AI app for government · no coding needed
Public facility accessibility inventory
Public accessibility information linked to dated inspection evidence.
Made for: Municipal facility managers

What it does for you
The problem
Accessibility information is inconsistent across facility listings.
What it gives you
Reviewed facility accessibility directory
What you give it
Verified facility auditsapproved public descriptions
How it works, step by step
- Extract observed features
- Normalize descriptions
- Flag unverified claims
- Track audit dates
- Draft public summaries
- Export verified listings
What you see on screen
- Facility catalog
- Evidence gaps
- Listing preview
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 Public facility accessibility inventory 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 Public facility accessibility inventory 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 criteria12 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 municipal facility managers, turn verified facility audits and approved public descriptions into reviewed facility accessibility directory. Address this specific problem: accessibility information is inconsistent across facility listings. The aim: public accessibility information linked to dated inspection evidence. The pilot tests whether that benefit holds up against reviewer effort and real operating costs.
The buyer creates a project, supplies verified facility audits and approved public descriptions, and confirms scope and access. Users correct extracted facts, resolve flagged uncertainties and approve the final reviewed facility accessibility directory before use. Retain source links and a version history for the next cycle.
How the AI works
Summarize audited features without inferring accessibility from photos. 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
Preserve official source versions, accessibility and audit records. Confirm agency-specific procurement, records and data handling requirements during discovery. Existing inspection evidence only; no compliance certification. 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: Existing inspection evidence only; no compliance certification. Start with one buyer organization and a bounded set of representative inputs. Implement the first two modules: extract observed features; normalize descriptions. Support the third task through an assisted review queue: flag unverified claims. Handle the remaining required functions manually until validated. Include input upload, source references, user correction, a reviewer approval step and export of reviewed facility accessibility directory. 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
Official publications, agency document stores and approved service workflows. 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 verified facility audits and approved public descriptions. 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 facility catalog; move into evidence gaps for the detailed task; finish in listing preview for review and handoff. Show the source record, uncertainty and approval status beside each proposed output.





