SCTR Case Study
How SCTR replaced monthly manual GPS reconciliation with 4-hour automated syncs and 4-week rolling predictive maintenance forecasts.
The results.
Real numbers from production systems—not projections.
The challenge.
What SCTR was dealing with before they came to us.
GPS data was reconciled against the revenue cycle management system once a month—manually. Discrepancies were caught weeks after they occurred.
Vehicles were serviced on fixed schedules or after breakdowns. No data-driven forecasting meant either wasted maintenance spend or costly downtime.
Without real-time GPS-to-RCM sync, billable miles and hours were routinely underreported—leaving money on the table every month.
What we built.
Custom AI workflows mapped to SCTR's existing SOPs and tools.
Automated pipeline that syncs GPS data to the revenue cycle management system every 4 hours—replacing monthly manual reconciliation entirely.
AI model that generates 4-week rolling maintenance forecasts based on mileage, usage patterns, and historical service data for every vehicle.
Automated comparison of GPS-tracked activity vs. billed activity, flagging discrepancies for review and recovering previously missed revenue.
"Going from monthly manual reconciliation to every 4 hours was a revelation. We found revenue we didn't even know we were missing."
READY TO AUTOMATE REAL WORK?
Roadmap-first. Outcome-owned. Built for live operations.