Complete AI Training

AI app for pr and communications · no coding needed

Public data story explanation studio

Make verified findings understandable without overstating causality.

Made for: Public-interest organizations publishing datasets

What Public data story explanation studio looks like
Open the demo For members · a working demo with sample data

What it does for you

The problem

Useful data is released without explanations people can inspect.

What it gives you

Reviewed data explanation package

What you give it

Licensed aggregate dataanalyst-approved findings

How it works, step by step

  1. Generate source-linked narrative alternatives
  2. Build transparent calculation notes
  3. Produce editor-reviewed explainers
  4. Compare the reviewed result with the recorded baseline and value assumptions
  5. Capture corrections and named-owner approval before consequential use
  6. Export a versioned reviewed data explanation package with source references and unresolved questions

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 Public data story explanation studio 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 Public data story explanation studio 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 build3 KB
  • prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare27 KB
  • prompt-vps.mdThe same build on your own server (Docker)27 KB
  • spec.jsonData model, API, AI pipeline, acceptance criteria14 KB
  • demo/index.htmlThe working demo on sample data201 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

Make verified findings understandable without overstating causality

Confirm the buyer's problem and scope, collect licensed aggregate data and analyst-approved findings, then follow this sequence: 1. Generate source-linked narrative alternatives. 2. Build transparent calculation notes. 3. Produce editor-reviewed explainers. Resolve uncertain cases with qualified reviewers, approve reviewed data explanation package, and measure reader comprehension and editorial hours per accepted story against a documented baseline.

How the AI works

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the three stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. Analysts validate every numerical claim and chart. A model suggestion is never a verified fact, professional decision or authorization to act.

Safeguards

Verify public facts and quotations. Keep publication authority explicit and preserve the original context behind media and reputation findings. Analysts validate every numerical claim and chart. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.

What to build first

Pilot scope: Analysts validate every numerical claim and chart. Implement one approved input format, a bounded representative case set and the first two task modules: generate source-linked narrative alternatives; build transparent calculation notes. Support the third module with operator review: produce editor-reviewed explainers. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.

What it can connect to

Approved company facts, permitted media sources and publication workflows. Document storage, word processor export, content management systems and approved publishing channels. Pilot with uploads and downloadable drafts before adding write integrations. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.

The screens in detail

Primary screens: Source brief, Editable evidence-linked draft, Approval and publication preview. Use a project list and editorial calendar beside a document editor. Keep original material and supporting passages in a collapsible side panel. Show outline, draft, review and approved stages. Provide tracked edits, comments, version comparisons and an export preview that reflects the final delivery format. Make the task-specific outcome reviewed data explanation package visible beside its evidence, review state and value baseline.