Texas Cross Dock Finder maps 114 logistics facilities across 40+ Texas cities. Built in about three weeks with an AI data pipeline — and now sitting on page one of Google for its niche, on autopilot.
Cross-docking — transferring freight between trucks without warehousing it — is a real logistics need with no good directory. Shippers who need a dock in Laredo or a transload partner in Houston were stuck with generic search results.
Texas Cross Dock Finder fills that gap: 114 facilities across Texas with services, contacts, ratings, and an interactive map. It was built as a test of a repeatable question:
The question: Can AI build a genuinely useful niche directory — data collection included — fast enough that ranking in a small market becomes economical?
Automated searches across every major Texas metro — fifteen query variations per city against the Google Places API — found candidate facilities, deduplicated and filtered to true cross-dock operations.
An AI model read each facility's website and extracted structured data — services offered, hours, contacts, capacity notes — turning messy logistics websites into a consistent, comparable schema.
Ten city landing pages at exact-match URLs (“cross-docking-houston”), each automatically populated with nearby facilities by distance from the city center. One dataset fans out into every page a searcher might want.
Static site on Cloudflare's edge with self-hosted vector maps — no database, no server, no per-request map fees. The whole thing costs essentially nothing to operate while it accrues rankings.
After the three-week build, the site has needed only occasional touch-ups — and search performance has compounded on its own:
A directory like this was never worth three months of hand-built effort. At three weeks — with AI doing discovery, enrichment, and page generation — the math changes. Any business that serves a fragmented local market can own the map of it: the directory becomes the lead source, and page one in a niche is far easier than page one anywhere else.
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