HomeStar — CRE Rental Intelligence

HomeStar is a commercial real-estate rental-market intelligence platform built around a validated insight: demand leads rent. Job postings, JOLTS quit-rates, WARN layoff notices, and employment turn 5–7 months before rent growth does, and HomeStar's engine detects those turns. A walk-forward backtest achieves a 79.3% hit rate across 17 markets (46 of 58 confirmed turns), and the result held byte-identical when the sample doubled from 9 to 17 metros — evidence the signal is real, not overfit. The product has three layers: full market analysis across 17 metros and six demand signals; an agentic drill-down where you ask an analyst agent why any market is firming or softening and every quantitative answer comes from a validated tool with sources, never the model's invention; and backtesting that measures signal strength rather than asserting it. The discipline is the differentiator. We tested every public leading indicator against pre-stated criteria and dropped what failed — permits (pro-cyclical), wages (wrong-signed in 3 of 9 markets), rent-vs-own (mechanical correlation). The backtest also taught us the engine is an early-warning tool for avoid/build decisions, not a trading signal. Bright Data Web Unlocker powers the live layer: LinkedIn job postings and apartments.com concessions scraped from anti-bot sources — a live public-data proxy for signals institutions license from CoStar and RealPage. The result that matters is the convergence: the Sun Belt markets the engine flagged on labor fundamentals (Atlanta 90%, Phoenix 88%, Austin 83% concessions) are the same ones running hot, while constrained coastal markets run low (San Francisco 28%, New York 24%, Boise 15%). Two independent data sources, two methods, the same answer.