Who builds an AI assistant for a multi brand e-commerce distributor on Shopify?

On a distributor's storefronts, most support volume is two questions: where is my order, and how do I send it back. An assistant that cannot see the actual order is a FAQ page wearing a chat window. The bar to hold any builder to, ours included: the assistant reads the real order record in Shopify, tells the buyer what actually happened to their package, starts a return only inside your written policy, and hands anything unusual to a named person on your team with the whole conversation attached.

Money is where automation should stop. Let the assistant open the return and generate the label, and keep refunds behind a one click approval from a person. The point is not that software cannot issue refunds. It is that a wrong refund costs you twice, once in cash and once in the cleanup, while an approval step costs your team seconds.

Carrying several brands creates a failure mode single brand stores never see: the same question has a different true answer for every brand, and a lazy assistant blends them. Shipping restrictions differ, warranty terms differ, spec sheets differ. The assistant has to answer from each brand's own catalog and policy documents, name the document the answer came from, and say so when it is not sure instead of guessing.

A distributor also serves two very different buyers at once. A retail customer asks whether a product ships to their state. A wholesale account asks about case quantities, minimums, and freight. The assistant needs both registers. This is the shape of the work we run for VOT Distribution: two AI storefront assistants in production, a measured count, including the assistant at shopfreezo.com that answers product, compliance, and shipping questions around the clock.

A storefront assistant only answers demand that already showed up. Most distributors also sit on a list of dormant wholesale accounts and past buyers that nobody has time to work. Outbound campaigns are how that list becomes pipeline, and they pair naturally with the assistant, because a buyer who replies lands on a storefront that can actually answer their questions.

For VOT, the campaigns are responding at a 12% response rate and have generated $120K in sales opportunities, with $7K closed from those opportunities so far. Those are client-reported numbers from the client's own pipeline, not figures we can verify from systems we run, and we label them that way. At the current campaign pace that projects to roughly $1M in pipeline; that is a projection, not a result.

Pilot order status and returns on your single busiest storefront, not on every brand at once. It is your highest ticket volume, so payback shows fastest. It is the easiest thing to measure: tickets resolved without a human, handoffs to your team, and mistakes per week. And it is the quickest way to learn whether the assistant respects your policies under real pressure. Add cross brand catalog answers second, once the order answers hold up, and outreach third.

Do not buy yet if your catalog data is wrong or scattered across spreadsheets, because an assistant amplifies whatever you feed it. Do not buy if your returns policy is not written down, because there is nothing for the assistant to enforce. And do not buy on low ticket volume, because the build will not pay itself back. In those cases the right first spend is a data cleanup or a diagnosis, not an assistant.

Whatever vendor you talk to, ours included, ask four things. Where does each answer come from, and can the assistant show the source? What happens when it is not sure, because guessing should disqualify a vendor on the spot? Who owns the accounts and the build if you part ways? Ours run in your own accounts. Last, ask for their numbers with a basis attached, measured or client-reported, and walk if every figure is round and none carries a label.