Fin Ops brings real-time cost intelligence across AWS, Azure, GCP and your clusters into one place: AI rightsizing recommendations, cost anomaly detection, budgets with alerts, and ML-based forecasting, so waste is caught early and Sentinel AI can act on it.
AI-powered insights
Debug logging left in prod
A recent deploy spiked logging costs, ready to fix.
Idle databases
Instances with no connections for two weeks, safe to remove.
Auto-fix available
One recommendation can be applied automatically.
What is Fin Ops
Cloud bills arrive after the money is gone, and the waste is buried across accounts, clusters and services. Fin Ops turns spend into real-time intelligence: cost across AWS, Azure, GCP and clusters in one view, AI recommendations to cut waste, anomaly detection that catches spikes before the invoice, budgets with alerts, and forecasting that warns you before you breach.
Real-time cost intelligence
See spend across AWS, Azure, GCP and your clusters together, with daily run-rate, end-of-month projection and the top services driving cost. A Fin Ops maturity score benchmarks your practices against peers, so you know where you stand and what to improve next.
AI recommendations & rightsizing
Fin Ops surfaces savings across dozens of categories, idle resources, reserved-instance coverage, rightsizing, storage and snapshot cleanup, unattached volumes, tagging compliance and more, each with the opportunity attached. Track implementation and realized savings, and let auto-fix handle the safe ones.
Cost anomaly detection
AI-powered detection watches spend against a learned baseline and flags cost spikes the moment they happen, grouped by cloud and service and ranked by severity. Root-cause analysis ties each anomaly to what caused it, an auto-scaling event, a config change, a traffic spike, so you stop paying for it fast.
Budgets & alerts
Set budgets scoped to a namespace, cloud account, label or team, and watch spend against limit in real time. Status shifts from on-track to approaching to breached with alerts at the thresholds you choose, so finance and engineering share one clear picture, not a surprise at month end.
Forecasting
ML-based forecasting projects spend forward against your budget line and predicts if and when you will breach, with the expected date and overage, plus an accuracy score so you know how much to trust it. Plan quarters and commitments on evidence, not last month's bill.
Budget breach expected
Forecast to exceed the budget limit, with a predicted date and overage.
06Real-world use cases
These are not demo scenarios. Each one is a situation Fin Ops teams meet in real operations, and each ends the same way: an investigation that starts at the evidence and finishes with a decision someone can defend.
Baseline detection ties the spike to the scaling or config change behind it.
Stopped the same dayBudgets scoped by namespace, cloud, label or team, with threshold alerts.
Finance and engineering agreeML forecast projects spend with a confidence interval and breach date.
Commitments on evidenceCommitment coverage tracked beside rightsizing and idle-resource findings.
Savings tracked to realised07Business perspective
Fin Ops is an engineering capability with a business ledger. The entries that matter are waste removed earlier, predictable cloud budget, accountable spend and savings you can prove, and it moves all of them.
Spikes caught in-day rather than on the monthly invoice.
Forecasting warns before the breach, with a date attached.
Budgets scoped per team, cloud or project, with alerts.
Recommendations tracked from generated to implemented to realised.
08The numbers
Worked example against an annual cloud commitment. Every figure shows the sum it came from; during a pilot we substitute your own inputs.
Spend running per day
$33k a day
$12M annual cloud spend / 365
Exposure while anomalies go unseen
$3.55M
$33k/day × 18 days × 6 anomalies
Provisioned and never consumed
$3.36M
28% idle × $12M annual cloud spend
Released if idle is reclaimed
$2.02M
Modelled at 60% reduction, not a measured result
Powered by Sentinel AI
Fin Ops does more than flag a spike or a breach. Every signal, spend, recommendations, anomalies, budgets and forecast, feeds Sentinel AI, the intelligence component at the core of Opstral, which resolves waste through governed, reversible Action Tickets.
Turn off debug logging, terminate idle instances, rightsize a workload, every step explained with citations and fully audited.
Observe
Fin Ops correlates spend, recommendations, anomalies, budgets and forecast across clouds.
Investigate
Sentinel AI finds the root cause of the spike or overspend and picks the right procedure.
Act
ProcBot executes the approved MOP, terminate, rightsize, cap, through a reversible Action Ticket.
Optimize
Sherlock validates the saving and feeds the learning back to keep spend in line.
Book a walkthrough and see unified cost intelligence, AI rightsizing, anomaly detection and forecasting on spend that looks like yours.