Apparel and fashion retail

Fit, care and reorder agents that remember the customer

An agent that remembers what size someone actually took last time, answers fabric and washing questions from your own care guides rather than the open internet, and follows up when a favourite is back in stock — across your site, Telegram and WhatsApp.

24/7
fit and care questions answered
1
size conversation per customer, not per season
0
restock follow-ups depending on someone's memory
With agent4

Remembers fit, not just orders

Which size they actually kept, what they returned and why, the cut they avoid. Held per customer and carried across sessions, so the second conversation does not start from the first question.

Care answers from your own guides

Fabric composition, washing symbols, storage, repair. The agent answers from your care documentation and size charts, with your wording — not from whatever the open internet says about silk.

Photograph the label

A customer sends a picture of a care label or a garment and the agent reads it into the conversation, so "can I machine wash this" gets an answer without them typing out symbols.

Restock and reorder follow-ups

Scheduled follow-ups reach the customer when their size is back or the season turns — over Telegram, WhatsApp or email, without waiting for them to come back to the site.

Knows which product they are looking at

Opened from a product page, the agent already has that garment's context, so the conversation starts at the question rather than at "which item do you mean?"

Measurements stay private

Each customer's conversations and files are isolated per space and encrypted with their own key. Sizes and body measurements are exactly the kind of data a shopper expects a brand to hold carefully.

Before agent4
"What size am I in your brand?" is the same conversation with the same customer every season
Care and washing questions arrive after the sale, when nobody is staffed to answer them
Fit returns are expensive and mostly preventable — the customer guessed
Preferences live in whoever served them last, and that person has left
Restock and new-arrival interest is remembered by nobody

Where it fits

Most apparel questions are not about the product. They are about this customer and the product: whether the medium that worked in linen will work in wool, whether the thing they liked in March exists in their size again, whether the garment they already own can go in a machine.

Those questions share a property that makes them expensive to answer well — the answer depends on what happened before. A shop assistant who has served someone twice answers instantly. A website cannot, and a general assistant cannot either, because it meets every customer for the first time.

How it is put together

Fit lives in the customer's profile, not in the order table. What they kept, what they returned and why, the cut they avoid. It is held per customer and carried across conversations, so the second season does not begin with the first question.

Care and sizing answers come from your documents. Composition, washing symbols, storage and repair guidance, uploaded as a knowledge base. The agent answers from your care guides and size charts in your wording — which matters most for the fabrics where general advice is wrong.

Follow-ups do the remembering. A restock, a seasonal return, a care reminder after a first wash — scheduled work that reaches the customer over the channel they already use.

Each customer is isolated. Conversations and files are scoped per customer and encrypted with their own key. Sizes and measurements are ordinary retail data and also personal in a way a shopper notices if you get it wrong.

What connects, rather than ships

Inventory, orders and returns live in your systems. The agent reaches them over MCP as tools you expose — stock for a size, order status, a return started — so it answers from live data instead of guessing, and your systems stay the record.

The platform runs the conversation and the memory. It is not a shop.

It answers from your size charts and your fit notes rather than general sizing, and what a customer kept or returned feeds the next conversation. The part worth planning for is writing down the fit guidance your team currently gives verbally.

Industry solutionsThe platform is industry-agnostic: agents, knowledge and playbooks are all per-tenant configuration. The pieces below carry over whatever you do — only the documents and the boundary change.Get startedTalk to us