CloudThinker's Frontier Investigation Agents find the why behind every cost spike. The Optimize agent proposes the fix and verifies the savings, so you pay only for what you use. Your engineers approve.
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.
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.
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.
A one-off cleanup helps for a month. New waste accumulates immediately, and the next review starts from zero. Cost control isn't continuous.
The Optimize agent doesn't stop at a recommendation. It runs the full DARV loop on every piece of waste, all the time. Savings are found, proposed, applied and confirmed, and your engineers only approve.
Continuously scan usage and billing data for idle compute, oversized resources, orphaned storage, and gaps in commitment coverage.
Attribute the cost to a team and service, quantify the savings, and assess blast radius before proposing a scoped, reversible fix.
Apply the fix inside a sandbox with brokered, scoped credentials, at the autonomy level you set, from recommend-only to act-with-guardrail.
Confirm the savings landed and nothing regressed, then record the whole action in a tamper-evident audit trail.
Every remediation runs at an autonomy level you promote over time. Start with recommend-only, and as the Optimize agent earns trust on a class of change, graduate it to act within a defined guardrail.
The agent surfaces prioritized savings with quantified impact. A human applies every change.
The agent prepares a scoped, reversible change and opens it for approval, so review takes seconds instead of an investigation.
For trusted change classes, the agent applies the fix once an approver signs off at the gate.
Within a defined guardrail, the agent detects, fixes, and verifies on its own. Engineers stay on the loop and review outcomes.
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.
Credentials are issued per task and scoped to the change. The agent never holds standing production keys.
Actions run inside an isolated environment where the credential lives in the sandbox, not the prompt.
Sensitive billing and account data is deterministically tokenized at egress before it ever reaches a model.
Every cost change is reversible and captured in a tamper-evident audit trail: who, what, when and why.
The agent works continuously, so idle and oversized resources are flagged and fixed as they appear, not in the next review cycle.
Because detection never stops, new waste is removed as fast as it accumulates. Cost control becomes a baseline, not a project.
Teams approve outcomes instead of hunting through billing exports. Time goes back to building, not to reclaiming forgotten volumes.
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 Frontier Investigation Agents 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.
Cost dashboards and native tools surface recommendations, then hand the work back to an engineer who has to investigate, decide and execute. 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.
Yes, because autonomy is graduated and governed. The Optimize 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.
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.
CloudThinker connects to your existing cloud accounts and billing/cost data through Connections, so the Optimize agent reasons over real usage rather than a static export. AWS is the primary target today.
Because the agent works continuously rather than in a quarterly review, the first waste report typically lands within days of connecting an account.
Connect an account. Frontier Investigation Agents find the waste and the why behind it, propose the fix and verify the savings. Your engineers approve, with a full audit trail.