Catch problems before they grow AI-powered alerts on the breakdowns you'd otherwise miss.
Google's time-series model TimesFM catches breaks that slip past your top-line metrics. It filters out seasonality and noise on its own leaving you nothing but the action.
A 30-minute live tour with your own metrics.
−40% conversion rate · UK · mobile · campaign X
Built on TimesFM — Google's foundation time-series model and proven against real production traffic.
Detection that does the watching for you
No setup, no thresholds, no warm-up. The model learns what normal looks like and only speaks up when it matters.
No warm-up
Works from day one
You don't wait months for data to pile up or sit through long training periods. The moment it connects, monitoring begins.
Zero configuration
No threshold tuning
You never write manual rules. The model learns what normal variation looks like, so it won't wear you down with a flood of needless false-positive alarms.
Pinpoint accuracy
Deep drill-down monitoring
It doesn't send a generic "your traffic dropped." It tells you: conversion rate in the UK market, on mobile devices, for campaign X is down an unexpected 40%.
Right place, right time
Instant alerts, where you already work
What changed, by how much, where? Every detection lands in your email or Slack channel within seconds.
Anomaly detected · conversion rate
Slack
#growth-alerts · just now
What's under the hood
TimesFM engine
Google's foundation time-series model does the forecasting heavy lifting.
Seasonality awareness
It won't mistake holiday or weekend swings for anomalies.
Multi-dimensional breakdown
Scans country × device × campaign combinations, not just the headline number.
Slack & email
Alerts arrive where your team is already looking no new dashboard to babysit.
Frequently asked questions
Still wondering about something? A discovery call clears it up fast.
No. Because the model learns your normal variation, only statistically significant deviations ever trigger an alert.