Why I built this

Hi, I'm Blaine Elliott. I've spent the last decade-plus inside data engineering organizations at companies most people would call "the ones who have this solved": LinkedIn, One Medical, and AbnormalAI among them. Full modern data stack, staffed correctly, with budget.

The thing nobody tells you: even at that scale, data still breaks constantly. A column type changes upstream and three dashboards lie for a week. A nightly job silently stops loading and the exec team makes a quarterly decision on stale numbers. The difference at a big company isn't that the data doesn't break, it's that there's a team whose entire job is catching it before anyone notices.

The data breaks the same way at five people as it does at five thousand. The only difference is who notices.

Meanwhile, a five-person company running on a Postgres database and a Snowflake account they spun up last quarter has the exact same problem and none of the headcount. The fix everyone points them at is "hire a data engineer and buy Monte Carlo." That stack costs more than their first three engineers combined and assumes someone is going to configure it.

So I built the thing I wished I could hand them: a service you point at a warehouse, that figures out on its own what each table should look like, and tells you when something genuinely breaks. The hard part of data quality isn't writing checks, it's deciding which checks matter and tuning them so they don't scream. That's the wall AnomalyArmor is built to get past, with the playbook I spent a decade learning at companies that could afford to learn it the expensive way.