A bot that doesn't make things up: how AI works on your catalog
The biggest fear store owners have about AI bots: “what if it tells my customers nonsense?”. It's a fair one — a bare language model can invent a price, a promotion and a returns policy. That's why a store bot is built differently. Here's how, without jargon.
How the bot knows what's in your store
A store bot doesn't answer “from memory”. Before it replies, it's handed an extract from your catalog: products matching the question, their prices, variants and stock, plus your delivery and returns rules. The language model is there to understand the question and phrase the answer — but the facts come from store data, not the internet.
The catalog reaches the bot from what you already have: your platform's API (Woo, Shopify, Presta), a product feed or a file. And it's synced — a price change in the store is a price change in the bot's answers.
What happens when the bot doesn't know
This is the real test of deployment quality. A well-configured bot is forbidden to guess: if the answer isn't in the catalog or the rules, it says “I don't have that information”, offers contact and collects details. A badly configured one wades in — because language models by nature prefer answering something over admitting ignorance.
When evaluating a vendor, ask for a demo of exactly this scenario: ask a question outside the catalog and watch what happens. Five minutes that tell you more than the whole sales deck.
Why a bot needs looking after
Even a well-built bot isn't “set and forget”. A store lives: products arrive, promotions change, customers start asking about things that didn't exist yesterday. Someone has to read conversations regularly, patch the bot's knowledge gaps and fix weak answers.
That's the real cost of owning a bot — and the main reason we manage bots for our clients instead of handing over a panel full of sliders. Answer quality after three months depends not on the AI model, but on whether anyone is minding it.
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