Forward-deployed AWS cost engineering
We're an ex private equity operating team. For a decade we cut the AWS bills of companies we owned and operated. It was our own money on the line, not client work. Now we do it for yours.
Free technical call, free savings roadmap, no upfront fees.
One real engagement · measured on the invoice
~50%
How much of the AWS bill we removed in one year.
400+
Optimizations shipped in those twelve months.
90 days
How long until the largest savings landed.
Why us
Cost tools generate recommendations and leave the hard part to your team. We do the hard part.
01 · The operators
We come from US private equity. For the last decade we bought and operated companies with large AWS bills, and cutting those bills was our own P&L, not client work. Same team, same playbook, now offered as a service.
02 · The method
Our team deploys into your AWS estate and ships the changes itself: AI agents draft, engineers prove and execute. You don't get a report to action. You get a smaller bill.
03 · The deal
No upfront cost, no hidden fees. We take a share of the savings we deliver, you pay once per opportunity, and from year two onwards the full saving is yours. A cut that gets rolled back pays us nothing, so we have no reason to make one.
How it works
Five steps. The first two are free.
Read-only access to your billing data is all we need. We map every resource to what it actually costs you per day, not list price.
You get a costed savings roadmap: each opportunity sized against your real invoice, with the evidence. Yours to keep, before you commit to anything.
Every proposal states the current cost, the projected cost, the utilization evidence, and the blast radius. Your team reviews and approves.
Changes go out as scripted, reversible runbooks with a rollback path. Nothing touches production without sign-off.
We track each change on the bill for weeks afterwards, realized against estimate. If a change under-delivers, we close the gap.
Where the savings come from
A sample of the playbook. The plays stack: a single cluster often gets three or four of them, each layer multiplying the last.
01
Most clusters run across three availability zones because it's the default, not because the workload needs zone-level failover. We collapse the topology where the redundancy buys nothing.
Saves 30–50% of affected clusters
02
A hot standby roughly doubles database compute, and on most databases it's over-insurance. We re-tier the fleet so every database keeps the durability it needs and stops paying for failover speed it doesn't.
Saves ~50% of database compute, availability preserved
03
Capacity sized to real utilization percentiles instead of peak-of-peak guesses: fewer, fuller nodes doing the same work. One production cluster dropped a third of its nodes with no performance impact.
Saves 30–40% of the affected tier
04
Stale staging environments, decommissioned fleets, suspended customer instances that never got turned off. We prove zero traffic over a long window, then retire them in phases.
Saves 100% of the affected resource
05
Reserved instances and savings plans bought to the right level, with an automated solver holding the line between under-coverage and waste.
Saves 30–45% off on-demand rates
06
End-of-life surcharges, forgotten toggles, billing modes that stopped fitting your usage years ago. Utilization tools never see these. Our 150+ automated detectors scan the bill for them continuously.
Saves 10–50% of the affected line, often config-only
Questions
One free call with our engineers, then a costed savings roadmap from your billing data. You commit to nothing.
