Movin Homes — PropTech AI Marketplace
A data-driven property marketplace that flags undervalued homes for 7-day flips
A dual-sided PropTech marketplace I built as CTO and co-founder. A Python and Streamlit analytics engine scrapes live market data from sources like 99acres and Housing.com, then applies variance mapping and sale-velocity analysis to flag undervalued properties — enabling 7-day flips at roughly 12% margins. A React and Tailwind consumer marketplace onboards buyers, sellers and brokers, scaling a network of 100+ brokers. The venture reached the South Park Commons Fall 2025 finals.
The pain this had to solve
Property arbitrage lives or dies on speed and signal. Spotting a genuinely undervalued listing means comparing it against live comparable sales, local price variance, and how fast similar homes are actually moving — work that is slow and error-prone when done by hand across fragmented portals.
On top of the data problem, a flip business needs deal flow. Without a marketplace that brings buyers, sellers and brokers into one place, even perfectly priced inventory has nowhere to transact quickly enough to hit a 7-day turnaround.
What I built — the architecture
A Python scraping layer pulls current listings and sold data from sources like 99acres and Housing.com, normalizing them into one comparable dataset for analysis.
The engine maps price variance across micro-markets to find listings priced well below their local comparable band — the core undervaluation signal.
Sale velocity gauges how fast similar homes actually move, so flagged deals are not just cheap but liquid enough to flip inside the target window.
A Streamlit app turns the pipeline into an internal dashboard where the team reviews flagged opportunities and acts on 7-day flips at roughly 12% margins.
A React and Tailwind consumer marketplace onboards buyers, sellers and brokers, with flows built to scale a network of 100+ brokers feeding deal flow.
What it delivered
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