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We optimize your cloud bill or you don't pay.

Hands-on optimization across your entire stack, done by us, in your repos, following your process. We take a share of what we actually save you: no retainer, no day rate, no audit fee.

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We work with teams spending $100k+/month (or $1M+/year) on cloud. AWS is our core; Azure and GCP through our specialist network.

You already know the bill is too high.

The hard part is who does something about it.

You have to find someone.

Cloud cost work needs current pricing knowledge across a dozen services, and the patience to go volume by volume, instance by instance, log group by log group. Very few engineers have that, and the ones who do are usually the ones you least want to pull off the roadmap.

You have to train them, and then keep them.

AWS pricing and service options change every quarter, so whatever your team learned last year is already partly stale and the internal doc that captured it was never updated. Worse, that knowledge lives in one person's head. When they leave, it leaves, and you start again.

And when it is done, nobody wants to do it again.

Cost work lands as a one-off project, gets celebrated, then decays. Six months later the bill is back where it started and the same conversation begins again, except now the team is tired of it.

Meanwhile every hour spent on this is an hour not spent on the product your customers actually pay for, and every hour you wait is another hour of overspending you never get back.

Why not just do it yourselves?

You could do all of this in-house. Some teams do, and it works, if cloud cost is the most valuable thing that engineer could be doing this quarter.

We have spent more than 10 years doing cloud optimization. Keeping current with every pricing and service change is our job, not a side quest for your team.

Four ways to fix this. One of them is free if it fails.

Do it yourselves

Who does the work
Your engineers
What you pay
Salary plus the roadmap you did not ship
If nothing gets saved
You still paid the salaries
Incentive to keep digging
Competes with every other priority
Coverage
Whatever the team gets round to
The long tail of small wins
Never worth an engineer's day
Speed to first saving
Weeks to quarters
Knowledge after it ends
Leaves with the engineer

Consultant on a day rate

Who does the work
Consultant advises, your engineers implement
What you pay
Day rate, outcome or not
If nothing gets saved
You still pay the invoice
Incentive to keep digging
Hours are the product
Coverage
Whatever is in the statement of work
The long tail of small wins
Never worth billing a day for
Speed to first saving
Weeks
Knowledge after it ends
Leaves with the consultant

FinOps SaaS tool

Who does the work
Your engineers, guided by a dashboard
What you pay
Subscription, outcome or not
If nothing gets saved
You still pay the subscription
Incentive to keep digging
None after signature
Coverage
Whatever the tool detects
The long tail of small wins
Flagged, then buried in a backlog
Speed to first saving
Weeks after rollout and triage
Knowledge after it ends
Rented, as long as you keep paying

LeanerCloud

Who does the work
We do it, in your repos, in your process
What you pay
A share of savings we actually delivered
If nothing gets saved
You pay nothing
Incentive to keep digging
Direct: more savings, more revenue for us
Coverage
Everything we can find, including the small stuff
The long tail of small wins
Automated, so a $200/month win still pays
Speed to first saving
Days
Knowledge after it ends
Savings live in your infrastructure, tooling is self-hosted and yours

The trade-offs the table cannot show

  • Hourly: you carry all the outcome risk, scope is fixed before anyone knows where the money is, small wins get skipped, and you end up managing the consultant.
  • SaaS tool: it reports more than it fixes, so your engineers still do the work. Any automation does not know your application, so it stays generic or limited and still needs their attention. You pay whether or not anything ships, and your whole footprint lives on someone else's backend.
  • Us, stated honestly: we are a small, senior team and can only take on a few clients a year, above $100k/month, so we are not a fit for everyone. And since we are paid on results, our share grows the more we save you, capped if you prefer.

How we work

We make low-risk, reversible changes in your repos and ship them through your own review and rollout process.

  1. 1

    Read-only access

    You grant scoped, read-only access. No standing admin, minimal IAM.

  2. 2

    Audit and prioritised list

    Every finding, what it saves per month, and how risky it is. Yours to keep whether or not you continue.

  3. 3

    First changes in your repo

    We open pull requests in your repositories, usually within days of getting access. They follow your process, stay low risk and reversible, and rarely require major architecture changes.

  4. 4

    First measured savings

    Changes land and the effect shows up on your bill in the same billing period.

  5. 5

    Monthly report

    What landed, what it saved, measured per change against the bill before it, and what is next.

We work with your security and procurement process: everyone who touches your account is under NDA, and we are happy to sign your MSA and DPA, complete your security reviews, and provide references under NDA. Billing is automated from your before-and-after cost data, so what you pay always ties back to the real bill.

Anyone can buy a Savings Plan

Buying commitments is an easy win, an afternoon of work, but they only ever cover part of the bill. Storage, logging and networking are not covered by any Savings Plan or Reserved Instance, so they only get cheaper when someone actually optimizes them.

So before we get anywhere near a Reserved Instance, we go through the whole stack and leave nothing unturned.

Compute

Spot, Graviton, right-sizing, autoscaling, and idle or oversized non-production.

Storage and databases

EBS types and IOPS, snapshots, S3 classes and lifecycle, Aurora I/O mode, oversized replicas.

Logging and networking

Log retention and volume, NAT and cross-AZ transfer, VPC endpoints.

Commitments

RIs and Savings Plans sized to your optimized footprint, plus EDP and private pricing.

The point is to commit to what you will actually run, not to what you happen to run today. Commit blindly up front and you lock in a year of paying for resources we may have removed.

The money is not in one big line item. It is in two hundred small ones.

Most of what we find is small. A few hundred dollars a month each, low risk, with no migration project or major architecture change. Individually, none of them justify pulling an engineer off the roadmap for half a day to research, execute and verify.

That is exactly why they never get done. Not because your team is not good enough, but because the arithmetic does not work for them.

It works for us, because we automated it.

We have spent years building and battle-testing tooling across multiple engagements. Detection, safety checks, execution and measurement are already automated end to end for most of the scenarios we run into. What costs your engineer half a day costs us minutes.

40 small optimizations, averaging $250 a month each.
Individually: not worth a half day of engineering time.
Together: $10,000 a month. $120,000 a year.
Manually, at half a day each: 20 engineering days, spread across people who have other jobs.
For us: a few days, mostly automated, and you pay only out of what it saves.

The long tail of small savingsA few large savings on the left, and a wide band of many small savings on the right whose combined area is larger.Headline winsThe long tail (bigger in total)
Illustrative: the small wins add up to more than the headline items.

Why we do not bill by the hour

A day rate pays for effort. We are paid for outcomes, so we only make money when you save money.

That is not a fairness slogan. A vendor paid a subscription is done when you sign. A consultant paid by the day is done when the days run out. We are done when there is nothing profitable left to find.

Our Engagement Models

We take a share of the savings, typically 5% to 30% depending on your size (larger footprints pay a lower share), for the first year after each change lands, invoiced monthly and measured automatically from your before-and-after billing data, per change against the bill before it. We can also bill through AWS Marketplace, and will agree a cap if you want one. It typically costs less than a FinOps SaaS subscription. We work with teams spending $100k+/month on cloud.

Done with You

We work side by side with your team to optimize your cloud costs together

  • We show your team what we do and help them adopt an efficiency mindset
  • Your team participates in implementation decisions
  • Your team keeps the knowledge behind each optimization
  • Changes follow your existing review and rollout process
Book a call
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Done for You

We offload as much as possible of the hands-on optimization work

  • The hands-on work happens in your repos
  • We handle the audit, implementation and measurement
  • Your engineers review changes instead of researching them
  • Monthly reports show what landed, what it saved and what is next
Book a call

Do it Yourself

Our cost savings automation software saves you money while you sleep

  • Start saving in minutes for certain AWS resources
  • Minimal effort and no config changes
  • We help you get started if needed
  • Billed through the AWS Marketplace
Get Started Now

What this looks like on your P&L

The bill is the wrong number to manage. What matters is what your infrastructure costs per customer, per transaction, per gigabyte processed, per seat.

We report savings that way wherever you can share the denominator: infrastructure cost per active user before and after, cloud cost as a percentage of revenue, gross margin impact.

A 30% reduction in run rate on a $200,000 a month bill is not an infrastructure result, it is two points of gross margin. For fast-growing teams the absolute bill may still rise, while the cost per unit falls and growth stays sustainable.

Results

Anonymised by industry and spend band. Every number measured against the bill before the change.

FinTech scale-up, US

$1.1M+/yr

delivered cost avoidance

~$3M/year AWS under an EDP. Decommissioned unused databases, IO1 to GP3, right-configured Aurora, RIs, ElastiCache to Valkey and more. Engagement ongoing.

E-commerce SaaS, US

~30%

off the bill, ~$178k/yr

A bill growing with the business, from $30k to $50k/month. Cut to $36k/month in 3-4 months across RDS, compute, ElastiCache, S3 and EBS.

Marketing/compliance SaaS, US

$300k/yr

identified in an audit

~$1M/year AWS. A prioritised list across S3, RDS, ECS+Spot, EBS and CloudWatch Logs, for the team to implement at their own pace.

Every engagement is under NDA, so client names and identifying details are anonymised; references are available under NDA. More detail on the case studies page.

The automation that makes this economical

We have a broad set of tools that cover most common use cases. Some automate an optimization end to end and are available on the AWS Marketplace; we use the others ourselves in client engagements.

AutoSpotting

Makes it a breeze to safely adopt Spot instances in AutoScaling groups: no configuration changes, automated instance type diversification with a bias for newer instance types, and failover to on-demand.

  • Up to 90% savings on auto-pilot
  • Install in minutes from CloudFormation or Terraform
  • Tag-based control - no resource reconfiguration
  • Self-hosted and privacy-focused: no SaaS backend
Read more about AutoSpotting

EBS Optimizer

Converts EBS volumes attached to your EC2 instances to the most suitable volume type, for lower costs with often better and more predictable performance.

  • GP2 to GP3 conversions for ~20% lower cost
  • Better and more predictable performance
  • Minimal IAM permissions and serverless design
  • Priced fairly as a small share of the savings
Read more about EBS Optimizer

About LeanerCloud

LeanerCloud is led by Cristian Magherusan-Stanciu, who founded it in 2022 after years at AWS, most recently as a Specialist Solutions Architect for Spot and Graviton. He runs every engagement himself, and brings in a handpicked network of freelance specialists, with decades of combined AWS experience, whenever the work calls for it.

We aim to offer the deepest and most comprehensive cloud optimization services on the market, at fair, customer-obsessed prices. AWS is our core, and we cover Azure and GCP through specialists in our network. We're always open to talented cloud professionals interested in joining us.

Cristian Magherusan-Stanciu

Cristian Magherusan-Stanciu

Cloud Optimization Specialist

We often share insights and learnings through our podcast and YouTube channel.

Frequently Asked Questions

Common questions about working with LeanerCloud

Still have questions?

Book a free savings audit or email us and we will get back to you.