Complete AI Training

AI app for it and development · no coding needed

Cloud spending analyst

Cost explanations linked to service ownership and operational events.

Made for: Engineering managers at small cloud software companies

What Cloud spending analyst looks like
Open the demo For members · a working demo with sample data

What it does for you

The problem

Unexpected infrastructure costs lack clear explanations.

What it gives you

Cloud cost investigation brief

What you give it

Billing exportsresource tagsdeployment history

How it works, step by step

  1. Normalize billing categories
  2. Detect changes
  3. Connect tagged services
  4. Compare deployment timing
  5. Flag idle candidates
  6. Document engineer findings

What you see on screen

  • Spend trends
  • resource evidence
  • investigation queue

Build it yourself with your AI system

Build this app yourself, no coding needed

Start with a quick version you can try in a few minutes. Like it? Then build the full app by copying and pasting our step-by-step instructions: everything is prepared for you.

Sign in to see how to build it yourself

Build a quick version to try, or get the full app pack for Cloud spending analyst with the step-by-step building instructions. You don't need any technical skills: you copy, paste and answer a few questions. Both are included in the membership.

Sign in Become a member

4 Have it built for you days to a few weeks

Rather not do it yourself, or want it fully tailored to your data, your way of working and your brand? Nexibeo builds Cloud spending analyst with you.

Have Nexibeo build it

What's in the app pack

Included in the Complete AI Training membership.

  • The building instructions your AI follows, step by step
  • The questions your AI will ask you about your business before it starts
  • A clickable demo you can open in your browser, to see how it should work
  • A detailed blueprint of the screens, the information it keeps and the checks it runs

Become a member to get the app packAlready a member? Sign in

The files, for the technically curious
  • START-HERE.mdHow to build it with your own AI (read first)3 KB
  • README.mdOverview and links1 KB
  • questions.mdQuestions to answer before you build2 KB
  • prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare21 KB
  • prompt-vps.mdThe same build on your own server (Docker)21 KB
  • spec.jsonData model, API, AI pipeline, acceptance criteria12 KB
  • demo/index.htmlThe working demo on sample data199 KB

Questions

Do I need to know how to code?

No. You copy and paste the prompts on this page into ChatGPT or Claude, and the AI does the building. When it asks you something, you answer in your own words.

What does it cost?

The quick version, the app pack and the step-by-step instructions are for members: you pay the membership price, not a price per app (see the plans). Building the full app uses your own ChatGPT or Claude subscription. Putting it online is often cheap or no cost at the start, and your AI tells you before anything costs money.

How long does it take?

The quick version: about two minutes. The real app: an afternoon for a first version you can use, longer if you want every feature.

Can I change it to fit my business?

Yes. Tell your AI what to change in plain words, like “add a column for the price” or “use our logo and colours”. Or have Nexibeo build and customise it for you.

More detailsHow the AI works, safeguards and what to build first

For engineering managers at small cloud software companies, turn billing exports, resource tags and deployment history into cloud cost investigation brief. Address the recurring problem: unexpected infrastructure costs lack clear explanations. The pilot measures reconciled costs and confirmed savings opportunities against the buyer's current method, before the larger build.

Agree definitions, import authorized data, validate coverage and identifiers, compute transparent measures, group relevant evidence, review findings, assign investigations or improvements, and repeat on a comparable period. Start with billing exports, resource tags and deployment history and finish with cloud cost investigation brief.

How the AI works

Classify text, summarize evidence and propose explanations to investigate. Compute financial or operational measures with deterministic code. Separate observed patterns from causal claims and preserve examples that contradict the summary.

Safeguards

Protect secrets, customer data and source code. Use controlled environments, technical review and a recoverable deployment process. Validate source access and reviewer availability during the pilot. Maintain customer-level access, data deletion controls and a record of final approvals.

What to build first

Begin with engineering managers at small cloud software companies and one recurring use case. Build the first two modules: normalize billing categories; detect changes. Provide operator assistance for the third module: connect tagged services. Deliver cloud cost investigation brief through a manual review queue. Perform other necessary full-scope functions manually during the pilot. Include all applicable access, accuracy and professional-review controls from the start.

What it can connect to

Authorized repositories, technical documentation, application APIs and logs. Read-only business data exports, reporting databases and task trackers. Reconcile source totals before scheduling recurring data refreshes. These are candidate integration categories, not verified supported connectors.

The screens in detail

Open with a compact overview and filters for the relevant period or segment. Let users drill from each theme or metric into underlying records. Keep source definitions and missing-data notes near the result. Use an action panel to assign investigations and record what was learned. In this product, the first view is spend trends, followed by resource evidence and investigation queue.