We review your Cloud + AI spend, find the biggest savings opportunities, and explain what to change.
Get in touchFor scale-ups whose AI features are already live:
Now the cloud bill and the model invoices climb every month, and nobody can say which feature drives which cost.
Or usage is about to scale, and you want the unit economics right before the volume arrives.
Nothing is broken, yet nobody on the team owns the full picture of spend.
That's why we built GoodInfra.
GoodInfra reviews your cloud and AI spend, sizes every saving and ranks it by effort, then walks your team through the plan.
Pricing starts from £2995, fixed before work begins, and the report lands within 7 days of the agreed access.
Get in touchBefore work starts
Every review starts with your bills. Once your enquiry arrives, we agree in writing which cloud accounts, model providers and billing exports are in scope, and how access will work.
You get a straight answer on fit, including whether your spend level makes the review worthwhile.
7 days from access
Once read-only access or the agreed exports arrive, the clock starts. We trace cloud and AI spend back to the services, models and features that drive it, then size every opportunity to reduce it.
Each finding carries its calculation, assumptions, limits, effort, risk and confidence.
After delivery
Then we make it usable. An optional session takes your team through the savings plan, ranked by size and effort, and tests each change against what you know about the product.
Implementation stays with your team. If you want hands-on help, it is scoped separately.
In a week, GoodInfra traced our cloud and model spend back to the features behind it and surfaced costs we had been carrying for months. We came away with the clarity, direction and a practical savings plan to act on straight away.
GoodInfra got to grips with our AI stack quickly and pinpointed exactly where tokens and GPU hours were going to waste. Every recommendation came with its working shown, so our team acted on it with confidence. Approachable, proactive and easy to recommend.
Four areas, examined against your own billing data and usage exports, across your cloud platform and model providers.
Area 01
Where the cloud bill goes, and which line items your usage data says you can cut.
Area 02
What each AI feature costs per request, and where tokens are spent for no return.
Area 03
Self-hosted and managed model serving, matched to the load it actually carries.
Area 04
Who sees spend, who owns it, and how fast a spike gets noticed.
Start here
from£2995fixed fee
An independent review of your cloud and LLM/AI infrastructure spend, built for teams spending £5k or more a month across both.
Support assistant resends the full conversation history with every model call
Managed database provisioned above observed peak utilisation
Straight answers before you get in touch.
One engineer carries out the whole review, from your first enquiry to the final report. The fee, scope and deadline are fixed and written down before work begins.
Cloud and AI spend are reviewed together, because once AI features are live, the two bills move together.
CTOs, heads of engineering and technical founders at scale-ups and funded startups, roughly 20 to 150 people, with AI features live in production.
It is built for combined cloud and AI spend of £5k a month or more.
Below that level, the fixed fee becomes a large share of any saving the review can find.
Our reply to your enquiry will say so plainly, and point you to the free provider tools worth using instead.
The review works with the major cloud platforms and model providers. Tell us your stack on the enquiry form, and our reply will confirm whether it's a good fit, or say so plainly if it isn't.
Fit depends on your setup, so there's no obligation either way.
Read-only billing and usage access, or exports you produce yourself: your cloud billing export, model provider usage reports and, where relevant, a resource inventory.
Nothing in your environment is changed. Prompt content is reviewed only where you choose to share samples.
Every finding states its risk to quality, latency or reliability next to the saving.
Model and prompt changes are flagged for testing against your own evaluations before rollout, and no change is recommended without that trade-off written down.
A completed enquiry form, the time it takes to grant read-only access or produce exports, occasional questions answered by one named contact, and an optional walkthrough.
Your engineers keep shipping while the review runs.
No savings figure is guaranteed. Each estimate shows its calculation, assumptions and limits, so you can check the arithmetic yourself.
Any saving depends on the changes your team chooses to make.
The recommendations are written for your own engineers to carry out.
If you want hands-on help with any of them, that can be scoped as separate work, with no obligation either way.