Bhandari's argument is that India has confused using deep tech with creating it. Most Indian companies — 80 to 90 per cent, on the split named here — are applying somebody else's model, wrapping a ChatGPT call in something that makes a problem easy, while the underlying layer stays foreign; he blames datasets, hardware and large-scale training infrastructure rather than talent, and expects India to leapfrog once those ease. Seafund's answer is a mandate with a hole deliberately cut in it: no direct-to-consumer, a conscious choice given a small fund and partners who describe their consumer instincts as close to non-existent. What is left is B2B, and the test he keeps returning to is the colour of money. Ten thousand dollars from two project customers is a services business whose multiplier is people and hours; five hundred dollars a month from twenty customers is a product that scales without hiring — and that pattern is itself the moat, though he concedes every high wall eventually meets a taller ladder, so the real question is whether you can build, monetise and move on first. From there the cheques go where India is thin: five rocket teams met in six to nine months, an indigenised camera shooting 7 km from a rooftop, a mid-mile logistics drone priced against what a man on a bike would charge for the same fifty kilometres, a vehicle control unit he calls the CPU of an EV, and chip design as the capability India should spotlight instead of fabs. Fund I reported returns of 45 to 48 per cent over four years and its state-government LP came back for Fund II — his evidence that patient capital for hard technology now exists here. The stakes: if the next wave of models and silicon is only consumed in India, the value accrues somewhere else.
Worth your time if you are
Deep-tech founders raising a first institutional cheque
SaaS founders still billing by the project
Chip engineers weighing a fabless startup
EV and battery operators arguing swap versus fast charge
State-government funds thinking about becoming LPs
