AI app for customer support · no coding needed
Technical troubleshooting assistant
Model-aware diagnostic sequences with explicit stopping conditions.
Made for: Service managers at connected appliance brands
What it does for you
The problem
Customers abandon complex diagnostic instructions.
What it gives you
Diagnostic record and repair referral summary
What you give it
Model manualsapproved diagnostic treesfault codes
How it works, step by step
- Identify device models
- Interpret approved error codes
- Branch diagnostic steps
- Record attempted actions
- Stop unsafe sequences
- Prepare repair handoffs
What you see on screen
- Diagnostic chat
- device context
- service handoff
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 troubleshooting assistant 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 troubleshooting assistant 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 data196 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 service managers at connected appliance brands, turn model manuals, approved diagnostic trees and fault codes into diagnostic record and repair referral summary. Address the recurring problem: customers abandon complex diagnostic instructions. The pilot measures safe resolution rate and unnecessary repeat steps against the buyer's current method, before the larger build.
Add an approved collection, assign source owners and access rules, test representative questions, let users ask questions, retrieve supporting passages, answer or request clarification, and hand off unresolved cases with their context. Start with model manuals, approved diagnostic trees and fault codes and finish with diagnostic record and repair referral summary.
How the AI works
Retrieve permitted passages and generate answers constrained to those sources. Use structured rules for transactional facts. Detect missing context and refuse to invent unsupported details. Store reviewer corrections for evaluation and controlled knowledge updates.
Safeguards
Keep customer account access scoped. Escalate missing evidence and consequential exceptions to staff. Review quality alongside any speed measure. 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 service managers at connected appliance brands and one recurring use case. Build the first two modules: identify device models; interpret approved error codes. Provide operator assistance for the third module: branch diagnostic steps. Deliver diagnostic record and repair referral summary 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
Support inboxes, help centers, order records and customer feedback systems. Approved knowledge repositories, websites, service desks and staff messaging systems. Validate access inheritance and use read-only ingestion for the initial deployment. These are candidate integration categories, not verified supported connectors.
The screens in detail
Give end users a simple search or conversation surface with short answers and expandable citations. Administrators get source status, unanswered questions and handoff queues. Show the source date beside relevant answers. Keep conversation context available to the staff member receiving an escalation. In this product, the first view is diagnostic chat, followed by device context and service handoff.
