A complaint log that can't assign fault
Most delivery businesses have a complaint log. Very few have a complaint log that tells them who was actually at fault. Was it the driver, the merchant, the dispatch system, or something outside anyone's control like weather or traffic? Without that distinction, every incident gets treated the same, and coaching, accountability, and process fixes all become guesswork.
Structured incident data
Agility structured the incident and quality data feeding into ATLAS to carry fault attribution, validation status, and sentiment on every logged complaint. Combined with GA4 product analytics, recommendation events, loyalty data, and Sentry error monitoring, this became one of the richest but least-used parts of the warehouse.
Feeding predictions and the Zone Explorer
That structured incident data feeds two things directly: the order-risk model's failure-type predictions, and the Zone Explorer, which lets analysts drill into any zone's orders, merchants, and hourly demand profile for coverage planning and merchant onboarding decisions.
The insight that mattered most
Most of the warehouse, the analytics, recommendations, loyalty, and error telemetry, was connected but sitting unused before this work. Each additional clean, joinable data source doesn't just add a chart, it unlocks a new class of prediction entirely.
Richer, consistently-attributed incident labels unlock multi-cause failure prediction instead of just a risk score. Clean driver identity joined across systems unlocks fair, per-driver reliability scoring. This is the throughline for every vertical ATLAS extends into: the platform's ceiling is set by data quality, not model architecture.