I started my career at TCS and Accenture doing something most engineers avoid: finding where systems break. My clients were Fidelity Investments, Prudential Financial, and Abrdn — places where a failed edge case doesn't mean a bad UX. It means regulatory exposure, financial liability, and broken trust at scale.

That taught me something I carry into everything: trust is the actual product. Not a feature. Every test I wrote, every regression I caught, every compliance framework I mapped — the goal was the same. Make the system worthy of the confidence people place in it.

Now I'm building TestMind — an agentic AI system that auto-generates compliance-mapped test cases across FCA, SOX, PCI-DSS, GDPR, and MiFID II. The AI testing problem is unsolved. The regulation is coming. The infrastructure needs to exist before the mandate arrives.

Alongside that, I'm founding KiranaConnect — connecting India's twelve million kirana stores to consumers and FMCG brands. The kirana store survived every wave of disruption not by digitising, but by being irreplaceable. I'm building on that, not against it. YC application submitted.

I'm completing my MS in Information Systems at Northeastern University, graduating May 2026. Actively looking for roles in AI product, technical product management, and compliance engineering — specifically at companies building AI that needs to work in regulated environments.

See my projects Full resume
I
Substance over signal
The builders who will matter are the ones doing the actual work — not optimising the optics of it. TestMind exists because the problem is real, not because it looks impressive.
II
Regulatory fluency as design
Most AI builders see compliance as a constraint. I see it as a design requirement. Understanding what breaks in regulated environments is how you build things that don't break.
III
Infrastructure over features
The most important work is usually invisible. Test frameworks. Traceability matrices. Post roads. The unglamorous foundations that make everything else possible.