LinkedIn · Featured work · Skills, with evidence
I've spent my career on the business side of trust: building a food brand as a co-founder, then payments products at Paytm, Dineout and now Qenta, where I lead the Responsible Gold due-diligence product. The question underneath all of it is the same: how do two parties who don't know each other trust a transaction? These repositories are my answers in code. Each one makes a decision and keeps the evidence for it.
Every number on these cards comes from a real run of the linked repository, and each README shows the output. All four are clean-room builds with synthetic data: no employer code, data or methodology. Each README also says who the product is for, what I'd measure, and what I cut.
- Claims need evidence. In the due-diligence engine, an unbacked "yes" scores zero. My skills matrix applies the same rule to me.
- Design the failure path first. A payment timeout means unknown, not failed. Getting that wrong is how customers get charged twice. (ADR-1)
- Optimise for the expensive mistake.
payee-verdictmust have zero false matches before accuracy counts, because a wrong "match" sends money to the wrong person. (corpus results) - AI only where it can be measured against a baseline. The LLM step must pass schema, consistency and grounding checks, and it's scored on silent errors against a regex baseline. The live-model run is still to come. (eval)
How my work connects
At Qenta I lead the Responsible Gold due-diligence product and contribute product strategy across its payments, G-Coin (digitised gold) and QID (decentralised identity) work. I build these prototypes with Claude Code as an AI pair programmer, and every claim in them is checked against tests and real runs.
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