Forecast Error (%)
Set: <= 10 %
Difference between projected and actual spend.
Case Study · Internal luckyCONCEPT operations platform
Cost Control
Cost Control is the central command layer for AI/API spend, budget risk, and service stability across multiple products.
“Teams now get a clear live picture of spend, anomalies, and service health, enabling earlier action before overspend or incidents escalate.”
Operational Metrics
Budget Alert Lead Time
Set: >= 7 days
Average warning time before projected budget overrun.
Anomaly Precision
Set: >= 80 %
Signal quality of anomaly alerts usable in operations.
Incident MTTR
Set: < 4 h
Mean time to resolve incidents in the control workflow.
Selected Screens
Challenge
Multiple systems generated ongoing spend, but there was no shared operational view of usage, risk, and service reliability.
Goal
The goal was one practical control center that combines cost, risk signals, and service status in a single decision-ready workflow.
Contribution
I built the stack end to end: ledger data model, API gateway, worker jobs, and admin UI with budgets, alerts, forecasts, and health monitoring.
Approach
Delivery followed a staged rollout: reliable data capture first, then budget and anomaly logic, then a UI that supports fast and confident decisions.
Outcome
Teams now get a clear live picture of spend, anomalies, and service health, enabling earlier action before overspend or incidents escalate.
Learnings
FinOps creates real value when cost, reliability, and operations are designed as one system—not as separate reporting layers.