Estate Scout — Real Estate Investment App Design
Estate Scout is a real estate investment app that ranks every listing by projected ROI instead of just price or square footage.
Every property enters the same funnel: a machine-learning model scores it on rent yield, appreciation trend, and neighborhood risk, then slots it into a ranked feed. Switching the sort order — highest ROI, fastest payback, lowest entry price — reshuffles the list instantly, so an investor comparing three markets never has to rebuild a spreadsheet by hand.
Opening a card pulls up the deeper story: a price forecast curve, comparable sales, and the factors driving the score. The dashboard reads like a trading terminal for property — dense with numbers, but organized so the one number that matters (ROI) never gets buried.
Visually the app leans into dark analytical surfaces, teal accent charts, and confident typography that keeps large data tables legible on a phone screen.
UX/UI Design • Mobile App • Proptech • Fintech • Data Visualization
ROI-ranked feed Listings aren't sorted by list price — they're ranked by projected return, so the top of the feed is always the best opportunity, not just the cheapest one.
Live sort switching Toggling between ROI, cap rate, and payback period re-ranks the entire list in place, letting an investor test different strategies against the same inventory in seconds.
Price forecast curve Each listing carries a 12-month price projection built from historical trends and local demand signals, giving a concrete number behind the model's confidence.
Risk-adjusted scoring The model discounts raw yield by neighborhood volatility and vacancy risk, so two listings with the same rent still land at different ranks.
Comparable sales panel Every property card surfaces nearby closed sales side by side, grounding the ML prediction in transactions that actually happened.
Portfolio-level view Saved properties roll up into a single return summary, showing how a shortlist performs as a portfolio rather than as isolated bets.