Turn on geocoding without turning it into a project
You need to turn an address into a coordinate. That's the whole ask. The problem is that the two ways to get there both start as a project.
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The case for Mailwoman — why neural, why TypeScript, why a staged pipeline.
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You've got a hundred thousand addresses to reconcile. Two databases, the same clinics and providers scattered across both, each one spelled a dozen ways none.
Geocoding that never phones home
Open the demo, open your browser's network tab, and type an address. It resolves to a rooftop coordinate: 1600 Pennsylvania Ave lands on the actual building, within about ten meters. The network tab shows no request carrying your address. The parser ran in the page. The gazetteer it resolved against is a file on a CDN, and the page read it a few kilobytes at a time. The query stayed on your machine.
We keep the receipt on every coordinate
Every geocoder turns an address into a coordinate. Almost none of them will tell you where that coordinate came from. You get a latitude, a longitude, and a vague confidence enum, and when it's wrong you have no thread to pull — no way to know whether the point came from a federal data release, a county GIS office, or a straight line drawn down the middle of a street. Mailwoman keeps the source on every point. Here's New York, every dot colored by the open dataset it came from.
Same building. Different company. Now what?
Suppose you have a set of records and no key to join them on. A clinic appears in the federal provider registry, again in a state licensing export, and a third time in a funding-program spreadsheet that someone typed by hand. The files share no identifier. The provider number is internal to one publisher, and the facility ID is internal to another. You must judge which records describe the same place for each pair, repeated a few million times.