How teams use
Stratum in the wild.
A look at the real problems data teams were dealing with before they started using Stratum — and what changed after.
From silent breakages to zero-surprise deploys
Watershed runs carbon accounting pipelines for hundreds of enterprise clients. A single bad deploy meant wrong emissions data — not something you can quietly roll back. Stratum gave their data team environment promotion gates and schema drift alerts, cutting data incidents by 60% in eight weeks.
Shipping product analytics without waking up at 3am
Linear's data team was small and fast-moving — but their Airflow DAGs were fragile. A schema change in one upstream event would break their entire product analytics stack. With Stratum, they version every DAG, get paged before stakeholders notice, and deploy changes in one click.
Lineage that actually makes sense to engineers
Retool's data team was spending three hours a week tracing why a downstream model was stale. The answer was always somewhere in a chain of upstream dependencies nobody had documented. Stratum's lineage visualization turned a three-hour debugging session into a two-minute click-through.
Want results like these?
Most teams catch their first pipeline failure in the first week.