AI app for it and development · no coding needed
Technical support diagnostic tool
Product-version context and evidence excerpts accompany every diagnostic suggestion.
Made for: Support engineering teams at infrastructure vendors
What it does for you
The problem
Large log files obscure the events relevant to a customer issue.
What it gives you
Evidence-linked diagnostic investigation brief
What you give it
Authorized logsknown error patternsproduct versions
How it works, step by step
- Parse log structure
- Redact secrets
- Group related errors
- Match known issues
- Suggest investigation steps
- Package engineering handoffs
What you see on screen
- Log timeline
- evidence excerpts
- investigation steps
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 Technical support diagnostic tool 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 Technical support diagnostic tool 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 build3 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 criteria15 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 support engineering teams at infrastructure vendors, turn authorized logs, known error patterns and product versions into evidence-linked diagnostic investigation brief. Address the recurring problem: large log files obscure the events relevant to a customer issue. The pilot measures useful suggestions and unsupported diagnoses 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 authorized logs, known error patterns and product versions and finish with evidence-linked diagnostic 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 support engineering teams at infrastructure vendors and one recurring use case. Build the first two modules: parse log structure; redact secrets. Provide operator assistance for the third module: group related errors. Deliver evidence-linked diagnostic 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 log timeline, followed by evidence excerpts and investigation steps.
