deeptech Future
Despite India’s long-standing challenges in deeptech, platforms like the NVIDIA Inception program offer startups the infrastructure, tools, and mentorship needed to develop production-grade AI systems. The vision of India emerging as a global net producer of AI is no longer a distant dream.
As Unnikrishnan succinctly put it, “The future belongs to those who architect for autonomy and scale, not just execution.” To achieve this ambitious future, India will need bold founders willing to innovate, long-term capital that understands the profound implications of deeptech, and a systemic commitment to nurturing this sector with conviction.
In summary, the collaboration between NVIDIA and Indian startups is an exciting development that could pave the way for India to emerge as a leader in deeptech, fostering innovation that can compete on a global scale. With the right foundational pillars in place, the future of deeptech in India looks promising.
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