🛠️ Projects & Experiments

Won Code Interpreter 2.0 Hackathon by building an AI tool that tests code in technical guides to make sure they actually work.

Found incomplete/incorrect code examples in OpenAI, Vite, and E2B docs. Saves developer time by automatically catching outdated documentation.

Won LangChain Factory Hackathon by building an agentic system that automates writing and tailoring software release notes for different stakeholders using a multi-agent architecture.

Created a solution that transforms sparse release notes into rich documentation tailored for different audiences (CEO, developers, downstream teams) through coordinated AI agents.

Built and won MongoDB GenAI Hackathon by creating an AI-powered tool that matches hackathon participants based on their profiles, skills, and interests.

Won $2000 in Fireworks AI credits. Created a scalable solution using hybrid search (vector + keyword) for optimal matching, with costs under $1 for development.

Currently building an AI-driven application designed to automate the categorization of personal financial transactions. This project involves using state-of-the-art Large Language Models (LLMs) to classify transactions based on descriptions and enriched context from Google search results.

The initiative aims to reduce manual categorization errors, enhance user experience by minimizing the need for manual input, and improve financial management efficiency.

Led the development of a groundbreaking MVP that leveraged Gen AI to revolutionize the ops and support of a re-insurance provider.

Realized approximately $50M in savings by optimizing the onboarding and modeling of insurance contracts. Created a sophisticated knowledge graph to enable powerful reasoning with large language models, reducing actuarial work hours by 64%.

Initiated and led the development of advanced machine learning models that successfully increased the customer win-back rate by 11%.

Enhanced customer retention strategies and set a new benchmark for predictive analytics in the telecommunications sector.

Managed a team of 9 data engineers and machine learning experts to implement cutting-edge ML solutions that enhanced core mining processes.

Reduced mining carbon footprint by 4%. Implemented MLOps best practices for model versioning and deployment, involving 18 models in production retrained monthly.

Designed and implemented a comprehensive org-wide quality solution that significantly enhanced the reliability of data products, driving business decisions.

Increased revenue by 18% within a single quarter through predictive modeling of customer fulfillment rates.

Led a team of 12 to overhaul SnapTravel's data platform, integrating advanced analytics that supported strategic business decisions.

Helped pivot the company from growth-focused strategies to profitability in just three months during the challenging first quarter of the COVID-19 pandemic.

Founded and led the development of a data intelligence platform integrating various data sources and accessed by thousands of users.