AI app for human resources · no coding needed
Pay transparency explanation studio
Explain compensation policy without inventing individual pay advice.
Made for: Compensation communication teams

What it does for you
The problem
Employees cannot understand approved pay frameworks.
What it gives you
HR-approved pay framework guide
What you give it
Approved pay bandscompensation principles
How it works, step by step
- Extract published principles
- Draft role-level explanations
- Flag inconsistent wording
- Build question guides
- Track approvals
- Export communication packs
What you see on screen
- Framework map
- Explanation draft
- HR review
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 Pay transparency 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.
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 Pay transparency explanation studio with you.
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 Cloudflare24 KB
- prompt-vps.mdThe same build on your own server (Docker)24 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria13 KB
- demo/index.htmlThe working demo on sample data200 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 compensation communication teams, turn approved pay bands and compensation principles into HR-approved pay framework guide. Address this specific problem: employees cannot understand approved pay frameworks. The aim: explain compensation policy without inventing individual pay advice. The pilot tests whether that benefit holds up against reviewer effort and real operating costs.
The buyer creates a project, supplies approved pay bands and compensation principles, and confirms scope and access. Users correct extracted facts, resolve flagged uncertainties and approve the final HR-approved pay framework guide before use. Retain source links and a version history for the next cycle.
How the AI works
Draft explanations strictly from approved principles. Keep model suggestions separate from verified facts. Link factual outputs to authorized input evidence and show missing information explicitly. Use deterministic checks for counts, dates, identifiers and arithmetic where applicable. A designated reviewer validates consequential outputs and signs off the delivered result.
Safeguards
Keep employee data access explicit and confidential. Use human judgment for personnel decisions and do not infer protected traits or hidden personal characteristics. Policy communication; no salary-setting or legal compliance verdict. Require appropriate access and publication approval. Preserve source material, label AI drafts and make corrections traceable. Measure false positives and missed cases alongside speed.
What to build first
Costed pilot: Policy communication; no salary-setting or legal compliance verdict. Start with one buyer organization and a bounded set of representative inputs. Implement the first two modules: extract published principles; draft role-level explanations. Support the third task through an assisted review queue: flag inconsistent wording. Handle the remaining required functions manually until validated. Include input upload, source references, user correction, a reviewer approval step and export of HR-approved pay framework guide. Authentication, account isolation, deletion controls and basic operational logging are included. Specialized production certification, live write integrations and broader rollout are not included unless explicitly stated.
What it can connect to
Approved HR documents, employee directories and learning records. Document storage, word processor export, content management systems and approved publishing channels. Pilot with uploads and downloadable drafts before adding write integrations. Begin with uploads and exports of approved pay bands and compensation principles. Any named system or connector is a candidate requiring current access and compatibility checks; no live connection is included by default.
The screens in detail
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. Open with framework map; move into explanation draft for the detailed task; finish in HR review for review and handoff. Show the source record, uncertainty and approval status beside each proposed output.





