CloudPi gives every optimization a next step. Low-risk changes can auto-execute, sensitive actions can wait for approval, and cross-team work can arrive as enriched tickets with context already attached.
One recommendation stream, one policy router, and three clear outcomes your teams can understand at a glance.
CloudPi estimates savings and checks policy coverage before routing.
Recommendation is strong financially but needs a higher-control path.
CloudPi checks environment, workload criticality, confidence, and expected savings.
Instead of long copy blocks, this page now shows how CloudPi moves recommendations through routing, action, and savings validation.
Teams see where a recommendation is, who owns the next step, and whether the outcome turned into realized savings.
Find optimization opportunities across AWS, Azure, and GCP.
Apply policy to send the recommendation into the right workflow.
Run automatically, wait for approval, or open a ticket with context.
Track approvals, execution status, and TRUE savings outcomes.
CloudPi supports the workflow each decision deserves instead of forcing every recommendation through the same process.
Best for repeatable savings actions where confidence is high and operational risk is low.
Use for production systems, business-critical services, or recommendations with higher change sensitivity.
CloudPi opens tickets with resource details, expected savings, and enough context for engineers to act immediately.
The platform helps teams understand movement across execution, ownership, and realized savings without waiting for perfect tags or manual spreadsheet tracking.
See whether an optimization is queued, approved, executed, deferred, or blocked.
Choose autonomy or review based on workload criticality and operational rules.
Give downstream teams tickets with resource details, savings impact, and ownership clues.
Prioritize actions that become measurable savings rather than static recommendation counts.
This is the lifecycle teams follow when automation is built into the operating model instead of left outside it.
Surface optimization opportunities across cloud environments.
Evaluate savings value, confidence, owner, and risk profile.
Choose auto-run, approval workflow, or ticket-based collaboration.
Monitor status changes and keep ownership visible across teams.
Focus reporting on actions that resulted in realized savings.
CloudPi turns cloud optimization into an operational system with visible routing, measurable outcomes, and a cleaner path to TRUE savings.
Low-risk recommendations can move without waiting in a manual queue.
Critical workloads stay protected by approvals and policy-based routing.
Teams receive richer tickets and shared visibility from insight through outcome.