Home / Results

Cloud cost optimization case studies

Every result below is measured against the client's own baseline and verified against billing data, then anonymized at the sector level. Our flagship engagement left a scaling fintech 41% lighter on its annual cloud run-rate, with no slip to its feature roadmap.

Flagship case

A scaling fintech, 41% lighter.

"They found $11M a year we'd written off as the cost of growth, and left us a team that keeps finding more."
VP of Platform Engineering
Series D fintech · 3 clouds

The fintech ran across AWS, Azure, and GCP with no single source of truth on cost. We built one normalized cost model on Datum, banked the no-regret wins first, then rearchitected the workloads driving the bill.

100%BEFORE59%AFTER−41%
41%
annual run-rate cut
$11M
recovered per year
11 wks
to break even on fee
0
feature roadmap slip
Portfolio

Results by sector and cloud.

Anonymized, sector-level engagements. Reductions are measured against each client's own baseline and verified against billing data.

Client (anonymized)CloudsPrimary leversReduction
Series D fintechAWS, Azure, GCPCommitment blend, rightsizing, data-transfer cleanup41%
Fortune 500 retailerAWSEDP renegotiation, Savings Plans coverage, storage tiering34%
European SaaS companyAzureReservations, Hybrid Benefit, Log Analytics caps29%
AI & ML platformGCP, OCICUD coverage, GPU capacity governance, BigQuery capacity pricing33%
Healthcare data providerOCIUniversal Credits sizing, Support Rewards, flexible compute shapes27%

// all figures verified against billing data and anonymized at the sector level

Repeatable

The same method every time.

Results like these are not luck. They come from a repeatable program: baseline the spend, ship the no-regret savings first, rearchitect the workloads that drive the bill alongside your engineers, then install the governance that keeps spend flat as you grow. Read the full approach in the method, phase by phase.

FAQ

People also ask.

Are these cloud cost optimization results real?
Yes. Every figure is measured against the client's own billing baseline and verified against billing data, then anonymized at the sector level so we never expose a client name. We do not publish numbers we cannot defend to a board.
What kind of reduction should we expect?
Typical programs cut spend by 20–40% through rightsizing, waste elimination, storage tiering, commitment coverage, and architecture decisions. Our portfolio median is a 31% reduction in the first 90 days. The flagship fintech reached 41%.
Do results depend on which cloud we run?
No. We work across AWS, Azure, GCP, and OCI and stay fully independent, so the plan follows your footprint and your forecast rather than any provider relationship.
How fast do savings appear?
We target the first measurable savings inside 90 days, starting with no-regret waste in the first weeks. The flagship fintech broke even on our fee in 11 weeks.
Your number, not someone else's

See your own number, not someone else's.

Send us your footprint and we will scope the savings against your billing data. Under our guarantee, we reduce your cloud spend or we reimburse our service fee.