AI app for human resources · no coding needed
Workplace investigation evidence index
Organize evidence without judging credibility or guilt.
Made for: Independent HR investigation consultants

What it does for you
The problem
Interview records and documents are difficult to reference consistently.
What it gives you
Confidential investigation evidence index
What you give it
Authorized evidenceinvestigator-defined issue labels
How it works, step by step
- Register source files
- Deduplicate copies
- Link investigator labels
- Preserve original wording
- Track access history
- Export reference index
What you see on screen
- Evidence vault
- Issue index
- Provenance timeline
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 Workplace investigation evidence index 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 Workplace investigation evidence index 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 Cloudflare22 KB
- prompt-vps.mdThe same build on your own server (Docker)22 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria11 KB
- demo/index.htmlThe working demo on sample data195 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 independent HR investigation consultants, turn authorized evidence and investigator-defined issue labels into confidential investigation evidence index. Address this specific problem: interview records and documents are difficult to reference consistently. The aim: organize evidence without judging credibility or guilt. The pilot tests whether that benefit holds up against reviewer effort and real operating costs.
The buyer creates a project, supplies authorized evidence and investigator-defined issue labels, and confirms scope and access. Users correct extracted facts, resolve flagged uncertainties and approve the final confidential investigation evidence index before use. Retain source links and a version history for the next cycle.
How the AI works
Suggest topics with citations for investigator confirmation. 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. Indexing only; no credibility scoring or findings. 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: Indexing only; no credibility scoring or findings. Start with one buyer organization and a bounded set of representative inputs. Implement the first two modules: register source files; deduplicate copies. Support the third task through an assisted review queue: link investigator labels. Handle the remaining required functions manually until validated. Include input upload, source references, user correction, a reviewer approval step and export of confidential investigation evidence index. 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. Source systems, catalog exports and cloud file storage. Start with reversible CSV or file imports and validate identifiers before any direct writes. Begin with uploads and exports of authorized evidence and investigator-defined issue labels. 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 searchable table or visual gallery with filters for the domain’s important attributes. Open each item into a detail drawer containing source records, ownership and history. Put proposed merges and field changes in a separate review queue. Provide a preview before any bulk export. Open with evidence vault; move into issue index for the detailed task; finish in provenance timeline for review and handoff. Show the source record, uncertainty and approval status beside each proposed output.





