AI EngineerFounderExplorer

I fell for computers young and started coding before I knew it could be a job. Security was the first thing that really held me — taking something apart to find where it gives, then closing the gap. It was never about breaking in. It was the puzzle.

I studied computer science at VIT Vellore and spent most of it in hackathons. Dynamic Angles is still my favourite: a low-latency pointing system that fused gyroscope, accelerometer and magnetometer readings and used the Earth's own gravity as the reference frame to map a human arm in 3D space, in real time, on a microcontroller. No cameras, no external rig — sensors and the planet.

Since then I've led twelve engineers building contact tracing that detected exposures three times better than the DP-3T standard, second of 2,000+ teams at the European Commission's EU vs Virus and named among India's top 15 student innovators, and spent two and a half years at McKinsey building AI systems for industries that make physical things. I'll leave that work out of this; it won the firm's global award for innovation and client impact, and it taught me the difference between a clever idea and one that survives contact with reality.

The thread through all of it is the same. I like problems where the answer has to be fast, physical and correct, and where being approximately right is the same as being wrong.

That's Chimère. An Indian freelancer invoices a US client and waits days for money that arrives lighter than it left — intermediaries, forex markups, capital frozen in transit. We settle it in 20 seconds at 1% all-in. The hard part was never moving money; it's the compliance India requires on every inbound payment — purpose codes, FIRA, the paperwork — which we do automatically instead of manually. And because the same rails expose a native endpoint for AI agents, the payer doesn't have to be a person at all. Money should move as fast as the thing that decided to spend it.