Overprovisioning is the default
Compute, databases, and Kubernetes requests get sized for a peak that rarely comes, then never revisited. Without governance at the point of provisioning, every new workload starts oversized and stays that way.
Agentic Cloud Optimization
Cloud cost optimization, proven on your bill
Jetscale finds the savings your discounts can't touch across AWS, Azure and GCP, then hands your engineers ready-to-approve fixes. Every saving is verified against your actual cloud bill.
Read-only access Terraform-native Guaranteed ROI
Trusted by engineering and platform teams at
The problem
Cloud bills keep climbing. The reports don't bring them down.
Teams have more cost visibility than ever: dashboards, tagging, anomaly alerts, savings decks. Yet 40% of the average cloud budget goes to over-provisioned compute, idle capacity, and mis-tiered storage, while cloud is now the second-largest line item on the corporate P&L, right after salaries. Most of that spend is going to resources nobody is using, because seeing a cost has never been the same as shipping the fix.
Idle resources run around the clock
Dev environments on weekends, unattached storage, endpoints nobody remembers deploying. It stays invisible because utilization data never reaches the person who owns the resource, and without that data, idle looks identical to essential.
AI tokens are the new unmetered spend
Token bills are growing faster than any other line item: no per-team attribution, models overqualified for the task, context windows padded by default. Spend that moves this fast outruns quarterly reviews; it needs resolution in days.
Breaking the cycle takes all three, in order: governance that catches over-provisioning the moment it appears → cost data in front of the owner who can actually act → resolution shipped in days, not quarters. That's the loop Jetscale runs.
The drift problem
And even after a cleanup, spend drifts back.
Point-in-time cleanups reset the meter. They don't stop it. New workloads launch oversized, defaults regress, environments outlive their purpose. Drift is continuous, so optimization has to be too.
Entropy is the default
New workloads launch oversized. Storage lands on legacy tiers by default. Test environments outlive their purpose. Manual cleanups only reset the clock.
The compounding gap
By month 12, drift reaches 33% of total spend. On $100K/month, that's $33K a month ($396K a year) gone to entropy.
The continuous fix
Jetscale doesn't optimize once. It monitors for drift, flags policy violations, and generates fresh Terraform-ready remediations as your infrastructure evolves.
- Oversized new instances
- Storage on legacy tiers
- Dev databases running 24/7
- Traffic on costly network paths
- Storage without lifecycle policies
- Pod requests never re-tuned
- Every one detected automatically.
How it works
Connect, detect, ship. Then verify the savings.
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Connect read-only
Plug in your AWS, Azure, and GCP accounts with read-only access. Jetscale never writes to your cloud. Nothing changes without your team's review.
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Detect and prioritize
The Analyzer Agent scans your footprint and ranks every opportunity with evidence: telemetry, configuration data, and business context. Findings, not hunches.
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Plan and ship Your team merges
Each finding becomes a structured plan (what changes, expected impact, safest rollout path) delivered as a PR-ready Terraform diff or a guided ClickOps runbook with exact console URLs. Review, merge, deploy. Like any other change.
See it in action
The whole loop, in one walkthrough.
From read-only connection to a merged Terraform fix and a verified line on your bill, watch Jetscale run the loop end to end.
Platform
Findings become pull requests. Pull requests become savings.
Built for the agentic era, and fully transparent about it. Jetscale's agents show their work: every finding carries the evidence behind it, the math on the savings, and the exact change that fixes it. You can audit every step the agent took. No black boxes, no mystery savings.
Continuous, evidence-backed detection
The Analyzer Agent doesn't audit once. It monitors for drift, flags policy violations, and generates fresh remediations as your infrastructure evolves. Every recommendation is validated by telemetry, configuration data, and business context. Cluster right-sizing, S3 tiering to Glacier, VPC endpoint gaps, outdated machine types, dev databases running 24/7. Found automatically, ranked by impact.
Fixes as code, not findings in a spreadsheet
Every opportunity ships as a PR-ready Terraform diff, reviewed, versioned, and rolled out like software, with a full audit trail. Prefer the console? Get a guided ClickOps runbook with the exact URLs and steps. Either way, the fix lands in your workflow, not in another dashboard.
Pre-verified savings, including Spot
OptimizeSpot simulates eviction risk against your actual workloads before recommending an On-Demand-to-Spot move. If it isn't safe, it isn't recommended. Spot savings you can bank, not gamble.
Pre-verified savingsRead-only by design. Self-funded by results.
Jetscale never writes to your cloud. Plans are policy-aligned, changes go through your Git review, and your engineers hold the merge button. Savings are confirmed against your actual bill, and they're what pays for Jetscale. Engineers keep control. Finance gets receipts.
Verified against your bill
pull/482 · rightsize-analytics-cluster.tf
resource "aws_instance" "analytics_worker" {- instance_type = "m5.4xlarge"+ instance_type = "m5.2xlarge" ami = data.aws_ami.worker.id subnet_id = aws_subnet.private_a.id}
OptimizeSpot · eviction-risk simulation
workloadbatch-etl / us-east-1
simulation30d usage replayed against Spot pools
eviction risk
low
Safe to migrate: On-Demand → Spot
Savings proof
The math, not the marketing.
33%
of total spend lost to drift by month 12 without continuous optimization
$396K/yr
recovered continuously on a $100K/mo cloud bill
$0
downside risk: if verified savings fall short of our fee, we credit the difference
Drift figures from Jetscale's compounding-drift model; see Cloud optimization for the breakdown.
Integrations
Built for the stack you already run.
Jetscale reads the cloud accounts you already have and writes back through the tools your engineers already use. No proprietary IaC, no new dashboard to babysit.
Clouds
AWS
Microsoft Azure
Google Cloud
Workloads
Kubernetescluster right-sizing, pod request tuningEKS · AKS · GKE
Virtual machinesright-sizing, Spot and Graviton suggestionsEC2 · Azure VMs and Scale Sets · Compute Engine
Managed databasesinstance and cluster right-sizingRDS and Aurora · Azure SQL · Cloud SQL
Block & object storageidle disks, tiering, lifecycle policiesEBS and S3 · Managed Disks and Storage Accounts · Persistent Disk
AI & dataAI token spend, data warehouse usageBedrock on AWS · BigQuery on GCP
Delivery
Terraform
GitHub & Git-based review
Your cloud consoleguided ClickOps
Your cloud
AWS · Azure · GCP, read-only
Jetscale
Analyzer Agent
Your repo
PR-ready Terraform · runbooks
Proof
Proof from teams who shipped the fix.
Cluster right-sizing
Kubernetes nodes and pod requests re-tuned to actual utilization, shipped as a reviewable Terraform diff.
On-Demand → Spot migration
Pre-verified by OptimizeSpot: eviction risk simulated against the real workload before the move was recommended.
S3 intelligent tiering to Glacier
Cold objects moved to the right storage class with lifecycle policies your team merged like any other change.
Find out how much budget
you will unlock
Monthly Cloud Bill
$120 000
Optimization scenario
10%: Conservative
20%: Average
35%: Optimistic
Redeem
Cashback
Engineering Hours
Processing Power
Tokens
Cash back to you every year
$231 212
CO2 Reduction
1 192 kg/year
57 trees
This estimate is indicative. Connect your cloud account read-only to get your real number.
How it compares
Brokers lower the rate. Dashboards chart the spend. Vendor agents take the keys.
Jetscale does the part they leave out. It finds the recoverable spend across AWS, Azure and GCP and hands your team each fix as a pull request, with read-only access. Each row is a question your security, engineering or finance team will ask.
| Question | JetscaleShips the fix as code | Commitment brokersBuy reserved instances and savings plans for you | Cost dashboardsShow where the spend goes | Vendor agentsChange your cloud for you |
|---|---|---|---|---|
| Lowers what you runright-sizing, storage, idle resources, network | Yes: Right-sizing, storage, idle resources and network, across the estate |
No: Lowers the rate on usage you commit to, not the usage |
Partly: Shows where the spend goes, with recommendations |
Partly: The compute it manages: clusters, serverless, VMs |
| Hands you the fix as codea pull request your team reviews and merges | Yes: A Terraform pull request in GitHub or Azure DevOps |
No: Nothing to merge. Commitments are bought for you |
No: A report. Your team writes the change |
No: Its automation applies the change in your cloud |
| Works without write accesswhat your security team signs off | Yes: Read-only. The merge is the only write |
Partly: Purchase rights. With some, your bill routes through the broker |
Yes: Read-only billing and usage data |
No: Write access to the resources it manages |
| Shows the evidencewhat your engineer sees before merging | Yes: Up to a year of telemetry with peaks kept, tags, attached resources, implementation effort |
No: Usage patterns, for sizing commitments |
Partly: Cost allocation and trends |
Partly: Runtime metrics for what it manages |
| Covers AWS, Azure and GCPin one costed view | Yes: All three, at the same depth, in one costed view |
Partly: Varies by broker |
Yes: Often multi-cloud |
Partly: Varies. Often Kubernetes-first or AWS-first |
| How you paywhat your CFO signs | Self-funded. If verified savings come in below the fee, we credit the difference. |
A share of savings, or free with a margin on your bill. |
A subscription, often tied to your cloud spend. |
A quote, often per resource, CPU or cluster. |
| The short version | Finds the recoverable spend across your clouds, ships each fix as code your team merges, and never needs write access. |
They lower the rate on what you buy. We lower what you need to buy. The two stack. |
They tell you where the spend is. We hand you the code that fixes it. |
They need a vendor agent in your infrastructure. We hand your team the change as code and the evidence that backs it. Your team decides what goes through. |
Built inPartly, or with conditionsNo
Category view, based on typical offerings. Individual vendors vary. Comparing a specific vendor? Ask us for the side-by-side
Three questions to ask any vendor
Put them to every tool on your shortlist. These are our answers.
Who writes the change once a recommendation is accepted?
We open the pull request. Your team reviews it and merges it.
Does it need write access to production?
No. Jetscale is read-only. The merge is the only write.
What do we pay if little is found?
If verified savings come in below the fee, we credit the difference.
FAQ
Frequently asked questions
Jetscale doesn't stop at reporting. It turns opportunities into Terraform-ready remediation changes your team implements through normal engineering workflows.
No. Monitoring shows signals and incidents. Jetscale uses those signals (plus cost and configuration context) to generate optimization recommendations and fixes.
Common and uncommon optimization opportunities: compute sizing, storage tiering, database configuration, network paths like missing VPC endpoints, each turned into a Terraform-ready remediation.
Every plan is pre-verified before it's recommended. OptimizeSpot simulates eviction risk against your actual workloads, and every fix ships as reviewable code with a structured plan, so your team validates scope and confirms impact after rollout. No blind changes.
No. Jetscale is read-only in your cloud environment. It generates reviewable, fix-ready IaC your team merges and deploys through your existing workflow.
Self-funded. Jetscale charges a fee and verifies savings against your actual bill. If verified savings come in below the fee, we credit the difference. ROI is guaranteed.
A commitment broker lowers the rate you pay by buying reserved instances and savings plans for you. Jetscale lowers what you need to buy in the first place: right-sizing, storage, idle resources and network, across AWS, Azure and GCP. The two stack, and your commitments then cover a smaller baseline.
Autonomous optimizers change your environment for you, so they need write access and an agent or a role in your cloud. Jetscale stays read-only. It hands your team each change as code, with the evidence behind it, and nothing changes until your engineers merge it.
Get started
See your number before you spend a dollar.
Read-only connection. Evidence-backed findings. PR-ready fixes. Self-funded, with guaranteed ROI.