[ multi-agent support ai for ecommerce ]
Help more shoppers without adding extra agents
AI agents for ecommerce handle order tracking, returns and more, instantly. Free up your team, reduce tickets, and support more shoppers without extra effort.
[ 01 of 04 ] · retail's big moments
Support shoppers through every occasion
The drop
A new collection lands and the inbox spikes with sizing, shipping and stock questions. Algomo answers every conversation at once, from live stock, and chat is unlimited, so the surge never raises the bill.
The sizing doubt
A shopper hesitates over fit and leaves. Algomo checks the exact size and colour in live stock, answers in the conversation, and can put the item in their bag at the page's own price.
Where is my order
The question that fills every retail inbox. Once your order system is connected, Algomo looks the order up and answers with where the order actually is.
The return
Algomo quotes the returns window you published and walks the shopper through what to do next. When the policy changes, you tell it once and every answer follows.
The promo question
Does the code still work, does the discount apply, when does the sale end. Algomo answers from what you actually published, so the shopper never hears a guess.
The handover
Some conversations need a person. Your team takes over with the whole conversation attached, and the shopper never repeats themselves.
[ 02 of 04 ] · why algomo
Three differences, one loop
It connects itself
Algomo discovers the endpoints your store's pages already call. That is why its answers come from live data instead of a help article.
It connects itselfSo its actions are real
Because it holds the store's own endpoints, adding to bag means the shopper's actual bag, in their session, at the price their checkout will charge.
So its actions are realAnd you run it by talking to it
New promotion, new policy, new limit: tell Algomo and the next conversation follows it. You never file a ticket to change your own agent.
Stop offering discount codes on sale items.
Done. The rule is live and the promotions answer now matches it.
Discovery gives it live data. Live data makes real actions safe. Plain-language control keeps the whole thing yours. Why Algomo →
And you run it by talking to it[ 03 of 04 ] · questions, answered
Questions, answered
Can an AI chatbot check live stock?
Yes. Algomo reads availability from the same source your product pages do, so it sees stock by size and colour as it is right now. If your site can show it, the agent can check it, and the answer reflects the shopper's own prices, availability and region where your store varies them.
Can an AI agent add items to the basket?
Yes, in the visitor's own session. Algomo uses the same cart endpoint your Add to bag button calls, so the item lands in the shopper's real basket at the price their checkout will charge, and checkout continues as normal. You decide, in plain language, whether it may do this on its own or only when asked.
How does the agent learn our catalogue and policies?
You give it your URL. It reads your site the way a shopper would, finds the APIs behind your product pages, and sets itself up from them. Delivery and returns answers come from the policies you have published, so there is nothing to re-enter and nothing to keep in sync by hand.
Does it work with Shopify?
Yes. It discovers what a Shopify storefront already exposes: the catalogue, stock and the real cart. WooCommerce and commercetools work the same way, and so do custom storefronts, because discovery starts from your pages rather than a plugin list.
Can it answer where-is-my-order questions?
Where we have set up your order system with you, a where-is-my-order runs a real lookup: the shopper hears where the order actually is and your team never sees the ticket. Before that connection is made, it gathers the order details and hands the question to your team with everything attached.
Can it process refunds?
Issuing the refund stays with a person. Algomo gathers the details, explains your published policy, and hands the case to your team with the conversation attached, so the shopper never explains twice.
Can it recommend products?
It narrows a vague request down to what is genuinely in stock: that size, that colour, right now. Because it answers from your own catalogue rather than a guess, what it suggests is always something the shopper can actually buy.
Can I change what it says or does after launch?
Yes, by telling it. A new promotion, a changed returns window, a rule about discount codes: say it in plain language and the next conversation follows it. Ask it what changed this week and it will tell you, with the call behind any answer you want to check.
What happens when we redesign the site?
A watchdog watches every connection. When a redesign moves an endpoint the agent depends on, it notices, rescans and rebuilds the part that broke. You hear about it after the fix, not from a customer.
Do you train models on our shoppers' conversations?
No. Conversations belong to you. We act on your instructions, for your purposes, and your customers' conversations are never used to train models.
What happens when it cannot help?
It hands over to your team with the conversation so far and the work it already did attached, so nothing lands cold and the shopper does not repeat themselves.
How long does setup take?
Minutes, because Algomo finds the endpoints your store's pages already call and builds its own tools to use them. You can try it against your live data before a visitor ever does. Systems behind a login are connected with us.
Can it handle Black Friday traffic?
Yes. It answers every conversation at once, and chat is unlimited, so the spike itself never raises the bill.
What does it cost?
You pay per useful conversation, not per seat, and chat is unlimited, so growing traffic alone never raises the bill. The model is on the pricing page.
[ 04 of 04 ] · explore more from algomo
Explore more from Algomo
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