Is this house the most convenient for me?
Experiment
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BeforeYouMove turns any address into a pre-move report in under 60 seconds, covering safety, noise, resident sentiment, pricing, walkability, sun exposure, commute, and local context in one decision layer. Open beforeyoumove.homes
I had an idea on the way back from the gym.
My wife & I were looking at places to buy. We have a daughter & a dog called Bruce. Every listing looked fine online. Every neighborhood looked "fine" too, until you started digging. Reddit threads from 2019. City-level averages that tell you nothing about your actual street. Sources you don't know are ads or not.
It's 2026. I opened my laptop & built the thing I was looking for.
BeforeYouMove runs 7 AI agents in parallel the moment you enter an address. Safety. Noise by hour. What real residents say. Demographics. Property trends. Walkability. One report. 60 seconds. Any address in the world. It also spawns 2 agents to verify and filter unsourced data.
Built it solo. Nights & weekends. One month. While working full-time.
It's live at beforeyoumove.homes. It's not perfect. But it answers the question every mover is asking & no one was building for.
What I used
React + Vite + Tailwind on Vercel, Supabase for auth/DB, 7 AI agents (Perplexity Sonar, Gemini 2.5 Flash, Grok, GPT-4.1-nano), Google Maps + Places, Reddit API, OpenStreetMap, Lemon Squeezy + Stripe for payments, Resend for email, PostHog for analytics.
What I built
Enter any address. 7 parallel agents return a full neighborhood report in ~60 seconds: safety, noise, sentiment, demographics, property market, micro-neighborhoods, walkability. Interactive web report with maps, charts, source citations. Free tier previews, paid tiers unlock everything. B2C ($4.99–$14.99/mo) + B2B ($49–$199/mo, white-label PDFs for agents).
Current state
Live soft launch with paid tiers enabled all working with 48 E2E + 23 unit tests passing. B2B pipeline open, with several warm interests. Deferring until first close. Solo. No team. Built at 5am before work.
This project helped me move from product insight to shipped consumer product, including monetization, experimentation, analytics, growth loops, and launch iteration.