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Cut the cloud bill without slowing a single release.

Tagging, rightsizing, commitments and GPU governance, plus the habits that stop the waste coming back.

Let's Build Together

One call with a senior engineer. A straight answer on what it would take.

Illustration: FinOps & cloud cost optimization

Where you are. Where you’ll be.

You need this if

  • Your cloud bill grows faster than revenue
  • Nobody can explain last month's spike
  • AI experiments are running on GPUs nobody remembers starting

What changes for your business

  • Immediate savings from waste found in the first weeks
  • Cost per customer, product or AI feature you can actually see
  • GPU and inference spend governed before it scales

What we hand over

  1. Cost allocation and tagging strategy
  2. Rightsizing, scheduling and commitment optimization
  3. GPU and AI inference cost governance
  4. FinOps operating model, dashboards and team training

What it is

FinOps is the operating practice that makes engineering, finance and product teams jointly accountable for cloud spend. It combines visibility of who spends what, budgets and forecasts, and continuous optimization, now including GPU and AI inference costs. The aim is spending that tracks value, not one-off cuts.

Most cost-cutting is a one-off sprint that decays within two quarters. We do the quick wins first (idle resources, oversized instances, missing commitments, orphaned storage) then install the system: cost allocation every team can see, budgets with alerts, unit economics per product or customer, and governance for GPU and inference spend. Engineering keeps its speed. Finance gets a forecast it can trust.

Why now
29% of IaaS and PaaS spend is wasted, the first rise in five years. Flexera State of the Cloud, 2026 (opens in a new tab)
Last reviewed

How it runs

  1. 01

    Diagnose

    Typically 2–4 weeks

    We map the problem, your data and your systems, and agree the one number that defines success.

  2. 02

    Prove

    Typically 4–8 weeks

    A working pilot on your real data, measured against that number. Not a slide demo.

  3. 03

    Ship

    Scoped to the outcome

    Production build with security, monitoring, cost controls and documentation included, not upsold.

  4. 04

    Run

    Ongoing, optional

    We operate what we built against clear service levels, or train your team to. Your call. No lock-in.

Questions you’ll ask

How much can we expect to save?
It depends on the estate, and we won't promise a percentage before looking. Flexera estimates 29% of IaaS and PaaS spend is wasted across the market. The diagnostic gives you your own number, itemized, before you commit to anything.
Why do cost-cutting projects lose their savings?
Because a one-off cleanup doesn't change how spend is created. Without allocation, budgets, alerts and owners, waste returns within a couple of quarters. The quick wins pay for the engagement; the operating system keeps the savings.
Can you control GPU and AI inference costs?
Yes. GPU clusters left running, oversized models and unmetered inference are the fastest-growing source of waste. We tag AI workloads, set budgets per use case, schedule idle capacity off and measure cost per task or per query.

Sound familiar? Let’s fix it.

One call with a senior engineer. You’ll leave with a straight answer on what it would take.

Let's Build Together

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