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Rentfacts.io

Building a rental transparency app that tells tenants the truth before signing a lease

Design and build a SaaS platform to help tenants uncover truths about prospective rentals and landlords, and to give landlords an opportunity to build trust with prospective tenants.

SaaSConsumerWeb appDesign systemsProduct developmentProduct design
Rentfacts main dashboard

Renters sign leases with almost no reliable information about a unit or a landlord. Rentfacts surfaces real, user-generated signal (reviews and reported issues) before someone signs, and gives landlords a reputational reason to take accountability.

Problem: know before you sign

The hard part is the two-sided cold start: the product is only useful once it has content, and content only comes once people trust it enough to contribute.

The pivot: gated → open contribution

The original model gated review-writing behind identity verification. It was the “right” answer for trust, but for a product whose whole problem is a cold start, the gate throttled the one thing that matters most: contribution. I flipped it - any signed-in user can write a review; it lands pending and only publishes after an admin approves it. Moderation moved from the front door to the back.

Before/after diagram: gated contribution vs. open submission with back-end moderation
Moderation moved from the front door to the back.

The shipped product

Search-first home, “Know before you sign”

The landing page leads with the promise and a single address search with live autocomplete. A trust note sits right beside it, putting the moderation promise at the point of entry, not buried in a policy page.

rentfacts.io
Rentfacts search-first home with live Oakland map
The cold-start and trust thinking made visible in one screen.

The contribution flow: turning a blank address into signal

Search an address no one has covered yet and the page doesn't dead-end — it lazy-materializes the listing and invites the first review.

rentfacts.io/listing/new
Empty-shell listing inviting the first review
Lazy-materialized listing: the record is created on demand, on first contribution.

From there a five-step wizard paces the tenant through overall experience, the best/worst split, property-quality and management ratings, then a final review-before-submit.

Wizard step 1 — overall experience
Experience
Wizard step 2 — best and worst
Best / worst
Wizard step 3 — property quality
Property
Wizard step 4 — management ratings
Management
Wizard step 5 — review before submit
Review

Listing detail

A property page pairs a neighbourhood map with a property-overview panel and a review summary card. Individual reviews break out per-dimension ratings, and a maintenance snapshot surfaces open/closed issues. Scannable, comparable signal, not a wall of prose.

rentfacts.io/listing/954-bayview-ave
Listing detail page with review summary and per-dimension ratings
The review summary runs today on a heuristic generator: the visible placeholder the AI summaries replaces.

Outcomes

A password-walled Vercel preview is the next milestone. The PostHog funnel is already wired and waiting on live traffic, so the metric that decides the concept: do visitors become contributors? Measurable the day visitors arrive.

Earn trust through moderation now; layer verification back as a trust upgrade later, not an entry tax.

Interested in working together?

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