CloudPivot · cloud cost control
Cost reports don't cut your bill. Execution does.
Find wasted cloud spend, schedule idle resources, and approve fixes from one control plane. Understand your AI costs alongside your infrastructure.
YOUR CLOUD + AI
ESTIMATED OPPORTUNITY
$8,940/mo
Illustrative monthly estimate
Always on · 168 hours per week
The control plane
From “we should fix that”
to already done.
Choose an opportunity. Inspect its evidence and estimated impact, then try the available action. Every interaction below uses sample data.
PROPOSED CHANGE
Give dev the weekend off
Stop development capacity Friday evening. Bring it back before the team arrives Monday.
Evidence: development-tagged fleet · no weekend schedule
› Preview complete. Waiting for your approval.
Your first session
Start with a finding.
Decide what happens next.
Quick Wins finds configuration waste in discovered inventory. You can start reviewing opportunities before you have weeks of metrics.
01Connect an account
Connect AWS with a scoped role. Choose the accounts and regions you want to explore.
02Discover your resources
Build an inventory and surface configuration waste without waiting for utilization history.
03Review your Quick Wins
Inspect each finding, its evidence and estimated impact. Choose which opportunities to take forward.
Estimated monthly opportunity
$580/mo
3 configuration findings · review before acting
EBS storage
gp2 volume eligible for gp3
CloudWatch logs
Log group has no retention limit
Unused public IPv4
Allocated address has no association
Sample estimates explain the workflow; actual findings depend on your inventory.
Resource-aware scheduling
Give idle infrastructure
the weekend off.
Set a window for development resources to rest and return. Explore an example weekend below, with production kept running.
The weekend belongs to you.
Approved schedules turn idle capacity off.SIMULATED TIME
FRI 20:30 UTCSCHEDULED REST
59 hours / weekendEXAMPLE SAVINGS
$646Resource-specific safeguards account for service behavior, including EKS ownership and autoscaler constraints.
AI economics
Know what your AI costs.
And what it is for.
Follow spending from provider to team to use case. Find cache and batch opportunities, and compare costs with the business value you record.
Explore AI tokenomicsAsk the agent to investigate
“Why did our support assistant cost more this week?” Explore usage, evidence and next steps in plain language.
Meet the agent →Total provider spend
$9,000
2.4 million requests
$0.00375 / request
A shared view of provider spend, with a consistent cost vocabulary.
Cache opportunity
Repeated context in support prompts. Review cache eligibility.
Batch opportunity
Offline document jobs may tolerate deferred responses.
Illustrative data · recommendations do not change provider settings
Built into the workflow
Your infrastructure.
Your rules for changing it.
- 01
Preview the change
Review the resource, proposed configuration and estimated impact before taking action.
- 02
Choose what can run
Approve supported changes and define the scope of automation. Advisory findings remain recommendations.
- 03
Follow the evidence
Inspect recorded actions and configuration checks. Keep estimated savings distinct from measured spending.
- 04
Stay in control
Undo supported changes and watch supported optimizations for configuration drift. Some actions cannot be reversed.
See what your cloud could save.
Start with a walkthrough of discovery, Quick Wins, and your first proposed schedule. See the evidence before choosing what to change.