The missing search engine for America’s cheapest real estate.

Land banks — public agencies created to return vacant and tax-foreclosed property to productive use — sell homes for a few thousand dollars and lots for a few hundred. But their inventory never reaches Zillow, Redfin, or the MLS. It lives on hundreds of separate municipal websites, embedded map portals, and monthly PDF lists.

LandBankSearch exists to fix that: one searchable map of every land bank property we can find, with prices, parcel boundaries, and a link to the official source for each one.

Where the data comes from

Every listing on LandBankSearch comes from an official public source: the land bank’s own listing feed, map service, or published inventory list. We don’t guess, and we don’t list anything a land bank hasn’t published itself. Our pipeline re-checks every source nightly, adds context from other public datasets — county assessed values, FEMA flood zones, U.S. Census neighborhood statistics — and retires listings when they leave the official list.

Public data is messy, and land bank lists change monthly. Details can lag or contain source errors, which is why every listing links back to its official page — always verify with the land bank before making decisions. If you spot something wrong, tell us and we’ll fix it.

What we believe

• Public inventory should be findable. Land banks want their properties sold and reused; obscurity helps no one.
• The real process, up front. Land bank purchases involve applications, proof of funds, and often renovation commitments. We explain the actual rules — no courses, no “free house” gimmicks.
• Free to search, forever. Browsing and email alerts cost nothing. We’re not brokers and take no fee from any purchase.

For land banks, press, and researchers

We’re mission-aligned distribution for land banks: if you run one and want your inventory represented better (or removed), we’ll work with you directly. Journalists and researchers are welcome to cite our statistics with attribution — reach out for data questions at jpnayt@gmail.com.