Address-to-well-record lookup and kit sizing automation for ArcGIS

What it calls

This is the endpoint this build calls directly, with runtime values replaced by a placeholder.

• the Census geocoder plus 17 state ArcGIS endpoints and a bespoke Wisconsin WCIS JSON adapter

What it reads and writes

Every read and every write this build makes is printed below, as the build sends it, with runtime values replaced by a placeholder.

• Postgres table `wells`

Safety checks

An automation that writes into a system of record has to refuse some cases. These are the checks this build makes before it acts.

every state pinned by a real captured fixture across 46 tests

Arizona, California and Delaware demoted to fallback-only

a confirm card, editable values and round-up dosing because zero room for error from records alone is impossible

an 8s upstream timeout and a per-instance in-memory rate limit and cache that resets on a cold start

Where it runs

It runs as Vercel, node runtime.

It also touches Census geocoder and Postgres.

What this record is

Data Jockey is a services firm, so this page is an implementation record. There is no product to buy here and no price on this page.

No customer is named on it either. Data Jockey publishes no customer list, and the calls and checks above are the part a reader can check.

Questions we hear

Is address-to-well-record lookup and kit sizing automation for ArcGIS a product or a project?

It is a project. The queries on this page are specific to how one company had its ArcGIS set up: which fields carried the human identifier, which documents already existed, and where a human had to stay in the loop. A product cannot know any of that in advance, which is why the integration is the work.

Did this run in production?

Yes. It runs in production today as Vercel, node runtime, and this page is read out of the code that runs.

What happens when the automation is not sure?

It stops. This build carries 4 distinct kinds of check, and every one of them exists to hand the case to a person. Automating the confident cases and routing the rest is what makes an integration safe to leave running.

Can Data Jockey build this for us?

Book a call and we will scope it against the systems you already run. Data Jockey publishes no prices, so there is no figure on this page, and what a build costs depends on what your setup turns out to need.

Where these facts come from

Every call, table, check and setting above comes from the delivery record of this build, and each identifier in it was checked against the file that implements it by tools/capture-proof-of-work.mjs. The capture is committed at data/raw/dj-proof-of-work-capture-2026-09-07.json and records a sha256 of each source file. Generated 2026-09-07. No figure here was rounded, averaged or estimated.