How AI Impacts the Indian Manufacturing Industry

Three AI use cases already live in his own operations, not theoretical: compiling weeks of operational data down to hours, using tools like GPT to summarise long documents and surface the one clause or number someone actually needs, and running years of historical data to sync demand with supply more accurately than instinct alone.

On the factory floor, AI removes the middlemen from the data flow between shop floor and dispatch, replaced by real-time dashboards that let him monitor production and shifts across multiple factories without standing in any of them.

India is roughly 30 years behind China in robotics, EV batteries and manufacturing infrastructure, a gap he attributes largely to the scale of state support Chinese manufacturers received. He is equally clear the gap is closing, citing new domestic policy and anchor players like Apple and Samsung.

His investing filter: back the jockey, not the horse. A strong founder iterates a mediocre model into something workable; a strong model in weak hands rarely survives contact with the market. He spends an hour or two most days with founders: about 80 per cent seeking investment, 20 per cent seeking advice.

The pattern he will not back: founders who take a round and immediately upgrade their own lifestyle, and founders trying to be a single-man army instead of building a team that functions without them in the room.

The venture studio he is building answers that directly, giving early-stage startups fractional access to CXO-level expertise they could not otherwise afford or justify hiring full-time.

What actually blocks AI adoption in traditional industry is mindset, not cost or capability: older leaders whose manual processes have worked for decades. The way in is small daily tools already sitting inside Gmail or a ChatGPT tab, building the comfort that larger integration later requires.

The unglamorous mistakes that cause real damage: operating as a sole proprietorship while raising funds, and never registering a trademark. It is material enough that he is writing a book about it, titled Startup Saga: Idea to IPO.

On the current funding landscape, his read is blunt: most of what is being funded is a wrapper around someone else’s large language model, and the founders who matter in five years will be the ones training their own.

Siora Capital, his investment arm, is named after his daughters, with the explicit intent of teaching his children to invest and manage risk rather than inherit a balance sheet. Posting structured personal thoughts on LinkedIn took him from 20,000 to 55,000 followers in a year, a working tool for finding mentors, co-founders and hires.