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> CASE STUDY · AI Workflow Automation

Movin Homes — PropTech AI Marketplace

A data-driven property marketplace that flags undervalued homes for 7-day flips

ROLE: CTO & co-founder — architecture, data engine, full buildWHEN: 2025STATUS: LAUNCHED

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 problem

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.

> The approach

What I built — the architecture

Live market-data scraping

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.

Variance mapping

The engine maps price variance across micro-markets to find listings priced well below their local comparable band — the core undervaluation signal.

Sale-velocity analysis

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.

Streamlit analytics surface

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.

Two-sided marketplace

A React and Tailwind consumer marketplace onboards buyers, sellers and brokers, with flows built to scale a network of 100+ brokers feeding deal flow.

BUILT WITH
PythonStreamlitWeb ScrapingData AnalyticsReactTailwind
> The result

What it delivered

7-day
flip cycle at ~12% margins
100+
broker network onboarded
SPC
Fall 2025 finalist
Live
market-data scraping pipeline
> RELATED

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