AI app for operations · no coding needed
Mall Trip Companion Agent
An agent that reads live store promotions and acts on the shopper's behalf inside the physical trip, which no map, app or loyalty card does today.
Made for: Marketing and operations leads at mid-sized shopping centres
What it does for you
The problem
Loyalty cards sit unused in wallets, shoppers forget errands and miss live promotions, and centres lose footfall to online retail.
What it gives you
Personalised shopping route with timed reminders, automatic discount application at checkout, trip receipts with total savings, and centre footfall, dwell and redemption dashboards
What you give it
Centre floor planstore directorystore inventoriesactive promotionsloyalty programme termsshopper voice noteslocation pings during trips
How it works, step by step
- Capture spoken errand lists and convert them to structured stops
- Build an efficient walking route across centre stores
- Read live store promotions, PDFs and images as they change
- Vibrate or notify at each stop, including errands like dry cleaning passed en route
- Apply eligible discounts and loyalty credits automatically at checkout
- Feed anonymised footfall and basket insights back to centre management
What you see on screen
- Errand capture
- route map
- promotion wallet
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 Mall Trip Companion Agent 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 Mall Trip Companion Agent 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 criteria12 KB
- demo/index.htmlThe working demo on sample data194 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 marketing and operations leads at mid-sized shopping centres, turn shopper voice notes, centre maps, store inventories and active promotions into a personalised shopping route, timed stop reminders and automatic discount application at checkout. Address the recurring problem: loyalty cards sit unused, shoppers forget errands and miss live promotions, and centres lose footfall to online retail. The value hypothesis is measurable gains in footfall, basket size and shopper data; the pilot must establish whether that benefit is real.
Tap the card or app to start a trip, speak the errand list, match stops against inventories and promotions, review the suggested route, walk the route with timed reminders, check out with automatic discount application, and close the trip with a receipt and insights record. Start with spoken errand lists, centre map data, store inventories and active promotions and finish with a completed route, redeemed savings report and centre footfall insights.
How the AI works
Use speech models to transcribe errand notes, language models to extract structured stops, document and image models to read promotions as they are published, and routing logic to sequence stops by location and opening hours. Deterministic checks confirm store locations, opening times and discount rules before anything is applied. A centre-side administrator reviews promotion matches and redemption rules before they go live, and no discount is charged without a valid store-authored promotion on file.
Safeguards
Location tracking is opt in and trips can be deleted by the shopper. Discount application is limited to store-authored promotions with valid terms and an approval record, and never changes prices without a confirmed integration. The system must not share individual shopper identities with stores, must not apply expired or unauthorised promotions, must not route shoppers to closed stores, and centre dashboards only expose aggregated anonymised data.
What to build first
One mid-sized shopping centre with 50 or more stores, one use case: speak an errand list and receive a fastest route across those stores on a static centre map. First two modules are voice capture with stop extraction and the route map with ordered reminders. Every promotion suggestion is manually reviewed by the centre team before shoppers see it.
What it can connect to
Start with a static centre map and store directory supplied as spreadsheets, then add point of sale and loyalty systems for discount application, store promotion feeds or PDF drops, and location services on the shopper's phone.
The screens in detail
Use a voice-first capture screen where shoppers speak their errands for the day, a central map of the centre with the fastest ordered route and live store pins, and a wallet showing applied deals, loyalty credits and dry cleaning reminders. Let shoppers reorder stops and see a vibration cue on each arrival. Display planned, in progress and completed trips. Provide a centre-side dashboard with footfall, dwell time and redemption data. In this product, the first view is errand capture, followed by route map and promotion wallet.
