Dec, 2016 - Oct, 2017


We worked on an interesting framework for Loanzen - a leading NBFC lending to unregulated and unorganized SME sector in India to help them collect and process data for their credit model. Their lending model is unique and they needed a system that can continuously monitor the creditworthiness of their customers. We designed an Android SDK that allowed them to capture different interesting data points from their customer’s mobile without impacting their privacy or battery life and experiment with that to identify attributes/features that can be used in their credit model.

We also designed our version of the hierarchical Naive Bayes Algorithm to automatically tag nontransactional SMS messages into different hierarchical categories such as banking, online shopping, loans, payments, etc. We then further processed the banking SMS to create a life continuously updating/live bank statements of their customers. We also built a notification engine that processed this data and generated alert based on some conditions

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Embedded BI Tool

We recently built an embeddable self-serve BI tool for Pashi - a YC startup that is building operating systems for manufacturing.

How we re-architected a Payment Fraud Detection Engine with 300% performance increase

We re-architected Xapo entire transactional fraud detection system and made it more reliable and performant


An experiment to build out a platform that allows publishers to replace ads with crypto miners(monero) running on user’s browsers / mobile phones. This project involved the following components

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