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Case study · AI applied to ecommerce

An assistant that sells with real data

AI shopping chat grounded in a real store's catalog: it answers about ingredients, allergens and budgets — without making anything up.

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The problem it solves

90% of online store chatbots frustrate users: generic answers, made-up information, or a menu of options disguised as conversation. The challenge isn't adding AI — it's making it answer only with the catalog's truth.

This assistant is connected to the real data of the performance case study's store: every ingredient, price, rating and description. When a fact isn't in the data, it says so and refers to the store's contact.

Real conversation

Which turrón has no egg?
The Milk Chocolate Turrón with Almonds contains no egg among its ingredients (40% almond, milk powder, sugar, cocoa butter…). Note: it may contain traces of tree nuts.
A gift under €35
I'd recommend the "La Terreta" 3-turrón artisan pack at €30.91 — it comes gift-wrapped. Prefer individual bars? Jijona (€10.45) + Alicante (€11.00) + Chocolate (€11.55) = €33.00 total.

What it can do

  • Allergens and ingredients quoted literally from the catalog — nothing invented
  • Budget recommendations with the math done right
  • When a fact isn't in the data, it admits it and refers to the store contact
  • Politely declines any topic unrelated to the store
  • Replies in the customer's language

How it's built

  • Full catalog injected as model context — single source of truth
  • Server-side proxy: the API key never reaches the browser
  • Model fallback chain: if one fails or saturates, the next takes over
  • Per-session and per-request abuse limits
  • Swappable AI provider (Gemini, Claude, OpenAI) by touching one file
  • Performance cost: +2 KB — the store keeps its 96/100 mobile score

Want this in your store?

This same pattern works with any catalog: products, services, pricing or documentation. If your store — or your clients' — needs support that sells without making things up, let's talk.

Let's talk