The Impact
90
%
faster detection of performance shifts across locations
70
%
reduction in manual analysis and reporting workload
3
x
faster generation of contextual root-cause insights
Enterprise AI: Build or Buy?
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The operations team lacked an intelligent alerting system to flag meaningful changes in business performance across sites. Although transactional data from Quivio was available, identifying issues like a 10% weekly drop in recurring plan usage required manual analysis and intuition. This reactive process delayed response times, obscured the root causes behind changes, and limited the ability to optimize quickly. Leadership needed a way to move from static reporting to continuous, AI-driven monitoring that could connect the “what” with the “why” behind performance shifts.
Unframe deployed an AI-powered performance monitoring system that continuously scans transactional data from Quivio to detect meaningful shifts in business performance across car wash locations. Using a Dynamic Triggering System, the AI identifies anomalies - such as a 10% drop in recurring washes or an unexpected revenue spike - and performs Root Cause Analysis (RCA) by layering public data like weather, traffic, holidays, and local events to explain why changes occur. This enables operations teams to respond proactively to issues, optimize faster, and make every decision data-driven.
