India's Indigenous AI Surge: Entrepreneurs and Startups Propel a National Tech Revolution

A New Era for India's Indigenous AI

India is witnessing a transformative phase in its pursuit of a sovereign artificial intelligence (AI) foundation model. Under the IndiaAI Mission, with a robust funding boost of Rs 1,500 crore and subsidised access to over 10,000 GPUs, entrepreneurs and researchers are setting the stage to build AI solutions that are deeply rooted in India’s cultural, legal, and linguistic landscape.

Pioneers Leading the Charge

Several visionaries have stepped forward:

• Ayush Gupta: A Stanford graduate who left a promising role at Apple to launch Genloop. His startup is developing an India-specific compliance large language model (LLM) pre-trained on a wealth of domestic sources including cultural contexts, historical data, and legal proceedings. The model is designed to support all 22 scheduled Indian languages, aiming to bridge local nuances with technological innovation. Although precise budget figures remain in flux, Gupta estimates his venture might require around $1.5 million.

• Aaditya Kirti: An engineer from Patna whose startup, EJY Health, is piloting an AI-driven solution in five hospitals—three government and two private. Incubated at IIT-Patna with support from the Startup Bihar initiative, his model is designed to reduce the documentation burden in healthcare, thereby enabling medical professionals to dedicate more time to patient care.

• Sahil Gulati: A Gurgaon entrepreneur with a background in B2B sales, leading EliteNotes. Despite not having a formal tech education, Gulati is developing a multilingual, multimodal small language model that integrates audio and video capabilities in multiple Indian languages. His team is preparing their proposal for submission by March 15.

Government Support Fuelling Innovation

The financial support and technological resources provided by the IndiaAI Mission are paving the way for experimental and groundbreaking AI projects in India. Key factors contributing to the race include:

• Subsidised Compute Resources: With compute being the costliest part of AI development, the government’s provision of subsidised GPUs levels the playing field, helping startups compete even against well-funded companies like Sarvam AI.
• Targeted Funding: Grants, compute credits, and staggered equity funding ensure that projects meet vital eligibility criteria such as research experience, development strategy, and unique data approaches.
• Structured Timeline: Officials, including Abhishek Singh, the IndiaAI Mission CEO, have indicated a 9 to 12-month timeline for developing a fully sovereign AI foundation model.

Conclusion

India's push towards indigenous AI development marks a strategic move to harness local talent and resources, fostering innovation that aligns with national priorities. As proposals are submitted and projects move forward, the country is set to emerge as a notable player in the global AI landscape.