During my master thesis on ESG Portfolio Optimization, I realized that existing software is too complex for users without a financial background. This inspired me to create a solution that allows anyone, worldwide, to define an optimal stock portfolio that maximizes return while minimizing risk. To tackle the problem of slow, less reliable optimization in current software, I leveraged quantum computing for faster and more accurate portfolio computation. I started by building a minimal MVP with extremely limited resources—just $12 for infrastructure and free data APIs. Surprisingly, even with these constraints, the platform attracted 700+ users without any paid marketing, showing early signs of product-market fit. After launching the second version of the MVP, the user base continued to grow, with 98+ new users in just two weeks, again without paid promotion. This process taught me the value of rapid iteration, resourcefulness, and user-focused design, and shaped how I approach the next phase of product development.

Soma Quantum Portfolio Optimization

Build stock portfolios super fast with quantum computing.

Build stock portfolios super fast with quantum computing.