A 115-page, 35-chapter blueprint for building TrueList — a browser extension and verification layer that cross-checks any real estate listing against authorized data sources in seconds and returns an honest confidence score, not a false single number. Written for a solo founder or small team, with a self-designed methodology and a legally-cautious, no-scraping data strategy.
A property can show "active" after it's already sold. A price can go stale between visits. And automated valuations can miss by tens of thousands of dollars on the very homes where buyers most need an honest number — off-market properties with no recent comparable sale.
The book walks you through building all of it — from property identity matching to a self-designed confidence score — sequenced so a solo founder can ship a real MVP, not a science project.
Detects supported listing pages in real time and runs a status, price, and confidence check without the buyer ever leaving the page they're already on.
A self-designed, weighted scoring methodology — not a copied formula — that shows its own reasoning: which sources agreed, how recent the data is, and what it couldn't confirm.
A range built from multiple valuation signals instead of one falsely precise "true value" — because no automated model honestly produces a single certain number.
A real IDX/VOW/RESO-aligned data-access strategy — MLS licensing, brokerage partnerships, and public records — the legally durable way to build a real estate data business.
Every chapter is TrueList-specific and practical — not generic startup advice. Every unverified number is labeled Industry Estimate, Assumption, or Founder Projection, on purpose.
10 named planning worksheets — confidence-score calibration, MVP scoping, a launch checklist, and a blank fillable KPI scorecard.
Agent and brokerage outreach emails, a partnership pitch, a customer support response template, and an investor update — ready to adapt.
A full worked property-verification-report example and a brokerage-dashboard feature breakdown — the reference to hand a developer on day one.
Awaiting first reader review.
Awaiting first reader review.
Awaiting first reader review.
You'll get the most out of this book if you're comfortable directing engineering work, even if you're not writing every line yourself. Chapter 26's lean-vs-scalable stack section and the AI Prompt Library are built to help a solo founder move faster with AI-assisted development.
No. Chapter 25's legal and compliance framework explains the regulatory landscape TrueList would operate in — including the CFPB's AVM rule and MLS licensing terms — but it is not a substitute for your own attorney. Every figure that isn't an independently verified, cited fact is explicitly labeled Industry Estimate, Assumption, or Founder Projection.
You get a 115-page PDF (the primary reading format, with all 6 charts and diagrams embedded) plus a DOCX version, delivered as an instant digital download after checkout.
No — and the book is explicit about this. Chapter 8 lays out the realistic, legally-cautious data-access strategy (MLS/IDX/VOW licensing, brokerage partnerships, public records) and a clear list of what a real product must never do.
You're covered by a 7-day money-back guarantee. If the blueprint isn't a fit, request a refund within 7 days of purchase.
No — and neither should any real product. The book is explicit that TrueList's confidence engine shows confidence, not certainty, and that a blended valuation range is used deliberately instead of a single falsely precise number. Regulatory and data landscapes evolve — always verify current requirements with a qualified attorney before relying on any compliance claim in a live product.
If the blueprint isn't the right fit for you, request a full refund within 7 days of purchase — no complicated process, no hard feelings.
115 pages. 6 diagrams. 12 templates. One payment, instant access.
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