AI-powered real estate analysis for modern investors.
Homestream is an AI-powered real estate analysis platform built to help investors evaluate potential deals quickly, clearly, and with confidence. It aggregates property, market, and financial data into a single structured view, replacing intuition-driven decisions with transparent, data-backed insights. By automating key steps like deal screening, pricing analysis, and investment scoring, Homestream reduces friction in the early stages of due diligence and allows investors to focus on the opportunities that truly matter. The platform is designed with scalability in mind, enabling both individual investors and teams to make smarter, faster decisions as they grow.
My co-founder and I built Homestream as a long-term tool we plan to use in the future. As a data science major with ambitions to build a large, geographically diverse real estate portfolio, I wanted a system that could scale with both my technical skills and investment goals over time. Growing up, I spent long periods living abroad, and when I returned home for summers my family would travel across the U.S., visiting different states—those experiences shaped a long-standing goal of owning property in every state. Homestream is my way of turning that vision into something practical: a data-driven framework I can rely on as I evaluate markets, manage risk, and make smarter decisions as my portfolio grows.
From a technical perspective, Homestream is built around cost-efficient data ingestion, API integration, and analytical modeling. I was responsible for sourcing and evaluating third-party APIs that provided reliable property, market, and financial data while remaining economically viable at scale, with a focus on selecting datasets that could be meaningfully contrasted against a user’s existing technology stack. Using this data, I designed and implemented calculations for key investment metrics such as estimated rehabilitation costs and deal viability scores. Throughout development, I engaged directly with multiple API providers through exploratory and technical calls to assess data quality, coverage, pricing models, and long-term scalability before integration.
