AI app for operations · no coding needed
Quality issue analyzer
Connects recurring symptoms to investigation evidence without inventing root causes.
Made for: Quality managers at small production businesses

What it does for you
The problem
Incident reports repeat problems without shared investigation context.
What it gives you
Quality investigation brief
What you give it
Quality reportsproduct batchescorrective actions
How it works, step by step
- Group related defects
- Preserve report details
- Compare batch context
- Flag recurrence
- Assign investigations
- Track corrective actions
What you see on screen
- Issue themes
- batch evidence
- investigation tracker
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 Quality issue analyzer 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 Quality issue analyzer 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 Cloudflare21 KB
- prompt-vps.mdThe same build on your own server (Docker)21 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria11 KB
- demo/index.htmlThe working demo on sample data198 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 quality managers at small production businesses, turn quality reports, product batches and corrective actions into quality investigation brief. Address the recurring problem: incident reports repeat problems without shared investigation context. The pilot measures confirmed patterns and repeated defects 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 quality reports, product batches and corrective actions and finish with quality 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
Make operational states and ownership explicit. Validate data and require appropriate approval before purchases, scheduling commitments or external system writes. 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 quality managers at small production businesses and one recurring use case. Build the first two modules: group related defects; preserve report details. Provide operator assistance for the third module: compare batch context. Deliver quality 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
Orders, inventory, supplier files, process documents and workflow records. 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 issue themes, followed by batch evidence and investigation tracker.





