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FinOps Intelligence

FinOps Intelligence runs cost-reduction recommendations and machine-learning analyses live against the Apache AGE Knowledge Graph. It is independent of the rule-based recommendation engine — refreshing the page re-runs the underlying graph queries — and organizes its analyses into tabs.

Analyses​

  • Overview — Headline KPIs, savings by category, and the top actions

  • Resource clusters — Groups of related resources

  • Cost-reduction analysis — Where and how to cut spend

  • Cost trend — Spend over time

  • ML: Anomaly detection — Statistically unusual spend

  • ML: Criticality (graph centrality) — The most connected, high-impact resources

  • Breakdowns — Spend broken down across dimensions

  • Top & orphan resources — Highest spenders and unattached resources

  • ML: Cost forecast — Projected future spend

  • Reservation candidates — Steady-state usage worth committing

  • ML: Spend spikes — Detected spikes in spend

Best Practices​

  • Refresh for current data — Each visit re-runs the analyses against the live graph; refresh after a sync
  • Start on Overview — The top actions summarize the highest-impact opportunities
  • Corroborate with Recommendations — Use it alongside the rule-based Recommendations for a complete picture