Instrumentation drifts from the roadmap
Events get added ad hoc by whichever engineer shipped the feature, and six months later nobody agrees what "signup_completed" means.
Product & Engineering
Ship the feature, then know if it worked.
Instrument once, then let every team query the same event schema — no more waiting on a data analyst to answer "did that launch actually move the number."
9 daysto 3 days per experiment
1shared metrics layer
-64%dashboard disputes
The problem today
What Aurora replaces.
Experiment results take a week
By the time the analytics team pulls significance on an A/B test, the sprint that shipped it is already three sprints behind.
Dashboards nobody trusts
Every team has its own version of "active user," so the weekly metrics review starts with an argument about whose number is right.
How it works
Built for this team.
Schema-governed event trackingLive view
Schema-governed event tracking
A typed event catalog with CI checks means a bad event name gets caught in code review, not three months into a dashboard.
Built-in experiment analysisLive view
Built-in experiment analysis
Point Aurora at your feature-flag provider and get sequential significance testing without exporting a single CSV.
One metrics layer, every teamLive view
One metrics layer, every team
Define "active user" once in the semantic layer and every dashboard, alert and report inherits the same definition.
Other teams
More solutions.
Retail & DTC
E-commerce & retail
Unify storefront, warehouse and ad-platform data in one place so merchandising, growth and finance work from the same numbers — down to the SKU.
Fintech & PaymentsFintech & payments
Stream transaction, KYC and support events into one governed warehouse so risk, compliance and product can all query the same source of truth.
See your data in Aurora
before your next standup.
Book a 20-minute walkthrough with a solutions engineer, using your own event schema if you want to.