CloudKeeper

Cloud cost optimization AI that acts on the waste it finds.

Dashboards tell you where the money leaks. CloudThinker's CloudKeeper and CostOps Agent detect the waste, analyze the cause, apply a scoped fix under your policy, and verify the savings — with brokered credentials and a full audit trail. Autonomous FinOps, with engineers on the loop.

  • Start free — no credit card
  • Graduated autonomy L1–L4
  • Tamper-evident audit trail
The problem

Your cloud bill grows faster than anyone can review it.

Cost tools generate hundreds of recommendations. Acting on them is manual, risky, and always second on the priority list. So idle resources keep running, right-sizing stalls in a ticket, and last quarter's savings quietly erode.

Recommendations, not action

A dashboard flags oversized instances and unattached volumes — then hands the work back to an engineer who is already busy. Savings sit in a backlog.

Fear of breaking production

Nobody wants to be the one who right-sized a database at 2am. Without guardrails and reversibility, the safe choice is to leave the waste running.

Savings that don't stick

A one-off cleanup helps for a month. New waste accumulates immediately, and the next review starts from zero. Cost control isn't continuous.

How CloudThinker solves it

A closed loop for cost: Detect, Analyze, Remediate, Verify.

CloudKeeper and the CostOps Agent don't stop at a recommendation. They run the full DARV loop on every piece of waste — continuously — so savings are found, applied, and confirmed without a human doing the toil.

Detect

Detect

Continuously scan usage and billing data for idle compute, oversized resources, orphaned storage, and gaps in commitment coverage.

Analyze

Analyze

Attribute the cost to a team and service, quantify the savings, and assess blast radius before proposing a scoped, reversible fix.

Remediate

Remediate

Apply the fix inside a sandbox with brokered, scoped credentials — at the autonomy level you set, from recommend-only to act-with-guardrail.

Verify

Verify

Confirm the savings landed and nothing regressed, then record the whole action in a tamper-evident audit trail.

Graduated autonomy

You decide how much the cost agent is allowed to do.

Every remediation runs at an autonomy level you promote over time. Start with recommend-only, and as the CostOps Agent earns trust on a class of change, graduate it to act within a defined guardrail.

L1

Recommend

The agent surfaces prioritized savings with quantified impact. A human applies every change.

L2

Draft the change

The agent prepares a scoped, reversible change and opens it for approval, so review takes seconds instead of an investigation.

L3

Act with approval

For trusted change classes, the agent applies the fix once an approver signs off at the gate.

L4

Autonomous in guardrail

Within a defined guardrail, the agent detects, fixes, and verifies on its own. Engineers stay on the loop and review outcomes.

Governance built in

Autonomous cost changes only stay safe with real guardrails.

CloudThinker gives the cost agent power without giving it standing access. The same controls that make production incident work safe apply to every cost action.

Brokered, scoped credentials

Credentials are issued per task and scoped to the change — the agent never holds standing production keys.

Sandboxed execution

Actions run inside an isolated environment where the credential lives in the sandbox, not the prompt.

Deterministic tokenization

Sensitive billing and account data is deterministically tokenized at egress before it ever reaches a model.

Reversible & audited

Every cost change is reversible and captured in a tamper-evident audit trail — who, what, when, and why.

Outcomes

What continuous, autonomous FinOps changes.

Waste caught in days, not quarters

The agent works continuously, so idle and oversized resources are flagged and fixed as they appear — not in the next review cycle.

Savings that hold

Because detection never stops, new waste is removed as fast as it accumulates. Cost control becomes a baseline, not a project.

Engineers freed from cost toil

Teams approve outcomes instead of hunting through billing exports. Time goes back to building, not to reclaiming forgotten volumes.

FAQ

Cloud cost optimization AI, answered.

What is cloud cost optimization AI?

Cloud cost optimization AI uses autonomous agents to continuously find and remove cloud waste — idle resources, oversized instances, unattached storage, forgotten environments, and inefficient commitments — instead of leaving it to a monthly manual review. CloudThinker goes past a dashboard of recommendations: its CloudKeeper and CostOps Agent detect the waste, analyze the root cause and blast radius, propose a scoped remediation, and — under your approval policy — apply and verify the fix, with every action captured in a tamper-evident audit trail.

How is this different from a cloud cost dashboard or a native cost tool?

Cost dashboards and native tools surface recommendations, then hand the work back to an engineer who has to investigate, decide, and execute — so savings stall in a backlog. CloudThinker closes the loop: it takes the recommendation as input, runs the analysis, and carries the action through to a reversible, approved change. You review outcomes, not spreadsheets.

Is it safe to let AI make changes to my cloud spend?

Yes — because autonomy is graduated and governed. The CostOps Agent runs at the level you set, from L1 (recommend only) up to L4 (act within a guardrail). Credentials are brokered and scoped per task, execution is sandboxed, sensitive data is deterministically tokenized at egress, and every change is reversible and logged in a tamper-evident audit trail. Engineers stay on the loop; the agent never gets standing production access.

What kinds of cloud waste can CloudThinker find and fix?

Idle and underutilized compute, oversized instances and databases, unattached and orphaned block/object storage, old snapshots, forgotten non-production environments, misconfigured autoscaling, inefficient logging and data-transfer patterns, and gaps in commitment coverage (Savings Plans / Reserved Instances). It attributes cost by team and service so savings land where the spend actually is.

Which clouds does the cloud cost optimization AI support?

CloudThinker connects to your existing cloud accounts and billing/cost data through Connections, so the CostOps Agent reasons over real usage rather than a static export. AWS is the primary target today. TODO(steve): confirm current multi-cloud coverage (Azure/GCP) wording before publishing.

How quickly do teams see savings?

Because the agent works continuously rather than in a quarterly review, the first waste report typically lands within days of connecting an account. TODO(steve): add a concrete time-to-first-savings figure and a customer outcome number once approved.

Start cutting cloud waste

Put a cost agent on your cloud bill.

Connect an account and let CloudKeeper find the waste, propose the fix, and verify the savings — under your policy, with a full audit trail.

  • Free to start
  • Engineers on the loop
  • SOC 2-aligned controls