AI agents for ecommerce that sell, take the order and follow up on their own.

Shoppers no longer start by browsing your product page. They start with a post, an ad, or a story, and they send you a private message before they even open your website. "Do you have this in Black?","Is this real leather?" The store answers none of that but a person does, hours later.

So you install a chatbot. It follows a certain script, it cannot see stock or the prices changed last week and the first time someone asks about a variant it either invents an answer or apologises and asks them to email support system. Both outcomes end the sale before it even begins.

Meanwhile the actual product data lives in Shopify or WooCommerce, one system away from the conversation where the purchase decision is being made.

You already paid to create the demand. The ad ran, the creative campaign was successful, and the shopper showed interest. What happens in the next few minutes determine whether this investment turns into an order or into a competitor’s order.

And the cost is not linear. A manual DM operation works efficiently at thirty conversations a day but it gradually breaks down at three hundred which is precisely the day your best campaign lands.

Nothing changes about your products or your pricing. What changes is that the conversation itself becomes an operator that knows your catalog.

Unifunl connects to your store WooCommerce, Shopify, PrestaShop, Magento, Odoo, Salla, Converty, or a custom store through the Unifunl Commerce API and syncs products, prices, variants and stock automatically. Once a product is indexed, the agent can recommend it. If it is not indexed, it does not exist for the agent, which is what stops invented stock.

The same agent runs on every channel where your shoppers already are: WhatsApp , Instagram DM, Facebook Messenger, TikTok DM and your website widget, all in one inbox with the context carried across them.

You brief it the way you would brief a new employee, store details, active promotions, delivery and return policies, persona, tone, languages, explicit rules about “what to always do” and “what to avoid at all costs, and the cases that must escalate to a human. Set it up manually, or just describe the changes to Copilot and confirm .

These are Unifunl customers whose DMs are handled by an AI agent trained on their own catalog. Each story explains what changed operationally, not just the headline number.

A helpdesk AI is measured on how many conversations it closes without a human. That is a support metric. It is perfectly rational for it to end a conversation, and perfectly useless for a conversation with intent to buy.

A chatbot is the opposite problem, the moment a shopper asks something outside the script, a person has to step in.

Unifunl is built for the intent to buy. It doesn't hand off when a shopper goes off-script or escalate to a human the moment things get complex. Instead, it reasons over live catalog data, creates the order and reports the revenue it produced.

Order analytics reports revenue, average order value, completion and cancellation rate, change over time and a product ranking, exportable as a PDF.

Follow-ups report Sent, Replied, Converted and attributed revenue , so re-engagement is a line item rather than a feeling.

The Stats page reports conversations, generated orders, average credits per conversation and average credits per order, which turns "is the agent worth it?" into cost per completed order instead of cost per seat.